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  <front>
    <journal-meta>
      <journal-id journal-id-type="publisher-id">87</journal-id>
      <journal-id journal-id-type="index">urn:lsid:arphahub.com:pub:A116C711-4C18-5A38-8F1E-5E97753A8A64</journal-id>
      <journal-title-group>
        <journal-title xml:lang="en">Folia Medica</journal-title>
        <abbrev-journal-title xml:lang="en">FM</abbrev-journal-title>
      </journal-title-group>
      <issn pub-type="ppub">0204-8043</issn>
      <issn pub-type="epub">1314-2143</issn>
      <publisher>
        <publisher-name>Plovdiv Medical University</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.3897/folmed.68.e184913</article-id>
      <article-id pub-id-type="publisher-id">184913</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Research Article</subject>
        </subj-group>
        <subj-group subj-group-type="scientific_subject">
          <subject>Oncology</subject>
          <subject>Pediatrics &amp; Genetic diseases</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Assessment of NGAL, eGFR, and tubular injury markers for early detection of chemotherapy-induced nephrotoxicity in pediatric oncology patients</article-title>
      </title-group>
      <contrib-group content-type="authors">
        <contrib contrib-type="author" corresp="no">
          <name name-style="western">
            <surname>Markova</surname>
            <given-names>Petya</given-names>
          </name>
          <uri content-type="orcid">https://orcid.org/0009-0009-3978-044X</uri>
          <xref ref-type="aff" rid="A1">1</xref>
          <xref ref-type="aff" rid="A2">2</xref>
        </contrib>
        <contrib contrib-type="author" corresp="no">
          <name name-style="western">
            <surname>Yaneva</surname>
            <given-names>Antoniya</given-names>
          </name>
          <xref ref-type="aff" rid="A3">3</xref>
        </contrib>
        <contrib contrib-type="author" corresp="no">
          <name name-style="western">
            <surname>Spasova</surname>
            <given-names>Mariya</given-names>
          </name>
          <uri content-type="orcid">https://orcid.org/0000-0001-9092-8133</uri>
          <xref ref-type="aff" rid="A1">1</xref>
          <xref ref-type="aff" rid="A2">2</xref>
        </contrib>
        <contrib contrib-type="author" corresp="yes">
          <name name-style="western">
            <surname>Markov</surname>
            <given-names>Stoyan</given-names>
          </name>
          <email xlink:type="simple">stoyan.markov@mu-plovdiv.bg</email>
          <xref ref-type="aff" rid="A4">4</xref>
          <xref ref-type="aff" rid="A5">5</xref>
        </contrib>
        <contrib contrib-type="author" corresp="no">
          <name name-style="western">
            <surname>Kostadinov</surname>
            <given-names>Kostadin</given-names>
          </name>
          <xref ref-type="aff" rid="A6">6</xref>
        </contrib>
      </contrib-group>
      <aff id="A1">
        <label>1</label>
        <addr-line content-type="verbatim">Department of Pediatrics, Faculty of Medicine, Medical University of Plovdiv, Plovdiv, Bulgaria</addr-line>
        <institution>Department of Pediatrics, St. George University Hospital</institution>
        <addr-line content-type="city">Plovdiv</addr-line>
        <country>Bulgaria</country>
      </aff>
      <aff id="A2">
        <label>2</label>
        <addr-line content-type="verbatim">Department of Pediatrics, St. George University Hospital, Plovdiv, Bulgaria</addr-line>
        <institution>Depatrment of Pediatrics, Medical University of Plovdiv</institution>
        <addr-line content-type="city">Plovdiv</addr-line>
        <country>Bulgaria</country>
      </aff>
      <aff id="A3">
        <label>3</label>
        <addr-line content-type="verbatim">Department of Medical Informatics, Biostatistics and eLearning, Faculty of Public Health, Medical University of Plovdiv, Plovdiv, Bulgaria</addr-line>
        <institution>Medical Informatics, Biostatistics and eLearning, Faculty of Public Health, Medical University of Plovdiv</institution>
        <addr-line content-type="city">Plovdiv</addr-line>
        <country>Bulgaria</country>
      </aff>
      <aff id="A4">
        <label>4</label>
        <addr-line content-type="verbatim">Department of Otorhinolaryngology, Faculty of Medicine, Medical University of Plovdiv, Plovdiv, Bulgaria</addr-line>
        <institution>Department of Otorhinolaryngology, Faculty of Medicine, Medical University of Plovdiv</institution>
        <addr-line content-type="city">Plovdiv</addr-line>
        <country>Bulgaria</country>
      </aff>
      <aff id="A5">
        <label>5</label>
        <addr-line content-type="verbatim">Department of Otorhinolaryngology, St. George University Hospital, Plovdiv, Bulgaria</addr-line>
        <institution>Department of Otorhinolaryngology, St. George University Hospital</institution>
        <addr-line content-type="city">Plovdiv</addr-line>
        <country>Bulgaria</country>
      </aff>
      <aff id="A6">
        <label>6</label>
        <addr-line content-type="verbatim">Department of Social Medicine and Public Health, Faculty of Public Health, Medical University of Plovdiv, Plovdiv, Bulgaria</addr-line>
        <institution>Department of Social Medicine and Public Health, Faculty of Public Health, Medical University of Plovdiv</institution>
        <addr-line content-type="city">Plovdiv</addr-line>
        <country>Bulgaria</country>
      </aff>
      <author-notes>
        <fn fn-type="corresp">
          <p><bold>Corresponding author</bold>: Stoyan Markov, Department of Otorhinolaryngology, Faculty of Medicine, Medical University of Plovdiv, 15A Vassil Aprilov Blvd., 4002 Plovdiv, Bulgaria; Email: <email xlink:type="simple">stoyan.markov@mu-plovdiv.bg</email>; Tel: 08989331347</p>
        </fn>
      </author-notes>
      <pub-date pub-type="collection">
        <year>2026</year>
      </pub-date>
      <pub-date pub-type="epub">
        <day>31</day>
        <month>08</month>
        <year>2026</year>
      </pub-date>
      <volume>68</volume>
      <issue>4</issue>
      <elocation-id>e184913</elocation-id>
      <uri content-type="arpha" xlink:href="http://openbiodiv.net/57C1941F-77F1-599D-B00A-14A381327ACE">57C1941F-77F1-599D-B00A-14A381327ACE</uri>
      <history>
        <date date-type="received">
          <day>11</day>
          <month>01</month>
          <year>2026</year>
        </date>
        <date date-type="accepted">
          <day>02</day>
          <month>03</month>
          <year>2026</year>
        </date>
      </history>
      <permissions>
        <copyright-statement>Petya Markova, Antoniya Yaneva, Mariya Spasova, Stoyan Markov, Kostadin Kostadinov</copyright-statement>
        <license license-type="creative-commons-attribution" xlink:href="http://creativecommons.org/licenses/by/4.0/" xlink:type="simple">
          <license-p>This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.</license-p>
        </license>
      </permissions>
      <abstract>
        <label>Abstract</label>
        <p><bold>Introduction</bold>: Acute kidney injury is a common complication in children with oncological diseases. Its etiology is multifactorial, with key risk factors including drug-induced nephrotoxicity, tumor lysis syndrome, and infection—including sepsis during periods of aplasia. The classical diagnostic criteria for <abbrev xlink:title="Acute kidney injury">AKI</abbrev> rely on monitoring serum creatinine levels and detecting oliguria. In the context of drug-induced nephrotoxicity, the predominant pathophysiological mechanism is tubular injury, which is typically non-oliguric and may not cause changes in serum creatinine, even in cases of severe damage.</p>
        <p><bold>Materials and methods</bold>: We studied 40 children undergoing 116 chemotherapy cycles with nephrotoxic agents at the Pediatric Hematology-Oncology Department, St. George University Hospital. Urinary NGAL, estimated GFR (<abbrev xlink:title="estimated GFR">eGFR</abbrev>) using the Schwartz, Schwartz-adjusted, and Brandt formulas, and tubular markers—fractional excretion of phosphate (<abbrev xlink:title="fractional excretion of phosphate">FeP</abbrev>) and tubular maximum reabsorption of phosphate per GFR (<abbrev xlink:title="tubular maximum reabsorption of phosphate per GFR">Tmp/GFR</abbrev>)—were measured before and 12 hours after each cycle.</p>
        <p><bold>Results</bold>: Urinary NGAL increased significantly after later chemotherapy cycles but remained within reference ranges and failed to detect two KDIGO-defined <abbrev xlink:title="Acute kidney injury">AKI</abbrev> episodes. The classical Schwartz formula identified only two <abbrev xlink:title="Acute kidney injury">AKI</abbrev> cases, while adjusted formulas revealed decreased <abbrev xlink:title="estimated GFR">eGFR</abbrev> in 36% of patients and a reduction in hyperfiltration prevalence from 50% to 28%. Tubular markers (<abbrev xlink:title="fractional excretion of phosphate">FeP</abbrev>, <abbrev xlink:title="tubular maximum reabsorption of phosphate per GFR">Tmp/GFR</abbrev>) showed consistent and significant changes across all cycles.</p>
        <p><bold>Conclusion</bold>: NGAL is not a reliable early biomarker for chemotherapy-related <abbrev xlink:title="Acute kidney injury">AKI</abbrev> in children. Adjusted <abbrev xlink:title="estimated GFR">eGFR</abbrev> formulas and tubular injury markers provide greater sensitivity and should be incorporated into monitoring protocols to enable earlier detection and reduce the risk of chronic kidney damage.</p>
      </abstract>
      <kwd-group>
        <label>Keywords</label>
        <kwd>acute kidney injury</kwd>
        <kwd>nephrotoxicity</kwd>
        <kwd>NGAL</kwd>
        <kwd>tubular injury markers</kwd>
      </kwd-group>
    </article-meta>
    <notes>
      <sec sec-type="Citation" id="sec1">
        <title>Citation</title>
        <p>Markova P, Yaneva A, Spasova M, Markov S, Kostadinov K. Assessment of NGAL, eGFR, and tubular injury markers for early detection of chemotherapy-induced nephrotoxicity in pediatric oncology patients. Folia Med (Plovdiv) 2026;68(4):e184913. <ext-link ext-link-type="doi" xlink:href="10.3897/folmed.68.e184913">doi: 10.3897/folmed.68.e184913</ext-link>.</p>
      </sec>
    </notes>
  </front>
  <body>
    <sec sec-type="Introduction" id="sec2">
      <title>Introduction</title>
      <p>Acute kidney injury (<abbrev xlink:title="Acute kidney injury">AKI</abbrev>) is a common issue in children with oncological diseases. The reported incident in literature ranges from 16.9% to 52%.<sup>[<xref ref-type="bibr" rid="B1">1</xref>,<xref ref-type="bibr" rid="B2">2</xref>]</sup> Its etiology is multifactorial, with key risk factors including drug-induced nephrotoxicity, tumor lysis syndrome, and infection, including sepsis emerging during periods of aplasia.<sup>[<xref ref-type="bibr" rid="B3">3</xref>]</sup> The occurrence of <abbrev xlink:title="Acute kidney injury">AKI</abbrev> during treatment often necessitates dose reduction of the implicated medication or its replacement with a less nephrotoxic alternative. This may have an adverse effect on the overall therapeutic outcome.</p>
      <p>The classical diagnosis of <abbrev xlink:title="Acute kidney injury">AKI</abbrev> relies on monitoring serum creatinine levels and the presence of oliguria. However, these are late markers, changing more than 48 hours after the onset of kidney injury. Furthermore, they are unable to differentiate between prerenal and renal injuries. Serum creatinine levels rise only after more than 50% of nephron function has been lost. This means that mild and moderate impairments in kidney function may go undetected.</p>
      <p>According to the KDIGO criteria, the diagnosis of acute kidney injury (<abbrev xlink:title="Acute kidney injury">AKI</abbrev>) is based on changes in serum creatinine levels and/or estimated glomerular filtration rate (<abbrev xlink:title="estimated GFR">eGFR</abbrev>), as well as the presence of oliguria. In pediatric practice, the Schwartz formula is the most widely applied method for estimating GFR, relying on serum creatinine concentration and patient height. Nevertheless, serum creatinine is strongly influenced by muscle mass, and in the context of cachexia, frequently observed in children with malignancies, its levels may remain deceptively low even in the presence of <abbrev xlink:title="Acute kidney injury">AKI</abbrev>. As a result, the use of the classical Schwartz formula, a simple and widely accessible method, tends to overestimate glomerular filtration. The literature provides only limited evidence regarding the optimal formula to apply in pediatric oncology patients; however, the available studies consistently emphasize formulas that incorporate body mass. These include the body surface area–adjusted Schwartz formula, as well as the Brandt and the Cockcroft–Gault formulas.</p>
      <p>In the context of drug-induced nephrotoxicity, the primary pathogenetic mechanism of <abbrev xlink:title="Acute kidney injury">AKI</abbrev> is tubular injury, which is typically non-oliguric, and even in cases of severe kidney damage, serum creatinine levels may remain unchanged. This highlights the need for new markers for the early diagnosis of <abbrev xlink:title="Acute kidney injury">AKI</abbrev> in pediatric oncology. One of them is NGAL, which has been extensively discussed in the literature as a biomarker of acute kidney injury (<abbrev xlink:title="Acute kidney injury">AKI</abbrev>), with proven sensitivity and specificity in various conditions such as <abbrev xlink:title="Acute kidney injury">AKI</abbrev> following perinatal asphyxia or after cardiac surgery with cardiopulmonary bypass, among others. Its role in pediatric oncology, and particularly as a marker of nephrotoxicity, remains incompletely elucidated. Other potential nephrotoxicity biomarkers include tubular markers of injury, such as the fractional excretion of phosphate (<abbrev xlink:title="fractional excretion of phosphate">FeP</abbrev>%), or the renal phosphate threshold.</p>
    </sec>
    <sec sec-type="Aim" id="sec3">
      <title>Aim</title>
      <p>To compare classical markers of <abbrev xlink:title="Acute kidney injury">AKI</abbrev> with tubular injury markers and NGAL as early markers of drug-induced nephrotoxicity in children undergoing chemotherapy.</p>
    </sec>
    <sec sec-type="materials|methods" id="sec4">
      <title>Materials and methods</title>
      <p>A cross-sectional study was conducted among 40 children undergoing chemotherapy with nephrotoxic medications at the Pediatric Hematology and Oncology Department of the Pediatrics Clinic at St. George University Hospital for the period 2021–2024.</p>
      <p><bold>Inclusion criteria</bold>: Children aged 0 to 18 years undergoing treatment with nephrotoxic medication (ifosfamide, cisplatin, or carboplatin), with no history of prior kidney injury or renal anomalies, and with signed informed consent.</p>
      <p><bold>Exclusion criteria</bold>: Presence of a comorbid condition—evidence of sepsis, or treatment with another nephrotoxic agent such as an antibiotic, antiviral, or antifungal medication, dehydration.</p>
      <p>For all children, blood and urine samples were collected before the start of each chemotherapy cycle, as well as 12 hours after its completion. The following parameters were analyzed:</p>
      <p>In blood, serum creatinine, urea, and electrolytes—including phosphorus and magnesium—were measured using an AU480 automated biochemical analyzer (Beckman Coulter) based on the turbidimetric principle. Estimated glomerular filtration rate (<abbrev xlink:title="estimated GFR">eGFR</abbrev>) was calculated using the original Schwartz formula, the body surface area–adjusted Schwartz formula (<bold>Equ. 1</bold>), and the Brandt equation (<bold>Equ. 2)</bold>.</p>
      <p><mml:math id="M1"><mml:msub><mml:mrow><mml:mi mathvariant="bold">G</mml:mi><mml:mi mathvariant="bold">F</mml:mi><mml:mi mathvariant="bold">R</mml:mi></mml:mrow><mml:mrow><mml:mrow><mml:mi>EST</mml:mi></mml:mrow></mml:mrow></mml:msub><mml:mrow><mml:mtext/><mml:mi>mL</mml:mi></mml:mrow><mml:mrow><mml:mo>/</mml:mo></mml:mrow><mml:mo>min</mml:mo><mml:mo>=</mml:mo><mml:mfrac><mml:mrow><mml:mrow><mml:mi mathvariant="normal">k</mml:mi></mml:mrow><mml:mo>⋅</mml:mo><mml:mrow><mml:mi>Ht</mml:mi></mml:mrow><mml:mo stretchy="false">(</mml:mo><mml:mrow><mml:mi mathvariant="bold">c</mml:mi><mml:mi mathvariant="bold">m</mml:mi></mml:mrow><mml:mo stretchy="false">)</mml:mo></mml:mrow><mml:msub><mml:mrow><mml:mi mathvariant="bold">S</mml:mi></mml:mrow><mml:mrow><mml:mrow><mml:mi>CR</mml:mi></mml:mrow></mml:mrow></mml:msub></mml:mfrac><mml:mo>×</mml:mo><mml:mfrac><mml:mrow><mml:mrow><mml:mi mathvariant="bold">B</mml:mi><mml:mi mathvariant="bold">S</mml:mi><mml:mi mathvariant="bold">A</mml:mi></mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:msup><mml:mrow><mml:mi mathvariant="bold">m</mml:mi></mml:mrow><mml:mn>2</mml:mn></mml:msup><mml:mo>)</mml:mo></mml:mrow></mml:mrow><mml:mrow><mml:mrow><mml:mn mathvariant="bold">1</mml:mn><mml:mo mathvariant="bold">.</mml:mo><mml:mn mathvariant="bold">73</mml:mn></mml:mrow><mml:msup><mml:mrow><mml:mi mathvariant="bold">m</mml:mi></mml:mrow><mml:mn>2</mml:mn></mml:msup></mml:mrow></mml:mfrac></mml:math> (Equ. 1)</p>
      <p>where k=0.45 for children ≤1 year, 0.70 for pubertal males, and 0.55 for all other children, Scr is serum creatinine level (mg/dL), BSA: body surface area, Ht : the child’s height in cm.</p>
      <p><mml:math id="M2"><mml:mrow><mml:mi mathvariant="bold">G</mml:mi><mml:mi mathvariant="bold">F</mml:mi><mml:mi mathvariant="bold">R</mml:mi></mml:mrow><mml:mrow><mml:mi>mL</mml:mi></mml:mrow><mml:mrow><mml:mo>/</mml:mo></mml:mrow><mml:mo>min</mml:mo><mml:mo>=</mml:mo><mml:mrow><mml:mi mathvariant="bold">k</mml:mi></mml:mrow><mml:msqrt><mml:mfrac><mml:mrow><mml:mo stretchy="false">(</mml:mo><mml:mtext> agemos </mml:mtext><mml:mo>+</mml:mo><mml:mn>6</mml:mn><mml:mo stretchy="false">)</mml:mo><mml:mo>×</mml:mo><mml:mrow><mml:mi>wt</mml:mi></mml:mrow></mml:mrow><mml:msub><mml:mrow><mml:mtext/><mml:mi mathvariant="normal">S</mml:mi></mml:mrow><mml:mrow><mml:mrow><mml:mi>CR</mml:mi></mml:mrow></mml:mrow></mml:msub></mml:mfrac></mml:msqrt></mml:math> (Equ. 2)</p>
      <p>where k is 1.05 for males and 0.95 for females; agemos is the child’s age in months; wt is the child’s weight in kilograms; Scr is serum creatinine levels (mg/dL).</p>
      <p>The KDIGO 2022 classification was used to stage acute kidney injury.<sup>[<xref ref-type="bibr" rid="B4">4</xref>]</sup> According to the KDIGO criteria, <abbrev xlink:title="Acute kidney injury">AKI</abbrev> is defined as an increase in serum creatinine levels or a decline in GFR of 25% for stage 1, 50% for stage 2, and 75% or an <abbrev xlink:title="estimated GFR">eGFR</abbrev> less than 35 mL/min/1.73 m<sup>2</sup> for stage 3 <bold>(Table <xref ref-type="table" rid="T1">1</xref>)</bold>.</p>
      <table-wrap id="T1" position="float" orientation="portrait">
        <label>Table 1.</label>
        <caption>
          <p>KDIGO classification of acute kidney injury (<abbrev xlink:title="Acute kidney injury">AKI</abbrev>)</p>
        </caption>
        <table>
          <tbody>
            <tr>
              <td rowspan="1" colspan="1">
                <bold>Stage</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold>Serum creatinine</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold>Urine output</bold>
              </td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">1</td>
              <td rowspan="1" colspan="1">1.5–1.9 times above baseline or &gt;26.5 µmol/L within 48 hours</td>
              <td rowspan="1" colspan="1">&lt;0.5 mL/kg/h for 6-12 hours</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">2</td>
              <td rowspan="1" colspan="1">1.0–2.9 times increase from baseline</td>
              <td rowspan="1" colspan="1">&lt;0.5 mL/kg/h for &gt;12 hours</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">3</td>
              <td rowspan="1" colspan="1">3.0 times above baseline, or serum creatinine &gt;353.6 µmol/L, or initiation of renal replacement therapy, or <abbrev xlink:title="estimated GFR">eGFR</abbrev> &lt;35 mL/min/1.73 m<sup>2</sup> (in patients &lt;18 years of age).</td>
              <td rowspan="1" colspan="1">&lt;0.3 mL/kg/h for &gt;24 hours or anuria for &gt;12 hours</td>
            </tr>
          </tbody>
        </table>
      </table-wrap>
      <p>In urine, neutrophil gelatinase-associated lipocalin (NGAL) was assessed for each chemotherapy cycle. Urine NGAL levels were measured 12 hours before and after treatment using a chemiluminescent microparticle immunoassay for quantitative determination of NGAL. NGAL was considered elevated if its value exceeded 150 ng/mL, the reference value provided by the manufacturer. The NGAL/creatinine ratio was calculated to account for the diluting effect of hyperhydration administered during each chemotherapy cycle. In addition, the fractional excretion of phosphate (<abbrev xlink:title="fractional excretion of phosphate">FeP</abbrev>%) was measured (<bold>Equ. 3)</bold>, and the renal phosphate threshold was calculated (<bold>Equ. 4</bold>).</p>
      <p><mml:math id="M3"><mml:mrow><mml:mi mathvariant="bold">F</mml:mi><mml:mi mathvariant="bold">e</mml:mi><mml:mi mathvariant="bold">P</mml:mi></mml:mrow><mml:mi mathvariant="normal">%</mml:mi><mml:mo>=</mml:mo><mml:mfrac><mml:mrow><mml:msub><mml:mrow><mml:mi>PO</mml:mi></mml:mrow><mml:mn>4</mml:mn></mml:msub><mml:mo stretchy="false">(</mml:mo><mml:mrow><mml:mi mathvariant="normal">U</mml:mi></mml:mrow><mml:mo stretchy="false">)</mml:mo><mml:mo>×</mml:mo><mml:mi>Cr</mml:mi><mml:mo stretchy="false">(</mml:mo><mml:mrow><mml:mi mathvariant="normal">S</mml:mi></mml:mrow><mml:mo stretchy="false">)</mml:mo></mml:mrow><mml:mrow><mml:msub><mml:mrow><mml:mi>PO</mml:mi></mml:mrow><mml:mn>4</mml:mn></mml:msub><mml:mo stretchy="false">(</mml:mo><mml:mrow><mml:mtext/><mml:mi mathvariant="normal">S</mml:mi></mml:mrow><mml:mo stretchy="false">)</mml:mo><mml:mo>×</mml:mo><mml:mi>Cr</mml:mi><mml:mo stretchy="false">(</mml:mo><mml:mrow><mml:mi mathvariant="normal">U</mml:mi></mml:mrow><mml:mo stretchy="false">)</mml:mo></mml:mrow></mml:mfrac><mml:mo>×</mml:mo><mml:mn>100</mml:mn></mml:math> (Equ. 3)</p>
      <p>where PO4: phosphate (mmol/L), Cr: creatinine (µmol/L), U: urine concentration, S: serum concentration.</p>
      <p><mml:math id="M4"><mml:mfrac><mml:mrow><mml:mi mathvariant="bold">T</mml:mi><mml:mi mathvariant="bold">m</mml:mi><mml:mi mathvariant="bold">p</mml:mi></mml:mrow><mml:mrow><mml:mi mathvariant="bold">G</mml:mi><mml:mi mathvariant="bold">F</mml:mi><mml:mi mathvariant="bold">R</mml:mi></mml:mrow></mml:mfrac><mml:mo>=</mml:mo><mml:mrow><mml:mi>Pp</mml:mi></mml:mrow><mml:mo>−</mml:mo><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mi>Up</mml:mi></mml:mrow><mml:mo>×</mml:mo><mml:mfrac><mml:mrow><mml:mi>Pcr</mml:mi></mml:mrow><mml:mrow><mml:mi>Ucr</mml:mi></mml:mrow></mml:mfrac><mml:mo>)</mml:mo></mml:mrow></mml:math> (Equ. 4)</p>
      <p>where P is the phosphate level, Pp is plasma phosphate concentration, Up is Urine phosphate concentration, Pcr is plasma creatinine concentration, and Ucr is the urine creatinine.</p>
      <p>Under conditions of normal serum phosphate levels, the fractional excretion of phosphate (<abbrev xlink:title="fractional excretion of phosphate">FeP</abbrev>) is normally up to 20%. In the presence of hypophosphatemia with proximal tubular dysfunction, <abbrev xlink:title="fractional excretion of phosphate">FeP</abbrev> increases above 20%, whereas in intact tubular function it is expected to decrease, even approaching 0%.</p>
      <sec sec-type="Statistical analysis" id="sec5">
        <title>Statistical analysis</title>
        <p>The following statistical methods were used for data analysis:</p>
        <p>- Descriptive and inferential statistics</p>
        <p>Data for qualitative, non-metric variables are presented using absolute frequencies and relative proportions (count, %). Quantitative variables are described using key parameters of central tendency (mean ± standard error of the mean, <abbrev xlink:title="mean ± standard error of the mean">SEM</abbrev>), statistical dispersion (standard deviation, <abbrev xlink:title="standard deviation">SD</abbrev>), and the 95% confidence interval (95% CI). Quantitative indicators that do not follow a normal distribution are described using the median and interquartile range (<abbrev xlink:title="interquartile range">IQR</abbrev>).</p>
        <p>- To assess the normality of the distribution of the analyzed variables, the Kolmogorov–Smirnov test was used.</p>
        <p>- When testing hypotheses for insignificant influence of factors, the χ² (chi-square) test for contingency tables and Fisher’s exact test for 2×2 tables were applied.</p>
        <p>- For the analysis of quantitative variables in independent groups that do not follow a normal distribution, the Mann–Whitney U test was applied.</p>
        <p>- To compare two or more relative proportions, the z-test was used. When comparing proportions across more than two groups, <italic>p</italic>-value correction was applied using the Bonferroni method.</p>
        <p>- For comparison of more than two independent groups with variables that do not follow a normal distribution, the Kruskal–Wallis test was used.</p>
        <p>- A significance level of <italic>p</italic>&lt;0.05 was adopted for the null hypothesis.</p>
        <p>The statistical analysis of the results was performed using the statistical software SPSS version 23.</p>
      </sec>
    </sec>
    <sec sec-type="Results" id="sec6">
      <title>Results</title>
      <sec sec-type="Patients" id="sec7">
        <title>Patients</title>
        <p>The analysis included 40 children who were followed up, with 18 being girls (45.0%) and 22 being boys (55.0%). The mean age of the participants was 10.59±5.26 years, with no statistically significant difference observed between the two sexes (<italic>p</italic>=0.376) <bold>(Table <xref ref-type="table" rid="T2">2</xref>)</bold>.</p>
        <table-wrap id="T2" position="float" orientation="portrait">
          <label>Table 2.</label>
          <caption>
            <p>Distribution of children by sex</p>
          </caption>
          <table>
            <tbody>
              <tr>
                <td rowspan="1" colspan="1">
                  <bold>Sex</bold>
                </td>
                <td rowspan="1" colspan="1">
                  <bold>N</bold>
                </td>
                <td rowspan="1" colspan="1">
                  <bold>Min</bold>
                </td>
                <td rowspan="1" colspan="1">
                  <bold>Max</bold>
                </td>
                <td rowspan="1" colspan="1">
                  <bold>Average</bold>
                </td>
                <td rowspan="1" colspan="1">
                  <bold>Median</bold>
                </td>
                <td rowspan="1" colspan="1">
                  <bold>U</bold>
                </td>
                <td rowspan="1" colspan="1">
                  <bold>z</bold>
                </td>
                <td rowspan="1" colspan="1">
                  <bold>
                    <italic>p</italic>
                  </bold>
                </td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">Girl</td>
                <td rowspan="1" colspan="1">18</td>
                <td rowspan="1" colspan="1">2.00</td>
                <td rowspan="1" colspan="1">21.00</td>
                <td rowspan="1" colspan="1">10.0122</td>
                <td rowspan="1" colspan="1">10.45 (6.35–12.25)</td>
                <td rowspan="1" colspan="1">165.5</td>
                <td rowspan="1" colspan="1">−0.885</td>
                <td rowspan="1" colspan="1">
                  <bold>0.376</bold>
                </td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">Boy</td>
                <td rowspan="1" colspan="1">22</td>
                <td rowspan="1" colspan="1">2.00</td>
                <td rowspan="1" colspan="1">18.00</td>
                <td rowspan="1" colspan="1">11.0595</td>
                <td rowspan="1" colspan="1">13.45 (5.78–15.13)</td>
                <td rowspan="1" colspan="1"/>
                <td rowspan="1" colspan="1"/>
                <td rowspan="1" colspan="1"/>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <fn>
              <p>* The data are presented as median (25th and 75th percentiles).</p>
            </fn>
          </table-wrap-foot>
        </table-wrap>
        <p>The distribution of children by malignant disease is shown in <bold>Table <xref ref-type="table" rid="T3">3</xref></bold>.</p>
        <table-wrap id="T3" position="float" orientation="portrait">
          <label>Table 3.</label>
          <caption>
            <p>Distribution of children by tumor type</p>
          </caption>
          <table>
            <tbody>
              <tr>
                <td rowspan="1" colspan="1">
                  <bold>Diagnosis</bold>
                </td>
                <td rowspan="1" colspan="1">
                  <bold>Number of patients</bold>
                </td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">Acute lymphoblastic leukemia (ALL)</td>
                <td rowspan="1" colspan="1">3</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">Teratoma</td>
                <td rowspan="1" colspan="1">2</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">Ewing sarcoma</td>
                <td rowspan="1" colspan="1">8</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">Brainstem glioma</td>
                <td rowspan="1" colspan="1">2</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">Medulloblastoma</td>
                <td rowspan="1" colspan="1">4</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">Osteosarcoma</td>
                <td rowspan="1" colspan="1">7</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">Astrocytoma</td>
                <td rowspan="1" colspan="1">1</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">Neuroblastoma</td>
                <td rowspan="1" colspan="1">3</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">Nephroblastoma</td>
                <td rowspan="1" colspan="1">3</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">Non-Hodgkin lymphoma</td>
                <td rowspan="1" colspan="1">5</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">Soft tissue sarcoma</td>
                <td rowspan="1" colspan="1">1</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">Hodgkin’s disease (Hodgkin lymphoma)</td>
                <td rowspan="1" colspan="1">1</td>
              </tr>
            </tbody>
          </table>
        </table-wrap>
        <p><bold>Table <xref ref-type="table" rid="T4">4</xref></bold> presents all parameters before and 12 hours after each chemotherapy cycle, by cycle number.</p>
        <table-wrap id="T4" position="float" orientation="portrait">
          <label>Table 4.</label>
          <caption>
            <p>Investigated parameters distributed by chemotherapy cycles</p>
          </caption>
          <table>
            <tbody>
              <tr>
                <td rowspan="2" colspan="1">
                  <bold>Parameter</bold>
                </td>
                <td rowspan="2" colspan="1">
                  <bold>Chemotherapy cycle sequence</bold>
                </td>
                <td rowspan="2" colspan="1">
                  <bold>N</bold>
                </td>
                <td rowspan="1" colspan="3">
                  <bold>Before chemotherapy</bold>
                </td>
                <td rowspan="1" colspan="3">
                  <bold>12 hours after chemotherapy</bold>
                </td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">
                  <bold>Mean</bold>
                </td>
                <td rowspan="1" colspan="1">
                  <bold>
                    <abbrev xlink:title="standard deviation">SD</abbrev>
                  </bold>
                </td>
                <td rowspan="1" colspan="1">
                  <bold>
                    <abbrev xlink:title="mean ± standard error of the mean">SEM</abbrev>
                  </bold>
                </td>
                <td rowspan="1" colspan="1">
                  <bold>Mean</bold>
                </td>
                <td rowspan="1" colspan="1">
                  <bold>
                    <abbrev xlink:title="standard deviation">SD</abbrev>
                  </bold>
                </td>
                <td rowspan="1" colspan="1">
                  <bold>
                    <abbrev xlink:title="mean ± standard error of the mean">SEM</abbrev>
                  </bold>
                </td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">Serum creatinine, (µmol/l)</td>
                <td rowspan="1" colspan="1">First cycle</td>
                <td rowspan="1" colspan="1">27</td>
                <td rowspan="1" colspan="1">46.222</td>
                <td rowspan="1" colspan="1">11.666</td>
                <td rowspan="1" colspan="1">2.245</td>
                <td rowspan="1" colspan="1">47.074</td>
                <td rowspan="1" colspan="1">11.812</td>
                <td rowspan="1" colspan="1">2.273</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1"/>
                <td rowspan="1" colspan="1">Second cycle</td>
                <td rowspan="1" colspan="1">24</td>
                <td rowspan="1" colspan="1">49.292</td>
                <td rowspan="1" colspan="1">11.719</td>
                <td rowspan="1" colspan="1">2.392</td>
                <td rowspan="1" colspan="1">48.913</td>
                <td rowspan="1" colspan="1">14.497</td>
                <td rowspan="1" colspan="1">3.023</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1"/>
                <td rowspan="1" colspan="1">Third cycle</td>
                <td rowspan="1" colspan="1">17</td>
                <td rowspan="1" colspan="1">46.529</td>
                <td rowspan="1" colspan="1">11.801</td>
                <td rowspan="1" colspan="1">2.862</td>
                <td rowspan="1" colspan="1">46.471</td>
                <td rowspan="1" colspan="1">10.199</td>
                <td rowspan="1" colspan="1">2.474</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1"/>
                <td rowspan="1" colspan="1">Cycles from 4 to 10</td>
                <td rowspan="1" colspan="1">48</td>
                <td rowspan="1" colspan="1">54.396</td>
                <td rowspan="1" colspan="1">14.623</td>
                <td rowspan="1" colspan="1">2.111</td>
                <td rowspan="1" colspan="1">54.042</td>
                <td rowspan="1" colspan="1">16.089</td>
                <td rowspan="1" colspan="1">2.322</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1"><abbrev xlink:title="estimated GFR">eGFR</abbrev>, ml/min/1.73 m<sup>2</sup></td>
                <td rowspan="1" colspan="1">First cycle</td>
                <td rowspan="1" colspan="1">27</td>
                <td rowspan="1" colspan="1">155.947</td>
                <td rowspan="1" colspan="1">30.861</td>
                <td rowspan="1" colspan="1">5.939</td>
                <td rowspan="1" colspan="1">159.581</td>
                <td rowspan="1" colspan="1">42.528</td>
                <td rowspan="1" colspan="1">8.185</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1"/>
                <td rowspan="1" colspan="1">Second cycle</td>
                <td rowspan="1" colspan="1">24</td>
                <td rowspan="1" colspan="1">147.115</td>
                <td rowspan="1" colspan="1">29.595</td>
                <td rowspan="1" colspan="1">6.171</td>
                <td rowspan="1" colspan="1">156.737</td>
                <td rowspan="1" colspan="1">40.228</td>
                <td rowspan="1" colspan="1">8.388</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1"/>
                <td rowspan="1" colspan="1">Third cycle</td>
                <td rowspan="1" colspan="1">17</td>
                <td rowspan="1" colspan="1">163.258</td>
                <td rowspan="1" colspan="1">35.344</td>
                <td rowspan="1" colspan="1">8.572</td>
                <td rowspan="1" colspan="1">161.481</td>
                <td rowspan="1" colspan="1">36.839</td>
                <td rowspan="1" colspan="1">8.935</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1"/>
                <td rowspan="1" colspan="1">Cycles from 4 to 10</td>
                <td rowspan="1" colspan="1">48</td>
                <td rowspan="1" colspan="1">155.478</td>
                <td rowspan="1" colspan="1">39.007</td>
                <td rowspan="1" colspan="1">5.751</td>
                <td rowspan="1" colspan="1">157.137</td>
                <td rowspan="1" colspan="1">44.254</td>
                <td rowspan="1" colspan="1">6.525</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">Mg, mmol/L</td>
                <td rowspan="1" colspan="1">First cycle</td>
                <td rowspan="1" colspan="1">27</td>
                <td rowspan="1" colspan="1">0.846</td>
                <td rowspan="1" colspan="1">0.218</td>
                <td rowspan="1" colspan="1">0.044</td>
                <td rowspan="1" colspan="1">1.059</td>
                <td rowspan="1" colspan="1">0.421</td>
                <td rowspan="1" colspan="1">0.081</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1"/>
                <td rowspan="1" colspan="1">Second cycle</td>
                <td rowspan="1" colspan="1">24</td>
                <td rowspan="1" colspan="1">0.827</td>
                <td rowspan="1" colspan="1">0.237</td>
                <td rowspan="1" colspan="1">0.048</td>
                <td rowspan="1" colspan="1">1.091</td>
                <td rowspan="1" colspan="1">0.350</td>
                <td rowspan="1" colspan="1">0.073</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1"/>
                <td rowspan="1" colspan="1">Third cycle</td>
                <td rowspan="1" colspan="1">17</td>
                <td rowspan="1" colspan="1">0.862</td>
                <td rowspan="1" colspan="1">0.058</td>
                <td rowspan="1" colspan="1">0.014</td>
                <td rowspan="1" colspan="1">1.209</td>
                <td rowspan="1" colspan="1">0.431</td>
                <td rowspan="1" colspan="1">0.104</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1"/>
                <td rowspan="1" colspan="1">Cycles from 4 to 10</td>
                <td rowspan="1" colspan="1">48</td>
                <td rowspan="1" colspan="1">0.836</td>
                <td rowspan="1" colspan="1">0.100</td>
                <td rowspan="1" colspan="1">0.015</td>
                <td rowspan="1" colspan="1">1.050</td>
                <td rowspan="1" colspan="1">0.326</td>
                <td rowspan="1" colspan="1">0.047</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">Phosphorus, mmol/L</td>
                <td rowspan="1" colspan="1">First cycle</td>
                <td rowspan="1" colspan="1">27</td>
                <td rowspan="1" colspan="1">1.443</td>
                <td rowspan="1" colspan="1">0.232</td>
                <td rowspan="1" colspan="1">0.047</td>
                <td rowspan="1" colspan="1">1.324</td>
                <td rowspan="1" colspan="1">0.237</td>
                <td rowspan="1" colspan="1">0.046</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1"/>
                <td rowspan="1" colspan="1">Second cycle</td>
                <td rowspan="1" colspan="1">24</td>
                <td rowspan="1" colspan="1">1.383</td>
                <td rowspan="1" colspan="1">0.291</td>
                <td rowspan="1" colspan="1">0.061</td>
                <td rowspan="1" colspan="1">1.236</td>
                <td rowspan="1" colspan="1">0.229</td>
                <td rowspan="1" colspan="1">0.048</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1"/>
                <td rowspan="1" colspan="1">Third cycle</td>
                <td rowspan="1" colspan="1">17</td>
                <td rowspan="1" colspan="1">1.504</td>
                <td rowspan="1" colspan="1">0.201</td>
                <td rowspan="1" colspan="1">0.050</td>
                <td rowspan="1" colspan="1">1.300</td>
                <td rowspan="1" colspan="1">0.193</td>
                <td rowspan="1" colspan="1">0.047</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1"/>
                <td rowspan="1" colspan="1">Cycles from 4 to 10</td>
                <td rowspan="1" colspan="1">48</td>
                <td rowspan="1" colspan="1">1.405</td>
                <td rowspan="1" colspan="1">0.467</td>
                <td rowspan="1" colspan="1">0.070</td>
                <td rowspan="1" colspan="1">1.132</td>
                <td rowspan="1" colspan="1">0.354</td>
                <td rowspan="1" colspan="1">0.051</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">NGAL (urine), ng/ml</td>
                <td rowspan="1" colspan="1">First cycle</td>
                <td rowspan="1" colspan="1">27</td>
                <td rowspan="1" colspan="1">13.012</td>
                <td rowspan="1" colspan="1">24.145</td>
                <td rowspan="1" colspan="1">4.735</td>
                <td rowspan="1" colspan="1">11.081</td>
                <td rowspan="1" colspan="1">27.816</td>
                <td rowspan="1" colspan="1">5.353</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1"/>
                <td rowspan="1" colspan="1">Second cycle</td>
                <td rowspan="1" colspan="1">24</td>
                <td rowspan="1" colspan="1">14.821</td>
                <td rowspan="1" colspan="1">18.532</td>
                <td rowspan="1" colspan="1">3.783</td>
                <td rowspan="1" colspan="1">7.443</td>
                <td rowspan="1" colspan="1">8.482</td>
                <td rowspan="1" colspan="1">1.769</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1"/>
                <td rowspan="1" colspan="1">Third cycle</td>
                <td rowspan="1" colspan="1">17</td>
                <td rowspan="1" colspan="1">19.553</td>
                <td rowspan="1" colspan="1">23.372</td>
                <td rowspan="1" colspan="1">5.669</td>
                <td rowspan="1" colspan="1">7.552</td>
                <td rowspan="1" colspan="1">14.428</td>
                <td rowspan="1" colspan="1">3.499</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1"/>
                <td rowspan="1" colspan="1">Cycles from 4 to 10</td>
                <td rowspan="1" colspan="1">48</td>
                <td rowspan="1" colspan="1">92.117</td>
                <td rowspan="1" colspan="1">308.326</td>
                <td rowspan="1" colspan="1">45.460</td>
                <td rowspan="1" colspan="1">34.647</td>
                <td rowspan="1" colspan="1">92.396</td>
                <td rowspan="1" colspan="1">13.477</td>
              </tr>
              <tr>
                <td rowspan="2" colspan="1">
                  <bold>Parameter</bold>
                </td>
                <td rowspan="2" colspan="1">
                  <bold>Chemotherapy cycle sequence</bold>
                </td>
                <td rowspan="2" colspan="1">
                  <bold>N</bold>
                </td>
                <td rowspan="1" colspan="3">
                  <bold>Before chemotherapy</bold>
                </td>
                <td rowspan="1" colspan="3">
                  <bold>12 hours after chemotherapy</bold>
                </td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">
                  <bold>Mean</bold>
                </td>
                <td rowspan="1" colspan="1">
                  <bold>
                    <abbrev xlink:title="standard deviation">SD</abbrev>
                  </bold>
                </td>
                <td rowspan="1" colspan="1">
                  <bold>
                    <abbrev xlink:title="mean ± standard error of the mean">SEM</abbrev>
                  </bold>
                </td>
                <td rowspan="1" colspan="1">
                  <bold>Mean</bold>
                </td>
                <td rowspan="1" colspan="1">
                  <bold>
                    <abbrev xlink:title="standard deviation">SD</abbrev>
                  </bold>
                </td>
                <td rowspan="1" colspan="1">
                  <bold>
                    <abbrev xlink:title="mean ± standard error of the mean">SEM</abbrev>
                  </bold>
                </td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">NGAL/creatinine, (urine)</td>
                <td rowspan="1" colspan="1">First cycle</td>
                <td rowspan="1" colspan="1">27</td>
                <td rowspan="1" colspan="1">2.527</td>
                <td rowspan="1" colspan="1">2.936</td>
                <td rowspan="1" colspan="1">0.565</td>
                <td rowspan="1" colspan="1">3.821</td>
                <td rowspan="1" colspan="1">5.797</td>
                <td rowspan="1" colspan="1">1.116</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1"/>
                <td rowspan="1" colspan="1">Second cycle</td>
                <td rowspan="1" colspan="1">24</td>
                <td rowspan="1" colspan="1">4.106</td>
                <td rowspan="1" colspan="1">4.634</td>
                <td rowspan="1" colspan="1">0.946</td>
                <td rowspan="1" colspan="1">7.639</td>
                <td rowspan="1" colspan="1">12.480</td>
                <td rowspan="1" colspan="1">2.548</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1"/>
                <td rowspan="1" colspan="1">Third cycle</td>
                <td rowspan="1" colspan="1">17</td>
                <td rowspan="1" colspan="1">4.255</td>
                <td rowspan="1" colspan="1">6.906</td>
                <td rowspan="1" colspan="1">1.675</td>
                <td rowspan="1" colspan="1">5.023</td>
                <td rowspan="1" colspan="1">7.404</td>
                <td rowspan="1" colspan="1">1.796</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1"/>
                <td rowspan="1" colspan="1">Cycles from 4 to 10</td>
                <td rowspan="1" colspan="1">48</td>
                <td rowspan="1" colspan="1">11.800</td>
                <td rowspan="1" colspan="1">28.964</td>
                <td rowspan="1" colspan="1">4.181</td>
                <td rowspan="1" colspan="1">16.139</td>
                <td rowspan="1" colspan="1">34.532</td>
                <td rowspan="1" colspan="1">4.984</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1"><abbrev xlink:title="fractional excretion of phosphate">FeP</abbrev>%</td>
                <td rowspan="1" colspan="1">First cycle</td>
                <td rowspan="1" colspan="1">27</td>
                <td rowspan="1" colspan="1">12.627</td>
                <td rowspan="1" colspan="1">23.038</td>
                <td rowspan="1" colspan="1">4.518</td>
                <td rowspan="1" colspan="1">27.098</td>
                <td rowspan="1" colspan="1">63.489</td>
                <td rowspan="1" colspan="1">12.451</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1"/>
                <td rowspan="1" colspan="1">Second cycle</td>
                <td rowspan="1" colspan="1">24</td>
                <td rowspan="1" colspan="1">17.547</td>
                <td rowspan="1" colspan="1">35.750</td>
                <td rowspan="1" colspan="1">7.454</td>
                <td rowspan="1" colspan="1">22.692</td>
                <td rowspan="1" colspan="1">19.152</td>
                <td rowspan="1" colspan="1">3.994</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1"/>
                <td rowspan="1" colspan="1">Third cycle</td>
                <td rowspan="1" colspan="1">17</td>
                <td rowspan="1" colspan="1">7.390</td>
                <td rowspan="1" colspan="1">5.777</td>
                <td rowspan="1" colspan="1">1.444</td>
                <td rowspan="1" colspan="1">15.707</td>
                <td rowspan="1" colspan="1">7.714</td>
                <td rowspan="1" colspan="1">1.871</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1"/>
                <td rowspan="1" colspan="1">Cycles from 4 to 10</td>
                <td rowspan="1" colspan="1">48</td>
                <td rowspan="1" colspan="1">13.606</td>
                <td rowspan="1" colspan="1">23.239</td>
                <td rowspan="1" colspan="1">3.390</td>
                <td rowspan="1" colspan="1">25.837</td>
                <td rowspan="1" colspan="1">19.140</td>
                <td rowspan="1" colspan="1">2.763</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">
                  <abbrev xlink:title="tubular maximum reabsorption of phosphate per GFR">Tmp/GFR</abbrev>
                </td>
                <td rowspan="1" colspan="1">First cycle</td>
                <td rowspan="1" colspan="1">27</td>
                <td rowspan="1" colspan="1">1.242</td>
                <td rowspan="1" colspan="1">0.399</td>
                <td rowspan="1" colspan="1">0.081</td>
                <td rowspan="1" colspan="1">0.933</td>
                <td rowspan="1" colspan="1">0.875</td>
                <td rowspan="1" colspan="1">0.179</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1"/>
                <td rowspan="1" colspan="1">Second cycle</td>
                <td rowspan="1" colspan="1">24</td>
                <td rowspan="1" colspan="1">1.194</td>
                <td rowspan="1" colspan="1">0.431</td>
                <td rowspan="1" colspan="1">0.090</td>
                <td rowspan="1" colspan="1">0.945</td>
                <td rowspan="1" colspan="1">0.310</td>
                <td rowspan="1" colspan="1">0.065</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1"/>
                <td rowspan="1" colspan="1">Third cycle</td>
                <td rowspan="1" colspan="1">17</td>
                <td rowspan="1" colspan="1">1.405</td>
                <td rowspan="1" colspan="1">0.210</td>
                <td rowspan="1" colspan="1">0.054</td>
                <td rowspan="1" colspan="1">1.096</td>
                <td rowspan="1" colspan="1">0.228</td>
                <td rowspan="1" colspan="1">0.055</td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1"/>
                <td rowspan="1" colspan="1">Cycles from 4 to 10</td>
                <td rowspan="1" colspan="1">48</td>
                <td rowspan="1" colspan="1">1.238</td>
                <td rowspan="1" colspan="1">0.604</td>
                <td rowspan="1" colspan="1">0.090</td>
                <td rowspan="1" colspan="1">0.858</td>
                <td rowspan="1" colspan="1">0.389</td>
                <td rowspan="1" colspan="1">0.056</td>
              </tr>
            </tbody>
          </table>
        </table-wrap>
      </sec>
    </sec>
    <sec sec-type="NGAL" id="sec8">
      <title>NGAL</title>
      <p>The analysis included 116 cycles, which were divided into four categories based on their cycle sequence: “first,” “second,” “third,” and “from the fourth to the tenth cycle.” These categories include all of the analysis’s first, second, and third cycles, respectively, while the final category includes all of the fourth to tenth cycles.</p>
      <p>The largest percentage of children were included in the “4–10 cycles” group. This is because, during the study period, in addition to newly diagnosed patients, children with disease relapse and those admitted for a new course of chemotherapy involving nephrotoxic medications were also included. Regarding the use of chemotherapy agents with high (ifosfamide, cisplatin) and low (carboplatin) nephrotoxicity, the children were divided into two main groups: a high nephrotoxicity group and a low nephrotoxicity group <bold>(Fig. <xref ref-type="fig" rid="F1">1</xref>)</bold>.</p>
      <fig id="F1">
        <object-id content-type="arpha">5CD74F30-34DC-5F4C-B4CB-EC7E9AC4E328</object-id>
        <label>Figure 1.</label>
        <caption>
          <p>Distribution of children by medication type.</p>
        </caption>
        <graphic xlink:href="foliamedica-68-4-e184913-g001.jpg" id="oo_1761314.jpg">
          <uri content-type="original_file">https://binary.pensoft.net/fig/1761314</uri>
        </graphic>
      </fig>
      <p>A higher percentage of children were treated with highly nephrotoxic medications—92 out of 116 cycles, or 79.3% of all cycles, involved a high-toxicity drug. <bold>Fig. <xref ref-type="fig" rid="F2">2</xref></bold> presents a summary of the NGAL values at baseline (0 hour) and at 12 hours post-treatment, distributed by cycles.</p>
      <fig id="F2">
        <object-id content-type="arpha">0FB925E3-D15D-5936-94F5-7B4BCCF00590</object-id>
        <label>Figure 2.</label>
        <caption>
          <p>Distribution of NGAL levels by chemotherapy cycles.</p>
        </caption>
        <graphic xlink:href="foliamedica-68-4-e184913-g002.jpg" id="oo_1761315.jpg">
          <uri content-type="original_file">https://binary.pensoft.net/fig/1761315</uri>
        </graphic>
      </fig>
      <p>The figure demonstrates that NGAL levels remain within the reference range and that, even at 12 hours, lower values are observed compared with those measured before the initiation of chemotherapy.</p>
      <p>To determine whether there was a statistically significant difference between NGAL levels before each chemotherapy cycle and 12 hours after, the Wilcoxon signed ranks test was used <bold>(Table <xref ref-type="table" rid="T5">5</xref>)</bold>.</p>
      <table-wrap id="T5" position="float" orientation="portrait">
        <label>Table 5.</label>
        <caption>
          <p>NGAL levels before and after each consecutive chemotherapy cycle</p>
        </caption>
        <table>
          <tbody>
            <tr>
              <td rowspan="3" colspan="1"><bold>NGAL ng/ml</bold>.</td>
              <td rowspan="3" colspan="1">
                <bold>N</bold>
              </td>
              <td rowspan="1" colspan="2">
                <bold>Median</bold>
              </td>
              <td rowspan="3" colspan="1">
                <bold>z</bold>
              </td>
              <td rowspan="3" colspan="1">
                <bold>
                  <italic>p</italic>
                </bold>
              </td>
            </tr>
            <tr>
              <td rowspan="1" colspan="2">
                <bold>(25th - 75th percentile)</bold>
              </td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">
                <bold>Before chemotherapy cycle</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold>12 hours after chemotherapy cycle</bold>
              </td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">First cycle</td>
              <td rowspan="1" colspan="1">
                <bold>26</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold>5.8 (1.175–14.575)</bold>
              </td>
              <td rowspan="1" colspan="1">2.7 (0.3–8.1)</td>
              <td rowspan="1" colspan="1">−1.472</td>
              <td rowspan="1" colspan="1">0.141</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Second cycle</td>
              <td rowspan="1" colspan="1">24</td>
              <td rowspan="1" colspan="1">6.15 (3.225–23.4)</td>
              <td rowspan="1" colspan="1">4.2 (1.3- 12.8)</td>
              <td rowspan="1" colspan="1">−3.011</td>
              <td rowspan="1" colspan="1">
                <bold>0.003</bold>
              </td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Third cycle</td>
              <td rowspan="1" colspan="1">17</td>
              <td rowspan="1" colspan="1">9.2 (1.55–33.6)</td>
              <td rowspan="1" colspan="1">2 (0.35–7.195)</td>
              <td rowspan="1" colspan="1">−2.344</td>
              <td rowspan="1" colspan="1">
                <bold>0.019</bold>
              </td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Cycles from 4 to 10</td>
              <td rowspan="1" colspan="1">46</td>
              <td rowspan="1" colspan="1">10.25(3.575–29.375)</td>
              <td rowspan="1" colspan="1">6.5(2.3-12.6)</td>
              <td rowspan="1" colspan="1">−2.856</td>
              <td rowspan="1" colspan="1">
                <bold>0.004</bold>
              </td>
            </tr>
          </tbody>
        </table>
      </table-wrap>
      <p>A statistically significant difference in NGAL levels before and 12 hours after the chemotherapy cycle was observed in patients who completed their second cycle (Z=−3.11, <italic>p</italic>=0.003) and third cycle (Z=−2.344, <italic>p</italic>=0.019), as well as in patients who underwent four or more chemotherapy cycles (Z=−0.856, <italic>p</italic>=0.004). However, NGAL levels remained within their reference values. Using KDIGO criteria, two episodes of <abbrev xlink:title="Acute kidney injury">AKI</abbrev> were diagnosed following treatment with a nephrotoxic agent. In both episodes, NGAL levels remained unchanged.</p>
      <p>To avoid the dilution effect resulting from hyperhydration, which is part of the chemotherapy protocol for these children, NGAL levels were compared to creatinine levels in a urine sample collected 12 hours after the chemotherapy cycle. The results are presented in <bold>Table <xref ref-type="table" rid="T6">6</xref></bold>.</p>
      <table-wrap id="T6" position="float" orientation="portrait">
        <label>Table 6.</label>
        <caption>
          <p>Urine NGAL/creatinine levels distributed by cycles</p>
        </caption>
        <table>
          <tbody>
            <tr>
              <td rowspan="2" colspan="1">
                <bold>NGAL/creatinine</bold>
              </td>
              <td rowspan="2" colspan="1">
                <bold>N</bold>
              </td>
              <td rowspan="1" colspan="2">
                <bold>Median (<abbrev xlink:title="interquartile range">IQR</abbrev>)®</bold>
              </td>
              <td rowspan="2" colspan="1">
                <bold>z</bold>
              </td>
              <td rowspan="2" colspan="1">
                <bold>
                  <italic>p</italic>
                </bold>
              </td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">
                <bold>Before chemotherapy cycle</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold>12 hours after chemotherapy cycle</bold>
              </td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">First cycle</td>
              <td rowspan="1" colspan="1">
                <bold>27</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold>1.5 (0.54–3.09)</bold>
              </td>
              <td rowspan="1" colspan="1">1.66 (0–4.9)</td>
              <td rowspan="1" colspan="1">−0.000</td>
              <td rowspan="1" colspan="1">0.317</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Second cycle</td>
              <td rowspan="1" colspan="1">24</td>
              <td rowspan="1" colspan="1">2.145 (1.105–5.842)</td>
              <td rowspan="1" colspan="1">2.9 (0.855–9.562)</td>
              <td rowspan="1" colspan="1">−0.600</td>
              <td rowspan="1" colspan="1">0.549</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Third cycle</td>
              <td rowspan="1" colspan="1">17</td>
              <td rowspan="1" colspan="1">1.39 (0.15–5.39)</td>
              <td rowspan="1" colspan="1">1.21 (0.53–5.95)</td>
              <td rowspan="1" colspan="1">−0.355</td>
              <td rowspan="1" colspan="1">0.723</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Cycles from 4 to 10</td>
              <td rowspan="1" colspan="1">48</td>
              <td rowspan="1" colspan="1">1.735 (0.89–5.3)</td>
              <td rowspan="1" colspan="1">3.22 (1.517–9.684)</td>
              <td rowspan="1" colspan="1">−2.066</td>
              <td rowspan="1" colspan="1">
                <bold>0.039</bold>
              </td>
            </tr>
          </tbody>
        </table>
        <table-wrap-foot>
          <fn>
            <p>*Median (<abbrev xlink:title="interquartile range">IQR</abbrev>) - median and interquartile range (25th-75th percentile)</p>
          </fn>
        </table-wrap-foot>
      </table-wrap>
      <p>A statistically significant marker increase was found only in the “4–10 cycles” group, that is, in patients who underwent multiple courses of nephrotoxic chemotherapy.</p>
    </sec>
    <sec sec-type="eGFR" id="sec9">
      <title>eGFR</title>
      <p>One of the main KDIGO criteria for diagnosing acute kidney injury is the patient’s GFR. Using the original Schwartz formula, GFR values were calculated before and after each chemotherapy cycle. Normal values were considered between 90 and 160 mL/min/1.73 m<sup>2</sup>, hyperfiltration was defined as values above 160 mL/min/1.73 m<sup>2 [<xref ref-type="bibr" rid="B5">5</xref>]</sup>, and reduced GFR as values below 90 mL/min/1.73 m<sup>2</sup><bold>(Fig. <xref ref-type="fig" rid="F3">3</xref>)</bold>.</p>
      <fig id="F3">
        <object-id content-type="arpha">2A0AC5E5-710A-5BD1-98C0-AEC9C1573B61</object-id>
        <label>Figure 3.</label>
        <caption>
          <p>Presentation of <abbrev xlink:title="estimated GFR">eGFR</abbrev> values at 0 and 12 hours.</p>
        </caption>
        <graphic xlink:href="foliamedica-68-4-e184913-g003.jpg" id="oo_1761316.jpg">
          <uri content-type="original_file">https://binary.pensoft.net/fig/1761316</uri>
        </graphic>
      </fig>
      <p>What stands out is the high percentage of hyperfiltration—almost 50% of all chemotherapy cycles—as well as the diagnosis of only one child with <abbrev xlink:title="Acute kidney injury">AKI</abbrev> before and two children after chemotherapy.</p>
      <p>To determine whether there was a statistically significant difference in <abbrev xlink:title="estimated GFR">eGFR</abbrev> before and 12 hours after chemotherapy for each cycle, the Wilcoxon signed ranks test was used <bold>(Table <xref ref-type="table" rid="T7">7</xref>)</bold>.</p>
      <table-wrap id="T7" position="float" orientation="portrait">
        <label>Table 7.</label>
        <caption>
          <p><abbrev xlink:title="estimated GFR">eGFR</abbrev> values before and after each chemotherapy cycle</p>
        </caption>
        <table>
          <tbody>
            <tr>
              <td rowspan="2" colspan="1">
                <bold><abbrev xlink:title="estimated GFR">eGFR</abbrev> mL/min/1.73 m<sup>2</sup></bold>
              </td>
              <td rowspan="2" colspan="1">
                <bold>N</bold>
              </td>
              <td rowspan="1" colspan="2">
                <bold>Median (<abbrev xlink:title="interquartile range">IQR</abbrev>)®</bold>
              </td>
              <td rowspan="2" colspan="1">
                <bold>z</bold>
              </td>
              <td rowspan="2" colspan="1">
                <bold>
                  <italic>p</italic>
                </bold>
              </td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">
                <bold>Before chemotherapy cycle</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold>12 hours after chemotherapy cycle</bold>
              </td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">First cycle</td>
              <td rowspan="1" colspan="1">
                <bold>27</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold>157 (133.38–176.57)</bold>
              </td>
              <td rowspan="1" colspan="1">164 (128.94–198)</td>
              <td rowspan="1" colspan="1">−0.148</td>
              <td rowspan="1" colspan="1">0.88</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Second cycle</td>
              <td rowspan="1" colspan="1">23</td>
              <td rowspan="1" colspan="1">149.69 (120–169)</td>
              <td rowspan="1" colspan="1">149.57 (128.62–182)</td>
              <td rowspan="1" colspan="1">−0.654</td>
              <td rowspan="1" colspan="1">0.51</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Third cycle</td>
              <td rowspan="1" colspan="1">17</td>
              <td rowspan="1" colspan="1">168.30 (141.165–185.215)</td>
              <td rowspan="1" colspan="1">165.58 (131.1–189)</td>
              <td rowspan="1" colspan="1">−0.157</td>
              <td rowspan="1" colspan="1">0.88</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Cycles from 4 to 10</td>
              <td rowspan="1" colspan="1">46</td>
              <td rowspan="1" colspan="1">161.63 (116.68–182.94)</td>
              <td rowspan="1" colspan="1">162.96 (112.705–191.252)</td>
              <td rowspan="1" colspan="1">−0.119</td>
              <td rowspan="1" colspan="1">0.91</td>
            </tr>
          </tbody>
        </table>
        <table-wrap-foot>
          <fn>
            <p>*Median (<abbrev xlink:title="interquartile range">IQR</abbrev>) - median and interquartile range (25th-75th percentile)</p>
          </fn>
        </table-wrap-foot>
      </table-wrap>
      <p>The data show no statistically significant difference in <abbrev xlink:title="estimated GFR">eGFR</abbrev> before and after the chemotherapy cycle.</p>
      <p>Given the fact that creatinine levels depend on muscle mass, in pediatric oncology their values are often pseudonormal, even in the presence of kidney injury. The standard Schwartz formula relies primarily on serum creatinine levels and the child’s height, which can lead to an overestimation of <abbrev xlink:title="estimated GFR">eGFR</abbrev>. The literature discusses the use of alternative formulas adapted for pediatric oncology patients<sup>[<xref ref-type="bibr" rid="B6">6</xref>]</sup>, two of which are the Schwartz formula corrected for the child’s body surface area, and the formula proposed by Brandt et al., which incorporates the child’s weight and age. The values obtained from these formulas have been compared with those derived using a steady-state methodology involving non-radioactive iothalamate (with a renal clearance similar to that of inulin), measured by high-performance liquid chromatography.<sup>[<xref ref-type="bibr" rid="B6">6</xref>]</sup><bold>Table <xref ref-type="table" rid="T8">8</xref></bold> presents the comparison of GFR values calculated using the classical Schwartz formula and the body surface area – the adjusted Schwartz formula.</p>
      <table-wrap id="T8" position="float" orientation="portrait">
        <label>Table 8.</label>
        <caption>
          <p>Comparison of GFR values calculated using the classical Schwartz formula and the body surface area−adjusted Schwartz formula</p>
        </caption>
        <table>
          <tbody>
            <tr>
              <td rowspan="2" colspan="1">
                <bold>
                  <abbrev xlink:title="estimated GFR">eGFR</abbrev>
                </bold>
              </td>
              <td rowspan="1" colspan="2">
                <bold>0 hour</bold>
              </td>
              <td rowspan="1" colspan="2">
                <bold>At 12 hours</bold>
              </td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">
                <bold>Schwartz</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold>Schwartz - corrected</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold>Schwartz</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold>Schwartz - corrected</bold>
              </td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Normal  GFR (90–160 mL/min/m<sup>2</sup>)</td>
              <td rowspan="1" colspan="1">61</td>
              <td rowspan="1" colspan="1">40</td>
              <td rowspan="1" colspan="1">55</td>
              <td rowspan="1" colspan="1">38</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Hyperfiltration  GFR (&gt;160 mL/min/m<sup>2</sup>)</td>
              <td rowspan="1" colspan="1">53</td>
              <td rowspan="1" colspan="1">30</td>
              <td rowspan="1" colspan="1">58</td>
              <td rowspan="1" colspan="1">31</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Low  GFR (&lt;90 mL/min/m<sup>2</sup>)</td>
              <td rowspan="1" colspan="1">1</td>
              <td rowspan="1" colspan="1">40</td>
              <td rowspan="1" colspan="1">2</td>
              <td rowspan="1" colspan="1">41</td>
            </tr>
          </tbody>
        </table>
      </table-wrap>
      <p>As demonstrated in <bold>Table <xref ref-type="table" rid="T8">8</xref></bold>, the data indicates a substantial increase in the number of chemotherapy cycles with reduced <abbrev xlink:title="estimated GFR">eGFR</abbrev>: from 2 at 12 hours using the standard Schwartz formula to 41 cycles when using the corrected formula. Furthermore, there is a decline in the percentage of cycles with hyperfiltration – to 31, which corresponds to 28% of all cycles, a percentage comparable to the results obtained using the radioisotope method for determining <abbrev xlink:title="estimated GFR">eGFR</abbrev>.</p>
      <p>Using the adjusted Schwartz formula and the Brandt formula, a statistically significant number of children (<italic>p</italic>&lt;0.001) were found to have reduced GFR before and after chemotherapy cycles. The number of affected children was nearly the same for both formulas, while the cycles with hyperfiltration were significantly fewer compared to the original formula. <bold>Table <xref ref-type="table" rid="T9">9</xref></bold> presents a comparative overview of the differences in <abbrev xlink:title="estimated GFR">eGFR</abbrev> calculation using the three formulas.</p>
      <table-wrap id="T9" position="float" orientation="portrait">
        <label>Table 9.</label>
        <caption>
          <p>Presentation of the differences in <abbrev xlink:title="estimated GFR">eGFR</abbrev> calculation using the three formulas</p>
        </caption>
        <table>
          <tbody>
            <tr>
              <td rowspan="1" colspan="8">%</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">
                <bold>
                  <abbrev xlink:title="estimated GFR">eGFR</abbrev>
                </bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold>Test 1 vs</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold>Test 2</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold>Difference</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold>z-score</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold>95% CI</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold>95% CI</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold><italic>p</italic> value (corrected)</bold>
              </td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Normal</td>
              <td rowspan="1" colspan="1">Schwartz</td>
              <td rowspan="1" colspan="1">Brandt</td>
              <td rowspan="1" colspan="1">−6.00%</td>
              <td rowspan="1" colspan="1">−1.06</td>
              <td rowspan="1" colspan="1">−0.17</td>
              <td rowspan="1" colspan="1">0.05</td>
              <td rowspan="1" colspan="1">0.58</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Normal</td>
              <td rowspan="1" colspan="1">Schwartz</td>
              <td rowspan="1" colspan="1">Schwartz-corrected</td>
              <td rowspan="1" colspan="1">10.00%</td>
              <td rowspan="1" colspan="1">2</td>
              <td rowspan="1" colspan="1">0</td>
              <td rowspan="1" colspan="1">0.2</td>
              <td rowspan="1" colspan="1">0.14</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Normal</td>
              <td rowspan="1" colspan="1">Brandt</td>
              <td rowspan="1" colspan="1">Schwartz-corrected</td>
              <td rowspan="1" colspan="1">16.00%</td>
              <td rowspan="1" colspan="1">3.08</td>
              <td rowspan="1" colspan="1">0.06</td>
              <td rowspan="1" colspan="1">0.26</td>
              <td rowspan="1" colspan="1">0.01</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Lowered</td>
              <td rowspan="1" colspan="1">Schwartz</td>
              <td rowspan="1" colspan="1">Brandt</td>
              <td rowspan="1" colspan="1">−46.00%</td>
              <td rowspan="1" colspan="1">−8.14</td>
              <td rowspan="1" colspan="1">−0.58</td>
              <td rowspan="1" colspan="1">−0.35</td>
              <td rowspan="1" colspan="1">&lt;0.001</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Lowered</td>
              <td rowspan="1" colspan="1">Schwartz</td>
              <td rowspan="1" colspan="1">Schwartz-corrected</td>
              <td rowspan="1" colspan="1">−46.00%</td>
              <td rowspan="1" colspan="1">−8.14</td>
              <td rowspan="1" colspan="1">−0.58</td>
              <td rowspan="1" colspan="1">−0.35</td>
              <td rowspan="1" colspan="1">&lt;0.001</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Lowered</td>
              <td rowspan="1" colspan="1">Brandt</td>
              <td rowspan="1" colspan="1">Schwartz-corrected</td>
              <td rowspan="1" colspan="1">0.00%</td>
              <td rowspan="1" colspan="1">0.00%</td>
              <td rowspan="1" colspan="1">−0.15</td>
              <td rowspan="1" colspan="1">0.15</td>
              <td rowspan="1" colspan="1">&gt;0.99</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Hyperfiltration</td>
              <td rowspan="1" colspan="1">Schwartz</td>
              <td rowspan="1" colspan="1">Brandt</td>
              <td rowspan="1" colspan="1">49.00%</td>
              <td rowspan="1" colspan="1">8.48</td>
              <td rowspan="1" colspan="1">0.38</td>
              <td rowspan="1" colspan="1">0.6</td>
              <td rowspan="1" colspan="1">&lt;0.001</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Hyperfiltration</td>
              <td rowspan="1" colspan="1">Schwartz</td>
              <td rowspan="1" colspan="1">Schwartz-corrected</td>
              <td rowspan="1" colspan="1">26.00%</td>
              <td rowspan="1" colspan="1">3.71</td>
              <td rowspan="1" colspan="1">0.12</td>
              <td rowspan="1" colspan="1">0.39</td>
              <td rowspan="1" colspan="1">&lt;0.001</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Hyperfiltration</td>
              <td rowspan="1" colspan="1">Brandt</td>
              <td rowspan="1" colspan="1">Schwartz-corrected</td>
              <td rowspan="1" colspan="1">−23.00%</td>
              <td rowspan="1" colspan="1">−4.22</td>
              <td rowspan="1" colspan="1">−0.34</td>
              <td rowspan="1" colspan="1">−0.13</td>
              <td rowspan="1" colspan="1">&lt;0.001</td>
            </tr>
          </tbody>
        </table>
      </table-wrap>
      <p>A comparison was made between the proposed formulas to determine which formula detects the most deviations (reduced <abbrev xlink:title="estimated GFR">eGFR</abbrev> as well as hyperfiltration), with the adjusted Schwartz formula standing out as the one identifying the most pathology <bold>(Table <xref ref-type="table" rid="T10">10</xref>)</bold>.</p>
      <table-wrap id="T10" position="float" orientation="portrait">
        <label>Table 10.</label>
        <caption>
          <p>Comparison of the three formulas for determining <abbrev xlink:title="estimated GFR">eGFR</abbrev></p>
        </caption>
        <table>
          <tbody>
            <tr>
              <td rowspan="2" colspan="1">
                <bold>Formula for  calculating GFR</bold>
              </td>
              <td rowspan="2" colspan="1">
                <bold>Normal n (%)</bold>
              </td>
              <td rowspan="2" colspan="1">
                <bold>Reduced GFR or hyperfiltration n (%)</bold>
              </td>
              <td rowspan="2" colspan="1">
                <bold>Difference in  relative proportions (Δ)</bold>
              </td>
              <td rowspan="2" colspan="1">
                <bold>z statistics</bold>
              </td>
              <td rowspan="1" colspan="2">
                <bold>95% CI 95% CI</bold>
              </td>
              <td rowspan="2" colspan="1">
                <bold><italic>p</italic>-value</bold>
              </td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">
                <bold>(L)</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold>(U)</bold>
              </td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Schwartz</td>
              <td rowspan="1" colspan="1">54 (47.79%)</td>
              <td rowspan="1" colspan="1">59 (52.21%)</td>
              <td rowspan="1" colspan="1">−4.42%</td>
              <td rowspan="1" colspan="1">−0.67</td>
              <td rowspan="1" colspan="1">−0.17</td>
              <td rowspan="1" colspan="1">0.09</td>
              <td rowspan="1" colspan="1">0.51</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Brandt</td>
              <td rowspan="1" colspan="1">63 (55.75%)</td>
              <td rowspan="1" colspan="1">50 (44.25%)</td>
              <td rowspan="1" colspan="1">11.50%</td>
              <td rowspan="1" colspan="1">1.74</td>
              <td rowspan="1" colspan="1">−0.01</td>
              <td rowspan="1" colspan="1">0.24</td>
              <td rowspan="1" colspan="1">0.16</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Schwartz (Corrected)</td>
              <td rowspan="1" colspan="1">38 (34.23%)</td>
              <td rowspan="1" colspan="1">73 (65.77%)</td>
              <td rowspan="1" colspan="1">−31.53%</td>
              <td rowspan="1" colspan="1">−4.95</td>
              <td rowspan="1" colspan="1">−0.44</td>
              <td rowspan="1" colspan="1">−0.19</td>
              <td rowspan="1" colspan="1">&lt;0.01</td>
            </tr>
          </tbody>
        </table>
      </table-wrap>
      <p>Since the corrected Schwartz formula identified the highest number of pathological cases, it was selected for use in subsequent analyses.</p>
      <p>In the course of the study, the elevated rate of hyperfiltration raised the question of whether this finding could be attributed to tubular creatinine loss in the context of tubular injury, which is recognized as the principal pathogenic mechanism of drug-induced nephrotoxicity.</p>
      <p>The main markers for tubular injury are the fractional excretion of phosphate and the more accurate indicator relative to the patient’s GFR — the renal phosphate threshold. To clarify the etiology of hyperfiltration, these two indicators — <abbrev xlink:title="estimated GFR">eGFR</abbrev> and fractional excretion of phosphate/renal phosphate threshold — were compared. Using the classical Schwartz formula for calculating <abbrev xlink:title="estimated GFR">eGFR</abbrev>, children with reduced <abbrev xlink:title="estimated GFR">eGFR</abbrev> were detected only in the “4–10 cycles” group. The comparison between <abbrev xlink:title="estimated GFR">eGFR</abbrev> and fractional phosphate excretion data is presented at <bold>Table <xref ref-type="table" rid="T11">11</xref></bold>.</p>
      <table-wrap id="T11" position="float" orientation="portrait">
        <label>Table 11.</label>
        <caption>
          <p>Comparison between <abbrev xlink:title="estimated GFR">eGFR</abbrev> and fractional phosphate excretion</p>
        </caption>
        <table>
          <tbody>
            <tr>
              <td rowspan="2" colspan="1">
                <bold>Filtration</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold>First cycle</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold>First cycle</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold>Second cycle</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold>Second cycle</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold>Third cycle</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold>Third cycle</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold>Cycles 4–10</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold>Cycles 4–10</bold>
              </td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">
                <bold><abbrev xlink:title="fractional excretion of phosphate">FeP</abbrev>&lt;20%</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold><abbrev xlink:title="fractional excretion of phosphate">FeP</abbrev>&gt;20%</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold><abbrev xlink:title="fractional excretion of phosphate">FeP</abbrev>&lt;20%</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold><abbrev xlink:title="fractional excretion of phosphate">FeP</abbrev>&gt;20%</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold><abbrev xlink:title="fractional excretion of phosphate">FeP</abbrev>&lt;20%</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold><abbrev xlink:title="fractional excretion of phosphate">FeP</abbrev>&gt;20%</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold><abbrev xlink:title="fractional excretion of phosphate">FeP</abbrev>&lt;20%</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold><abbrev xlink:title="fractional excretion of phosphate">FeP</abbrev>&gt;20%</bold>
              </td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Hyperfiltration</td>
              <td rowspan="1" colspan="1"/>
              <td rowspan="1" colspan="1"/>
              <td rowspan="1" colspan="1"/>
              <td rowspan="1" colspan="1"/>
              <td rowspan="1" colspan="1"/>
              <td rowspan="1" colspan="1"/>
              <td rowspan="1" colspan="1"/>
              <td rowspan="1" colspan="1"/>
            </tr>
            <tr>
              <td rowspan="1" colspan="1"><abbrev xlink:title="estimated GFR">eGFR</abbrev>&gt;160 mL/min/1.73 m<sup>2</sup></td>
              <td rowspan="1" colspan="1">92.9%</td>
              <td rowspan="1" colspan="1">7.1%</td>
              <td rowspan="1" colspan="1">80.0%</td>
              <td rowspan="1" colspan="1">20.0%</td>
              <td rowspan="1" colspan="1">88.9%</td>
              <td rowspan="1" colspan="1">11.1%</td>
              <td rowspan="1" colspan="1">58.3%</td>
              <td rowspan="1" colspan="1">41.7%</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Normal filtration</td>
              <td rowspan="1" colspan="1"/>
              <td rowspan="1" colspan="1"/>
              <td rowspan="1" colspan="1"/>
              <td rowspan="1" colspan="1"/>
              <td rowspan="1" colspan="1"/>
              <td rowspan="1" colspan="1"/>
              <td rowspan="1" colspan="1"/>
              <td rowspan="1" colspan="1"/>
            </tr>
            <tr>
              <td rowspan="1" colspan="1"><abbrev xlink:title="estimated GFR">eGFR</abbrev>=90–160 mL/min/1.73 m<sup>2</sup></td>
              <td rowspan="1" colspan="1">69.2%</td>
              <td rowspan="1" colspan="1">30.8%</td>
              <td rowspan="1" colspan="1">58.3%</td>
              <td rowspan="1" colspan="1">41.7%</td>
              <td rowspan="1" colspan="1">62.5%</td>
              <td rowspan="1" colspan="1">37.5%</td>
              <td rowspan="1" colspan="1">38.1%</td>
              <td rowspan="1" colspan="1">61.9%</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Low filtration</td>
              <td rowspan="1" colspan="1"/>
              <td rowspan="1" colspan="1"/>
              <td rowspan="1" colspan="1"/>
              <td rowspan="1" colspan="1"/>
              <td rowspan="1" colspan="1"/>
              <td rowspan="1" colspan="1"/>
              <td rowspan="1" colspan="1"/>
              <td rowspan="1" colspan="1"/>
            </tr>
            <tr>
              <td rowspan="1" colspan="1"><abbrev xlink:title="estimated GFR">eGFR</abbrev>&lt;90 mL/min/1.73 m<sup>2</sup></td>
              <td rowspan="1" colspan="1">–</td>
              <td rowspan="1" colspan="1">–</td>
              <td rowspan="1" colspan="1">–</td>
              <td rowspan="1" colspan="1">–</td>
              <td rowspan="1" colspan="1">–</td>
              <td rowspan="1" colspan="1">–</td>
              <td rowspan="1" colspan="1">0.0%</td>
              <td rowspan="1" colspan="1">100.0%</td>
            </tr>
          </tbody>
        </table>
      </table-wrap>
      <p>The comparison revealed no positive correlation between hyperfiltration and increased fractional excretion of phosphate, which is particularly evident during the first chemotherapy cycle. In all children with reduced <abbrev xlink:title="estimated GFR">eGFR</abbrev>, an elevated <abbrev xlink:title="fractional excretion of phosphate">FeP</abbrev>% was observed.</p>
      <p>A comparison was again made between the 12-hour <abbrev xlink:title="estimated GFR">eGFR</abbrev> calculated using the body surface area – corrected Schwartz formula and the fractional excretion of phosphate (<abbrev xlink:title="fractional excretion of phosphate">FeP</abbrev>%) <bold>(Fig. <xref ref-type="fig" rid="F4">4</xref>)</bold>.</p>
      <fig id="F4">
        <object-id content-type="arpha">B496D80A-08B4-5F59-933B-7F82A59F451C</object-id>
        <label>Figure 4.</label>
        <caption>
          <p>Comparison between <abbrev xlink:title="fractional excretion of phosphate">FeP</abbrev> and <abbrev xlink:title="estimated GFR">eGFR</abbrev> (Schwartz-corrected).</p>
        </caption>
        <graphic xlink:href="foliamedica-68-4-e184913-g004.jpg" id="oo_1761326.jpg">
          <uri content-type="original_file">https://binary.pensoft.net/fig/1761326</uri>
        </graphic>
      </fig>
      <p>Once again, no positive correlation was found between the cycles with hyperfiltration and elevated <abbrev xlink:title="fractional excretion of phosphate">FeP</abbrev>% (&gt;20%). Using the adjusted formula, it was found that elevated <abbrev xlink:title="fractional excretion of phosphate">FeP</abbrev>% was mainly observed in children from cycles with reduced <abbrev xlink:title="estimated GFR">eGFR</abbrev>. Only in the “4–10” cycle it was equally represented across all <abbrev xlink:title="estimated GFR">eGFR</abbrev> groups, unlike the classic Schwartz formula, where increased phosphate excretion was mainly seen in children with normal <abbrev xlink:title="estimated GFR">eGFR</abbrev>.</p>
      <sec sec-type="Fractional excretion of phosphate and renal phosphate threshold" id="sec10">
        <title>Fractional excretion of phosphate and renal phosphate threshold</title>
        <p>Nephrotoxic chemotherapeutic agents primarily cause tubular damage, which is why this study focused on two tubular markers: the fractional excretion of phosphate (<abbrev xlink:title="fractional excretion of phosphate">FeP</abbrev>%) and renal phosphate threshold, because phosphate reabsorption is disrupted earliest in tubular injury, making it the most clinically significant impairment. Both markers were measured before and at 12 hours after each chemotherapy course. <bold>Fig. <xref ref-type="fig" rid="F5">5</xref></bold> presents the summarized results for all cycles.</p>
        <fig id="F5">
          <object-id content-type="arpha">90B689C3-4282-54E2-894E-914C36862F3B</object-id>
          <label>Figure 5.</label>
          <caption>
            <p>Levels of <abbrev xlink:title="fractional excretion of phosphate">FeP</abbrev>% at 0 and at 12 hours.</p>
          </caption>
          <graphic xlink:href="foliamedica-68-4-e184913-g005.jpg" id="oo_1761317.jpg">
            <uri content-type="original_file">https://binary.pensoft.net/fig/1761317</uri>
          </graphic>
        </fig>
        <p>A statistically significant change was observed in the number of patients with <abbrev xlink:title="fractional excretion of phosphate">FeP</abbrev>% above 20%. Before the chemotherapy cycle, 10.3% of the subjects had <abbrev xlink:title="fractional excretion of phosphate">FeP</abbrev>% above 20%, while at 12 hours after the cycle, this increased to 35.3%. This indicates a statistically significant rise in the number of patients with fractional excretion of phosphate exceeding 20% at 12 hours post-chemotherapy <bold>(Table <xref ref-type="table" rid="T12">12</xref>)</bold>.</p>
        <table-wrap id="T12" position="float" orientation="portrait">
          <label>Table 12.</label>
          <caption>
            <p>Dynamics of <abbrev xlink:title="fractional excretion of phosphate">FeP</abbrev>% values for all 116 cycles</p>
          </caption>
          <table>
            <tbody>
              <tr>
                <td rowspan="1" colspan="1">
                  <bold>Marker</bold>
                </td>
                <td rowspan="1" colspan="1">
                  <bold>Before chemotherapy cycle</bold>
                </td>
                <td rowspan="1" colspan="1">
                  <bold>At 12 hours after the chemotherapy cycle</bold>
                </td>
                <td rowspan="1" colspan="1">
                  <bold>Change  (% and 95% CI)</bold>
                </td>
                <td rowspan="1" colspan="1">
                  <bold><italic>P</italic> value</bold>
                </td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1"><abbrev xlink:title="fractional excretion of phosphate">FeP</abbrev>%</td>
                <td rowspan="1" colspan="1">10.3%</td>
                <td rowspan="1" colspan="1">35.3%</td>
                <td rowspan="1" colspan="1">25.00% (15.78, 34.22)</td>
                <td rowspan="1" colspan="1">&lt;0.0001</td>
              </tr>
            </tbody>
          </table>
        </table-wrap>
        <p>Distributed by cycles, the results for fractional excretion of phosphate at 0 hour and at 12 hours are presented in <bold>Fig. <xref ref-type="fig" rid="F6">6</xref></bold>.</p>
        <fig id="F6">
          <object-id content-type="arpha">02AC03DF-A84C-57FE-8AE5-D2A68C3AB389</object-id>
          <label>Figure 6.</label>
          <caption>
            <p>Changes in fractional excretion of phosphates before and after chemotherapy across treatment cycles.</p>
          </caption>
          <graphic xlink:href="foliamedica-68-4-e184913-g006.jpg" id="oo_1761318.jpg">
            <uri content-type="original_file">https://binary.pensoft.net/fig/1761318</uri>
          </graphic>
        </fig>
        <p>Presented by cycles, it was found that <abbrev xlink:title="fractional excretion of phosphate">FeP</abbrev>% increases significantly during the “4–10” cycle at 12 hours after chemotherapy, indicating that tubular damage increases with the number of chemotherapy cycles administered.</p>
        <p>Using the Wilcoxon signed ranks test <bold>(Table <xref ref-type="table" rid="T13">13</xref>)</bold>, a statistically significant difference was found in urinary <abbrev xlink:title="fractional excretion of phosphate">FeP</abbrev>% levels before and after chemotherapy cycle, across all consecutive cycles.</p>
        <table-wrap id="T13" position="float" orientation="portrait">
          <label>Table 13.</label>
          <caption>
            <p>Urinary <abbrev xlink:title="fractional excretion of phosphate">FeP</abbrev>% values before and after consecutive chemotherapy cycle </p>
          </caption>
          <table>
            <tbody>
              <tr>
                <td rowspan="1" colspan="6">
                  <bold>Parameters</bold>
                </td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1"/>
                <td rowspan="1" colspan="1"/>
                <td rowspan="1" colspan="2">
                  <bold>Median (<abbrev xlink:title="interquartile range">IQR</abbrev>)*</bold>
                </td>
                <td rowspan="2" colspan="1">
                  <bold>z</bold>
                </td>
                <td rowspan="2" colspan="1">
                  <bold>
                    <italic>p</italic>
                  </bold>
                </td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">
                  <bold><abbrev xlink:title="fractional excretion of phosphate">FeP</abbrev>% in urine</bold>
                </td>
                <td rowspan="1" colspan="1">
                  <bold>N</bold>
                </td>
                <td rowspan="1" colspan="1">
                  <bold>Before chemotherapy cycle</bold>
                </td>
                <td rowspan="1" colspan="1">
                  <bold>12 hours after chemotherapy cycle</bold>
                </td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">First cycle</td>
                <td rowspan="1" colspan="1">26</td>
                <td rowspan="1" colspan="1">7.47 (3.597–13.192)</td>
                <td rowspan="1" colspan="1">11.36 (9.067–17.597)</td>
                <td rowspan="1" colspan="1">−2.381</td>
                <td rowspan="1" colspan="1">
                  <bold>0.017</bold>
                </td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">Second cycle</td>
                <td rowspan="1" colspan="1">23</td>
                <td rowspan="1" colspan="1">9.28 (3.75–16.31)</td>
                <td rowspan="1" colspan="1">16.38 (9.23–27.41)</td>
                <td rowspan="1" colspan="1">−2.281</td>
                <td rowspan="1" colspan="1">
                  <bold>0.023</bold>
                </td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">Third cycle</td>
                <td rowspan="1" colspan="1">16</td>
                <td rowspan="1" colspan="1">7.24 (2.107–12.087)</td>
                <td rowspan="1" colspan="1">17.88 (8.595–19.96)</td>
                <td rowspan="1" colspan="1">−2.896</td>
                <td rowspan="1" colspan="1">
                  <bold>0.004</bold>
                </td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">Cycles from 4 to 10</td>
                <td rowspan="1" colspan="1">47</td>
                <td rowspan="1" colspan="1">6.91 (4.69–11.44)</td>
                <td rowspan="1" colspan="1">19.72 (13.85–30.157)</td>
                <td rowspan="1" colspan="1">−2.856</td>
                <td rowspan="1" colspan="1">
                  <bold>&lt;0.001</bold>
                </td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <fn>
              <p>* Median (<abbrev xlink:title="interquartile range">IQR</abbrev>) - median and interquartile range (25th-75th percentile)</p>
            </fn>
          </table-wrap-foot>
        </table-wrap>
      </sec>
      <sec sec-type="Renal phosphate threshold" id="sec11">
        <title>Renal phosphate threshold</title>
        <p>The renal phosphate threshold (TmP/GFR) is a more accurate marker as it is adjusted for the glomerular filtration rate. A statistically significant change was observed in the renal phosphate threshold across all cycles. Before chemotherapy, 77.6% (90 cycles) had a normal renal phosphate threshold, while at 12 hours after therapy, this decreased to 58.6% (68 cycles). This represents a statistically significant reduction (<italic>p</italic>=0.0031) in the number of cycles with a normal renal phosphate threshold at 12 hours post-chemotherapy. <bold>Fig. <xref ref-type="fig" rid="F7">7</xref></bold> graphically presents the values of this parameter by cycles.</p>
        <fig id="F7">
          <object-id content-type="arpha">E9B2F083-C073-5AD5-8268-8F7E304EE763</object-id>
          <label>Figure 7.</label>
          <caption>
            <p>Renal phosphate threshold at 0 and 12 hours presented by cycles.</p>
          </caption>
          <graphic xlink:href="foliamedica-68-4-e184913-g007.jpg" id="oo_1761319.jpg">
            <uri content-type="original_file">https://binary.pensoft.net/fig/1761319</uri>
          </graphic>
        </fig>
        <p>A statistically significant difference in levels was again observed in each of the chemotherapy cycles performed <bold>(Table <xref ref-type="table" rid="T14">14</xref>)</bold>.</p>
        <table-wrap id="T14" position="float" orientation="portrait">
          <label>Table 14.</label>
          <caption>
            <p>Values of renal phosphate threshold (TmP/GFR) before and after consecutive chemotherapy cycles </p>
          </caption>
          <table>
            <tbody>
              <tr>
                <td rowspan="1" colspan="6">
                  <bold>Parameter</bold>
                </td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1"/>
                <td rowspan="1" colspan="1"/>
                <td rowspan="1" colspan="2">
                  <bold>Median (<abbrev xlink:title="interquartile range">IQR</abbrev>)*</bold>
                </td>
                <td rowspan="2" colspan="1">
                  <bold>z</bold>
                </td>
                <td rowspan="2" colspan="1">
                  <bold>
                    <italic>p</italic>
                  </bold>
                </td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">
                  <bold>
                    <abbrev xlink:title="tubular maximum reabsorption of phosphate per GFR">Tmp/GFR</abbrev>
                  </bold>
                </td>
                <td rowspan="1" colspan="1">
                  <bold>N</bold>
                </td>
                <td rowspan="1" colspan="1">
                  <bold>Before chemotherapy cycle</bold>
                </td>
                <td rowspan="1" colspan="1">
                  <bold>12 hours after chemotherapy cycle</bold>
                </td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">First cycle</td>
                <td rowspan="1" colspan="1">24</td>
                <td rowspan="1" colspan="1">1.335 (1.063–1.527)</td>
                <td rowspan="1" colspan="1">1.103 (0.922–1.34)</td>
                <td rowspan="1" colspan="1">−2.419</td>
                <td rowspan="1" colspan="1">
                  <bold>0.016</bold>
                </td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">Second cycle</td>
                <td rowspan="1" colspan="1">23</td>
                <td rowspan="1" colspan="1">1.259 (1.053–1.486)</td>
                <td rowspan="1" colspan="1">0.986 (0.616–1.202)</td>
                <td rowspan="1" colspan="1">−2.224</td>
                <td rowspan="1" colspan="1">
                  <bold>0.026</bold>
                </td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">Third cycle</td>
                <td rowspan="1" colspan="1">15</td>
                <td rowspan="1" colspan="1">1.384 (1.24–1.519)</td>
                <td rowspan="1" colspan="1">1.02 (0.975–1.236)</td>
                <td rowspan="1" colspan="1">−2.897</td>
                <td rowspan="1" colspan="1">
                  <bold>0.004</bold>
                </td>
              </tr>
              <tr>
                <td rowspan="1" colspan="1">Cycles from 4 to 10</td>
                <td rowspan="1" colspan="1">45</td>
                <td rowspan="1" colspan="1">1.301 (1.108–1.525)</td>
                <td rowspan="1" colspan="1">0.866 (0.649–1.108)</td>
                <td rowspan="1" colspan="1">−4.713</td>
                <td rowspan="1" colspan="1">
                  <bold>&lt;0.001</bold>
                </td>
              </tr>
            </tbody>
          </table>
          <table-wrap-foot>
            <fn>
              <p>* Median (<abbrev xlink:title="interquartile range">IQR</abbrev>) - median and interquartile range (25th-75th percentile)</p>
            </fn>
          </table-wrap-foot>
        </table-wrap>
        <p>To assess the clinical significance of tubular damage, serum phosphorus and magnesium levels were monitored. Hypophosphatemia was detected in 5 cycles before chemotherapy, representing children undergoing a subsequent cycle, which accounts for 4% of all cycles. At 12 hours after chemotherapy, hypophosphatemia was observed in 14 cycles, representing 12% of all cycles. To evaluate whether the changes in electrolytes, namely phosphorus and magnesium, across cycles were statistically significant, the Wilcoxon signed ranks test was again used. The results are presented in <bold>Tables 15</bold> and <bold>16</bold>.</p>
        <p>It was found that there was a statistically significant difference in serum phosphorus levels during the third and “4–10” cycles. Regarding magnesium, statistically significant changes were observed during the second, third, and “4–10” cycles. These data indicate that with the accumulation of nephrotoxicity, tubular injury progresses to clinically evident electrolyte disturbances, ultimately resulting in clinical manifestations.</p>
      </sec>
    </sec>
    <sec sec-type="Discussion" id="sec12">
      <title>Discussion</title>
      <p>One of the widely discussed in the literature early biomarkers for diagnosing subclinical <abbrev xlink:title="Acute kidney injury">AKI</abbrev>, as well as a predictive marker for the development of clinically manifested <abbrev xlink:title="Acute kidney injury">AKI</abbrev>, is NGAL. This marker has been shown to have high sensitivity and specificity for detecting acute kidney injury following an episode of hypoxia (e.g., newborns with perinatal asphyxia, children after cardiac surgery under cardiopulmonary bypass).<sup>[<xref ref-type="bibr" rid="B7">7</xref>-<xref ref-type="bibr" rid="B12">12</xref>]</sup> Regarding its role as a marker of drug-induced nephrotoxicity, and specifically following chemotherapy, there is very little and conflicting data.<sup>[<xref ref-type="bibr" rid="B13">13</xref>-<xref ref-type="bibr" rid="B17">17</xref>]</sup><bold>Table <xref ref-type="table" rid="T17">17</xref></bold> presents the most frequently cited studies on NGAL and its role as an early marker of <abbrev xlink:title="Acute kidney injury">AKI</abbrev> in pediatric oncology.<sup>[<xref ref-type="bibr" rid="B18">18</xref>,<xref ref-type="bibr" rid="B19">19</xref>]</sup></p>
      <table-wrap id="T15" position="float" orientation="portrait">
        <label>Table 15.</label>
        <caption>
          <p>Serum phosphorus levels before and after consecutive chemotherapy cycles </p>
        </caption>
        <table>
          <tbody>
            <tr>
              <td rowspan="1" colspan="6">
                <bold>Parameter</bold>
              </td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1"/>
              <td rowspan="1" colspan="1"/>
              <td rowspan="1" colspan="2">
                <bold>Median (<abbrev xlink:title="interquartile range">IQR</abbrev>)*</bold>
              </td>
              <td rowspan="2" colspan="1">
                <bold>z</bold>
              </td>
              <td rowspan="2" colspan="1">
                <bold>
                  <italic>p</italic>
                </bold>
              </td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">
                <bold>Phosphorus mmol/L</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold>N</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold>Before chemotherapy cycle</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold>12 hours after chemotherapy cycle</bold>
              </td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">First cycle</td>
              <td rowspan="1" colspan="1">24</td>
              <td rowspan="1" colspan="1">1.435 (1.332–1.617)</td>
              <td rowspan="1" colspan="1">1.34 (1.112–1.495)</td>
              <td rowspan="1" colspan="1">−1.544</td>
              <td rowspan="1" colspan="1">0.123</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Second cycle</td>
              <td rowspan="1" colspan="1">23</td>
              <td rowspan="1" colspan="1">1.43 (1.2–1.56)</td>
              <td rowspan="1" colspan="1">1.25 (1.09–1.43)</td>
              <td rowspan="1" colspan="1">−1.703</td>
              <td rowspan="1" colspan="1">0.089</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Third cycle</td>
              <td rowspan="1" colspan="1">16</td>
              <td rowspan="1" colspan="1">1.48 (1.392–1.655)</td>
              <td rowspan="1" colspan="1">1.24 (1.19–1.415)</td>
              <td rowspan="1" colspan="1">−2.793</td>
              <td rowspan="1" colspan="1">
                <bold>0.005</bold>
              </td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Cycles from 4 to 10</td>
              <td rowspan="1" colspan="1">45</td>
              <td rowspan="1" colspan="1">1.4 (1.25–1.585)</td>
              <td rowspan="1" colspan="1">1.17 (0.892–1.392)</td>
              <td rowspan="1" colspan="1">−1.088</td>
              <td rowspan="1" colspan="1">
                <bold>&lt;0.001</bold>
              </td>
            </tr>
          </tbody>
        </table>
        <table-wrap-foot>
          <fn>
            <p>* Median (<abbrev xlink:title="interquartile range">IQR</abbrev>) - median and interquartile range (25th-75th percentile)</p>
          </fn>
        </table-wrap-foot>
      </table-wrap>
      <table-wrap id="T16" position="float" orientation="portrait">
        <label>Table 16.</label>
        <caption>
          <p>Serum magnesium levels before and after consecutive chemotherapy cycles</p>
        </caption>
        <table>
          <tbody>
            <tr>
              <td rowspan="1" colspan="6">
                <bold>Parameter</bold>
              </td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1"/>
              <td rowspan="1" colspan="1"/>
              <td rowspan="1" colspan="2">
                <bold>Median (<abbrev xlink:title="interquartile range">IQR</abbrev>)*</bold>
              </td>
              <td rowspan="2" colspan="1">
                <bold>z</bold>
              </td>
              <td rowspan="2" colspan="1">
                <bold>
                  <italic>p</italic>
                </bold>
              </td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">
                <bold>Magnesium mmol/L</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold>N</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold>Before chemotherapy cycle</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold>12 hours after chemotherapy cycle</bold>
              </td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">First cycle</td>
              <td rowspan="1" colspan="1">25</td>
              <td rowspan="1" colspan="1">0.87 (0.815–0.92)</td>
              <td rowspan="1" colspan="1">0.87 (0.77–1.44)</td>
              <td rowspan="1" colspan="1">−1.543</td>
              <td rowspan="1" colspan="1">0.123</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Second cycle</td>
              <td rowspan="1" colspan="1">24</td>
              <td rowspan="1" colspan="1">0.82 (0.75–0.907)</td>
              <td rowspan="1" colspan="1">1.17 (0.79–1.38)</td>
              <td rowspan="1" colspan="1">−2.695</td>
              <td rowspan="1" colspan="1">
                <bold>0.007</bold>
              </td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Third cycle</td>
              <td rowspan="1" colspan="1">16</td>
              <td rowspan="1" colspan="1">0.865 (0.822–0.902)</td>
              <td rowspan="1" colspan="1">1.27 (0.815–1.57)</td>
              <td rowspan="1" colspan="1">−2.529</td>
              <td rowspan="1" colspan="1">
                <bold>0.011</bold>
              </td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">Cycles from 4 to 10</td>
              <td rowspan="1" colspan="1">45</td>
              <td rowspan="1" colspan="1">0.83 (0.76–0.9)</td>
              <td rowspan="1" colspan="1">0.885 (0.79–1.387)</td>
              <td rowspan="1" colspan="1">−2.761</td>
              <td rowspan="1" colspan="1">
                <bold>0.006</bold>
              </td>
            </tr>
          </tbody>
        </table>
        <table-wrap-foot>
          <fn>
            <p>* Median (<abbrev xlink:title="interquartile range">IQR</abbrev>) - median and interquartile range (25th–75th percentile)</p>
          </fn>
        </table-wrap-foot>
      </table-wrap>
      <table-wrap id="T17" position="float" orientation="portrait">
        <label>Table 17.</label>
        <caption>
          <p>Studies on NGAL in pediatric oncology as a marker for nephrotoxicity </p>
        </caption>
        <table>
          <tbody>
            <tr>
              <td rowspan="1" colspan="1">
                <bold>Year</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold>Authors</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold>Medication</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold>Number of patients</bold>
              </td>
              <td rowspan="1" colspan="1">
                <bold>NGAL results</bold>
              </td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">2022</td>
              <td rowspan="1" colspan="1">Asma Abdel Sameea Mahmoud et al.</td>
              <td rowspan="1" colspan="1">Cisplatin, methotrexate</td>
              <td rowspan="1" colspan="1">52 children after treatment</td>
              <td rowspan="1" colspan="1">A good predictor of tubular damage  in children who have completed  treatment</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">2017</td>
              <td rowspan="1" colspan="1">Kelly R. McMahon et al.<sup>[<xref ref-type="bibr" rid="B16">16</xref>]</sup></td>
              <td rowspan="1" colspan="1">Cisplatin</td>
              <td rowspan="1" colspan="1">150 children</td>
              <td rowspan="1" colspan="1">Predictive marker for <abbrev xlink:title="Acute kidney injury">AKI</abbrev></td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">2021</td>
              <td rowspan="1" colspan="1">Eryk Latoch et al.</td>
              <td rowspan="1" colspan="1">Ifosfamide, cisplatin</td>
              <td rowspan="1" colspan="1">60 children after treatment</td>
              <td rowspan="1" colspan="1">Marker for CKD</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">2022</td>
              <td rowspan="1" colspan="1">Kelly R. McMahon et al.<sup>[<xref ref-type="bibr" rid="B14">14</xref>]</sup></td>
              <td rowspan="1" colspan="1">Cisplatin</td>
              <td rowspan="1" colspan="1">159 children</td>
              <td rowspan="1" colspan="1">Predictive marker, but during the later chemotherapy cycles</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">2017</td>
              <td rowspan="1" colspan="1">Maya Sterling et al.<sup>[<xref ref-type="bibr" rid="B15">15</xref>]</sup></td>
              <td rowspan="1" colspan="1">Ifosfamide, cisplatin</td>
              <td rowspan="1" colspan="1">51 children</td>
              <td rowspan="1" colspan="1">Predictive for <abbrev xlink:title="Acute kidney injury">AKI</abbrev> with ifosfamide, but not with cisplatin</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">2015</td>
              <td rowspan="1" colspan="1">Mohamed A. Almalky<sup>[<xref ref-type="bibr" rid="B13">13</xref>]</sup></td>
              <td rowspan="1" colspan="1">Cisplatin, ifosfamide</td>
              <td rowspan="1" colspan="1">60 children</td>
              <td rowspan="1" colspan="1">High predictive value for <abbrev xlink:title="Acute kidney injury">AKI</abbrev></td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">2014</td>
              <td rowspan="1" colspan="1">Elisa Ylinen et al.<sup>[<xref ref-type="bibr" rid="B17">17</xref>]</sup></td>
              <td rowspan="1" colspan="1">High dosed methotrexate</td>
              <td rowspan="1" colspan="1">20 children</td>
              <td rowspan="1" colspan="1">No advantages over other markers – cystatin C</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">2015</td>
              <td rowspan="1" colspan="1">V. Kesik<sup>[<xref ref-type="bibr" rid="B19">19</xref>]</sup></td>
              <td rowspan="1" colspan="1">Ifosfamide</td>
              <td rowspan="1" colspan="1">29 children</td>
              <td rowspan="1" colspan="1">Marker for CKD diagnosing</td>
            </tr>
            <tr>
              <td rowspan="1" colspan="1">2016</td>
              <td rowspan="1" colspan="1">Katarzyna Musiol et al.</td>
              <td rowspan="1" colspan="1">Cisplatin, ifosfamide, methotrexate</td>
              <td rowspan="1" colspan="1">38 children</td>
              <td rowspan="1" colspan="1">Low sensitivity for CKD</td>
            </tr>
          </tbody>
        </table>
      </table-wrap>
      <p>In the study by Mohamed Almalky et al., conducted among 30 children with solid tumors undergoing chemotherapy, the authors found a statistically significant difference between the number of children diagnosed with <abbrev xlink:title="Acute kidney injury">AKI</abbrev> based on urinary NGAL levels (10 out of 30) and those diagnosed using serum creatinine levels (0 out of 30). However, they used an NGAL cutoff value of &gt;25 ng/mL for predictive significance<sup>[<xref ref-type="bibr" rid="B13">13</xref>]</sup>, rather than the &gt;113 ng/mL threshold commonly discussed in the literature.</p>
      <p>In another large prospective study by McMahon et al., involving 159 children undergoing chemotherapy with cisplatin, urinary NGAL levels were found to have low predictive value for <abbrev xlink:title="Acute kidney injury">AKI</abbrev>. Higher NGAL values were observed during later infusions of the drug compared to the initial cycles of therapy (AUC-ROC 0.54–0.75 for late infusion vs. AUC-ROC 0.48–0.65 for early infusion).<sup>[<xref ref-type="bibr" rid="B14">14</xref>]</sup></p>
      <p>In a study by Miloševski-Lomić et al., published in 2023, emphasis is placed on the higher predictive value of using a combination of biomarkers (NGAL, KIM-1, L-FABP) for the diagnosis of <abbrev xlink:title="Acute kidney injury">AKI</abbrev> following the administration of nephrotoxic drugs in children, compared to the use of each biomarker individually.<sup>[<xref ref-type="bibr" rid="B20">20</xref>]</sup></p>
      <p>In our study, using the KDIGO criteria, two episodes of <abbrev xlink:title="Acute kidney injury">AKI</abbrev> were diagnosed following courses of nephrotoxic medication. In both episodes, NGAL levels remained unchanged. In two children with disease relapse, elevated NGAL levels were observed both before and after the chemotherapy course; all of these courses were within the “cycle 4–10” group, meaning the patients had undergone previous chemotherapy cycles. For the rest of the children, especially for the second, third, and “4–10” cycles, a statistically significant difference in NGAL levels was observed; however, the values remained within the reference range and, in most cases, were lower than those measured prior to chemotherapy. One of the questions that arises is whether this could be due to urine dilution as a result of the hyperhydration administered to all children after each chemotherapy cycle. To account for this dilution effect, a NGAL-to-creatinine ratio was calculated from a single urine sample collected 12 hours after the chemotherapy cycle. A statistically significant increase of this ratio was observed only in the “4–10 cycle“ group, indicating that NGAL levels rise as a result of the cumulative nephrotoxic effect—an observation consistent with the findings of Kelly R. McMahon. This identifies NGAL as a marker that is not reliable for diagnosing <abbrev xlink:title="Acute kidney injury">AKI</abbrev> induced by nephrotoxic drugs, particularly chemotherapeutic agents.</p>
      <p>Regarding the classical indicators for diagnosing <abbrev xlink:title="Acute kidney injury">AKI</abbrev>, the more accurate measure is the estimation of <abbrev xlink:title="estimated GFR">eGFR</abbrev>. Its determination is extremely important in oncology, especially when nephrotoxic chemotherapy regimens are to be administered, in order to optimize drug dosing according to renal function. There are very few studies in the literature concerning GFR in pediatric oncology patients. The method used to determine GFR is also widely discussed. The most accurate methods for measuring absolute GFR are radioisotope techniques (such as [51Cr]-EDTA). Unfortunately, the need for multiple blood samples or the lack of access to the respective radioisotope makes these methods rarely used and less preferred in clinical practice. One of the proposed methods for estimating GFR is the classical Schwartz formula, which, given the low body weight of pediatric oncology patients, is recommended to be adjusted for body surface area.<sup>[<xref ref-type="bibr" rid="B6">6</xref>]</sup> An interesting finding across all these studies is the high prevalence of hyperfiltration, regardless of the chosen GFR measurement method, both before the start of treatment and after the initial chemotherapy cycles. Such is the study by Kwatra et al., which found a 43.5% rate of hyperfiltration among 177 children, measured by DTPA (diethylenetriaminepentaacetic acid) clearance during at least one chemotherapy cycle. In a study by Hjorth et al., also using a radioisotope method (iohexol clearance), a hyperfiltration rate of 31% was reported.<sup>[<xref ref-type="bibr" rid="B6">6</xref>,<xref ref-type="bibr" rid="B21">21</xref>,<xref ref-type="bibr" rid="B22">22</xref>]</sup> In the follow-up of <abbrev xlink:title="estimated GFR">eGFR</abbrev> levels in our study, a high rate of hyperfiltration was also observed, comparable to the cited studies, both at disease onset (55 cycles, 47.8%), and after chemotherapy (58 cycles, 50.43%) measured at 12 hours post-cycle. Hyperfiltration was defined as <abbrev xlink:title="estimated GFR">eGFR</abbrev> values &gt;160 mL/min/1.73 m<sup>2</sup>. The pathophysiology of hyperfiltration is widely discussed, with the most accepted theory being the hypermetabolic state in which children with oncological diseases find themselves, especially during chemotherapy.<sup>[<xref ref-type="bibr" rid="B6">6</xref>,<xref ref-type="bibr" rid="B21">21</xref>,<xref ref-type="bibr" rid="B22">22</xref>]</sup> The hypothesis of increased creatinine excretion due to tubular injury during chemotherapy cycles as an etiology for hyperfiltration was not confirmed, since no statistically significant correlation was found between children with hyperfiltration and fractional excretion of phosphate or the renal phosphate threshold.</p>
      <p>The use of the classical Schwartz formula is an easy and widely accessible method but tends to overestimate glomerular filtration. There are few studies in the literature regarding which formula to use for pediatric oncology patients, but all recommend formulas based on body weight. These include the body surface area–corrected Schwartz formula, the Brandt formula, or the Cockcroft–Gault formula.<sup>[<xref ref-type="bibr" rid="B6">6</xref>,<xref ref-type="bibr" rid="B21">21</xref>-<xref ref-type="bibr" rid="B25">25</xref>]</sup> Our study used two of these formulas, the adjusted Schwartz formula and the Brandt formula. With both formulas, the percentage of hyperfiltration observed with the classical Schwartz formula decreased significantly but remained high—up to 28%. This result is comparable to those obtained in studies measuring GFR in pediatric oncology patients using radioisotope methods; however, an increase in cases with reduced <abbrev xlink:title="estimated GFR">eGFR</abbrev> was also observed. Unlike the classical formula, where children with increased fractional excretion of phosphate and correspondingly low renal phosphate threshold mostly have normal GFR, the formulas based on body weight tend to show these children predominantly have reduced GFR.</p>
      <p>Some of the medications used in pediatric oncology, especially in children with solid tumors, are nephrotoxic and primarily cause tubular injury. The proximal tubule, being the most metabolically active part of the tubular apparatus, is the most affected. This leads to the manifestation of partial or generalized proximal tubular dysfunction—renal Fanconi syndrome. The clinical presentation is characterized by aminoaciduria, hypophosphatemia, low-molecular-weight proteinuria (β2-microglobulin, retinol-binding protein), normoglycemic glucosuria, metabolic acidosis, hypokalemia, and hypouricemia. While tubular proteinuria and glucosuria do not have a significant impact on the body, increased phosphate excretion leading to hypophosphatemia is one of the main clinically important tubular dysfunctions as it leads to skeletal demineralization and osteomalacia, proximal muscle weakness, bone pain, spontaneous fractures, or the development of hypophosphatemic rickets. Due to preserved distal tubular function, polyuria is a rare clinical finding, and metabolic acidosis is generally mild (HCO<sub>3</sub>&gt;15).<sup>[<xref ref-type="bibr" rid="B25">25</xref>-<xref ref-type="bibr" rid="B28">28</xref>]</sup></p>
      <p>By using only standard methods to assess renal function—serum creatinine levels and oliguria—this type of injury often goes unrecognized, since glomerular function is usually preserved, except in cases where the distal tubule is also affected and creatinine secretion is impaired. In the conducted study, increased phosphate excretion was observed before the chemotherapy cycle in only 10% of all 116 cycles, while 12 hours after the treatment course, the percentage increased significantly to 35.5%. Furthermore, as the cycle number increased, so did the number of children with tubular injury, indicating a cumulative nephrotoxic effect. A similar result was observed using the more precise marker, the renal phosphate threshold. A low renal phosphate threshold was present before the start of therapy in only 17 cycles (14.7%), and 12 hours after the cycle in 44 cycles (37.0%). Here too, an increase in the percentage of low renal phosphate threshold cases was observed with the increasing number of chemotherapy cycles administered.</p>
      <p>Monitoring serum electrolyte levels of phosphorus and magnesium shows that with the cumulative nephrotoxic effect over successive cycles, clinically manifest hypophosphatemia and hypomagnesemia develop. The frequency of hypophosphatemia reported in the literature varies from 0 to 36.8%, and tubular phosphate reabsorption disorders range from 0 to 62%.<sup>[<xref ref-type="bibr" rid="B29">29</xref>]</sup> Our data are consistent with the ones reported in the literature. As a rule, upon the manifestation of tubular toxicity, the medication should be discontinued, or if it must be continued (with no alternative), its dose should be reduced according to the severity of acute kidney injury. In most cases, tubulopathy is reversible and transient, lasting a few months, but in some children, it becomes chronic, with a reported incidence of tubular injury reaching up to 20–25%.<sup>[<xref ref-type="bibr" rid="B30">30</xref>]</sup> This necessitates the development of a monitoring algorithm for children who have undergone chemotherapy, including for late side effects related to kidney function.</p>
      <p>We present an algorithm for monitoring renal function in children undergoing chemotherapy with nephrotoxic drugs <bold>(Fig. <xref ref-type="fig" rid="F8">8</xref>)</bold>.</p>
      <fig id="F8">
        <object-id content-type="arpha">B92282E0-BEA1-5D21-88B3-55426C11EA2C</object-id>
        <label>Figure 8.</label>
        <caption>
          <p>Algorithm for monitoring renal function in pediatric patients receiving nephrotoxic chemotherapy.</p>
        </caption>
        <graphic xlink:href="foliamedica-68-4-e184913-g008.jpg" id="oo_1761320.jpg">
          <uri content-type="original_file">https://binary.pensoft.net/fig/1761320</uri>
        </graphic>
      </fig>
      <p>Our study has certain limitations, most notably the small sample size and its single-center design, which restrict the ability to draw more robust conclusions.</p>
    </sec>
    <sec sec-type="Conclusions" id="sec13">
      <title>Conclusions</title>
      <p>Acute kidney injury (<abbrev xlink:title="Acute kidney injury">AKI</abbrev>) is a common complication in the treatment of pediatric oncology patients. One of the leading risk factors for its development is drug-induced nephrotoxicity, particularly associated with nephrotoxic chemotherapeutic agents. This necessitates careful monitoring of renal function both during therapy and after its discontinuation.</p>
      <p>The widely discussed biomarker NGAL, although considered an early marker of <abbrev xlink:title="Acute kidney injury">AKI</abbrev>, has limitations when used as a standalone diagnostic tool in children receiving nephrotoxic chemotherapy. While its role has been better established in hypoxic conditions and certain surgical settings, its diagnostic and predictive value in pediatric oncology remains controversial. It is influenced by multiple factors, including the cumulative effect of treatment cycles and the impact of hyperhydration.</p>
      <p>The measurement of <abbrev xlink:title="estimated GFR">eGFR</abbrev> remains a key parameter in evaluating kidney function in pediatric oncology patients. The use of formulas adjusted for body surface area or body mass provides more accurate assessments compared to the classical Schwartz formula.</p>
      <p>Markers of tubular injury, such as <abbrev xlink:title="fractional excretion of phosphate">FeP</abbrev>% and <abbrev xlink:title="tubular maximum reabsorption of phosphate per GFR">Tmp/GFR</abbrev> (renal phosphate threshold), can serve as valuable tools for the early detection of drug-induced nephrotoxicity in pediatric oncology. The observed cumulative toxicity highlights the urgent need for the development of a standardized algorithm for monitoring renal function both during and after the completion of oncological treatment in order to ensure timely intervention and reduce the risk of progression to chronic kidney disease.</p>
    </sec>
  </body>
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    <sec sec-type="Additional information" id="sec14">
      <title>Additional information</title>
      <p>
        <bold>Ethical approval</bold>
      </p>
      <p>This study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Ethics Committee of the Medical University of Plovdiv (protocol No. HO-11/2021).</p>
      <p>
        <bold>Ethical statements</bold>
      </p>
      <list list-type="bullet">
        <list-item>
          <p>The authors declared that no clinical trials were used in the present study.
</p>
        </list-item>
        <list-item>
          <p>The authors declared that no experiments on humans or human tissues were performed for the present study.
</p>
        </list-item>
        <list-item>
          <p>Written informed consent was obtained from all subjects involved in the study. The signed informed consent forms are safely deposited at the Department of Pathophysiology in the Medical University of Plovdiv and available for review upon request.
</p>
        </list-item>
        <list-item>
          <p>The authors declared that no experiments on animals were performed for the present study.
</p>
        </list-item>
        <list-item>
          <p>The authors declared that no commercially available immortalized human and animal cell lines were used in the present study.
</p>
        </list-item>
      </list>
      <p>
        <bold>Conflict of interest</bold>
      </p>
      <p>We declare no conflict of interest between the authors of this paper and other entities.</p>
      <p>
        <bold>Artificial Intelligence (AI) use</bold>
      </p>
      <p>he authors accept full responsibility for the content of the manuscript, including the disclosure of any use of AI.</p>
      <p>No AI tools were used in the preparation of this manuscript.</p>
      <p>
        <bold>Funding</bold>
      </p>
      <p>No funding was reported.</p>
      <p>
        <bold>Author contributions</bold>
      </p>
      <p>All authors have contributed equally to the preparation of this manuscript and have permitted their names to be included as co-authors.</p>
      <p>
        <bold>Author ORCIDs</bold>
      </p>
      <p>Kameliya Bratoeva <ext-link xlink:href="https://orcid.org/0000-0002-6235-3384" ext-link-type="uri">https://orcid.org/0000-0002-6235-3384</ext-link></p>
      <p>
        <bold>Data availability</bold>
      </p>
      <p>All data used are referenced or included in the article.</p>
    </sec>
  </back>
</article>
