Original Article |
Corresponding author: Vladimir Aleksiev ( vl_alex@abv.bg ) © 2025 Vladimir Aleksiev, Daniel Markov, Boyko Yavorov, Kristian Bechev, Galabin Markov, Filip Shterev, Dimcho Argirov.
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.
Citation:
Aleksiev V, Markov D, Yavorov B, Bechev K, Markov G, Shterev F, Argirov D (2025) Enhanced diagnostic approaches for malignant pleural effusions: an extensive biochemical and statistical analysis. Folia Medica 67(2): e145825. https://doi.org/10.3897/folmed.67.e145825
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Introduction: Malignant pleural effusions are a common and debilitating complication of advanced malignancies, affecting approximately one million patients annually. This condition leads to significant morbidity and a decline in quality of life. Accurate diagnosis and effective management are critical yet challenging due to the overlap in biochemical markers between malignant and benign pleural effusions.
Aim: This study evaluates an extended panel of biochemical parameters, including albumin gradient, total protein, cholesterol, pH, glucose, specific gravity, and lactate dehydrogenase (LDH), to enhance diagnostic precision.
Materials and methods: In order to achieve this, we conducted a cross-sectional, observational case-control study in order to analyze pleural fluid samples from 151 Bulgarian patients, including 79 with malignant effusions and 72 with benign effusions. Biochemical markers, such as albumin gradient, total protein, cholesterol, lactate dehydrogenase (LDH), pH, glucose, and specific gravity, were measured using advanced clinical chemistry analyzers.
Statistical analyses, including Mann-Whitney U tests, t-tests, and Spearman’s rank correlations, were used to identify diagnostic markers.
Results: The key findings highlighted the diagnostic value of albumin gradient, total protein, and cholesterol levels, which are strongly associated with malignant effusions. LDH and specific gravity also demonstrated potential as supplementary markers, while pH and glucose measurements showed limited utility in differentiating malignancy.
Conclusion: Combining these biochemical parameters enhances the precision of pleural effusion analysis, offering a more robust framework for diagnosing and managing malignant pleural effusions effectively.
albumin gradient, biochemical markers, diagnostic differentiation, malignant pleural effusion, pleural fluid analysis
Malignant pleural effusions (MPE) are a major challenge in medical practice, putting a strain on healthcare systems due to their socioeconomic impact. MPEs affect nearly one million people each year and are a leading cause of severe shortness of breath and a lower quality of life. Pleural effusions are a common complication of cancer, affecting approximately 20% of cancer patients.[
The prognosis for patients with MPE is often poor, with median survival ranging from 4 to 9 months, depending on the cancer type and its stage.[
Normal pleural fluid is a clear straw-yellow liquid. Several baseline indicators are used to investigate pleural pathologies:
The acidity of pleural fluid is a poorly studied parameter in modern literature. Only one study exists that addresses the normal pH of pleural fluid in humans.[
When pleural pH falls below 7.3, the condition is known as pleural acidosis.[
Carbon dioxide buildup is linked to both increased production and reduced transport across pleural membranes, as well as increased leukocyte glycolysis.[
Detailed literature analysis even reveals cases of pleural alkalosis, where pleural fluid pH reaches 7.8.[
In addition to distinguishing between exudates and transudates, one of the most practical uses of pleural pH measurement is its prognostic value in predicting the success of pleurodesis. Pleural pH remains the sole independent predictor for successful pleurodesis, with the likelihood of obliterating the pleural space progressively decreasing with lower pleural pH. When pH falls below 7.15, the positive predictive value drops to around 45.7%.[
The specific gravity of pleural fluid is the most precise indirect method for measuring its viscosity. Tavana’s comprehensive study[
Samples were collected from 100 patients undergoing thoracentesis. Based on Light’s criteria, punctates were classified, and specific gravity was measured using refractometry. Among the samples, 70% were classified as exudative effusions and 30% as transudative. In the exudative group, the mean specific gravity was 1033.6, while it was 1021.4 in the transudative group.
The optimal sensitivity and specificity were achieved at a threshold of 1024, with sensitivity, specificity, positive predictive value, and negative predictive value of 91.4%, 66.7%, 86.5%, and 76.9%, respectively.
Quantitative determination of glucose in pleural fluid is an important step in the biochemical analysis of pleural effusions. Values can vary significantly, ranging from 0.00 to 29.36 mmol/L, with a threshold value of 3.30 mmol/L considered significant.[
Several studies have examined the correlation between glucose and pleural fluid acidity.[
For example, while linear dependence is observed in many non-infectious effusions, tuberculous effusions often exhibit drastically low glucose levels unrelated to pleural fluid pH.[
Normal pleural fluid is relatively low in proteins. Protein presence and composition are critical for distinguishing effusion types, as emphasized in Light’s criteria.
Samanta et al.[
LDH is a cytoplasmic enzyme found in all organ cells that plays an essential role in anaerobic metabolism. It is an indicator of inflammation or cellular damage, such as ischemia, dehydration, or bacterial and chemical injury.
In pleural effusions, LDH values above 1000 U/L are significant, often pointing to infectious causes, rheumatoid serositis, tuberculosis, or malignancy.[
Cholesterol, a key sterol in the human body, enters pleural fluid through increased vascular permeability or as a product of degenerating cells. A clinical-laboratory threshold of >45 mg/dL is used for differentiating exudative from transudative effusions.[
In order to achieve the established objectives, a cross-sectional observational case-control study was conducted on a Bulgarian population of patients diagnosed with pleural effusions.
A total of 151 patients participated in the analysis. In the control group of 72 patients, a benign disease was diagnosed and confirmed through subsequent biopsy. Of these, 38 cases were identified as inflammatory, while 34 were verified as pleural effusions of non-inflammatory origin. Malignant pleural involvement was confirmed in 79 patients. These two groups are representative of the main types of pleural pathology.
Pleural fluid was obtained using a closed container for biological material. The biological material was collected during thoracentesis or intraoperatively during VATS. A portion of the collected pleural fluid was used to determine biochemistry parameters, while the remaining fluid was set aside for the analysis of tumor markers and cytological examination. All analyses were carried out using the clinical chemistry analyzer Beckman Coulter, model AU480, in accordance with the original programs.
The choice of statistical methods was made according to the objectives of the study, the type of variables, and established practices in scientific research in the field of thoracic surgery. The systematization, processing, and analysis of primary data in the form of quantitative and qualitative variables were carried out using the statistical software package IBM SPSS Statistics. The analysis and conclusions from the study were drawn after a summarized presentation of the empirical results in tabular form and were illustrated with the corresponding graphs. The graphical analysis was performed using MS Office 365. To objectify the results of the analyses conducted, the following statistical and mathematical methods were used:
- Mann-Whitney Wilcoxon Test: A non-parametric statistical analysis used to compare two independent groups. Its purpose is to determine whether the distribution of the two parameters differs significantly from each other.
- Kolmogorov-Smirnov’s One-Sample Test: A non-parametric test used to check whether a given sample follows a specific distribution. It compares the empirical distribution of data with the theoretical distribution.
- Independent Samples t-test: A parametric test used to compare the means of two independent groups.
- Levene’s Test for Equality of Variances: A statistical test used to check for equality of variances among two or more groups.
- Correlation Analysis: A statistical method used to assess the relationship between two or more variables. It helps to understand whether changes in one independent variable are associated with changes in another dependent variable. It does not establish a causal relationship but measures the degree of association between the variables.
To analyze whether different variables from the full panel of biochemical markers follow a normal distribution, we first applied Kolmogorov-Smirnov’s One-Sample test. The obtained results are shown in Table
It is evident that all included variables significantly deviate from a normal distribution, as supported by the asymptotic significance, which is below the standard significance level of p<0.05 in all cases. Therefore, these variables are not assumed to follow a normal distribution.
This hypothesis is further supported by the application of the Independent Samples t-test, which allows us to check whether there is a statistically significant difference between the mean values of the necessary variables in the two groups of patients. The Levene’s test for Equality of Variances checks whether the variance of the two groups is statistically significant and whether both groups demonstrate homogeneity of variances. The t-test for Equality of Means seeks to find a difference between the means of the two groups and tests whether this difference is statistically significant. The results presented in Table
The benign group shows higher specific gravity values, while cholesterol levels are elevated in the malignant group. Commenting on the cytological examination results, the values for monocytes show equal variances, and the difference in p is close to significant but does not reach it: Levene’s Test (Sig.=0.562); t(149)=−1.768, p=0.079.
If we apply the Mann-Whitney U test, we obtain the results presented in Table
Focusing on the presented data, we note that the albumin gradient, triglyceride levels, specific gravity, total protein, LDH levels, cholesterol levels, and the number of monocytes show a statistically significant difference between the malignant and benign groups. Others, such as pH, glucose levels, and the number of segmented neutrophils, do not show a significant difference. The total leukocyte count and the number of lymphocytes is at the borderline of significance.
To delve into the relationship between the examined indicators, it is necessary to search for a correlation between them. For this, we will use Spearman’s rank correlation coefficient, which evaluates the degree of dependence between two variables without assuming normal distribution of the data. The values range from -1 to 1. To confirm a direct relationship, the value should be positive, while negative values indicate an inverse relationship. For convenience, Table
Normal parameters | Most extreme differences | Statistical test | Asymp. sig. (2-tailed) | |||||
N | Mean | Std. deviation | Absolute | Positive | Negative | |||
SEAG | 151 | 16.0397 | 5.36269 | 0.085 | 0.085 | −0.051 | 0.035 | 0.009 |
TG | 151 | 0.4865 | 1.74971 | 0.410 | 0.395 | −0.410 | 0.410 | <0.001 |
pH | 151 | 7.2748 | 0.42304 | 0.331 | 0.331 | −0.231 | 0.331 | <0.001 |
PSG | 151 | 1012.8146 | 4.22596 | 0.300 | 0.230 | −0.300 | 0.300 | <0.001 |
GLU | 151 | 5.6530 | 3.67905 | 0.173 | 0.173 | −0.167 | 0.173 | <0.001 |
TP | 151 | 35.1987 | 10.73873 | 0.083 | 0.053 | −0.083 | 0.033 | 0.013 |
LDH | 151 | 431.4503 | 622.20932 | 0.269 | 0.269 | −0.261 | 0.269 | <0.001 |
CHOL | 151 | 1.7025 | 0.81446 | 0.085 | 0.085 | −0.054 | 0.035 | 0.009 |
TLC | 151 | 119.77 | 175.413 | 0.264 | 0.264 | −0.253 | 0.264 | <0.001 |
SEG | 151 | 15.88 | 17.672 | 0.238 | 0.238 | −0.203 | 0.238 | <0.001 |
MON | 151 | 5.91 | 3.001 | 0.137 | 0.137 | −0.073 | 0.137 | <0.001 |
LYMPH | 151 | 78.12 | 19.168 | 0.214 | 0.162 | −0.214 | 0.214 | <0.001 |
The t-test for Independent Samples applied to our biochemical parameters
Levene’s test for Equality of Variances | t-test for Equality of Means | 95% Confidence interval of the difference | ||||||||
F | Sig. | t | dr | Sig. (2 tailed) | Mean difference | Sid. error difference | Lower | Upper | ||
SEAG | Equal variances assumed | 7.443 | 0.007 | 4.786 | 149 | <0.001 | 3.90612 | 0.8162 | 2.29330 | 5.51893 |
Equal variances not assumed | 4.703 | 122.8 | <0.001 | 3.90612 | 0.8306 | 2.26197 | 5.55027 | |||
TG | Equal variances assumed | 1.832 | 0.178 | −1.007 | 149 | 0.315 | −0.28717 | 0.2851 | −0.85047 | 0.27614 |
Equal variances not assumed | −1.054 | 79.814 | 0.295 | −0.28717 | 0.2723 | −0.82915 | 0.25481 | |||
pH | Equal variances assumed | 1.054 | 0.306 | −1.661 | 149 | 0.099 | 0.11384 | 0.0685 | −0.24924 | 0.02157 |
Equal variances not assumed | −1.674 | 148.2 | 0.096 | 0.11384 | 0.0680 | −0.24822 | 0.02054 | |||
PSG | Equal variances assumed | 0.741 | 0.391 | 2.855 | 149 | 0.005 | 1.92071 | 0.6727 | 0.59145 | 3.24997 |
Equal variances not assumed | 2.843 | 144.2 | 0.005 | 1.92071 | 0.6755 | 0.58550 | 3.25592 | |||
GLU | Equal variances assumed | 0.091 | 0.763 | 0.158 | 149 | 0.874 | 0.09518 | 0.6014 | −1.0932 | 1.28355 |
Equal variances not assumed | 0.155 | 120.0 | 0.877 | 0.09518 | 0.6129 | −1.1183 | 1.30866 | |||
TP | Equal variances assumed | 11.829 | <0.001 | −3.227 | 149 | 0.002 | −5.47679 | 1.697 | −8.8306 | −2.1230 |
Equal variances not assumed | −3.175 | 125.4 | 0.002 | −5.47679 | 1.725 | −8.8905 | −2.0631 | |||
LDH | Equal variances assumed | 0.064 | 0.801 | 0.947 | 149 | 0.345 | −96.08527 | 101.4 | −296.48 | 104.308 |
Equal variances not assumed | −0.957 | 146.7 | 0.340 | −96.08527 | 100.4 | −294.48 | 102.307 | |||
CHOL | Equal variances assumed | 1.943 | 0.165 | −2.559 | 149 | 0.011 | −0.33346 | 0.1303 | −0.59097 | −0.07596 |
Equal variances not assumed | −2.525 | 130.6 | 0.013 | −0.33346 | 0.1321 | −0.59472 | −0.07220 | |||
TLC | Equal variances assumed | 0.874 | 0.351 | −1.050 | 149 | 0.296 | −29.993 | 28.57 | −86.449 | 26.464 |
Equal variances not assumed | −1.071 | 133.3 | 0.286 | −29.993 | 26.01 | −85.385 | 25.399 | |||
SEG | Equal variances assumed | 0.549 | 0.460 | −0.261 | 149 | 0.794 | −0.754 | 2.888 | −6.462 | 4.953 |
Equal variances not assumed | −0.259 | 140.5 | 0.796 | −0.754 | 2.909 | −6.506 | 4.997 | |||
MON | Equal variances assumed | 0.338 | 0.562 | −1.768 | 149 | 0.079 | −0.858 | 0.486 | −1.817 | 0.101 |
Equal variances not assumed | −1.757 | 141.9 | 0.081 | −0.858 | 0.488 | −1.824 | 0.108 | |||
LYMPH | Equal variances assumed | 0.867 | 0.353 | 0.580 | 149 | 0.563 | 1.816 | 3.130 | −4.369 | 8.001 |
Equal variances not assumed | 0.575 | 138.2 | 0.566 | 1.816 | 3.157 | −4.427 | 8.060 |
Mann-Whitney U | Wilcoxon W | Z | Asymp. sig. (2-tailed) | |
SEAG | 1722.000 | 4882.000 | −4.190 | <0.001 |
TG | 2176.000 | 4804.000 | −2.490 | 0.013 |
pH | 2467.500 | 5095.500 | −1.569 | 0.117 |
PSG | 2134.500 | 5294.500 | −2.903 | 0.004 |
GLU | 2800.500 | 5960.500 | −0.162 | 0.871 |
TP | 2027.500 | 4655.500 | −3.044 | 0.002 |
LDH | 2054.000 | 4682.000 | −2.943 | 0.003 |
CHOL | 1902.000 | 4530.000 | −3.512 | <0.001 |
TLC | 2313.000 | 4941.000 | −1.979 | 0.048 |
SEG | 2578.500 | 5206.500 | −0.993 | 0.321 |
MON | 2207.500 | 4835.500 | −2.387 | 0.017 |
LYMPH | 2366.000 | 5526.000 | −1.783 | 0.075 |
SEAG | TG | pH | PSG | GLU | TP | LDH | CHOL | TLC | SEG | MON | LYMPH | |||
Spearman's rho | SEAG | Correlation coef. | 1.000 | −0.322 | −0.180 | 0.081 | 0.030 | −0.531 | −0.446 | −0.405 | −0.080 | −0.035 | −0.049 | 0.072 |
Sig. (2-tailed) | <0.001 | 0.027 | 0.322 | 0.716 | <0.001 | <0.001 | <0.001 | 0.326 | 0.666 | 0.547 | 0.379 | |||
N | 151 | 151 | 151 | 151 | 151 | 151 | 151 | 151 | 151 | 151 | 151 | 151 | ||
TG | Correlation coef. | −0.322 | 1.000 | 0.117 | −0.102 | −0.048 | 0.397 | 0.450 | 0.457 | 0.195 | 0.161 | 0.132 | −0.191 | |
Sig. (2-tailed) | <0.001 | 0.151 | 0.212 | 0.562 | <0.001 | <0.001 | <0.001 | 0.016 | 0.048 | 0.106 | 0.019 | |||
N | 151 | 151 | 151 | 151 | 151 | 151 | 151 | 151 | 151 | 151 | 151 | 151 | ||
pH | Correlation coef. | −0.180 | −0.117 | 1.000 | −0.340 | −0.118 | 0.120 | 0.059 | 0.178 | 0.145 | 0.157 | 0.027 | −0.141 | |
Sig. (2-tailed) | 0.027 | 0.151 | <0.001 | 0.148 | 0.143 | 0.473 | 0.029 | 0.076 | 0.055 | 0.738 | 0.084 | |||
N | 151 | 151 | 151 | 151 | 151 | 151 | 151 | 151 | 151 | 151 | 151 | 151 | ||
PSG | Correlation coef. | 0.081 | −0.102 | −0.340 | 1.000 | −0.029 | −0.241 | <0.000 | −0.089 | −0.107 | 0.010 | 0.163 | −0.058 | |
Sig. (2-tailed) | 0.322 | 0.212 | <0.001 | 0.722 | 0.003 | 0.996 | 0.275 | 190 | 0.906 | 0.045 | 0.482 | |||
N | 151 | 151 | 151 | 151 | 151 | 151 | 151 | 151 | 151 | 151 | 151 | 151 | ||
GLU | Correlation coef. | 0.030 | −0.048 | −0.118 | −0.029 | 1.000 | −0.009 | −0.310 | −0.077 | −0.196 | −0.228 | −0.035 | 0.216 | |
Sig. (2-tailed) | 0.716 | 0.562 | 0.148 | 0.722 | 0.916 | <0.001 | 0.350 | 0.018 | 0.005 | 0.668 | 0.008 | |||
N | 151 | 151 | 151 | 151 | 151 | 151 | 151 | 151 | 151 | 151 | 151 | 151 | ||
TP | Correlation coef. | −0.531 | 0.397 | 120 | −0.241 | −0.009 | 1.000 | 0.460 | 0.586 | 0.357 | 0.207 | 0.104 | −0.253 | |
Sig. (2-tailed) | 0.001 | <0.001 | 143 | 0.003 | 0.916 | <0.001 | <0.001 | <0.001 | 0.011 | 20.04 | 0.002 | |||
N | 151 | 151 | 151 | 151 | 151 | 151 | 151 | 151 | 151 | 151 | 151 | 151 | ||
LDH | Correlation coef. | −0.446 | 0.450 | 0.059 | 0.000 | −0.310 | 0.460 | 1.000 | 0.397 | 0.352 | 0.409 | 0.168 | −0.426 | |
Sig. (2-tailed) | <0.001 | <0.001 | 0.473 | 0.996 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | 0.039 | <0.001 | |||
N | 151 | 151 | 151 | 151 | 151 | 151 | 151 | 151 | 151 | 151 | 151 | 151 | ||
CHOL | Correlation coef. | 0.405 | 0.457 | 0.178 | −0.089 | −0.077 | 0.586 | 0.397 | 1.000 | 0.287 | 0.210 | 0.101 | −0.248 | |
Sig. (2-tailed) | <0.001 | <0.001 | 0.029 | 0.275 | 0.350 | <0.001 | <0.001 | <0.001 | 0.010 | 0.216 | 0.002 | |||
N | 151 | 151 | 151 | 151 | 151 | 151 | 151 | 151 | 151 | 151 | 151 | 151 | ||
TLC | Correlation coef. | −0.080 | 0.195 | 0.145 | −0.107 | −0.196 | 0.357 | 0.352 | 0.287 | 1.000 | 0.435 | 0.308 | −0.488 | |
Sig. (2-tailed) | 0.326 | 0.016 | 0.076 | 190 | 0.016 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | |||
N | 151 | 151 | 151 | 151 | 151 | 151 | 151 | 151 | 151 | 151 | 151 | 151 | ||
SEG | Correlation coef. | −0.035 | 0.161 | 0.157 | 0.010 | −0.228 | 0.207 | 0.409 | 0.210 | 0.435 | 1.000 | 0.367 | 0.947 | |
Sig. (2-tailed) | 0.666 | 0.048 | 0.055 | 0.906 | 0.005 | 0.011 | <0.001 | 0.010 | <0.001 | <0.001 | <0.001 | |||
N | 151 | 151 | 151 | 151 | 151 | 151 | 151 | 151 | 151 | 151 | 151 | 151 | ||
MON | Correlation coef. | −0.049 | 0.132 | 0.027 | 0.163 | −0.035 | 0.104 | 0.168 | 0.101 | 0.308 | 0.367 | 1.000 | 0.561 | |
Sig. (2-tailed) | 0.547 | 0.106 | 0.738 | 0.045 | 0.668 | 0.204 | 0.039 | 0.216 | <0.001 | <0.001 | <0.001 | |||
N | 151 | 151 | 151 | ISI | 151 | 151 | 151 | 151 | 151 | 151 | 151 | 151 | ||
LYMPH | Correlation coef. | 0.072 | 0.191 | −0.141 | −0.058 | 0.216 | −0.253 | −0.426 | −0.248 | −0.488 | −0.947 | −0.561 | 1.000 | |
Sig. (2-tailed) | 0.379 | 0.019 | 0.084 | 0.482 | 0.008 | 0.002 | <0.001 | 0.002 | <0.001 | <0.001 | <0.001 | |||
N | 151 | 151 | 151 | 151 | 151 | 151 | 151 | 151 | 151 | 151 | 151 | 151 |
A good amount of evidence suggests a correlation between total protein and albumin, as a major component in its composition. This justifies considering both parameters together.
High total protein content in pleural effusion increases the likelihood that it is malignant. This was proven by Hsieh et al.[
Their results clearly showed that total protein content was significantly elevated in the malignant group.
The albumin gradient, as a function of albumin content in pleural fluid, provides much more accurate information compared to isolated albumin testing. It can effectively differentiate exudative from transudative pleural effusions. This concept is supported by recent observations from a study conducted by Benin Ceyhan, who recommends using an upper limit of the albumin gradient at 1.2 g/dl, which provides 76% sensitivity and 100% specificity for detecting exudative pleural effusions.[
To reinforce the benefits of studying the albumin gradient (serum-effusion albumin gradient), we will present a prospective observational study conducted by Sandeesha et al.[
By conducting a comparative analysis between the two groups in our study, we found the following. Using Kolmogorov-Smirnov test values, total protein (p=0.013) and albumin gradient (p=0.009) show non-normal distribution. When applying the Mann-Whitney U test, with p=0.002 and p<0.001 for total protein and albumin gradient respectively, we see that these values show promising levels of statistical significance in distinguishing malignant from benign pleural effusions. The analysis of the results also leads us to the hypothesis that elevated protein content is associated with the severity of pleural damage, whether malignant or inflammatory.
The relationship between triglyceride levels and secondary malignant diseases of the pleura remains controversial. Research on triglycerides in pleural fluid does not provide significant advantages for diagnosing malignant pleural effusions based on the sources used. There is a noticeable lack of adequate studies examining their values in secondary malignant diseases of the pleura. According to the results we obtained from the Kolmogorov-Smirnov test, the triglyceride values in the examined patients with pleural effusions do not follow a normal distribution with p<0.001. On the other hand, Independent Samples tests show conflicting results, with the Equality of Variances test giving p=0.178, and the Equality of Means test showing p=0.315.
Additionally, when analyzing the Mann-Whitney U data, triglycerides show good statistical significance with p=0.013. Therefore, triglyceride values in pleural punctates should be interpreted cautiously and in the context of the overall analysis of the expanded biochemical panel.
An extensive review of available literature shows that increased levels of cholesterol in pleural fluid are associated with an exudative nature of hydrothorax. In a study conducted by Shen et al.[
In addition, Hamm et al. demonstrates that malignant pleural effusions register significantly elevated levels of pleural cholesterol, independent of serum cholesterol with an average of 94 mg/dl, followed by inflammatory pleural effusions (76 mg/dl) and non-malignant effusions (30 mg/dl). He also suggests an upper limit of 60 mg/dl, which differentiates exudative from transudative pleural effusions with only a 5% error.[
Comparing these data with our results, we can observe several intersections. From the Kolmogorov-Smirnov test, with p=0.009, we can conclude that the values do not follow a normal distribution. From the Equality of Variances test, there is an equal variation in the data as p=0.165. However, the Equality of Means test gives a difference between the means with p=0.011.
Given our results and the available information, we can conclude that pleural cholesterol is one of the best diagnostic tools to aid the diagnosis of malignant pleural effusions.
Several studies link about one-third of malignant pleural effusions with a pleural fluid pH<7.30 at the initial manifestation of hydrothorax.[
According to our data, the pH of the punctate has a non-normal distribution of the data in the Kolmogorov-Smirnov test with p<0.001. In the Independent Samples tests, particularly the Equality of Variances test, we get p=0.306, while the Equality of Means test gives p=−1.007.
Additionally, the Mann-Whitney U test shows that there is no statistically significant difference between the malignant and benign groups with p=0.117. Therefore, the acidity of pleural effusion in malignant pleural diseases is not as informative as, for example, in inflammatory diseases.
Regarding glucose values, we see that according to our results, there is a non-normal distribution of the obtained values, p<0.001 in the Kolmogorov-Smirnov test. Expanding this analysis, in the Independent Samples tests, the Equality of Variances test gives p=0.763, and the Equality of Means test gives p=0.874. The statistical significance assessment from the Mann-Whitney U test confirms the hypothesis that glucose does not have statistical significance in differentiating between malignant and benign pleural effusions with p=0.871.
The study of specific gravity in pleural fluid to differentiate malignant from benign pleural effusions is sparsely studied in the available literature. However, there are studies that examine its potential use in distinguishing between exudative and transudative pleural effusions. A study by Abdollahi and Nozarian[
According to our data, the values of relative weight in pleural punctates from the examined patients show a non-normal distribution according to the Kolmogorov-Smirnov test (p<0.001). This is also true in the Independent Samples t-test. Although the parameters show equal variation in the data in the Equality of Variances test p=0.391, the Equality of Means test gives p=0.005. When applying the Mann-Whitney U test, we see that p=0.004, indicating a statistically significant difference between the values in the two groups.
Several studies highlight the importance of lactate dehydrogenase in the diagnosis of malignant pleural effusions and its significance in differentiating between exudative and transudative pleural effusions.[
According to Vergnon et al.[
From the data obtained from the Kolmogorov-Smirnov test, we see that LDH does not demonstrate a normal distribution of the data with p<0.001. When applying the Independent Samples tests, it is evident that the parameters show equal variation in the data in the equality of variances test with p=0.801. In the Equality of Means test, p=0.345. The Mann-Whitney U test reveals a statistically significant difference for LDH between the malignant and benign groups with p=0.003.
As with the total protein levels in the punctate, we hypothesize that LDH levels are indicative of the severity of pleural damage in both inflammatory and malignant pleural effusions, with malignant effusions possibly being a predictor of the degree of pleural carcinomatosis and a poor prognostic factor.[
From all examined parameters of the extended panel of biochemical markers, the tests performed, and the correlations drawn, the most dependable remain the examination of total protein and albumin gradient, lactate dehydrogenase levels. However, the diagnostics can be enhanced by strengthening their application and including cholesterol levels, as well as investigating the total leukocyte count and their subpopulations.
The extended biochemical analysis of pleural punctate reveals that several parameters, including the albumin gradient, total protein, and cholesterol levels, are valuable for differentiating between malignant and benign pleural effusions. Among these, the albumin gradient and total protein stand out as key diagnostic markers, with high total protein levels associated with malignant effusions and the albumin gradient being useful for distinguishing exudative from transudative effusions.
Pleural cholesterol has shown high sensitivity and specificity in diagnosing malignant effusions and is recommended as an important diagnostic parameter. On the other hand, pH and glucose levels, although they correlate with other conditions, are less informative in diagnosing malignant pleural effusions.
While the specific gravity parameter remains underexplored, it holds potential for further use in distinguishing different types of effusions. Combining these biomarkers can enhance diagnostic accuracy, providing a more comprehensive approach to identifying pleural effusions.
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The authors have declared that no competing interests exist.
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