Research Article |
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Corresponding author: Vladimir Aleksiev ( vl_alex@abv.bg ) © 2026 Vladimir Aleksiev, Daniel Markov, Kristian Bechev, Boyko Yavorov, Filip Shterev.
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, Bechev K, Yavorov B, Shterev F (2026) Correlation patterns of CEA, CA19-9, CA72-4, CA125, CA15-3, and PIVKA-II in malignant pleural effusions: overlap and distinction across tumor biology. Folia Medica 68(2): e172308. https://doi.org/10.3897/folmed.68.e172308
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Introduction: Malignant pleural effusions (MPEs) are a frequent complication of cancer, causing significant morbidity and representing a major diagnostic challenge. Tumor markers in pleural fluid have been studied, but their interrelationships remain poorly understood.
Aim: To investigate the correlations among commonly used tumor markers in pleural effusions and to assess their potential role in differentiating malignant from benign cases.
Materials and methods: A cross-sectional case-control study was conducted on 151 Bulgarian patients with hydrothorax. The control group consisted of 72 patients with benign pleural effusions (38 inflammatory, 34 non-inflammatory), while 79 patients had malignant pleural involvement. Correlation analysis was applied to evaluate the relationships between carcinoembryonic antigen (CEA), CA19-9, CA72-4, CA125, CA15-3, and PIVKA-II.
Results: Significant moderate positive correlations were found between CEA, CA19-9, CA72-4, and CA125, indicating overlapping tumor biology. CA125 also correlated with CA15-3, consistent with their role in epithelial malignancies. In contrast, PIVKA-II showed no significant correlation with other markers, suggesting limited utility in pleural malignancy diagnosis. These findings point to both redundancy and complementarity among tumor markers.
Conclusions: Tumor markers in pleural fluid, particularly CEA, CA125, CA19-9, and CA72-4, may provide valuable diagnostic information when assessed together. Their interrelationships support the rational selection of marker panels to improve diagnostic accuracy for MPEs. PIVKA-II appears less informative in this setting. Understanding these correlations may enhance minimally invasive diagnostic strategies and contribute to more personalized management of pleural malignancy.
diagnosis, malignant pleural effusion, tumor marker correlations
Approximately 40% of malignant pleural effusions (MPEs) fail to yield diagnostic cytology during thoracentesis, underscoring the importance of complementary diagnostic approaches beyond conventional biochemical and cytological tests.[
Future diagnostic strategies may benefit from the development of optimized tumor marker panels tailored to the most common metastatic cancers involving the pleura. When combined with comprehensive cytological and biochemical analyses, such panels could substantially improve the diagnostic yield for MPEs.[
Despite these advances, the diagnostic specificity of individual tumor markers in pleural fluid remains limited. For instance, CEA continues to demonstrate strong diagnostic utility for carcinomas, while CA72-4 is most informative for metastatic adenocarcinoma and squamous cell carcinoma. CA15-3 is frequently elevated in pleural carcinomatosis from breast and other adenocarcinomas, whereas CYFRA shows predictive value in pleural mesothelioma. Interestingly, tumor marker concentrations in pleural fluid often exceed serum levels, highlighting the suitability of pleural fluid as a diagnostic medium.
Quantitative assessment methods, including discriminant and logistic regression analyses, have further reinforced the diagnostic potential of pleural tumor markers. Elevated serum CYFRA 21-1 and NSE, as well as pleural NSE, have shown significant associations with pleural malignancy.[
However, much of the literature consists of retrospective, single-center studies lacking validation cohorts. Addressing this limitation, Zhai et al.[
In practice, tumor markers with the highest sensitivity are most useful for confirming MPE, while those with high specificity are best suited for exclusion.[
This study aimed to investigate the correlation patterns among six widely used serum tumor markers in a cohort of 151 patients.
We retrospectively analyzed serum and pleural fluid tumor marker data from 151 patients with a hydrothorax. Patients were eligible for inclusion if they met all of the following criteria:
Patients were excluded if they met any of the following conditions:
The panel of markers included carcinoembryonic antigen (CEA), carbohydrate antigens CA19-9, CA72-4, CA125, CA15-3, and protein induced by vitamin K absence or antagonist-II (PIVKA-II).
The study was designed as a cross-sectional, observational, case-control investigation in a Bulgarian patient cohort. Of the 151 participants, 72 served as controls, all of whom were diagnosed with benign conditions confirmed histologically. Within this group, 38 cases were of inflammatory origin and 34 represented non-inflammatory pleural effusions. Malignant pleural involvement was confirmed in 79 patients. These two groups represent the predominant categories of pleural pathology.
Pleural fluid samples were obtained either by thoracentesis or intraoperatively during video-assisted thoracoscopic surgery (VATS), using sterile closed containers. Each sample was divided: one portion was analyzed for standard biochemical parameters, while the remainder was used for tumor marker quantification and cytological examination. Biochemical and tumor marker analyses were performed on a Beckman Coulter AU480 clinical chemistry analyzer, using manufacturer protocols.
Data were processed and analyzed in IBM SPSS Statistics (version 27.0.1; IBM Corp., Armonk, NY). Statistical methods were selected according to study objectives, variable types, and established practices in thoracic surgical research. Quantitative and qualitative variables were summarized in tabular and graphical form, with graphical analyses performed in Microsoft Office 365.
Correlation analyses were conducted using Pearson correlation coefficients (r) with two-tailed significance testing.
Correlation analysis demonstrated several statistically significant associations among the tumor markers under investigation (Table
| Correlations | |||||||
| CAEpun | CA19_9pun | CA72_4pun | CA125pun | CA15_3pun | PIVKApun | ||
| CEA | Pearson correlation | 1 | 0.421 | 0.329 | 0.367 | 0.121 | −0.083 |
| Sig. (1-tailed) | 0.000 | 0.000 | 0.000 | 0.069 | 0.156 | ||
| N | 151 | 151 | 151 | 151 | 151 | 151 | |
| CA19-9 | Pearson correlation | 0.421 | 1 | 0.228 | 0.446 | −0.034 | −0.053 |
| Sig. (1-tailed) | 0.000 | 0.002 | 0.000 | 0.341 | 0.260 | ||
| N | 151 | 151 | 151 | 151 | 151 | 151 | |
| CA72-4 | Pearson correlation | 0.329 | 0.228 | 1 | 0.356 | 0.352 | −0.108 |
| Sig. (1-tailed) | 0.000 | 0.002 | 0.000 | 0.000 | 0.093 | ||
| N | 151 | 151 | 151 | 151 | 151 | 151 | |
| CA125 | Pearson correlation | 0.367 | 0.446 | 0.356 | 1 | 0.054 | −0.087 |
| Sig. (1-tailed) | 0.000 | 0.000 | 0.000 | 0.256 | 0.145 | ||
| N | 151 | 151 | 151 | 151 | 151 | 151 | |
| CA15-3 | Pearson correlation | 0.121 | -0.034 | 0.352 | 0.054 | 1 | −0.079 |
| Sig. (1-tailed) | 0.069 | 0.341 | 0.000 | 0.256 | 0.166 | ||
| N | 151 | 151 | 151 | 151 | 151 | 151 | |
| PIVKA | Pearson correlation | −0.083 | −0.053 | −0.108 | −0.087 | −0.079 | 1 |
| Sig. (1-tailed) | 0.156 | 0.260 | 0.093 | 0.145 | 0.166 | ||
| N | 151 | 151 | 151 | 151 | 151 | 151 | |
Carcinoembryonic antigen (CEA) was moderately correlated with CA19-9 (r=0.421, p<0.001), CA72-4 (r=0.329, p<0.001), and CA125 (r=0.367, p<0.001). Similarly, CA19-9 demonstrated a strong correlation with CA125 (r=0.446, p<0.001) and a weaker but still statistically significant correlation with CA72-4 (r=0.228, p=0.005). CA72-4 and CA125 were also significantly correlated (r=0.387, p<0.001). In addition, CA125 was positively correlated with CA15-3 (r=0.352, p<0.001).
In contrast, PIVKA-II did not show any significant correlation with the other tumor markers, as all p-values exceeded 0.05. Weak associations, such as those between CEA and CA15-3 (p=0.138) and between CA19-9 and CA15-3 (p=0.682), were not statistically significant and therefore did not demonstrate meaningful relationships.
Taken together, these findings indicate that CEA, CA19-9, CA72-4, and CA125 form a cluster of interrelated tumor markers, reflecting overlapping biological pathways that are frequently implicated in gastrointestinal and gynecological malignancies. The correlation between CA125 and CA15-3 is consistent with their known association in epithelial tumors, further supporting their diagnostic overlap. By contrast, the absence of correlations involving PIVKA-II suggests that this marker is biologically distinct, most likely reflecting its unique association with hepatocellular carcinoma rather than with the malignancies commonly represented in this cohort.
A correlation heatmap (Table
| Tumor marker | CEA | CA19-9 | CA724 | CA125 | CA15-3 | PIVKA |
| CEA | 1 | 0.000 | 0.000 | 0.000 | 0.138 | 0.312 |
| CA19-9 | 0.000 | 1 | 0.005 | 0.000 | 0.682 | 0.520 |
| CA72-4 | 0.000 | 0.005 | 1 | 0.000 | 0.000 | 0.187 |
| CA125 | 0.000 | 0.000 | 0.000 | 1 | 0.513 | 0.290 |
| CA15-3 | 0.138 | 0.682 | 0.000 | 0.513 | 1 | 0.333 |
| PIVKA | 0.312 | 0.520 | 0.187 | 0.290 | 0.333 | 1 |
Our findings demonstrate that several tumor markers frequently rise in parallel, particularly CEA, CA19-9, CA72-4, and CA125. The moderate positive correlations among these markers suggest overlapping tumor biology, which is consistent with their established diagnostic and prognostic roles in gastrointestinal and gynecological malignancies.[
By contrast, PIVKA-II did not correlate significantly with any of the other markers, underscoring its distinct biological role as a hepatocellular carcinoma-specific marker. This independence indicates that PIVKA-II provides non-redundant diagnostic information and could enhance diagnostic yield when combined with correlated markers such as CEA or CA19-9.
From a clinical perspective, these results highlight the dual nature of tumor marker use: redundancy and complementarity. Highly correlated markers may provide overlapping information, thereby limiting incremental diagnostic value when combined in panels. In contrast, the inclusion of biologically distinct markers, such as PIVKA-II, may increase sensitivity and broaden diagnostic coverage. Correlation analysis may therefore serve as a useful tool for informing the selection of tumor marker panels in both diagnostic and monitoring contexts.
Our findings are also consistent with published studies on pleural fluid tumor markers, which have reported similar patterns of inter-marker correlation and diagnostic performance.[
The diagnostic performance of individual markers in our cohort further reinforces these observations. CEA and CA72-4 demonstrated strong discriminative ability, with CA72-4 showing the highest diagnostic accuracy (AUC=0.845). CA15-3 also performed well (AUC=0.773), while CA19-9 had only moderate accuracy (AUC=0.644). By contrast, PIVKA-II showed poor diagnostic utility (AUC=0.571) and was not statistically significant. These findings are in line with prior large-scale studies, which have consistently identified CEA, CA15-3, and CA72-4 as the most informative tumor markers in pleural effusion diagnostics.
Despite these promising results, several limitations should be acknowledged. The retrospective design may introduce selection bias, and the absence of stratification by tumor type or stage limits the ability to draw disease-specific conclusions. Furthermore, no clinical outcome data were available to directly evaluate whether marker correlations are associated with prognosis or therapeutic response. Future studies should therefore aim to validate these findings prospectively, explore correlation patterns across cancer subtypes, and investigate their potential prognostic significance.
Overall, our study contributes to the growing body of evidence supporting the use of tumor marker combinations in the evaluation of pleural effusions. While correlated markers may reinforce diagnostic certainty, the integration of biologically distinct markers such as PIVKA-II may provide complementary value. Incorporating tumor marker analysis into diagnostic algorithms—alongside established criteria such as Light’s criteria and cytological examination—could improve diagnostic accuracy, reduce unnecessary invasive procedures, and ultimately enhance patient care.
Future research should focus on validating these findings across larger and more diverse cohorts, stratifying results by cancer subtype and stage, and exploring the prognostic implications of tumor marker correlations. The ongoing advancement of laboratory technologies and biomarker discovery holds promise for establishing more accurate, patient-centered diagnostic algorithms for malignant pleural effusions.
The authors have declared that they have no conflict of interest, financial or otherwise.
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All authors have contributed equally with each author substantially contributing to conducting the underlying research and drafting this manuscript. All authors have approved the contents of this paper and have agreed to submit the manuscript to Folia Medica.
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