Association and discriminative performance of TNF-α and CA125 for disease severity and pain severity in endometriosis patients

In: Narra J · 2026 · vol. 6(3) , pp. e3132 · doi:10.52225/narra.v6i3.3132 · W7208826257
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In histopathologically confirmed endometriosis, CA125 significantly correlated with disease severity and showed good discriminative ability, while both CA125 and TNF-α exhibited only weak correlations with pain severity.

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This cross-sectional study evaluated the association and discriminative performance of peritoneal fluid TNF-α and serum CA125 against anatomical disease severity and pain intensity in women with histopathologically confirmed endometriosis. Researchers measured biomarker levels and assessed severity using the rASRM classification and Numeric Rating Scale, finding that CA125 significantly correlated with disease stage and demonstrated good discriminative ability for severity classification. While both markers showed weak but significant correlations with pain scores, their overall capacity to discriminate severe pain was limited compared to their utility in assessing structural disease burden. This paper is centrally about endometriosis — specifically investigating biomarkers for disease and pain severity in patients with histopathologically confirmed endometriosis.

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Abstract

Endometriosis is a chronic inflammatory disease frequently associated with pelvic pain and disease progression. Tumor necrosis factor-alpha (TNF-α) and cancer antigen 125 (CA125) have been proposed as potential biomarkers reflecting inflammatory activity and disease burden. However, evidence remains limited on whether these biomarkers are associated with both anatomical disease severity and pain severity, particularly among patients with histopathologically confirmed endometriosis. The aim of this study was to evaluate the associations and discriminative performance of TNF-α and CA125 in relation to endometriosis severity and pain severity. A cross-sectional study was conducted at Dr. Zainoel Abidin Hospital, Banda Aceh, Indonesia, from October 2025 to January 2026, in which women with histopathologically confirmed endometriosis were included. Disease severity was classified intraoperatively using the revised American Society for Reproductive Medicine (rASRM) system. Pain severity was assessed using the Numeric Rating Scale (NRS). Peritoneal fluid TNF-α was measured using enzyme-linked immunosorbent assay (ELISA), and serum CA125 was measured using electrochemiluminescence immunoassay (ECLIA). Associations were analyzed using Spearman correlation, and discriminative ability was assessed using receiver operating characteristic (ROC) curve analysis. CA125 showed a significant positive correlation with rASRM stage (r=0.401; p=0.005) and TNF-α showed no significant correlation (r=0.068; p=0.649). ROC analysis demonstrated that CA125 had good discriminative ability for disease severity (AUC=0.808; p<0.001) with an optimal cut-off value of 32 U/mL. For pain severity, both CA125 (r=0.344; p=0.018) and TNF-α (r=0.338; p=0.020) had weak but significant positive correlations with NRS scores. ROC analysis indicated fair discriminative ability of CA125 (AUC=0.700; p=0.010) and TNF-α (AUC=0.674; p=0.031) for severe pain, with optimal cut-off values of 50.85 U/mL and 0.023 pg/mL, respectively. These findings highlight that CA125 is more consistently associated with endometriosis severity than TNF-α, while both biomarkers show limited ability to discriminate pain severity.
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Association and discriminative performance of TNF-α and CA125 for disease severity and pain severity in endometriosis patients DOI: https://doi.org/10.52225/narra.v6i3.3132Keywords: Endometriosis, TNF-α, CA125, disease severity, pelvic painAbstract Endometriosis is a chronic inflammatory disease frequently associated with pelvic pain and disease progression. Tumor necrosis factor-alpha (TNF-α) and cancer antigen 125 (CA125) have been proposed as potential biomarkers reflecting inflammatory activity and disease burden. However, evidence remains limited on whether these biomarkers are associated with both anatomical disease severity and pain severity, particularly among patients with histopathologically confirmed endometriosis. The aim of this study was to evaluate the associations and discriminative performance of TNF-α and CA125 in relation to endometriosis severity and pain severity. A cross-sectional study was conducted at Dr. Zainoel Abidin Hospital, Banda Aceh, Indonesia, from October 2025 to January 2026, in which women with histopathologically confirmed endometriosis were included. Disease severity was classified intraoperatively using the revised American Society for Reproductive Medicine (rASRM) system. Pain severity was assessed using the Numeric Rating Scale (NRS). Peritoneal fluid TNF-α was measured using enzyme-linked immunosorbent assay (ELISA), and serum CA125 was measured using electrochemiluminescence immunoassay (ECLIA). Associations were analyzed using Spearman correlation, and discriminative ability was assessed using receiver operating characteristic (ROC) curve analysis. CA125 showed a significant positive correlation with rASRM stage (r=0.401; p=0.005) and TNF-α showed no significant correlation (r=0.068; p=0.649). ROC analysis demonstrated that CA125 had good discriminative ability for disease severity (AUC=0.808; p<0.001) with an optimal cut-off value of 32 U/mL. For pain severity, both CA125 (r=0.344; p=0.018) and TNF-α (r=0.338; p=0.020) had weak but significant positive correlations with NRS scores. ROC analysis indicated fair discriminative ability of CA125 (AUC=0.700; p=0.010) and TNF-α (AUC=0.674; p=0.031) for severe pain, with optimal cut-off values of 50.85 U/mL and 0.023 pg/mL, respectively. These findings highlight that CA125 is more consistently associated with endometriosis severity than TNF-α, while both biomarkers show limited ability to discriminate pain severity. Downloads Downloads Published How to Cite Issue Section License Copyright (c) 2026 Rauzatul Jannah, Rusnaidi Rusnaidi, Hasanuddin Hasanuddin, Cut Meurah Yeni, Dewi Karlina Rusly, Muhammad Yani This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

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