Association between the neutrophil percentage-to-albumin ratio and pelvic adhesion severity in endometriosis: A retrospective cross-sectional study - Xiurong Tan; Hong Zhang; Chun Yang; Junhui Chen (PLoS ONE, 2025)
Study background Preoperative assessment of the severity of pelvic adhesions in endometriosis remains challenging. Inflammation may drive adhesion formation, and the predictive value of the neutrophil percentage-to-albumin ratio (NPAR, the ratio multiplied by 10 for analysis), an emerging biomarker of systemic inflammation, in endometriosis pelvic adhesions has not been evaluated. Methods In this study, we retrospectively analyzed the data of 246 patients with histologically confirmed ovarian endometriotic cysts and statistically analyzed NPAR. We evaluated the correlation between NPAR and pelvic adhesion severity in patients with endometriosis using logistic regression models and logistic fitted curves (to evaluate the dose-response relationships). Additionally, the predictive efficacy of NPAR for pelvic adhesion severity was assessed using a receiver operating characteristic (ROC) curve analysis. Results NPAR was positively correlated with the severity of pelvic adhesions, demonstrating statistically significant associations with moderate-to-severe pelvic adhesions in all models when utilized as a continuous variable, and the risk of moderate-to-severe pelvic adhesions increased by 82% for every 10-unit increase in NPAR (Odds Ratio, OR = 1.82); when used as a categorical variable, the risk of moderate-to-severe pelvic adhesions was remarkably increased in the highest tertile of NPAR. ROC curve analysis demonstrated that the area under the curve of the NPAR score was 0.717, which was superior to that of the CA125 (Area Under the Curve,AUC = 0.564). Conclusion NPAR is an independent predictor of moderate to severe pelvic adhesions in patients with endometriosis and is superior to that of CA125. As an easily accessible blood-based biomarker, NPAR may be useful for preoperative risk stratification, guiding surgical planning and individualized treatment decisions.