Associations between aggregate index of systemic inflammation and endometriosis risk utilizing logistic regression analysis

Jing Chen, Kaiqiang Xu, Yanyan Xing, Songping Liu, Lijuan Lu
In: Frontiers in Medicine · 2026 · vol. 13 , pp. 1817928 · doi:10.3389/fmed.2026.1817928 · PMID:42158120 · PMC13180812 · W7160107606
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This study found that an aggregate index of systemic inflammation (AISI) is significantly associated with endometriosis risk, and a nomogram incorporating AISI improved predictive ability for endometriosis.

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Abstract

Objective Systemic inflammatory response plays a key role in the pathogenesis of endometriosis. This study aimed to investigate the association between the aggregate index of systemic inflammation (AISI), defined as neutrophil count × platelet count × monocyte count/lymphocyte count, and the risk of endometriosis, and to develop a predictive nomogram incorporating AISI. Methods A retrospective analysis was conducted on patients presenting with symptoms suggestive of endometriosis at Jinshan Hospital of Fudan University from January 2023 to December 2025. Participants were classified into endometriosis and non-endometriosis groups based on pathological diagnosis. Baseline characteristics, lipid profiles, and complete blood cell counts were collected. Univariate logistic regression was first performed, followed by multivariate logistic regression with a backward stepwise approach. Model performance was assessed using the area under the receiver operating characteristic curve (AUC), calibration curves, and decision curve analysis. External validation was conducted using data from the National Health and Nutrition Examination Survey (NHANES, 2001–2006). Results A total of 226 patients were included, with 104 (46.02%) diagnosed with endometriosis. Compared to the non-endometriosis group, patients with endometriosis had significantly higher age, total cholesterol (TC), total triglycerides (TG), low-density lipoprotein cholesterol (LDL) and AISI levels, and significantly lower body mass index (BMI), high-density lipoprotein cholesterol (HDL), red blood cell count (RBC) and earlier age at menarche (all p < 0.05). Multivariate analysis identified age (OR: 1.08, 95%CI: 1.02–1.14, p = 0.005), BMI (OR: 0.74, 95%CI: 0.64–0.85, p < 0.001), age at menarche (OR: 0.58, 95%CI: 0.43–0.79, p < 0.001), RBC (OR: 0.19, 95%CI: 0.06–0.54, p = 0.003), log2-AISI (OR: 4.18, 95%CI: 2.42–7.22, p < 0.001), TC (OR: 2.31, 95%CI: 1.40–3.82, p = 0.001) and HDL (OR: 0.10, 95%CI: 0.03–0.32, p < 0.001) as independent predictors of endometriosis risk. The nomogram showed good calibration and strong discriminatory ability, with an AUC of 0.869 (95% CI: 0.823–0.915), which outperformed models excluding AISI (AUC 0.811) or using AISI alone (AUC 0.721). Decision curve analysis demonstrated high clinical utility of the nomogram. External validation from NHANES confirmed that log2-AISI remained independently associated with endometriosis (OR: 2.38, 95% CI: 1.90–2.98, p < 0.001) after full adjustment. Conclusion AISI is significantly associated with the risk of endometriosis, and the nomogram incorporating AISI with clinical and lipid parameters provides an objective tool for early identification of high-risk individuals.

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endometriosis

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