An immune-inflammatory and thyroid function machine learning model for predicting adverse pregnancy outcomes: Development in a retrospective cohort and external validation in a prospective cohort.

Authors

Yumao Huang, Haihui Chen, Xiaolei Xie, Yu Jin, Jin Huang

Published in

International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics. Oct 27, 2026. Epub Oct 27, 2026.

Abstract

Maternal thyroid dysfunction is associated with adverse pregnancy outcomes, yet thyroid status alone stratifies individual risk poorly and the immune-inflammatory contribution is rarely incorporated into prospectively validated prediction tools. We aimed to develop and externally validate a model predicting a composite adverse pregnancy outcome from antenatal thyroid and cytokine markers.
The model was developed in a retrospective cohort (n = 650; 131 events, 20.2%) and externally validated in an independent prospective cohort (n = 150; 26 events, 17.3%). Fifteen antenatal candidate predictors common to both cohorts were considered. Least absolute shrinkage and selection operator (LASSO) regression was used for variable selection; LASSO-logistic regression, random forest, extreme gradient boosting, and a support-vector machine were compared by repeated stratified cross-validation. Discrimination was quantified using the area under the receiver operating characteristic curve (AUC); calibration and clinical utility were also assessed, with internal-external cross-validation (IECV) as a sensitivity analysis.
LASSO retained three predictors: thyroid peroxidase antibody (TPOAb), interleukin-6 (IL-6), and interleukin-10 (IL-10). LASSO-logistic regression was selected (development cross-validated AUC 0.762, 95% confidence interval [CI] 0.692-0.846). On external validation, the model achieved an AUC of 0.750 (95% CI 0.647-0.848), exceeding a thyroid group-only reference model (AUC 0.625); the Brier score was 0.127, and the calibration slope was 1.77. Random 10-fold IECV gave a pooled AUC of 0.761 (95% CI 0.720-0.800). Higher IL-6 was associated with increased risk and higher IL-10 with decreased risk.
A parsimonious three-marker model combining TPOAb, IL-6, and IL-10 showed moderate discrimination for adverse pregnancy outcomes and outperformed thyroid status alone. Calibration requires refinement, and validation in larger multicenter cohorts is warranted before clinical implementation.

PMID:
42944562
Bibliographic data and abstract were imported from PubMed on 27 Oct 2026.

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