article · F1000Research
<ns3:p>Background Endometrial malignancy in premenopausal women with abnormal uterine bleeding (AUB) is rare but clinically challenging. Current diagnostic strategies rely on endometrial sampling, which is invasive and often unnecessary. This study aimed to develop and internally validate a novel risk prediction score for endometrial malignancy in premenopausal women with AUB. Methods A retrospective longitudinal analytical study was conducted over 8 years and 11 months (January 2016–November 2024) at Charles Nicolle Hospital, Tunis, Tunisia. Premenopausal women with AUB who underwent endometrial biopsy followed by hysterectomy were included. Comparative analyses, logistic regression, and ROC curve analysis were performed. Significant variables were weighted according to adjusted odds ratios to construct a risk prediction score. Results Among 209 patients, 13 (6.2%) had endometrial malignancy. Independent predictors of endometrial malignancy were: oral contraceptive use (OR 29.9, 95% CI 1.5–587.1, p = 0.025), endometrial thickness >9 mm (OR 25.3, 95% CI 4.3–147.6, p < 0.001), vascularization (OR 98.3, 95% CI 3.7–2594.8, p = 0.006). Protective factors included hemorrhage episode ≤1 (OR 0.20, 95% CI 0.08–0.52, p = 0.001) and lower bleeding abundance (OR 0.30, 95% CI 0.13–0.65, p = 0.002). The final score allocated points as follows: endometrial thickness >9 mm (+3), oral contraceptive use (+3), vascularization (+4), hemorrhage episodes ≤1 (−2), and lower bleeding abundance (−1). A score ≥7 defined high risk. Model discrimination was excellent (AUC 0.901, 95% CI 0.825–0.976, p < 0.001). At a cutoff ≥7, sensitivity was 77%, specificity 90%, positive predictive value 34%, and negative predictive value 98%. Conclusions We developed and internally validated a novel risk prediction score for endometrial malignancy in premenopausal women with AUB. With strong diagnostic performance and high negative predictive value, this score may help clinicians better identify women who truly require invasive sampling.</ns3:p>
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DOI: 10.12688/f1000research.170227.1
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