Work

Development and validation of a nomogram for predicting the risk of malignancy in intraductal papillary neoplasms: a retrospective study

Year: 2025

Type: article

Abstract: • Our study involved a robust sample of 6646 patients diagnosed to identify ten independent predictors for malignancy risk and integrated these into a predictive nomogram model. • The model demonstrated excellent predictive performance and practical utility and can reliably guide clinicians in making individualized treatment decisions. • Our study involves the largest sample size to date and is the first to construct a risk model to predict the probability of malignancy in patients with Intraductal Papillary Neoplasms. Development and validation of a simple, accurate nomogram for predicting the risk of malignancy in intraductal papillary neoplasms (IPNs). Some studies have explored the independent risk factors associated with malignant IPNs, but no validated predictive model has been developed to help clinicians assess the probability of malignancy in patients with IPNS. This case-control study included 6646 patients with IPNs which date came from single-center. A nomogram predicting the malignant probability of IPNs was developed by incorporating independent predictors identified through multivariate logistic regression analysis, and the nomogram was externally validated. Age ≥50 years, bloody discharge, palpable tumor, postmenopausal status, multiple tumors, unclear boundaries, blood flow signals, tumor size ≥15 mm, distance from the nipple ≥1 cm, and the presence of tumor calcification were identified as independent risk factors for predicting malignancy in IPNs. A nomogram was constructed using these 10 factors, yielding a C-index and the area under the curve of 0.871 (95% CI 0.857–0.884) in the training set and 0.874 (95% CI 0.858–0.890) in the validation set. Moreover, the calibration curves demonstrated a high level of agreement between predicted and actual values, and clinical decision curve analysis and clinical impact curve visually confirmed the satisfactory clinical utility of the model. According to the nomogram, we suggest that IPNs patients with a malignant probability <10% can choose regular follow-up rather than surgical treatment. Our nomogram may assist clinicians in identifying IPNs with varying degrees of malignant risk, facilitating decision-making for personalized treatment in clinical practice.

Source: Translational Oncology

DOI: 10.1016/j.tranon.2025.102545