ArticleiLIVER2025
Optimizing postoperative chemotherapy for ampullary cancer: A risk-driven approach to precision care.
Article in iLIVER, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
4 authors.
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Abstract
Background and aims: This research aimed to develop an innovative predictive model for estimating overall survival (OS) in patients with ampullary carcinoma and to evaluate the clinical benefits of postoperative chemotherapy (POCT) tailored to individual risk profiles. Methods: Data from patients with ampullary carcinoma were retrospectively analyzed. Multivariable analysis identified key prognostic factors, which were incorporated into a predictive nomogram. The impact of POCT on OS was assessed within risk groups stratified by the nomogram. Results: Data for 3921 patients were included, with 2744 in the training cohort and 1177 in the validation cohort. A nomogram incorporating age, sex, tumor grade, T stage, N stage, and tumor size outperformed the TNM staging system, with areas under the curve for 3-year, 5-year, and 8-year OS of 0.755 vs 0.687, 0.752 vs 0.694, and 0.750 vs 0.694, respectively, in the training cohort and 0.705 vs 0.664, 0.717 vs 0.679, and 0.734 vs 0.703 in the validation cohort. Calibration plots showed excellent agreement between predicted and observed survival outcomes. Decision curve analysis indicated a net benefit across threshold probabilities above that of TNM staging. Risk stratification based on the model indicated that high-risk patients had a significantly increased mortality risk ( Conclusion: Not all patients benefit from POCT. The proposed nomogram predicts survival effectively and can guide treatment decisions, optimizing outcomes by providing additional chemotherapy for high-risk patients while sparing low-risk patients from unnecessary treatment.
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