ArticleGland surgery2026
Recursive partitioning analysis improves risk stratification in node-negative differentiated thyroid cancer: a retrospective cohort study.
Article in Gland surgery, 2026. 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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Abstract
Background: The applicability of the Tumor-Node-Metastasis (TNM) staging system in node-negative differentiated thyroid cancer (DTC) remains uncertain. While recursive partitioning analysis (RPA) offers a powerful alternative for staging refinement, its utility for prognostic prediction in node-negative DTC remains unexplored. This study aimed to develop and validate a novel RPA-based staging system for node-negative DTC. Methods: This retrospective cohort study included 8,816 eligible node-negative DTC patients (15-year follow-up) from the Surveillance, Epidemiology, and End Results (SEER) database, which were randomly assigned to training (n=6,172) and validation sets (n=2,644). Overall survival (OS) was the primary outcome. Independent prognostic factors were identified using Cox proportional hazards models and were used to develop an RPA-based staging system. Prognostic performance was compared with the American Joint Committee on Cancer (AJCC) TNM system using Kaplan-Meier analysis, time-dependent receiver operating characteristic (tROC) curves, and Harrell's concordance index (C-index). Results: In the training set, 15-year OS rates for AJCC TNM stages T1-T4 were 94.4%, 89.9%, 85.4%, and 54.1%. Multivariate analysis (MVA) identified older age, higher tumor grade, advanced T-stage, etc., as independent OS predictors (all P<0.05). RPA categorized patients into stages I-III with 15-year OS rates of 93.6%, 5.6%, and 0% (P<0.05), showing a significantly higher prognostic accuracy (Harrell's C-index: 0.947 Conclusions: The developed and validated RPA-based model demonstrates superior prognostic performance it holds the potential to improve the staging of lymph node-negative DTC.
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