Modified RECIST submodels and ordinal regression model predict neoadjuvant chemoimmunotherapy response in locally advanced gastric cancer​​.

ABSTRACT: This study evaluated predictive models integrating Computed Tomography(CT) and ultrasound(US) to assess neoadjuvant therapy response in locally advanced gastric cancer (LAGC). A prospective multicenter trial (n = 75) developed five RECIST 1.1-derived submodels (RECIST_Expansion, UC_RECIST, CT_RECIST, V-RECIST, U-RECIST) and an ordinal regression-based nomogram, using pathological tumor regression grade (TRG) as the reference standard. The geometric approximation model V-RECIST exhibited superior diagnostic performance for TRG 0-2 vs. 3 discrimination (area under the curve [AUC] = 0.951, sensitivity 96.8%/specificity 80.1%) and TRG 0-1 vs. 2-3 classification (AUC = 0.868, sensitivity 85.7%/specificity 80.0%), validated by calibration curves and decision curve analysis. The US-only U-RECIST

SUBMITTER: Chen S 

PROVIDER: S-EPMC12504738 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature