aceThe Lymph Node Ratio as a Predictive Biomarker for Individualized Benefit from Adjuvant Chemotherapy in Gastric Cancer: A Retrospective Cohort and Causal Machine Learning Study
Background Optimizing adjuvant chemotherapy (AC) for gastric cancer (GC) remains challenging due to patient heterogeneity. While the lymph node ratio (LNR) is a known prognostic factor, its role in predicting individualized AC benefit remains underexplored. This study aimed to leverage causal machine learning to explore LNR's role for personalized treatment. Methods We conducted a retrospective cohort study of 2,748 patients undergoing radical gastrectomy (2007-2017, re-staged by AJCC 8th edition). While the ful…
Causal Forest analysis of Stage II-III gastric cancer patients found lymph node ratio was the dominant predictor of individualized benefit from adjuvant chemotherapy, with high-LNR patients showing improved survival.
In the matched Stage II-III cohort, patients with low lymph node ratio showed potential harm from adjuvant chemotherapy, indicating heterogeneous treatment effects and risk of overtreatment.
Findings derive from a retrospective single-cohort design and are framed as exploratory, limiting causal certainty and generalizability without prospective validation.
Evidence
- Peer-reviewedJournal of Gastrointestinal Cancer2026-08-22
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Truvace Impact Record TRV-2026-0866, v1: “The Lymph Node Ratio as a Predictive Biomarker for Individualized Benefit from Adjuvant Chemotherapy in Gastric Cancer: A Retrospective Cohort and Causal Machine Learning Study.” Truvace, 2026-08-24. /record/TRV-2026-0866 (accessed at citation time). sha256 16fc600c78b6ff31…
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