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Risk factors for early mortality among patients with gastrointestinal malignancy in the C-CAT database

  • 0Department of Gastroenterology, Fukushima Medical University School of Medicine, 1 Hikarigaoka, Fukushima, 960-1295, Japan. subaru@fmu.ac.jp.
International Journal of Clinical Oncology +

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June 19, 2025

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June 19, 2025

View abstract on PubMed

Summary

This summary is machine-generated.

A new model predicts early mortality in gastrointestinal cancer patients undergoing comprehensive genomic profiling (CGP). This tool helps identify high-risk individuals for better treatment decisions and timing of CGP.

Area Of Science

  • Oncology
  • Genomics
  • Precision Medicine

Background

  • Comprehensive genomic profiling (CGP) is crucial for precision medicine in cancer treatment.
  • Early mortality within 90 days of CGP submission is a significant concern for patients with gastrointestinal (GI) malignancies.
  • Identifying risk factors for early mortality is essential for optimizing patient care.

Purpose Of The Study

  • To identify independent risk factors associated with early mortality in GI cancer patients after CGP.
  • To develop and validate a predictive model for early mortality in this patient population.
  • To assess the model's utility in stratifying patients for prognostic purposes.

Main Methods

  • Retrospective analysis of 18,657 GI cancer patients from the Japanese C-CAT database.
  • Definition of early mortality as death within 90 days of CGP submission.
  • Construction and validation of a weighted scoring prediction model based on clinical factors, including cancer type, performance status, and disease status.

Main Results

  • The overall early mortality rate was 14.2%.
  • Key predictors of early mortality included pancreatic/biliary cancer type, ECOG-PS ≥2, metastases, disease progression, and male sex.
  • The prediction model effectively stratified patients into risk groups (low, intermediate, high, very high) with moderate discrimination (C-statistic: 0.70-0.73) and distinct survival outcomes.

Conclusions

  • The developed prediction model accurately stratifies GI cancer patients based on early mortality risk post-CGP.
  • This tool aids in better patient selection for CGP and informs decisions regarding the optimal timing of the procedure.
  • A web-based application is available for predicting early mortality risk: https://mortality-within-90days-cgp.shinyapps.io/mortality_treatment_20250130/.

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