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Clinical Calculator for Predicting Freedom From Recurrence After Resection of Stage I-III Colon Cancer in Patients
Ayyuce Begum Bektas1, Lynn Hakki2, Asama Khan2
1Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY.
JCO Clinical Cancer Informatics
|August 9, 2024
Summary
A new nomogram model accurately predicts recurrence-free survival in patients with microsatellite instability (MSI) colon cancer. This tool identifies high-risk individuals, aiding surveillance and clinical trial design for better outcomes.
Area of Science:
- Oncology
- Gastroenterology
- Cancer Research
Background:
- Patients with nonmetastatic microsatellite instability (MSI) colon cancer generally have a favorable prognosis.
- However, specific high-risk subgroups within this population require better identification for tailored management.
Purpose of the Study:
- To develop and validate a nomogram model for predicting freedom from recurrence (FFR) in patients with resected MSI colon cancer.
- To create a clinical calculator to identify patients at high risk of recurrence.
Main Methods:
- Retrospective analysis of data from 384 patients (training cohort) and 164 patients (validation cohort) with resected stage I-III MSI colon cancer.
- Multivariable analysis identified significant predictors of recurrence, including T category and lymph node status.
- Model performance was assessed using the concordance index (CI).
Main Results:
- The nomogram model demonstrated robust predictive accuracy with a CI of 0.812 in the training cohort and 0.744 in the validation cohort.
- The model outperformed the AJCC staging schema (CI 0.759) in the training cohort.
- Advanced T category and number of positive lymph nodes were significant predictors of recurrence.
Conclusions:
- The developed nomogram effectively identifies patients with MSI colon cancer at high risk for recurrence.
- This tool can inform personalized surveillance strategies and assist in the design of clinical trials for novel adjuvant therapies.
- Accurate risk stratification is crucial for optimizing treatment and follow-up in MSI colon cancer.

