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Updated: Jul 28, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
A simple stratification factor prognostic for survival in advanced cancer: the good/bad/uncertain index
J A Sloan1, C L Loprinzi, J A Laurine
1Mayo Clinic and Mayo Foundation, Rochester, MN 55905, USA. jsloan@mayo.edu
Purpose:
This article summarizes the third step of a research program to identify variables that supplement the predictive power of the the Eastern Cooperative Oncology Group (ECOG) performance status (PS) for survival. The objective was to produce a simple, practical, stratification factor for phase III oncology clinical trials involving patients with advanced malignant disease.
Patients And Methods:
A questionnaire was administered to 729 patients with metastatic colorectal or lung cancers. Patients provided a Karnofsky index and appetite rating while physicians provided a survival estimate and the ECOG-PS. Scores for each item were categorized as having a positive, neutral, or negative indication for survival. A patient was classified as having a relatively good prognosis if three or more of the four items showed a positive indication, a bad prognosis if three or more items were negative, and an uncertain prognosis otherwise (Good/Bad/Uncertain [GBU] index).
Results:
The GBU index improved on the prognostic power of a Cox model quartile index and PS alone and increased the accuracy of survival classification estimates by 5% to 10% more than ECOG-PS alone. For patients with PS of 0 or 1, significant survival patterns exist between GBU groups (P=.002 and.0001, respectively).
Conclusion:
The GBU index may be recommended as a supplementary stratification factor for certain future phase III trials in metastatic lung or colorectal cancer where patient heterogeneity is a particular concern. The GBU represents a relatively modest increase to the cost and patient burden of a clinical trial given the additional control that is achieved over the potentially confounding concomitant to the treatment variable.
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