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BACKGROUND: The ACCENT database, with individual patient data for 20 898 patients from 18 colon cancer clinical trials, was used to support Food and Drug Administration (FDA) approval of 3-year disease-free survival as a surrogate for 5-year overall survival. We hypothesised substantive differences in survival estimation with log-normal modelling rather than standard Kaplan-Meier or Cox approaches. METHODS: Time to relapse, disease-free survival, and overall survival were estimated using Kaplan-Meier, Cox, and log-normal approaches for male subjects aged 60-65 years, with stage III colon cancer, treated with 5-fluorouracil-based chemotherapy regimens (with 5FU), or with surgery alone (without 5FU). RESULTS: Absolute differences between Cox and log-normal estimates with (without) 5FU varied by end point. The log-normal model had 5.8 (6.3)% higher estimated 3-year time to relapse than the Cox model; 4.8 (5.1)% higher 3-year disease-free survival; and 3.2 (2.2)% higher 5-year overall survival. Model checking indicated greater data support for the log-normal than the Cox model, with Cox and Kaplan-Meier estimates being more similar. All three model types indicate consistent evidence of treatment benefit on both 3-year disease-free survival and 5-year overall survival; patients allocated to 5FU had 5.0-6.7% higher 3-year disease-free survival and 5.3-6.8% higher 5-year overall survival. CONCLUSION: Substantive absolute differences between estimates of 3-year disease-free survival and 5-year overall survival with log-normal and Cox models were large enough to be clinically relevant, and warrant further consideration.

Original publication

DOI

10.1038/bjc.2013.34

Type

Journal article

Journal

Br J Cancer

Publication Date

05/03/2013

Volume

108

Pages

784 - 790

Keywords

Aged, Clinical Trials, Phase III as Topic, Colonic Neoplasms, Combined Modality Therapy, Databases as Topic, Disease-Free Survival, Endpoint Determination, Fluorouracil, Humans, Kaplan-Meier Estimate, Male, Middle Aged, Models, Statistical, Proportional Hazards Models, Randomized Controlled Trials as Topic