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ACCENT-based web calculators to predict recurrence and overall survival in stage III colon cancer
Lindsay A Renfro1, Axel Grothey2, Yuan Xue2
1Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN (LAR, DJS); Department of Oncology, Mayo Clinic, Rochester, MN (AMG, SRA, CLL); Department of Statistics, University of Virginia, Charlottesville, VA (YX); Gastrointestinal Oncology Service, Memorial Sloan-Kettering Cancer Center, New York, NY (LBS); Hôpital Saint Antoine, Paris, France; Pierre and Marie Curie University, Paris, France (TA); Leeds Institute of Cancer and Pathology, University of Leeds and St. James's University Hospital, Leeds Cancer Research UK Centre, UK (CT); Oncology Unit, Ospedale Giovanni XXIII, Bergamo, Italy (RL); Division of Hematology and Oncology, University of Florida, Gainesville, FL (CJA); National Surgical Adjuvant Breast and Bowel Project Biostatistical Center, Pittsburgh, PA (GY). renfro.lindsay@mayo.edu.
Background:
Current prognostic tools in colon cancer use relatively few patient characteristics. We constructed and validated clinical calculators for overall survival (OS) and time to recurrence (TTR) for stage III colon cancer and compared their performance against an existing tool (Numeracy) and American Joint Committee on Cancer (AJCC) version 7 staging.
Methods:
Data from 15936 stage III patients accrued to phase III clinical trials since 1989 were used to construct Cox models for TTR and OS. Variables included age, sex, race, body mass index, performance status, tumor grade, tumor stage, ratio of positive lymph nodes to nodes examined, number and location of primary tumors, and adjuvant treatment (fluoropyrimidine single agent or in combination). Missing data were imputed, and final models internally validated for optimism-corrected calibration and discrimination and compared with AJCC. External validation and comparisons against Numeracy were performed using stage III patients from NSABP trial C-08. All statistical tests were two-sided.
Results:
All variables were statistically and clinically significant for OS prediction, while age and race did not predict TTR. No meaningful interactions existed. Models for OS and TTR were well calibrated and associated with C-indices of 0.66 and 0.65, respectively, compared with C-indices of 0.58 and 0.59 for AJCC. These tools, available online, better predicted patient outcomes than Numeracy, both overall and within patient subgroups, in external validation.
Conclusions:
The proposed ACCENT calculators are internally and externally valid, better discriminate patient risk than AJCC version 7 staging, and better predict patient outcomes than Numeracy. These tools have replaced Numeracy for online clinical use and will aid prognostication and patient/physician communication.
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