Lindsay A Renfro1, Axel M Grothey2, James Paul3, Irene Floriani4, Franck Bonnetain5, Donna Niedzwiecki6, Takeharu Yamanaka7, Ioannis Souglakos8, Greg Yothers9, Daniel J Sargent1. 1. Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN, USA. 2. Department of Oncology, Mayo Clinic, Rochester, MN, USA. 3. Cancer Research UK, Beatson West of Scotland Cancer Centre, Institute of Cancer Sciences, University of Glasgow, Glasgow, Scotland. 4. Department of Oncology, IRCCS Instituto di RicercheFarmacologiche Mario Negri, Milan, Italy. 5. Methodological and Quality of Life Unit in Oncology, University Hospital, Besançon, France. 6. Department of Biostatistics, Duke University, Durham, NC, USA. 7. Department of Biostatistics, National Cancer Center, Tokyo, Japan. 8. Division of Internal Medicine, University of Crete, Crete, Greece. 9. National Surgical Adjuvant Breast and Bowel Project Biostatistical Center, Pittsburgh, PA, USA.
Abstract
PURPOSE: Clinical trials are expensive and lengthy, where success of a given trial depends on observing a prospectively defined number of patient events required to answer the clinical question. The point at which this analysis time occurs depends on both patient accrual and primary event rates, which typically vary throughout the trial's duration. We demonstrate real-time analysis date projections using data from a collection of six clinical trials that are part of the IDEA collaboration, an international preplanned pooling of data from six trials testing the duration of adjuvant chemotherapy in stage III colon cancer, and we additionally consider the hypothetical impact of one trial's early termination of follow-up. PATIENTS AND METHODS: In the absence of outcome data from IDEA, monthly accrual rates for each of the six IDEA trials were used to project subsequent trial-specific accrual, while historical data from similar Adjuvant Colon Cancer Endpoints (ACCENT) Group trials were used to construct a parametric model for IDEA's primary endpoint, disease-free survival, under the same treatment regimen. With this information and using the planned total accrual from each IDEA trial protocol, individual patient accrual and event dates were simulated and the overall IDEA interim and final analysis times projected. Projections were then compared with actual (previously undisclosed) trial-specific event totals at a recent census time for validation. The change in projected final analysis date assuming early termination of follow-up for one IDEA trial was also calculated. RESULTS: Trial-specific predicted event totals were close to the actual number of events per trial for the recent census date at which the number of events per trial was known, with the overall IDEA projected number of events only off by eight patients. Potential early termination of follow-up by one IDEA trial was estimated to postpone the overall IDEA final analysis date by 9 months. CONCLUSIONS: Real-time projection of the final analysis time during a trial, or the overall analysis time during a trial collaborative such as IDEA, has practical implications for trial feasibility when these projections are translated into additional time and resources required.
PURPOSE: Clinical trials are expensive and lengthy, where success of a given trial depends on observing a prospectively defined number of patient events required to answer the clinical question. The point at which this analysis time occurs depends on both patient accrual and primary event rates, which typically vary throughout the trial's duration. We demonstrate real-time analysis date projections using data from a collection of six clinical trials that are part of the IDEA collaboration, an international preplanned pooling of data from six trials testing the duration of adjuvant chemotherapy in stage III colon cancer, and we additionally consider the hypothetical impact of one trial's early termination of follow-up. PATIENTS AND METHODS: In the absence of outcome data from IDEA, monthly accrual rates for each of the six IDEA trials were used to project subsequent trial-specific accrual, while historical data from similar Adjuvant Colon Cancer Endpoints (ACCENT) Group trials were used to construct a parametric model for IDEA's primary endpoint, disease-free survival, under the same treatment regimen. With this information and using the planned total accrual from each IDEA trial protocol, individual patient accrual and event dates were simulated and the overall IDEA interim and final analysis times projected. Projections were then compared with actual (previously undisclosed) trial-specific event totals at a recent census time for validation. The change in projected final analysis date assuming early termination of follow-up for one IDEA trial was also calculated. RESULTS: Trial-specific predicted event totals were close to the actual number of events per trial for the recent census date at which the number of events per trial was known, with the overall IDEA projected number of events only off by eight patients. Potential early termination of follow-up by one IDEA trial was estimated to postpone the overall IDEA final analysis date by 9 months. CONCLUSIONS: Real-time projection of the final analysis time during a trial, or the overall analysis time during a trial collaborative such as IDEA, has practical implications for trial feasibility when these projections are translated into additional time and resources required.
Entities:
Keywords:
Adjuvant therapy; Colon cancer; Duration of therapy; Meta-analysis
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