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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/25695

Title: The impact of data errors on the outcome of randomized clinical trials
Authors: Buyse, Marc
Squifflet, Pierre
Coart, Elisabeth
Quinaux, Emmanuel
Punt, Cornelis J. A.
Saad, Everardo D.
Issue Date: 2017
Citation: CLINICAL TRIALS, 14(5), p. 499-506
Abstract: Background/aims: Considerable human and financial resources are typically spent to ensure that data collected for clinical trials are free from errors. We investigated the impact of random and systematic errors on the outcome of randomized clinical trials. Methods: We used individual patient data relating to response endpoints of interest in two published randomized clinical trials, one in ophthalmology and one in oncology. These randomized clinical trials enrolled 1186 patients with age-related macular degeneration and 736 patients with metastatic colorectal cancer. The ophthalmology trial tested the benefit of pegaptanib for the treatment of age-related macular degeneration and identified a statistically significant treatment benefit, whereas the oncology trial assessed the benefit of adding cetuximab to a regimen of capecitabine, oxaliplatin, and bevacizumab for the treatment of metastatic colorectal cancer and failed to identify a statistically significant treatment difference. We simulated trial results by adding errors that were independent of the treatment group (random errors) and errors that favored one of the treatment groups (systematic errors). We added such errors to the data for the response endpoint of interest for increasing proportions of randomly selected patients. Results: Random errors added to up to 50% of the cases produced only slightly inflated variance in the estimated treatment effect of both trials, with no qualitative change in the p-value. In contrast, systematic errors produced bias even for very small proportions of patients with added errors. Conclusion: A substantial amount of random errors is required before appreciable effects on the outcome of randomized clinical trials are noted. In contrast, even a small amount of systematic errors can severely bias the estimated treatment effects. Therefore, resources devoted to randomized clinical trials should be spent primarily on minimizing sources of systematic errors which can bias the analyses, rather than on random errors which result only in a small loss in power.
Notes: [Buyse, Marc] IDDI, 757 N Point St, San Francisco, CA 94109 USA. [Buyse, Marc] Hasselt Univ, Interuniv Inst Biostat & Stat Bioinformat IBioSta, Hasselt, Belgium. [Squifflet, Pierre; Coart, Elisabeth; Quinaux, Emmanuel; Saad, Everardo D.] IDDI, Louvain La Neuve, Belgium. [Punt, Cornelis J. A.] Univ Amsterdam, Acad Med Ctr, Dept Med Oncol, Amsterdam, Netherlands.
URI: http://hdl.handle.net/1942/25695
DOI: 10.1177/1740774517716158
ISI #: 000412535000012
ISSN: 1740-7745
Category: A1
Type: Journal Contribution
Validation: ecoom, 2018
Appears in Collections: Research publications

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