Prevalence and implications of significance testing for baseline covariate imbalance in randomised cancer clinical trials: The Table 1 Fallacy
Year: 2023
Type: article
Abstract: BACKGROUND: The 'Table 1 Fallacy' refers to the unsound use of significance testing for comparing the distributions of baseline variables between randomised groups to draw erroneous conclusions about balance or imbalance. We performed a cross-sectional study of the Table 1 Fallacy in phase III oncology trials. METHODS: From ClinicalTrials.gov, 1877 randomised trials were screened. Multivariable logistic regressions evaluated predictors of the Table 1 Fallacy. RESULTS: A total of 765 randomised controlled trials involving 553,405 patients were analysed. The Table 1 Fallacy was observed in 25% of trials (188 of 765), with 3% of comparisons deemed significant (59 of 2353), approximating the typical 5% type I error assertion probability. Application of trial-level multiplicity corrections reduced the rate of significant findings to 0.3% (six of 2345 tests). Factors associated with lower odds of the Table 1 Fallacy included industry sponsorship (adjusted odds ratio [aOR] 0.29, 95% confidence interval [CI] 0.18-0.47; multiplicity-corrected P < 0.0001), larger trial size (≥795 versus <280 patients; aOR 0.32, 95% CI 0.19-0.53; multiplicity-corrected P = 0.0008), and publication in a European versus American journal (aOR 0.06, 95% CI 0.03-0.13; multiplicity-corrected P < 0.0001). CONCLUSIONS: This study highlights the persistence of the Table 1 Fallacy in contemporary oncology randomised controlled trials, with one of every four trials testing for baseline differences after randomisation. Significance testing is a suboptimal method for identifying unsound randomisation procedures and may encourage misleading inferences. Journal-level enforcement is a possible strategy to help mitigate this fallacy.
Source: European Journal of Cancer
Institutions: The University of Texas MD Anderson Cancer Center, University of North Carolina at Chapel Hill, insitro, inc. (United States), Stanford Medicine, Stanford University, The University of Texas Southwestern Medical Center, Memorial Sloan Kettering Cancer Center, The University of Texas Health Science Center at Houston, Johns Hopkins University, Johns Hopkins Medicine, Goethe University Frankfurt, German Cancer Research Center, Frankfurt Cancer Institute, Deutsches Konsortium für Translationale Krebsforschung, Rabin Medical Center
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,800
Funders: Andrew Sabin Family Foundation, Fund for Innovation in Cancer Informatics, National Institutes of Health, University of Texas MD Anderson Cancer Center, National Cancer Institute, National Institute of Biomedical Imaging and Bioengineering, National Institute of Dental and Craniofacial Research
OpenAlex ID: W4386947352
