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This quantitative study assessed the association of the design methods used for early phase oncology studies (adaptive versus traditional) and the outcome of late stage clinical trials. Differences by cancer type and by drug classification were also assessed. The theoretical and conceptual frameworks used were the general systems theory and the design and evaluation of complex interventions, respectively. Units of analysis were individual oncology studies in the ClinicalTrials.gov database and Bayesian logistic modeling was applied on a random sample of 381 studies initiated after November 1999 to December 2016. When assessing study design and outcome, there were lower odds of a positive outcome when adaptive methods were used though this association was not statistically significant (OR [95% highest posterior density (HPD)]:0.66 [0.20, 1.21]). Among the different drug types, using adaptive compared to traditional methods was associated with significantly higher odds of a positive outcome for taxanes, OR: 2.75, 95% HPD: 1.01, 5.16) and other, OR: 3.23, 95% HPD: 1.58, 5.46) but no association among studies of monoclonal antibodies or protein kinase inhibitors. Also, there were no significant associations between early phase study design and outcome in late phase studies by cancer type (lung, breast, other). Further research should be conducted using all completed oncology clinical trials in the database to more precisely determine the relationship between adaptive study design in early phase oncology studies and outcomes in late stage studies. Social change can occur through increased uptake of adaptive design methods, which may lead to more efficacious cancer treatment options.