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2022 World Conference on Lung Cancer (ePosters)
EP01.05-009. Simulation-Based Sample Size Estimati ...
EP01.05-009. Simulation-Based Sample Size Estimation for an Early Detection of Lung Cancer Clinical Utility Trial in Indeterminate Pulmonary Nodules
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In this document, the authors describe a simulation-based approach to estimate the sample size for a randomized Phase IIb trial evaluating the clinical utility of a combined risk prediction score in the early detection of lung cancer in patients with indeterminate pulmonary nodules. The study aims to improve risk stratification and reduce unnecessary invasive procedures. The authors used data from two US clinical sites to design a site-stratified two-arm trial and assumed that improvements in clinical utility under the combined risk prediction score would result from correct reclassification compared to the Mayo risk model alone.<br /><br />The authors performed 1000 simulations, varying the number of patients with intermediate risk IPN (500-1000) and randomly assigning them to the standard of care or the combined risk prediction score. They randomly generated numbers of patients with lung cancer or benign disease, assuming a 33% prevalence of lung cancer. Time to diagnosis and invasive procedures were compared between the two groups. The authors determined that a total of at least 560 patients is needed to achieve a minimum of 80% power for each utility outcome based on the observed site-specific practice patterns.<br /><br />The authors emphasize that simulation-based approaches offer flexibility in evaluating differences in disease prevalence, practice patterns, and enrollment across multiple sites. This approach can be customized based on site-specific preliminary observational data and can be scaled up to any arbitrary number of sites and outcomes. They highlight the limitations of standard sample size estimation methods, which may not adequately account for testing multiple outcomes across sites with varying practices.<br /><br />In conclusion, the authors propose a simulation-based sample size estimation approach for a clinical utility trial in indeterminate pulmonary nodules. They demonstrate how this approach can be used to estimate the sample size needed to achieve the desired statistical power, taking into account site-specific practice patterns. This approach provides greater flexibility compared to standard methods and can be applied to evaluate the clinical utility of biomarkers in similar contexts.
Asset Subtitle
Michael Nolan Kammer
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Speaker
Michael Nolan Kammer
Topic
Early Detection and Screening - Pulmonary Nodule
Keywords
simulation-based approach
sample size estimation
randomized Phase IIb trial
clinical utility
lung cancer
indeterminate pulmonary nodules
risk prediction score
risk stratification
invasive procedures
site-specific practice patterns
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