Interim analysis of clinical trials: Simulation studies of fractional Brownian motion

Interim clinical trial monitoring procedures were motivated by ethical and economic considerations. Classical Brownian motion (Bm) techniques for statistical monitoring of clinical trials were widely used. Conditional power argument and α-spending function based boundary crossing probabilities are popular statistical hypothesis testing procedures under the assumption of Brownian motion. However, it is not rare that the assumptions of Brownian motion are only partially met for trial data. Therefore, I used a more generalized form of stochastic process, called fractional Brownian motion (fBm), to model the test statistics. Fractional Brownian motion does not hold Markov property and future observations depend not only on the present observations but also on the past ones. In this dissertation, we simulated a wide range of fBm data, e.g., H = 0.5 (that is, classical Bm) vs. 0.5< H <1, with treatment effects vs. without treatment effects. Then the performance of conditional power and boundary-crossing based interim analyses were compared by assuming that the data follow Bm or fBm. Our simulation study suggested that the conditional power or boundaries under fBm assumptions are generally higher than those under Bm assumptions when H > 0.5 and also matches better with the empirical results. ^

Workers and respirators: What factors influence medical clearance? Experience in the petrochemical industry 2004--2008

This retrospective cohort study analyzed data from more than 2200 OSHA-mandated respirator medical evaluations performed between 2004 and 2008, with information initially obtained using an online questionnaire, to determine what factors influence medical clearance and the ability to safely wear respiratory protection in a large petrochemical company.^ The employees were mostly white males with a high school education, ranging in age from 25 to 60 years of age, who had been employed with the company an average of eight years. Their work was typically performed outdoors in a rural or offshore setting. Respirators were typically required for emergency response – escape or rescue only – and/or limited to less than four hours per month.^ Approximately 90% of the population achieved medical clearance by utilizing the online questionnaire. Of the remaining 10%, 66% were cleared after additional "hands-on" medical examination exam; 28% of the individuals' jobs were modified by their supervisor in order to not use a respirator, and 6% of the individuals (n=13) were excluded from wearing a respirator on the basis of the medical examination. The primary causes for exclusion from respirator use were cardiovascular (37.5%) and respiratory (31.3%) issues, followed by psychological (18.8%) and musculoskeletal (12.5%) concerns. Ultimately, over 99% of workers evaluated under this system were found capable of using respiratory protection safely. This questionnaire has proven to be an excellent health screening tool capable of initiating early detection and further investigation of potentially serious medical conditions within a large and diverse population in multiple locations. ^