CHAPTER 4 200 therapeutics is increasing trial management complexity for which strategies such as simplifying patient enrolment effort, reducing variables on case report forms (averaging at 165 pages in 2012) and frequency of monitoring and patient visits have been proposed.47,76,79 The notion of expanding generalizability is often associated with larger trials. However, relaxing trial entry criteria also presents advantages in reduced recruitment complexity, accelerated participant enrolment and reduction in recruitment cost per patient of up to 21%.80 In a cost analysis of phase III cardiovascular trials, Eisenstein and colleagues demonstrated 40% total cost savings with fewer CRF pages, monitoring and site visits while maintaining the same number of patients and sites.76 Concerns with increased patient heterogeneity, non-cardiovascular competing risks or low event rates can be understood and mitigated by data-driven optimization at the pre-design stage. Clinical trial simulation is an established practice among pharmaceutical companies to traditionally model design variability such as dose, schedule, study size and risk of protocol deviations.81,82 Existing expertise can be used to simulate What-if scenarios of more inclusive enrolment criteria on expected hazard ratios, trial accrual and follow-up duration. Examples are seen in cancer trials whereby change in efficacy endpoints were simulated in a trial setting with and without addition of patients with low performance status.83 Additionally, machine learning approaches provide opportunities for optimizing balance between eligibility criteria, outcome event rate and projected generalizability of results. The reality remains that clinical evidence that has low generalizability impacts implementation down the pipeline be it from a regulatory, practicing clinician, payer or patient perspective.47 The American Society for Clinical Oncology, together with Friends of Cancer Research and FDA issued working group recommendations focusing on broadening four criteria topics that commonly lead to exclusion in cancer trials: brain metastases, minimum participant age (to include pediatric cohorts), HIV infection and organ dysfunction and prior or concurrent malignancy.84,85 Though primarily focused on the US setting86, public-private collaborations like the Heart Failure Collaboratory87 play influential roles to bring together relevant stakeholders in open discussions and consensus for more inclusionary trial enrolment practices. A key long-term goal of the Collaboratory is representative populations; with specific objectives comprising standards for
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