PRAGMATIC Study Designs: Elderly Cancer Trials Karla V. Ballman Alliance Cancer in the Elderly Statistician Mayo Clinic May 2015

What is a “Pragmatic” Trial? Concept introduced by Schwartz and Lellouch, 1967 Contrast between “explanatory” and “pragmatic” trials explanatory trial purpose: answer a scientific question pragmatic trial purpose: which treatment to use

Key Differences: Question Explanatory Can the intervention work? Pragmatic Does the intervention work when used in normal practice?

Key Differences: Setting Explanatory Well resourced Ideal setting Pragmatic Normal practice

Key Differences: Participants Explanatory Highly selected Exclude many poorly adherent patients those with conditions that might dilute the effect Homogeneous population Pragmatic Little or no selection beyond the clinical indication of interest Heterogeneous

Key Differences: Intervention Explanatory Strictly enforced Adherence is monitored closely Pragmatic Applied flexibly as would be in normal practice

Key Differences: Outcomes Explanatory Often short-term surrogates Process measurements Pragmatic Directly relevant to participants to funders to communities to healthcare practitioners

Key Differences: Relevance to Practice Explanatory Indirect: little effort made to match the design of the trial to the decision making needs of those in the usual setting in which the intervention will be implemented Pragmatic Direct: the trial is designed to meet the needs of those making decisions about treatment options in the setting in which the intervention will be implemented

Large Simple Trials: Goals Idea started in 1980s Goals address important health care questions identify small but worthwhile improvement in major outcomes in common diseases confirm conclusions from meta-analyses of smaller trials

Large Simple Trials: Characteristics Eligibility based on “uncertainty principle” Minimal restrictions on care other than assigned treatment Rigorous attention to control of bias by focusing on control of systematic errors rather than random errors Reliable assessment of effect of treatment in “real world” setting Limited data collection

Cluster Randomized Trials Randomization of units instead of individual patients Examples randomization of physicians to a particular intervention randomization of sites to different drug regimens Design consideration: statistical power depends more on number of clusters than on number of individuals per cluster

Divergent Conclusions Why? Setting highly controlled administration; specialized centers (traditional randomized trial) real practice Outcomes biomedical surrogate outcome measured health gain

Key Characteristics of Pragmatic Trials Focused on questions from and important to stakeholders Conducted in everyday clinical practice environment (multiple and varied settings) rather than in “parallel research universe” Intervention tailored to needs of setting, intended for sustained real-world practice, and compared to real world alternatives Representative populations / few exclusion criteria – enrolled patients are those identified as having greatest need Multiple outcomes important to decision and policy makers evaluation based on clinical and administrative data that are highly relevant (e.g., patient reported outcomes already clinically collected, pattern of health service utilization including medication use, and health care costs)

Challenges Improve efficiency of patient recruitment Improve the reliability and validity of clinical information in the EMRs More actively engage clinicians and implement reward systems that value their participation in pragmatic clinical trials Decrease regulatory barriers for conducting low- risk pragmatic trials

Discussion Is there a role for pragmatic trials within the older cancer population?