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Addressing guideline and policy changes during pragmatic clinical trials.

ABSTRACT: While conducting a set of large-scale multi-site pragmatic clinical trials involving high-impact public health issues such as end-stage renal disease, opioid use, and colorectal cancer, there were substantial changes to both policies and guidelines relevant to the trials. These external changes gave rise to unexpected challenges for the trials, including decisions regarding how to respond to new clinical practice guidelines, increased difficulty in implementing trial interventions, achieving separation between treatment groups, and differential responses across sites. In this article, we describe these challenges and the approaches used to address them. When deliberating appropriate action in the face of external changes during a pragmatic clinical trial, we recommend considering the well-being of the participants, clinical equipoise, and the strength and quality of the evidence associated with the change; involving those charged with data and safety monitoring; and where possible, planning for potential external changes as the trial is being designed. Any solution must balance the primary obligation to protect the well-being of participants with the secondary obligation to protect the integrity of the trial in order to gain meaningful answers to important public health questions.

SUBMITTER: Curtis LH

PROVIDER: S-EPMC6663617 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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Addressing guideline and policy changes during pragmatic clinical trials.

Curtis Lesley H LH Dember Laura M LM Vazquez Miguel A MA Murray David D DeBar Lynn L Staman Karen L KL Septimus Edward E Mor Vincent V Volandes Angelo A Wells Barbara L BL Huang Susan S SS Green Beverly B BB Coronado Gloria G Meyers Catherine M CM Tuzzio Leah L Hernandez Adrian F AF Sugarman Jeremy J

Clinical trials (London, England) 20190514 4

While conducting a set of large-scale multi-site pragmatic clinical trials involving high-impact public health issues such as end-stage renal disease, opioid use, and colorectal cancer, there were substantial changes to both policies and guidelines relevant to the trials. These external changes gave rise to unexpected challenges for the trials, including decisions regarding how to respond to new clinical practice guidelines, increased difficulty in implementing trial interventions, achieving sep ...[more]

PMID: 31084378

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Project description:BackgroundPragmatic trials provide the opportunity to study the effectiveness of health interventions to improve care in real-world settings. However, use of open-cohort designs with patients becoming eligible after randomization and reliance on electronic health records (EHRs) to identify participants may lead to a form of selection bias referred to as identification bias. This bias can occur when individuals identified as a result of the treatment group assignment are included in analyses.MethodsTo demonstrate the importance of identification bias and how it can be addressed, we consider a motivating case study, the PRimary care Opioid Use Disorders treatment (PROUD) Trial. PROUD is an ongoing pragmatic, cluster-randomized implementation trial in six health systems to evaluate a program for increasing medication treatment of opioid use disorders (OUDs). A main study objective is to evaluate whether the PROUD intervention decreases acute care utilization among patients with OUD (effectiveness aim). Identification bias is a particular concern, because OUD is underdiagnosed in the EHR at baseline, and because the intervention is expected to increase OUD diagnosis among current patients and attract new patients with OUD to the intervention site. We propose a framework for addressing this source of bias in the statistical design and analysis.ResultsThe statistical design sought to balance the competing goals of fully capturing intervention effects and mitigating identification bias, while maximizing power. For the primary analysis of the effectiveness aim, identification bias was avoided by defining the study sample using pre-randomization data (pre-trial modeling demonstrated that the optimal approach was to use individuals with a prior OUD diagnosis). To expand generalizability of study findings, secondary analyses were planned that also included patients newly diagnosed post-randomization, with analytic methods to account for identification bias.ConclusionAs more studies seek to leverage existing data sources, such as EHRs, to make clinical trials more affordable and generalizable and to apply novel open-cohort study designs, the potential for identification bias is likely to become increasingly common. This case study highlights how this bias can be addressed in the statistical study design and analysis.Trial registrationClinicalTrials.gov, NCT03407638. Registered on 23 January 2018.

Project description:ImportancePragmatic clinical trials that seek informed consent after randomization (ie, postrandomization consent) are increasingly used, but debate on ethics persists because control arm patients are not specifically informed about the trials and randomization occurs before consent for the trials. The public's attitude toward postrandomization consent trials is unknown, but the way the trials are described could bias people's views.ObjectivesTo assess the attitudes of the US general public toward postrandomization informed consent for pragmatic trials and to measure potential framing and other factors associated with those attitudes.Design, setting, and participantsAn online, 2 × 2 experimental survey (fielded between February 23 and April 3, 2018) portraying 4 scenarios of postrandomization informed consent (with prior broad consent for medical record use) was conducted. These scenarios included traditional randomized clinical trial language framing vs alternative framing in a high-stakes trial (ie, survival in leukemia) or low-stakes trial (ie, blood glucose level in diabetes). A total of 3793 individuals invited to participate were part of an existing panel representative of the US general public (GfK KnowledgePanel).Main outcomes and measuresThe proportion of participants who would recommend that an ethics review board approve a postrandomization consent pragmatic trial.ResultsA total of 2042 of 3739 invitees (54.6%) responded; after exclusion of 38 incomplete surveys, 2004 participants were included in the analysis. Of these, 997 (49.8%) were women, 1440 (71.9%) were white non-Hispanic, 199 (9.9%) were black non-Hispanic, and 233 (11.6%) were Hispanic. Mean (SD) age was 47.5 (17.4) years. Across scenarios, weighted data showed that 75.4% of the participants would recommend approval of the postrandomization consent pragmatic trial, 20.4% would probably not recommend approval, and 4.2% would definitely not recommend approval. Approval was not sensitive to framing language (traditional vs new framing in high-stakes scenario, 74.3% vs 76.8%, P = .40; in low-stakes scenario, 77.7% vs 72.9%, P = .10) or to the stakes (low vs high stakes in traditional framing, 77.7% vs 74.3%, P = .25; in new framing, 72.9% vs 76.8%, P = .18). Better understanding of the postrandomization consent design was associated with higher rate of approval (78.1% vs 65.0%, P = .002 for high-stakes scenario; 77.2% vs 64.9%, P = .004 for low-stakes scenario), especially among those with less education. However, opinions about personal involvement in the control arm were more cautious (range depending on scenario, 45.6%-59.7%) and sensitive to stakes but not to framing.Conclusions and relevanceThe public's generally high rate of approval of the ethics of postrandomization informed consent for pragmatic trial designs does not appear to be affected by whether postrandomization consent design is framed using traditional randomized clinical trial terminology, regardless of the stakes of the trial. Promoting better understanding of the design may increase its acceptance by the public.

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Addressing guideline and policy changes during pragmatic clinical trials.

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Addressing guideline and policy changes during pragmatic clinical trials.

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