Effectiveness of Aspirin in COPD: Biases in the Observational Studies.

Several observational studies report decreased incidence of mortality and of exacerbations with aspirin use in patients with chronic obstructive pulmonary disease (COPD), with calls for a large randomized trial. Aspirin does have local and systemic pulmonary mechanisms of action that could make this drug beneficial in the treatment of COPD. However, the potential for biases in the observational studies has not been examined. We searched the literature for all observational studies reporting on the effect of aspirin in COPD patients on exacerbation and mortality. We reviewed the studies for the presence of time-related and other biases. We identified eight observational studies reporting an overall reduction in all-cause mortality or exacerbation with aspirin use of 21% (pooled rate ratio (RR) 0.79; 95% CI 0.71-0.86). We found two studies affected by immortal time bias (pooled RR 0.81; 95% CI 0.74-0.89), three studies affected by collider-stratification bias (pooled RR 0.66; 95% CI 0.55-0.79) and three that involved some exposure misclassification (pooled RR 0.85; 95% CI 0.78-0.92). Moreover, while adjusting for cardiovascular factors, six of the eight studies did not adjust for important markers of COPD severity and thus remain susceptible to confounding bias. In conclusion, all observational studies reporting on the effectiveness of aspirin on major outcomes of COPD are affected by biases known to exaggerate the effectiveness of a drug. As these studies cannot be used to support a beneficial effect for aspirin in COPD, it would be premature to consider a randomized trial to investigate this question until methodologically rigorous studies are available.

A Versatile and Scalable Platform That Streamlines Data Collection for Patient-Centered Studies: Usability and Feasibility Study.

BACKGROUND: The Food and Drug Administration Center for Biologics Evaluation and Research (CBER) established the Biologics Effectiveness and Safety (BEST) Initiative with several objectives, including the expansion and enhancement of CBER's access to fit-for-purpose data sources, analytics, tools, and infrastructures to improve the understanding of patient experiences with conditions related to CBER-regulated products. Owing to existing challenges in data collection, especially for rare disease research, CBER recognized the need for a comprehensive platform where study coordinators can engage with study participants and design and deploy studies while patients or caregivers could enroll, consent, and securely participate as well. OBJECTIVE: This study aimed to increase awareness and describe the design, development, and novelty of the Survey of Health and Patient Experience (SHAPE) platform, its functionality and application, quality improvement efforts, open-source availability, and plans for enhancement. METHODS: SHAPE is hosted in a Google Cloud environment and comprises 3 parts: the administrator application, participant app, and application programming interface. The administrator can build a study comprising a set of questionnaires and self-report entries through the app. Once the study is deployed, the participant can access the app, consent to the study, and complete its components. To build SHAPE to be scalable and flexible, we leveraged the open-source software development kit, Ionic Framework. This enabled the building and deploying of apps across platforms, including iOS, Android, and progressive web applications, from a single codebase by using standardized web technologies. SHAPE has been integrated with a leading Health Level 7 (HL7®) Fast Healthcare Interoperability Resources (FHIR®) application programming interface platform, 1upHealth, which allows participants to consent to 1-time data pull of their electronic health records. We used an agile-based process that engaged multiple stakeholders in SHAPE's design and development. RESULTS: SHAPE allows study coordinators to plan, develop, and deploy questionnaires to obtain important end points directly from patients or caregivers. Electronic health record integration enables access to patient health records, which can validate and enhance the accuracy of data-capture methods. The administrator can then download the study data into HL7® FHIR®-formatted JSON files. In this paper, we illustrate how study coordinators can use SHAPE to design patient-centered studies. We demonstrate its broad applicability through a hypothetical type 1 diabetes cohort study and an ongoing pilot study on metachromatic leukodystrophy to implement best practices for designing a regulatory-grade natural history study for rare diseases. CONCLUSIONS: SHAPE is an intuitive and comprehensive data-collection tool for a variety of clinical studies. Further customization of this versatile and scalable platform allows for multiple use cases. SHAPE can capture patient perspectives and clinical data, thereby providing regulators, clinicians, researchers, and patient advocacy organizations with data to inform drug development and improve patient outcomes.