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Increasing emphasis on the use of real-world evidence (RWE) to support clinical policy and regulatory decision-making has led to a proliferation of guidance, advice, and frameworks from regulatory agencies, academia, professional societies, and industry. A broad spectrum of studies use real-world data (RWD) to produce RWE, ranging from randomized trials with outcomes assessed using RWD to fully observational studies. Yet, many proposals for generating RWE lack sufficient detail, and many analyses of RWD suffer from implausible assumptions, other methodological flaws, or inappropriate interpretations. The Causal Roadmap is an explicit, itemized, iterative process that guides investigators to prespecify study design and analysis plans; it addresses a wide range of guidance within a single framework. By supporting the transparent evaluation of causal assumptions and facilitating objective comparisons of design and analysis choices based on prespecified criteria, the Roadmap can help investigators to evaluate the quality of evidence that a given study is likely to produce, specify a study to generate high-quality RWE, and communicate effectively with regulatory agencies and other stakeholders. This paper aims to disseminate and extend the Causal Roadmap framework for use by clinical and translational researchers; three companion papers demonstrate applications of the Causal Roadmap for specific use cases.

Abstract Randomized controlled trials (RCTs) continue to be the basis for essential evidence regarding the efficacy of interventions such as cancer therapies. Limitations associated with RCT designs, including selective study populations, strict treatment regimens, and being time-limited, mean they do not provide complete information about an intervention’s safety or the applicability of the trial’s results to a wider range of patients seen in real-world clinical practice. For example, recent data from Alberta showed that almost 40% of patients in the province’s cancer registry would be trial-ineligible per common exclusion criteria. Real-world evidence (RWE) offers an opportunity to complement the RCT evidence base with this kind of information about safety and about use in wider patient populations. It is also increasingly recognized for being able to provide information about an intervention’s effectiveness and is considered by regulators as an important component of the evidence base in drug approvals. Here, we examine the limitations of RCTs in oncology research, review the different types of RWE available in this area, and discuss the strengths and limitations of RWE for complementing RCT oncology data. There is a growing awareness of the importance of real-world evidence (RWE) in understanding its application to management and informing treatment choices in oncology. This article provides an overview of the strengths and limitations of randomized controlled trial and how it complements RCT oncology data, providing oncologists with additional information to make optimal clinical decisions for their patients.

Ideally, real-world data (RWD) collected to generate real-world evidence (RWE) should lead to impact on the care and health of real-world patients. Deriving from care in which clinicians and patients try various treatments to inform therapeutic decisions, N-of-1 trials bring scientific methods to real-world practice. These single-patient crossover trials generate RWD and RWE by giving individual patients various treatments in a double-blinded way in sequential periods to determine the most effective treatment for a given patient. This approach is most often used for patients with chronic, relatively stable conditions that provide the opportunity to make comparisons over multiple treatment periods, termed Type 1 N-of-1 trials. These are most helpful when there is heterogeneity of treatment effects among patients and no a best option. N-of-1 trials also can be done for patients with rare diseases, potentially testing only one treatment, to generate evidence for personalized treatment decisions, designated as Type 2 N-of-1 trials. With both types, in addition to informing individual's treatments, when uniform protocols are used for multiple patients with the same condition, the data collected in the individual N-of-1 trials can be aggregated to provide RWD/RWE to inform more general use of the treatments. Thereby, N-of-1 trials can provide RWE for the care of individuals and for populations. To fulfill this potential, we believe N-of-1 trials should be built into our current healthcare ecosystem. To this end, we are building the needed infrastructure and engaging the stakeholders who should receive value from this approach.

Real-world data privacy is a complex yet underexplored topic. To date, few studies have reported adult perspectives around real-world data privacy and willingness to share real-world data with researchers. Relevant survey items were identified in the literature, adapted and pilot tested among a small convenience sample, and finalized for distribution. The survey was distributed electronically in April 2021 among adults (≥18 years of age) registered in ResearchMatch (www.researchmatch.org). Microsoft Excel was used to assess descriptive statistics across demographical items and four privacy-related items. Of 402 completed responses received, half of respondents (∼50%) expressed willingness to share their prescription history data and music streaming data with researchers and unwillingness to share real-world data from several other sources. Most (53-93%) of participants expressed concern with five statements reflecting the sharing and use of their digital data online. Most participants (71-75%) agreed with four statements focused on individual measures taken to protect their personal privacy and disagreed (77-85%) with two statements centered on not being concerned about sharing or 3 party access to their personal data online. Our observations indicate an important yet unmet need to further explore and address real-world data privacy concerns among US adults engaging as prospective research participants.

Real-world data, such as administrative claims and electronic health records, are increasingly used for safety monitoring and to help guide regulatory decision-making. In these settings, it is important to document analytic decisions transparently and objectively to assess and ensure that analyses meet their intended goals. The Causal Roadmap is an established framework that can guide and document analytic decisions through each step of the analytic pipeline, which will help investigators generate high-quality real-world evidence. In this paper, we illustrate the utility of the Causal Roadmap using two case studies previously led by workgroups sponsored by the Sentinel Initiative - a program for actively monitoring the safety of regulated medical products. Each case example focuses on different aspects of the analytic pipeline for drug safety monitoring. The first case study shows how the Causal Roadmap encourages transparency, reproducibility, and objective decision-making for causal analyses. The second case study highlights how this framework can guide analytic decisions beyond inference on causal parameters, improving outcome ascertainment in clinical phenotyping. These examples provide a structured framework for implementing the Causal Roadmap in safety surveillance and guide transparent, reproducible, and objective analysis.

Evidence from medication use in the real world setting can help to extrapolate and/or augment data obtained in randomized controlled trials and establishes a broad picture of a medication's place in everyday clinical practice. By supplementing and complementing safety and efficacy data obtained in a narrowly defined (and often optimized) patient population in the clinical trial setting, real world evidence (RWE) may provide stakeholders with valuable information about the safety and effectiveness of a medication in large, heterogeneous populations. RWE is emerging as a credible information source; however, there is scope for enhancements to real world data (RWD) sources by understanding their complexities and applying the most appropriate analytical tools in order to extract relevant information. In addition to providing information for clinicians, RWE has the potential to meet the burden of evidence for regulatory considerations and may be used in approval of new indications for medications. Further understanding of RWD collection and analysis is needed if RWE is to achieve its full potential.

Introduction People with type 2 diabetes have increased risk of dementia. Glucagon‐like peptide‐1 (GLP‐1) receptor agonists (RAs) are among the promising therapies for repurposing as a treatment for Alzheimer's disease; a key unanswered question is whether they reduce dementia incidence in people with type 2 diabetes. Methods We assessed exposure to GLP‐1 RAs in patients with type 2 diabetes and subsequent diagnosis of dementia in two large data sources with long‐term follow‐up: pooled data from three randomized double‐blind placebo‐controlled cardiovascular outcome trials (15,820 patients) and a nationwide Danish registry‐based cohort (120,054 patients). Results Dementia rate was lower both in patients randomized to GLP‐1 RAs versus placebo (hazard ratio [HR]: 0.47 (95% confidence interval [CI]: 0.25–0.86) and in the nationwide cohort (HR: 0.89; 95% CI: 0.86–0.93 with yearly increased exposure to GLP‐1 RAs). Discussion Treatment with GLP‐1 RAs may provide a new opportunity to reduce the incidence of dementia in patients with type 2 diabetes.

Interleukin (IL)-23 inhibitors, guselkumab, risankizumab, and tildrakizumab, represent the latest class of biologics approved for the treatment of moderate-to-severe psoriasis. Since their approval numerous real-life studies were published on anti-IL-23 use in routine clinical practice. Indeed, real-life data are important to improve the dermatological decision-making process, including patients who are typically excluded from clinical trials, such as subjects suffering from several comorbidities, subjects on polypharmacy, as well as multifailure patients. Herein, we performed a comprehensive literature review about real-life data available on guselkumab, risankizumab, and tildrakizumab. Real-life data of anti-IL-23 seem to confirm the promising results of IL-23 shown by clinical trials, highlighting the efficacy and safety profiles of this new class of biologics also in clinical practice. Keywords: guselkumab, tildrakizumab, risankizumab, psoriasis, review, real life, real-world practice, real-world evidence

Background Standard‐dose seasonal influenza vaccines often produce modest immunogenic responses in adults ≥65 years old. MF59 is intended to elicit a greater magnitude and increased breadth of immune response. Objective To determine the effectiveness of seasonal MF59‐adjuvanted trivalent/quadrivalent influenza vaccine (aTIV/aQIV) relative to no vaccination or vaccination with standard or high‐dose egg‐based influenza vaccines among people ≥65 years old. Methods Cochrane methodological standards and PRISMA‐P guidelines were followed. Real‐world evidence from non‐interventional studies published in peer‐reviewed journals and gray literature from 1997 through to July 15, 2020, including cluster‐randomized trials, were eligible. Two reviewers independently extracted data; risk of bias was assessed using the ROBINS‐I tool. Results Twenty‐one studies conducted during the 2006/07–2019/20 influenza seasons were included in the qualitative review; 16 in the meta‐analyses. Meta‐analysis of test‐negative studies found that aTIV reduced medical encounters due to lab‐confirmed influenza with pooled estimates of 40.7% (95% CI: 21.9, 54.9; I2 = 0%) for non‐emergency outpatient visits and 58.5% (40.7, 70.9; I2 = 52.9%) for hospitalized patients. The pooled estimate of VE from case‐control studies was 51.3% (39.1, 61.1; I2 = 0%) against influenza‐ or pneumonia‐related hospitalization. The pooled estimates for the relative VE of aTIV for the prevention of influenza‐related medical encounters were 13.9% (4.2, 23.5; I2 = 95.9%) compared with TIV, 13.7% (3.1, 24.2; I2 = 98.8%) compared with QIV, and 2.8% (−2.9, 8.5; I2 = 94.5%) compared with HD‐TIV. Conclusions Among adults ≥65 years, aTIV demonstrated significant absolute VE, improved relative VE compared to non‐adjuvanted standard‐dose TIV/QIV, and comparable relative VE to high‐dose TIV.

Our previous real‐world studies raised concerns that sequential biomarker testing may lead to increased time to treatment when compared with simultaneous single biomarker testing. The Oncomine Dx target test (ODxTT), a next‐generation sequencing–based multiplex biomarker panel test approved in Japan in 2019, is expected to improve time to treatment due to changes in testing methods. This retrospective observational study examined data claims for reimbursement submitted for patients with lung cancer in Japan between June 1, 2019, and March 31, 2020. To evaluate the change in testing prevalence over time and associated improvements in time to treatment, descriptive statistics were used to characterize biomarker testing patterns and rates and evaluate the time to treatment in the time following the approval of ODxTT considering transitions over time during the evaluation period. EGFR and programmed death ligand 1 (PD‐L1) were the most tested biomarkers in overall single and simultaneous single testing in the 6177 patients in this study. Individual single biomarker testing gradually decreased over time, except testing for PD‐L1, which remained constant. The use of ODxTT gradually increased in this period. Time to treatment decreased from 29 to 22 days with ODxTT, in contrast to single biomarker tests (median 21–23 days overall). These results indicate that biomarker testing frequency changed in Japanese clinical practice during the study and that the use of ODxTT has increased over time, which potentially contributed to the shortening of time to treatment. This retrospective observational study examined data claims for patients with lung cancer in Japan between June 1, 2019, and March 31, 2020. During this period, the use of single biomarker testing decreased over time while the use of the Oncomine Dx target test (ODxTT), a next‐generation sequencing–based multiplex biomarker panel test, gradually increased. These results indicate that biomarker testing frequency has changed the clinical practice in Japan, leading to improvements in time to treatment.