Introduction: High-quality randomised controlled trials (RCTs) provide the most reliable evidence on the comparative efficacy of new medicines. However, non-randomised studies (NRS) are increasingly recognised as a source of insights into the real-world performance of novel therapeutic products, particularly when traditional RCTs are impractical or lack generalisability. This means there is a growing need for synthesising evidence from RCTs and NRS in healthcare decision making, particularly given recent developments such as innovative study designs, digital technologies and linked databases across countries. Crucially, however, no formal framework exists to guide the integration of these data types. Objectives and Methods: To address this gap, we used a mixed methods approach (review of existing guidance, methodological papers, Delphi survey) to develop guidance for researchers and healthcare decision-makers on when and how to best combine evidence from NRS and RCTs to improve transparency and build confidence in the resulting summary effect estimates. Results: Our framework comprises seven steps on guiding the integration and interpretation of evidence from NRS and RCTs and we offer recommendations on the most appropriate statistical approaches based on three main analytical scenarios in healthcare decision making (specifically, ‘high-bar evidence’ when RCTs are the preferred source of evidence, ‘medium,’ and ‘low’ when NRS is the main source of inference). Conclusion: Our framework augments existing guidance on assessing the quality of NRS and their compatibility with RCTs for evidence synthesis, while also highlighting potential challenges in implementing it. This manuscript received endorsement from the International Society for Pharmacoepidemiology.

Introduction Cerebral vasospasm (VSP) is the leading risk factor of neurological deterioration (i.e., delayed cerebral ischemia [DCI] and cerebral infarction) after aneurysmal subarachnoid hemorrhage (aSAH) and a cause of morbidity and mortality. The objective of this systematic literature review is to summarize the economic and humanistic burden of VSP and its related complications after aSAH. Methods A predefined protocol was designed, and Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. Systematic searches were conducted in MEDLINE, Embase, and Cochrane (in January 2021) to identify studies reporting economic and/or humanistic (i.e., health-related quality of life [HRQoL]) outcomes for patients with asymptomatic and symptomatic VSP after aSAH. Related conferences and additional sources were searched manually. Dual screening, data extraction, and qualitative analysis were conducted. Results Of 3818 abstracts identified for review, 43 full-text articles representing 42 single studies met the inclusion criteria and were included. Most studies (33) were observational; nine were randomized clinical trials (RCTs). Economic outcomes were reported in 31 studies, and alongside HRQoL outcomes in 4 studies; 7 studies reported HRQoL outcomes only. Forty studies were conducted in single countries, while only 2 RCTs were conducted in multiple countries. Patients diagnosed with VSP or DCI spent between 2.1 and 7.4 days longer in intensive care and between 4.7 and 17 days longer in hospital (total) compared with patients without VSP or DCI. A significantly higher cost burden of US$33,945 (2021 £26,712) was identified for patients with VSP and £9370 (2021 £13,733) for patients with DCI compared with patients without. Patients with DCI were also disadvantaged by being employed for 62 fewer days (during 24-month follow-up), with an estimated mean cost of £3821 (2021 £5600) for days off work. Poor HRQoL was associated with ≥ 1 days with VSP symptoms (odds ratio [OR]: 2.8, 95% confidence interval [CI]: 1.4–5.3), symptomatic VSP (OR: 1.9, 95% CI: 1.0–3.6), and DCI (OR: 2.3, 95% CI: 1.3–4.2), although this was not consistent across all studies. Symptomatic VSP and DCI were identified as significant risk factors for depressed mood (OR: 2.2, 95% CI: 1.0–4.9) and global cognitive impairment (OR: 2.3) at 12 months, respectively. The severity of VSP was a critical predictor of post-aSAH economic and humanistic burden. Similar trends in economic and humanistic burden were identified in the general aSAH patient population. Study design and patient heterogeneity precluded direct metaanalysis of the results. Conclusion A substantial direct and indirect economic burden is linked to VSP and its related complications after aSAH. Although limited evidence was identified for humanistic burden, these patients seem to suffer from poor HRQoL with long-lasting burden. Overall, there is an urgent need to understand better the concept of “burden of illness” of VSP and its related complications after aSAH.

Aim: Regulatory and health technology assessment (HTA) agencies have increasingly published frameworks, guidelines, and recommendations for the use of real-world evidence (RWE) in healthcare decision-making. Variations in the scope and content of these documents, with updates running in parallel, may create challenges for their implementation especially during the market authorization and reimbursement phases of a medicine's life cycle. This environmental scan aimed to comprehensively identify and summarize the guidance documents for RWE developed by most well-established regulatory and reimbursement agencies, as well as other organizations focused on healthcare decision-making, and present their similarities and differences. Methods: RWE guidance documents, including white papers from regulatory and HTA agencies, were reviewed in March 2024. Data on scope and recommendations from each body were extracted by two reviewers and similarities and differences were summarized across four topics: study planning, choosing fit-for-purpose data, study conduct, and reporting. Post-authorization or non-pharmacological guidance was excluded. Results: Forty-six documents were identified across multiple agencies; US FDA produced the most RWE-related guidance. All agencies addressed specific and often similar methodological issues related to study design, data fitness-for-purpose, reliability, and reproducibility, although inconsistency in terminologies on these topics was noted. Two HTA bodies (National Institute for Health and Care Excellence [NICE] and Canada's Drug Agency) each centralized all related RWE guidance under a unified framework. RWE quality tools and checklists were not consistently named and some differences in preferences were noted. European Medicines Agency, NICE, Haute Autorité de Santé, and the Institute for Quality and Efficiency in Health Care included specific recommendations on the use of analytical approaches to address RWE complexities and increase trust in its findings. Conclusion: Similarities in agencies' expectations on RWE studies design, quality elements, and reporting will facilitate evidence generation strategy and activities for manufacturers facing multiple, including global, regulatory and reimbursement submissions and re-submissions. A strong preference by decision-making bodies for local real-world data generation may hinder opportunities for data sharing and outputs from international federated data networks. Closer collaboration between decision-making agencies towards a harmonized RWE roadmap, which can be centrally preserved in a living mode, will provide manufacturers and researchers clarity on minimum acceptance requirements and expectations, especially as novel methodologies for RWE generation are rapidly emerging.

Objective To determine whether assessment tools for non-randomised studies (NRS) address critical elements that influence the validity of NRS findings for comparative safety and effectiveness of medications. Design Systematic review and Delphi survey. Data sources We searched PubMed, Embase, Google, bibliographies of reviews and websites of influential organisations from inception to November 2019. In parallel, we conducted a Delphi survey among the International Society for Pharmacoepidemiology Comparative Effectiveness Research Special Interest Group to identify key methodological challenges for NRS of medications. We created a framework consisting of the reported methodological challenges to evaluate the selected NRS tools. Study selection Checklists or scales assessing NRS. Data extraction Two reviewers extracted general information and content data related to the prespecified framework. Results Of 44 tools reviewed, 48% (n=21) assess multiple NRS designs, while other tools specifically addressed case–control (n=12, 27%) or cohort studies (n=11, 25%) only. Response rate to the Delphi survey was 73% (35 out of 48 content experts), and a consensus was reached in only two rounds. Most tools evaluated methods for selecting study participants (n=43, 98%), although only one addressed selection bias due to depletion of susceptibles (2%). Many tools addressed the measurement of exposure and outcome (n=40, 91%), and measurement and control for confounders (n=40, 91%). Most tools have at least one item/question on design-specific sources of bias (n=40, 91%), but only a few investigate reverse causation (n=8, 18%), detection bias (n=4, 9%), time-related bias (n=3, 7%), lack of new-user design (n=2, 5%) or active comparator design (n=0). Few tools address the appropriateness of statistical analyses (n=15, 34%), methods for assessing internal (n=15, 34%) or external validity (n=11, 25%) and statistical uncertainty in the findings (n=21, 48%). None of the reviewed tools investigated all the methodological domains and subdomains. Conclusions The acknowledgement of major design-specific sources of bias (eg, lack of new-user design, lack of active comparator design, time-related bias, depletion of susceptibles, reverse causation) and statistical assessment of internal and external validity is currently not sufficiently addressed in most of the existing tools. These critical elements should be integrated to systematically investigate the validity of NRS on comparative safety and effectiveness of medications. Systematic review protocol and registration https://osf.io/es65q.

Cost-effectiveness analyses (CEA) are important in healthcare decision-making and resource allocation; however, expanding the scope of CEAs beyond the traditional clinicoeconomic concepts to also include value elements such as health equity has attracted much interest in recent years. This umbrella review aimed to synthesize evidence on how equity concepts have been considered in modified types of CEAs. Publicly available articles in MEDLINE were searched on January 25, 2024, to identify systematic reviews (SLRs) published in English since 2013 that incorporate health equity considerations in CEAs. Title/abstract, fulltext article screening and data extraction were conducted by a single reviewer and validated by a second reviewer. Results were qualitatively synthesized to identify common themes. Eight SLRs were included. Distributional CEAs (DCEA), equity-based weighting, extended CEA (ECEA), mathematical programming and multi-criteria decision analysis (MCDA) were the most discussed approaches. A lack of consensus on the best approach for incorporating health equity into CEAs was highlighted, as these approaches are not currently consistently used in decision-making. Important limitations included scarcity of robust data to inform health equity indices, bias associated with commonly used health outcome metrics and the challenge of accounting for additional contextual factors such as fairness and opportunity costs. Proposals to expand CEAs to address equity issues come with challenges due to data unavailability, methods complexity, and decision-makers unfamiliarity with these approaches. Our review indicates that extended and distributional CEAs can support decision-making by capturing the impact of inequity on the clinical and cost-effectiveness assessment of treatments, although future modeling should account for additional contextual factors such as fairness and opportunity costs. Recommendations for actions moving forward include standardization of data collection for outcomes related to equity and familiarity with methodologies to account for the complexities of integrating health equity considerations in CEAs.