Background Master protocols, classified as basket trials, umbrella trials, and platform trials, are novel designs that investigate multiple hypotheses through concurrent sub-studies (e.g., multiple treatments or populations or that allow adding/removing arms during the trial), offering enhanced efficiency and a more ethical approach to trial evaluation. Despite the many advantages of these designs, they are infrequently used. Methods We conducted a landscape analysis of master protocols using a systematic literature search to determine what trials have been conducted and proposed for an overall goal of improving the literacy in this emerging concept. On July 8, 2019, English-language studies were identified from MEDLINE, EMBASE, and CENTRAL databases and hand searches of published reviews and registries. Results We identified 83 master protocols (49 basket, 18 umbrella, and 16 platform trials). The number of master protocols has increased rapidly over the last five years. Most have been conducted in the US (n = 44/83) and investigated experimental drugs (n = 82/83) in the field of oncology (n = 76/83). The majority of basket trials were exploratory (i.e., phase I/II; n = 47/49) and not randomized (n = 44/49), and more than half (n = 28/48) investigated only a single intervention. The median sample size of basket trials was 205 participants (interquartile range, Q3-Q1 [IQR]: 500–90 = 410), and the median study duration was 22.3 (IQR: 74.1–42.9 = 31.1) months. Similar to basket trials, most umbrella trials were exploratory (n = 16/18), but the use of randomization was more common (n = 8/18). The median sample size of umbrella trials was 346 participants (IQR: 565–252 = 313), and the median study duration was 60.9 (IQR: 81.3–46.9 = 34.4) months. The median number of interventions investigated in umbrella trials was 5 (IQR: 6–4 = 2). The majority of platform trials were randomized (n = 15/16), and phase III investigation (n = 7/15; one did not report information on phase) was more common in platform trials with four of them using seamless II/III design. The median sample size was 892 (IQR: 1835–255 = 1580), and the median study duration was 58.9 (IQR: 101.3–36.9 = 64.4) months. Conclusions We anticipate that the number of master protocols will continue to increase at a rapid pace over the upcoming decades. More efforts to improve awareness and training are needed to apply these innovative trial design methods to fields outside of oncology.

Background: Recent approval and adoption of pangenotypic direct acting antivirals (DAAs) necessitated a revision of the 2015 World Health Organization guidelines for the management of persons with hepatitis C virus (HCV) infection. Methods: We searched MEDLINE, EMBASE, CENTRAL, and relevant conference proceedings to identify randomized and non-randomized trials, as well as prospective observational studies of DAAs. The proportions of persons with events were pooled for sustained virological response at 12 weeks post-treatment (SVR12), discontinuations due to adverse events (DAEs), serious adverse events (SAEs), and all-cause mortality. Analyses were stratified by HCV genotype and antiviral treatment experience, with subgroup analyses based on presence of cirrhosis and HIV-HCV coinfection. Findings: The evidence base consisted of 238 publications describing 142 studies. In the overall analysis, which included all persons irrespective of treatment experience or comorbidities, the pooled proportion achieving SVR12 exceeded 0.94 for all pangenotypic regimens across genotypes 1, 2, and 4. Some heterogeneity may have led to lower SVR rates in persons with genotype 3 infection. High SVR12 (>0.90) was observed in persons with genotype 1 infection with cirrhosis, though evidence varied and was limited for genotypes 2À4. Evidence was sparse for persons with HIVÀHCV coinfection. All regimens were associated with small proportions of persons with DAEs, SAEs, or all-cause mortality. Interpretation: Based on this and other supporting evidence, the WHO issued updated guidelines with a conditional recommendation, based on moderate quality evidence, for the use of pangenotypic DAA regimens for persons with chronic HCV infection aged 18 years and older (July 2018). Funding: This study was funded by the World Health Organization.

Background In September 2018 the FDA provided a draft guidance on master protocols reflecting an increased interest in these designs by industry. Master protocols refer to a single overarching protocol developed to evaluate multiple hypotheses and may be further categorized as basket, umbrella, and platform trials. However, inconsistencies in reporting persist in the literature. We conducted a systematic review to describe master protocol reporting with the goal of facilitating the further development and spread of these innovative trial designs. Methods We searched MEDLINE, EMBASE, and CENTRAL from inception to April 25, 2019 for English articles on master protocols. This was supplemented by hand searches of trial registries and of the bibliographies of published reviews. We used the FDA's definitions of master protocols as references and compared them to self-reported master protocols. Results We identified 278 master protocol publications, consisting of 228 protocols and 50 reviews. Sixty-six records provided unique definitions of master protocol types. We observed considerable heterogeneity in definitions of master protocols, and over half (54%) used oncology-specific language. The majority of self-classified master protocols (57%) were consistent with the FDA's definitions of master protocols. Conclusion The terms ‘master protocol’, ‘basket trial’, ‘umbrella trial’, and ‘platform trial’ are inconsistently described. Careful treatment of these terms and adherence to the definitions set forth by the FDA will facilitate better understanding of these trial designs and allow them to be used broadly and to their full potential in clinical research. We encourage trial methodologists to use these trial designations when applicable.

Background To inform World Health Organization (WHO) global guidelines, we updated and expanded the evidence base to assess the comparative efficacy, tolerability, and safety of first-line antiretroviral therapy (ART) regimens. Methods We searched Embase, Medline and CENTRAL on 28 February 2020 to update the systematic literature review of clinical trials comparing recommended first-line ART that informed previous WHO guidelines. Outcomes included viral suppression, change in CD4 cell counts, mortality, serious and overall adverse events (AEs), discontinuation, discontinuations due to AEs (DAEs); and new outcomes: drug-resistance, neuropsychiatric AEs, early viral suppression, weight gain and birth outcomes. Comparative effects were assessed through network meta-analyses and certainty in the evidence was assessed using the GRADE framework. Findings We identified 156 publications pertaining to 68 trials for the primary population. Relative to efavirenz, dolutegravir had improved odds of viral suppression across all time points (odds ratio [OR]: 1·94; 95% credible interval [CrI]: 1·48–2·56 at 96 weeks); was protective of drug-resistance (OR: 0·13; 95%CrI: 0·04–0·48); and led to fewer discontinuations (OR: 0·58; 95%CrI: 0·48–0·70). Evidence supported dolutegravir use among TB-HIV co-infected persons and pregnant women. Adverse birth outcomes were observed in 33.2% of dolutegravir-managed pregnancies and 35.0% of efavirenz-managed pregnancies. Low-dose efavirenz had comparable efficacy and safety to standard-dose efavirenz, but led to fewer DAEs (OR: 0·70; 95%CrI: 0·50–0·92). Interpretation The evidence supports choosing dolutegravir in combination with lamivudine/emtricitabine and tenofovir disoproxil fumarate as the preferred first-line regimen and low-dose efavirenz-based regimens as an alternative. Dolutegravir can be considered to be effective, safe and tolerable. Funding WHO.

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This paper aims to provide a perspective on data sharing practices in the context of the COVID-19 pandemic. The scientific community has made several important inroads in the fight against COVID-19, and there are over 2500 clinical trials registered globally. Within the context of the rapidly changing pandemic, we are seeing a large number of trials conducted without results being made available. It is likely that a plethora of trials have stopped early, not for statistical reasons but due to lack of feasibility. Trials stopped early for feasibility are, by definition, statistically underpowered and thereby prone to inconclusive findings. Statistical power is not necessarily linear with the total sample size, and even small reductions in patient numbers or events can have a substantial impact on the research outcomes. Given the profusion of clinical trials investigating identical or similar treatments across different geographical and clinical contexts, one must also consider that the likelihood of a substantial number of false-positive and false-negative trials, emerging with the increasing overall number of trials, adds to public perceptions of uncertainty. This issue is complicated further by the evolving nature of the pandemic, wherein baseline assumptions on control group risk factors used to develop sample size calculations are far more challenging than those in the case of well-documented diseases. The standard answer to these challenges during nonpandemic settings is to assess each trial for statistical power and risk-of-bias and then pool the reported aggregated results using meta-analytic approaches. This solution simply will not suffice for COVID-19. Even with random-effects meta-analysis models, it will be difficult to adjust for the heterogeneity of different trials with aggregated reported data alone, especially given the absence of common data standards and outcome measures. To date, several groups have proposed structures and partnerships for data sharing. As COVID-19 has forced reconsideration of policies, processes, and interests, this is the time to advance scientific cooperation and shift the clinical research enterprise toward a data-sharing culture to maximize our response in the service of public health.

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Cost-utility analysis (CUA) is a widely recommended form of health economic evaluation worldwide. The outcome measure in CUA is quality-adjusted life-years (QALYs), which are calculated using health state utility values (HSUVs) and corresponding life-years. Therefore, HSUVs play a significant role in determining cost-effectiveness. Formal adoption and endorsement of CUAs by reimbursement authorities motivates methodological advancement in HSUV measurement and application. A large body of evidence exploring various methods in measuring HSUVs has accumulated, imposing challenges for investigators in identifying and applying HSUVs to CUAs. First, large variations in HSUVs between studies are often reported, and these may lead to different cost-effectiveness conclusions. Second, issues concerning the quality of studies that generate HSUVs are increasingly highlighted in the literature. This issue is compounded by the limited published guidance and methodological standards for assessing the quality of these studies. Third, reimbursement decision making is a context-specific process. Therefore, while an HSUV study may be of high quality, it is not necessarily appropriate for use in all reimbursement jurisdictions. To address these issues, by promoting a systematic approach to study identification, critical appraisal, and appropriate use, we are developing the Health Utility Book (HUB). The HUB consists of an HSUV registry, a quality assessment tool for health utility studies, and a checklist for interpreting their use in CUAs. We anticipate that the HUB will make a timely and important contribution to the rigorous conduct and proper use of health utility studies for reimbursement decision making. In this way, health care resource allocation informed by HSUVs may reflect the preferences of the public, improve health outcomes of patients, and maintain the efficiency of health care systems.