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DARE-19 (NCT04350593) was a randomized trial studying the effects of dapagliflozin, an SGLT2 inhibitor, in hospitalized patients with COVID-19 pneumonia and cardiometabolic risk factors. The conduct of DARE-19 offered the opportunity to define an innovative and clinically meaningful endpoint in a new disease that would best reflect the known profile of dapagliflozin, accompanied by the statistical challenges of analysis and interpretation of such a novel endpoint.Hierarchical composite endpoints (HCEs) are based on clinical outcomes which, unlike traditional composite endpoints incorporate ranking of components according to clinical importance. Design of an HCE requires the clinical considerations specific to the therapeutic area under study and the mechanism of action of the investigational treatment. Statistical aspects for the clinical endpoints include the proper definition of the estimand as suggested by ICH E9(R1) for the precise specification of the treatment effect measured by an HCE.We describe the estimand of the DARE-19 trial, where an HCE was constructed to capture the treatment effect of dapagliflozin in hospitalized patients with COVID-19, and was analyzed using a win odds. Practical aspects of designing new studies based on an HCE are described. These include sample size, power, and minimal detectable effect calculations for an HCE based on the win odds analysis, as well as handling of missing data and the clinical interpretability of the win odds in relation to the estimand.HCEs are flexible endpoints that can be adapted for use in different therapeutic areas, with win odds as the analysis method. DARE-19 is an example of a COVID-19 trial with an HCE as one of the primary endpoints for estimating a clinically interpretable treatment effect in the COVID-19 setting.

Real-world data (RWD) can contextualize findings from single-arm trials when randomized comparative trials are unethical or unfeasible. Findings from single-arm trials alone are difficult to interpret and a comparison, when feasible and meaningful, to patient-level information from RWD facilitates the evaluation. As such, there have been several recent regulatory applications including RWD or other external data to support the product's efficacy and safety. This paper summarizes some lessons learned from such contextualization from 20 notable new drug or biologic licensing applications in oncology and rare diseases.This review focuses on 20 notable new drug or biologic licensing applications that included patient-level RWD or other external data for contextualization of trial results. Publicly available regulatory documents including clinical and statistical reviews, advisory committee briefing materials and minutes, and approved product labeling were retrieved for each application. The authors conducted independent assessments of these documents focusing on the regulatory evaluation, in each case. Three examples are presented in detail to illustrate the salient issues and themes identified across applications.Regulatory decisions were strongly influenced by the quality and usability of the RWD. Comparability of cohort attributes such as endpoints, populations, follow-up, index and censoring criteria, as well as data completeness and accuracy of key variables appeared to be essential to ensure the quality and relevance of the RWD. Given adequate sample size of the clinical trials or external control, the use of appropriate analytic methods to properly account for confounding, such as regression or matching, and pre-specification of these methods while blinded to patient outcomes seemed good strategies to address baseline differences.Contextualizing single-arm trials with patient-level RWD appears to be an advance in regulatory science; however, challenges remain. Statisticians and epidemiologists have long focused on analytical methods for comparative effectiveness but hurdles in use of RWD have often occurred upstream of the analyses. More specifically, we noted hurdles in evaluating data quality, justifying cohort selection or initiation of follow-up, and demonstrating comparability of cohorts and endpoints.

Background and objectives: Patients who were hospitalized with coronavirus disease 2019 (COVID-19) infection are at high risk of AKI and KRT, especially in the presence of CKD. The Dapagliflozin in Respiratory Failure in Patients with COVID-19 (DARE-19) trial showed that in patients hospitalized with COVID-19, treatment with dapagliflozin versus placebo resulted in numerically fewer participants who experienced organ failure or death, although these differences were not statistically significant. We performed a secondary analysis of the DARE-19 trial to determine the efficacy and safety of dapagliflozin on kidney outcomes in the overall population and in prespecified subgroups of participants defined by baseline eGFR.Design, setting, participants, & measurements: The DARE-19 trial randomized 1250 patients who were hospitalized (231 [18%] had eGFR 2) with COVID-19 and cardiometabolic risk factors to dapagliflozin or placebo. Dual primary outcomes (time to new or worsened organ dysfunction or death, and a hierarchical composite end point of recovery [change in clinical status by day 30]), and the key secondary kidney outcome (composite of AKI, KRT, or death), and safety were assessed in participants with baseline eGFR 2.Results: The effect of dapagliflozin versus placebo on the primary prevention outcome (hazard ratio, 0.80; 95% confidence interval, 0.58 to 1.10), primary recovery outcome (win ratio, 1.09; 95% confidence interval, 0.97 to 1.22), and the composite kidney outcome (hazard ratio, 0.74; 95% confidence interval, 0.50 to 1.07) were consistent across eGFR subgroups (P for interaction: 0.98, 0.67, and 0.44, respectively). The effects of dapagliflozin on AKI were also similar in participants with eGFR 2 (hazard ratio, 0.71; 95% confidence interval, 0.29 to 1.77) and ≥60 ml/min per 1.73 m2 (hazard ratio, 0.69; 95% confidence interval, 0.37 to 1.29). Dapagliflozin was well tolerated in participants with eGFR 2.Conclusions: The effects of dapagliflozin on primary and secondary outcomes in hospitalized participants with COVID-19 were consistent in those with eGFR below/above 60 ml/min per 1.73 m2. Dapagliflozin was well tolerated and did not increase the risk of AKI in participants with eGFR below or above 60 ml/min per 1.73 m2.

The win odds is a distribution-free method of comparing locations of distributions of two independent random variables. Introduced as a method for analyzing hierarchical composite endpoints, it is well suited to be used in the analysis of ordinal scale endpoints in COVID-19 clinical trials. For a single outcome, we provide power and sample size calculation formulas for the win odds test. We also provide an implementation of the win odds analysis method for a single ordinal outcome in a commonly used statistical software to make the win odds analysis fully reproducible.

Summary Background COVID-19 can lead to multiorgan failure. Dapagliflozin, a SGLT2 inhibitor, has significant protective benefits for the heart and kidney. We aimed to see whether this agent might provide organ protection in patients with COVID-19 by affecting processes dysregulated during acute illness. Methods DARE-19 was a randomised, double-blind, placebo-controlled trial of patients hospitalised with COVID-19 and with at least one cardiometabolic risk factor (ie, hypertension, type 2 diabetes, atherosclerotic cardiovascular disease, heart failure, and chronic kidney disease). Patients critically ill at screening were excluded. Patients were randomly assigned 1:1 to dapagliflozin (10 mg daily orally) or matched placebo for 30 days. Dual primary outcomes were assessed in the intention-to-treat population: the outcome of prevention (time to new or worsened organ dysfunction or death), and the hierarchial composite outcome of recovery (change in clinical status by day 30). Safety outcomes, in patients who received at least one study medication dose, included serious adverse events, adverse events leading to discontinuation, and adverse events of interest. This study is registered with ClinicalTrials.gov , NCT04350593 . Findings Between April 22, 2020 and Jan 1, 2021, 1250 patients were randomly assigned with 625 in each group. The primary composite outcome of prevention showed organ dysfunction or death occurred in 70 patients (11·2%) in the dapagliflozin group, and 86 (13·8%) in the placebo group (hazard ratio [HR] 0·80, 95% CI 0·58–1·10; p=0·17). For the primary outcome of recovery, 547 patients (87·5%) in the dapagliflozin group and 532 (85·1%) in the placebo group showed clinical status improvement, although this was not statistically significant (win ratio 1·09, 95% CI 0·97–1·22; p=0·14). There were 41 deaths (6·6%) in the dapagliflozin group, and 54 (8·6%) in the placebo group (HR 0·77, 95% CI 0·52–1·16). Serious adverse events were reported in 65 (10·6%) of 613 patients treated with dapagliflozin and in 82 (13·3%) of 616 patients given the placebo. Interpretation In patients with cardiometabolic risk factors who were hospitalised with COVID-19, treatment with dapagliflozin did not result in a statistically significant risk reduction in organ dysfunction or death, or improvement in clinical recovery, but was well tolerated. Funding AstraZeneca.

AIMS: Coronavirus disease 2019 (COVID-19) is caused by a novel severe acute respiratory syndrome coronavirus 2. It can lead to multiorgan failure, including respiratory and cardiovascular decompensation, and kidney injury, with significant associated morbidity and mortality, particularly in patients with underlying metabolic, cardiovascular, respiratory or kidney disease. Dapagliflozin, a sodium-glucose cotransporter-2 inhibitor, has shown significant cardio- and renoprotective benefits in patients with type 2 diabetes (with and without atherosclerotic cardiovascular disease), heart failure and chronic kidney disease, and may provide similar organ protection in high-risk patients with COVID-19. MATERIALS AND METHODS: DARE-19 (NCT04350593) is an investigator-initiated, collaborative, international, multicentre, randomized, double-blind, placebo-controlled study testing the dual hypotheses that dapagliflozin can reduce the incidence of cardiovascular, kidney and/or respiratory complications or all-cause mortality, or improve clinical recovery, in adult patients hospitalized with COVID-19 but not critically ill on admission. Eligible patients will have ≥1 cardiometabolic risk factor for COVID-19 complications. Patients will be randomized 1:1 to dapagliflozin 10 mg or placebo. Primary efficacy endpoints are time to development of new or worsened organ dysfunction during index hospitalization, or all-cause mortality, and the hierarchical composite endpoint of change in clinical status through day 30 of treatment. Safety of dapagliflozin in individuals with COVID-19 will be assessed. CONCLUSIONS: DARE-19 will evaluate whether dapagliflozin can prevent COVID-19-related complications and all-cause mortality, or improve clinical recovery, and assess the safety profile of dapagliflozin in this patient population. Currently, DARE-19 is the first large randomized controlled trial investigating use of sodium-glucose cotransporter 2 inhibitors in patients with COVID-19.

The COVID-19 pandemic presents unprecedented challenges for drug developers seeking to evaluate the safety and efficacy of potential treatments for COVID-19. Clinical researchers must work quickly ...

The win ratio is a general method of comparing locations of distributions of two independent, ordinal random variables, and it can be estimated without distributional assumptions. In this paper we provide a unified theory of win ratio estimation in the presence of stratification and adjustment by a numeric variable. Building step by step on the estimate of the crude win ratio we compare corresponding tests with well known non-parametric tests of group difference (Wilcoxon rank-sum test, Fligner–Policello test, van Elteren test, test based on the regression on ranks, and the rank analysis of covariance test). We show that the win ratio gives an interpretable treatment effect measure with corresponding test to detect treatment effect difference under minimal assumptions.

A model-based approach to analyze two incomplete disease surveillance datasets is described. Such data typically consist of case counts, each originating from a specific geographical area. A Bayesian hierarchical model is proposed for estimating the total number of cases with disease while simultaneously adjusting for spatial variation. This approach explicitly accounts for model uncertainty and can make use of covariates.The method is applied to two surveillance datasets maintained by the Centers for Disease Control and Prevention on Rocky Mountain spotted fever (RMSF). An inference is drawn using Markov Chain Monte Carlo simulation techniques in a fully Bayesian framework. The central feature of the model is the ability to calculate and estimate the total number of cases and disease incidence for geographical regions where RMSF is endemic.The information generated by this model could significantly reduce the public health impact of RMSF and other vector-borne zoonoses, as well as other infectious or chronic diseases, by improving knowledge of the spatial distribution of disease risk of public health officials and medical practitioners. More accurate information on populations at high risk would focus attention and resources on specific areas, thereby reducing the morbidity and mortality caused by some of the preventable and treatable diseases.

From 1982 to 1984, the authors conducted a population-based case-control study of lung cancer in men and women nonsmokers in New York State. In-person interviews were completed for 437 lung cancer cases (197 never smokers, 240 former smokers) and 437 matched population controls. Cases and controls were asked to report any history of physician-diagnosed nonmalignant lung disease; cases were more likely than controls to report such a history. Statistically significant associations were found for emphysema (odds ratio (OR) = 1.94, 95% confidence interval (CI) 1.10-3.43), chronic bronchitis (OR = 1.73, 95% CI 1.10-2.72), and the combined endpoint of emphysema, chronic bronchitis, or asthma (OR = 1.82, 95% CI 1.26-2.63). After adjustment for active and passive tobacco smoke exposure, emphysema, chronic bronchitis, and asthma (each condition and the combined endpoint) were significantly associated with lung cancer risk. The risk was more marked for squamous cell carcinomas and for subjects who were diagnosed at older ages, and it remained significant when surrogate interviews were excluded. These results are consistent with the hypothesis that certain prior lung conditions increase the risk of lung cancer in men and women nonsmokers.

ContextComplicated, left-sided native valve endocarditis causes significant morbidity and mortality in adults. The presumed benefits of valve surgery remain unproven due to lack of randomized controlled trials.ObjectiveTo determine whether valve surgery is associated with reduced mortality in adults with complicated, left-sided native valve endocarditis.Design and SettingRetrospective, observational cohort study conducted from January 1990 to January 2000 at 7 Connecticut hospitals. Propensity analyses were used to control for bias in treatment assignment and prognostic imbalances.PatientsOf the 513 adults with complicated, left-sided native valve endocarditis, 230 (45%) underwent valve surgery and 283 (55%) received medical therapy alone.Main Outcome MeasureAll-cause mortality at 6 months after baseline.ResultsIn the 6-month period after baseline, 131 patients (26%) died. In unadjusted analyses, valve surgery was associated with reduced mortality (16% vs 33%; hazard ratio [HR], 0.43; 95% confidence interval [CI], 0.29-0.63; P

ContextComplicated left-sided native valve endocarditis causes significant morbidity and mortality in adults. Lack of valid data regarding estimation of prognosis makes management of this condition difficult.ObjectiveTo derive and externally validate a prognostic classification system for adults with complicated left-sided native valve endocarditis.Design, Setting, and PatientsRetrospective observational cohort study conducted from January 1990 to January 2000 at 7 Connecticut hospitals among 513 patients older than 16 years who experienced complicated left-sided native valve endocarditis and who were divided into derivation (n = 259) and validation (n = 254) cohorts.Main Outcome MeasureAll-cause mortality at 6 months after baseline.ResultsIn the derivation and validation cohorts, the 6-month mortality rates were 25% and 26%, respectively. Five baseline features were independently associated with 6-month mortality (comorbidity [P = .03], abnormal mental status [P = .02], moderate to severe congestive heart failure [P = .01], bacterial etiology other than viridans streptococci [P

The Veterans Health Administration (VHA) is the largest integrated healthcare system in the world and provides care to approximately 20,000 multiple sclerosis (MS) patients. Here, we report that these MS patients are disproportionately more likely to be older, male, unemployed, and disabled with lower levels of education and financial resources when compared to veterans not receiving care within the VHA or to nonveteran MS patients. When comparing the VHA MS patients to a cohort of nonveteran MS patients matched for age, sex, and disability, we found that veterans receiving care within the VHA were equally likely to have received care from a neurologist and more likely to have received care from rehabilitation specialists and primary care physicians than nonveterans. Similarly, veterans in the VHA were more likely to receive therapy with certain symptomatic medications but were less likely to be treated with disease-modifying agents for MS (DMAMS) than nonveterans. When treated with DMAMS, they are more likely to be treated with Avonex and significantly less likely to receive treatment with Copaxone or Novantrone.