Background In this study, we aimed to evaluate the effects of tocilizumab in adult patients admitted to hospital with COVID-19 with both hypoxia and systemic inflammation. Methods This randomised, controlled, open-label, platform trial (Randomised Evaluation of COVID-19 Therapy [RECOVERY]), is assessing several possible treatments in patients hospitalised with COVID-19 in the UK. Those trial participants with hypoxia (oxygen saturation <92% on air or requiring oxygen therapy) and evidence of systemic inflammation (C-reactive protein ≥75 mg/L) were eligible for random assignment in a 1:1 ratio to usual standard of care alone versus usual standard of care plus tocilizumab at a dose of 400 mg–800 mg (depending on weight) given intravenously. A second dose could be given 12–24 h later if the patient's condition had not improved. The primary outcome was 28-day mortality, assessed in the intention-to-treat population. The trial is registered with ISRCTN (50189673) and ClinicalTrials.gov ( NCT04381936 ). Findings Between April 23, 2020, and Jan 24, 2021, 4116 adults of 21 550 patients enrolled into the RECOVERY trial were included in the assessment of tocilizumab, including 3385 (82%) patients receiving systemic corticosteroids. Overall, 621 (31%) of the 2022 patients allocated tocilizumab and 729 (35%) of the 2094 patients allocated to usual care died within 28 days (rate ratio 0·85; 95% CI 0·76–0·94; p=0·0028). Consistent results were seen in all prespecified subgroups of patients, including those receiving systemic corticosteroids. Patients allocated to tocilizumab were more likely to be discharged from hospital within 28 days (57% vs 50%; rate ratio 1·22; 1·12–1·33; p<0·0001). Among those not receiving invasive mechanical ventilation at baseline, patients allocated tocilizumab were less likely to reach the composite endpoint of invasive mechanical ventilation or death (35% vs 42%; risk ratio 0·84; 95% CI 0·77–0·92; p<0·0001). Interpretation In hospitalised COVID-19 patients with hypoxia and systemic inflammation, tocilizumab improved survival and other clinical outcomes. These benefits were seen regardless of the amount of respiratory support and were additional to the benefits of systemic corticosteroids. Funding UK Research and Innovation (Medical Research Council) and National Institute of Health Research.

Propensity score based weighting approaches provide an alternative to propensity score matching and are especially useful when preserving a large majority of the study sample is needed to maximise precision Propensity score based weighting approaches can target treatment effect estimation in specific populations including the average treatment effect in the whole population, average treatment effect among the treated population, or average treatment effect in a subpopulation with clinical equipoise Principles outlined in this report are intended to help investigators in identifying the most suitable propensity score based weighting approach for their analysis and provide a framework for transparent reporting on 4 September 2020 by guest. Protected by copyright.

Background There is controversy regarding whether the use of selective serotonin reuptake inhibitors (SSRIs) and other antidepressants in pregnancy is associated with increased risks for congenital cardiac defects. In particular, concerns exist about a possible association between paroxetine and right ventricular outflow tract obstruction (RVOTO), and between sertraline and ventricular septal defects (VSD). Methods We performed a cohort study nested in the 2000–2007 nationwide Medicaid Analytic eXtract. The study included 949,504 pregnant women enrolled in Medicaid from three months before conception through one month post delivery, and their live-born infants. We compared the risk of major cardiac defects in women with antidepressant medication use during the first trimester versus no use, restricting the cohort to women with depression and using propensity score adjustment to control for depression severity and other potential confounders. Results 64,389 women (6.8%) used antidepressants during the first trimester. Overall, 6,403 infants not exposed to antidepressants were born with a cardiac defect (72.3 per 10,000), compared with 580 infants exposed (90.1 per 10,000). Associations between antidepressant use and cardiac defects were attenuated with increasing levels of adjustment for confounding. For SSRIs, relative risks for any cardiac defect were 1.25 (95%CI, 1.13–1.38) unadjusted, 1.12 (1.00–1.26) depression-restricted, and 1.06 (0.93–1.22) depression-restricted and fully-adjusted. We found no significant associations between the use of paroxetine and RVOTO (1.07, 0.59–1.93), or the use of sertraline and VSD (1.04, 0.76–1.41). Conclusions Results of this large population-based cohort study suggest no substantial increased risk of cardiac malformations attributable to SSRIs.

Regulators consider randomized controlled trials (RCTs) as the gold standard for evaluating the safety and effectiveness of medications, but their costs, duration, and limited generalizability have caused some to look for alternatives. Real world evidence based on data collected outside of RCTs, such as registries and longitudinal healthcare databases, can sometimes substitute for RCTs, but concerns about validity have limited their impact. Greater reliance on such real world data (RWD) in regulatory decision making requires understanding why some studies fail while others succeed in producing results similar to RCTs. Key questions when considering whether RWD analyses can substitute for RCTs for regulatory decision making are WHEN one can study drug effects without randomization and HOW to implement a valid RWD analysis if one has decided to pursue that option. The WHEN is primarily driven by externalities not controlled by investigators, whereas the HOW is focused on avoiding known mistakes in RWD analyses.

Objective While serious infections are significant causes of morbidity and mortality in systemic lupus erythematosus (SLE), the epidemiology in a nationwide cohort of SLE and lupus nephritis (LN) patients has not been examined. Methods Using the Medicaid Analytic eXtract (MAX) database, 2000-2006, we identified patients 18-64 years with SLE and a subset with LN. We ascertained hospitalized serious infections using validated algorithms, and 30-day mortality rates. We used Poisson regression to calculate infection incidence rates (IR), and multivariable Cox proportional hazards models to calculate hazard ratios (HR) for first infection, adjusted for sociodemographics, medication use, and a SLE-specific risk adjustment index. Results We identified 33,565 patients with SLE and 7,113 with LN. There were 9,078 serious infections in 5,078 SLE patients and 3,494 infections in 1,825 LN patients. The infection IR per 100 person-years was 10.8 in SLE and 23.9 in LN. In adjusted models, in SLE, we observed increased risks of infection among males compared to females (HR 1.33, 95% CI 1.20-1.47), in Blacks compared to Whites (HR 1.14, 95% CI 1.06-1.21), and glucocorticoid users (HR 1.51, 95% CI 1.43-1.61) and immunosuppressive users (HR 1.11, 95% CI 1.03-1.20) compared with non-users. Hydroxychloroquine users had a reduced risk of infection compared to non-users (HR 0.73, 95% CI 0.68-0.77). The 30-day mortality rate per 1,000 person-years among those hospitalized with infections was 21.4 in SLE and 38.7 in LN. Conclusion In this diverse, nationwide cohort of SLE patients, we observed a substantial burden of serious infections with many subsequent deaths.

Inferring causation from non-randomized studies of exposure requires that exposure groups can be balanced with respect to prognostic factors for the outcome. Although there is broad agreement in the literature that balance should be checked, there is confusion regarding the appropriate metric. We present a simulation study that compares several balance metrics with respect to the strength of their association with bias in estimation of the effect of a binary exposure on a binary, count, or continuous outcome. The simulations utilize matching on the propensity score with successively decreasing calipers to produce datasets with varying covariate balance. We propose the post-matching C-statistic as a balance metric and found that it had consistently strong associations with estimation bias, even when the propensity score model was misspecified, as long as the propensity score was estimated with sufficient study size. This metric, along with the average standardized difference and the general weighted difference, outperformed all other metrics considered in association with bias, including the unstandardized absolute difference, Kolmogorov-Smirnov and Lévy distances, overlapping coefficient, Mahalanobis balance, and L1 metrics. Of the best-performing metrics, the C-statistic and general weighted difference also have the advantage that they automatically evaluate balance on all covariates simultaneously and can easily incorporate balance on interactions among covariates. Therefore, when combined with the usual practice of comparing individual covariate means and standard deviations across exposure groups, these metrics may provide useful summaries of the observed covariate imbalance.

Background: The EMPA-REG OUTCOME trial showed that empagliflozin, a sodium-glucose co-transporter-2 inhibitor (SGLT2i), reduces the risk of hospitalization for heart failure (HHF) by 35%, on top of standard of care in patients with type 2 diabetes (T2D) and established CV disease (CVD). The EMPagliflozin compaRative effectIveness and SafEty (EMPRISE) study aims to assess empagliflozin's effectiveness, safety, and healthcare utilization in routine care from 08/2014 through 09/2019. In this first interim analysis, we investigated the risk of HHF among T2D patients initiating empagliflozin vs. sitagliptin, a dipeptidyl peptidase-4 inhibitor (DPP-4i). Methods: Within two commercial and one federal (Medicare) claims data sources in the U.S., we identified a 1:1 propensity-score (PS) matched cohort of T2D patients ≥18 years initiating empagliflozin or sitagliptin from 08/2014 through 09/2016. The HHF outcome was defined as a HF discharge diagnosis in the primary position (HHF-specific); a broader definition was based on a HF discharge diagnosis in any position (HHF-broad). Hazard ratios (HR) and 95% confidence intervals (CI) were estimated controlling for over 140 baseline characteristics in each data source and pooled by fixed-effects meta-analysis. Results: After PS-matching, we identified 16,443 patient pairs who initiated empagliflozin or sitagliptin. Average age was approximately 59 years, almost 54% of the participants were males, and approximately 25% had records of existing cardiovascular disease. Compared to sitagliptin, the initiation of empagliflozin decreased the risk of HHF-specific by 50% (HR = 0.50; 95% CI = 0.28-0.91), and the risk of HHF-broad by 49% (HR: 0.51;95% CI: 0.39-0.68), over a mean follow-up of 5.3 months. Results were consistent in patients with and without baseline cardiovascular disease, and for both empagliflozin 10 mg or 25mg daily dose; analyses comparing

Background The incidence of opioid-related death in women has increased five-fold over the past decade. For many women, their initial opioid exposure will occur in the setting of routine medical care. Approximately 1 in 3 deliveries in the U.S. is by Cesarean and opioids are commonly prescribed for post-surgical pain management. Objective The objective of this study was to determine the risk that opioid naïve women prescribed opioids after Cesarean delivery will subsequently become consistent prescription opioid users in the year following delivery, and to identify predictors for this behavior. Study Design We identified women in a database of commercial insurance beneficiaries who underwent Cesarean delivery and who were opioid-naïve in the year prior to delivery. To identify persistent users of opioids, we used trajectory models, which group together patients with similar patterns of medication filling during follow-up, based on patterns of opioid dispensing in the year following Cesarean delivery. We then constructed a multivariable logistic regression model to identify independent risk factors for membership in the persistent user group. Results 285 of 80,127 (0.36%, 95% confidence interval 0.32 to 0.40), opioid-naïve women became persistent opioid users (identified using trajectory models based on monthly patterns of opioid dispensing) following Cesarean delivery. Demographics and baseline comorbidity predicted such use with moderate discrimination (c statistic = 0.73). Significant predictors included a history of cocaine abuse (risk 7.41%; adjusted odds ratio 6.11, 95% confidence interval 1.03 to 36.31) and other illicit substance abuse (2.36%; adjusted odds ratio 2.78, 95% confidence interval 1.12 to 6.91), tobacco use (1.45%; adjusted odds ratio 3.04, 95% confidence interval 2.03 to 4.55), back pain (0.69%; adjusted odds ratio 1.74, 95% confidence interval 1.33 to 2.29), migraines (0.91%; adjusted odds ratio 2.14, 95% confidence interval 1.58 to 2.90), antidepressant use (1.34%; adjusted odds ratio 3.19, 95% confidence interval 2.41 to 4.23) and benzodiazepine use (1.99%; adjusted odds ratio 3.72, 95% confidence interval 2.64 to 5.26) in the year prior to Cesarean delivery. Conclusions A very small proportion of opioid-naïve women (approximately 1 in 300) become persistent prescription opioid users following Cesarean delivery. Pre-existing psychiatric comorbidity, certain pain conditions, and substance use/abuse conditions identifiable at the time of initial opioid prescribing were predictors of persistent use.