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BackgroundMultiple features in the presentation of randomized controlled trial (RCT) results are known to influence comprehension and interpretation. We aimed to compare interpretation of cancer RCTs with time-to-event outcomes when the reported treatment effect measure is the hazard ratio (HR), difference in restricted mean survival times (RMSTD), or both (HR+RMSTD). We also assessed the prevalence of misinterpretation of the HR.MethodsWe carried out a randomized experiment. We selected 15 cancer RCTs with statistically significant treatment effects for the primary outcome. We masked each abstract and created three versions reporting either the HR, RMSTD, or HR+RMSTD. We randomized corresponding authors of RCTs and medical residents and fellows to one of 15 abstracts and one of 3 versions. We asked how beneficial the experimental treatment was (0–10 Likert scale). All participants answered a multiple-choice question about interpretation of the HR. Participants were unaware of the study purpose.ResultsWe randomly allocated 160 participants to evaluate an abstract reporting the HR, 154 to the RMSTD, and 155 to both HR+RMSTD. The mean Likert score was statistically significantly lower in the RMSTD group when compared with the HR group (mean difference −0.8, 95% confidence interval, −1.3 to −0.4, P < 0.01) and when compared with the HR+RMSTD group (difference −0.6, −1.1 to −0.1, P = 0.05). In all, 47.2% (42.7%−51.8%) of participants misinterpreted the HR, with 40% equating it with a reduction in absolute risk.ConclusionMisinterpretation of the HR is common. Participants judged experimental treatments to be less beneficial when presented with RMSTD when compared with HR. We recommend that authors present RMST-based measures alongside the HR in reports of RCT results.

Aims Frailty is associated with an increased risk of all-cause mortality and cardiovascular (CV) events. Limited data exist from the modern era of CV prevention on the relationship between frailty and CV mortality. We hypothesized that frailty is associated with an increased risk of CV mortality. Methods and results All US Veterans aged ≥65 years who were regular users of Veteran Affairs care from 2002 to 2017 were included. Frailty was defined using a 31-item previously validated frailty index, ranging from 0 to 1. The primary outcome was CV mortality with secondary analyses examining the relationship between frailty and CV events (myocardial infarction, stroke, revascularization). Survival analysis models were adjusted for age, sex, ethnicity, geographic region, smoking, hyperlipidaemia, statin use, and blood pressure medication use. There were 3 068 439 US Veterans included in the analysis. Mean age was 74.1 ± 5.8 years in 2002, 76.0 ± 8.3 years in 2014, 98% male, and 87.5% White. In 2002, the median (interquartile range) frailty score was 0.16 (0.10–0.23). This increased and stabilized to 0.19 (0.10–0.32) for 2006–14. The presence of frailty was associated with an increased risk of CV mortality at every stage of frailty. Frailty was associated with an increased risk of myocardial infarction and stroke, but not revascularization. Conclusion In this population, both the presence and severity of frailty are tightly correlated with CV death, independent of underlying CV disease. This study is the largest and most contemporary evaluation of the relationship between frailty and CV mortality to date. Further work is needed to understand how this risk can be diminished. Key Question Can an electronic frailty index identify adults aged 65 and older who are at risk of CV mortality and major CV events? Key Finding Among 3 068 439 US Veterans aged 65 and older, frailty was associated with an increased risk of CV mortality at every level of frailty. Frailty was also associated with an increased risk of myocardial infarction and stroke, but not revascularization. Take Home Message Both the presence and severity of frailty are associated with CV mortality and major CV events, independent of underlying CV disease.

Background The risk factors associated with the stages of Coronavirus Disease-2019 (COVID-19) disease progression are not well known. We aim to identify risk factors specific to each state of COVID-19 progression from SARS-CoV-2 infection through death. Methods and results We included 648,202 participants from the Veteran Affairs Million Veteran Program (2011-). We identified characteristics and 1,809 ICD code-based phenotypes from the electronic health record. We used logistic regression to examine the association of age, sex, body mass index (BMI), race, and prevalent phenotypes to the stages of COVID-19 disease progression: infection, hospitalization, intensive care unit (ICU) admission, and 30-day mortality (separate models for each). Models were adjusted for age, sex, race, ethnicity, number of visit months and ICD codes, state infection rate and controlled for multiple testing using false discovery rate (≤0.1). As of August 10, 2020, 5,929 individuals were SARS-CoV-2 positive and among those, 1,463 (25%) were hospitalized, 579 (10%) were in ICU, and 398 (7%) died. We observed a lower risk in women vs. men for ICU and mortality (Odds Ratio (95% CI): 0.48 (0.30–0.76) and 0.59 (0.31–1.15), respectively) and a higher risk in Black vs. Other race patients for hospitalization and ICU (OR (95%CI): 1.53 (1.32–1.77) and 1.63 (1.32–2.02), respectively). We observed an increased risk of all COVID-19 disease states with older age and BMI ≥35 vs. 20–24 kg/m2. Renal failure, respiratory failure, morbid obesity, acid-base balance disorder, white blood cell diseases, hydronephrosis and bacterial infections were associated with an increased risk of ICU admissions; sepsis, chronic skin ulcers, acid-base balance disorder and acidosis were associated with mortality. Conclusions Older age, higher BMI, males and patients with a history of respiratory, kidney, bacterial or metabolic comorbidities experienced greater COVID-19 severity. Future studies to investigate the underlying mechanisms associated with these phenotype clusters and COVID-19 are warranted.

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