Avoidable flaws in observational analyses: an application to statins and cancer

The increasing availability of large healthcare databases is fueling an intense debate on whether real-world data should play a role in the assessment of the benefit–risk of medical treatments. In many observational studies, for example, statin users were found to have a substantially lower risk of cancer than in meta-analyses of randomized trials. Although such discrepancies are often attributed to a lack of randomization in the observational studies, they might be explained by flaws that can be avoided by explicitly emulating a target trial (the randomized trial that would answer the question of interest). Using the electronic health records of 733,804 UK adults, we emulated a target trial of statins and cancer and compared our estimates with those obtained using previously applied analytic approaches. Over the 10-yr follow-up, 28,408 individuals developed cancer. Under the target trial approach, estimated observational analogs of intention-to-treat and per-protocol 10-yr cancer-free survival differences were −0.5% (95% confidence interval (CI) −1.0%, 0.0%) and −0.3% (95% CI −1.5%, 0.5%), respectively. By contrast, previous analytic approaches yielded estimates that appeared to be strongly protective. Our findings highlight the importance of explicitly emulating a target trial to reduce bias in the effect estimates derived from observational analyses

Emulating a target trial in case-control designs: an application to statins and colorectal cancer

BACKGROUND: Previous case-control studies have reported a strong association between statin use and lower cancer risk. It is unclear whether this association reflects a benefit of statins or is the result of design decisions that cannot be mapped to a (hypothetical) target trial (that would answer the question of interest). METHODS: We outlined the protocol of a target trial to estimate the effect of statins on colorectal cancer incidence among adults with low-density lipoprotein (LDL) cholesterol below 5 mmol/L. We then emulated the target trial using linked electronic health records of 752 469 eligible UK adults (CALIBER 1999-2016) under both a cohort design and a case-control sampling of the cohort. We used pooled logistic regression to estimate intention-to-treat and per-protocol effects of statins on colorectal cancer, with adjustment for baseline and time-varying risk factors via inverse-probability weighting. Finally, we compared our case-control effect estimates with those obtained using previous case-control procedures. RESULTS: Over the 6-year follow-up, 3596 individuals developed colorectal cancer. Estimated intention-to-treat and per-protocol hazard ratios were 1.00 (95% confidence interval [CI]: 0.87, 1.16) and 0.90 (95% CI: 0.71, 1.12), respectively. As expected, adequate case-control sampling yielded the same estimates. By contrast, previous case-control analytical approaches yielded estimates that appeared strongly protective (odds ratio 0.57, 95% CI: 0.36, 0.91, for ≥5 vs. <5 years of statin use). CONCLUSIONS: Our study demonstrates how to explicitly emulate a target trial using case-control data to reduce discrepancies between observational and randomized trial evidence. This approach may inform future case-control analyses for comparative effectiveness research

Exploration of Burnout, Emotional Thriving, and Emotional Recovery in an Academic Medical Center: a Mixed Methods Quality Improvement Project

Introduction: Healthcare provider burnout, an indicator of wellbeing, impacts patient safety, provider distress, and employee turnover. In this mixed methods, multi-site quality improvement study conducted \u3c6 months prior to the start of the COVID-19 pandemic, we assessed employee wellbeing in a large clinical department. Methods: Wellbeing surveys were sent electronically to Department of Medicine clinicians, researchers, administrators, and staff from August-September 2019 assessing perceptions of Burnout, Emotional Thriving (ET), and Emotional Recovery (ER). Qualitative responses were reviewed for themes using mixed inductive-deductive analysis. The initial coding was done by small teams with consensus obtained through large group discussions. This study was IRB-approved as non-human subjects research. Results: Of the 671 respondents, 54% met criteria for burnout (Burnout+), 65% for ER (ER+), and 61% for ET (ET+). ER+ and ET+ were present in nearly half of Burnout+ respondents (53% and 43% respectively). Several themes emerged in the qualitative analysis: workload and expectations; tangible resources; work culture; and salary/benefits, with leadership influencing each of the domains. Conclusion: Burnout, ET, and ER can co-exist within the same individual. Employee wellbeing is not adequately reflected by the binary of whether or not an individual is experiencing burnout. All employees at academic medical centers, including staff, researchers, and clinicians, are vulnerable to the same workplace factors driving burnout. Our findings have been used to target areas of intervention during the COVID-19 pandemic at our institution. We propose that other academic medical centers may have similar workplace stressors that they could assess and target for improvement