Invited Commentary: The Prevalent New-User Design in Pharmacoepidemiology-Challenges and Opportunities

Clarifying the causal contrast: An empirical example applying the prevalent new user study design

PURPOSE

The prevalent new user design extends the active comparator new user design to include patients switching to a treatment of interest from a comparator. We examined the impact of adding "switchers" to incident new users on the estimated hazard ratio (HR) of hospitalized heart failure.

METHODS

Using MarketScan claims data (2000-2014), we estimated HRs of hospitalized heart failure between patients initiating GLP-1 receptor agonists (GLP-1 RA) and sulfonylureas (SU). We considered three estimands: (1) the effect of incident new use; (2) the effect of switching; and (3) the effect of incident new use or switching, combining the two population. We used time-conditional propensity scores (TCPS) and time-stratified standardized morbidity ratio (SMR) weighting to adjust for confounding.

RESULTS

We identified 76 179 GLP-1 RA new users, of which 12% were direct switchers (within 30 days) from SU. Among incident new users, GLP-1 RA was protective against heart failure (adjHRSMR = 0.74 [0.69, 0.80]). Among switchers, GLP-1 RA was not protective (adjHRSMR = 0.99 [0.83, 1.18]). Results in the combined population were largely driven by the incident new users, with GLP-1 RA having a protective effect (adjHRSMR = 0.77 [0.72, 0.83]). Results using TCPS were consistent with those estimated using SMR weighting.

CONCLUSIONS

When analyses were conducted only among incident new users, GLP-1 RA had a protective effect. However, among switchers from SU to GLP-1 RA, the effect estimates substantially shifted toward the null. Combining patients with varying treatment histories can result in poor confounding control and camouflage important heterogeneity.

Sodium-glucose cotransporter 2 inhibitors and the risk of venous thromboembolism: A population-based cohort study

AIMS

The cardiovascular benefits of sodium-glucose cotransporter 2 inhibitors (SGLT2Is) result from their complex impact on coronary and arterial vessels. However, their effect on veins and the risk of venous thromboembolism (VTE) remains unclear. Meta-analysis of trials has suggested no significant change in risk, but observational studies on the topic are scarce. Our objective was to determine if the use of SGLT2Is, compared to the use of dipeptidyl peptidase 4 inhibitors (DPP-4Is), is associated with the risk of VTE among patients with type 2 diabetes.

METHODS

Using the Clinical Practice Research Datalink linked to hospitalization and vital statistics databases, we conducted a retrospective cohort study using a prevalent new-user design. SGLT2Is were matched to DPP-4I users on calendar time, diabetes treatment intensity, duration of previous DPP-4I use and time-conditional high-dimensional propensity score. Cox proportional hazard models estimated the hazard ratio (HR) for VTE with SGLT2Is versus DPP-4Is.

RESULTS

SGLT2I use was not associated with an increased risk of VTE (HR 0.65, 95% confidence interval [CI] 0.34 to 1.25). This finding was consistent among prevalent (HR 0.47, 95% CI 0.16 to 1.42) and incident (HR 0.75, 95% CI 0.33 to 1.72) new users.

CONCLUSIONS

We found that SGLT2Is were not associated with an increased risk of VTE compared to DPP-4Is. Although we observed a numerically decreased risk of VTE with SGLT2Is, estimates were accompanied by wide 95% CIs. Nonetheless, given the morbidity associated with VTE, our results provide some reassurance regarding the safety of SGLT2Is with respect to VTE.

Core concepts in pharmacoepidemiology: Key biases arising in pharmacoepidemiologic studies

Pharmacoepidemiology has an increasingly important role in informing and improving clinical practice, drug regulation, and health policy. Therefore, unrecognized biases in pharmacoepidemiologic studies can have major implications when study findings are translated to the real world. We propose a simple taxonomy for researchers to use as a starting point when thinking through some of the most pervasive biases in pharmacoepidemiology. We organize this discussion according to biases best assessed with respect to the study population (including confounding by indication, channeling bias, healthy user bias, and protopathic bias), the study design (including prevalent user bias and immortal time bias), and the data source (including misclassification bias and missing data/loss to follow up). This tutorial defines, provides a curated list of recommended references, and illustrates through relevant case examples these key biases to consider when planning, conducting, or evaluating pharmacoepidemiologic studies.

Statin use is associated with lower risk of dementia in stroke patients: a community-based cohort study with inverse probability weighted marginal structural model analysis

Current evidence is inconclusive on cognitive benefits or harms of statins among stroke patients, who have high risk of dementia. This observational cohort study investigated the association between statin use and post-stroke dementia using data from the Clinical Practice Research Datalink. Patients without prior dementia who had an incident stroke but received no statins in the preceding year were followed for up to 10 years. We used inverse probability weighted marginal structural models to estimate observational analogues of intention-to-treat (ITT, statin initiation vs. no initiation) and per-protocol (PP, sustained statin use vs. no use) effects on the risk of dementia. To explore potential impact of unmeasured confounding, we examined the risks of coronary heart disease (CHD, positive control outcome), fracture and peptic ulcer (negative control outcomes). In 18,577 statin initiators and 14,613 non-initiators (mean follow-up of 4.2 years), the adjusted hazard ratio (aHR) for dementia was 0.70 (95% confidence interval [CI] 0.64–0.75) in ITT analysis and 0.55 (95% CI 0.50–0.62) in PP analysis. The corresponding aHR_ITT and aHR_PP were 0.87 (95% CI 0.79–0.95) and 0.70 (95% CI 0.62–0.80) for CHD, 1.03 (95% CI 0.82–1.29) and 1.09 (95% CI 0.77–1.54) for peptic ulcer, and 0.88 (95% CI 0.80–0.96) and 0.86 (95% CI 0.75–0.98) for fracture. Statin initiation after stroke was associated with lower risk of dementia, with a potentially greater benefit in patients who persisted with statins over time. The observed association of statin use with post-stroke dementia may in part be overestimated due to unmeasured confounding shared with the association between statin use and fracture.

Reporting of abstracts in studies that used routinely collected data for exploring drug treatment effects: a cross-sectional survey

Background

In recent years, studies that used routinely collected data (RCD), such as electronic medical records and administrative claims, for exploring drug treatment effects, including effectiveness and safety, have been increasingly published. Abstracts of such studies represent a highly attended source for busy clinicians or policy-makers, and are important for indexing by literature database. If less clearly presented, they may mislead decisions or indexing. We thus conducted a cross-sectional survey to systematically examine how the abstracts of such studies were reported.

Methods

We searched PubMed to identify all observational studies published in 2018 that used RCD for assessing drug treatment effects. Teams of methods-trained collected data from eligible studies using pilot-tested, standardized forms that were developed and expanded from “The reporting of studies conducted using observational routinely collected health data statement for pharmacoepidemiology” (RECORD-PE) statement. We used descriptive analyses to examine how authors reported data source, study design, data analysis, and interpretation of findings.

Results

A total of 222 studies were included, of which 118 (53.2%) reported type of database used, 17 (7.7%) clearly reported database linkage, and 140 (63.1%) reported coverage of data source. Only 44 (19.8%) studies stated a predefined hypothesis, 127 (57.2%) reported study design, 140 (63.1%) reported statistical models used, 142 (77.6%) reported adjusted estimates, 33 (14.9%) mentioned sensitivity analyses, and 39 (17.6%) made a strong claim about treatment effect. Studies published in top 5 general medicine journals were more likely to report the name of data source (94.7% vs. 67.0%) and study design (100% vs. 53.2%) than those in other journals.

Conclusions

The under-reporting of key methodological features in abstracts of RCD studies was common, which would substantially compromise the indexing of this type of literature and prevent the effective use of study findings. Substantial efforts to improve the reporting of abstracts in these studies are highly warranted.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12874-021-01482-9.