Cardiovascular safety of linagliptin compared with other oral glucose-lowering agents in patients with type 2 diabetes: A sequential monitoring programme in routine care

Epidemiological surveillance of drug safety using cumulative sequential analysis in electronic healthcare data

BACKGROUND

Methods for safety signal detection in electronic healthcare data analysing data sequentially are being developed to meet the limitations of spontaneous reporting systems.

OBJECTIVES

This study aims to provide an overview of the literature on sequential analysis of electronic healthcare data and describe the development and testing of a novel epidemiological surveillance system.

METHODS

We searched Medline, Embase, PubMed, Scopus, Web of Science, and the Cochrane Library applying similar in- and exclusion criteria as those of a previous systematic review. The proposed system consisted of repeated cohort studies and was tested in an emulated prospective setting. Two signal evaluations were performed with several sensitivity analyses and a target trial emulation.

FINDINGS

In the literature, 11 studies analysed the data sequentially of which two applied traditional epidemiological methods. Epidemiological surveillance of several exposures and outcomes can be successfully conducted with the newly proposed sequential analysis of electronic healthcare data. Signal evaluation studies confirmed the results of the system.

CONCLUSIONS

Very few studies in the literature analysed data at multiple time points, although this seems to be a prerequisite for testing the methods in a realistic setting. We demonstrated the feasibility of a sequential surveillance system using electronic healthcare data.

Surveillance of Antidepressant Safety (SADS): Active Signal Detection of Serious Medical Events Following SSRI and SNRI Initiation Using Big Healthcare Data

Introduction

The current process for generating evidence in pharmacovigilance has several limitations, which often lead to delays in the evaluation of drug-associated risks.

Objectives

In this study, we proposed and tested a near real-time epidemiological surveillance system using sequential, cumulative analyses focusing on the detection and preliminary risk quantification of potential safety signals following initiation of selective serotonin reuptake inhibitors (SSRIs) and serotonin-norepinephrine reuptake inhibitors (SNRIs).

Methods

We emulated an active surveillance system in an historical setting by conducting repeated annual cohort studies using nationwide Danish healthcare data (1996–2016). Outcomes were selected from the European Medicines Agency's Designated Medical Event list, summaries of product characteristics, and the literature. We followed patients for a maximum of 6 months from treatment initiation to the event of interest or censoring. We performed Cox regression analyses adjusted for standard sets of covariates. Potential safety signals were visualized using heat maps and cumulative hazard ratio (HR) plots over time.

Results

In the total study population, 969,667 new users were included and followed for 461,506 person-years. We detected potential safety signals with incidence rates as low as 0.9 per 10,000 person-years. Having eight different exposure drugs and 51 medical events, we identified 31 unique combinations of potential safety signals with a positive association to the event of interest in the exposed group. We proposed that these signals were designated for further evaluation once they appeared in a prospective setting. In total, 21 (67.7%) of these were not present in the current summaries of product characteristics.

Conclusion

The study demonstrated the feasibility of performing epidemiological surveillance using sequential, cumulative analyses. Larger populations are needed to evaluate rare events and infrequently used antidepressants.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40264-021-01110-x.

The use of real-world evidence in ICER's scoping process and clinical evidence assessments

BACKGROUND: There has been growing interest in using real-world evidence (RWE) for health technology assessment (HTA) in the United States. The Institute for Clinical and Economic Review (ICER) is an independent U.S.-based HTA organization that focuses primarily on pharmaceuticals. RWE is used to inform ICER's scoping and comparative clinical effectiveness (CCE) assessments, but the extent to which it is used has not been quantified. OBJECTIVE: To systematically evaluate use of RWE in the scoping and CCE assessment sections of the ICER HTA reports on pharmaceuticals. METHODS: We reviewed all ICER reports of pharmaceuticals published between January 2014 and June 2019. We examined the average number of instances and the proportion of RWE use in the scoping documents to inform the population, intervention, comparator, outcome, setting, or timing (PICOTS) elements of the appraisal. We also examined the average number of instances and the proportion of RWE use in the CCE assessments to inform effectiveness, safety, or treatment patterns. Finally, we evaluated use of RWE in clinical guidelines that were cited in the CCE assessments. RESULTS: In ICER scoping documents, the mean (SD) number of instances of RWE use was 3.8 (3.7) per document (55% for outcomes, 20% for population, 14% for comparator, 11% for intervention, and 0% for timing and setting). In ICER CCE assessments, the mean (SD) number of instances per assessment was 0.7 (0.5) per drug (53% for effectiveness, 44% for safety, and 3% for treatment patterns). In clinical guidelines used in ICER reports, the mean (SD) number of instances of RWE use was 1.6 (2.3) per drug per guideline (41% for effectiveness, 30% for safety, and 29% for treatment patterns). CONCLUSIONS: RWE was frequently used in the ICER scoping process, particularly to inform selection of outcomes. RWE was used infrequently in ICER CCE assessments, while more often used to inform effectiveness, safety, and treatment patterns in relevant clinical guidelines. There are opportunities to increase the use of RWE in U.S. HTA processes. DISCLOSURES: This study was supported by the Health Tech Fund, University of Washington School of Pharmacy, which was created through unrestricted support from several health care industry companies. Veenstra and Carlson report grant support from the Institute for Clinical and Economic Review outside the submitted work. Carlson reports personal fees from Bayer, Allergan, and Galderma outside the submitted work. Jiao, Lee, and Devine report no support outside the submitted work.

Using Real-World Data to Predict Findings of an Ongoing Phase IV Cardiovascular Outcome Trial: Cardiovascular Safety of Linagliptin Versus Glimepiride

OBJECTIVE

Using real-world data (RWD) from three U.S. claims data sets, we aim to predict the findings of the CARdiovascular Outcome Trial of LINAgliptin Versus Glimepiride in Type 2 Diabetes (CAROLINA) comparing linagliptin versus glimepiride in patients with type 2 diabetes (T2D) at increased cardiovascular risk by using a novel framework that requires passing prespecified validity checks before analyzing the primary outcome.

RESEARCH DESIGN AND METHODS

Within Medicare and two commercial claims data sets (May 2011-September 2015), we identified a 1:1 propensity score-matched (PSM) cohort of T2D patients 40-85 years old at increased cardiovascular risk who initiated linagliptin or glimepiride by adapting eligibility criteria from CAROLINA. PSM was used to balance >120 confounders. Validity checks included the evaluation of expected power, covariate balance, and two control outcomes for which we expected a positive association and a null finding. We registered the protocol (NCT03648424, ClinicalTrials.gov) before evaluating the composite cardiovascular outcome based on CAROLINA's primary end point. Hazard ratios (HR) and 95% CIs were estimated in each data source and pooled with a fixed-effects meta-analysis.

RESULTS

We identified 24,131 PSM pairs of linagliptin and glimepiride initiators with sufficient power for noninferiority (>98%). Exposure groups achieved excellent covariate balance, including key laboratory results, and expected associations between glimepiride and hypoglycemia (HR 2.38 [95% CI 1.79-3.13]) and between linagliptin and end-stage renal disease (HR 1.08 [0.66-1.79]) were replicated. Linagliptin was associated with a 9% decreased risk in the composite cardiovascular outcome with a CI including the null (HR 0.91 [0.79-1.05]), in line with noninferiority.

CONCLUSIONS

In a nonrandomized RWD study, we found that linagliptin has noninferior risk of a composite cardiovascular outcome compared with glimepiride.