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Abstract
Background
Channeling bias may occur when a newly marketed drug and an established drug, despite similar indications, are prescribed to patients with different prognostic characteristics (ie, confounding).
Aim
To investigate channeling bias and its impact on relative effectiveness of glucagon-like peptide-1 (GLP-1) analogs versus basal insulin and dipeptidyl peptidase-4 inhibitors (DPP-4i) versus sulfonylurea.
Methods
In the UK Clinical Practice Research Datalink, patients with type 2 diabetes initiating treatment between 2006 and 2015 were included. Analyses were stratified by years since first prescription of GLP-1 and DPP-4i, respectively. The characteristics of GLP-1 versus insulin and DPP-4i versus sulfonylurea initiators were compared over time. After propensity score matching, the relative effectiveness regarding 6-month changes in glycated hemoglobin (HbA1c) and body weight was estimated.
Results
In total, 8,398 GLP-1, 14,807 insulin, 24,481 DPP-4i, and 33,505 sulfonylurea initiators were identified. No major channeling was observed. Considerable overlap in distributions of characteristics allowed for propensity score-matched analyses. Relative effectiveness was similar across time. The overall relative effect of GLP-1 versus insulin showed no difference for HbA1c and relative increase in body weight (3.57 kg [95% confidence interval {CI}: 3.21, 3.92]) for insulin. The overall relative effect of DPP-4i versus sulfonylurea showed relative decrease in HbA1c (−0.34% [95% CI: −0.38, −0.30]) and increase in body weight (1.58 kg [95% CI: 1.38, 1.78]) for sulfonylurea.
Conclusion
No major channeling was identified in the investigated glucose-lowering drugs. Relative effectiveness could be estimated already in the first year after launch and was consistent in the years thereafter.
Acknowledgments
The research leading to these results was conducted as part of the GetReal consortium. For further information, please refer to www.imi-getreal.eu. This article only reflects the personal views of the stated authors. The authors thank Vinay Mehta, Center for Observational & Real World Evidence (CORE), Merck Research Labs, North Wales, PA, USA, for his comments on the protocol of this study. Preliminary results of this work were presented as a poster at the 32nd International Conference on Pharmacoepidemiology & Therapeutic Risk Management (ICPE) in Dublin (August 25–28, 2016).
Disclosure
The work leading to these results has received support from the Innovative Medicines Initiative Joint Undertaking (IMI JU) under grant agreement number (115546), resources of which are composed of financial contribution from the European Union’s Seventh Framework Programme (FP7/2007–2013) and the European Federation of Pharmaceutical Industries and Association (EFPIA) companies in kind contribution. In addition, as a special form of the IMI JU grant, University Medical Center, Utrecht, the Netherlands, received a direct financial contribution from Novo Nordisk A/S to support work on this article. MZA, BLT, and EA belong to EFPIA member companies in the IMI JU, and costs related to their part in the research were carried by the respective company as in kind contribution under the IMI JU scheme.
MZA is employed by Novo Nordisk A/S as a postdoc in the IMI GetReal project. BLT and EA are employed by Novo Nordisk A/S and are shareholders in Novo Nordisk A/S. RHHG, MSA, and OHK have no conflicts of interest. The authors report no other conflicts of interest in this work.
Author contributions
MZA, RHHG, MSA and OHK conceived the study. MZA did the coding with inputs from BLT and EA. All authors analyzed data and interpreted the results. MZA drafted the manuscript. All authors revised the manuscript. All authors read and approved the final manuscript and agreed to be accountable for all aspects of the work.