GLP-1 Receptor Agonist Switching Patterns 2018–2025: What Semaglutide Persistence Data Means for Peptide Therapy Patients

If you are considering semaglutide or another GLP-1 receptor agonist for weight management or metabolic health, one of the most practical questions you can ask is: *how often do patients actually stay on the medication they start with?* A newly published real-world study from Poland's largest private healthcare network provides some of the most granular switching data available to date—and the findings have direct implications for how physicians like me counsel patients before initiating peptide therapy.

Łupina, Dziewierz, Janczura, and Siudak conducted a retrospective analysis of GLP-1 receptor agonist (GLP-1 RA) prescription records from the LUX MED network spanning 2018 through 2025. The cohort included **42,423 patients** who filled more than one GLP-1 RA prescription, making this one of the largest real-world GLP-1 persistence datasets published to date. "Switching" was defined as any change in agent between consecutive prescriptions.

The primary analysis used a sophisticated transition-level discrete-time hazard model, meaning each prescription-to-prescription interval was treated as an independent observation. This approach corrects for a common flaw in simpler switching studies: it accounts for *how many opportunities* a patient had to switch and adjusts for the calendar year in which the switch occurred. Current-therapy switching odds were benchmarked against subcutaneous semaglutide—the agent most relevant to my patients.

Published ahead of print in *Acta Diabetologica* (2026), the study was approved under the Declaration of Helsinki and represents hypothesis-generating, observational evidence.

This study matters because switching is not a neutral event. Every agent change introduces a new titration schedule, a new side-effect profile to manage, and potential gaps in metabolic benefit. The fact that nearly one in three GLP-1 RA users switched at least once underscores that **medication selection, patient education, and proactive side-effect management are foundational to durable outcomes**.

The strong calendar-time effect—where tirzepatide uptake surged following market availability—tells a familiar story in peptide medicine: patients and prescribers respond quickly to emerging efficacy data. This has direct relevance to how I structure initial consultations. Setting realistic expectations about the therapeutic landscape, including the possibility that a newer or more personalized option may become available, helps patients make informed decisions rather than reactive ones.

The liraglutide finding warrants interpretive caution. Its very low switching odds almost certainly reflect **era effects**: liraglutide dominated earlier years of the dataset when fewer alternatives existed, so patients on liraglutide had fewer agents to switch *to*. The model adjusted for calendar time, but residual confounding by era is acknowledged by the authors themselves.

If you are evaluating whether to start semaglutide or a related peptide, this research reinforces several practical points:

The authors appropriately note several constraints. **Reasons for switching were not captured**—whether driven by side effects, cost, supply issues, or physician preference remains unknown. The dataset is drawn from a single private-sector Polish network, which may limit generalizability to publicly insured or North American populations. Additionally, while the discrete-time hazard model is methodologically rigorous, residual confounding by indication and by unmeasured patient characteristics cannot be excluded. The study is explicitly **hypothesis-generating** and should not be used to rank agents by tolerability without supporting clinical trial data.