Skip to content
This GLP
← Research
Evidence

Do GLP-1 Drugs Prevent Diabetic Foot Ulcers? The Database Cannot Say

Diabetic foot took up half as much of the GLP-1 adverse event pile as of the comparison pile. That reads as protective until you notice what the method does. A reporting database can find harm appearing too often, and it can never find harm missing.

Ruth Alvarez9 min read
Share of each drug’s report pile, per 1,000 reportsGLP-1 drugs — 1,819 reports6.38other diabetes drugs — 17,20611.31Reporting ratio 0.56 (0.54 to 0.59)The method only runs one wayAbove the expected share is a reason to investigate.Below it has too many ordinary explanations to be a finding.

Nobody knows, and the study usually cited for it cannot say. Diabetic foot complications made up 6.38 of every 1,000 GLP-1 adverse event reports against 11.31 per 1,000 for other diabetes drugs, a ratio of 0.56 [1]. That is a share of a report pile, not a rate in patients. The question underneath is a good one, because people with diabetes lose toes and feet to ulcers that begin as small wounds. The trouble is that the instrument used here answers only whether harm appears more often than expected. It cannot be turned around and asked whether something appears less often than it should, which is the same asymmetry running under the dose-error reports.

What was measured

The FDA’s adverse event database was queried for every report naming a GLP-1 drug between 2005 and 2024, and for every report naming one of the other diabetes drug classes. [1] There were 1,819 of the former and 17,206 of the latter. Diabetic foot complications made up 6.38 per thousand of the GLP-1 pile. The comparison pile carried 11.31 per thousand. That gives a proportional reporting ratio of 0.56, with an interval from 0.54 to 0.59 narrow enough to look like certainty about something.

Semaglutide came out at 0.45, dulaglutide at 0.49 and liraglutide at 0.30, and the pattern held across sensitivity analyses. The consistency is genuine. What it is consistent about is the part that needs care — and the mechanics of the database itself we have covered in a separate piece.

The direction the method runs

A larger evidence map across several safety databases makes the same point from the other end [2]. What that kind of mapping surfaces is the terms reported unusually often — dosing errors, gastrointestinal events, injection-site problems — because those are the only ones the arithmetic can find. Nothing in it is built to notice a complication that failed to turn up at all.

Disproportionality analysis was designed to find signals: to notice when a drug’s reports contain a strange term far more often than the background does, so that somebody can go and investigate properly. Running above the expected share is a reason to look. Running below it is not a finding, because the things that suppress a share are so numerous and so ordinary that no ratio can separate them.

This is the same asymmetry that makes an absent result different from a negative one, arriving through a different door.

The genetic half

The authors also ran a Mendelian randomization, using inherited variation in the GLP-1 receptor gene as a stand-in for the drug, and report that it broadly agreed with the database analysis.

That is a genuinely independent instrument, which is worth more than another pass through the same reports. It also answers a different question. Small lifelong differences in a receptor are not eighteen months of a therapeutic dose in a fifty-year-old. A method that models a lifetime cannot tell you what happens after a year, much as a model trained on one thing keeps getting read as evidence about another.

What would settle it

A cohort with feet in it. Count the people taking each drug, examine them, and record the ulcers — the trial evidence already exists for wound-adjacent outcomes in other conditions, so the design is not exotic.

Until then, the honest summary is the one the authors themselves wrote: preliminary, requiring prospective validation. Weight loss and better glucose control ought to help a diabetic foot, so the hypothesis is reasonable on its face. Reasonable is not the same as demonstrated, and a large database is not the same as a large study.

Frequently asked

Do GLP-1 drugs protect against diabetic foot ulcers?
This analysis cannot answer that. It compares how large a share of each drug's adverse event reports mentioned diabetic foot, which depends on what else got reported alongside.
What is a proportional reporting ratio?
The share of one drug's reports naming a given problem, divided by that share for comparison drugs. Its denominator is reports rather than patients, so it measures reporting rather than risk.
Why can it find harm but not safety?
An unusually high share is a reason to investigate. A low share has too many ordinary explanations — chiefly that other symptoms crowded into the same pile — for any of them to be ruled out.
Does the genetic analysis settle it?
No. It uses inherited variation in the receptor as a proxy, which models a lifetime of small differences rather than a year or two of a therapeutic dose.

Sources

  1. [1] Zhang T, et al. (2026). Assessing the Association Between GLP-1 Receptor Agonists and Diabetic Foot Complications Using Real-World Pharmacovigilance Database and Mendelian Randomization The International Journal of Lower Extremity Wounds. PMID 42726083
  2. [2] Ren L, et al. (2026). Postmarketing Safety Signals and Medication-Use Risks of GLP-1-Based Therapies in Diabetes and Obesity: A Multi-Source Pharmacovigilance and Regulatory Evidence-Mapping Study Diabetes, Obesity and Metabolism. PMID 42687799

Where to get it

Best GLP-1 injections

Every injectable seller we can verify, with the price each one publishes and an honest read of what the trials measured.

Compare providers →

More in Evidence