Emerging evidence, as reported by the American Academy of Ophthalmology, suggests that glycemic surveillance should be considered for all patients undergoing teprotumumab therapy for thyroid eye disease (TED), regardless of their baseline metabolic status. Findings from a recent retrospective analysis conducted at Massachusetts Eye and Ear indicate that the drug may adversely affect glucose control even in individuals without prior dysglycemia.
Study Overview
The study, led by Ha and colleagues and published in Ophthalmic Plastic and Reconstructive Surgery (2026), evaluated longitudinal changes in hemoglobin A1c (HbA1c) among 71 patients treated with teprotumumab. Participants were stratified at baseline as normoglycemic (HbA1c ≤5.6%), prediabetic (5.7–6.4%), or diabetic (≥6.5%). The median follow-up period extended to approximately 28 months after treatment initiation, allowing for assessment of both immediate and longer-term glycemic effects.
Key Findings
Worsening glycemic control—defined as either an HbA1c rise of at least 0.5% or progression to a higher glycemic category—was common across all patient groups. The incidence was highest among those with diabetes, affecting 90% of this subgroup. However, the effect was not limited to those with preexisting metabolic disease: 50% of patients with prediabetes and 44% of those with normal baseline HbA1c also demonstrated deterioration in glycemic status.
The magnitude and timing of HbA1c elevation differed by baseline category. Patients with diabetes experienced the largest and most rapid increase, with a median rise of 1.4% peaking at roughly 4.8 months. In comparison, patients with prediabetes showed a more modest increase of 0.5% at around 7.7 months, while normoglycemic individuals had a smaller rise of 0.3% that peaked later, at approximately 13 months.
Clinical management implications were notable. Among diabetic patients, 60% required initiation or escalation of glucose-lowering therapy during treatment. This need was less frequent in prediabetic patients (30%) and rare in normoglycemic individuals (about 2–3%). Importantly, recovery to baseline glycemic levels was least likely among patients with diabetes, with only one-third returning to their pre-treatment HbA1c. In contrast, recovery rates were higher in prediabetic patients (approximately 75%) and modest in normoglycemic individuals (around 35%).
Safety and Treatment Continuation
Although most patients (65 of 71) completed the full eight-infusion course of teprotumumab, treatment discontinuation due to hyperglycemia occurred in a small number of cases. These findings highlight that while the therapy is generally manageable, metabolic side effects can occasionally necessitate early cessation.
Study Limitations
The authors acknowledge several limitations. The retrospective design introduces the possibility of selection bias, particularly since individuals with poorly controlled diabetes were less likely to be prescribed teprotumumab. As a result, the study may underestimate the drug’s glycemic impact in higher-risk populations. Additionally, HbA1c measurements were not collected at uniform time intervals, which may reduce precision in determining the timing of peak glycemic changes.
Clinical Implications
These results reinforce prior observations linking teprotumumab to hyperglycemia but extend understanding by demonstrating that risk is not confined to patients with known metabolic disease. Notably, the earlier onset and greater magnitude of HbA1c elevation in patients with diabetes suggest a need for more intensive early monitoring in this group. However, the substantial proportion of normoglycemic patients experiencing deterioration underscores that baseline status alone should not guide monitoring decisions.
Takeaway
A proactive, risk-stratified approach to glucose monitoring is warranted for all patients receiving teprotumumab. Collaboration with primary care providers or endocrinologists may help optimize outcomes, particularly for those with preexisting glycemic abnormalities. Routine HbA1c assessment both during and after therapy appears essential to detect and manage treatment-related metabolic changes effectively.
