ArticlePloS one2026
The association between long-term opioid therapy and composite infection-related dental outcomes.
Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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14 authors.
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Abstract
backgroundThe Food and Drug Administration's warning that transmucosal buprenorphine, a partial opioid agonist used to treat opioid use disorder and chronic pain, may cause dental disease opens questions about potential class-wide adverse effects involving more widely prescribed opioid analgesics.
methodsThis was a retrospective matched national cohort study of patients in care at the Department of Veterans Affairs (VA) between October 2010-September 2019. Patients prescribed LTOT were matched 1:2 to patients not prescribed LTOT on age, sex, service region, and VA dental coverage. Cox regression models estimated the association between LTOT and a composite infection-related dental outcome (CIDO). Sensitivity analyses excluded patients with cancer, restricted to patients with comprehensive dental coverage, and to patients with ≥180 days of follow-up time, respectively.
resultsThe cohort comprised 2,173,435 patients including 787,825 (36%) receiving LTOT; 612,101 (28%) experienced CIDO. In both simple and multivariable regression models, LTOT exposure was associated with greater CIDO risk; HR (95% CI) =1.24 (1.23, 1.25); aHR (95% CI) =1.08 (1.07, 1.08), respectively; p < 0.001. Sensitivity analyses showed similar results except among patients with full dental coverage for whom CIDO rates were substantially higher and LTOT was not statistically significantly associated with risk.
conclusionshe observed positive association between LTOT and CIDO in this large VA sample may inform patient-provider discussions and decision-making around use of LTOT. High CIDO rates among patients with full VA dental coverage may reflect their unique vulnerability to dental infection associated with service-related dental or disabling conditions. Limitations include risk for ascertainment bias, unclear generalizability to a broader clinical population, and the potential for residual confounding.
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