Sage Journals: Discover world-class research

Abstract

Background:

The US Food and Drug Administration (FDA) issued a drug safety communication warning of dental-related adverse events (DAE) reported in patients using buprenorphine films or tablets in January 2022. This study utilized more recent data with a broader dental outcome definition beyond what has been previously reported to provide comprehensive evidence of this risk.

Objective:

Assess the association between buprenorphine use and the risk of DAE among opioid use disorder (OUD) patients.

Design:

A retrospective cohort study.

Methods:

Using the Veradigm-MarketScan® linked dataset, adults aged ⩾18 years with an OUD diagnosis between June 30, 2018, and July 1, 2023, and who met our selection criteria were included. Patients were grouped as: (1) BUP users and (2) non-BUP users (control group). We used Prescription Time Distribution Matching (PTDM) and Inverse Probability Treatment Weighting (IPTW) methods to balance potential confounders between the 2 groups. The primary outcome was dental-related adverse events (DAE). Cox proportional hazards models estimated adjusted hazard ratios (HRs).

Results:

A total of 14 495 OUD adult patients were included. Of these patients, 4199 (28.97%) initiated oral buprenorphine. Among the overall population, most were males, 8742 (60.3%), with an average age of 44.9 years. The absolute risk of DAE was slightly higher among buprenorphine users (2.17%) compared to controls (1.66%). We found an increased risk of DAE in buprenorphine users compared to the control group (adjusted HR, 1.36; 95%CI, 1.04-1.78).

Conclusions:

There is an increased risk of DAE among buprenorphine users compared to non-users after 6 months of follow-up. Although this risk is modest, this finding suggests the need for increased awareness and preventive interventions among these users.

Keywords

buprenorphine dental opioid use disorders adverse events oral health intervention

Introduction

Buprenorphine (BUP), a partial opioid agonist, is 1 of the 3 FDA-approved medications for opioid use disorders (MOUD), alongside naltrexone and methadone.^1,2 Clinical evidence demonstrates that BUP use is associated with reduced opioid-related mortality, lower rates of illicit opioid use, and improved treatment retention, making it integral to the evidence-based management of opioid use disorders (OUD).^3,4 However, the adoption of transmucosal BUP formulations (sublingual films or tablets) has raised unexpected safety concerns regarding dental-related adverse events (DAE). In January 2022, the FDA issued a drug safety communication warning of DAE, such as tooth decay, cavities, oral infections, and tooth loss, reported in patients using BUP films or tablets, including cases reported in individuals without prior dental disease.⁵ These adverse events can arise as early as 2 weeks after initiating treatment, although later-onset cases are also prevalent.⁵ This elevated dental risk in OUD patients receiving BUP may stem from multiple converging biological and behavioral factors.^6,7 One of these includes the anticholinergic properties of many opioids, which could lead to conditions such as xerostomia (dry mouth), which further compromises the protective role of saliva and increases susceptibility to dental caries and oral infections.^6,8

In response to the FDA’s warning, a few pharmacoepidemiologic studies have investigated the potential relationship between BUP use and oral outcomes using real-world data. Tuan et al⁹ found an increased incidence of oral dental events among BUP users compared to non-users. In another study that assessed commercially insured OUD patients initiating BUP, Etminan et al¹⁰ also found an increased risk of dental caries and tooth loss among BUP users. Compared to prior studies, our outcome definition encompassed more dental-related events potentially associated with BUP use, extending beyond earlier definitions that excluded oral conditions such as gingivitis and xerostomia. Our study also incorporates more recent data, beyond the 2002 to 2020 period used in prior studies, to include data through December 2023. Although BUP’s pharmacologic properties have remained stable over time, its use patterns and treatment settings have changed substantially in recent years, with broader adoption in primary care and telehealth expansion following the removal of the X-waiver, and increased treatment uptake among diverse patient populations.¹¹ Evaluating DAE using more recent data allows for a policy-relevant and contemporary assessment of risk under current clinical practice. In addition, by incorporating a broader dental outcome definition, this study captures a wider range of BUP-related dental effects, providing a more comprehensive view of oral safety in real-world use.¹² Hence, our study aims to provide more recent and updated real-world evidence on the comprehensive risk of DAE associated with BUP treatment for OUD patients.

Methods

This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guidelines for cohort studies.¹³ The University of Houston Institutional Review Board (IRB) approved this study after deeming it human subject exempt, given the deidentified nature of the data.

Data Sources

We utilized the Veradigm-MarketScan® linked dataset and included data from January 2018 to December 2023¹⁴ that integrates healthcare utilization and cost data from MarketScan with detailed clinical insights from the Veradigm Network EHR system. This combination ensures that comprehensive administrative data is complemented by clinical details from electronic medical record systems, offering a complete view of medical services and prescribed treatments without data fragmentation. The Veradigm EHR portion consists of de-identified patient records sourced from ambulatory/outpatient primary care and multi-specialty practices. It is structured into multiple subsections, including patient demographic information such as race and ethnicity, patient visit details, laboratory testing orders and results, vitals assessment, and medication prescribed. The MarketScan® portion consists of adjudicated healthcare claims for employees, retirees, and their dependents of over 300 medium and large employers and health plans. Private health insurance plans and Medicare data are included. The database includes claims information from more than 130 payers and describes the health care service use and expenditures for approximately 8.2 million covered employees and family members per year. It is divided into subsections, including inpatient medical claims, outpatient medical claims, outpatient prescription drug claims, and enrollment information. Both datasets are securely linkable through a unique encrypted patient identifier, preserving patient privacy while enabling analyses of healthcare patterns and outcomes.

Study Participants and Selection Criteria

We identified patients with Opioid Use Disorder (OUD) diagnosis using the International Classification of Diseases, 10th edition (ICD-10) diagnosis codes (F11.xx) and included those with at least 1 inpatient claim of OUD or 2 outpatient diagnosis claim of OUD that are greater than 30 days apart between June 30, 2018, and July 1, 2023.¹⁵ We excluded OUD patients without continuous enrollment in the 6-month baseline period, those with prior DAE, and those below 18 years of age.

Study Design and Exposure Status

This was a retrospective, longitudinal, cohort study. We assessed prescription fills and, using the national drug codes (NDC), identified OUD patients who initiated sublingual BUP prescriptions and had ⩾2 fills within the follow-up period.¹⁶ This criterion was applied to ensure inclusion of patients with sustained BUP exposure, as a single fill may reflect non-initiation or administrative claims errors, which could lead to exposure misclassification and dilute the observed association. We then specified 2 exposure groups based on BUP exposure status: (a) BUP cohort and (b) no BUP cohort.

Outcomes

The outcome is DAE, identified based on ICD-10 codes for dental-related problems, including dental caries, xerostomia, periodontitis, gingivitis, and loss of teeth due to caries. In addition to structural dental events, we included functional outcomes such as xerostomia, which may differ in clinical severity but represent an early stage in the same pathophysiologic pathway leading to caries and tooth loss. Excluding it may risk understating the full spectrum of BUP-associated dental harm. A comprehensive list of dental-related outcomes considered in this study can be found on the supplementary page (Table S1). DAE was defined as having any claim of these codes in the 6-month follow-up period. A 6-month follow-up period was selected to capture the early to intermediate onset of BUP-related dental adverse events, consistent with the onset patterns reported in clinical and pharmacovigilance data.¹⁷ This timeframe also reflects real-world treatment dynamics, as BUP use is often characterized by variable adherence and discontinuation over time.¹⁸ Extending follow-up could increase the risk of exposure misclassification, whereby dental events occurring after treatment discontinuation might be incorrectly attributed to BUP. Moreover, because the comparator group comprised non-users, prolonged follow-up could unevenly accumulate risk in that group while diluting exposure-related risk among BUP users, potentially biasing relative estimates toward the null. Although this approach may miss later-onset events, it provides a valid assessment of early-onset dental risk among incident BUP users.

Covariates

We controlled for baseline and index patient characteristics such as demographic characteristics, comorbidities, and prior medications. These variables were selected because they can confound the association between our exposure and outcome, they are associated with outcomes only, or proxies of unmeasured confounders.^19,20 Demographic characteristics assessed on the index date include age, gender (male or female), ethnicity (Hispanic or non-Hispanic), race (Asian, White, or Black), and region (Northeast, Northcentral, South, West). Comorbidities were assessed in the baseline period, and they include tobacco use disorder, obesity, chronic kidney disease, alcohol use disorder, asthma, type 2 diabetes, and chronic obstructive pulmonary disease/bronchitis. Prior medication use was also assessed in the 6-month pre-index period, and they include opioid analgesic, orphenadrine, alprazolam, amitriptyline, decongestants, and albuterol use.

Statistical Analysis

We reported means and standard deviations for continuous variables and frequencies and percentages for categorical variables. The index date was defined as the date of the first BUP prescription. In order to specify a time zero for the control group and mitigate potential immortal time bias in the outcome assessment, we employed prescription time distribution matching (PTDM) method where we individually assigned index dates to the control group that corresponded to the index date for BUP users – matched by age, sex, and OUD diagnosis dates.^21,22 In PTDM, each control was randomly assigned an index date drawn from the empirical distribution of time between OUD diagnosis and BUP initiation among exposed patients. This approach aligns the start of follow-up between groups and prevents the introduction of immortal person-time that would otherwise occur if controls were followed from diagnosis while exposed individuals had variable lag times before treatment initiation.²³ Outcome assessment was then specified within 6 months of the index dates for the study cohorts (Figure 1). To adjust for baseline imbalances between the 2 exposure groups, we utilized inverse probability of treatment weighting (IPTW), which estimated each individual’s probability of receiving BUP given their observed covariates. The propensity model included demographic factors and key clinical characteristics which are predictors of oral health outcomes. Covariate balance before and after weighting was assessed using standardized mean differences (SMDs), with values <0.1 considered indicative of adequate balance.^24,25 All eligible patients were followed from the index date until the occurrence of the first of the following events: any DAE, discontinuation of medical insurance enrolment or the end of the follow-up period, defined as a 6-month period from the index date. Using a Cox proportional hazard model, we estimated the hazard ratios of DAE outcome, adjusting for the IPT weights in the analyses. We reported HRs and 95%CI. Statistical significance was set at P < .05. All analyses were conducted using SAS 9.4 software version.

Figure 1.

Study diagram.

Results

Study Population and Characteristics

A total of 14 495 OUD adult patients met our study inclusion criteria after PTDM. Of these patients, 4199 (28.97%) were included in the BUP cohort (Figure 2). Among the overall population, most were males, 8742 (60.3%), with an average age of 44.9 years. After IPTW, SMDs show covariate balance between the 2 groups (Table 1). Means, frequencies, and SMDs between patient characteristics and treatment groups are also summarized in Table 1.

Figure 2.

Cohort attrition.

Table 1.

Characteristics of Included Patients.

Patient characteristics	Total number of OUD patients n (%)(N = 14 495)	Treated with buprenorphine n (%)		SMD
Patient characteristics	Total number of OUD patients n (%)(N = 14 495)	No (N = 10 296)	Yes (N = 4199)	Before IPTW	After IPTW
Demographics
Mean age (at index)	44.9 (14.95)	46.3 (14.84)	41.4 (14.66)	0.02	0.0033
Age categories
18-34	4232 (29.20)	2682 (26.05)	1550 (36.91)	0.03	0.02
35-44	3107 (21.43)	2099 (20.39)	1008 (24.01)
45-54	2732 (18.85)	1999 (19.42)	733 (17.46)
55-64	2945 (20.32)	2334 (22.67)	611 (14.55)
65+	1479 (10.20)	1182 (11.48)	297 (7.07)
Gender n (%)
Female	5753 (39.7)	4205 (40.8)	1548 (36.9)	0.05	0.01
Male	8742 (60.3)	6091 (59.2)	2651 (63.1)	0.05	0.01
Region^a
Northeast	1924 (13.27)	1299 (12.62)	625 (14.88)
Northcentral	973 (6.71)	565 (5.49)	408 (9.72)	0.04	0.01
South	5844 (40.32)	3964 (38.50)	1880 (44.77)
West	2665 (18.39)	1817 (17.65)	848 (20.20)
Race^a
Asian	223 (1.54)	148 (1.44)	75 (1.79)	0.13	0.005
Black	727 (5.02)	597 (5.80)	130 (3.10)
White	7954 (54.87)	5667 (55.04)	2287 (54.47)
Ethnicity^a
Hispanic	203 (1.40)	153 (1.49)	50 (1.19)	0.26	0.003
Non-Hispanic	9538 (65.80)	6591 (64.02)	2947 (70.18)
Prior medications, n (%)
Opioid analgesic use
No	7973 (55.0)	5962 (57.9)	2011 (47.89)	0.04	0.002
Yes	6522 (45.0)	3774 (42.1)	2188 (52.11)
Orphenadrine use
No	14463 (99.8)	10270 (99.7)	4193 (99.9)	0.02	0.01
Yes	32 (0.2)	26 (0.3)	6 (0.1)
Alprazolam use
No	13445 (92.8)	9531 (92.6)	3914 (93.2)	0.17	0.001
Yes	1050 (7.2)	765 (7.4)	285 (6.8)
Amitriptyline use
No	14139 (97.5)	10025 (97.4)	4114 (98.0)	0.04	0.034
Yes	356 (2.5)	271 (2.6)	85 (2.0)
Decongestant use
No	14405 (99.4)	10229 (99.3)	4176 (99.5)	0.04	0.013
Yes	90 (0.6)	67 (0.7)	23 (0.5)
Albuterol use
No	13889 (95.8)	9909 (96.2)	3980 (94.8)	0.07	0.009
Yes	606 (4.2)	387 (3.8)	219 (5.2)
Prior conditions, n (%)
Tobacco use disorder
No	12646 (87.2)	9204 (89.4)	3442 (82.0)	0.21	0.004
Yes	1849 (12.8)	1092 (10.6)	757 (18.0)
Obesity
No	12449 (85.9)	8751 (85.0)	3698 (88.1)	0.09	0.001
Yes	2046 (14.1)	1545 (15.0)	501 (11.9)
Chronic kidney disease
No	14253 (98.3)	10094 (98.0)	4159 (99.0)	0.08	0.01
Yes	242 (1.7)	202 (2.0)	40 (1.0)
Alcohol use disorder
No	12749 (88.0)	9195 (89.3)	3554 (84.6)	0.13	0.02
Yes	1746 (12.0)	1101 (10.7)	645 (15.4)
Asthma
No	13672 (94.3)	9694 (94.2)	3978 (94.7)	0.02	0.0006
Yes	823 (5.7)	602 (5.8)	221 (5.3)
COPD/bronchitis
No	13706 (94.6)	9711 (94.3)	3995 (95.1)	0.04	0.003
Yes	789 (5.4)	585 (5.7)	204 (4.9)
Type 2 diabetes
No	12966 (89.5)	9059 (88.0)	3907 (93.0)	0.18	0.012
Yes	1529 (10.5)	1237 (12.0)	292 (7.0)

Abbreviations: COPD, chronic obstructive pulmonary disease; SMD, standardized mean difference.

SMD < 0.1 indicates covariate balance.

Variables contain missing values, % may not add up.

Association between BUP use and the risk of DAE

Number of DAE

Table 2 shows the overall number of DAE and absolute risk in the 2 exposure groups after 6 months of follow-up. BUP users had 91 (2.17%) DAE compared with 171 (1.66%) in the no BUP cohort.

Table 2.

Risk of Adverse Dental Effects Associated With the Use of Buprenorphine.

Exposure	Number of patients, n	Dental adverse events, n (%)	HR (95%CI)^a
Exposure	Number of patients, n	Dental adverse events, n (%)	Unadjusted	Adjusted
Buprenorphine	4199	91 (2.17)	1.31 (1.01-1.68)	1.36 (1.04-1.78)
No buprenorphine	10 296	171 (1.66)	1 [Reference]	1 [Reference]

Abbreviations: HR, hazard ratio; CI, confidence interval.

Outcome Model is Cox proportional hazard model with IPTW adjusted weight as covariate.

Bolded estimates: Statistically significant HR estimates (P < .05).

Unadjusted and Adjusted hazard ratios of DAE outcomes for the treatment group and covariates

The hazard ratio (HR) for the risk of DAE before IPTW was (HR, 1.31; 95%CI, 1.01-1.68) for BUP users compared to the control group. After adjusting for IPT weights, the adjusted HR for BUP cohort compared to the control cohort was (HR, 1.36; 95%CI, 1.04-1.78) (Table 2). HRs for patient characteristics are summarized in Table 3.

Table 3.

Patient Characteristics and the Adjusted Risk of Adverse Dental Effects.

Patient characteristics	HR (95%CI)^a
Mean age	1.00 (0.99-1.01)
Gender (men vs female [reference])	1.42 (1.09-1.85)
Region
Northeast	0.74 (0.49-1.12)
Northcentral	0.79 (0.46-1.35)
South	1 [Reference]
West	0.98 (0.70-1.37)
Race
Asian	0.73 (0.23-2.37)
Black	0.83 (0.43-1.61)
White	1 [Reference]
Ethnicity
Hispanic	0.34 (0.04-2.74)
Non-Hispanic	1 [Reference]
Opioid analgesic use (yes vs no)	1.13 (0.21-1.61)
Orphenadrine use (yes vs no)	Inest.
Alprazolam use (yes vs no)	0.94 (0.57-1.54)
Amitriptyline use (yes vs no)	1.90 (1.07-3.39)
Decongestant use (yes vs no)	0.86 (0.19-3.98)
Albuterol use (yes vs no)	1.60 (0.94-2.73)
Tobacco use disorder (yes vs no)	1.44 (1.02-2.06)
Obesity (yes vs no)	1.30 (0.92-1.83)
Chronic kidney disease (yes vs no)	0.71 (0.26-1.89)
Alcohol use disorder (yes vs no)	1.25 (0.85-1.85)
Asthma (yes vs no)	1.13 (0.68-1.89)
COPD/bronchitis (yes vs no)	1.18 (0.72-1.93)
Type 2 diabetes (yes vs no)	1.20 (0.82-1.77)

Abbreviations: HR, hazard ratio; CI, confidence interval; COPD, chronic obstructive pulmonary disease; Inest, inestimable.

[No] is the reference group in the model. Bolded effect estimates are statistically significant (P < .05).

Outcome Model is Cox proportional hazard model with adjusted for patient covariates.

Discussion

With over 15 million BUP prescriptions issued in 2023 alone^26,27 and the growing concern about population-level dental risk associated with BUP use, this study utilized more recent prescription data to provide updated evidence about this risk among OUD patients in the real world. After 6 months of follow-up, we found the incidence of the outcome to be slightly higher among BUP users. Ultimately, our study found an increased risk of DAE among BUP users compared to non-users. This risk may escalate with longer-term exposure, particularly in individuals with poor oral hygiene or limited access to dental care.

Our results are consistent with already existing findings about this association.^9,10 This risk has been linked to biological causes, as evidenced in prior preclinical studies. Zheng et al²⁸ demonstrated that sublingual BUP rapidly accumulates in salivary gland tissues in rats and persists in oral fluids at concentrations nearly 50-fold higher than plasma levels up to 24 hours post-dose, possibly through active secretion by salivary solute carrier transporters. Such accumulation disrupts normal salivary flow, compromises antimicrobial defenses, and promotes oral dysbiosis, mechanisms conducive to enamel demineralization and caries.²⁸ While preclinical evidence from Zheng et al provides important insights into the salivary pharmacokinetics and potential local effects of BUP, these findings are based on rat models and may not fully translate to human physiology. Nonetheless, they support the biologic plausibility of BUP-associated oral effects observed in real-world clinical settings. This includes clinical reports from patients, as reported by Suzuki and Park,²⁹ which also showed extensive dental decay in patients initiating BUP, despite impeccable oral hygiene and no prior xerostomia. In a population-based claims data analysis, Etminan et al¹⁰ reported a 42% increased risk of any dental event and a 57% higher risk of caries or tooth loss in sublingual BUP users compared to transdermal formulations. Similarly, Tuan et al⁹ found that BUP-treated adults had higher oral health event rates after treatment initiation. Although our study used a different data source and more recent data, the slight differences in effect magnitude are likely attributable to our broader dental outcome definition compared with previous population-level studies. By incorporating both functional and structural dental outcomes, our findings offer a more comprehensive characterization of BUPE-associated oral risks and their potential implications for the clinical management of OUD.

Our findings have important clinical and policy implications. Although the relative risk associated with BUP use was statistically significant, the absolute risk increase was modest, corresponding to a number needed to harm of approximately 200. This indicates that, although the overall population-level risk is small, the finding remains clinically meaningful. These results emphasize the importance of targeted preventive strategies particularly among high-risk patients. BUP remains an efficacious and convenient treatment option for managing OUD, however, DAE, if unaddressed, may contribute to treatment discontinuation, a pervasive challenge in this population, with studies indicating that patients discontinue their treatment due to adverse events experienced even in the early phases of treatment.^30,31 Discontinuation could worsen treatment outcomes, including increased risks of relapse and overdose.^32,33 Our study is timely in expanding the awareness of this safety risk among prescribers, dentists, and patients. As adoption and adherence to BUP continues to increase, our findings also provide justifications for evidence-based preventive strategies that can be integrated into BUP treatment protocols. These include patient education on oral hygiene practices, routine dental checkups, and coordination between prescribers, dentists, and pharmacists to support early detection and management of dental complications. Implementing such preventive measures may help mitigate BUP-associated oral risks without interrupting treatment for OUD. These recommendations are in line with those highlighted by FDA.⁸ The effectiveness of these strategies was not tested within the scope of this study; hence future studies may investigate their impact in mitigating BUP-related DAE or in reducing treatment discontinuation.

Our study findings should be interpreted with these limitations in mind. First, although we leveraged linked EHR and claims data, our outcome definition relied on diagnostic and procedure codes, which are susceptible to under coding or inconsistent documentation, particularly for oral health conditions, which are often underrepresented in non-dental datasets.^15,34 Additionally, our dataset may not capture dental services provided in independent dental practices or scenarios where patients pay out-of-pocket, potentially underestimating the true burden of DAE. As a result, the dental events identified likely represent medically attended or severe dental conditions rather than routine care. However, since both exposed and comparator group were drawn from the same medical claims source, any under capture of routine dental services is expected to be nondifferential. More studies may want to explore this risk using data sources that capture routine dental services. Second, while we used a robust analytical approach, residual confounding remains a concern. Important unmeasured variables such as oral hygiene practices, dietary patterns, and access to fluoridated water were not available in our data, yet they may influence both BUP use and oral health outcomes. A formal power or sample size calculation was not performed, as this was a retrospective database study based on all eligible patients meeting the inclusion criteria. Another limitation is the high proportion of missing data for race and ethnicity in the EHR component of our dataset. Although we found no evidence that missingness differed by exposure status and included these variables in the IPTW model along with related demographic factors, residual confounding due to incomplete race and ethnicity data cannot be entirely excluded. Also, our comparator group may include a combination of users of other MOUD which may introduce heterogeneity in this group; however, our focus was to estimate the overall risk associated with BUP use among all OUD patients. Lastly, our 6-month follow-up period may not fully capture the long-term trajectory of dental complications, particularly given prior evidence of persistent oral health risk over multi-year horizons. However, the choice of a 6-month period emphasizes the early onset of this risk following BUP initiation, a period which represents a critical timeframe when complications may affect treatment continuity and risk of early discontinuation. Despite these limitations, our study used an enriched dataset to provide the most recent data about comprehensive dental adverse risks among incident BUP users with OUD.

Conclusion

There is an increased risk of DAE among BUP users compared to non-users after 6 months of follow-up. Although this risk is modest, this finding suggests the need for increased awareness and preventive interventions among these users. Future studies may explore the impact of these strategies toward mitigating this risk among OUD patients on BUP treatment.

Supplemental Material

sj-docx-1-sat-10.1177_29768357251411168 – Supplemental material for Buprenorphine Use and the Risk of Dental Adverse Events in Patients With Opioid Use Disorder

Supplemental material, sj-docx-1-sat-10.1177_29768357251411168 for Buprenorphine Use and the Risk of Dental Adverse Events in Patients With Opioid Use Disorder by Chijioke M. Okeke, Michael Okonkwo, Olajumoke Olateju, Vesna Tumbas Saponjac, Ming Hu, Rashim Singh, Mansib Mursalin and J. Douglas Thornton in Substance Use: Research and Treatment

Footnotes

Acknowledgements

Rashim Singh is supported by the National Center for Advancing Translational Sciences (NCATS) of the National Institutes of Health under award number K12TR004522.

ORCID iD

Chijioke M. Okeke

Ethical Considerations

Data are de-identified and fully compliant with the Health Insurance Portability and Accountability Act (HIPAA); therefore the University of Houston Institutional Review Board deemed the study exempt from human subjects’ review.

Consent for Publication

Not applicable.

Author Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of Conflicting Interests

The authors declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: None. Dr. Thornton is a consultant for the Plaintiff’s Steering Committee for Opioid Litigation and a member of the Texas Opioid Abatement Fund Council. Dr Ming Hu and Dr. Rashim Singh are the co-founders of Sanarentero LLC. Vesna Tumbas also has a financial interest in Sanarentero LLC. Sanarentero LLC had no role in the design, conduct, data collection, analysis, or interpretation of this study, and no financial or material support was received from the company. These affiliations are not also involved in deciding the research direction of this project; hence no authors reported a conflict of interest.

Generative AI Statement

The authors declare that no Generative AI was used in the creation of this manuscript.

Supplemental Material

Supplemental material for this article is available online.

References

Substance Abuse and Mental Health Services Administration (SAMHSA). Substance use disorder treatment options. 2025. Accessed May 25, 2025. https://www.samhsa.gov/substance-use/treatment/options/medications

Khatri

Lopez

Yen

, et al. Receipt of buprenorphine and naltrexone for opioid use disorder by race and ethnicity and insurance type. JAMA Network Open. 2025;8(6):e2518493. doi:10.1001/jamanetworkopen.2025.18493

Wakeman

Barnett

ML.

Primary care and the opioid-overdose crisis—buprenorphine myths and realities. N Engl J Med. 2018;379(1):1-4. doi:10.1056/NEJMp1802741

Sordo

Barrio

Bravo

, et al. Mortality risk during and after opioid substitution treatment: systematic review and meta-analysis of cohort studies. BMJ. 2017;357:j1550. doi:10.1136/bmj.j1550

U.S. Food and Drug Administration. Buprenorphine: Drug Safety Communication - FDA warns about dental problems with buprenorphine medicines dissolved in the mouth to treat opioid use disorder and pain. FDA. 2022. Accessed August 9, 2025. https://www.fda.gov/safety/medical-product-safety-information/buprenorphine-drug-safety-communication-fda-warns-about-dental-problems-buprenorphine-medicines

Teoh

Moses

McCullough

Oral manifestations of illicit drug use. Aust Dent J. 2019;64(3):213-222. doi:10.1111/adj.12709

Robinson

Acquah

Gibson

Drug users: oral health-related attitudes and behaviours. Br Dent J. 2005;198(4):219-224. doi:10.1038/sj.bdj.4812090

Simon

Choudhary

Ticku

Barrow

Tobey

Dental care utilization in Massachusetts before and after initiation of medication for opioid use disorder: a cross-sectional study of a state all-payer claims database. J Public Health Dent. 2022;82(4):461-467. doi:10.1111/jphd.12488

Tuan

Clebak

Jawadi

Snyder

Zgierska

AE.

Risk of oral health problems in adults with opioid use disorder treated with transmucosal buprenorphine. J Addict Med. 2025;19(5):529-535. doi:10.1097/ADM.0000000000001453

10.

Etminan

Rezaeianzadeh

Kezouh

Aminzadeh

Association between sublingual buprenorphine-naloxone exposure and dental disease. JAMA. 2022;328(22):2269. doi:10.1001/jama.2022.17485

11.

Federal Register: Practice guidelines for the administration of buprenorphine for treating opioid use disorder. Accessed November 2, 2025. https://www.federalregister.gov/documents/2021/04/28/2021-08961/practice-guidelines-for-the-administration-of-buprenorphine-for-treating-opioid-use-disorder

12.

U.S. Drug Enforcement Administration. Buprenorphine Treatment for Substance Use Disorder. 2024. Accessed August 9, 2025. https://deadiversion.usdoj.gov/pubs/docs/IQVIA-Buprenorphine-for-SUD-v3.pdf

13.

von Elm

Altman

Egger

Pocock

Gøtzsche

Vandenbroucke

JP.

Strengthening the reporting of observational studies in epidemiology (STROBE) statement: guidelines for reporting observational studies. J Clin Epidemiol. 2007;335(7624):806-808. doi:10.1136/BMJ.39335.541782.AD

14.

Veradigm. Linked Claims + EHR Database by MarketScan^® and Veradigm^®. Accessed July 7, 2025. https://lp.veradigm.com/linked-claims-ehr-database

15.

Osterhage

Hser

Mooney

, et al. Identifying patients with opioid use disorder using International Classification of Diseases (ICD) codes: challenges and opportunities. Addiction. 2024;119(1):160-168. doi:10.1111/add.16338

16.

Simonaitis

McDonald

CJ.

Using National Drug Codes and drug knowledge bases to organize prescription records from multiple sources. Am J Health Syst Pharm. 2009;66(19):1743-1753. doi:10.2146/ajhp080221

17.

Bihan

Lebrun-Vignes

Funck-Brentano

Salem

JE.

Uses of pharmacovigilance databases: an overview. Therapies. 2020;75(6):591-598. doi:10.1016/j.therap.2020.02.022

18.

Olateju

Okeke

Shrestha

Thornton

Association between buprenorphine adherence trajectories, health outcomes, and health care costs among Medicaid enrollees. J Addict Med. 2025;19(5):578-590. doi:10.1097/ADM.0000000000001458

19.

Howards

PP.

An overview of confounding. Part 1: the concept and how to address it. Acta Obstet Gynecol Scand. 2018;97(4):394-399. doi:10.1111/aogs.13295

20.

VanderWeele

TJ.

Principles of confounder selection. Eur J Epidemiol. 2019;34(3):211-219. doi:10.1007/s10654-019-00494-6

21.

Zhou

Rahme

Abrahamowicz

Pilote

Survival bias associated with time-to-treatment initiation in drug effectiveness evaluation: a comparison of methods. Am J Epidemiol. 2005;162(10):1016-1023. doi:10.1093/aje/kwi307

22.

Karim

Gustafson

Petkau

Tremlett

Comparison of statistical approaches for dealing with immortal time bias in drug effectiveness studies. Am J Epidemiol. 2016;184(4):325-335. doi:10.1093/aje/kwv445

23.

Suissa

Immortal time bias in pharmacoepidemiology. Am J Epidemiol. 2008;167(4):492-499. doi:10.1093/AJE/KWM324

24.

Chesnaye

Stel

Tripepi

, et al. An introduction to inverse probability of treatment weighting in observational research. Clin Kidney J. 2022;15(1):14-20. doi:10.1093/CKJ/SFAB158

25.

Wallace

Singh

Blakney

Rene

Johnston

SS.

Optimization-based stable balancing weights versus propensity score weighting for samples with high covariate imbalance. Pharmacoepidemiol Drug Saf. 2024;33(7):e5864. doi:10.1002/pds.5864

26.

American Medical Association. AMA Overdose Epidemic Report. 2024. Accessed July 2, 2025. https://www.ama-assn.org/system/files/ama-overdose-epidemic-report.pdf

27.

Buprenorphine Dispensing Rate Maps. Overdose Prevention. CDC. Accessed November 2, 2025. https://www.cdc.gov/overdose-prevention/data-research/facts-stats/buprenorphine-dispensing-maps.html

28.

Zheng

Chen

Srinual

, et al. Buprenorphine salivary gland accumulation sustaining high oral fluid exposure and increasing the risk of Streptococcus mutans biofilm formation. J Addict Med. 2025;19(5):520-528. doi:10.1097/ADM.0000000000001401

29.

Suzuki

Park

EM.

Buprenorphine/naloxone and dental caries: a case report. Am J Addict. 2012;21(5):494-495. doi:10.1111/j.1521-0391.2012.00254.x

30.

Stafford

Marrero

Naumann

Lich

Wakeman

Jalali

MS.

Identifying key risk factors for premature discontinuation of opioid use disorder treatment in the United States: a predictive modeling study. Drug Alcohol Depend. 2022;237:109507. doi:10.1016/j.drugalcdep.2022.109507

31.

Wyse

Eckhardt

Waller

, et al. Patients’ perspectives on discontinuing buprenorphine for the treatment of opioid use disorder. J Addict Med. 2024;18(3):300-305. doi:10.1097/ADM.0000000000001292

32.

National Institute of Dental and Craniofacial Research. Oral Health in America. 2021. Accessed July 2, 2025. https://www.nidcr.nih.gov/sites/default/files/2021-12/Oral-Health-in-America-Advances-and-Challenges.pdf

33.

Sulley

Ndanga

Inpatient opioid use disorder and social determinants of health: a nationwide analysis of the National Inpatient Sample. Cureus. 2020;12(11):e11311. doi:10.7759/cureus.11311

34.

Alqaderi

Alhazmi

Gritzer

, et al. Assessing the readiness of dental electronic health records for machine learning prediction of procedure outcomes: Insights from the bigmouth repository on composite and amalgam restoration survival rates. J Dent. 2025;160:105865. doi:10.1016/j.jdent.2025.105865

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.02 MB