Addressing tobacco use in the context of opioid use disorder: A systematic review of smoking cessation interventions

Abstract

Background and Objectives

Rates of tobacco use disorder (TUD) are high among individuals with opioid use disorder (OUD), who consistently show lower response rates to evidence‐based treatment approaches for TUD relative to the general population. This systematic review aims to provide a comprehensive and updated examination of the current evidence regarding TUD treatments for individuals with OUD. We first summarize potential mechanisms driving TUD and treatment nonresponse among those with OUD, given the likely roles of overlapping reward and withdrawal processes in co‐occurrence and treatment challenges. We then provide an updated review of the relevant literature on treating TUD among those with OUD.

Methods

Our review identified a total of 25 studies, with 9 examining pharmacological treatments, 5 examining behavioral treatments, and 11 examining a combination treatment approach.

Results

Consistent with previous research, pharmacological treatments were generally ineffective for smoking cessation among those with OUD. No studies reported continuous abstinence at 6 months post‐quit date. Contingency management interventions showed some promise but smoking largely resumed after incentives were removed.

Discussion and Conclusions

Overall, findings demonstrate limited progress in identifying durable, effective smoking cessation interventions for individuals with OUD.

Scientific Significance

Traditional cessation treatment approaches fail to address smoking in individuals with OUD. Novel pharmacological and behavioral strategies that can be implemented into existing medications for OUD clinical care are necessary.

INTRODUCTION

Tobacco use disorder (TUD) is a significant global public health problem. In the United States, an estimated 19.8% of adults use tobacco products, with declines in combustible cigarette use (from 42.6% in 1965 to 11.6% in 2022) coinciding with increasing use of e‐cigarettes and related products. ¹ Cigarette smoking is disproportionately high among individuals with mental health and substance use disorders, a pattern that is especially notable among individuals with opioid use disorder (OUD), who report some of the highest rates of cigarette smoking, including up to 85% of those receiving medications for OUD (MOUD), with 72.6% smoking daily. ² Lifetime history of any e‐cigarette use among those with OUD receiving MOUD is high (62.1%); however, only 6% use daily. ² While individuals with OUD often express interest in smoking cessation and motivation to quit, the lower effectiveness of smoking cessation treatments for this population compared to those without OUD is possibly a barrier to successful cessation.

This systematic review aims to provide a comprehensive and updated examination of the current evidence regarding treatment interventions for TUD in individuals with OUD. We extend and update previously published commentary and narrative reviews on this topic ³ , ⁴ by incorporating new research and additional insights. First, we summarize the potential mechanisms contributing to high rates of co‐use, which provide valuable insight into related treatment challenges. Following, we provide a systematic review of the relevant literature on the treatment of TUD among those with OUD. We conclude by synthesizing findings and identifying gaps in the current literature to guide future research in this critical area.

POTENTIAL MECHANISMS OF HIGH RATES OF DUAL‐USE

Enhanced reinforcement/reward

Although opioids and nicotine have distinct pharmacological and behavioral effects, they also share some common actions, particularly within the brain's reward system. ⁵ A key step in drug reward is the activation of the mesolimbic dopamine (DA) pathway, leading to the release of DA. ⁶ This pathway originates from the ventral tegmental area (VTA) and projects to limbic and cortical areas, including the nucleus acumens, amygdala, and prefrontal cortex (PFC). Nicotine enhances DA release by activating the alpha4beta2 nicotinic acetylcholine receptors (nAChRs) on DA neurons within the VTA. ⁶ Conversely, opioids, through activation of mu and delta opioid receptors, increase DA release by inhibiting the GABAergic interneurons in the VTA, effectively disinhibiting DA release. Activation of nAChRs by nicotine also releases endogenous opioid peptides, including endorphins and enkephalins, in the striatum, potentially contributing to nicotine's rewarding and addictive effects.

Preclinical and clinical evidence suggest that opioids can enhance the rewarding effects of nicotine and vice versa. In rats, morphine pretreatment increases nicotine reward sensitivity and nicotine pretreatment increases morphine self‐administration. ⁷ Human behavioral pharmacology studies consistently support this preclinical work demonstrating the effects of opioids on enhancing nicotine reinforcement. Opioid agonists, including heroin, methadone, and buprenorphine, increase the subjective reward from smoking and/or the number of cigarettes smoked. ⁸ Ecological momentary assessment (EMA) data have also demonstrated that cigarette smoking temporally coincides with heroin and cocaine use or craving. ⁹ Additionally, research suggests that opioid agonists, like methadone, might play a role in maintaining smoking behavior by enhancing the rewarding effects of nicotine and alleviating withdrawal symptoms. Taken together, this work points to a potential role for reciprocal reinforcement effects between nicotine and opioids as one explanation for high rates of co‐use and related treatment challenges.

Withdrawal and relapse

Similarities in withdrawal syndromes as well as cross‐alleviation of withdrawal symptoms may also drive high rates of co‐use. Opioid withdrawal has a strong physical component, including muscle aches, runny nose, insomnia, goosebumps, abdominal cramps, nausea, vomiting, and sweating. Nicotine withdrawal typically presents with a relatively milder physical component, including increased appetite, constipation, insomnia, headaches, and coughing. Both nicotine and opioid withdrawal induce a negative affective state, characterized by irritability, dysphoria, increased stress, and anhedonia. The negative affective state, particularly dysphoria and anhedonia, likely contributes to smoking maintenance and high rates of relapse, as resuming smoking rapidly alleviates this aversive state (negative reinforcement). Mechanistic studies in rodents have shown that withdrawal from nicotine or opioids reduces DA levels and decreases tonic and phasic DA release in the nucleus accumbens, likely contributing to the anhedonia and dysphoria of withdrawal.

Research across animal and human models support the reciprocal effects of opioids and nicotine on withdrawal states. In rats, repeated nicotine administration attenuates naloxone‐induced opioid withdrawal in morphine dependent mice. ¹⁰ Conversely, morphine alleviates spontaneous or nicotine‐antagonist precipitated nicotine withdrawal. Studies in individuals receiving methadone treatment have demonstrated that methadone and nicotine both alleviate nicotine withdrawal symptoms and cigarette smoking potentiates methadone's effect in suppressing opioid withdrawal. ¹¹ There is also evidence that administration of opioid antagonists like naloxone exacerbates nicotine withdrawal in opioid‐naïve individuals who use nicotine. These studies collectively suggest that the alleviation of withdrawal likely contributes to the co‐use of nicotine and opioids.

The potential reciprocal relationship between opioids and nicotine for relapse risk has not been fully elucidated. Research using the reinstatement model of relapse in rodents has shown that a priming dose of morphine triggers nicotine‐seeking behavior, and this effect is blocked by naloxone. ¹² However, research examining nicotine's effects on morphine reinstatement has yielded inconsistent findings. As noted above, co‐occurring OUD reduces success rates for smoking cessation; this challenge is also seen across substance use disorders and may not be unique to OUD. Nevertheless, research on withdrawal alleviation and relapse points to potential pharmacological pathways through which opioids and nicotine may contribute to unique shared risks of maintenance of use and relapse risk.

Shared factors

High rates of opioid and tobacco co‐use also appear related to several shared factors, including genetics, comorbidities, and psychosocial resources. For example, genome‐wide association (GWA) research has identified a shared genetic liability between OUD and TUD, associated with behavioral traits like risk‐taking, neuroticism, and impaired executive function. A number of comorbid conditions are also shared among those with OUD and/or TUD. For psychiatric disorders, individuals with depression are more likely to smoke cigarettes and misuse prescription opioids, a co‐occurrence that may be driven or exacerbated by the anhedonia and related affective symptoms of nicotine and opioid withdrawal. Chronic pain is also common with both OUD and TUD, and may precede or follow the development of both. Opioids and nicotine both have analgesic effects, and their prolonged use can lead to heightened sensitivity to pain (i.e., hyperalgesia), pointing to numerous explanatory pathways for this shared co‐occurring condition. ⁵ Pain severity predicts a greater likelihood of continued tobacco use, transition to e‐cigarette use, and co‐use of cigarettes and e‐cigarettes. ¹³ Finally, OUD and TUD share several psychosocial risk factors that may contribute to frequency of co‐use and challenges for effective treatment, including socioeconomic disadvantage, adverse childhood experiences, high rates of smoking within one's social network, and high levels of stress.

METHODS

To update previously published reviews on this topic, ³ , ⁴ a search strategy was developed by a clinical librarian (J.P.) with extensive experience in medical literature retrieval, in collaboration with the authorship team. Subject headings were sourced from the National Library of Medicine's Medical Subject Headings (MeSH), Elsevier's Emtree, EBSCO's CINAHL Subject Headings, and EBSCO's APA PsycINFO Thesaurus of Psychological Index Terms. Additional keywords were identified by the expert team and through abstract reviews of relevant studies. Our methods were carried out in accordance with the Preferred Reporting Items for Systematic reviews and Meta‐Analyses guidelines (PRISMA).

Eligibility criteria included published, peer‐reviewed clinical trials that met the following criteria: (1) available in English, (2) study population included individuals with OUD, and (3) study intervention was defined as a pharmacologic and/or non‐pharmacologic intervention specifically designed for smoking cessation or reduction of tobacco/nicotine use. Studies that were observational by design or focused on individuals prescribed opioids in the context of pain care without evidence of OUD or opioid misuse were excluded.

Searches were performed in six databases: PubMed, EMBASE, Cochrane Library, CINAHL, APA PsycINFO, and MEDLINE. These databases were selected for their comprehensive coverage of medical, psychological, and clinical trial literature relevant to the research question. All searches applied the filters “Humans” and “English Language” unless otherwise specified. Additional keywords encompassed four domains: OUD (e.g., “Opioid‐Related Disorders,” “Heroin Addiction”), smoking behaviors (e.g., “Cigarette Smoking,” “Vaping”), smoking cessation interventions (e.g., “Smoking Cessation,” “Nicotine Replacement Therapy”), and clinical trial designs (e.g., “clinical trial,” “randomized controlled trial”). MeSH terms were translated to Emtree, CINAHL Subject Headings, and APA PsycINFO Thesaurus terms for respective databases. The full search strategies, including all keywords, subject headings, and combined searches, are provided in Supplementary Materials. The systematic review protocol was registered on PROSPERO (CRD420250650592) on February 9, 2025. All searches were conducted on March 26 through 28, 2025.

A total of 899 records were retrieved and imported into EndNote for citation management. Automated deduplication and manual review for peer reviewed clinical trials using EndNote's “Type of Work” function reduced this to 621 references; ⁴ additional records were identified following a secondary review resulting in 625 references. These were imported into Covidence, a screening and data extraction workflow tool for systematic reviews; following a check for duplicates (n = 5), title/abstract screening, full‐text review, and data extraction, 554 references were excluded. Full‐text reviews of the remaining 66 articles identified 25 which met eligibility criteria. A PRISMA diagram of search strategy is depicted in Figure 1.

Figure 1.

PRISMA diagram of literature search.

RESULTS

Selected studies (see Table 1) varied with respect to MOUD type (methadone only: n = 15; buprenorphine only: n = 5; methadone or buprenorphine: n = 4). Only one study did not require participants to be maintained on MOUD and instead compared smoking intervention outcomes among subjects with OUD to those with other SUD. ¹⁷ See Figure 2 for a sankey chart depicting study intervention description by MOUD type. The majority of studies focused on individuals with OUD engaged in methadone (n = 15), followed by buprenorphine (n = 5), both (n = 4), and a single study with no MOUD. The four studies that evaluated both methadone and buprenorphine did not report differences by MOUD type. The combined demographics of included studies was equivalent with respect to sex (50.2% male, 49.8% female), overwhelmingly white, with an average age of 40.7 years.

Table 1.

Clinical trials for smoking cessation treatment among participants with OUD.

Study	Medication for OUD intervention(s) study design	Mean age (sex/gender) Race/Ethnicity	Outcome measures assessment timepoints	Primary findings	Other findings
Pharmacological treatments
Adams et al. 14	MTD, BUP Standard clinical MAT care (SCC) then crossover to SCC + Varenicline (N = 7). Each treatment for 4 weeks Crossover	47 (86% M, 14% F) 57% H/L; 28.5% AA; 14% W	CPD Breath CO (<8 ppm) 2, 4, 6, and 8 weeks	Reduction in CPD during both phases compared to baseline (no inferential statistics). No change in abstinence	Co‐users of tobacco and cannabis. Cannabis use was lower during both phases compared to baseline (no inferential statistics)
Felicione et al. 15	BUP Second‐generation e‐cigarette, 18 ng/mL (n = 14) versus 0 ng/mL nicotine (n = 11) Randomized	32.4 (28% M; 72% F) 100% W	CPD Breath CO (≤8 ppm) 2 and 4 weeks	CPD significantly reduced in both arms relative to baseline No significant effects for breath CO.
Felicione et al. 16	BUP Varenicline 2 mg daily through three phases based on time in BUP (N = 35) Quasi experimental	32.6 (40.5% M, 59.5% F) 100% W	CPD Breath CO (<6 ppm) Phase 1: 0–90 days of treatment; Phase 2: 91–365 days; Phase 3: >365 days	CPD significantly declined in all three phases for the first few weeks; the decline continued for those in phase 1 but plateaued in phases 2 and 3. No significant effects for CO.	47.3% completed the study No difference in varenicline adverse effects between phases.
Martin et al. 17	OUD (n = 47) versus non‐OUD (n = 90) Varenicline 2 mg or placebo versus NRT or placebo *Secondary analysis of a larger sample from outpatient SUD clinics Randomized, placebo‐controlled	39.6 (72% M, 28% F) 83% W; 15% AA; 7% Other	CPD Breath CO (≤4 ppm) Saliva cotinine (≤15 ng/mL) Self‐reported drug use 3 and 6 months	No significant difference in CPD and biochemical markers of smoking on OUD (vs. non‐OUD).	No difference for drug use days between 1 and 3 months, but for 4 and 6 months, OUD participants on varenicline had significantly more drug use days than those on NRT.
Nahvi et al. 18	MTD Varenicline 2 mg daily via directly observed (n = 50) or via unsupervised self‐administered treatment (n = 50) Randomized	49 (56% M, 44% F) 14% W; 44% H/L, 30% AA; 10% Multiracial	7‐day PP via breath CO (<8 ppm) 12 weeks	No significant difference in CO‐verified smoking abstinence
Pericot‐Valverde et al. 19	BUPE‐cigarettes (6 mg/mL) with choice of flavor (n = 30) Single arm	44.5 (50% M, 50% F) 93.3% W; 3.3% AA; 6.7% H/L; 2% Other	CPD Breath CO (<6 ppm) FTND 4 and 8 weeks.	Significant decline from baseline in CPD, CO levels, and FTND scores at both 4‐ and 8‐week time points
Poling et al. 20	MTD (also using cocaine) Varenicline 2 mg/day (n = 13) versus placebo (n = 18)	35.3 (81% M, 19% F) 61.3% W; 22.6% AA; 16.1% Other	CPD Breath CO (<8 ppm) Cocaine use via urine toxicology 12 weeks	Varenicline group had significantly greater reductions in CPD and weeks with CO < 8 ppm.	No difference in cocaine use
Stein et al. 21	MTD Varenicline 2 mg (n = 137) versus NRT (n = 133) versus placebo (n = 45) Randomized	40 (50% M, 50% F) 79.4% W; 20.6.% Other	CPD Breath CO (<8 ppm) Saliva or urine cotinine 3 and 6 months	No differences between groups in CPD or biochemically verified abstinence. Across groups, a reduction of CPD from baseline at 6 months.
Stein et al. 22	MTD E‐cigarettes (n = 15) Single arm	45.9 (50% M, 50% F) 100% W	CPD 7‐day PP via breath CO (<8 ppm) 3, 5, 7, and 9 weeks	Significant reductions in mean CPD relative to baseline.	Overall adherence to E‐cigarettes (used daily) was 89.1%.
Behavioral treatments
Dunn et al. 23	MTD Vouchers for smoking abstinence in the CM group (n = 10) versus yoke‐control (vouchers independent of smoking status; n = 10)	29.75 (40% M, 60% F) Race/ethnicity not reported	CPD Breath CO (days 1–5; ≤6 ppm) Urine cotinine (days 6–14; ≤80 ng/mL) 14, 30, 60, and 90 days	CM group (vs. non‐CM) achieved significantly more initial smoking abstinence and longer duration of abstinence at 14‐day timepoint. No significant difference at 30‐, 60‐, or 90‐day timepoints.
Haug et al. 24	MTD Four motivational enhancement therapy sessions (n = 30) versus standard care (cessation advice + printed material; n = 33) Randomized	29.7 (100% F, pregnant) 84% AA	CPD Breath CO (<8 ppm) Urine cotinine (<200 ng/mL) 10 weeks	No significant difference between the groups for the CPD, breath CO, and cotinine.
Schmitz et al. 25	MTD CM versus non‐CM in a within‐subject crossover (A‐B‐A‐B) model (n = 5) Crossover, open‐label	38.4 (80% M, 20% F) 60% W; 40% AA	CPD Breath CO (<8 ppm) 8 weeks (2 weeks/condition)	No significant overall effect of CM intervention on CO levels. The reduction in CPD was significant only during the first contingency intervention but not thereafter.
Shoptaw et al. 26	MTD Contingency management treatment (n = 17) 4 weeks Open label	43.7 (76% M, 24% F) Race/ethnicity not reported	Breath CO (≤4 ppm) Drug use via urine toxicology 4 weeks	Breath CO levels were significantly lower at the end of the study period compared to baseline.	Participants with lower nicotine dependence were more likely to achieve abstinence 94% used illicit substances at least once during the trial.
Tuten et al. 27	MTD Contingent behavioral incentive (CBI; n = 42) versus non‐contingent incentives (NCBI; n = 28) versus treatment as usual (TAU; n = 32)	30.8 (100% F, pregnant) 65% W; 35% AA	CPD Breath CO (<4 ppm) Proportion meeting smoking reduction targets 1‐, 3‐, and 6‐month post‐partum	Significantly lower CPD in the CBI group versus TAU but not versus the NCBI group CBI significantly lowered mean breath CO values versus NCBI or TAU 48% met the smoking reduction target of 75% and 31% met the abstinence target at week 12	Reduced smoking did not yield a significant difference in birth outcomes.
Combination treatments
Cooperman et al. 28	MTD 8‐session information‐motivation‐behavioral skills (IMB) plus NRT (n = 41) versus facilitated referral to a quitline (n = 42) Randomized	43 (42% M, 58% F) 75% W; 23% AA or H/L	CPD 7‐day PP via breath CO (threshold not reported) Quit attempts Smoke‐free days 3 and 6 months	IMB, compared to Quitline referral, reported significantly fewer CPD. No significant group differences in quit attempts, smoke‐free days, or rate of abstinence.
Cooperman et al. 29	MTD 12‐week DBT plus NRT for 8 weeks (n = 7) Open‐label, single arm	39 (100% F) 86% W; 14% H/L	CPD Breath CO (threshold not reported) 6 and 12 weeks	Significantly fewer CPD at 6 and 12 weeks compared to baseline 86% (n = 6) made a quit attempt One achieved a 7‐day PP abstinence	No participant used illicit drugs
Druckrey‐Fiskaaen et al. 30	MTD, BUP Brief behavioral intervention (short motivational talk + psychoeducation) and NRT (n = 135) versus no smoking cessation intervention (n = 124)	48.5 (69.% M 31% F) Race/ethnicity not reported	CPD Breath CO (<6 ppm) 16 weeks	Significant odds ratio of at least halving the number of cigarettes smoked, 2.07 (95% CI, 1.14–3.75), in intervention compared to control group.	Intervention effects stronger for men, those aged 40–60, receiving buprenorphine, no injection drug use, and those with greater then 15 years of smoking.
Dunn et al. 31	MTD, BUP Vouchers for smoking negative samples in the CM group (n = 20) versus yoke‐control (n = 20) group. All offered bupropion Randomized trial	31 (33% M; 67% F) Race/ethnicity not reported	Breath CO (days 1–5; ≤6 ppm) Urine cotinine (days 6–14; ≤80 ng/mL) 14, 30, 60, and 90 days	CM participants (vs. non‐CM) achieved significantly more initial smoking abstinence and longer duration of abstinence at the 14‐day timepoint. No significant difference at 30‐, 60‐, or 90‐day timepoints.	Bupropion did not significantly influence abstinence outcomes.
Hall et al. 32	BUP Skills training + NRT or varenicline + CBT (n = 85) versus information (control; n = 90) Randomized	40.3 (77% M, 23% F) 69.4% W; 30.6% Other	CPD 7‐day PP using CO (<5 ppm) and urine anatabine/anabasine (<2) 3, 6, 12, and 18 months	Significantly higher biochemically verified abstinence in the Intervention group versus the control at 3 months. No significant differences at other timepoints.	Cannabis use and CPD in the prior month were predictors for continuing smoking
Heydari et al. 33	MTD NRT + behavioral therapy (n = 212) versus behavioral therapy alone (n = 212) Randomized	43.9 (100% M) 100% Iranian descent	CPD Breath CO (threshold not reported) 1 and 6 months	At 1 and 6 months, there was a significant reduction in CPD, compared to baseline, in both groups. Breath CO results not reported.
Mooney et al. 34	BUP Bupropion 300 mg po daily (n = 20) versus placebo (n = 20) All received relapse prevention and CM for abstinence from tobacco and illicit substances Randomized	34.2 (85% M, 15% F) 82% W; 8% AA; 10% Other	Breath CO (<10 ppm) Drug use via urine toxicology 2, 4, 6, 8, and 10 weeks	Bupropion was not more effective than placebo for CO or drug use.
Nahvi et al. 35	MTD Varenicline 2 mg (n = 57) versus placebo (n = 55) All were offered brief individual counseling Randomized	48 (47% M, 43% F) 9% W; 27.7% AA; 63.3% Other	CPD 7‐day PP using breath CO (<8 ppm) Quit attempts 12 and 24 weeks	Significantly higher abstinence and lower CPD with varenicline (vs. placebo) at 12 weeks; no difference at 24 weeks.	No difference in adverse events
Shoptaw et al. 36	MTD NRT + one of four conditions: (1) NRT only (n = 43); (2) relapse prevention + NRT (n = 42); (3) CM + NRT (n = 43); (4) CM + NRT + relapse prevention (n = 47) Randomized	44 (60.5% M, 39.5% F) 38.9% W; 23.3% AA; 37.7% H	CPD Breath CO (<8 ppm) Urine cotinine (<30 ng/mL) 12 weeks, 6 and 12 months	At 12 weeks, the CM condition had significantly higher rates of smoking abstinence, CO levels, and CPD than the non‐CM groups. Results were not significant for 6‐ or 12‐month time points	No difference observed for relapse prevention with regard to illicit drug use.
Sigmon et al. 37	MTD, BUP Phase 1—CM for smoking abstinence weeks 1–2 (n = 88); Phase 2—Extended CM (EC; n = 31) versus extended noncontingent (EN; n = 32) for weeks 3–12 All offered bupropion Randomized	34.4 (41% M, 59% F) 97% W	CPD Breath CO (≤6 ppm) Urine cotinine (≤80 ng/mL) 12 weeks	No differences between groups during phase 1. EC group (vs. EN) achieved significantly greater smoking abstinence. EC group achieved a significantly longer duration of continuous abstinence compared with EN.	Bupropion did not significantly influence abstinence outcomes.
Stein et al. 38	MTD NRT + 3 tailored behavioral treatment sessions: MET + skills counseling + relapse prevention (n = 191) versus brief advice (n = 192) Randomized	40 (53% M; 47% F) 78% W, 23% Other	CPD 7‐day PP using breath CO (<8 ppm) Time to first cigarette after quit date 3 and 6months	Reduction in abstinence and CPD for all participants in the study, with no significant difference between groups.	CO verified abstinence at 3 and 6 months was lower than the number of self‐reported abstinence.

Abbreviations: AA, African American; BUP, buprenorphine; CBT, cognitive behavioral therapy; CM, contingency management; CO, carbon monoxide; CPD, cigarettes smoked per day; F, female; IMB, information‐motivation‐behavioral; M, male; MTD, methadone; NRT, nicotine replacement therapy; OUD, opioid use disorder; PP, point‐prevalence; SUD, substance use disorder; TAU, treatment as usual; TLFB, timeline follow‐back.

Figure 2.

Study count groupings per MOUD and treatment type(s) received by participants. “Both” refers to studies where participants could be receiving methadone or buprenorphine. “Ind. Counseling” refers to study descriptions of “behavioral therapy”, “individual counseling”, “skills training”, or “brief behavioral intervention.” CBT, cognitive behavioral therapy; E‐cig, e‐cigarette; MET, motivational enhancement therapy; MI, motivational interviewing; MOUD, medication treatment for opioid use disorder. CM, contingency management; NRT, nicotine replacement therapy; RP, relapse prevention.

For intervention type, 9 studies only included pharmacological interventions in the active arm, 5 used only behavioral interventions, and 11 employed a combination approach. Prescriptive pharmacological interventions included varenicline (n = 8), bupropion (n = 3), and nicotine replacement therapy (NRT; n = 9). Six studies evaluated varenicline alone, while the remaining two combined varenicline with brief individual counseling, ³⁵ or cognitive behavioral therapy (CBT). ³² Bupropion was compared to placebo in one study where all participated received relapse prevention and contingency management (CM). ³⁴ The other two studies were combined CM interventions for which bupropion was available to all participants. ³¹ , ³⁷ Two studies evaluated NRT as an active comparator to varenicline, ¹⁷ , ²¹ while the remaining seven examined NRT as an adjunct or comparator for behavioral treatments. ²⁸ , ²⁹ , ³⁰ , ³² , ³³ , ³⁶ , ³⁸ We also identified three studies utilizing e‐cigarettes for smoking cessation. Two assessed the feasibility and effects of e‐cigarettes alone on smoking‐related outcomes in buprenorphine‐maintained persons with OUD, ¹⁵ , ¹⁹ while the third evaluated changes in smoking outcomes over 6 weeks among participants maintained on methadone. ²² No studies combined e‐cigarettes with behavioral treatment as an intervention.

Among the studies that included a behavioral treatment, CM was the most common when examined alone (n = 4) and was also included in three of the combined pharmacological and behavioral treatments. All CM studies incentivized abstinence, typically via breath carbon monoxide (CO) and/or urine cotinine. Other behavioral interventions include a single behavioral only intervention that used motivational enhancement (ME), ²⁴ while the combined studies included Dialectical Behavioral Therapy, ²⁹ ME, ²⁸ , ³⁸ relapse prevention, ³⁶ psychoeducation and counseling, ³⁰ , ³⁵ or a skills‐based model. ³² , ³³

The most common outcome measures were 7‐day point prevalence of smoking abstinence and reduction in cigarettes per day (CPD). Abstinence was assessed via participant self‐report, often verified through breath CO and/or cotinine levels in urine or saliva. Most studies using breath CO for abstinence used thresholds greater than or equal to 8 ppm (n = 11), while others employed more conservative levels of 6ppm (n = 6), 5 ppm (n = 1), or 4 ppm (n = 4). One study employed a less conservative threshold of 10 ppm, ³⁴ and two studies did not report a threshold. ²⁹ , ³³ Other outcomes used in studies included smoke‐free days, quit attempts, adherence to reduction targets, dependence measures (i.e., Fagerstrom Test for Nicotine Dependence, time to first cigarette), other drug use (self‐report and urine toxicology), and urine anatabine/anabasine.

Regarding efficacy, only six studies measured point‐prevalence abstinence (all 7‐day) and 3‐month extended abstinence was reported in three studies with no results reporting continuous abstinence at 6 months. Pharmacological treatments, including NRT, bupropion, and varenicline, either alone or combined with behavioral treatment, showed only modest reductions in the number of cigarettes smoked and were not effective for quitting smoking. Among behavioral interventions, CM seemed to be the most promising. Six of the seven CM studies demonstrated some effect on smoking outcomes (e.g., reduction in CO and/or CPD). In general, the effects of CM on smoking reduction across studies were not durable. Non‐CM behavioral interventions were less successful. Two behavioral studies examined smoking cessation treatment in pregnant women, with one showing no effect of motivational enhancement on at 10 weeks, ²⁴ and the other demonstrated significant reductions in CPD and breath CO for CM at 3 months. ²⁷ A recent study using an integrated approach (brief behavioral intervention plus NRT) was twice as likely to achieve a reduction in smoking consumption by at least 50% at 4 months. ³⁰ Two studies that leveraged e‐cigarettes as an intervention reported reductions in CPD, but not corresponding breath CO, ¹⁵ , ²² with the third showing promise at 8 weeks, though without further follow up. ¹⁹

Quality assessment

Cochrane's Risk of Bias 2 was used to assess study quality and potential for biased reporting. Results revealed that 50% of the included studies had an overall low risk of bias, while 30% and 20% were categorized as high risk and unclear, respectively. Across studies, bias in reporting outcomes was generally low, relying on objective criteria such as exhaled breath CO, cotinine, and CPD. The total sample sizes for six of the studies were small (≥20), increasing the likelihood that the analyses are underpowered to detect any differences should they exist. Additional information on quality assessment can be found in Supplemental Materials.

DISCUSSION

The current systematic review identified several key findings regarding the current efficacy of smoking interventions for individuals on MOUD. Consistent with previous reviews, first‐line smoking cessation pharmacotherapies, including NRT, bupropion, and varenicline, were largely ineffective in achieving abstinence for individuals engaged in MOUD. Among behavioral interventions, CM appears to have a fair degree of success in promoting initial abstinence among OUD patients, but these positive effects tended to be short‐lived. Integrated approaches that included both pharmacological and behavioral treatments demonstrated some success in achieving a meaningful reduction in cigarettes smoked per day; however, verification using objective measures (e.g., breath CO and cotinine) was either non‐significant or not measured. Overall, this updated review demonstrates limited progress in efforts to support smoking cessation among individuals with OUD and the need for further investigation into alternative treatments.

While some studies on first‐line pharmacotherapies observed a reduction in the number of cigarettes smoked per day, these effects were short‐lived. These findings contrast sharply with those observed in the general population, in which these medications double or triple the odds of smoking cessation at 6‐month follow‐up. ³⁹ These medications work by reducing nicotine reinforcement, craving, and withdrawal symptoms by targeting neurochemical pathways in the brain, including the nicotinic receptors and noradrenergic and dopaminergic systems. Individuals with OUD commonly experience craving and opioid withdrawal symptoms that are partially alleviated by smoking. OUD is associated with chronic changes in the neurochemical pathways that are targeted with smoking cessation medications. As such, novel pharmacological approaches are likely needed to address the unique biological context of co‐occurring OUD and TUD.

The vast majority of behavioral intervention studies identified by this review focused on CM interventions. While these studies generally demonstrated initial success, all faced a common challenge: once the incentive is removed, the behavior may revert. Nevertheless, these efforts align with broader evidence supporting CM and reinforcement‐based interventions for OUD. CM has demonstrated efficacy across multiple substance use disorders and has potential when treating opioid and tobacco use. Importantly, CM has been widely implemented across veterans affairs (VA) hospitals; demonstrating that it is possible to sustain CM treatment within large healthcare systems. ⁴⁰ To overcome the lack of durability of treatment effect beyond the duration of the intervention, there is a need for long‐term or maintenance‐based strategies, where the skills and motivation developed during the incentive period are sustained through other means.

Findings from combined pharmacological and behavioral interventions largely mirrored the patterns from non‐combined approaches—early success followed by diminishing effects over time. However, one promising study conducted in Norway found an integrated treatment to be twice as effective as the control in reducing the number of cigarettes smoked per day. ³⁰ This finding highlights a potential shift in treatment goals from complete abstinence to harm reduction. While quitting smoking remains the gold standard, focusing on a more achievable goal like reducing smoking may be a more pragmatic approach for this population. This is consistent with the harm reduction approach for TUD, which acknowledges that alternatives like reducing the number of cigarettes or switching to potentially less harmful nicotine products, such as e‐cigarettes, can help to reduce harm from tobacco. Unfortunately, the three included studies evaluating e‐cigarettes have small sample sizes and do not include an accompanying behavioral intervention. which could improve the use of e‐cigarettes as a tool to decrease cigarette smoking. ⁴¹ Almost half (46%) of individuals with OUD receiving MOUD report using e‐cigarettes as a means to quit or cut down on smoking. ² A recent Cochrane Review highlighted that there is some evidence that e‐cigarettes assist smoking cessation, ⁴² but remains possible that e‐cigarettes may perpetuate nicotine dependence. It's important to note that while reducing the number of daily cigarettes smoked may reduce biomarkers of tobacco‐specific carcinogens and other toxicants, the reduction is often much less than the proportional reduction in daily cigarettes consumed. This is due to compensatory changes in smoking behaviors, such as more frequent and deeper inhalations. While many of the harms from smoking, such as lung cancer, are related to daily smoking consumption, other outcomes, like all‐cause mortality and cardiovascular disease, are not consistently lowered with reduced smoking. ⁴³ Additionally, if e‐cigarettes are combined with behavioral treatment or NRT, it would be important to evaluate the effect of these interventions alone and in combination with e‐cigarettes using outcomes that track number of cigarettes smoked per day.

Multiple psychosocial factors may have an unfavorable impact on smoking cessation treatments, including financial problems, unstable housing, stressful living environment, and lack of access to medical care. ⁴⁴ The co‐occurrence of OUD and TUD may have significant biological and psychosocial interactions that lessen the effectiveness of available treatments. Further, two major shifts in the opioid and tobacco product landscape may be further affecting the treatment of TUD for individuals with OUD engaged in MOUD. First, the widespread use of fentanyl has led to significantly decreased MOUD retention rates. In some reports, retention rates have been cut by more than half. ⁴⁵ This shortened retention and high turnover of MOUD clinics reduce the window of opportunity to provide comprehensive smoking cessation within the MOUD setting. Second, with the rise of novel nicotine products, most notably e‐cigarettes and nicotine pouches, cigarette smoking reached historically low levels; approximately 11.6% of adults smoke cigarettes in the United States. ⁴⁶ While this presents a potential opportunity to transition individuals on MOUD to less harmful nicotine products, more research is needed to determine the effectiveness of these products in helping people quit smoking and to evaluate their long‐term health effects. E‐cigarettes appear to be a promising treatment approach for reducing regular tobacco cigarette use among people with OUD, but given the scarcity of clinical trials exploring this avenue, more studies may be needed to substantiate the results.

Some promising treatment approaches have not yet been evaluated for co‐occurring OUD and TUD. Psilocybin, a psychedelic compound with potent 5‐HT2A agonist properties, has shown promise as a treatment for TUD in early open‐label studies, and randomized clinical trials are currently underway. ⁴⁷ Given a favorable safety profile for medically administered psilocybin in clinical trials focused on complex psychiatric and addiction samples, ⁴⁸ it may also have therapeutic potential for individuals with OUD. A recent review article highlighted the potential for psilocybin to reduce opioid and nicotine use, with mixed results for other SUDs. ⁴⁷ Another promising approach is the use of digital technologies to expand the reach of CM beyond the clinic setting. ⁴⁹ Such an approach, if extended over longer periods, may reduce the risk of early relapse once the incentives are removed. Furthermore, low‐cost CM interventions, such as the fishbowl approach, could potentially be adapted for extended use, including for the treatment of TUD in individuals engaged in MOUD. In the fishbowl approach, participants can earn tickets for each reinforced behavior and then enter them into a drawing for a prize, providing a sustainable and scalable way to provide ongoing reinforcement with limited cost. The included studies also only incentivized abstinence; however, alternative reinforcers such as incentivizing treatment attendance, time, weight, or measure completion may also be effective.

To summarize, the prevalence of TUD remains exceptionally high among those with OUD receiving MOUD, despite a strong decline in tobacco product use across the broader population. This disparity highlights a critical need for targeted treatment development for this population, as treatment response rates are substantially lower for traditional treatments relative to the general population. We did not find any clinical trials focused on the use of novel tobacco products, such as nicotine pouches, that have been promoted by the manufacturers as a cessation aid with inconclusive efficacy. ⁵⁰ Problematically, very few studies defined abstinence using clear language related to the use of “noncombustible” products, and only six studies measured 7‐day point‐prevalence, the preferred measure when using biochemical verification. ⁵¹ Breath CO outcomes might reflect a reduction in cigarette smoking, but do not capture use of other “noncombustible” products. Reflecting a harm reduction approach, treatments aiming to reduce smoking are considered, but the benefits of such approaches, as well as the use of novel nicotine products like e‐cigarettes and nicotine pouches, warrant further investigation. Finally, most of the included studies focused on MOUD treatment with methadone; additional research is needed for buprenorphine, particularly for behavioral treatments, and examination of potential differential treatment effects by MOUD type. Given the significant health risks associated with TUD for people in MOUD, there is a clear and urgent need to develop more effective and lasting treatments for TUD in this population.

AUTHOR CONTRIBUTIONS

All authors are responsible for the content and writing of this paper.

CONFLICT OF INTEREST STATEMENT

The authors declare no conflicts of interest.

Supporting information

Supporting information.

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Parida S, Ameral V, Wolkowicz N, et al. Addressing tobacco use in the context of opioid use disorder: a systematic review of smoking cessation interventions. Am J Addict. 2026;35:565‐577. 10.1111/ajad.70154