Comparative effectiveness of missed dose protocols of opioid agonist treatment in British Columbia, Canada: protocol for a population-based target trial emulation

Abstract

Introduction

Methadone and buprenorphine/naloxone are effective medications for people with opioid use disorder; however, interruptions in daily dosing are common and diminish the benefits of these medications. While clinical guidelines in most North American jurisdictions, including British Columbia (BC), recommend dose adjustment after treatment interruptions to varying levels of specificity, the evidence to support these recommendations is limited. We aim to estimate the comparative effectiveness of alternative dose adjustment strategies on subsequent overdose-related acute care visits and discontinuation of opioid agonist treatment in BC, Canada.

Methods and analysis

Using a linkage of nine health administrative databases, we propose a population-level retrospective cohort study of adults aged 18 years or older in BC who initiated methadone or buprenorphine/naloxone between 1 January 2010 and 31 December 2022. We will specify parallel hypothetical trials, known as target trials, for methadone interruptions of 1–3 days, 4 days and 5–14 days, and buprenorphine/naloxone interruptions of 1–5 days and 6–14 days. Following the index interruption, the primary outcomes are the time to overdose-related acute care visits and treatment discontinuation (interruptions lasting >14 days), with time to all-cause acute care visits as a secondary outcome. The intention-to-treat effect will be estimated using both propensity score and instrumental variable approaches. A range of sensitivity analyses will assess the robustness of our results, including cohort and timeline restriction, alternative definitions of exposure and outcome and alternative estimation strategies.

Ethics and dissemination

The protocol, cohort creation and analysis plan have been classified and approved as a quality improvement initiative by Providence Health Care Research Institute and the Simon Fraser University Office of Research Ethics. All data are deidentified, securely stored and accessed in accordance with provincial privacy regulations. Results will be disseminated to local advocacy groups and decision-makers, national and international clinical guideline developers, presented at international conferences and published in peer-reviewed journals electronically and in print.

STRENGTHS AND LIMITATIONS OF THIS STUDY.

• By leveraging nine linked datasets from British Columbia, the study captures a broad and representative population with detailed longitudinal data on opioid agonist treatment (OAT) episodes, clinical outcomes and healthcare utilisation.

• The study applies a robust design to emulate the components of a randomised controlled trial using real-world administrative data, enhancing causal inference while maintaining the feasibility of observational research.

• The study evaluates retention and overdose-related acute care visits—outcomes with direct implications for patient safety and clinical practice—ensuring findings are actionable and impactful for OAT policy and guidelines.

• By employing the inverse probability of treatment weighting, high dimensional propensity score and instrumental variable estimation approaches, this study will yield strong evidence for missed dose protocols.

• Threats to internal validity, such as confounding by indication, variable definitions and potential uncontrolled confounding, will be addressed through a comprehensive range of sensitivity analyses and bias assessments.

Introduction

Opioid use disorder and its treatment

Opioid use disorder (OUD) is a significant public health concern, affecting an estimated 40.5 million people globally in 2017.¹ In 2023, 22 Canadians died each day on average from opioid toxicity, marking a 7% increase compared with 2022.² Methadone and buprenorphine/naloxone, two long-acting opioid agonist treatments (OAT), are used to treat people with OUD. Treatment typically begins with a low initial dose that is gradually titrated to a stabilised dosage that eliminates individuals’ opioid withdrawal symptoms and manages opioid cravings.³ Maintaining the stabilised dose reduces intoxication and opioid craving,^{4 5} with a long history of demonstrated effectiveness in reducing morbidity and mortality among people with OUD.6,11 Despite an estimated 9.37 million adults in the USA needing treatment for OUD in 2022, only 25.1% received medications such as methadone, buprenorphine, buprenorphine-naloxone, injectable buprenorphine, buprenorphine implants or naltrexone (oral or injectable).¹² In Canada, the annual number of OAT claims decreased by 19.5% from 2018 to 2022.¹³ This decline in treatment engagement indicates a failure to initiate and retain individuals in OAT.¹⁴

Methadone and buprenorphine/naloxone are often dispensed on a daily basis¹⁵ which is burdensome for many to sustain engagement in treatment.^{16 17} Tolerance can be substantially lost when methadone is interrupted ≥5 days due to the re-equilibration of methadone-inducible enzymes, necessitating a restart to prevent overdose. In contrast, buprenorphine/naloxone, being a partial agonist, requires a lower degree of vigilance and treatment may need to be restarted after interruptions lasting ≥6 days.^{3 18} Each month in British Columbia (BC), Canada, 10% of individuals receiving methadone interrupt their treatment for ≥5 days and 21% of individuals receiving buprenorphine/naloxone interrupt their treatment for ≥6 days,¹⁹ often failing to reach a stabilised dose through induction.²⁰ These interruptions may occur repeatedly, presenting a barrier to reaching and retaining the stabilised dose and to eliminating the need for individuals to seek out unregulated opioids. Successful re-engagement after interruptions is a significant challenge as individuals may encounter considerable risk of overdose toxicity.^{21 22} Individuals exhibit a 1.56–4.30 fold higher likelihood of opioid overdose in any given month with interruptions lasting for ≥15 days, compared with periods of stable treatment.²³ Therefore, missed dose protocols in OUD treatment guidelines in Canada and other jurisdictions recommend dose adjustment at reinitiation.318 24,31 The consecutive number of missed days during the interruption period may be indicative of degree of tolerance lost and can guide the reinitiation, which may be done with either a reduced dose or the same as the last dispensed dose prior to interruption. Following reinitiation, prescribers titrate individuals’ doses to eliminate withdrawal symptoms, thereby reducing the risk of overdose. The extent of parallel use of unregulated substances such as fentanyl during the interruption is often unknown to the prescribers, adding uncertainty when determining individuals’ tolerance and the appropriate dose adjustment following the interruption.³² Safe and effective dose adjustment after interruptions relies on the judgement of prescribers to a varying degree in Canada and other jurisdictions.318 24,31 33 While lower reinitiation dosages may be insufficient to control withdrawal symptoms, resuming the past dose dispensed may lead to methadone toxicity, leaving prescribers to weigh the difficult choice between a subtherapeutic effect and the potential for harm.

Current clinical practices on dose adjustment following interruption

We summarised the missed dose protocols of methadone and buprenorphine/naloxone interruptions from the clinical guidelines for BC, Canada and other jurisdictions in table 1.

Table 1. Clinical guidelines on missed dose protocols of methadone and buprenorphine/naloxone treatment.

Guideline	Methadone		Buprenorphine/naloxone
	Interruptions	Dose adjustment*	Interruptions	Dose adjustment
BCCSU, BC, CAN, 20173	1–2 days	No change	1–5 days	No change
	3–4 days	No change, ≤30 mg or 50% reduction	6–7 days	No change, 4/1 mg or 8/2 mg
	≥5 days	5–30 mg	≥8 days	4/1 mg
BCCSU, BC, CAN, 202318	1–3 days	No change	1–5 days	No change
	4 days	Maximum of 50% reduction or 30–40 mg	≥6 days	Retitration
	≥5 days	30–40 mg
CAMH, CAN, 202130	1–3 days	No change	1–5 days	No change
	4 days	Maximum of 50% reduction or 30–40 mg	6–7 days	No change, 4/1 mg or 8/2 mg
	≥5 days	30–40 mg	≥8 days	4/1 mg
Q-Land, AUS, 202331	1–3 days	No change	1–3 days	No change
	4–5 days	50% reduction or 40 mg	4–5 days	No change or maximum 24 mg
	>5 days	Retitration	>5 days	Retitration
AUS, 201426	1–3 days	No change	1–3 days	No change
	4–5 days	Minimum of 50% reduction or 40 mg	4–5 days	Minimum of 50% reduction or 8 mg
	>5 days	Retitration	>5 days	Retitration
NSW, AUS, 201827	1–3 days	No change	1–3 days	No change
	4–5 days	Maximum of 50% reduction or 40 mg	4–5 days	Maximum of 50% reduction or 8 mg
	>5 days	Retitration	>5 days	Retitration
New Zealand, 201424	1–2 days	No change	1–2 days	No change
	3 days	No change or 50% reduction	3 days	No change or 50% reduction
	4–5 days	50% reduction	4–5 days	50% reduction
	>5 days	Retitration	>5 days	Retitration
UK, 201729	1–2 days	No change	1–2 days	No change
	3–4 days	No change or reduction	3–4 days	No change or reduction
	≥5 days	Retitration	≥5 days	Retitration

CRISM, Canada, 2018 and ASAM, USA, 2015,34 202035 guidelines have limited specific guidelines for dose adjustment after missed days.

^*Alternative adjustment strategy depends on the daily dosage on the last date of treatment receipt before interruption.

ASAM, American Society of Addiction Medicine; AUS, Australia; BC, British Columbia; BCCSU, British Columbia Centre on Substance Use; CAMH, Centre for Addiction and Mental Health; CAN, Canada; CRISM, Canadian Research Initiative on Substance Misuse; NSW, New South Wales; Q-Land, Queensland state.

Notably, the 2023 BC Guidelines updated the missed dose protocols established in 2017 making the dose adjustment recommendations more flexible, while still differentiating guidance based on the number of missed days of treatment.^{3 18}

Clinical guidelines from other jurisdictions, including the Centre for Addiction and Mental Health in Ontario, Canada (published in 2021),³⁰ Australian national guidelines (published in 2014),²⁶ New South Wales, Australia (published in 2018)²⁷ and New Zealand (published in 2014)²⁴ recommend resuming the previous dose after a 1–2-day methadone interruption. For 3–4 day and ≥5 days interruptions, recommendations varied widely. Despite buprenorphine/naloxone being a partial agonist therapy, unlike the full agonist methadone, guidelines from Queensland and New South Wales, Australia,^{27 31} New Zealand²⁴ and the UK (published in 2017)²⁹ suggest similar dose adjustments following interruptions for both therapies. Several guidelines such as Canadian national guidelines published in 2018,²⁸ and the American Society of Addiction Medicine’s guidelines published in 2015 and 2020^{34 35} provide no specific guidance.

Inconsistencies in the recommendations of dose adjustment strategies after missed doses across clinical guidelines highlight the lack of evidence supporting this practice. Evidence referenced in missed dose protocols of the 2017 BC guidelines³ was primarily derived from a report on safe induction and stabilisation of methadone (published in 2013).³⁶ The report, based on a review of research publications from 1979 to 2011 and expert consensus in the field, recommended reinitiating treatment with a reduced dose after an interruption, though it does not specify a particular adjustment strategy.³⁶ The 2023 BC guidelines updated missed dose protocols with consideration of the increased likelihood of fentanyl use.¹⁸ These updates were informed by earlier BC guidelines¹⁵ as well as the clinical guidelines from other jurisdictions such as California,³⁷ Australia²⁷ and the UK.²⁹ However, the reference guidelines were largely based on expert consensus rather than empirical evidence. Thus, 2023 BC guidelines lack any empirical evidence from current clinical practices to support their missed dose protocols. Likewise, we found no empirical evidence extracted from clinical trials or observational studies to support dose adjustment strategies after buprenorphine/naloxone interruptions.^{3 18} In an observational study cited in the 2017 BC guideline, several starting doses were compared for buprenorphine retention, which found moderate (8–24 mg) dose more effective compared with lower (<8 mg) and higher (>24 mg) starting dose.³⁸ However, the study did not investigate dose adjustment following interruptions in buprenorphine treatment. Therefore, it is unclear from any empirical studies how effective these strategies are in preventing overdose-related acute care visits and promoting treatment retention.

Qualitative studies assessing client perspectives on missed days and subsequent dose adjustment rules have indicated that current practices do not adequately meet their needs or prevent discontinuation. People with lived and living experience of OAT report frustration and disagreement with dose adjustment rules and management,^{39 40} challenges with maintaining daily treatment⁴⁰ and turning to the unregulated drug supply following dose adjustment.^{41 42} For example, a 2014 study in Maryland, USA interviewed 139 OAT clients who had discontinued buprenorphine within 6 months—24% discontinued treatment due to disagreements with OAT programme staff and 17% discontinued due to difficulties attending the programme or interrupting regular doses.⁴⁰ In 2019, another qualitative study in Ottawa, Ontario, interviewed 12 individuals who had been on methadone for periods ranging from 3 months to 4 years. One participant reported a preference for unregulated drugs due to the challenges they faced after missed days on treatment.⁴¹

We aim to evaluate the effectiveness of dose adjustment strategies following treatment interruptions in minimising the risk of overdose-related acute care visits and preventing treatment discontinuation among adults aged 18 and older in BC who have initiated methadone or buprenorphine/naloxone therapy from 2010 to 2022. We will compare a range of dose adjustment strategies following methadone and buprenorphine/naloxone treatment interruptions of up to 14 days.

Methods and analysis

Study design

We propose a population-based retrospective cohort study to emulate target trials (ie, hypothetical randomised clinical trials (RCTs)) from the population of methadone and buprenorphine/naloxone initiators from 1 January 2010 to 31 December 2022 (or most recent data available at the time of analysis) in BC. We will adjust for COVID-19-related practice changes in our analytical approach. While RCTs represent the gold standard for establishing comparative effectiveness, conducting an RCT is time-consuming and may not be generalisable to the population of treatment recipients in BC or elsewhere.⁴³ By combining large health administrative data with robust statistical methods, observational studies can avoid many common biases and provide treatment effect estimates derived from real-world settings.44,47 Table 2 summarises the key components of the proposed study design.

Table 2. Key components of the emulated target trials on dose adjustment strategy following interruptions using the observational data.

Protocol components	Hypothetical target trial	Emulation of the trial from BC health administrative data
Eligibility criteria	Adults aged 18 years or older who initiated methadone or buprenorphine/naloxone between 1 January 2010 and 31 December 2022 will be included. Individuals who interrupted methadone for 1–3 days will be eligible for trial 1. Similarly, trials 2 and 3 will include methadone initiators interrupted for 4 days and 5–14 days, respectively. Trials 4 and 5 will include buprenorphine/naloxone initiators interrupted for 1–5 days and 6–14 days, respectively. Participants must not be pregnant, incarcerated on the reinitiation date after the interruption, or have a history of cancer or palliative care.	The same eligibility criteria as the hypothetical target trial will be applied. The emulation will include both incident user and prevalent new-user designs.
Treatment strategies	Initiation of trial-specific treatment strategies defined in figure 2 which is based on 2023 BC clinical guideline.18	Same.
Assignment procedures	Eligible individuals of specific trial will be randomly assigned to one of the treatment strategies on the reinitiation date. The prescribers, healthcare teams and individuals are aware of the treatment status.	We will classify individuals into one of treatment strategies based on their dispensation records on the reinitiation date. The prescribers, healthcare teams and individuals are aware of the treatment status.
Time zero	The date when eligible individuals are randomised to treatment strategies.	The date when eligible individuals reinitiate treatment following the trial-specific interruption.
Outcomes	Time to overdose-related acute care visits and treatment discontinuation are the primary outcomes of interest. The first visit date due to overdose after the time zero will be considered to define the time to overdose-related acute care visits. Treatment discontinuation is defined if methadone or buprenorphine/naloxone dispensation is interrupted for >14 days.	Same. Due to the lack of inpatient information in our linked database, we assume individuals starting treatment before hospitalisation will continue treatment during their hospital stay without discontinuation.
Follow-up	Follow-up begins on the date of randomisation and concludes on treatment discontinuation (only for the outcome of OAT discontinuation), death, overdose-related acute care visits, loss to follow-up, 1 year after time zero or the administrative end of follow-up on 31 December 2022 whichever occurs first.	Follow-up begins on the reinitiation date and ends at the earliest of the following events: treatment discontinuation (only for the outcome of OAT discontinuation), overdose-related acute care visits, death, loss to follow-up, 1 year after time zero or the administrative end of follow-up on 31 December 2022.
Causal contrasts	Intention-to-treat	Treatment initiator analysis
Analysis plan	Unadjusted Cox-PH regression to estimate the association between treatment strategies and treatment discontinuation. HRs, cumulative incidence (risk) differences and cumulative incidence curves will be estimated from fitted Cox-PH model for comparison purposes.63 64 81 Model-based SE will be used for inference.	IPTW, hdPS and IVs will be applied to control observed and unobserved confounders alongside weighted Cox-PH regression models. The weights will be calculated from the fitted exposure models through binary or multinomial logistic regression approach.* HRs, risk differences and cumulative incidence curves will be estimated for comparison. Sandwich variance will be used to construct 95% CIs for the HR, but bootstrap-based method will be applied to construct the confidence intervals for the risk difference and cumulative incidence curves under IPTW, hdPS and IV analysis.63 64 81

^* Least absolute shrinkage and selection operator models for hdPS analysis.

BC, British Columbia; Cox-PH, Cox-proportional hazard; hdPS, high dimensional propensity score estimation; hdPS, high-dimensional propensity score; IPTW, inverse probability of treatment weighting estimation; IV, instrumental variable.

We will employ population-level data derived from a linkage of nine provincial health administrative databases in BC, Canada, where residents are obligated to enrol in a provincial single-payer health insurance plan. Using the BC PharmaNet database⁴⁸ (which records daily medication dispensations), we will identify methadone and buprenorphine/naloxone dispensation dates and doses (see the list of drug/product identification numbers in online supplemental eTable 1) to define treatment interruptions. The Discharge Abstract Database⁴⁹ (DAD; documenting hospitalisations), Medical Services Plan⁵⁰ (MSP; containing physician billing records), BC Vital Statistics⁵¹ (capturing deaths and their underlying causes), BC Provincial Corrections⁵² (recording entries into incarcerations and releases to the community), Perinatal Care Database⁵³ (capturing maternal/infant care and outcomes), National Ambulatory Care Reporting System⁵⁴ (NACRS; capturing Emergency Department visits), Client roster⁵⁵ (capturing demographic and geographic information for the Ministry’s clients) and BC Social Development and Poverty Reduction database⁵⁶ (capturing social assistance receipt) will be used. These databases are linked using a unique deidentified individual-level personal health number by the BC Ministry of Health.⁵⁷ The database description and timeline for data extraction from the various linked databases is summarised in online supplemental eTable 2.

Study population

Since the 2023 BC guidelines¹⁸ outlined differential dose adjustment strategies following 1–3, 4 and ≥5 days interruptions of methadone, and 1–5 and ≥6 days interruptions of buprenorphine/naloxone interruption, we will conduct distinct target trials using each of these durations to estimate the effectiveness of subsequent dose adjustment strategies as outlined in table 2. A maximum 14 days interruption threshold will be considered to define trials of methadone interruption for 5–14 days and buprenorphine/naloxone interruption of 6–14 days. Implicitly, these duration thresholds correspond to the assumption of homogeneous physiological changes following these interruptions.¹⁸ For both methadone and buprenorphine/naloxone trials, individuals will be included if they are aged ≥18 years and received methadone or buprenorphine/naloxone between 1 January 2010 and 31 December 2022. We will exclude individuals who are pregnant, incarcerated on the day they reinitiate treatment and/or have a history of cancer or palliative care. Pregnant women will be excluded due to potential variations in clinical management of treatment interruptions unique to pregnant individuals.¹⁸ Individuals under incarceration will be excluded as their initiation of treatment within the criminal justice system may necessitate distinct treatment management strategies.⁵⁸

Study follow-up

OAT episodes are defined as continuous receipt of OAT dispensations without an interruption lasting >14 days (see details in figure 1). For an OAT episode in which at least one interruption lasting ≤14 days occurs, we define time zero as the date on which the individual receives their first dose of methadone or buprenorphine/naloxone after their first interruption, hereafter referred to as the reinitiation date. To capture the clinical experiences of both first and successive attempts, we will use both incident user and prevalent new-user designs. The former will require individuals having an interruption within the first OAT episode (since 1 January 1996), while the prevalent new-user design includes individuals who reinitiate within the first OAT episode and those who reinitiate in the subsequent episodes after interruption of >14 days. Follow-up starts from the reinitiation date and ends at overdose-related acute care visits, treatment discontinuation (defined as no OAT receipt for >14 consecutive days), death, 1 year after time zero or the administrative end of follow-up on 31 December 2022, whichever happens first.

Figure 1. Construction of OAT episodes for incident and prevalent new-user designs in primary and sensitivity analysis. OAT, opioid agonist treatment.

Key measures

The primary exposure and outcome are empirically derived since they are not indicated directly within the linked databases. The primary exposure is the derived dose adjustment strategy on the reinitiation date—the thresholds for which were defined according to the 2023 BC OUD guidelines.¹⁸ To estimate and compare the effectiveness of alternative dose adjustment strategies, we have additionally considered the guidelines in other jurisdictions and otherwise employed subject area expertise (see trial-specific exposure categories in figure 2).

Figure 2. Treatment strategies for methadone and buprenorphine/naloxone trials for primary and sensitivity analysis. Individuals falling into multiple treatment groups will be assigned based on a descending order of precedence.

Time to overdose-related acute care visits and treatment discontinuation will be considered as our primary outcomes of interest. Time to overdose-related acute care visits will be measured based on the first visit date due to overdose (ICD-10 codes T40, T42.4 and T43.6) after the time zero. Treatment discontinuation will be defined as receiving no OAT dispensation for >14 consecutive days. Our linked database lacks information on treatment dispensation in inpatient settings. Therefore, we assume that individuals who were on OAT before hospitalisation will remain in treatment throughout their hospital stay.

Covariate selection

In observational studies, the assumption of no uncontrolled confounding cannot be fully validated. However, we will account for all possible confounding variables that are accessible in our linked database. A systematic review was conducted to identify factors associated with OAT retention.⁵⁹ The list of covariates was then augmented by another study with factors associated with OAT retention.⁶⁰ We propose to use the augmented list of covariates to select confounders for our study based on the modified disjunctive cause criterion⁶¹ where we include factors associated with the exposure, outcome and both. The proxies of the factors will be included additionally as confounders, excluding instrumental variables (IVs) for the primary analysis. The confounder set will include individuals’ demographic characteristics such as age (18–29, 30–39, 40–49, 50+ years), sex (male, female), region (rural, urban), unstable housing (never/last >5 years, last 1 year, last 5 years), receipt of income assistance history (never/last>1 year, <1 year), incarceration history (never/last>1 year, <1 year); comorbidities and clinical history related factors such as opioid dispensation history prior to OUD diagnosis in the past year (yes, no), Charlson comorbidity index (0, >0), drug-related acute care visits in the past month (yes, no), asthma or chronic obstructive pulmonary disease in the past year (yes, no), dispensations of psychiatric or sedative medication in the past month (yes, no), substance use disorder other than opioid in past year (yes, no), alcohol use disorder in past year (yes, no), serious mental health disorder in past year (yes, no), hepatitis C in past year (yes, no), chronic pain in past year (yes, no), tobacco use disorder in past year (yes, no), urine drug test in past month (yes, no), attachment to the prescriber on the reinitiation date (yes, no) are associated with both treatment strategies and outcome.^{59 60} Additionally, the calendar year at time zero, duration of treatment retention before the interruption, number of prior treatment episodes (for prevalent new-user design) and daily dosage on the last date of treatment receipt before interruption, virtual care in past month (yes, no), and receipt of prescriber safer supply in past month (yes, no) will be included as controls for confounding.

Statistical analysis

We will conduct an initiator analysis to compare the time to overdose-related acute care visits and treatment discontinuation in each group of individuals exposed to the different treatment strategies.⁶² We will report the HR, cumulative incidence (risk) difference at 1 year post-reinitiation date and cumulative incidence curves to facilitate the comparison of the alternative dose adjustment strategies recommended in clinical guidelines.^{63 64} As the primary analysis, inverse propensity of treatment weighting (IPTW) will control for measured factors that may systematically influence the selection of dose adjustment strategies and the outcomes. We propose an alternative specification of the IPTW by high-dimensional propensity score (hdPS) to reduce the residual confounding as sensitivity analysis. Additional sensitivity analysis will be considered through IV estimation as an alternative estimation strategy to address selection into alternative exposure strategies by unmeasured factors. Concordance in findings from IPTW with only measured confounders, and hdPS or IVs will strengthen our inference. We will use SAS V.9.4 to prepare analytical data and conduct the statistical analysis using R V.4.5.0.

IPTW estimation

We will apply the IPTW approach to control for potential factors that may influence selection into a specific dose adjustment strategy under each trial.⁶⁴ Binary or multinomial logistic regression models will be used for the estimation of the propensity score of specific dose adjustment strategies. Stabilised weights, truncated at the 99th percentile, will be assigned to individuals based on the inverse of the propensity score to achieve the balance in baseline covariates. Weighted Cox proportional hazard (Cox-PH) regression models will then be used, including the exposure category (binary or multinomial) and any baseline confounders that remain imbalanced after weighting. The HR estimated from the fitted Cox-PH models for both primary outcomes will compare the specific dose adjustment strategy group versus no dose change group. We will then compute the predicted time-to-event (survival) probabilities, specific to each individual, at each day under the fitted Cox-PH model, and then average these survival probabilities over all individuals. We then compute the risk of overdose-related acute care visits and treatment discontinuation as 1 minus the averaged probability of survival and the corresponding risk differences for the specific dose adjustment group versus no dose change group. Sandwich variance estimates will be used to construct 95% CIs for the estimated HRs. For the risk difference and cumulative incidence curves, we will take 500 bootstrap samples (with replacement) to construct CIs and confidence curves, respectively.^{63 64} IPTW estimation steps are detailed in online supplemental eMethods 1.

hdPS estimation

The IPTW approach calculates propensity score-based weights using investigator-selected covariates. However, this method may be subject to residual confounding. For example, aspects of individuals’ disease severity and level of medical comorbidity may not be fully observed and thus left uncontrolled in the IPTW estimation. To address this potential residual confounding, we will employ the hdPS algorithm⁶⁵ which is a semiautomated, data-driven technique that identifies potentially important proxy variables from administrative data for inclusion in propensity score models. We will use five data dimensions: DAD diagnostic codes (International Classification of Diseases (ICD)-10, four digits), DAD procedure codes (five digits), MSP diagnostic codes (ICD-9, three digits), MSP fee codes (five digits) and PharmaNet drug dispensation codes (eight digits). For each trial, covariates will be assessed within a 6-month window, excluding the covariates related to the investigator-selected covariates, exposure and outcome, colliders and selected instruments. Proxy covariates with low prevalence (<50 individuals for trials 1 and 4,<20 for the trial 2, 3 and 5) will be excluded. For each candidate variable, we will create three recurrence variables (occurrence at least once, more frequent than median and more frequent than the 75th percentile), and duplicates will be deleted. For each outcome, we will apply the least absolute shrinkage and selection operator (LASSO) method with Cox PH model to select the top-ranked 200 covariates.⁶⁶ The selected empirical covariates along with the investigator-selected covariates will be included in the propensity score models (binary, multinomial regression models or LASSO models) to estimate the propensity score weights.⁶⁷ We will calculate the stabilised weights (truncated at 99th percentile) and apply weighted Cox-PH regression models that include the exposure variable and any investigator-selected covariates remain imbalanced (Standardized Mean Difference (SMD)≥0.10). These models will estimate HRs, risk differences and cumulative incidence curves. Inference for HRs will be conducted using sandwich variance estimators, while CIs for risk differences and cumulative incidence curves will be calculated from 500 bootstrap samples, as described in IPTW estimation.^{63 64} The detailed steps of hdPS estimation are outlined in online supplemental eMethods 2.

IV estimation

Propensity score methods are predicated on the assumption of selection on the basis of measurable factors. IV methods will be used to control for the potential unmeasured factors influencing the selection of individuals into dose adjustment groups on the reinitiation date.^{68 69} For IV methods to be valid, the chosen instrument variable must meet four key conditions: (1) IV must be associated with the exposure; (2) it must affect the outcome only through the exposure (exclusion restriction); (3) it must not share any uncontrolled causes with the outcome (the IV must not be confounded) and (4) monotonicity in the association between the IV and exposure, and the IV must not be an effect modifier of the exposure-outcome association (homogeneity). Prescriber preference has been used as a suitable IV in several comparative effectiveness studies.70,72 Given the limited guidance on IV analysis for multicategory exposures with time to event outcomes in the literature, we will analyse binary exposures that will be defined by collapsing treatment categories (eg, any dose adjustment vs no dose change) for each trial. The trials with >2 categories such as the trials 1–3: methadone interruption of up to 14 days, and the trial 5: buprenorphine/naloxone interruption of 6–14 days may require repeated analyses. For each trial, we propose testing two binary IVs: (a) the prescriber-level preference to prescribe a specific dose adjustment on the reinitiation date and (b) the facility-level preference for the same, measured among OAT clients within the 6 months prior to reinitiation.⁷³

While the IV assumptions can be assessed, in part, empirically, they cannot definitively confirm all IV assumptions. These assumptions may be assessed empirically by evaluating the IV’s association with dose adjustment strategies (condition 1), which we will support by conducting first stage regression and an F-test afterwards. We will test the evidence of falsification for the conditions 2 and 3 using the instrumental inequalities and clinical expertise of a scientific advisory committee. For condition 3, we additionally will present the bias component between a non-IV estimator and the IV estimator for each measured covariate to empirically check that the proposed IV is not associated with the covariate. We will consider the opinions from clinical expertise of the committee to assess the condition 4 (homogeneity and monotonicity).⁷⁴ We will apply a two-stage residual inclusion approach to execute the IV estimation and estimate the local average treatment effect.^{75 76} The first stage involves a logistic regression approach to model the exposure on the selected IV and other selected covariates and to estimate the residuals. The estimated residuals indicate uncontrolled effect in exposure selection due to unmeasured covariates. We will incorporate the residuals into Cox-PH outcome models alongside the original exposure and selected covariates. The HR, risk difference and cumulative incidence curves will be estimated from the fitted Cox-PH models. CIs for the HRs will be calculated using sandwich variance estimators, while bootstrap-based CIs will be used for risk differences and cumulative incidence curves, as outlined in the IPTW and hdPS estimation methods.^{63 64} The steps of IV estimation are outlined in online supplemental eMethods 3.

Subgroup and sensitivity analyses

We propose to conduct a range of subgroup and sensitivity analyses to evaluate the robustness of our results and the heterogeneity of treatment effects among key subgroups. We will establish predetermined objectives focusing on restricting the study population and timeline, categorising key variables and applying alternative estimation strategies (see table 3 for details). Relevant findings from each analytical approach will be presented in a forest plot. Any deviations from this protocol will be documented in the final reports.

Table 3. Proposed subgroup and sensitivity analysis.

Proposed sensitivity analysis	Rationale
Sample restriction
Stratified analysis for individuals who interrupted at a higher dose (≥80 mg/day for methadone; ≥16 mg/day for buprenorphine/naloxone)	A higher dose (≥80 mg/day for methadone; ≥16 mg/day for buprenorphine/naloxone) is associated with increased treatment retention and reduced unregulated opioid use.18 We will stratify the cohort based on the aforementioned dose at treatment interruption and conduct a stratified analysis to assess the impact on our primary results
Stratified analysis for the duration of treatment retention before time zero (1 to <3, 3 to <6, 6 to <12 and ≥12 months for methadone and buprenorphine/naloxone)	Cumulative incidence of treatment interruption (5 days for methadone or 6 days for buprenorphine/naloxone) increases with the duration from OAT initiation.82 We will stratify individuals based on the treatment retention and conduct a stratified analysis.
People who completed induction	The induction phase for treatment with methadone and buprenorphine/naloxone occurs while individuals receive their initial dose and gradually titrate up to their maintenance dose. Individuals are closely monitored during the induction phase to assess withdrawal symptoms, cravings and other adverse effects.3 18 Individuals are more unstable during induction phase compared with the maintenance phase.83 We will restrict the study population to individuals who completed induction, that is, individual reaches the end of a 2-week period with no dose increases.20 We will re-run the analysis to assess the impact of induction phase on our results.
Individuals with OUD with >1 year of cumulative OAT experience	To access the impact of dose adjustment strategies on treatment discontinuation among individuals with OAT experience
Evaluation of alternate exposure thresholds according to different clinical guidelines	Given that the 2017 BC guidelines3 provided dose adjustment strategies after missed methadone doses of 1–2, 3–4 or ≥5 days, and missed buprenorphine/naloxone doses of 1–5, 6–7 and ≥8 days, we will redefine the methadone trial to account for interruptions of 1–2, 3–4, 5–7 and 8–14 days, and the buprenorphine/naloxone trial to account for interruptions of 1–5, 6–7 and 8–14 days. Other components of trial emulation protocol will remain unchanged. This alternative trial definition will help assess the robustness of the results across different interruption lengths.
Excluding individuals who reinitiated from 1 October 2022 to 31 December 2022.	To address potential bias due to inadequate follow-up time near the study end date, we will exclude individuals reinitiating OAT in the final 3 months. This allows assessment of robustness to administrative censoring.
People with OUD in regions with highest fentanyl concentrations*	To access the treatment association among those who primarily misuse fentanyl.
Timeline restriction
The date of the first death for which fentanyl was detected in the province (1 April 2012)	Fentanyl, which is 50–100 times more potent than morphine, has significantly contributed to the overdose epidemic in North America and is implicated in 84% of drug-related toxicity cases in Canada from January to June 2023.84 Fentanyl was first detected in overdose deaths in BC on 1 April 2012. We will redefine the study population to the fentanyl era (1 April 2012 to 31 December 2022) and conduct the analysis. This will control for the impact of fentanyl’s emergence on treatment strategies and discontinuation.
Exposure classification
Treatment categories of each trial are redefined as of figure 1.	The treatment categories in the primary analysis are not explicitly defined but are empirically derived from the linked data set. This reclassification of treatment categories will assess the impact of alternative dose adjustment strategies on the primary results.
Alternative time zero: reinitiation dates after any (ie, first, second, and subsequent) treatment interruptions within episode	While we considered the first reinitiation date as the time zero in primary analyses, incorporating repeated eligibility and subsequent time zero increases statistical efficiency of the estimate.85 An individual may meet eligibility criteria repeatedly (such as following the first, second and subsequent interruptions) within an OAT episode in incident user and prevalent new-user designs. Following each interruption, we will mark the reinitiation date as a new time zero to emulate the trials. All covariates measured at each time zero will be included in the propensity score models of IPTW along with one additional confounder.† Other components of the emulation protocols will remain the same.
Outcome definition
Episode discontinuation: 30 days	Alternative discontinuation thresholds have been defined in other studies.86
Secondary outcome: all-cause acute care visits	In 2023, opioid-related poisonings resulted in 17 hospitalisations and 78 ED visits per day in Canada, marking a 16% increase compared with 2022.2 Repeat ED visits (two or more) for OUDs within a year rose from 26% to 34% between 2018 and 2022 in Alberta, Ontario and the Yukon.87 Time to all-cause acute care visits will be considered secondary outcomes. We will repeat the statistical analysis for this outcome to evaluate the impact of secondary outcome on our results. Other components of the target trial and emulation process will remain the same.
No truncation at 12 months of follow-up	While this redefining follow-up may cause instability in the weights of statistical analysis, the non-truncation at 12 months is to confirm the results.
Alternative definition of prevalent new users: no OAT dispensation in past 30 days	To account impact of alternative definition of prevalent new users on our results.
Composite outcome: Overdose-related acute care visits or OAT discontinuation	Instead of considering separate outcomes of overdose-related acute care visits and OAT discontinuation, we will consider the composite outcome of any of the two events. The other components of emulation will remain the same.
Model specification
Machine learning algorithms in hdPS analysis67 88	Potential interactions and non-linear terms may not have been fully captured in the hdPS analysis due to the large number of investigator-selected and top-ranked 200 empirical covariates, potentially leading to model misspecification bias. To address this potential bias, we will apply cross-fitted doubly-robust estimator to compare the treatment.88 We will model the binary exposure‡ using SuperLearner89 with a library consisting of generalised linear models, generalised additive models, multivariate adaptive regression splines, random forests and extreme gradient boosting. The conditional survival and censoring models will be estimated using the survSuperLearner90 with a library consisting of the treatment group-specific Kaplan-Meier estimators, parametric survival models, Cox proportional hazard models, generalised additive models and piecewise constant hazard models.88 A fivefold cross-validation will be applied to estimate each of the models using the same selected covariates specific to each trial. We will then estimate the risk difference at 1 year of post reinitiation date and cumulative incidence curves to compare the dose adjustment strategy (see detailed in online supplemental eMethods 4).

^*Restricted to the lower mainland Vancouver area after 1 April 2016 (declaration of public health emergency).

^†number of treatment interruptions prior to time zero.

^‡Binary exposure (which are the same as constructed for IV analysis): 1 for specific dose adjustment strategy and 0 for no dose change group.

BC, British Columbia; ED, emergency department; hdPS, high dimensional propensity score estimation; IPTW, inverse probability of treatment weighting estimation; IV, instrumental variable; OAT, opioid agonist treatment; OUD, opioid use disorder.

Patient and public involvement

Although no patients were directly engaged in designing this study, its conceptualisation was shaped by previous interactions with local advocacy organisations representing individuals who use drugs and those accessing OAT.⁷⁷ Qualitative feedback on this and other related objectives outlined in the parent grant R01DA050629 was incorporated to prioritise this analysis, taking into account its potential impact on client engagement. The results will be disseminated to local advocacy groups after the analysis is completed.

Ethics and dissemination

The research team obtained access to databases through the BC Ministries of Health and Mental Health and Addiction in response to the provincial opioid overdose public health emergency. This initiative is categorised as a quality improvement project. The Providence Health Care Research Institute and the Simon Fraser University Office of Research Ethics reviewed the analysis, deeming it exempt according to Article 2.5 of the 2018 Tri-Council Policy Statement: Ethical Conduct for Research Involving Humans.⁷⁸ This study adheres to international guidelines, including Strengthening the Reporting of Observational Studies in Epidemiology guidelines,⁷⁹ and will be administered for ex post evaluation by a multidisciplinary scientific advisory committee. All study data are stored and managed in a secure, access-controlled environment maintained by Centre for Advancing Health Outcomes and accessed through approved data access protocols. Only authorised research personnel can access deidentified data. Data handling follows institutional and provincial privacy regulations. The results will be disseminated through peer-reviewed journals both electronically and in print, as well as at national and international conferences. This research aims to generate robust evidence for the safe and effective dose adjustment strategy after missed methadone or buprenorphine/naloxone on the reinitiation date, with the goal of improving treatment retention⁸⁰ and life-saving⁸¹ medications.