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Eligibility for heroin-assisted treatment (HAT) among people who inject opioids and are living with HIV… Klimas, Jan; Dong, Huiru; Fairbairn, Nadia; Socías, Eugenia; Barrios, Rolando; Wood, Evan; Kerr, Thomas; Montaner, Julio; Milloy, M.-J. Feb 7, 2018

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Klimas et al. Addict Sci Clin Pract  (2018) 13:3 https://doi.org/10.1186/s13722-017-0104-yRESEARCHEligibility for heroin-assisted treatment (HAT) among people who inject opioids and are living with HIV in a Canadian settingJan Klimas1,2,3 , Huiru Dong1, Nadia Fairbairn1,3, Eugenia Socías1,3, Rolando Barrios1, Evan Wood1,2, Thomas Kerr1,2, Julio Montaner1,2 and M.‑J. Milloy1,2*Abstract Objectives: A growing body of evidence supports the effectiveness of injectable diacetylmorphine (i.e., heroin) for individuals with treatment‑refractory opioid use disorder. Despite this evidence, and the increasing toll of opioid‑associated morbidity and mortality, it remains controversial in some settings. To investigate the possible contribution of heroin‑assisted treatment (HAT) to HIV treatment‑related outcomes, we sought to estimate the proportion and characteristics of HIV‑positive people who inject opioids that might be eligible for HAT in Vancouver, Canada.Methods: We used data from a prospective cohort of people living with HIV who use illicit drugs in Vancouver, Canada. Using generalized estimating equations (GEE), we assessed the longitudinal relationships between eligibility for HAT, using criteria from previous clinical trials and guidelines, with behavioural, social, and clinical characteristics.Results: Between 2005 and 2014, 478 participants were included in these analyses, contributing 1927 person‑years of observation. Of those, 94 (19.7%) met eligibility for HAT at least once during the study period. In a multivariable GEE model, after adjusting for clinical characteristics, being eligible for HAT was positively associated with homelessness, female gender, high‑intensity illicit drug use, drug dealing and higher CD4 count.Conclusions: In our study of HIV‑positive people with a history of injection drug use, approximately 20% of par‑ticipants were eligible for HAT at ≥ 1 follow‑up period. Eligibility was linked to risk factors for sub‑optimal HIV/AIDS treatment outcomes, such as homelessness and involvement in the local illicit drug trade, suggesting that scaling‑up access to HAT might contribute to achieving optimal HIV treatment in this setting.Keywords: Substance‑related disorders, Heroin, HIV/AIDS, Illicit drug use, Opioid agonist treatment© The Author(s) 2018. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.BackgroundA growing body of evidence, including findings from ran-domised controlled trials (RCT) in Europe and North America, and systematic reviews by the Cochrane Col-laboration and others, supports the effectiveness of injectable diacetylmorphine (i.e., prescribed heroin) for treatment-refractory opioid use disorder [1–3]. Despite this support, heroin-assisted treatment (HAT) remains controversial and unavailable in most settings [4]. However, given the growing amount of evidence and the increasing toll of opioid-associated morbidity and mortality, efforts to develop guidance on injectable opi-oid agonist treatments for opioid use disorder, including medications that do not face the same regulatory barri-ers as diacetylmorphine (e.g., hydromorphone), are under way in some settings [5].Medical management of people living with HIV (PLHIV), with co-occurring substance use disorder (SUD), poses many challenges. There remains low cover-age of medically-proven treatment for SUD in many set-tings [6, 7]; furthermore, HIV-positive people who use illicit drugs (PWID) have not fully benefitted from scale-up of HIV testing and antiretroviral treatment (ART), a Open AccessAddiction Science & Clinical Practice*Correspondence:  bccsu‑mjsm@cfenet.ubc.ca 1 British Columbia Centres on Substance Use and Excellence in HIV/AIDS, St. Paul’s Hospital, 608‑1081 Burrard Street, Vancouver, BC V6Z 1Y6, CanadaFull list of author information is available at the end of the articlePage 2 of 8Klimas et al. Addict Sci Clin Pract  (2018) 13:3 strategy commonly referred to treatment-as-prevention (TasP), has resulted in reduced rates of HIV-associated morbidity, mortality and viral transmission [8]. As a result of sub-optimal HIV treatment outcomes and bar-riers to accessing harm reduction supplies, such as sterile syringes, HIV outbreaks among PWID are common and ongoing in many settings [9, 10].Despite the demonstrated benefits of oral opioid ago-nist therapy (OAT, i.e. methadone, buprenorphine/naloxone) on reducing illicit opioid use and HIV risk behaviours and promoting optimal HIV treatment out-comes [11, 12], gaps in SUD treatment persist, especially for PWID living with HIV [6, 13]. The limitations of oral OAT are many and significant, specifically the attrition that has been shown to increase the mortality risk during the induction phase onto methadone treatment, during the first year and during the time immediately after leav-ing treatment.[ENTER REF SORDO] In this respect, sev-eral RCTs (e.g., NAOMI, SALOME) have demonstrated the potential benefits of HAT for people with treatment-refractory opioid use disorder, including decreased levels of used syringe sharing, reduced illicit drug use, criminal activity and increased engagement with healthcare [1–3, 14]. However, we are unaware of any study to explore the potential uptake of HAT in the HIV-positive population. Thus, we sought to estimate the prevalence and charac-teristics of HIV-positive individuals that might be eligible for HAT in Vancouver, Canada.MethodsData for these analyses were derived from a prospective cohort of people who use illicit drugs and live with HIV in Vancouver, Canada, the AIDS Care Cohort to evalu-ate Exposure to Survival Services (ACCESS), which has been described elsewhere [15–17]. In brief, ACCESS is a cohort of HIV-seropositive adults who have used at least one illicit drug (other than or in addition to cannabis) in the month prior to recruitment. Individuals are recruited from community settings via snowball sampling and outreach techniques. At baseline and each biannual follow-up interview, participants complete inter-viewer-administered questionnaires that assess socio-demographic, drug use and other related behaviours, characteristics, or exposures. This includes a nursing examination and phlebotomy for HIV clinical monitor-ing. In addition to the interview data, we also accessed linked (using a government-issued identifier, i.e., Per-sonal Health Number—PHN) data from a comprehensive retrospective and prospective HIV clinical monitor-ing profile, including all plasma HIV-1 RNA viral loads, CD4 cell counts and records of all antiretroviral therapy (ART) dispensations, available from the Drug Treatment Program at the BC Centre for Excellence in HIV/AIDS (BC-CfE), as described previously [18]. The BC-CfE is responsible for dispensing ART, provided at no charge, to all people living with HIV in the province. The records include all clinical measures conducted through the study or by a participant’s physician or healthcare provider.Participants are compensated at each study inter-view with a $30 CDN stipend. The University of British Columbia/Providence Healthcare Research Ethics Board approved the study and all participants provided written informed consent at baseline.We included all participants who completed at least one study visit between December 1, 2005 and May 31, 2014 and who were older than 18 years old and reported ever injecting drugs at least once at the baseline inter-view. Our primary outcome of interest was being eligible for HAT as per the historical criteria from previous pub-lished RCTs [1–3], that defined HAT eligibility variably as: (a) currently residing in the study area (i.e., the city of Vancouver); (b) current regular injection of illicit opioids (i.e., ≥  one time in the previous 6  months); (c) at least two self-reported prior SUD treatment attempts, includ-ing one episode of OAT (i.e., methadone or buprenor-phine/naloxone); (d) at least 5 years of illicit opioid use; and (e) poor health, or psychosocial functioning, defined as a self-reported mental health diagnosis. At each inter-view period of the present study, we determined if an individual was eligible for HAT during that period by evaluating each criterion using responses given to rel-evant interview questions, specifically: (a) current resi-dence in the City of Vancouver; (b) ≥  weekly injection of an opioid (e.g., heroin, methadone, prescription opi-oids, etc.) in the last 6  months (yes vs. no); (c) number of times during the study period reporting being engaged in any SUD treatment and any OAT included if (1) posi-tive response to at least two of the options, or at least two positive responses for “number of times in treatment” at baseline, including one MMT programme, or included if (2) participants reported at least two prior “attempts at treatment” over follow-up, defined as not being currently in treatment but treatment in the last 6 months (≥ 2 vs. < 2); (d) number of years since initiation of illicit opioid use (≥ 5 vs. < 5 years); and (e) reporting a mental health diagnosis (Have you been diagnosed with a mental health issue in the last 6 months? Yes vs. no), or baseline depres-sion, as measured by the Center for Epidemiologic Stud-ies Depression scale (CES-D) (score of ≥ 16 vs. score of < 16). Participants had to fulfill all the above criteria to be deemed eligible for HAT.We also defined a number of explanatory variables, including: age (per year older); gender (male vs. non-male); Caucasian ethnicity/ancestry (yes vs. no); hepatitis C virus antibody status (positive vs. negative); number of years of using injection heroin at baseline; homelessness Page 3 of 8Klimas et al. Addict Sci Clin Pract  (2018) 13:3 (yes vs. no); relationship status (legally married/common law/regular partner vs. other); highest level of educa-tion completed (≥ high school diploma vs. < high school diploma); formal employment (yes vs. no, i.e., regular job, temporary job, or self-employed); money spent on drugs per day (≥ $50 per day vs. < $50 per day); drug dealing (yes vs. no); ≥  daily non-injection cocaine use (yes vs. no); ≥ daily non-injection heroin use (yes vs. no); ≥ daily crack use (yes vs. no); ≥ daily methamphetamine use (yes vs. no); non-fatal overdose (yes vs. no); lent used syringe (yes vs. no); recent incarceration (yes vs. no); engagement in any form of unprotected sex (yes vs. no); exchange of sex for gifts, food, shelter, clothes, etc. (yes vs. no); being a victim of violence, defined as having been attacked or assaulted (yes vs. no) [19–21]. All time-updated variables refer to behaviours or exposures in the 6-month period prior to the study interview.We also included the following data based on the con-fidential linkage (using PHN identifier) to the local HIV clinical monitoring registry and ART dispensary: HIV-1 RNA plasma viral load (VL), using the median of all observations in the previous 6  months or, if none, the most recent observation, dichotomised at >  50 versus ≤ 50 copies/mL; ART engagement, using the number of days of ART dispensed in the previous 6 months (dichot-omized at ≥ 1 vs. 0 day); and CD4 cell count, using the median of all observations in the previous 6 months or, if none, the most recent observation (expressed per 100 cells/mL) [22].As a first step, we described the study sample at base-line stratified by eligibility for HAT. We used Chi square test and Fisher’s exact test to compare categorical vari-ables and Wilcoxon’s rank-sum test to compare continu-ous variables.To evaluate the association between eligibility for HAT and each of the explanatory variables of interest, we built a statistical model, using generalised estimating equa-tion (GEE), assuming a binomial distribution, a logit-link function and an exchangeable working correlation structure. We first build bivariable GEE to examine the association between being eligible for HAT and each of the explanatory variables. To fit the final multivariable model, we applied an a priori-defined backward model selection approach based on examination of quasilikeli-hood under the independence model criterion statistic (QIC). We first included all explanatory variables that were associated with the outcome at the level of p < 0.10 in bivariable analyses in a full model. From the QIC of the model, we excluded the variable with the largest p value and constructed a reduced model. We proceeded this iterative method and chose the multivariable model with the lowest QIC value [23]. All p values were two-sided. All statistical analyses were performed using the SAS software version 9.4 (SAS, Cary, NC, USA).ResultsBetween December 2005 and May 2014, 852 individuals were recruited into the cohort, of whom 478 (56.1%) par-ticipants satisfied all criteria, including age and injection drug use, and were included in the analysis. They con-tributed 3495 observations, or a median of 7 interviews [inter-quartile range (IQR): 3–11] during follow-up. Of those, 94 (19.7%) were deemed to be eligible for HAT at least once through study period: 32 reported eligible for once, 19 twice, 11 thrice, and 32 more than thrice. Base-line characteristics are reported in Table  1. As shown, most participants included in this analysis were Cauca-sian (273, 57.1%), males (321, 67.2%), with median age of 43.1 (IQR 36.7–47.9) years.As shown in Table 2, the following variables were posi-tively associated with being eligible for HAT: homeless-ness [adjusted odds ratio (AOR) 1.47; 95% confidence interval (CI) 1.07–2.01]; drug dealing in the last 6 months (AOR 1.76; 95% CI 1.33–2.31); ≥  daily non-injection heroin use (AOR 8.18; 95% CI 1.25–53.56); ≥ daily crack use (AOR1.35; 95% CI 1.01–1.82); and CD4 cell count (per 100 cells/mL increase, AOR 1.08; 95% CI 1.00–1.17). Male gender was negatively associated with the outcome (AOR 0.50; 95% CI 0.31–0.82).DiscussionIn this study to estimate the prevalence and character-istics of PLHIV who inject drugs that might be eligible for HAT, we observed that approximately one-fifth of all participants were eligible at least once during study fol-low-up. Periods of HAT eligibility were associated with important factors that have been linked with sub-optimal HIV treatment outcomes in previous studies, including markers of severe SUD, such as high-intensity illicit drug use, homelessness and drug dealing [3, 4, 17]. These asso-ciations signal that expanding HAT to this population might influence the factors linked with sub-optimal HIV treatment and improve HIV treatment outcomes, thus contributing to TasP goals [15]. Moreover, they provide further support for the potential role of HAT in decreas-ing opioid-associated morbidity and mortality.The links between HAT eligibility and various drug-related (e.g., high-intensity illicit drug use and survival dealing as markers of severe SUD), and socio-structural determinants of health (e.g., homelessness), indicate that HAT-eligible individuals face numerous barriers to opti-mal HIV treatment outcomes, even in a setting where HIV treatment and care is delivered at no cost [16, 24]. Admittedly, HAT eligibility can impact markers of severe Page 4 of 8Klimas et al. Addict Sci Clin Pract  (2018) 13:3 Table 1 Baseline characteristics of participants who inject opioids and live with HIV in Vancouver, BC, stratified by the baseline HAT eligibility statusCharacteristic Total (%) (n = 478) HAT eligibility p valueYes (%)45 (9.4)No (%)433 (90.6)Age (median, inter‑quartile range‑IQR)b 43.1 (36.7–47.9) 36.7 (34.2–43.7) 43.5 (37.9–48.1) < 0.001Gender Male 321 (67.2) 23 (51.1) 298 (68.8) 0.016 Non‑male 157 (32.8) 22 (48.9) 135 (31.2)Ethnicity Caucasian 273 (57.1) 29 (64.4) 244 (56.4) 0.296 Non‑Caucasian 205 (42.9) 16 (35.6) 189 (43.6)Homelessnessa Yes 169 (35.4) 22 (48.9) 147 (33.9) 0.026 No 305 (63.8) 21 (46.7) 284 (65.6)Relationship  statusa Legally married/common law/regular partner 126 (26.4) 15 (33.3) 111 (25.6) 0.228 Other 339 (70.9) 28 (62.2) 311 (71.8)Highest level of education completed ≥ high school diploma 229 (47.9) 23 (51.1) 206 (47.6) 0.512 < high school diploma 241 (50.4) 20 (44.4) 221 (51.0)Employmenta,c Yes 101 (21.1) 4 (8.9) 97 (22.4) 0.035 No 377 (78.9) 41 (91.1) 336 (77.6)Money spent on drugs p/dayc ≥ $50 p/day 315 (65.9) 39 (86.7) 276 (63.7) < 0.001 < $50 p/day 158 (33.1) 5 (11.1) 153 (35.3)Drug  dealinga Yes 148 (31.0) 25 (55.6) 123 (28.4) < 0.001 No 330 (69.0) 20 (44.4) 310 (71.6)Years of using heroin injection heroin at baseline (median, IQR)b Number of years 14.8 (7.3–22.6) 15.7 (8.7–20.4) 14.4 (7.3–22.7) 0.640Daily non‑injection cocaine  usea,c Yes 2 (0.4) 0 (0.0) 2 (0.5) 1.000 No 476 (99.6) 45 (100.0) 431 (99.5)Daily non‑injection heroin  usea,c Yes 4 (0.8) 1 (2.2) 3 (0.7) 0.328 No 474 (99.2) 44 (97.8) 430 (99.3)Daily crack  usea Yes 181 (37.9) 25 (55.6) 156 (36.0) 0.010 No 297 (62.1) 20 (44.4) 277 (64.0)Daily crystal meth  usea Yes 19 (4.0) 5 (11.1) 14 (3.2) 0.025 No 459 (96.0) 40 (88.9) 419 (96.8)Overdosea Yes 32 (6.7) 7 (15.6) 25 (5.8) 0.012 No 446 (93.3) 38 (84.4) 408 (94.2)Lent  syringea,c Yes 17 (3.6) 3 (6.7) 14 (3.2) 0.210 No 460 (96.2) 42 (93.3) 418 (96.5)Page 5 of 8Klimas et al. Addict Sci Clin Pract  (2018) 13:3 SUD (and indirectly HIV treatment outcomes) but no direct associations with indicators of HIV status were observed. Nevertheless, because a noteworthy propor-tion of PLHIV met the HAT eligibility criteria in the current study, investment into HAT, and other intensive treatments of this targeted group, might also improve their general medical care outcomes as their commonly comorbid diseases (e.g., HCV) can require intense care and frequent follow-up [1]. Similar impact has been dem-onstrated through protective effect of methadone main-tenance therapy on hepatitis C and HIV incidence among PWIDs in this setting [25, 26]. Another justification for expanding access to HAT among this population lies in the growing body of evidence that confirms that many people who do not respond to typical treatment of opi-oid use disorder (OUD) improve in HAT in areas such as treatment retention, reduced use of illicit drugs, and social functioning [3]. In response, some settings have started developing guidelines for injectable OAT as a treatment for OUD [27].We have identified a cohort of PWID with indicators of severe SUD suggesting treatment-refractory opioid use disorders, who could benefit from combined treat-ment of SUD and concurrent chronic diseases, such as HIV. The association with homelessness, as another potential marker of severe SUD, could suggest that HAT eligible PWIDs cannot afford to stay in housing or access services to facilitate housing [28, 29]. Males in our HIV-positive sample were less likely to be deemed HAT eligible, which is a novel finding, given that men are dis-proportionately being represented in the opioid epidemic in terms of overdose deaths and in the SUD treatment [30]. In this respect, longitudinal research has identi-fied an adherence gap whereby women living with HIV had lower ART adherence than men which suggest that targeted research into a potential role of HAT in facili-tating HAT adherence among women is needed [31]. Studies have shown HIV risk reduction with oral opioid agonist treatment (OAT) [32, 33]. Aligned with the sci-entific literature, these findings suggest that treatment of Table 1 continuedCharacteristic Total (%) (n = 478) HAT eligibility p valueYes (%)45 (9.4)No (%)433 (90.6)Recent  incarcerationa Yes 75 (15.7) 12 (26.7) 63 (14.5) 0.034 No 402 (84.1) 33 (73.3) 369 (85.2)Engaged in any form of unprotected  sexa,c Yes 46 (9.6) 5 (11.1) 41 (9.5) 0.790 No 429 (89.7) 40 (88.9) 389 (89.8)Exchanged sex for gifts, food, shelter, clothes, etc.a Yes 72 (15.1) 15 (33.3) 57 (13.2) < 0.001 No 403 (84.3) 30 (66.7) 373 (86.1)Attacked, assaulted, or suffered  violencea Yes 98 (20.5) 12 (26.7) 86 (19.9) 0.293 No 377 (78.9) 33 (73.3) 344 (79.4)HCVc Yes 429 (89.7) 40 (88.9) 389 (89.8) 0.797 No 49 (10.3) 5 (11.1) 44 (10.2)Plasma HIV‑1 RNA viral load > 50 c/mL Yes 313 (65.5) 31 (68.9) 282 (65.1) 0.656 No 162 (33.9) 14 (31.1) 148 (34.2)On ART (≥ 1 day)a Yes 283 (59.2) 28 (62.2) 255 (58.9) 0.665 No 195 (40.8) 17 (37.8) 178 (41.1)CD4+ cell count per 100  cellsa,b Median, IQR 3.2 (2.0–4.8) 3.2 (1.6–5.0) 3.2 (2.0–4.8) 0.696a All behavioural variables refer to the 6 months prior to the follow-up questionnaireb Continuous variable, p value is generated from Wilcoxon rank-sum testc p value is generated from Fisher’s exact test because of small cell countPage 6 of 8Klimas et al. Addict Sci Clin Pract  (2018) 13:3 Table 2 Bivariable and multivariable GEE analysis of factors associated with HAT eligibility among people who live with HIVCharacteristic Bivariable MultivariableOdds ratio (95% CI) p value Odds ratio (95% CI) p valueAge (Per 10 years older) 0.97 (0.94–1.01) 0.101Gender (Male vs. female/non‑male) 0.49 (0.31–0.80) 0.004 0.50 (0.31–0.82) 0.006Ethnicity (Caucasian vs. other) 1.39 (0.84–2.28) 0.198Homelessnessa (Yes vs. no) 1.61 (1.21–2.16) 0.001 1.47 (1.07–2.01) 0.016Relationship  statusa (Legally married/common law/regular partner vs. other) 0.82 (0.60–1.12) 0.213Highest level of education completed (≥ high school diploma vs. < high school diploma) 1.01 (0.62–1.65) 0.957Employmenta (Yes vs. no) 0.73 (0.56–0.95) 0.018Money spent on drugs p/day (= $50 per day vs. < $50 per day) 1.53 (1.15–2.02) 0.003Drug  dealinga (Yes vs. no) 1.93 (1.50–2.49) < 0.001 1.76 (1.33–2.31) < 0.001Years of using injection heroin at baseline (Per year increase) 1.00 (0.98–1.02) 0.781Daily non‑injection cocaine  usea (Yes vs. no) 1.76 (0.54–5.68) 0.347Daily non‑injection heroin  usea (Yes vs. no) 7.45 (1.50–37.05) 0.014 8.18 (1.25–53.56) 0.028Daily crack  usea (Yes vs. no) 1.56 (1.17–2.09) 0.003 1.35 (1.01–1.82) 0.045Daily meth  usea (Yes vs. no) 1.79 (0.97–3.30) 0.061Overdosea (Yes vs. no) 1.29 (0.77–2.15) 0.328Lent  syringea (Yes vs. no) 0.93 (0.24–3.59) 0.915Recent  incarcerationa (Yes vs. no) 1.34 (0.83–2.18) 0.233Engaged in any form of unprotected  sexa (Yes vs. no) 1.07 (0.64–1.81) 0.787Exchanged sex for gifts, food, shelter, clothes, etc.a (Yes vs. no) 1.30 (0.73–2.32) 0.378Attacked, assaulted, or suffered  violencea (Yes vs. no) 1.10 (0.76–1.58) 0.613HCVa (Yes vs. no) 1.05 (0.53–2.05) 0.898Plasma HIV‑1 RNA viral load > 50 c/mLa (Yes vs. no) 0.98 (0.76–1.25) 0.853On ART (≥ 1 day)a (Yes vs. no) 0.79 (0.56–1.10) 0.162CD4+ cell  counta (Per 100 cells/mL increase) 1.07 (0.99–1.15) 0.096 1.08 (1.00–1.17) 0.042a All behavioural variables refer to the 6 months prior to the follow-up questionnairePage 7 of 8Klimas et al. Addict Sci Clin Pract  (2018) 13:3 SUD should be tailored to the needs of the individuals, including providing supervised injectable HAT to people with treatment-refractory OUD that does not respond to first and second-line oral OAT alternatives [4]. Oral OAT has been shown effective, but not for everyone [34]. For example, between 46 and 65% of patients who initiate methadone OAT discontinue treatment in the first year and relapse to opioid use—a period of high risk for fatal overdose [35]. Furthermore, adherence to therapeutic dose guidelines, which is independently associated with retention, remains problematic in many settings [36]. The benefits of providing concomitant HAT and ART to peo-ple with treatment-refractory opioid use disorder, and the potential synergetic effects on treatment outcomes of both diseases, have yet to be established.This study is limited by several factors. Our sample was not recruited at random and cannot be assumed to represent the larger population of PWID in Vancouver. We did not confirm the diagnoses of mental health and opioid use disorder and did not retrieve provider-level data for treatment episodes. However, the results from previous HAT research did not suggest that a group of PLHIV might not benefit from HAT, because they were not excluded from those studies [2]. Potential risk fac-tors for opioid overdose, such as current co-use of ben-zodiazepines, alcohol or non-injection heroin, should be explored in future as well. The omission of these factors may have inflated the potentially eligible group. Finally, it is possible that we underestimated the rates of risky behaviours and drug use, such as syringe sharing, due to the effects of social desirability.To conclude, in our 10-year longitudinal study of PLHIV, approximately 20% of participants would have been eligible for HAT at least once during the study period. Being eligible for HAT was linked to a number of important risk factors for sub-optimal HIV treatment outcomes, and onward viral transmission, suggesting that more evidence is needed for scaling-up access to HAT and how it might contribute to treatment-as-prevention goals.Authors’ contributionsJK and MJM conceived the study and hypothesis. HD analysed the data. TK, EW conceived the cohorts that provided the data for this analysis. NF, ES, RB, EW, TK, JM, MJM participated in the study design and drafting the manuscript. All authors read and approved the final manuscript.Author details1 British Columbia Centres on Substance Use and Excellence in HIV/AIDS, St. Paul’s Hospital, 608‑1081 Burrard Street, Vancouver, BC V6Z 1Y6, Canada. 2 Department of Medicine, University of British Columbia, St. Paul’s Hospital, 608‑1081 Burrard Street, Vancouver, BC V6Z 1Y6, Canada. 3 School of Medicine, University College Dublin, Health Sciences Centre, Belfield, Dublin 4, Ireland. AcknowledgementsThe authors thank the study participants for their contribution to the research, as well as current and past researchers and staff. The study was supported by the US National Institutes of Health (R25DA037756, U01DA021525, U01DA038886). This research was undertaken, in part, thanks to funding from the Canada Research Chairs program through a Tier 1 Canada Research Chair in Inner City Medicine that supports Dr. Evan Wood. Dr. Milloy is supported by the United States National Institutes of Health (U01‑DA021525), a New Investigator award from the Canadian Institutes of Health Research and a Scholar award from the Michael Smith Foundation for Health Research. His institution has received unstructured funds from National Green Biomed, Ltd., to support him. ELEVATE: Irish Research Council International Career Develop‑ment Fellowship—co‑funded by Marie Cure Actions (ELEVATEPD/2014/6); and European Commission (701698)—supported Dr. Jan Klimas. Dr. Eugenia Socías is supported by Michael Smith Foundation for Health Research and Canadian Institute for Health Research fellowship awards and a Canada Addiction Medicine Research Fellowship (US National Institute on Drug Abuse, R25‑DA037756). Dr. Nadia Fairbairn is supported by a Scholar award from the Michael Smith Foundation for Health Research and the Research in Addiction Medicine Scholars Program from the United States National Institutes of Health (R25DA033211).Competing interestsThe authors declare that they have no competing interests.Ethics approval and consent to participateThe University of British Columbia/Providence Healthcare Research Ethics Board approved the study and all participants provided written informed consent at baseline. 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