Incidence of drug injection: systematic review and meta-analysis of cohort studies among at risk populations

Transcription

1 Incidence of drug injection: systematic review and meta-analysis of cohort studies among at risk populations María J Bravo Blanca I Indave EMCDDA annual expert meeting on Drug-related deaths (DRD) & Drug-related infectious diseases (DRID) October 2013 EMCDDA (Lisbon)

2 Background Initiation into drug injection is an important determinant of morbidity and mortality(blood-borne infections HIV, HCV and overdose). Incidence of drug injection(idi) is relevat Prevention/projections IDI Cohortstudiesneverinjectorsof illegaldrugs/vulnerable lifestyle Cohort studies(coh-s) potential of bias Validity(internal/external) Coh-S of hidden population presents difficultis for recruitement + high attrition lack of statistical power There is remarkable heterogeneity between theidi of well-known cohorts No systematic reviews published

3 AIMS 1. To carry out a Systematic Review of cohort studies that estimate IDI among never drug injectors at risk 2. Toconducta meta-analysis pooledidi and explore sources of heterogeneity and bias

4 Methods-Systematicreview Search for Cohort Studies on initiation into DI among vulnerable pop EMBASE, Lilacs, Medline, PsycINFO. Cochrane database MeSH, key words. No language restrictions. Published/grey literature. Data extraction: Twoindependentreviewers. STROBE guidelines. Standardize quality assessment form(sign50 Scottish Intercollegiate Network-) & Drug relatedchecklist(ndarc). Inclusion criteria: Cohort studies on initiation on drug injection: the first documented or self-referred event of non-prescribed drug injection. Exclusioncriteria: No original search; Non-human study; Case report series of qualitative research Study desing other than observational cohort(ct, C-C, C-S) Population of former injectors at baseline No explicitidi, no data tocompute it(new injectors/100 p-y at risk)

5 Methods-Statisticalanalysis Analysis restricted to Never-injectors at baseline that completed at least one follow-up visit Random-effects meta-regression to: Estimate pooled IDI and 95% CI Identify determinants of heterogeneity Calculate trends analysis over selected variables Study-specific IDI were log transformed and weigheted by inverse of variance Betweenstudyheterogeneity chi-squared test and the I 2 statistic Pooled IDI rates were calculated by: Country (North American vs European) Mostly heroin users (no vs. yes) % homeless (<50% vs 50%) Recruitment methods (street-based vs service-engaged or mixed) Publication bias was also assessed % men (< 65% vs. 65%) Mean age(< 25 vs. 25 years) Mid point of follow-up period (< 2000 vs Average follow-up length (< 2 vs. 2 years).

6 Flow diagram of the study selection process. Potentially relevant articles identified through Data Bases PubMed: 2794 Cochrane: 261 PsyINFO: 862 EMBASE: 1572 Lilacs: 1521 Results Additional citations from rewiew of reference lists and Related Articles*: 495 Overall: 6063 Duplicated articles: ,063 articles identified Additional sources provided by expert group: 21 Grey literature references: 12 Excluded by Issue out of interest: Animals and/or molecular investigation: 456 Non focus on drug use: Clinical studies: 1965 Methodological/Economics studies: 80 Legal/Forensic: 65 Others: 156 Focus out of drugs of interest: 396 Articles focus in diagnosis and treatment: 765 Excluded by design: Case series: 801 Letter/editorial and similar: 113 Review/debate: 316 Qualitative studies: 35 Cross studies/prevalence studies: 317 Trial:191 Case/Control: papers selected for cohorts originating several reports we selected the publication with the largest baseline population or the longest follow-up period Studies of population who consumes drugs of interest that include follow-up: 121 Articles selected: 9 No data about initiation into the injection: 100 Population who had injected drug before follow-up: 55 Population includes never injectors but results non focus on: 45 Lack of information about time of follow-up: 3 Lack of data about if the patients have ever injected: 3 9 prospective cohort studies were finally selected, published between ,843 participants

7 Characteristics of cohort studies on incidence of drug injection ordered by average follow-up length Results Study, country age (y) followup (%) follow-up (y) new injectors Roy, 2011 Canada Population Homeless Street Youth youths Primary drug use, baseline Mixed pattern of cocaine and heroine ψ Recruitment * Parriott, 2009, Homeless youths USA Cocaine Street-based Valdez, 2011 Never-injecting heroin, USA users Heroin Street-based Miller, 2011, Aboriginals, illicit drug Cocaine Canada users Mixed Bravo, 2012, Never-injecting heroin Spain users Heroin Street-based Roy, 2003, Serviceengaged Homeless Street Youth youths Cocaine ψ Canada Serviceengaged Men Mean Lost to No. of Follow-up Average No. of (%) subjects period QS van Ameijden, 1994, The Netherlands Methadone program participants, drugusing prostitutes Opioids (heroine or illegal methadone) Serviceengaged Neaigus, 2006 USA Never-injecting heroin users Heroin Street-based Buster, 2009 The Netherlands Never-injecting illicit drug users λ Cocaine Mixed * Street-based (targeted sampling, street outreach, chain referral), service-engaged (social services, health care providers, treatment centers), or mixed recruitment; Lost to follow-up between baseline and first follow-up visit. Participants with at least one follow-up visit; Quality Assessment Score: Range 0 to 13.(QS); Other than marijuana; ψ A very small % might be non-illegal drug users λ Users of heroin, methadone, cocaine and/or amphetamine

8 Study-specific IDIs and overall pooled IDI Mean Average No. of cases/ Incidence rate of initiation into drug injection Study, year age (y) follow -up (y) person-years per 100 person-years (95% CI) Parriott, / ( ) Valdez, / ( ) Miller, / ( ) Bravo, / ( ) Roy, / ( ) Roy, / ( ) van Ameijden, / ( ) Neaigus, / ( ) Buster, / ( ) Overall 7.8 ( ) Strong between study heterogeneity No specificstudyseemedtodrive thepooledidi The area of each square is proportional to the study weight in the meta-analysis. Horizontal lines represent exact 95% confidence intervals (CIs) based on the Poisson distribution. The diamond represents the pooled estimate from an inverse-variance weighted random-effects meta-analysis on log-transformed incidence rates.

9 Pooled incidence rates of drug injection among never-injecting drug users by study characteristics. Study characteristic No. Incidence rate per 100 personyears* (95% CI) Studies P value Country 0.21 North American ( ) European ( ) Mostly op/heroin users 0.82 No ( ) Yes ( ) Homeless (%) 0.44 < ( ) ( ) Recruitment 0.19 Street-based ( ) Service-eng or mixed ( ) Men (%) 0.52 < ( ) ( ) Mean age (y) 0.06 < ( ) ( ) Midpoint follow-up period 0.58 < ( ) ( ) Average follow-up length (y) < ( ) ( ) Pooled incidence rates and 95% confidence intervals (CIs) were obtained from separate random-effects meta-regression models including indicator variables for each category of the study characteristic. P value for heterogeneity of pooled incidence rates across categories of the study characteristic.

10 Trend of pooled IDI by mean age at baseline 50 Incidence rate of initiation into drug injection per 100 person-years Parriott, 2009 Valdez, 2011 Miller, 2011 Roy, 2003 Roy, % decreasein pooledidi per 1-year increase in themean ageat baseline pooled linear trend not significant heterogeneity remain strong Bravo, 2012 van Ameijden, 1994 Neaigus, 2006 Buster, Mean age at baseline (y) The area of each circle is proportional to the study weight in the meta-regression. The pooled trend (solid line) and its 95% confidence band (shaded region) were obtained from an inverse-variance weighted random-effects meta-regression of log-transformed incidence rates on mean baseline ages.

11 Trend of pooled IDI by average length of follow-up 50 Incidence rate of initiation into drug injection per 100 person-years Parriott, 2009 Valdez, % decreasein pooledidi per 1-year increase in thein theaverageof follow-up no residual heterogeneity in IDI after accounting for the follow-up length Miller, 2011 Bravo, 2012 Roy, 2003 van Ameijden, 1994 Roy, 2011 Neaigus, Buster, Average follow -up (y) The area of each circle is proportional to the study weight in the meta-regression. The pooled trend (solid line) and its 95% confidence band (shaded region) were obtained from an inverse-variance weighted random-effects meta-regression of log-transformed incidence rates on average follow-up lengths.

12 Discussion Small numberstudies comprehensiveviewof thenatural history of drug injecting career(?) A strong trendin IDI as the length of follow-up Review and discuss the main factors thatcan affecttheidi and which couldhelptoexplainourresultsorbe opposed to them. Differential LsTF(selection bias): differential survival diferentialnon-response (no location, refusal) Other bias/factors

13 Discussion Factors that would progressively reduce the IDI and explain our results. Differentiallosstofollow-up Differential survival: Higher mortality among DI than non-injectors Differential non-response (no location/refusal): Higher morbidity & higher unstable-disruptive lifestyle among DI/problem drug users than non-di Drug injectorsorproblemdruguserswouldbelostat a higherratethan never injectors A progressive higher loss of NEW-DI vs NEVER-DI as follow-up increases progresive decrease on IDI The losses to follow-up ranged from 9%-40% between intake and 1st follow-up. The cumulative losses would likely lead to higher differential loss to follow-up in the studies with longer follow-up periods. Misclassification of former injectors as non-injectors at intake Spurious IDI at thefirststagesof thefollow-up and a consecutive

14 Discussion Factors that would progressively reduce the IDI and explain our results. The longer the period remaining as never injector, the higher the probability of quitting heroin/cocaine use Someparticipantsmayabandoncocaine/heroinuse duringthefollow-up and remain in the study as population at risk(denominator) Progressive of theidi as thelengthof heroin/cocaineuse Our follow-up length finding might partially capture the effect of length of use The longer studies might grasp this effect more easily than shorter ones Factors that would progresively increase the IDI and are opposed to our findings If the% of never-di quitting heroin/cocaine use (and consequently with a less risk of starting injecting) were higher among dropouts than among remaining enrolees Spurious of theidi Participantsare notlongerinterestedin keepingcontact with a study about a life-style that they intend to leave behind

15 Discussion Spain and Netherlands: triangulation of sources: prevalence of DI in last 25 years Longer studies would capture the downward calendar-trend of IDI more easily This phenomena was not observed in the other cities of our selected studies during the study periods: Montreal, Vancouver, New York, San Francisco. // S Antonio (Texas) Probably this is not an explanation for our results Characteristics of drop-outs in the review studies: The selected studies do not include the reasons for LsTF. They test the differences between losses and remaining enrolees. Some factors underestimation of the IDI among the remaining enrolees. Others opposite direction The limited discussion in the majority of the reviewed studies on the potential differential LsTFhinders the assessment of the direction of the potential attrition bias

16 Limitations The small number identified studies hampered the exploration of a higher number of relevant variables for IDI heterogeneity. Limited statistical power. Multivariate meta-regression was not feasible. The variations in the categorization of variables in the selected studies hindered the inclusion of more explanatory variables in the meta-analysis. It was not possible to assess the effect of other potential explanatory variables (length and frequency of drug use, type of non-injecting route, heroin/cocaine formulation, proximity to DI networks, MMT attendance.) because they were not included in the majority or the selected studies.

17 Conclusions Scarcity of cohort studies on IDI very little prospective research including injectors and never injectors. IDI rates are strongly heterogeneous across studies. The strong downward trend on IDI as the study average of follow-up trend increases is highly consistent with a differential LTF. Other bias as misclassification bias might contribute in the same direction. Strategies to maximize retention and minimize non-response are recommended, as well as linkage with mortality register, treatment registers and others. More rigouron the critical appraisal on both the source and the level of bias is needed in studies on IDI. More information on causes of LTF should be provided. Use of statistical tools to correct the data during the analysis: i.e. Inverse probability weighting for marginal structural models. Additional research on the predictors of LTF among illegal drug users is recommended.

18 Thanksto Colleagues from the National Centre of Epidemiology: Barrio Gregorio Pastor Roberto Sordo Luis Colleague from National Drug and Alcohol Research Centre. Australia: Degenhardt Louisa Thanksforyourattention