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) 16-18 October 2013 – EMCDDA (Lisbon) 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 Cohort studies never injectors of illegal drugs/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 AIMS
1. To carry out a Systematic Review of cohort studies that estimate IDI among never drug injectors at risk
2. To conduct a meta-analysis pooled IDI and explore sources of heterogeneity and bias Methods -Systematic review • Search for Cohort Studies on initiation into DI among vulnerable pop • EMBASE, Lilacs, Medline, PsycINFO. Cochrane database. 1980-2012 • MeSH, key words. No language restrictions. Published/grey literature. • Data extraction: Two independent reviewers. STROBE guidelines. • Standardize quality assessment form (SIGN50 –Scottish Intercollegiate Network-) & Drug related check list (NDARC). • Inclusion criteria: Cohort studies on initiation on drug injection: “the first documented or self-referred event of non-prescribed drug injection”. • Exclusion criteria: • 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 explicit IDI, no data to compute it (new injectors/100 p-y at risk) Methods-Statistical analysis • 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
• Between study heterogeneity chi-squared test and the I2 statistic
• Pooled IDI rates were calculated by: • Country (North American vs European) • % men (< 65% vs. ≥ 65%) • Mostly heroin users (no vs. yes) • Mean age(< 25 vs. ≥ 25 years) • % homeless (<50% vs ≥50%) • Mid point of follow-up period (< 2000 vs. ≥ 2000) • Recruitment methods (street-based vs • Average follow-up length (< 2 vs. ≥ 2 years). service-engaged or mixed) • Publication bias was also assessed Flow diagram of the study selection process.
Potentially relevant articles identified through Data Bases PubMed: Cochrane: PsyINFO: EMBASE: Lilacs: 2794 261 862 1572 1521 Results
Additional citations from Duplicated articles: 1443 rewiew of reference lists and Related Articles*: 495 • 6,063 articles identified Overall: 6063 • 13 papers selected Additional sources Excluded by Issue out of interest: provided by expert •Animals and/or molecular investigation: 456 group: 21 •Non focus on drug use: •Clinical studies: 1965 •Methodological/Economics studies : 80 Grey literature •Legal/Forensic: 65 • for cohorts originating references: 12 Others: 156 •Focus out of drugs of interest: 396 •Articles focus in diagnosis and treatment: 765 several reports we
Excluded by design: selected the publication •Case series: 801 •Letter/editorial and similar: 113 with the largest baseline •Review/debate: 316 •Qualitative studies: 35 •Cross studies/prevalence studies: 317 population or the •Trial:191 •Case/Control: 317 longest follow-up period
Studies of population who consumes drugs of interest that include follow-up: 121 • 9 prospective cohort studies •No data about initiation into the injection: 100 •Population who had injected drug before follow-up: were finally selected, published 55 •Population includes never injectors but results non between 1994-2012 focus on: 45 •Lack of information about time of follow-up: 3 •Lack of data about if the patients have ever injected: 3 • 1,843 participants Articles selected: 9 Characteristics of cohort studies on incidence of drug injection Results ordered by average follow-up length Study, Primary drug Recruitment No. of Population Men Mean Lost to Follow-up Average No.QS§ of country use, baseline * subjects‡ age follow- follow-up new (%) period (y) up† (%) (y) injectors Parriott, 2009, Homeless youths Cocaine Street-based 67.1 20.1 27.8 7004–2005 20 0.5 8 9 USA Never-injecting heroin Valdez, 2011 Heroin Street-based 62.6 21.4 9 219 2002–2005 1.1 43 7 , USA users Miller, 2011, Aboriginals, illicit drug Cocaine Mixed 61.9 22.2 27 197 2003–2007 1.7 39 10 Canada users ¥ Never-injecting heroin Bravo, 2012, Heroin Street-based 68.5 26 35.4 197 2001–2006 1.8 27 9 Spain users Roy, 2003, Service- Homeless youths Cocaineψ 68.4 19.5 10.6 415 1995–2000 2.2 74 10 Canada Street Youth engaged Mixed pattern of Service- 72 20 17.8 352 2002–2005 2.4 37 8 Roy, 2011Street Homeless Youth youths cocaine and engaged heroineψ Canada van Ameijden,Methadone program Opioids (heroine or Service- participants, drug- 59 29.9 35.2 100 1985–1992 2.5 18 9 1994, The illegal engaged Netherlands using prostitutes methadone)¶
Neaigus, Never-injecting heroin Heroin Street-based 62.7 33.2 40.5 209 1996–2003 2.6 25 10 2006 users USA
Buster, 2009 Never-injecting illicit Cocaine Mixed 71.4 28 32.6 84 2000–2007 3.4 6 9 The drug usersλ Netherlands
* 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 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, 2009 20.1 0.5 8/ 33.0 24.2 ( 10.5-47.8)
Valdez, 2011 21.4 1.1 43/ 232.5 18.5 ( 13.4-24.9)
Miller, 2011 22.2 1.7 39/ 339.1 11.5 ( 8.2-15.7)
Bravo, 2012 26.0 1.8 27/ 359.6 7.5 ( 4.9-10.9)
Roy, 2003 19.5 2.2 74/ 902.4 8.2 ( 6.4-10.3)
Roy, 2011 20.0 2.4 37/ 860.5 4.3 ( 3.0-5.9) van Ameijden, 1994 29.9 2.5 18/ 250.0 7.2 ( 4.3-11.4)
Neaigus, 2006 33.2 2.6 25/ 543.5 4.6 ( 3.0-6.8)
Buster, 2009 28.0 3.4 6/ 285.7 2.1 ( 0.8-4.6)
Overall 7.8 ( 5.0-12.3) • Strong between study heterogeneity • No specific study seemed to drive the pooled IDI 1 2 5 10 20 50
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. Pooled incidence rates of drug injection among never-injecting drug users by study characteristics. No. Incidence rate per 100 person- Study characteristic P value† Studies years* (95% CI) Country 0.21 North American 6 9.5 (5.5–16.2) European 3 5.2 (2.3–11.4) Mostly op/heroin users 0.82 No 5 7.4 (3.8–14.3) Yes 4 8.3 (4.0–17.0) Homeless (%) 0.44 < 50 5 6.6 (3.5–12.5) ≥ 50 4 9.6 (4.7–19.4) Recruitment 0.19 Street-based 4 10.8 (5.6–21.0) Service-eng or mixed 5 6.0 (3.3–10.9) Men (%) 0.52 < 65 4 9.2 (4.6–18.5) ≥ 65 5 6.8 (3.6–12.8) Mean age (y) 0.06 < 25 5 10.9 (6.4–18.4) ≥ 25 4 5.0 (2.7–9.3) Midpoint follow-up period 0.58 < 2000 3 6.5 (2.9–14.6) ≥ 2000 6 8.6 (4.8–15.4) Average follow-up length (y) 0.002 < 2 4 13.5 (8.5–21.3) ≥ 2 5 5.1 (3.4–7.7) • 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. Trend of pooled IDI by mean age at baseline
50 • 7% decrease in pooled IDI per 1-year increase Parriott, 2009 in the mean age at baseline
Valdez, 2011 • pooled linear trend not significant 20 • heterogeneity remain strong
Miller, 2011
10 Bravo, 2012 van Ameijden, 1994
Roy, 2003 Neaigus, 2006 per 100 person-years per 100 5
Incidence rate of initiation into drug injection drug into initiation of rate Incidence Roy, 2011
Buster, 2009
2
20 22 24 26 28 30 32 34 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. Trend of pooled IDI by average length of follow-up
50
• 57% decrease in pooled IDI per 1-year increase in the in the average of follow-up Valdez, 2011 • no residual heterogeneity in IDI after accounting 20 Parriott, 2009 for the follow-up length
Miller, 2011
Roy, 2003 10 van Ameijden, 1994
Bravo, 2012 Neaigus, 2006 per 100 person-years 100 per 5
Incidence rate of initiation into drug injection drug into initiation of rate Incidence Roy, 2011
2 Buster, 2009
0.5 1 1.5 2 2.5 3 3.5 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% co nfidence band (shaded region) were obtained from an inverse-variance weighted random-effects meta-regression of log-transformed incidence rates on average follow-up lengths. Discussion
• Small number studies comprehensive view of the natural history of drug injecting career (¿?)
Review and discuss the main factors • A strong ↓ trend in IDI as the that can affect the IDI and which length of follow-up ↑ could help to explain our results or be opposed to them. Differential LsTF (selection bias): • differential survival • diferential non-response (no location, refusal) Other bias/factors Discussion Factors that would progressively reduce the IDI and explain our results.
Differential loss to follow-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 injectors or problem drug users would be lost at a higher rate than 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 the first stages of the follow-up and a consecutive ↓ 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
Some participants may abandon cocaine/heroin use during the follow-up and remain in the study as population at risk (denominator)
Progressive ↓ of the IDI as the length of heroin/cocaine use ↑ 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
Participants are not longer interested in keeping contact with a study about a life-style that they intend to leave behind Spurious ↑ of the IDI 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 LsTF hinders the assessment of the direction of the potential attrition bias 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. 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 rigour on 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. Thanks to Colleagues from the National Centre of Epidemiology: •Barrio Gregorio •Pastor Roberto •Sordo Luis
Colleague from National Drug and Alcohol Research Centre. Australia: •Degenhardt Louisa
Thanks for your attention [email protected]