Predictors of study retention in addiction treatment trials KORTE JE 1, MAGRUDER KM 1,2, KILLEEN TK 1, SONNE SC 1, SAMPSON RR 1 and BRADY KT 1,2 1. Medical University of South Carolina, Charleston, South Carolina, USA 2. Ralph H. Johnson VA Medical Center, Charleston, South Carolina, USA Predictors of study retention in addiction treatment trials KORTE JE 1, MAGRUDER KM 1,2, KILLEEN TK 1, SONNE SC 1, SAMPSON RR 1 and BRADY KT 1,2 1. Medical University of South Carolina, Charleston, South Carolina, USA 2. Ralph H. Johnson VA Medical Center, Charleston, South Carolina, USA  Design Secondary data analysis Pooled analysis of randomized controlled trials for drug addiction treatment First fifteen protocols in NIDA Clinical Trials Network (CTN) with datasets locked and appropriate for analyses of client retention during follow-up CTN 01, 02, 03, 04, 05, 06, 07, 09, 10, 11, 13, 15, 18, 19, 21  Retention definition Study-specific definition of retention Based on whether each client completed the final study assessment at which the major outcome variable was collected (as defined by the respective study protocols)  Study Population Each protocol included individuals meeting specific criteria for drug use (criteria varied by protocol) Participants were included in the retention analyses if they met study criteria and were randomized.  Follow-up Scheduled study visits varied by protocol (see Table 1)  Analysis Preliminary analyses: chi square for bivariate associations Logistic regression modeling to predict the odds of retention during follow-up Main predictors of interest: gender and ethnicity Stratified model by whether clients had taken prescribed methadone in 30 days before study baseline Other covariates: age, length of study follow-up NIDA Blending Conference, Albuquerque NM April 22-23, 2010 RESULTSINTRODUCTION OBJECTIVE METHODS SUMMARY AND CONCLUSIONS  Clients on methadone were seen to have better retention than other clients; further, among clients on methadone, other potential predictors were not strongly related to retention in study follow-up.  Among clients not on methadone, Caucasians were most likely to be lost to follow-up, and Hispanic/other clients were least likely. Women were 15% less likely to be lost to follow-up in comparison to men. In particular, Hispanic/other women had better retention than any other group.  By improving our ability to identify clients at increased risk of loss to follow-up during research studies, we can devise strategies to maximize retention for all participants. Future analyses will take into consideration other client and protocol characteristics to further refine our assessment of factors related to retention during follow-up. Differential attrition in research studies is a threat to study validity. Attrition during the treatment phase of a study should be conceptualized and studied separately from attrition during follow-up. Unbiased assessment of intervention effectiveness requires good follow-up rates, and roughly equivalent follow-up rates between groups. By focusing on retention during follow-up, we can improve our ability to maximize internal and external validity of study results. The current study is focused on attrition during follow-up, which is primarily relevant for valid ascertainment of research outcomes (as opposed to retention during treatment, which is relevant for both research outcomes and treatment planning). We examined predictors of follow-up completion in the first 15 protocols to have locked datasets in the NIDA Clinical Trials Network (CTN). We focused on gender and ethnicity as the main predictors of interest. The objective of the current study is to improve our understanding of why certain types of clients are lost to follow-up, in order to design better study procedures to maximize retention for all participants. In preliminary analyses, we observed large differences in retention between different CTN protocols (Table 2). Some of these differences are attributable to structural protocol characteristics (e.g. length of follow-up), or attributable to differences in the proportion of clients in methadone maintenance programs (expected to increase retention). In multivariate models of retention, we found that use of prescribed methadone during the last 30 days, as expected, was a highly significant predictor of retention during follow-up, with clients on methadone less than half as likely to be lost to follow-up (p<0.001). Stratifying by methadone status in logistic regression models (Table 4), we found that among methadone clients, no retention differences were seen by age, race, gender, or length of study follow-up. In contrast, among clients not using prescribed methadone, we found highly significant differences. In comparison to African Americans, white clients were 50% more likely to be lost to follow-up, whereas Hispanic/other clients were 30% less likely. Longer length of study follow-up was associated with better retention; this finding bears further investigation and may be due to other study/client characteristics. Finally, in both methadone and non- methadone clients, we found that women were 15% less likely to be lost to follow-up; this finding was significant in overall models and among non-methadone clients, but not among models limited to methadone clients. We observed a significant interaction between ethnicity and gender in relation to study retention: this interaction was largely driven by Hispanic/other women not in methadone treatment, who were approximately 40% less likely to be lost to follow-up than their African American counterparts. In contrast, white women (not in methadone treatment) were approximately 20% more likely to be lost to follow-up than their African American counterparts Race/ethnicity Caucasian59%41%71%42%84%38%28%36%70%64%37%49%48%58%0% African American21%38%11%42%12%45%54%24%0%35%33%35%25%24%0% Hispanic20%22%18%16%4%16%18%40%30%1%30%17%27%18%100% Gender Female59%28%33%71%58%55%43%48%42%37%100% 0%100%11% Age (mean) Retained to final follow- up visit 83%80%51%68%75%68%83%80%60%72%74%77%68%65%78% Using prescribed methadone in last 30 days 1% 4%0.4%1%100%72%3% 12%13%51%59%2% CTN protocol number Type of intervention Visit scheduleRetention definition 1Medication trial for inpatient opiate detox 13 days detox; then follow-up at 1, 3, and 6 months 13-day end of treatment 2Medication trial for outpatient opiate detox 13 days detox; then follow-up at 1, 3, and 6 months 13-day end of treatment 3Suboxone taper: comparison of two schedules 4 weeks of stabilization; then 7 or 28 days of taper; then follow-up at 1 and 3 months post-taper 3-month follow- up 4Motivational enhancement 28 day treatment; then follow-up at 1 and 3 months 3-month follow- up 5Motivational interviewing Single 2-hour session; then follow-up at 1 and 3 months 3-month follow- up 6Motivational incentives (drug free clinics) 12-week study, with follow-up visits at 1, 3, and 6 months after enrollment 6-month follow- up 7Motivational incentives (methadone clinics) 12-week study, with follow-up visits at 1, 3, and 6 months after enrollment 6-month follow- up 9Smoking cessation treatment 9-week study, with follow-up visits at 9, 13, and 26 weeks after target smoking quit date 13-week follow- up 10Medication trial for opioid- dependent adolescents 12-week study, with follow-up visits at 24, 36, and 52 weeks after enrollment 12-week end of treatment 11Telephone call support to increase post- discharge engagement and decrease drug/alcohol use 12-week study, with follow-up visit at week week follow- up 13Motivational enhancement in pregnant substance users 4-week study, with follow-up visits at 4 and 12 weeks after study 12-week follow- up 15“Seeking Safety” treatment for trauma for women with PTSD 6-week study, with follow-up visits at 1 week, 3, 6, and 12 months after treatment 12-month follow- up 18HIV/STD safer sex for men 1 or 5 session intervention, with follow-up visits immediately, and 3 and 6 months post treatment 3-month follow- up 19HIV/STD safer sex for women 1 or 5 session intervention, with follow-up visits immediately, and 3 and 6 months post treatment 3-month follow- up 21Motivational enhancement for Spanish- speaking clients 3 session intervention, with follow-up visits at 1 and 3 months 3-month follow- up Table 2. Client characteristics by protocol Table 1. Protocol characteristics %Chi-square p-value Ethnicity< Black70% White62% Hispanic/other74% Gender0.11 Male67% Female69% Age< % % % % % 60+69% Prescription methadone in last 30 days < No64% Yes80% Table 3. Proportion of clients completing study endpoint visit Table 4. Odds ratios from multivariate logistic regression models, modeling the odds of failing to complete the study endpoint visit Model 1: Clients on methadone (last 30 days) OR (95% CI)p-value Age (1-year interval)0.99 (0.97, 1.004)0.13 Ethnicity Black-reference- White0.95 (0.59, 1.5)0.77 Hispanic/other0.82 (0.49, 1.4)0.37 Sex (female)0.83 (0.58, 1.2)0.31 Length of follow-up (days)1.001 (0.998, 1.004)0.37 Model 2: Clients not on methadone OR (95% CI)p-value Age (1-year interval)0.994 (0.986, 1.002)0.12 Ethnicity Black-reference- White1.5 (1.2, 1.9)< Hispanic/other0.70 (0.55, 0.89)< Sex (female)0.84 (0.71, Length of follow-up (days)0.999 (0.998, 1.0)0.03