1. Demographic Characteristics and Smoking Severity at entry into the SALOME Study Scott MacDonald 1, Eugenia Oviedo-Joekes 2,3, Kirsten Marchand 2,3, Daphne Guh 3 (1) Providence Health Care, Crosstown Clinic (2) School of Population and Public Health, University of British Columbia (3) Centre for Health Evaluation and Outcome Sciences Conclusions Background Objectives Results Table 2. Mean smoking severity score by demographic characteristics at baseline References Contact Information Studies in Europe and Canada 1,2,3 have demonstrated that injectable diacetylmorphine (the active ingredient in heroin), provided in specialized clinics, is effective at engaging and retaining the most vulnerable street heroin injectors in treatment. Due to the political restrictions around the prescription of diacetylmorphine, alternatives are needed. Such an alternative could be injectable hydromorphone (a licensed pain medication). This group of illicit heroin users has a high degree of tobacco use. The morbidity associated with their tobacco use could affect outcomes and participation in opioid substitution treatment. The aim of this baseline analysis was to describe participants' smoking severity at entry into a study of injectable diacetylmorphine and hydromorphone and to identify characteristics associated with smoking severity. Methods and Analysis Design : The Study to Assess Long-term Opioid Medication Effectiveness (SALOME) was a two-stage phase III, single site (Vancouver, Canada), randomized double blind controlled trial. SALOME was designed to test if hydromorphone was as effective as diacetylmorphine for the treatment of long-term illicit opioid injection. Study sample : SALOME randomized a total of 202 men and women with chronic, long-term opioid dependence. At treatment entry, participants were current illicit injection opioid users and had at least one previous episode of opioid maintenance treatment. Data collection: Baseline questionnaires were collected by an independent research team and measured demographic, substance use, and health status. The main outcome variable of interest, smoking severity, was measured using the Fagerstrom Test for Nicotine Dependence 4. Data analysis: Data were measured with descriptive statistics. Continuous variables were described with mean ± SD and categorical variables were described by frequencies and percentages. To test the relationship between baseline demographic characteristics and Fagerstrom score, independent t-tests were used. Dr. Scott MacDonald, Physician Lead, Providence Crosstown Clinic 84 West Hastings Street Vancouver, BC V6B 1G6 Smacdonald2@providencehealth.bc.ca 1) Oviedo-Joekes, E., Brissette, S., Marsh, D. C., Lauzon, P., Guh, D., Anis, A., & Schechter, M. T. (2009). Diacetylmorphine versus methadone for the treatment of opioid addiction. New England Journal of Medicine, 361 (8), 777-786. 2) Van den Brink, W., Hendriks, V. M., Blanken, P., Koeter, M. W., van Zwieten, B. J., & Van Ree, J. M. (2003). Medical prescription of heroin to treatment resistant heroin addicts: two randomized controlled trials. Bmj, 327 (7410), 310. 3) March, J. C., Oviedo-Joekes, E., Perea-Milla, E., & Carrasco, F. (2006). Controlled trial of prescribed heroin in the treatment of opioid addiction. Journal of substance abuse treatment, 31 (2), 203-211. 4) Heatherton TF, Kozlowski LT, Frecker RC, Fagerstrom K. (1991). The Fagerstrom Test for Nicotine Dependence: a revision of the Fagerstrom Tolerance Questionnaire. British Journal of Addiction, 86 (9), 1119-1127. This is a group of patients with severe opiate use disorder as well as concurrent chronic disease, including smoking disease. Their severe symptomatology may be mitigated by smoking cessation. This analysis suggests there is a group of injectable opioid assisted treatment (iOAT) recipients who could benefit from intensified programs such as the Ottawa Smoking Cessation Model. Future analysis may show improvement in this group of patients in whom smoking is often ignored as an important intervention. Table 1 and Figure 1 present the proportion of participants in baseline Fagerstrom severity score category groups. Several baseline characteristics at baseline entry to SALOME are presented here, including: gender, education, age, and crack cocaine use (see table 2). The only characteristic which showed a statistically significant difference was self-reported chronic disease. These data show that study participants who self- reported chronic disease on enrolment had significantly higher smoking dependence (Mean Fagerstrom score = 4.73 [SD=2.34]) compared to those without chronic disease (Mean Fagerstrom score = 3.95 [SD=2.51]) (p<0.028). CharacteristicsFagerstrom Score Total Sample 4.40 ± 2.44 Women 4.31 ± 2.51 Men 4.44 ± 2.41 Less than 40 years old 4.81 ± 2.46 40 years or older 4.24 ± 2.42 Non-Aboriginal ethnicity 4.21 ± 2.43 Aboriginal ethnicity 4.84 ± 2.42 Less than high school education 4.64 ± 2.32 High school education or higher 4.19 ± 2.53 Has a self-reported chronic condition * 4.73 ± 2.34 No self-reported chronic conditions * 3.95 ± 2.51 HIV Positive 4.25 ± 2.58 HIV Negative 4.43 ± 2.42 Hepatitis C Positive 4.45 ± 2.46 Hepatitis C Negative 4.08 ± 2.32 Using crack cocaine 4.59 ± 2.28 No crack cocaine use4.08 ± 2.67 Table 1: Fagerstrom smoking severity score groups Smoking Severity Score Group Number of participants (%) Not currently smoking (Score= 0) 17 (8.95) Low dependence (Score= 1-2)30 (15.79) Low to moderate dependence (Score= 3-4)35 (18.42) Moderate dependence (Score= 5-7)94 (49.47) High dependence (Score= 8+)14 (7.37) Figure 1. Proportion of participants in smoking severity groups * p < 0.05 n missing = 12