Risk factors for poor treatment outcomes among opioid-dependent clients taking methadone in Mombasa, Kenya

TL;DR

The study identifies factors like lack of education and unemployment that increase the risk of poor treatment outcomes for opioid-dependent individuals on methadone in Mombasa, Kenya.

Contribution

The study provides new insights into specific risk factors for poor methadone treatment outcomes in Kenya, particularly among opioid-dependent clients.

Findings

Lack of formal education, unemployment, and being a non-injector were associated with poor treatment outcomes.

Females were younger, more educated, and had higher HIV and HCV prevalence compared to males.

Integration of Comprehensive Care Clinic services into MMT is recommended to improve outcomes.

Abstract

Background: The Methadone Maintenance Treatment (MMT) program has been proven to be beneficial in reducing illicit opioid use, increasing access to and retention of HIV treatment and other therapies, and reducing HIV transmission, and other drug-related morbidities and mortalities. However, determinants of treatment retention and outcomes for opioid-dependent persons accessing MMT in Kenya are limited. We sought to identify factors contributing to poor treatment outcomes among opioid-dependent persons enrolled in the Mombasa MMT program, between 2017 and 2019.

Method: We conducted a retrospective records review for opioid-dependent persons receiving Methadone treatment in the Kisauni MAT clinic enrolled during 2017–2019. We defined poor clinical or health-related treatment outcome as any client Lost-To-Follow-Up (LTFU), turned HIV or Viral hepatitis positive, and/or missed two or more antiretroviral therapy (ART) appointments intake during MMT. Variables abstracted from clinical and pharmacological MMT service delivery tools included socio-demographic characteristics, clinical history, risk factors, and MMT outcomes. Data were analyzed using Epi Info7. We calculated Prevalence Odds Ratios (POR) and 95% Confidence Intervals (CI) to identify factors associated with adverse health outcomes.

Results: Of the total 443 eligible records, the mean age was 37 years (SD ± 7.2) and males comprised 90.7%. The majority of females clients, 79.1% (34/43), were aged ≤35 years, 7.0% (3/43) had no education, 32.6% (14/43) were employed, 39.5% (17/43) were HIV positive and 18.6% (8/43) were HCV-positive. Overall, adverse treatment outcomes were at 27.5% (122/443), namely: LTFU at 22.8% (101/443), new HIV cases at 1.0% (4/391), HCV at 1.2% (5/405), and Hepatitis B Virus (HBV) at 1.2% (5/411), and 1.1% (5/443) died. Of HIV-infected clients linked to Comprehensive Care Clinic (CCC), 3.6% (2/56) defaulted from ART, and 25% (2/8) had detectable Viral Load of those retested. Lack of formal education (POR: 2.7, 95% CI: 1.3–5.7), unemployment (POR: 2.4, 95% CI: 1.4–4.0), and being a Non-Injector (POR: 1.7, 95% CI: 1.0–2.9) were negatively associated with treatment retention.

Conclusion: Females were younger, and more educated with higher HIV and HCV prevalence. Being a Non-injector, unemployment, and lack of formal education may increase the likelihood of poor treatment outcomes among MMT clients. Closer monitoring of MMT clients with these characteristics is recommended with the integration of CCC into MMT services.

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