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Background: Patient-perceived Quality-of-Life (QOL) and treatment effectiveness (TEA) have previously been shown to be positively associated with better substance use treatment outcomes.
Objectives: This study examined potentially causal relationships amongst QOL, TEA, and cocaine abstinence.
Methods: Secondary data analyses (CTN-0148) were conducted on the NIDA Clinical Trial Network study, Cocaine Use Reduction with Buprenorphine (CTN-0048). N = 301 participants with DSM-IV cocaine dependence and opioid use history were administered injectable naltrexone and randomized to one of three buprenorphine/naloxone doses, 4 mg/1 mg, 16 mg/4 mg or placebo. Mediation models estimated direct and indirect effects amongst QOL, TEA, and cocaine abstinence.
Results: The QOL Environment domain exerted a significant indirect effect (B=0.01, SE=0.01, 95% CI=[0.00, 0.02]) on cocaine abstinence and a direct effect on TEA (B=0.57, SE=0.22, 95% CI=[0.16, 1.01]). Other QOL domains and individual QOL items exerted no statistically significant direct effects on cocaine abstinence. Overall QOL exerted a significant direct effect on TEA (95% CI=[0.32, 2.45]) along with a significant indirect effect on cocaine abstinence (95% CI=[0.01, 0.05]). TEA had a significant positive direct effect on cocaine abstinence (95% CI=[0.01, 0.02]).
Conclusion: Overall QOL and environmental QOL are related to treatment response through their relationship with patients’ perception of treatment effectiveness. TEA is directly related to cocaine abstinence at the end of treatment. QOL and TEA measures may serve as indicators of a need for additional support within care plans. These findings highlight the impact of a patient’s sense of well-being and their perceived treatment effectiveness on biochemically validated cocaine abstinence.
Related protocols: CTN-0148
This study aimed to estimate health state utility values (HSUVs) for the key health states found in opioid use disorder (OUD) cost-effectiveness models in the published literature. Data were obtained from six trials representing 1,777 individuals with OUD in the NIDA Clinical Trials Network (CTN-0001, -0002, -0009. -0030, -0049, and -0051). Researchers implemented mapping algorithms to harmonize data from different measures of quality of life (the SF-12 Versions 1 and 2 and the EQ-5D-3 L). They performed a regression analysis to quantify the relationship between HSUVs and the following variables: days of extra-medical opioid use in the past 30 days, injecting behaviors, treatment with medications for OUD, HIV status, and age. A secondary analysis explored the impact of opioid withdrawal symptoms.
There were statistically significant reductions in HSUVs associated with extra-medical opioid use (-0.002 (95% CI [-0.003,-0.0001]) to -0.003 (95% CI [-0.005,-0.002]) per additional day of heroin or other opiate use, respectively), drug injecting compared to not injecting (-0.043 (95% CI [-0.079,-0.006])), HIV-positive diagnosis compared to no diagnosis (-0.074 (95% CI [-0.143,-0.005])), and age (-0.001 per year (95% CI [-0.003,-0.0002])). Parameters associated with medications for OUD treatment were not statistically significant after controlling for extra-medical opioid use (0.0131 (95% CI [-0.0479,0.0769])), in line with prior studies. The secondary analysis revealed that withdrawal symptoms are a fundamental driver of HSUVs, with predictions of 0.817 (95% CI [0.768, 0.858]), 0.705 (95% CI [0.607, 0.786]), and 0.367 (95% CI [0.180, 0.575]) for moderate, severe, and worst level of symptoms, respectively.
Conclusions: Researchers for this study observed HSUVs for OUD that were higher than those from previous studies that had been conducted without input from people living with the condition.
Related protocols: CTN-0001, CTN-0002, CTN-0009, CTN-0030, CTN-0049, CTN-0051
Investigators and colleagues associated with the Center for Health Economics of Treatment Interventions for Substance Use Disorder, HCV, and HIV (CHERISH) conducted primary and secondary economic analyses using data collected from the X:BOT trial (CTN-0051). They measured the cost, quality of life impact, and cost-effectiveness of initiating extended-release naltrexone (XR-NTX) and buprenorphine naloxone (BUP-NX) in inpatient and residential treatment programs.
This two-page factsheet provides an overview of the study and its findings and makes these recommendations:
- Policymakers interested in maximizing economic value should consider supporting policies that promote BUP-NX as the preferred treatment over XR-NTX when both medications are shown to be equally effective and clinically appropriate for patients.
- Providers should direct patients to services that address their socioeconomic and psychosocial needs in addition to efforts to improve medication adherence. Customizing care to a patient’s needs can improve HRQoL benefits of treatment for OUD.
- Healthcare systems should invest in models of care that increase the likelihood of successful initiation of medication treatment for OUD, especially for XR-NTX, and decrease the duration of detoxification and residential days.
Funding: NIDA supported the health economic analyses (R01DA035808) and dissemination activities (P30DA040500). The X:BOT trial was supported by the NIDA CTN (UG1DA013034; UG1DA013035; UG1DA013714; HHSN271201200017C; HHSN271201500065C; U10DA013045; U10DA013046; U10DA013714; U10DA015833).
Related protocols: CTN-0051
This study aimed to examine the health-related quality-of-life (HRQoL) of people with opioid use disorder (OUD) seeking treatment in an inpatient detoxification or short-term residential setting, continuing treatment as outpatients.
Researchers conducted a secondary analysis of data (N=508) from NIDA Clinical Trials Network protocol CTN-0051 (X:BOT), where participants were randomized to extended-release naltrexone or buprenorphine-naloxone for the prevention of opioid relapse. They used a generalized structural equation regression mixture model to identify associations of HRQoL (EQ-5D) trajectories, including latent characteristics, over the 24-week trial and 36-week follow-up period, among participants who reported HRQoL beyond baseline. This novel framework accounted for baseline and time-varying characteristics, while simultaneously identifying latent classes.
Two subpopulations were identified: HRQoL “pharmacotherapy responsive” (82.3 %) and HRQoL “characteristic sensitive” (17.7 %). The pharmacotherapy responsive subpopulation was characterized by a short-term HRQoL improvement and then stable HRQoL over time, and by a positive association between HRQoL and receiving pharmacotherapy in the past 30 days. The characteristic sensitive subpopulation was characterized by an initial improvement in HRQoL with a gradual decline over time, and no significant HRQoL response to pharmacotherapy. HRQoL changes over time in this subpopulation were more influenced by baseline demographic, socioeconomic, and psychosocial characteristics.
Conclusions: These findings suggest that while HRQoL may be improved and sustained through targeted efforts to promote use of pharmacotherapy for many persons with OUD, an identifiable subpopulation may require additional services that address socioeconomic and psychosocial issues to achieve HRQoL benefits. This analysis provides insight for improving individualized care for persons with opioid use disorder seeking treatment.
Related protocols: CTN-0051
Health-related quality of life (HRQoL), a subjective assessment of physical and mental well-being in daily life, has emerged as a measure of the burden of disease and as a patient-centered outcome. In substance use disorder (SUD) research, HRQoL has been proposed as a measure of the negative impacts of substance use across life domains, as a way to identify subjective experience important to clients, and as an assessment of recovery beyond substance use outcomes.
This study, conducted in 24 SUD treatment programs affiliated with the NIDA Clinical Trials Network (10 residential, 7 outpatient, 7 methadone maintenance), used HRQoL to examine relationships of smoking status and tobacco-related variables among clients in substance use disorder treatment. Participants (N=2,068, 46.6% female) completed surveys reporting demographics, smoking status, and past-month days they experienced physical and/or mental health distress.
Current smokers (n=1,596; 77.2% of sample) answered questions on tobacco-related variables (smoking status, nicotine dependence, menthol smoking, electronic-cigarette use, health concerns, and cost as reasons affecting reducing/quitting smoking, past and future attempts) with HRQoL in four categories: good health, physical health distress, mental health distress, or both physical and mental health distress.
Current smokers were significantly more likely than former smokers to report frequent physical and mental health distress than good health (OR=1.97, 95% CI=1.16, 3.34), as were smokers with higher nicotine dependence (OR=1.18, 95% CI=1.03, 1.35). Smokers reporting both frequent physical and mental health distress were more sensitive to cigarettes’ cost (OR=1.56, 95% CI=1.06, 2.29), and less likely to use e-cigarettes (OR=0.59, 95% CI=0.38, 0.94).
Conclusions: Findings of poor HRQoL among nicotine-dependent smokers with additional SUDs strengthen the imperative to provide smoking cessation interventions in addictions treatment. These clients experience poor subjective well-being, which may have a reciprocal relationship with smoking and substance use, impacting treatment progress. If smoking cessation treatment is provided and smoking cessation can be achieved, it may have a positive impact on clients’ HRQoL which, in turn, may mediate improved substance use disorder treatment outcomes as well.
This study compared the cause-specific standardized mortality ratios (SMRs) and expected years of life lost (EYLL) among opioid-dependent individuals in the United States and Taiwan. Survival data came from two cohorts followed until 2014: The U.S. data were based on a randomized trial of 1267 opioid-dependent participants enrolled between 2006 and 2009, the CTN START study (CTN-0027); the Taiwan data were from a study of 983 individuals that began in 2006, when opioid agonist treatment (OAT) was implemented in Taiwan. SMRs were calculated for each national cohort and compared. Kaplan-Meier estimation was performed on the survival data, then lifespans were extrapolated to 70 years (840 months) to estimate life expectancy using a semi-parametric method. EYLLs for both cohorts were estimated by subtracting their life expectancies from the age- and gender-matched referents within the general population of their respective country.
Compared with age- and gender-matched references, the SMRs were 3.2 for the U.S. sample and 7.8 for the Taiwan sample; the EYLLs were 7.7 and 16.4 years, respectively. Half of decedents died of unnatural causes in both cohorts; overdose deaths predominated in the U.S. and suicide in Taiwan (with suicide mortality among the Taiwan OAT group 20 times greater than that of the U.S. START group).
Conclusions: Despite different contexts in two vastly different countries, the current estimates of EYLL highlight that opioid dependence and its associated comorbidities and risk factors still contribute severe health burdens across regions. This comparison of cause-specific SMRs could inform stakeholders as they make health policy modifications relevant to their region. Given the prominent role of overdose in the U.S. START cohort, improving access to medication-assisted treatment to prevent overdoses or naloxone to treat them will help address the problem. Suicide is preventable; intervention strategies, including regular screening of ideation and depressive symptoms and providing treatment and support among opioid users in OAT treatment, are urgently needed in Taiwan.
Related protocols: CTN-0027
Qualify of life is an important construct in assessing outcomes of substance use treatment interventions. The goal of the current analysis was to evaluate changes in participants’ quality of life in the Clinical Trials Network multi-site Cocaine Use Reduction with Buprenorphine (CURB) study in cocaine-dependent opioid users. Participants were randomly assigned to 1 of 3 conditions provided with extended-release naltrexone: 16 mg/day buprenorphine+naloxone (BUP) (BUP 16), 4mg/day BUP (BUP 4), 0mg/day BUP (placebo, PLB), plus weekly therapy and extended-release naltrexone (XR-NTX). Participants completed the WHOQOL-BREF at screening, end of medication/treatment, and the 3-month follow-up. This 24-item measure assessed quality of life across physical, psychological, social, and environmental domains. Of the 302 study participants, 219 completed QOL surveys at all time points and were used in the analyses. Baseline Quality of Life scores were lower than the norms established for individuals in a healthy population in all domains. No treatment effects were found, but there were statistically significant differences in mean ratings of QOL across the time points in all domains: physical, psychological, social, and environmental. Despite the significant increase in QOL at end of treatment, compared to the general population, participants were still scoring low in Social and Environmental domains.
Conclusions: The results showed significant improvements in quality of life between the start and end of treatment. However, despite the improvement, participants remained considerably lower than healthy population norms across some domains, suggesting the particular vulnerability of this substance-using population.
Related protocols: CTN-0048
Although prescription opioid use disorder has recently increased sharply in the United States, relatively little is known about the general well-being of this population. Assessment of quality of life in patients with substance use disorders has been recommended to improve clinical care. In this study, health-related quality of life was examined in prescription opioid-dependent patients at entry to the National Drug Abuse Treatment Clinical Trials Network’s “Prescription Opiate Addiction Treatment Study (POATS)”, a national multi-site trial, to compare quality of life scores in the study sample to other populations. Background variables associated with quality of life in the literature were also examined.
Prescription opioid-dependent patients (N=653) were compared to general populations on the Medical Outcome Study Short Form-36 (SF-36) quality of life measure, and the association between patient background variables and quality of life was examined. Compared to a general population, the current sample of prescription opioid-dependent patients had worse physical and mental quality of life as measured by the SF-36, similar to other opioid-use disorder populations. Within this sample, women showed more impairment than men in mental quality of life, while older patients scored worse on physical, but not mental, quality of life. Chronic pain was associated with poorer physical quality of life.
Conclusions: The growing focus on wellness underscores the importance of measuring quality of life in addition to substance use outcomes. Routine assessment of health-related quality of life can add an important dimension to overall evaluation of patients’ treatment response. Furthermore, brief, widely-used measures of health-related quality of life such as the SF-36 enable comparisons of these factors between different patient populations and can inform both clinical treatment selection and policy decisions about the allocation of health care resources.
Related protocols: CTN-0030