Comparing the Performance of World Mental Health Composite International Diagnostic Interview Substance Abuse Module in Adolescents to Diagnoses Made by Pediatric Addiction Medicine Specialists.

OBJECTIVES: The World Mental Health Composite International Diagnostic Interview Substance Abuse Module (WMH-CIDI-SAM) is commonly used as a criterion standard measure for substance use disorder (SUD) diagnoses, although the accuracy of this tool when used with adolescents is unknown. The objective of this study was to evaluate the agreement between SUD diagnoses for adolescents made by WMH-CIDI-SAM and those made by specialists based on Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition) ( DSM-5 ) SUD criteria during an SUD evaluation. METHODS: Adolescents aged 12 to 17 years presenting to an outpatient SUD program for youth were administered the WMH-CIDI-SAM by a trained research assistant, and results were compared with diagnoses made by experienced clinicians based on DSM-5 SUD criteria during an initial SUD evaluation. Chance-corrected concordance was estimated using the κ coefficient for the comparisons. RESULTS: The level of concordance between the WMH-CIDI-SAM interview and the clinician diagnosis based on DSM-5 SUD criteria were fair to moderate for alcohol use disorder and tobacco use disorder and poor for cannabis use disorder. Three of 11 WMH-CIDI-SAM item constructs showed poor concordance with clinician diagnosis. CONCLUSIONS: Interpreting the diagnostic criteria for SUDs, particularly cannabis use disorders, is nuanced, and the meaning of the criteria may be misunderstood by adolescents. Further evaluation of the performance of the WMH-CIDI-SAM diagnostic interview for identifying cannabis use disorders in adolescents is needed.

Subthreshold opioid use disorder prevention (STOP) trial: a cluster randomized clinical trial: study design and methods.

BACKGROUND: Preventing progression to moderate or severe opioid use disorder (OUD) among people who exhibit risky opioid use behavior that does not meet criteria for treatment with opioid agonists or antagonists (subthreshold OUD) is poorly understood. The Subthreshold Opioid Use Disorder Prevention (STOP) Trial is designed to study the efficacy of a collaborative care intervention to reduce risky opioid use and to prevent progression to moderate or severe OUD in adult primary care patients with subthreshold OUD. METHODS: The STOP trial is a cluster randomized controlled trial, randomized at the PCP level, conducted in 5 distinct geographic sites. STOP tests the efficacy of the STOP intervention in comparison to enhanced usual care (EUC) in adult primary care patients with risky opioid use that does not meet criteria for moderate-severe OUD. The STOP intervention consists of (1) a practice-embedded nurse care manager (NCM) who provides patient participant education and supports primary care providers (PCPs) in engaging and monitoring patient-participants; (2) brief advice, delivered to patient participants by their PCP and/or prerecorded video message, about health risks of opioid misuse; and (3) up to 6 sessions of telephone health coaching to motivate and support behavior change. EUC consists of primary care treatment as usual, plus printed overdose prevention educational materials and an educational video on cancer screening. The primary outcome measure is self-reported number of days of risky (illicit or nonmedical) opioid use over 180 days, assessed monthly via text message using items from the Addiction Severity Index and the Current Opioid Misuse Measure. Secondary outcomes assess other substance use, mental health, quality of life, and healthcare utilization as well as PCP prescribing and monitoring behaviors. A mixed effects negative binomial model with a log link will be fit to estimate the difference in means between treatment and control groups using an intent-to-treat population. DISCUSSION: Given a growing interest in interventions for the management of patients with risky opioid use, and the need for primary care-based interventions, this study potentially offers a blueprint for a feasible and effective approach to improving outcomes in this population. TRIAL REGISTRATION: Clinicaltrials.gov, identifier NCT04218201, January 6, 2020.

Nurse Care Management for Opioid Use Disorder Treatment: The PROUD Cluster Randomized Clinical Trial.

Importance: Few primary care (PC) practices treat patients with medications for opioid use disorder (OUD) despite availability of effective treatments. Objective: To assess whether implementation of the Massachusetts model of nurse care management for OUD in PC increases OUD treatment with buprenorphine or extended-release injectable naltrexone and secondarily decreases acute care utilization. Design, Setting, and Participants: The Primary Care Opioid Use Disorders Treatment (PROUD) trial was a mixed-methods, implementation-effectiveness cluster randomized clinical trial conducted in 6 diverse health systems across 5 US states (New York, Florida, Michigan, Texas, and Washington). Two PC clinics in each system were randomized to intervention or usual care (UC) stratified by system (5 systems were notified on February 28, 2018, and 1 system with delayed data use agreement on August 31, 2018). Data were obtained from electronic health records and insurance claims. An implementation monitoring team collected qualitative data. Primary care patients were included if they were 16 to 90 years old and visited a participating clinic from up to 3 years before a system's randomization date through 2 years after. Intervention: The PROUD intervention included 3 components: (1) salary for a full-time OUD nurse care manager; (2) training and technical assistance for nurse care managers; and (3) 3 or more PC clinicians agreeing to prescribe buprenorphine. Main Outcomes and Measures: The primary outcome was a clinic-level measure of patient-years of OUD treatment (buprenorphine or extended-release injectable naltrexone) per 10 000 PC patients during the 2 years postrandomization (follow-up). The secondary outcome, among patients with OUD prerandomization, was a patient-level measure of the number of days of acute care utilization during follow-up. Results: During the baseline period, a total of 130 623 patients were seen in intervention clinics (mean [SD] age, 48.6 [17.7] years; 59.7% female), and 159 459 patients were seen in UC clinics (mean [SD] age, 47.2 [17.5] years; 63.0% female). Intervention clinics provided 8.2 (95% CI, 5.4-∞) more patient-years of OUD treatment per 10 000 PC patients compared with UC clinics (P = .002). Most of the benefit accrued in 2 health systems and in patients new to clinics (5.8 [95% CI, 1.3-∞] more patient-years) or newly treated for OUD postrandomization (8.3 [95% CI, 4.3-∞] more patient-years). Qualitative data indicated that keys to successful implementation included broad commitment to treat OUD in PC from system leaders and PC teams, full financial coverage for OUD treatment, and straightforward pathways for patients to access nurse care managers. Acute care utilization did not differ between intervention and UC clinics (relative rate, 1.16; 95% CI, 0.47-2.92; P = .70). Conclusions and Relevance: The PROUD cluster randomized clinical trial intervention meaningfully increased PC OUD treatment, albeit unevenly across health systems; however, it did not decrease acute care utilization among patients with OUD. Trial Registration: ClinicalTrials.gov Identifier: NCT03407638.

Assessment of Screening Tools to Identify Substance Use Disorders Among Adolescents.

Importance: Efficient screening tools that effectively identify substance use disorders (SUDs) among youths are needed. Objective: To evaluate the psychometric properties of 3 brief substance use screening tools (Screening to Brief Intervention [S2BI]; Brief Screener for Tobacco, Alcohol, and Drugs [BSTAD]; and Tobacco, Alcohol, Prescription Medication, and Other Substances [TAPS]) with adolescents aged 12 to 17 years. Design, Setting, and Participants: This cross-sectional validation study was conducted from July 1, 2020, to February 28, 2022. Participants aged 12 to 17 years were recruited virtually and in person from 3 health care settings in Massachusetts: (1) an outpatient adolescent SUD treatment program at a pediatric hospital, (2) an adolescent medicine program at a community pediatric practice affiliated with an academic institution, and (3) 1 of 28 participating pediatric primary care practices. Participants were randomly assigned to complete 1 of the 3 electronic screening tools via self-administration, followed by a brief electronic assessment battery and a research assistant-administered diagnostic interview as the criterion standard measure for Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) diagnoses of SUDs. Data were analyzed from May 31 to September 13, 2022. Main Outcomes and Measures: The main outcome was a DSM-5 diagnosis of tobacco/nicotine, alcohol, or cannabis use disorder as determined by the criterion standard World Mental Health Composite International Diagnostic Interview Substance Abuse Module. Classification accuracy of the 3 substance use screening tools was assessed by examining the agreement between the criterion, using sensitivity and specificity, based on cut points for each tool for use disorder, chosen a priori from previous studies. Results: This study included 798 adolescents, with a mean (SD) age of 14.6 (1.6) years. The majority of participants identified as female (415 [52.0%]) and were White (524 [65.7%]). High agreement between screening results and the criterion standard measure was observed, with area under the curve values ranging from 0.89 to 1 for nicotine, alcohol, and cannabis use disorders for each of the 3 screening tools. Conclusions and Relevance: These findings suggest that screening tools that use questions on past-year frequency of use are effective for identifying adolescents with SUDs. Future work could examine whether these tools have differing properties when used with different groups of adolescents in different settings.

Design of a pragmatic clinical trial to improve screening and treatment for opioid use disorder in primary care.

BACKGROUND: Opioid-related deaths continue to rise in the U.S. A shared decision-making (SDM) system to help primary care clinicians (PCCs) identify and treat patients with opioid use disorder (OUD) could help address this crisis. METHODS: In this cluster-randomized trial, primary care clinics in three healthcare systems were randomized to receive or not receive access to an OUD-SDM system. The OUD-SDM system alerts PCCs and patients to elevated risk of OUD and supports OUD screening and treatment. It includes guidance on OUD screening and diagnosis, treatment selection, starting and maintaining patients on buprenorphine for waivered clinicians, and screening for common comorbid conditions. The primary study outcome is, of patients at high risk for OUD, the percentage receiving an OUD diagnosis within 30 days of index visit. Additional outcomes are, of patients at high risk for or with a diagnosis of OUD, (a) the percentage receiving a naloxone prescription, or (b) the percentage receiving a medication for OUD (MOUD) prescription or referral to specialty care within 30 days of an index visit, and (c) total days covered by a MOUD prescription within 90 days of an index visit. RESULTS: The intervention started in April 2021 and continues through December 2023. PCCs and patients in 90 clinics are included; study results are expected in 2024. CONCLUSION: This protocol paper describes the design of a multi-site trial to help PCCs recognize and treat OUD. If effective, this OUD-SDM intervention could improve screening of at-risk patients and rates of OUD treatment for people with OUD.

Baseline representativeness of patients in clinics enrolled in the PRimary care Opioid Use Disorders treatment (PROUD) trial: comparison of trial and non-trial clinics in the same health systems.

BACKGROUND: Pragmatic primary care trials aim to test interventions in "real world" health care settings, but clinics willing and able to participate in trials may not be representative of typical clinics. This analysis compared patients in participating and non-participating clinics from the same health systems at baseline in the PRimary care Opioid Use Disorders treatment (PROUD) trial. METHODS: This observational analysis relied on secondary electronic health record and administrative claims data in 5 of 6 health systems in the PROUD trial. The sample included patients 16-90 years at an eligible primary care visit in the 3 years before randomization. Each system contributed 2 randomized PROUD trial clinics and 4 similarly sized non-trial clinics. We summarized patient characteristics in trial and non-trial clinics in the 2 years before randomization ("baseline"). Using mixed-effect regression models, we compared trial and non-trial clinics on a baseline measure of the primary trial outcome (clinic-level patient-years of opioid use disorder (OUD) treatment, scaled per 10,000 primary care patients seen) and a baseline measure of the secondary trial outcome (patient-level days of acute care utilization among patients with OUD). RESULTS: Patients were generally similar between the 10 trial clinics (n = 248,436) and 20 non-trial clinics (n = 341,130), although trial clinics' patients were slightly younger, more likely to be Hispanic/Latinx, less likely to be white, more likely to have Medicaid/subsidized insurance, and lived in less wealthy neighborhoods. Baseline outcomes did not differ between trial and non-trial clinics: trial clinics had 1.0 more patient-year of OUD treatment per 10,000 patients (95% CI: - 2.9, 5.0) and a 4% higher rate of days of acute care utilization than non-trial clinics (rate ratio: 1.04; 95% CI: 0.76, 1.42). CONCLUSIONS: trial clinics and non-trial clinics were similar regarding most measured patient characteristics, and no differences were observed in baseline measures of trial primary and secondary outcomes. These findings suggest trial clinics were representative of comparably sized clinics within the same health systems. Although results do not reflect generalizability more broadly, this study illustrates an approach to assess representativeness of clinics in future pragmatic primary care trials.

Clinical documentation of patient-reported medical cannabis use in primary care: Toward scalable extraction using natural language processing methods.

Background: Most states have legalized medical cannabis, yet little is known about how medical cannabis use is documented in patients' electronic health records (EHRs). We used natural language processing (NLP) to calculate the prevalence of clinician-documented medical cannabis use among adults in an integrated health system in Washington State where medical and recreational use are legal. Methods: We analyzed EHRs of patients ≥18 years old screened for past-year cannabis use (November 1, 2017-October 31, 2018), to identify clinician-documented medical cannabis use. We defined medical use as any documentation of cannabis that was recommended by a clinician or described by the clinician or patient as intended to manage health conditions or symptoms. We developed and applied an NLP system that included NLP-assisted manual review to identify such documentation in encounter notes. Results: Medical cannabis use was documented for 16,684 (5.6%) of 299,597 outpatient encounters with routine screening for cannabis use among 203,489 patients seeing 1,274 clinicians. The validated NLP system identified 54% of documentation and NLP-assisted manual review the remainder. Language documenting reasons for cannabis use included 125 terms indicating medical use, 28 terms indicating non-medical use and 41 ambiguous terms. Implicit documentation of medical use (e.g., "edible THC nightly for lumbar pain") was more common than explicit (e.g., "continues medical cannabis use"). Conclusions: Clinicians use diverse and often ambiguous language to document patients' reasons for cannabis use. Automating extraction of documentation about patients' cannabis use could facilitate clinical decision support and epidemiological investigation but will require large amounts of gold standard training data.

An Examination of the Feasibility of Detecting Cocaine Use Using Smartwatches.

As digital technology increasingly informs clinical trials, novel ways to collect study data in the natural field setting have the potential to enhance the richness of research data. Cocaine use in clinical trials is usually collected via self-report and/or urine drug screen results, both of which have limitations. This article examines the feasibility of developing a wrist-worn device that can detect sufficient physiological data (i.e., heart rate and heart rate variability) to detect cocaine use. This study aimed to develop a wrist-worn device that can be used in the natural field setting among people who use cocaine to collect reliable data (determined by data yield, device wearability, and data quality) that is less obtrusive than chest-based devices used in prior research. The study also aimed to further develop a cocaine use detection algorithm used in previous research with an electrocardiogram on a chestband by adapting it to a photoplethysmography sensor on the wrist-worn device which is more prone to motion artifacts. Results indicate that wrist-based heart rate data collection is feasible and can provide higher data yield than chest-based sensors, as wrist-based devices were also more comfortable and affected participants' daily lives less often than chest-based sensors. When properly worn, wrist-based sensors produced similar quality of heart rate and heart rate variability features to chest-based sensors and matched their performance in automated detection of cocaine use events. Clinical Trial Registration: www.ClinicalTrials.gov, identifier: NCT02915341.

PRimary Care Opioid Use Disorders treatment (PROUD) trial protocol: a pragmatic, cluster-randomized implementation trial in primary care for opioid use disorder treatment.

BACKGROUND: Most people with opioid use disorder (OUD) never receive treatment. Medication treatment of OUD in primary care is recommended as an approach to increase access to care. The PRimary Care Opioid Use Disorders treatment (PROUD) trial tests whether implementation of a collaborative care model (Massachusetts Model) using a nurse care manager (NCM) to support medication treatment of OUD in primary care increases OUD treatment and improves outcomes. Specifically, it tests whether implementation of collaborative care, compared to usual primary care, increases the number of days of medication for OUD (implementation objective) and reduces acute health care utilization (effectiveness objective). The protocol for the PROUD trial is presented here. METHODS: PROUD is a hybrid type III cluster-randomized implementation trial in six health care systems. The intervention consists of three implementation strategies: salary for a full-time NCM, training and technical assistance for the NCM, and requiring that three primary care providers have DEA waivers to prescribe buprenorphine. Within each health system, two primary care clinics are randomized: one to the intervention and one to Usual Primary Care. The sample includes all patients age 16-90 who visited the randomized primary care clinics from 3 years before to 2 years after randomization (anticipated to be > 170,000). Quantitative data are derived from existing health system administrative data, electronic medical records, and/or health insurance claims ("electronic health records," [EHRs]). Anonymous staff surveys, stakeholder debriefs, and observations from site visits, trainings and technical assistance provide qualitative data to assess barriers and facilitators to implementation. The outcome for the implementation objective (primary outcome) is a clinic-level measure of the number of patient days of medication treatment of OUD over the 2 years post-randomization. The patient-level outcome for the effectiveness objective (secondary outcome) is days of acute care utilization [e.g. urgent care, emergency department (ED) and/or hospitalizations] over 2 years post-randomization among patients with documented OUD prior to randomization. DISCUSSION: The PROUD trial provides information for clinical leaders and policy makers regarding potential benefits for patients and health systems of a collaborative care model for management of OUD in primary care, tested in real-world diverse primary care settings. Trial registration # NCT03407638 (February 28, 2018); CTN-0074 https://clinicaltrials.gov/ct2/show/NCT03407638?term=CTN-0074&draw=2&rank=1.

Addressing identification bias in the design and analysis of cluster-randomized pragmatic trials: a case study.

BACKGROUND: Pragmatic trials provide the opportunity to study the effectiveness of health interventions to improve care in real-world settings. However, use of open-cohort designs with patients becoming eligible after randomization and reliance on electronic health records (EHRs) to identify participants may lead to a form of selection bias referred to as identification bias. This bias can occur when individuals identified as a result of the treatment group assignment are included in analyses. METHODS: To demonstrate the importance of identification bias and how it can be addressed, we consider a motivating case study, the PRimary care Opioid Use Disorders treatment (PROUD) Trial. PROUD is an ongoing pragmatic, cluster-randomized implementation trial in six health systems to evaluate a program for increasing medication treatment of opioid use disorders (OUDs). A main study objective is to evaluate whether the PROUD intervention decreases acute care utilization among patients with OUD (effectiveness aim). Identification bias is a particular concern, because OUD is underdiagnosed in the EHR at baseline, and because the intervention is expected to increase OUD diagnosis among current patients and attract new patients with OUD to the intervention site. We propose a framework for addressing this source of bias in the statistical design and analysis. RESULTS: The statistical design sought to balance the competing goals of fully capturing intervention effects and mitigating identification bias, while maximizing power. For the primary analysis of the effectiveness aim, identification bias was avoided by defining the study sample using pre-randomization data (pre-trial modeling demonstrated that the optimal approach was to use individuals with a prior OUD diagnosis). To expand generalizability of study findings, secondary analyses were planned that also included patients newly diagnosed post-randomization, with analytic methods to account for identification bias. CONCLUSION: As more studies seek to leverage existing data sources, such as EHRs, to make clinical trials more affordable and generalizable and to apply novel open-cohort study designs, the potential for identification bias is likely to become increasingly common. This case study highlights how this bias can be addressed in the statistical study design and analysis. TRIAL REGISTRATION: ClinicalTrials.gov, NCT03407638. Registered on 23 January 2018.

Documented opioid use disorder and its treatment in primary care patients across six U.S. health systems.

BACKGROUND: The United States is in the middle of an opioid overdose epidemic, and experts are calling for improved detection of opioid use disorders (OUDs) and treatment with buprenorphine or extended release (XR) injectable naltrexone, which can be prescribed in general medical settings. To better understand the magnitude of opportunities for treatment among primary care (PC) patients, we estimated the prevalence of documented OUD and medication treatment of OUD among PC patients. METHODS: This cross-sectional study included patients with ≥2 visits to PC clinics across 6 healthcare delivery systems who were ≥16 years of age during the study period (fiscal years 2014-2016). Diagnoses, prescriptions, and healthcare utilization were ascertained from electronic health records and insurance claims (5 systems that also offer health insurance). Documented OUDs were defined as ≥1 International Classification of Diseases code for OUDs (active or remission), and OUD treatment was defined as ≥1 prescription(s) for buprenorphine formulations indicated for OUD or naltrexone XR, during the 3-year study period. The prevalence of documented OUD and treatment (95% confidence intervals) across health systems were estimated, and characteristics of patients by treatment status were compared. Prevalence of OUD and OUD treatment were adjusted for age, gender, and race/ethnicity. Combined results were also adjusted for site. RESULT: Among 1,403,327 eligible PC patients, 54-62% were female and mean age ranged from 46 to 51 years across health systems. The 3-year prevalence of documented OUD ranged from 0.7-1.4% across the health systems. Among patients with documented OUD, the prevalence of medication treatment (primarily buprenorphine) varied across health systems: 3%, 12%, 16%, 20%, 22%, and 36%. CONCLUSION: The prevalence of documented OUD and OUD treatment among PC patients varied widely across health systems. The majority of PC patients with OUD did not have evidence of treatment with buprenorphine or naltrexone XR, highlighting opportunities for improved identification and treatment in medical settings. These results can inform initiatives aimed at improving treatment of OUD in PC. Future research should focus on why there is such variation and how much of the variation can be addressed by improving access to medication treatment.

Prevalence and treatment of opioid use disorders among primary care patients in six health systems.

BACKGROUND: The U.S. experienced nearly 48,000 opioid overdose deaths in 2017. Treatment of opioid use disorder (OUD) with buprenorphine is a recommended part of primary care, yet little is known about current U.S. practices in this setting. This observational study reports the prevalence of documented OUD and OUD treatment with buprenorphine among primary care patients in six large health systems. METHODS: Adults with ≥2 primary care visits during a three-year period (10/1/2013-9/30/2016) in six health systems were included. Data were obtained from electronic health record and claims data, with measures, assessed over the three-year period, including indicators for documented OUD from ICD 9 and 10 codes and OUD treatment with buprenorphine. The prevalence of OUD treatment was adjusted for age, gender, race/ethnicity, and health system. RESULTS: Among 1,368,604 primary care patients, 13,942 (1.0 %) had documented OUD, and among these, 21.0 % had OUD treatment with buprenorphine. For those with documented OUD, the adjusted prevalence of OUD treatment with buprenorphine varied across demographic and clinical subgroups. OUD treatment was lower among patients who were older, women, Black/African American and Hispanic (compared to white), non-commercially insured, and those with non-cancer pain, mental health disorders, greater comorbidity, and more opioid prescriptions, emergency department visits or hospitalizations. CONCLUSIONS: Among primary care patients in six health systems, one in five with an OUD were treated with buprenorphine, with disparities across demographic and clinical characteristics. Less buprenorphine treatment among those with greater acute care utilization highlights an opportunity for systems-level changes to increase OUD treatment.

Towards detecting cocaine use using smartwatches in the NIDA clinical trials network: Design, rationale, and methodology.

Cocaine use in clinical trials is often measured via self-report, which can be inaccurate, or urine drug screens, which can be intrusive and burdensome. Devices that can automatically detect cocaine use and can be worn conveniently in daily life may provide several benefits. AutoSense is a wearable, physiological-monitoring suite that can detect cocaine use, but it may be limited as a method for monitoring cocaine use because it requires wearing a chestband with electrodes. This paper describes the design, rationale, and methodology of a project that seeks to build upon and extend previous work in the development of methods to detect cocaine use via wearable, unobtrusive mobile sensor technologies. To this end, a wrist-worn sensor suite (i.e., MotionSense HRV) will be developed and evaluated. Participants who use cocaine (N = 25) will be asked to wear MotionSense HRV and AutoSense for two weeks during waking hours. Drug use will be assessed via thrice-weekly urine drug screens and self-reports, and will be used to isolate periods of cocaine use that will be differentiated from other drug use. The present study will provide information on the feasibility and acceptability of using a wrist-worn device to detect cocaine use.

Effect of Oral Valproic Acid vs Placebo for Vision Loss in Patients With Autosomal Dominant Retinitis Pigmentosa: A Randomized Phase 2 Multicenter Placebo-Controlled Clinical Trial.

Importance: There are no approved drug treatments for autosomal dominant retinitis pigmentosa, a relentlessly progressive cause of adult and childhood blindness. Objectives: To evaluate the potential efficacy and assess the safety of orally administered valproic acid (VPA) in the treatment of autosomal dominant retinitis pigmentosa. Design, Setting, and Participants: Multicenter, phase 2, prospective, interventional, placebo-controlled, double-masked randomized clinical trial. The study took place in 6 US academic retinal degeneration centers. Individuals with genetically characterized autosomal dominant retinitis pigmentosa were randomly assigned to receive treatment or placebo for 12 months. Analyses were intention-to-treat. Interventions: Oral VPA 500 mg to 1000 mg daily for 12 months or placebo. Main Outcomes and Measures: The primary outcome measure was determined prior to study initiation as the change in visual field area (assessed by the III4e isopter, semiautomated kinetic perimetry) between baseline and month 12. Results: The mean (SD) age of the 90 participants was 50.4 (11.6) years. Forty-four (48.9%) were women, 87 (96.7%) were white, and 79 (87.8%) were non-Hispanic. Seventy-nine participants (87.8%) completed the study (42 [95.5%] received placebo and 37 [80.4%] received VPA). Forty-two (46.7%) had a rhodopsin mutation. Most adverse events were mild, although 7 serious adverse events unrelated to VPA were reported. The difference between the VPA and placebo arms for mean change in the primary outcome was -150.43 degree2 (95% CI, -290.5 to -10.03; P = .035). Conclusions and Relevance: This negative value indicates that the VPA arm had worse outcomes than the placebo group. This study brings to light the key methodological considerations that should be applied to the rigorous evaluation of treatments for these conditions. This study does not provide support for the use of VPA in the treatment of autosomal dominant retinitis pigmentosa. Trial Registration: ClinicalTrials.gov Identifier: NCT01233609.

Buprenorphine + naloxone plus naltrexone for the treatment of cocaine dependence: the Cocaine Use Reduction with Buprenorphine (CURB) study.

AIMS: To examine the safety and effectiveness of buprenorphine + naloxone sublingual tablets (BUP, as Suboxone(®) ) provided after administration of extended-release injectable naltrexone (XR-NTX, as Vivitrol(®) ) to reduce cocaine use in participants who met DSM-IV criteria for cocaine dependence and past or current opioid dependence or abuse. METHODS: This multi-centered, double-blind, placebo-controlled study, conducted under the auspices of the National Drug Abuse Treatment Clinical Trials Network, randomly assigned 302 participants at sites in California, Oregon, Washington, Colorado, Texas, Georgia, Ohio, New York and Washington DC, USA to one of three conditions provided with XR-NTX: 4 mg/day BUP (BUP4, n = 100), 16 mg/day BUP (BUP16, n = 100, or no buprenorphine (placebo; PLB, n = 102). Participants received pharmacotherapy for 8 weeks, with three clinic visits per week. Cognitive behavioral therapy was provided weekly. Follow-up assessments occurred at 1 and 3 months post-intervention. The planned primary outcome was urine drug screen (UDS)-corrected, self-reported cocaine use during the last 4 weeks of treatment. Planned secondary analyses assessed cocaine use by UDS, medication adherence, retention and adverse events. RESULTS: No group differences were found between groups for the primary outcome (BUP4 versus PLB, P = 0.262; BUP16 versus PLB, P = 0.185). Longitudinal analysis of UDS data during the evaluation period using generalized linear mixed equations found a statistically significant difference between BUP16 and PLB [P = 0.022, odds ratio (OR) = 1.71] but not for BUP4 (P = 0.105, OR = 1.05). No secondary outcome differences across groups were found for adherence, retention or adverse events. CONCLUSIONS: Buprenorphine + naloxone, used in combination with naltrexone, may be associated with reductions in cocaine use among people who meet DSM-IV criteria for cocaine dependence and past or current opioid dependence or abuse.

Cocaine use reduction with buprenorphine (CURB): rationale, design, and methodology.

BACKGROUND: Effective medications to treat cocaine dependence have not been identified. Recent pharmacotherapy trials demonstrate the potential efficacy of buprenorphine (BUP) (alone or with naltrexone) for reducing cocaine use. The National Institute on Drug Abuse Clinical Trials Network (CTN) launched the Cocaine Use Reduction with Buprenorphine (CURB) investigation to examine the safety and efficacy of sublingual BUP (as Suboxone®) in the presence of extended-release injectable naltrexone (XR-NTX, as Vivitrol®) for the treatment of cocaine dependence. This paper describes the design and rationale for this study. METHODS: This multi-site, double-blind, placebo-controlled study will randomize 300 participants across 11 sites. Participants must meet the DSM-IV criteria for cocaine dependence and past or current opioid dependence or abuse. Participants are inducted onto XR-NTX after self-reporting at least 7 days of abstinence from opioids and tolerating a naloxone challenge followed by oral naltrexone and are then randomly assigned to one of three medication conditions (4 mg BUP, 16 mg BUP, or placebo) for 8 weeks. Participants receive a second injection of XR-NTX 4 weeks after the initial injection, and follow-up visits are scheduled at 1 and 3 months post-treatment. Participants receive weekly cognitive behavioral therapy (CBT). Recruitment commenced in September, 2011. Enrollment, active medication, and follow-up phases are ongoing, and recruitment is exceeding targeted enrollment rates. CONCLUSIONS: This research using 2 medications will demonstrate whether BUP, administered in the presence of XR-NTX, reduces cocaine use in adults with cocaine dependence and opioid use disorders and will demonstrate if XR-NTX prevents development of physiologic dependence on BUP.

Prognostic model for survival in patients with metastatic renal cell carcinoma: results from the international kidney cancer working group.

PURPOSE: To develop a single validated model for survival in metastatic renal cell carcinoma (mRCC) using a comprehensive international database. EXPERIMENTAL DESIGN: A comprehensive database of 3,748 patients including previously reported clinical prognostic factors was established by pooling patient-level data from clinical trials. Following quality control and standardization, descriptive statistics were generated. Univariate analyses were conducted using proportional hazards models. Multivariable analysis using a log-logistic model stratified by center and multivariable fractional polynomials was conducted to identify independent predictors of survival. Missing data were handled using multiple imputation methods. Three risk groups were formed using the 25th and 75th percentiles of the resulting prognostic index. The model was validated using an independent data set of 645 patients treated with tyrosine kinase inhibitor (TKI) therapy. RESULTS: Median survival in the favorable, intermediate and poor risk groups was 26.9 months, 11.5 months, and 4.2 months, respectively. Factors contributing to the prognostic index included treatment, performance status, number of metastatic sites, time from diagnosis to treatment, and pretreatment hemoglobin, white blood count, lactate dehydrogenase, alkaline phosphatase, and serum calcium. The model showed good concordance when tested among patients treated with TKI therapy (C statistic = 0.741, 95% CI: 0.714-0.768). CONCLUSIONS: Nine clinical factors can be used to model survival in mRCC and form distinct prognostic groups. The model shows utility among patients treated in the TKI era.