Predicting nicotine metabolism across ancestries using genotypes.

BACKGROUND: There is a need to match characteristics of tobacco users with cessation treatments and risks of tobacco attributable diseases such as lung cancer. The rate in which the body metabolizes nicotine has proven an important predictor of these outcomes. Nicotine metabolism is primarily catalyzed by the enzyme cytochrone P450 (CYP2A6) and CYP2A6 activity can be measured as the ratio of two nicotine metabolites: trans-3'-hydroxycotinine to cotinine (NMR). Measurements of these metabolites are only possible in current tobacco users and vary by biofluid source, timing of collection, and protocols; unfortunately, this has limited their use in clinical practice. The NMR depends highly on genetic variation near CYP2A6 on chromosome 19 as well as ancestry, environmental, and other genetic factors. Thus, we aimed to develop prediction models of nicotine metabolism using genotypes and basic individual characteristics (age, gender, height, and weight). RESULTS: We identified four multiethnic studies with nicotine metabolites and DNA samples. We constructed a 263 marker panel from filtering genome-wide association scans of the NMR in each study. We then applied seven machine learning techniques to train models of nicotine metabolism on the largest and most ancestrally diverse dataset (N=2239). The models were then validated using the other three studies (total N=1415). Using cross-validation, we found the correlations between the observed and predicted NMR ranged from 0.69 to 0.97 depending on the model. When predictions were averaged in an ensemble model, the correlation was 0.81. The ensemble model generalizes well in the validation studies across ancestries, despite differences in the measurements of NMR between studies, with correlations of: 0.52 for African ancestry, 0.61 for Asian ancestry, and 0.46 for European ancestry. The most influential predictors of NMR identified in more than two models were rs56113850, rs11878604, and 21 other genetic variants near CYP2A6 as well as age and ancestry. CONCLUSIONS: We have developed an ensemble of seven models for predicting the NMR across ancestries from genotypes and age, gender and BMI. These models were validated using three datasets and associate with nicotine dosages. The knowledge of how an individual metabolizes nicotine could be used to help select the optimal path to reducing or quitting tobacco use, as well as, evaluating risks of tobacco use.

Multiethnic Prediction of Nicotine Biomarkers and Association With Nicotine Dependence.

INTRODUCTION: The nicotine metabolite ratio and nicotine equivalents are measures of metabolism rate and intake. Genome-wide prediction of these nicotine biomarkers in multiethnic samples will enable tobacco-related biomarker, behavioral, and exposure research in studies without measured biomarkers. AIMS AND METHODS: We screened genetic variants genome-wide using marginal scans and applied statistical learning algorithms on top-ranked genetic variants, age, ethnicity and sex, and, in additional modeling, cigarettes per day (CPD), (in additional modeling) to build prediction models for the urinary nicotine metabolite ratio (uNMR) and creatinine-standardized total nicotine equivalents (TNE) in 2239 current cigarette smokers in five ethnic groups. We predicted these nicotine biomarkers using model ensembles and evaluated external validity using dependence measures in 1864 treatment-seeking smokers in two ethnic groups. RESULTS: The genomic regions with the most selected and included variants for measured biomarkers were chr19q13.2 (uNMR, without and with CPD) and chr15q25.1 and chr10q25.3 (TNE, without and with CPD). We observed ensemble correlations between measured and predicted biomarker values for the uNMR and TNE without (with CPD) of 0.67 (0.68) and 0.65 (0.72) in the training sample. We observed inconsistency in penalized regression models of TNE (with CPD) with fewer variants at chr15q25.1 selected and included. In treatment-seeking smokers, predicted uNMR (without CPD) was significantly associated with CPD and predicted TNE (without CPD) with CPD, time-to-first-cigarette, and Fagerström total score. CONCLUSIONS: Nicotine metabolites, genome-wide data, and statistical learning approaches developed novel robust predictive models for urinary nicotine biomarkers in multiple ethnic groups. Predicted biomarker associations helped define genetically influenced components of nicotine dependence. IMPLICATIONS: We demonstrate development of robust models and multiethnic prediction of the uNMR and TNE using statistical and machine learning approaches. Variants included in trained models for nicotine biomarkers include top-ranked variants in multiethnic genome-wide studies of smoking behavior, nicotine metabolites, and related disease. Association of the two predicted nicotine biomarkers with Fagerström Test for Nicotine Dependence items supports models of nicotine biomarkers as predictors of physical dependence and nicotine exposure. Predicted nicotine biomarkers may facilitate tobacco-related disease and treatment research in samples with genomic data and limited nicotine metabolite or tobacco exposure data.

Effects of Buprenorphine Dose and Therapeutic Engagement on Illicit Opiate Use in Opioid Use Disorder Treatment Trials.

The impact of agonist dose and of physician, staff and patient engagement on treatment have not been evaluated together in an analysis of treatment for opioid use disorder. Our hypotheses were that greater agonist dose and therapeutic engagement would be associated with reduced illicit opiate use in a time-dependent manner. Publicly-available treatment data from six buprenorphine efficacy and safety trials from the Federally-supported Clinical Trials Network were used to derive treatment variables. Three novel predictors were constructed to capture the time weighted effects of buprenorphine dosage (mg buprenorphine per day), dosing protocol (whether physician could adjust dose), and clinic visits (whether patient attended clinic). We used time-in-trial as a predictor to account for the therapeutic benefits of treatment persistence. The outcome was illicit opiate use defined by self-report or urinalysis. Trial participants (N = 3022 patients with opioid dependence, mean age 36 years, 33% female, 14% Black, 16% Hispanic) were analyzed using a generalized linear mixed model. Treatment variables dose, Odds Ratio (OR) = 0.63 (95% Confidence Interval (95%CI) 0.59−0.67), dosing protocol, OR = 0.70 (95%CI 0.65−0.76), time-in-trial, OR = 0.75 (95%CI 0.71−0.80) and clinic visits, OR = 0.81 (95%CI 0.76−0.87) were significant (p-values < 0.001) protective factors. Treatment implications support higher doses of buprenorphine and greater engagement of patients with providers and clinic staff.

Biosignature Discovery for Substance Use Disorders Using Statistical Learning.

There are limited biomarkers for substance use disorders (SUDs). Traditional statistical approaches are identifying simple biomarkers in large samples, but clinical use cases are still being established. High-throughput clinical, imaging, and 'omic' technologies are generating data from SUD studies and may lead to more sophisticated and clinically useful models. However, analytic strategies suited for high-dimensional data are not regularly used. We review strategies for identifying biomarkers and biosignatures from high-dimensional data types. Focusing on penalized regression and Bayesian approaches, we address how to leverage evidence from existing studies and knowledge bases, using nicotine metabolism as an example. We posit that big data and machine learning approaches will considerably advance SUD biomarker discovery. However, translation to clinical practice, will require integrated scientific efforts.

Oral fingolimod for chronic inflammatory demyelinating polyradiculoneuropathy (FORCIDP Trial): a double-blind, multicentre, randomised controlled trial.

BACKGROUND: Fingolimod is approved for the treatment of relapsing-remitting multiple sclerosis and was effective in experimental autoimmune neuritis in rats, a possible model for chronic inflammatory demyelinating polyradiculoneuropathy (CIDP). We aimed to evaluate the efficacy of fingolimod in delaying disability progression in patients with CIDP who withdrew from currently effective treatments (intravenous immunoglobulin [IVIg] or corticosteroids). METHODS: This double-blind, multicentre, randomised, placebo-controlled, parallel-group, event-driven study was done at 48 neurology centres in Australia, Canada, Israel, Japan, the USA, and nine countries in Europe. Participants with CIDP who were receiving IVIg or corticosteroids were randomly assigned (1:1) to once-daily oral fingolimod 0·5 mg or placebo. Owing to the event-driven design, treatment duration was flexible and could be up to 4·5 years. Randomisation was done with an automated interactive voice response-web response system and was stratified by Inflammatory Neuropathy Cause and Treatment (INCAT) disability scale scores. Previous IVIg treatment was discontinued after one final course ending the day before the first dose of fingolimod or placebo was given, whereas corticosteroids were tapered off over 8 weeks after randomisation. The primary endpoint was time to first confirmed worsening (≥1 point increase on the adjusted INCAT disability scale score versus baseline) and was assessed in the full analysis set, which consisted of all patients who underwent randomisation and had at least one efficacy assessment for the primary analysis. The survival distribution functions of time to first worsening were estimated within each treatment group according to the Kaplan-Meier survival distribution function and compared with a stratified log-rank test. The trial is registered with ClinicalTrials.gov, number NCT01625182. FINDINGS: Of 106 participants randomly assigned between Jan 24, 2013, and March 10, 2016, 54 received fingolimod (41 who had been receiving IVIg and 13 who had been receiving corticosteroids) and 52 received placebo (41 who had been receiving IVIg and 11 who had been receiving corticosteroids). The trial ended for futility as recommended by an independent data monitoring committee after an interim analysis when 44 confirmed worsening events had occurred. At the end of the study, the survival estimate of the proportion of participants free from confirmed worsening was not significantly different between the fingolimod group (42%, 95% CI 23-60) and the placebo group (43%, 28-59; p=0·91). Adverse events occurred in 41 (76%) participants receiving fingolimod and 44 (85%) on placebo, and serious adverse events occurred in nine (17%) and four (8%) patients, respectively. The most common adverse events with fingolimod were headache (12 [22%] patients), hypertension (ten [19%]), and extremity pain (seven [13%]). Adverse events leading to study discontinuation occurred in seven (13%) participants on fingolimod and none on placebo. INTERPRETATION: Fingolimod 0·5 mg once-daily was not better than placebo for the treatment of CIDP. Future trial designs should take account of the possibility that if IVIg is stopped abruptly, some patients might relapse soon afterwards whereas others might remain in remission. FUNDING: Novartis Pharma.

The immediate and long-term effects of exercise and patient education on physical, functional, and quality-of-life outcome measures after single-level lumbar microdiscectomy: a randomized controlled trial protocol.

BACKGROUND: Low back pain remains a costly quality-of-life-related health problem. Microdiscectomy is often the surgical procedure of choice for a symptomatic, single-level, lumbar disc herniation in younger and middle-aged adults. The question of whether a post-microdiscectomy exercise program enhances function, quality of life, and disability status has not been systematically explored. Thus, the overall purpose of this study is to assess immediate and long-term outcomes of an exercise program, developed at University of Southern California (USC), targeting the trunk and lower extremities (USC Spine Exercise Program) for persons who have undergone a single-level microdiscectomy for the first time. METHODS/DESIGN: One hundred individuals between the ages of 18 and 60 who consent to undergo lumbar microdiscectomy will be recruited to participate in this study. Subjects will be randomly assigned to one of two groups: 1) one session of back care education, or 2) a back care education session followed by the 12-week USC Spine Exercise Program. The outcome examiners (evaluators), as well as the data managers, will be blinded to group allocation. Education will consist of a one-hour "one-on-one" session with the intervention therapist, guided by an educational booklet specifically designed for post-microdiscectomy care. This session will occur four to six weeks after surgery. The USC Spine Exercise Program consists of two parts: back extensor strength and endurance, and mat and upright therapeutic exercises. This exercise program is goal-oriented, performance-based, and periodized. It will begin two to three days after the education session, and will occur three times a week for 12 weeks. Primary outcome measures include the Oswestry Disability Questionnaire, Roland-Morris Disability Questionnaire, SF-36 quality of life assessment, Subjective Quality of Life Scale, 50-foot Walk, Repeated Sit-to-Stand, and a modified Sorensen test. The outcome measures in the study will be assessed before and after the 12-week post-surgical intervention program. Long-term follow up assessments will occur every six months beginning one year after surgery and ending five years after surgery. Immediate and long-term effects will be assessed using repeated measures multivariate analysis of variance (MANOVA). If significant interactions are found, one-way ANOVAs will be performed followed by post-hoc testing to determine statistically significant pairwise comparisons. DISCUSSION: We have presented the rationale and design for a randomized controlled trial evaluating the effectiveness of a treatment regimen for people who have undergone a single-level lumbar microdiscectomy.

Lead extraction in the contemporary setting: the LExICon study: an observational retrospective study of consecutive laser lead extractions.

OBJECTIVES: This study sought to examine the safety and efficacy of laser-assisted lead extraction and the indications, outcomes, and risk factors in a large series of consecutive patients. BACKGROUND: The need for lead extraction has been increasing in direct relationship to the increased numbers of cardiovascular implantable electronic devices. METHODS: Consecutive patients undergoing transvenous laser-assisted lead extraction at 13 centers were included. RESULTS: Between January 2004 and December 2007, 1,449 consecutive patients underwent laser-assisted lead extraction of 2,405 leads (20 to 270 procedures/site). Median implantation duration was 82.1 months (0.4 to 356.8 months). Leads were completely removed 96.5% of the time, with a 97.7% clinical success rate whereby clinical goals associated with the indication for lead removal were achieved. Failure to achieve clinical success was associated with body mass index <25 kg/m(2) and low extraction volume centers. Procedural failure was higher in leads implanted for >10 years and when performed in low volume centers. Major adverse events in 20 patients were directly related to the procedure (1.4%) including 4 deaths (0.28%). Major adverse effects were associated with patients with a body mass index <25 kg/m(2). Overall all-cause in-hospital mortality was 1.86%; 4.3% when associated with endocarditis, 7.9% when associated with endocarditis and diabetes, and 12.4% when associated with endocarditis and creatinine > or =2.0. Indicators of all-cause in-hospital mortality were pocket infections, device-related endocarditis, diabetes, and creatinine > or =2.0. CONCLUSIONS: Lead extraction employing laser sheaths is highly successful with a low procedural complication rate. Total mortality is substantially increased with pocket infections or device-related endocarditis, particularly in the setting of diabetes, renal insufficiency, or body mass index <25 kg/m(2). Centers with smaller case volumes tended to have a lower rate of successful extraction.

The physical therapy clinical research network (PTClinResNet): methods, efficacy, and benefits of a rehabilitation research network.

This article describes the vision, methods, and implementation strategies used in building the infrastructure for PTClinResNet, a clinical research network designed to assess outcomes for health-related mobility associated with evidence-based physical therapy interventions across and within four different disability groups. Specific aims were to (1) create the infrastructure necessary to develop and sustain clinical trials research in rehabilitation, (2) generate evidence to evaluate the efficacy of resistance exercise-based physical interventions designed to improve muscle performance and movement skills, and (3) provide education and training opportunities for present and future clinician-researchers and for the rehabilitation community at-large in its support of evidence-based practice. We present the network's infrastructure, development, and several examples that highlight the benefits of a clinical research network. We suggest that the network structure is ideal for building research capacity and fostering multisite, multiinvestigator clinical research projects designed to generate evidence for the efficacy of rehabilitation interventions.

Effect of highly active antiretroviral therapy on time to acquired immunodeficiency syndrome or death using marginal structural models.

To estimate the net (i.e., overall) effect of highly active antiretroviral therapy (HAART) on time to acquired immunodeficiency syndrome (AIDS) or death, the authors used inverse probability-of-treatment weighted estimation of a marginal structural model, which can appropriately adjust for time-varying confounders affected by prior treatment or exposure. Human immunodeficiency virus (HIV)-positive men and women (n = 1,498) were followed in two ongoing cohort studies between 1995 and 2002. Sixty-one percent (n = 918) of the participants initiated HAART during 6,763 person-years of follow-up, and 382 developed AIDS or died. Strong confounding by indication for HAART was apparent; the unadjusted hazard ratio for AIDS or death was 0.98. The hazard ratio from a standard time-dependent Cox model that included time-varying CD4 cell count, HIV RNA level, and other time-varying and fixed covariates as regressors was 0.81 (95% confidence interval: 0.61, 1.07). In contrast, the hazard ratio from a marginal structural survival model was 0.54 (robust 95% confidence interval: 0.38, 0.78), suggesting a clinically meaningful net benefit of HAART. Standard Cox analysis failed to detect a clear net benefit, because it does not appropriately adjust for time-dependent covariates, such as HIV RNA level and CD4 cell count, that are simultaneously confounders and intermediate variables.