Long- and short-term effects of fecal microbiota transplantation on antibiotic resistance genes: results from a randomized placebo-controlled trial.

In small series, third-party fecal microbiota transplantation (FMT) has been successful in decolonizing the gut from clinically relevant antibiotic resistance genes (ARGs). Less is known about the short- and long-term effects of FMT on larger panels of ARGs. We analyzed 226 pre- and post-treatment stool samples from a randomized placebo-controlled trial of FMT in 100 patients undergoing allogeneic hematopoietic cell transplantation or receiving anti-leukemia induction chemotherapy for 47 ARGs. These patients have heavy antibiotic exposure and a high incidence of colonization with multidrug-resistant organisms. Samples from each patient spanned a period of up to 9 months, allowing us to describe both short- and long-term effects of FMT on ARGs, while the randomized design allowed us to distinguish between spontaneous changes vs. FMT effect. We find an overall bimodal pattern. In the first phase (days to weeks after FMT), low-level transfer of ARGs largely associated with commensal healthy donor microbiota occurs. This phase is followed by long-term resistance to new ARGs as stable communities with colonization resistance are formed after FMT. The clinical implications of these findings are likely context-dependent and require further research. In the setting of cancer and intensive therapy, long-term ARG decolonization could translate into fewer downstream infections.

Association between psychosocial factors and co-morbid cigarette smoking and alcohol use in a population experiencing homelessness.

The prevalence of combustible cigarette smoking in populations experiencing homelessness in the United States is five times that of the general population. The psychosocial well-being of persons who smoke and experience homelessness is poorer if such persons also use alcohol heavily. The PTQ2 study was a randomized clinical trial among persons experiencing homelessness who were also current smokers and heavy alcohol consumers. Secondary data analysis of the PTQ2 baseline data was conducted to examine associations among psychosocial variables (anxiety, depression, hopelessness, social network size), heaviness of smoking (cigarettes/day) and alcohol consumption (drinking days/month), and duration and frequency of homelessness. Among the 420 participants, the majority were male (75%), black (70%) and non-Hispanic (94%) with a mean age of 46.6 years (SD = 11.6).  Bivariate analyses show that heaviness of smoking was positively correlated with social network size (r = 0.16, p = .001). Heaviness of drinking was positively correlated with the MINI anxiety score (r = 0.13, p = .009) and marijuana use (median total number of drinks in past 30 days among those who used marijuana in past 30 days vs. did not use: 50 vs. 24, p < .0001), and associated with frequency of homelessness (median total number of drinks in past 30 days among those experiencing homelessness once vs. >1 time: 30 vs. 44, p = .022). The findings highlight the psychosocial factors that warrant consideration when addressing heavy smoking and alcohol consumption in persons experiencing homelessness.

Potential of Fecal Microbiota Transplantation to Prevent Acute GVHD: Analysis from a Phase II Trial.

PURPOSE: Intestinal microbiota disruptions early after allogeneic hematopoietic cell transplantation have been associated with increased risk for acute GVHD (aGVHD). In our recent randomized phase II trial of oral, encapsulated, third-party fecal microbiota transplantation (FMT) versus placebo, FMT at the time of neutrophil recovery was safe and ameliorated dysbiosis. Here, we evaluated in post hoc analysis whether donor microbiota engraftment after FMT may protect against aGVHD. EXPERIMENTAL DESIGN: We analyzed pre- and post-FMT stool samples and estimated donor microbiota engraftment (a preplanned secondary endpoint) by determining the fraction of post-FMT microbiota formed by unique donor taxa (donor microbiota fraction; dMf). RESULTS: dMf was higher in patients who later developed grade I or no aGVHD (median 33.9%; range, 1.6%-74.3%) than those who developed grade II-IV aGVHD (median 25.3%; range, 2.2%-34.8%; P = 0.006). The cumulative incidence of grade II-IV aGVHD by day 180 was lower in the group with greater-than-median dMf than the group with less-than-median dMf [14.3% (95% confidence interval, CI, 2.1-37.5) vs. 76.9% (95% CI, 39.7-92.8), P = 0.008]. The only determinant of dMf in cross-validated least absolute shrinkage and selection operator (LASSO)-regularized regression was the patient's pre-FMT microbiota diversity (Pearson correlation coefficient -0.82, P = 1.6 × 10-9), indicating more potent microbiota modulation by FMT in patients with more severe dysbiosis. Microbiota network analysis revealed major rewiring including changes in the most central nodes, without emergence of keystone species, as a potential mechanism of FMT effect. CONCLUSIONS: FMT may have protective effects against aGVHD, especially in patients with more severe microbiota disruptions.

Randomized Double-Blind Phase II Trial of Fecal Microbiota Transplantation Versus Placebo in Allogeneic Hematopoietic Cell Transplantation and AML.

PURPOSE: Gut microbiota injury in allogeneic hematopoietic cell transplantation (HCT) recipients and patients with AML has been associated with adverse clinical outcomes. Previous studies in these patients have shown improvements in various microbiome indices after fecal microbiota transplantation (FMT). However, whether microbiome improvements translate into improved clinical outcomes remains unclear. We examined this question in a randomized, double-blind, placebo-controlled phase II trial. METHODS: Two independent cohorts of allogeneic HCT recipients and patients with AML receiving induction chemotherapy were randomly assigned in a 2:1 ratio to receive standardized oral encapsulated FMT versus placebo upon neutrophil recovery. After each course of antibacterial antibiotics, patients received a study treatment. Up to three treatments were administered within 3 months. The primary end point was 4-month all-cause infection rate. Patients were followed for 9 months. RESULTS: In the HCT cohort (74 patients), 4-month infection density was 0.74 and 0.91 events per 100 patient-days in FMT and placebo arms, respectively (infection rate ratio, 0.83; 95% CI, 0.48 to 1.42; P = .49). In the AML cohort (26 patients), 4-month infection density was 0.93 in the FMT arm and 1.25 in the placebo arm, with an infection rate ratio of 0.74 (95% CI, 0.32 to 1.71; P = .48). Unique donor bacterial sequences comprised 25%-30% of the fecal microbiota after FMT. FMT improved postantibiotic recovery of microbiota diversity, restored several depleted obligate anaerobic commensals, and reduced the abundance of expanded genera Enterococcus, Streptococcus, Veillonella, and Dialister. CONCLUSION: In allogeneic HCT recipients and patients with AML, third-party FMT was safe and ameliorated intestinal dysbiosis, but did not decrease infections. Novel findings from this trial will inform future development of FMT trials.

Inhibition of lung adenocarcinoma by combinations of sulfasalazine (SAS) and disulfiram-copper (DSF-Cu) in cell line models and mice.

Sulfasalazine (SAS) is a repurposed antitumor drug which inhibits the proliferation and survival of cancer cells by inhibiting the xCT cellular antioxidant system. Recent clinical studies have shown that, due to poor bioavailability, the antitumor effects of SAS monotherapy are minimal. Therefore, we hypothesized that DSF, another repurposed drug that has demonstrated anticancer effects, or its complex with copper (DSF-copper, DSF-Cu) could potentiate the antilung cancer effects of SAS. Exposure of non-small cell lung cancer cells to therapeutically achievable concentrations of SAS-induced low-to-moderate cytotoxic effects (20-40% reduction in cell viability) and, unexpectedly, induced the antioxidant protein NRF2 and its downstream effectors xCT and ALDH1A1. However, combinations of SAS and DSF-Cu, but not SAS and DSF, induced a significantly higher cytotoxic effect (64-88% reduction in cell viability), apoptosis and generation of mitochondrial reactive oxygen species as compared with SAS or DSF-Cu alone. Moreover, DSF-Cu abrogated SAS-induced NRF2, xCT and ALDH1A1 expression. In a mouse model of lung tumor, SAS + DSF-Cu showed a higher efficacy than the individual drugs in reducing the number and size of tumors as well as the incidence and multiplicity of lung adenocarcinoma. Taken together, our findings indicate that the observed antilung cancer effects of SAS plus DSF-Cu are mediated, at least in part, via impairment of reactive oxygen species defense and -enhancement of oxidative stress and provide evidence for the preventive/therapeutic potential of this combinatorial approach against lung cancer.

A UVR-sensor wearable device intervention to reduce sun exposure in melanoma survivors: Results from a randomized controlled trial.

BACKGROUND: Melanoma survivors are at increased risk of developing a second primary melanoma; however, some report sub-optimal sun behaviors and sunburns. We tested the effectiveness of a wearable device with ultraviolet radiation (UVR)-sensing technology to improve sun behaviors and reduce sunburns in cutaneous melanoma survivors. MATERIALS AND METHODS: We conducted a randomized controlled trial using Shade 2, a commercially available wrist device that measures UVR. The intervention group received the device and mobile application notifications about their exposure and prompts to use sunscreen. The control group received the device and a separate research mobile application without information about their exposure or notifications. Participants wore the device for 12 weeks and self-reported sun behaviors before, during, and after the intervention. The primary outcome was a composite score of sun protection behaviors at week 12. RESULTS: 386 participants were randomized (186 control, 182 intervention). Most were female and 5+ years past their first melanoma diagnosis. The average age was 56 years. Most (93%) completed the study, though 40% experienced device issues. No meaningful differences were observed in self-reported sun protection behaviors at week 12 (controls 3.0±0.5 vs. intervention 2.9±0.5, p = 0.06), any sunburn during the intervention period (controls 14.4% vs. intervention 12.7%, p = 0.75), or average daily objective UVR exposure (controls median 87 vs. intervention 83 J/m2, p = 0.43). CONCLUSION: Wearing a device that measured and alerted melanoma survivors to UVR exposure did not result in different sun behaviors, exposure, or sunburns relative to controls. The technology needs refinement before further attempts to assess the effectiveness of self-monitoring UVR exposure. CLINICAL TRIALS REGISTRATION: NCT03927742.

Switching to cigarette brand variants with different filter ventilation levels: a descriptive analysis.

BACKGROUND: Regulation of filter ventilation (FV) has been proposed to reduce misperceptions that ventilation reduces the health risks of smoking. We describe smoking behaviour and exposure after switching to a cigarette brand variant (CBV) with a different FV level. METHODS: Wave 1 (2013-2014) of the Population Assessment of Tobacco Use and Health Study was merged with FV levels of participants' CBV and restricted to adults with a usual CBV, smoked daily and included in wave 4 (2016-2017; n=371). Generalised estimation equations method modelled changes in FV and cigarettes per day (CPD), quit interest, total nicotine equivalents (TNE) and total NNAL (biomarker of a tobacco-specific carcinogen). FV change was defined as a change in CBV resulting in a ≥20% increase or decrease in FV. Secondary analyses used FV change based on an increase from <5% to >10% or a decrease from >10% to <5%. RESULTS: A non-significant pattern indicating an increase of 0.97 and 0.49 CPD was observed among those who switched to a CBV and increased FV by ≥20% and from <5% to >10%, respectively. A non-significant pattern indicating a decrease of 1.31 and 1.97 CPD was observed among those who decreased FV by ≥20% and from >10% to <5%, respectively. Changes in quit interest and biomarkers were also non-significant with one exception: greater reduction in TNE among those who decreased from >10% to <5% FV versus no change (-8.51 vs -0.25 nmol/mg creatinine; p=0.0447). CONCLUSIONS: Switching to CBV with lower FV does not appear to increase exposure and may even reduce exposure for some. Additional investigations are recommended to confirm these descriptive findings.

Increased Levels of the Acrolein Metabolite 3-Hydroxypropyl Mercapturic Acid in the Urine of e-Cigarette Users.

Carcinogen and toxicant uptake by e-cigarette users have not been fully evaluated. In the study reported here, we recruited 30 e-cigarette users, 63 nonsmokers, and 33 cigarette smokers who gave monthly urine samples over a period of 4-6 months. Their product use status was confirmed by measurements of exhaled CO, urinary total nicotine equivalents, cyanoethyl mercapturic acid (CEMA), and total 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol. Urinary biomarkers of exposure to the carcinogens acrolein (3-hydroxypropyl mercapturic acid, 3-HPMA), benzene (S-phenyl mercapturic acid, SPMA), acrylonitrile (CEMA), and a combination of crotonaldehyde, methyl vinyl ketone, and methacrolein (3-hydroxy-1-methylpropyl mercapturic acid, HMPMA) were quantified at each visit. Data from subject visits with CEMA > 27 pmol/mL were excluded from the statistical analysis of the results because of possible unreported exposures to volatile combustion products such as secondhand cigarette smoke or marijuana smoke exposure; this left 22 e-cigarette users with 4 or more monthly visits and all 63 nonsmokers. Geometric mean levels of 3-HPMA (1249 versus 679.3 pmol/mL urine) were significantly higher (P = 0.003) in e-cigarette users than in nonsmokers, whereas levels of SPMA, CEMA, and HMPMA did not differ between these two groups. All analytes were significantly higher in cigarette smokers than in either e-cigarette users or nonsmokers. The results of this unique multimonth longitudinal study demonstrate consistent significantly higher uptake of the carcinogen acrolein in e-cigarette users versus nonsmokers, presenting a warning signal regarding e-cigarette use.

Risk perceptions and continued smoking as a function of cigarette filter ventilation level among US youth and young adults who smoke.

BACKGROUND: While evidence demonstrates that the industry's marketing of cigarettes with higher filter ventilation (FV) misleads adults about their health risks, there is no research on the relationships between FV, risk perceptions and smoking trajectories among youth (ages 12-17) and young adults (ages 18-24). METHODS: Data on FV levels of major US cigarette brands/sub-brands were merged with the Population Assessment of Tobacco and Health Study to examine whether FV level in cigarettes used by wave 1 youth/young adults (n=1970) predicted continued smoking at waves 2-4, and whether those relationships were mediated by perceived risk of their cigarette brand. FV was modelled based on tertiles (0.2%-11.8%, low; 11.9%-23.2%, moderate; 23.3%-61.1%, high) to predict daily smoking, past 30-day smoking and change in number of days smoking at successive waves. RESULTS: The odds of perceiving one's brand as less harmful than other cigarette brands was 2.21 times higher in the high versus low FV group (p=0.0146). Relationships between FV and smoking outcomes at successive waves were non-significant (all p>0.05). CONCLUSION: Youth and young adults who use higher FV cigarettes perceived their brand as less harmful compared with other brands. However, level of FV was not associated with continued smoking.

Cigarette filter ventilation, smoking topography, and subjective effects: A mediational analysis.

BACKGROUND: Filter ventilation in cigarettes has been associated with alterations in smoking topography in order to compensate for the lower nicotine yields. Subjective effects of cigarettes include sensations, which can be affected by how a person smokes a cigarette. We look at smoking topography as a mediator in the relationship between filter ventilation levels and subjective effects. METHODS: Smoking topography and subjective effects data come from the baseline usual cigarette brand laboratory visits of participants (N = 607) in a randomized clinical trial on reduced nicotine cigarettes. Conditional process analysis was done using PROCESS macro version 3.5 in SPSS. RESULTS: There was a positive indirect effect of ventilation on satisfaction through total puff volume (0.004, 95% CI: 0.002, 0.007]) as well as ventilation on satisfaction through puff count then total puff volume, sequentially (0.001, 95% CI: [0.000, 0.003]). There was a positive indirect effect of ventilation on enjoyment through puff count for individuals less than 43 years of age (0.01, 95% CI: [0.002, 0.013]). There was a positive indirect effect of ventilation on enjoyment through total puff volume for individuals who smoke less than 14.33 cigarettes per day (0.009, 95% CI: [0.004, 0.015]). CONCLUSIONS: We found preliminary evidence that topography measures (puff count and total puff volume), mediate the relationship between filter ventilation and specific subjective effects of smoking (satisfaction and enjoyment). Age and cigarettes smoked per day moderated these relationships. These results could have implications regarding filter ventilation restrictions and smokers' perceptions of using such cigarettes.

Smoking abstinence and cessation-related outcomes one month after an immediate versus gradual reduction in nicotine content of cigarettes.

The United States Food and Drug Administration has the authority to reduce the nicotine content in cigarettes to minimal or non-addictive levels and could do so immediately or gradually over time. A large clinical trial compared the two approaches. This secondary analysis assesses abstinence and cessation-related outcomes one month after the trial concluded, when participants no longer had access to very low nicotine content (VLNC) research cigarettes. Smokers not interested in quitting (N = 1250) were recruited for the parent trial from 2014 to 2016 across 10 sites throughout the US and randomized to a 20-week study period during which they immediately switched to VLNC cigarettes, gradually transitioned to VLNC cigarettes with five monthly dose reductions, or smoked normal nicotine research cigarettes (control). At the one-month follow-up, both immediate and gradual reduction resulted in greater mean cigarette-free days (4.7 and 4.6 respectively) than the control group (3.2, both p < .05). Immediate reduction resulted in fewer mean cigarettes per day (CPD = 10.3) and lower Fagerström Test for Cigarette Dependence (FTCD = 3.7) than the gradual (CPD = 11.7, p = .001; FTCD = 3.8, p = .039) and control (CPD = 13.5, p < .001; FTCD = 4.0, p < .001) groups. Compared to controls, gradual reduction resulted in reduced CPD (p = .012) but not FTCD (p = .13). Differences in CO-verified 7-day point-prevalence abstinence were not significant. Findings demonstrate that switching to VLNC cigarettes resulted in reduced smoking and nicotine dependence severity that was sustained for at least a month after the VLNC trial period in smokers who were not interested in cessation. The greatest harm reduction endpoints were observed in those who immediately transitioned to VLNC cigarettes.

The implementation of a smoking cessation and alcohol abstinence intervention for people experiencing homelessness.

BACKGROUND: In the United States, eighty percent of the adult homeless population smokes cigarettes compared to 15 percent of the general population. In 2017 Power to Quit 2 (PTQ2), a randomized clinical trial, was implemented in two urban homeless shelters in the Upper Midwest to address concurrent smoking cessation and alcohol treatment among people experiencing homelessness. A subset of this study population were interviewed to assess their experiences of study intervention. The objective of this study was to use participants' experiences with the intervention to inform future implementation efforts of combined smoking cessation and alcohol abstinence interventions, guided by the Consolidated Framework for Implementation Research (CFIR). METHODS: Qualitative semi-structured interviews were conducted with 40 PTQ2 participants between 2016-2017 and analyzed in 2019. Interviews were audio-recorded, transcribed, and analyzed using a socially constructivist approach to grounded theory. RESULTS: Participants described the PTQ2 intervention in positive terms. Participants valued the opportunity to obtain both counseling and nicotine-replacement therapy products (intervention characteristics) and described forming a bond with the PTQ2 staff and reliance on them for emotional support and encouragement (characteristics of individuals). However, the culture of alcohol use and cigarette smoking around the shelter environment presented a serious challenge (outer setting). The study setting and the multiple competing needs of participants were reported as the most challenging barriers to implementation (implementation process). CONCLUSION: There are unique challenges in addressing smoking cessation with people experiencing homelessness. For those in shelters there can be the difficulty of pro-smoking norms in and around the shelter itself. Considering pairing cessation with policy level interventions targeting smoke-free spaces, or pairing cessation with housing support efforts may be worthwhile.. Participants described a discord in their personal goals of reduction compared with the study goals of complete abstinence, which may pose a challenge to the ways in which success is defined for people experiencing homelessness. TRIAL REGISTRATION: Clinicaltrials.gov, NCT01932996 , registered 08/30/2013.

BivRec: an R package for the nonparametric and semiparametric analysis of bivariate alternating recurrent events.

BACKGROUND: Bivariate alternating recurrent event data can arise in longitudinal studies where patients with chronic diseases go through two states that occur repeatedly, e.g., care periods and break periods. However, there was no statistical software that provided tools for the analysis of such data. To meet this software need, we developed BivRec, a package for R that contains a set of tools for exploratory, nonparametric and semiparametric regression analysis of bivariate alternating recurrent events. RESULTS: The BivRec package provides functions for nonparametric estimations for the joint distribution of bivariate gap times (bivrecNP) and semiparametric regression methods for evaluating covariate effects on the two types of gap times under the accelerated failure time model framework (bivrecReg). The package also provides exploratory data analysis tools such as a visualization of the gap times by groups. We utilize a subset of the South Verona Psychiatric Case Register (PCR) data to illustrate the use of the BivRec package for the reviewed methods. CONCLUSIONS: We demonstrate BivRec's capability for data visualization, nonparametric and regression based analysis, as well as data simulation. The package has default methods with satisfactory performance despite the complexity of calculations and fills a gap in software for statistical analysis of bivariate alternating recurrent events. BivRec is accessible under the GPL-3 General Public License through CRAN, facilitating its installation.

A Bayesian hierarchical model for individual participant data meta-analysis of demand curves.

Individual participant data meta-analysis is a frequently used method to combine and contrast data from multiple independent studies. Bayesian hierarchical models are increasingly used to appropriately take into account potential heterogeneity between studies. In this paper, we propose a Bayesian hierarchical model for individual participant data generated from the Cigarette Purchase Task (CPT). Data from the CPT details how demand for cigarettes varies as a function of price, which is usually described as an exponential demand curve. As opposed to the conventional random-effects meta-analysis methods, Bayesian hierarchical models are able to estimate both the study-specific and population-level parameters simultaneously without relying on the normality assumptions. We applied the proposed model to a meta-analysis with baseline CPT data from six studies and compared the results from the proposed model and a two-step conventional random-effects meta-analysis approach. We conducted extensive simulation studies to investigate the performance of the proposed approach and discussed the benefits of using the Bayesian hierarchical model for individual participant data meta-analysis of demand curves.

Two-sample survival probability curves: A graphical approach for the analysis of time to event data in clinical trials.

With the aim to improve the communication of trial results, we introduce a novel graphical approach that complements the analysis of time to event outcomes in two-arm randomized trials. We define the so-called two-sample survival probability curve and propose a nonparametric estimator of the curve based on a random walk using Kaplan-Meier survival estimates for the two arms. We then use the estimated curve to visualize treatment effect as well as potential effect modification of factors of interest. We also propose to estimate two-sample survival probability curves within the framework of the Cox model to graphically assess model fit. The proposed two-sample survival probability plot puts trials in a standardized [0,1] × [0,1] space, allowing for a simple visualization of the main effect, effect modification, and the adequacy of a model fit.

Does the institutional environment influence corporate social responsibility? Consideration of green investment of enterprises-evidence from China.

Green investment, as a socially responsible investment, conforms to the concept of ecological civilization. It is considerable to promote enterprises to make green investment. This article is based on 211 questionnaires for employees of various enterprises in China, using STATA.14 for descriptive statistical analysis, logistical regression analysis, and trend analysis. It aims to explore the impact of government-led institutional environment on enterprises from five aspects. This study examines that the institutional environment has a positive effect on enterprise' green investment from the legal and cultural aspects, but it has no significant impact from the political, economic, and financial aspects. Finally, this paper provides policy advice that can promote the construction of institutional environment to encourage enterprises to make green investment.

Cigarette Smokers Versus Cannabis Smokers Versus Co-users of Cigarettes and Cannabis: A Pilot Study Examining Exposure to Toxicants.

INTRODUCTION: Studies suggest tobacco and cannabis co-users may experience greater toxicant exposure than exclusive cigarette (ET) smokers. No study has systematically tested differences in toxicant exposure among co-users, exclusive cannabis (ECa) smokers, and ET smokers. AIMS AND METHODS: Adult daily cigarette smokers and/or weekly cannabis smokers completed two laboratory visits. Co-users (n = 19) tested positive for urinary 11-nor-9-carboxy-Δ 9-tetrahydrocannabinol (THCCOOH), self-reported cannabis use ≥1 per week, and smoked ≥5 cigarettes per day (CPD). ET smokers (n = 18) denied past month cannabis use, tested negative for urinary THCCOOH and smoked ≥5 CPD. ECa smokers (n = 16) tested positive for urinary THCCOOH, self-reported cannabis use ≥1 per week, and denied past month tobacco use (NicAlert <3). Self-reported tobacco and cannabis use were collected at both visits. First morning urinary tobacco and combustion-related biomarkers of exposure were compared following a cannabis or tobacco smoking session (visit 2). RESULTS: Co-users and ET smokers had higher levels of exhaled carbon monoxide, total nicotine equivalents, metabolites of 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNAL), and all four measured mercapturic acids (measures of volatile organic compounds) than ECa smokers (ps < .005). ET smokers (geometric mean = 7220.2 pmol/mg) had higher levels of 2-hydroxypropylmercapturic acid than co-users (geometric mean = 5348.7 adjusted p = .009). Phenanthrene tetraol did not differ by group (p > .05). CONCLUSIONS: Co-users and ET smokers demonstrated comparable levels of biomarkers of exposure to harmful constituents despite smoking similar amounts of tobacco. ECa smokers demonstrated lower levels of toxicant exposure for most biomarkers. IMPLICATIONS: Although ECa smokers are exposed to significantly lower levels of harmful constituents compared with co-users and exclusive cigarette smokers, this group is still exposed to higher levels of toxicants than observed in studies of nonsmokers. Additionally, these three groups were exposed to similar levels of phenanthrene tetraol. It is important to account for cannabis use in studies examining biomarkers of exposure among cigarette smokers. Additionally, further research is needed examining exposure to harmful chemicals among various types of cannabis and tobacco users.

Nonparametric estimation in an illness-death model with component-wise censoring.

In disease settings where study participants are at risk for death and a serious nonfatal event, composite endpoints defined as the time until the earliest of death or the nonfatal event are often used as the primary endpoint in clinical trials. In practice, if the nonfatal event can only be detected at clinic visits and the death time is known exactly, the resulting composite endpoint exhibits "component-wise censoring." The standard method used to estimate event-free survival in this setting fails to account for component-wise censoring. We apply a kernel smoothing method previously proposed for a marker process in a novel way to produce a nonparametric estimator for event-free survival that accounts for component-wise censoring. The key insight that allows us to apply this kernel method is thinking of nonfatal event status as an intermittently observed binary time-dependent variable rather than thinking of time to the nonfatal event as interval-censored. We also propose estimators for the probability in state and restricted mean time in state for reversible or irreversible illness-death models, under component-wise censoring, and derive their large-sample properties. We perform a simulation study to compare our method to existing multistate survival methods and apply the methods on data from a large randomized trial studying a multifactor intervention for reducing morbidity and mortality among men at above average risk of coronary heart disease.

Additive rates model for recurrent event data with intermittently observed time-dependent covariates.

Various regression methods have been proposed for analyzing recurrent event data. Among them, the semiparametric additive rates model is particularly appealing because the regression coefficients quantify the absolute difference in the occurrence rate of the recurrent events between different groups. Estimation of the additive rates model requires the values of time-dependent covariates being observed throughout the entire follow-up period. In practice, however, the time-dependent covariates are usually only measured at intermittent follow-up visits. In this paper, we propose to kernel smooth functions involving time-dependent covariates across subjects in the estimating function, as opposed to imputing individual covariate trajectories. Simulation studies show that the proposed method outperforms simple imputation methods. The proposed method is illustrated with data from an epidemiologic study of the effect of streptococcal infections on recurrent pharyngitis episodes.

A mixed effects model for analyzing area under the curve of longitudinally measured biomarkers with missing data.

A simple approach for analyzing longitudinally measured biomarkers is to calculate summary measures such as the area under the curve (AUC) for each individual and then compare the mean AUC between treatment groups using methods such as t test. This two-step approach is difficult to implement when there are missing data since the AUC cannot be directly calculated for individuals with missing measurements. Simple methods for dealing with missing data include the complete case analysis and imputation. A recent study showed that the estimated mean AUC difference between treatment groups based on the linear mixed model (LMM), rather than on individually calculated AUCs by simple imputation, has negligible bias under random missing assumptions and only small bias when missing is not at random. However, this model assumes the outcome to be normally distributed, which is often violated in biomarker data. In this paper, we propose to use a LMM on log-transformed biomarkers, based on which statistical inference for the ratio, rather than difference, of AUC between treatment groups is provided. The proposed method can not only handle the potential baseline imbalance in a randomized trail but also circumvent the estimation of the nuisance variance parameters in the log-normal model. The proposed model is applied to a recently completed large randomized trial studying the effect of nicotine reduction on biomarker exposure of smokers.