Environmental tobacco smoke exposure, respiratory and cardiovascular health in restaurant and bar workers in Mexico

Environmental tobacco smoke (ETS) is a well established health hazard, being causally associated to lung cancer and cardiovascular disease. ETS regulations have been developed worldwide to reduce or eliminate exposure in most public places. Restaurants and bars constitute an exception. Restaurants and bar workers experience the highest ETS exposure levels across several occupations, with correspondingly increased health risks. In Mexico, previous exposure assessment in restaurants and bars showed concentrations in bars and restaurants to be the highest across different public and workplaces. Recently, Mexico developed at the federal level the General Law for Tobacco Control restricting indoors smoking to separated areas. AT the local level Mexico City developed the Law for the Protection of Non-smokers Health, completely banning smoking in restaurants and bars. Studies to assess ETS exposure in restaurants and bars, along with potential health effects were required to evaluate the impact of these legislative changes and to set a baseline measurement for future evaluations.^ A large cross-sectional study conducted in restaurants and bars from four Mexican cities was conducted from July to October 2008, to evaluate the following aims: Aim 1) Explore the potential impact of the Mexico City ban on ETS concentrations through comparison of Mexico City with other cities. Aim 2). Explore the association between ETS exposure, respiratory function indicators and respiratory symptoms. Aim 3). Explore the association between ETS exposure and blood pressure and heart rate.^ Three cities with no smoking ban were selected: Colima (11.5% smoking prevalence), Cuernavaca (21.5% smoking prevalence) and Toluca (27.8% smoking prevalence). Mexico City (27.9% smoking prevalence), the only city with a ban at the time of the study, was also selected. Restaurants and bars were randomly selected from municipal records. A goal of 26 restaurants and 26 bars per city was set, 50% of them under 100 m2. Each establishment was visited during the highest occupancy shift, and managers and workers answered to a questionnaire. Vapor-phase nicotine was measured using passive monitors, that were activated at the beginning and deactivated at the end of the shift. Also, workers participated at the beginning and end of the shift in a short physical evaluation, comprising the measurement of Forced Expiratory Volume in the first second (FEV1) and Peak Expiratory Flow (PEF), as well as blood pressure and heart rate.^ A total of 371 establishments were invited, 219 agreed to participate for a 60.1% participation rate. In them, 828 workers were invited, 633 agreed to participate for a 76% participation rate. Mexico City had at least 4 times less nicotine compared to any of the other cities. Differences between Mexico City and other cities were not explained by establishment characteristics, such as ventilation or air extraction. However, differences between cities disappeared when ban mechanisms, such as policy towards costumer's smoking, were considered in the models. An association between ETS exposure and respiratory symptoms (cough OR=1.27, 95%CI=1.04, 1.55) and respiratory illness (asthma OR=1.97, 95%CI=1.20, 3.24; respiratory illness OR=1.79, 95%CI=1.10, 2.94) was observed. No association between ETS and phlegm, wheezing or respiratory infections was observed. No association between ETS and any of the spirometric indicators was observed. An association between ETS exposure and increased systolic and diastolic blood pressure at the end of the shift was observed among non-smokers (systolic blood pressure beta=1.51, 95%CI=0.44, 2.58; diastolic blood pressure beta=1.50, 95%CI=0.72, 2.28). The opposite effect was observed in heavy smokers, were increased ETS exposure was associated with lower blood pressure at the end of the shift (systolic blood pressure beta=1.90, 95%CI=-3.57, -0.23; diastolic blood pressure beta=-1.46, 95%CI=-2.72, -0.02). No association in light smokers was observed. No association for heart rate was observed. ^ Results from this dissertation suggest Mexico City's smoking ban has had a larger impact on ETS exposure. Ventilation or air extraction, mechanisms of ETS control suggested frequently by tobacco companies to avoid smoking bans were not associated with ETS exposure. This dissertation suggests ETS exposure could be linked to changes in blood pressure and to increased respiratory symptoms. Evidence derived from this dissertation points to the potential negative health effects of ETS exposure in restaurants and bars, and provides support for the development of total smoking bans in this economic sector. ^

Bayesian adaptive designs for drug combinations in early phase clinical trials

Treating patients with combined agents is a growing trend in cancer clinical trials. Evaluating the synergism of multiple drugs is often the primary motivation for such drug-combination studies. Focusing on the drug combination study in the early phase clinical trials, our research is composed of three parts: (1) We conduct a comprehensive comparison of four dose-finding designs in the two-dimensional toxicity probability space and propose using the Bayesian model averaging method to overcome the arbitrariness of the model specification and enhance the robustness of the design; (2) Motivated by a recent drug-combination trial at MD Anderson Cancer Center with a continuous-dose standard of care agent and a discrete-dose investigational agent, we propose a two-stage Bayesian adaptive dose-finding design based on an extended continual reassessment method; (3) By combining phase I and phase II clinical trials, we propose an extension of a single agent dose-finding design. We model the time-to-event toxicity and efficacy to direct dose finding in two-dimensional drug-combination studies. We conduct extensive simulation studies to examine the operating characteristics of the aforementioned designs and demonstrate the designs' good performances in various practical scenarios.^

Bayesian Adaptive Designs for Early Phase Clinical Trials

My dissertation focuses mainly on Bayesian adaptive designs for phase I and phase II clinical trials. It includes three specific topics: (1) proposing a novel two-dimensional dose-finding algorithm for biological agents, (2) developing Bayesian adaptive screening designs to provide more efficient and ethical clinical trials, and (3) incorporating missing late-onset responses to make an early stopping decision. Treating patients with novel biological agents is becoming a leading trend in oncology. Unlike cytotoxic agents, for which toxicity and efficacy monotonically increase with dose, biological agents may exhibit non-monotonic patterns in their dose-response relationships. Using a trial with two biological agents as an example, we propose a phase I/II trial design to identify the biologically optimal dose combination (BODC), which is defined as the dose combination of the two agents with the highest efficacy and tolerable toxicity. A change-point model is used to reflect the fact that the dose-toxicity surface of the combinational agents may plateau at higher dose levels, and a flexible logistic model is proposed to accommodate the possible non-monotonic pattern for the dose-efficacy relationship. During the trial, we continuously update the posterior estimates of toxicity and efficacy and assign patients to the most appropriate dose combination. We propose a novel dose-finding algorithm to encourage sufficient exploration of untried dose combinations in the two-dimensional space. Extensive simulation studies show that the proposed design has desirable operating characteristics in identifying the BODC under various patterns of dose-toxicity and dose-efficacy relationships. Trials of combination therapies for the treatment of cancer are playing an increasingly important role in the battle against this disease. To more efficiently handle the large number of combination therapies that must be tested, we propose a novel Bayesian phase II adaptive screening design to simultaneously select among possible treatment combinations involving multiple agents. Our design is based on formulating the selection procedure as a Bayesian hypothesis testing problem in which the superiority of each treatment combination is equated to a single hypothesis. During the trial conduct, we use the current values of the posterior probabilities of all hypotheses to adaptively allocate patients to treatment combinations. Simulation studies show that the proposed design substantially outperforms the conventional multi-arm balanced factorial trial design. The proposed design yields a significantly higher probability for selecting the best treatment while at the same time allocating substantially more patients to efficacious treatments. The proposed design is most appropriate for the trials combining multiple agents and screening out the efficacious combination to be further investigated. The proposed Bayesian adaptive phase II screening design substantially outperformed the conventional complete factorial design. Our design allocates more patients to better treatments while at the same time providing higher power to identify the best treatment at the end of the trial. Phase II trial studies usually are single-arm trials which are conducted to test the efficacy of experimental agents and decide whether agents are promising to be sent to phase III trials. Interim monitoring is employed to stop the trial early for futility to avoid assigning unacceptable number of patients to inferior treatments. We propose a Bayesian single-arm phase II design with continuous monitoring for estimating the response rate of the experimental drug. To address the issue of late-onset responses, we use a piece-wise exponential model to estimate the hazard function of time to response data and handle the missing responses using the multiple imputation approach. We evaluate the operating characteristics of the proposed method through extensive simulation studies. We show that the proposed method reduces the total length of the trial duration and yields desirable operating characteristics for different physician-specified lower bounds of response rate with different true response rates.