Analysis of Occupational Asbestos Exposure and Lung Cancer Mortality Using the G Formula

We employed the parametric G formula to analyze lung cancer mortality in a cohort of textile manufacturing workers who were occupationally exposed to asbestos in South Carolina. A total of 3,002 adults with a median age of 24 years at enrollment (58% male, 81% Caucasian) were followed for 117,471 person-years between 1940 and 2001, and 195 lung cancer deaths were observed. Chrysotile asbestos exposure was measured in fiber-years per milliliter of air, and annual occupational exposures were estimated on the basis of detailed work histories. Sixteen percent of person-years involved exposure to asbestos, with a median exposure of 3.30 fiber-years/mL among those exposed. Lung cancer mortality by age 90 years under the observed asbestos exposure was 9.44%. In comparison with observed asbestos exposure, if the facility had operated under the current Occupational Safety and Health Administration asbestos exposure standard of <0.1 fibers/mL, we estimate that the cohort would have experienced 24% less lung cancer mortality by age 90 years (mortality ratio = 0.76, 95% confidence interval: 0.62, 0.94). A further reduction in asbestos exposure to a standard of <0.05 fibers/mL was estimated to have resulted in a minimal additional reduction in lung cancer mortality by age 90 years (mortality ratio = 0.75, 95% confidence interval: 0.61, 0.92)

A Comparison of Methods to Estimate the Hazard Ratio Under Conditions of Time-varying Confounding and Nonpositivity

In occupational epidemiologic studies, the healthy-worker survivor effect refers to a process that leads to bias in the estimates of an association between cumulative exposure and a health outcome. In these settings, work status acts both as an intermediate and confounding variable, and may violate the positivity assumption (the presence of exposed and unexposed observations in all strata of the confounder). Using Monte Carlo simulation, we assess the degree to which crude, work-status adjusted, and weighted (marginal structural) Cox proportional hazards models are biased in the presence of time-varying confounding and nonpositivity. We simulate data representing time-varying occupational exposure, work status, and mortality. Bias, coverage, and root mean squared error (MSE) were calculated relative to the true marginal exposure effect in a range of scenarios. For a base-case scenario, using crude, adjusted, and weighted Cox models, respectively, the hazard ratio was biased downward 19%, 9%, and 6%; 95% confidence interval coverage was 48%, 85%, and 91%; and root MSE was 0.20, 0.13, and 0.11. Although marginal structural models were less biased in most scenarios studied, neither standard nor marginal structural Cox proportional hazards models fully resolve the bias encountered under conditions of time-varying confounding and nonpositivity

Estimating the Effect of Cumulative Occupational Asbestos Exposure on Time to Lung Cancer Mortality: Using Structural Nested Failure-Time Models to Account for Healthy-Worker Survivor Bias

BACKGROUND: Previous estimates of the effect of occupational asbestos on lung cancer mortality have been obtained by using methods that are subject to the healthy-worker survivor bias. G-estimation of a structural nested model provides consistent exposure effect estimates under this bias. METHODS: We estimated the effect of cumulative asbestos exposure on lung cancer mortality in a cohort comprising 2564 textile factory workers who were followed from January 1940 to December 2001. RESULTS: At entry, median age was 23 years, with 42% of the cohort being women and 20% nonwhite. During the follow-up period, 15% of person-years were classified as occurring while employed and 13% as occupationally exposed to asbestos. For a 100 fiber-year/ml increase in cumulative asbestos, a Weibull model adjusting for sex, race, birth year, baseline exposure, and age at study entry yielded a survival time ratio of 0.88 (95% confidence interval = 0.83 to 0.93). Further adjustment for work status yielded no practical change. The corresponding survival time ratio obtained using g-estimation of a structural nested model was 0.57 (0.33 to 0.96). CONCLUSIONS: Accounting for the healthy-worker survivor bias resulted in a 35% stronger effect estimate. However, this estimate was considerably less precise. When healthy-worker survivor bias is suspected, methods that account for it should be used

The Parametric g-Formula for Time-to-event Data: Intuition and a Worked Example

The parametric g-formula can be used to estimate the effect of a policy, intervention, or treatment. Unlike standard regression approaches, the parametric g-formula can be used to adjust for time-varying confounders that are affected by prior exposures. To date, there are few published examples in which the method has been applied

Assessing the component associations of the healthy worker survivor bias: occupational asbestos exposure and lung cancer mortality

The healthy worker survivor bias is well-recognized in occupational epidemiology. Three component associations are necessary for this bias to occur: i) prior exposure and employment status; ii) employment status and subsequent exposure; and iii) employment status and mortality. Together, these associations result in time-varying confounding affected by prior exposure. We illustrate how these associations can be assessed using standard regression methods

Multicenter prevalence of anaphylaxis in clinic-based oral food challenges

Background Although previous single-center studies report the rate of anaphylaxis for oral food challenges (OFCs) as 9% to 11%, little is known regarding the epidemiology of clinical OFCs across multiple centers in the United States. Objective To examine the epidemiology, symptoms, and treatment of clinical low-risk OFCs in the nonresearch setting. Methods Data were obtained from 2008 to 2013 through a physician survey in 5 food allergy centers geographically distributed across the United States. Allergic reaction rates and the association of reaction rates with year, hospital, and demographics were determined using a linear mixed model. Meta-analysis was used to pool the proportion of reactions and anaphylaxis with inverse-variance weights using a random-effects model with exact confidence intervals (CIs). Results A total of 6,377 OFCs were performed, and the pooled estimate of anaphylaxis was 2% (95% CI, 1%-3%). The rate of allergic reactions was 14% (95% CI, 13%-16%) and was consistent during the study period (P = .40). Reaction rates ranged from 13% to 33%. Males reacted 16% more frequently than females (95% CI, 4%-37.5%; P = .04). Foods challenged in 2013 varied geographically, with peanut as the most challenged food in the Northeast, Midwest, and West and egg as the most challenged in the South. Conclusion As the largest national survey of allergic reactions of clinical open OFCs in a nonresearch setting in the United States, this study found that performing clinical nonresearch open low-risk OFCs results in few allergic reactions, with 86% of challenges resulting in no reactions and 98% without anaphylaxis

Methicillin-Susceptible Staphylococcus aureus as a Predominantly Healthcare-Associated Pathogen: A Possible Reversal of Roles?

Methicillin-resistant Staphylococcus aureus (MRSA) strains have become common causes of skin and soft tissue infections (SSTI) among previously healthy people, a role of methicillin-susceptible (MSSA) isolates before the mid-1990s. We hypothesized that, as MRSA infections became more common among S. aureus infections in the community, perhaps MSSA infections had become more important as a cause of healthcare-associated infection.We compared patients, including children and adults, with MRSA and MSSA infections at the University of Chicago Medical Center (UCMC) from all clinical units from July 1, 2004-June 30, 2005; we also compared the genotypes of the MRSA and MSSA infecting bacterial strains.Compared with MRSA patients, MSSA patients were more likely on bivariate analysis to have bacteremia, endocarditis, or sepsis (p = 0.03), to be an adult (p = 0.005), to be in the intensive care unit (21.9% vs. 15.6%) or another inpatient unit (45.6% vs. 40.7%) at the time of culture. MRSA (346/545) and MSSA (76/114) patients did not differ significantly in the proportion classified as HA-S. aureus by the CDC CA-MRSA definition (p = 0.5). The genetic backgrounds of MRSA and MSSA multilocus sequence type (ST) 1, ST5, ST8, ST30, and ST59 comprised in combination 94.5% of MRSA isolates and 50.9% of MSSA isolates. By logistic regression, being cared for in the Emergency Department (OR 4.6, CI 1.5-14.0, p = 0.008) was associated with MRSA infection.Patients with MSSA at UCMC have characteristics consistent with a health-care-associated infection more often than do patients with MRSA; a possible role reversal has occurred for MSSA and MRSA strains. Clinical MSSA and MRSA strains shared genotype backgrounds

Higher incidence of perineal community acquired MRSA infections among toddlers

<p>Abstract</p> <p>Background</p> <p>A six-fold increase in pediatric MRSA infections, prompted us to examine the clinical profile of children with MRSA infections seen at Mercy Children's Hospital, Toledo, Ohio and to characterize the responsible strains.</p> <p>Methods</p> <p>Records were reviewed of pediatric patients who cultured positive for MRSA from June 1 to December 31, 2007. Strain typing by pulsed field gel electrophoresis (PFT) and DiversiLab, SCC<it>mec </it>typing, and PCR-based <it>lukSF-PV </it>gene (encodes Panton-Valentine leukocidin), arginine catabolic mobile element (ACME) and <it>cap</it>5 gene detection was performed.</p> <p>Results</p> <p>Chart review of 63 patients with MRSA infections revealed that 58(92%) were community acquired MRSA (CAMRSA). All CAMRSA were skin and soft tissue infections (SSTI). Twenty five (43%) patients were aged < 3 yrs, 19(33%) aged 4-12 and 14(24%) aged 13-18. Nineteen (76%) of those aged < 3 yrs had higher incidence of perineal infections compared to only 2(11%) of the 4-12 yrs and none of the 13-18 yrs of age. Infections in the extremities were more common in the older youth compared to the youngest children. Overall, there was a significant association between site of the infection and age group (Fisher's Exact p-value < 0.001). All CAMRSA were USA300 PFT, clindamycin susceptible, SCC<it>mec </it>type IVa and <it>lukSF-PV gene </it>positive. Nearly all contained ACME and about 80% were <it>cap</it>5 positive. Of the 58 USA300 strains by PFT, 55(95%) were also identified as USA300 via the automated repetitive sequence-based PCR method from DiversiLab.</p> <p>Conclusions</p> <p>CAMRSA SSTI of the perineum was significantly more common among toddlers and that of the extremities in older children. The infecting strains were all USA300 PFT. Further studies are needed to identify the unique virulence and colonization characteristics of USA300 strains in these infections.</p

The Role of Health Behaviours Across the Life Course in the Socioeconomic Patterning of All-Cause Mortality: The West of Scotland Twenty-07 Prospective Cohort Study

Background: Socioeconomic differentials in mortality are increasing in many industrialised countries. Purpose: This study aims to examine the role of behaviours (smoking, alcohol, exercise, and diet) in explaining socioeconomic differentials in mortality and whether this varies over the life course, between cohorts and by gender. Methods: Analysis of two representative population cohorts of men and women, born in the 1950s and 1930s, were performed. Health behaviours were assessed on five occasions over 20 years. Results: Health behaviours explained a substantial part of the socioeconomic differentials in mortality. Cumulative behaviours and those that were more strongly associated with socioeconomic status had the greatest impact. For example, in the 1950s cohort, the age-sex adjusted hazard ratio comparing respondents with manual versus non-manual occupational status was 1.80 (1.25, 2.58); adjustment for cumulative smoking over 20 years attenuated the association by 49 %, diet by 43 %, drinking by 13 % and inactivity by only 1%. Conclusions: Health behaviours have an important role in explaining socioeconomic differentials in mortality. © 2013 The Author(s)