Bayesian Profile Regression to Deal With Multiple Highly Correlated Exposures and a Censored Survival Outcome. First Application in Ionizing Radiation Epidemiology

As multifactorial and chronic diseases, cancers are among these pathologies for which the exposome concept is essential to gain more insight into the associated etiology and, ultimately, lead to better primary prevention strategies for public health. Indeed, cancers result from the combined influence of many genetic, environmental and behavioral stressors that may occur simultaneously and interact. It is thus important to properly account for multifactorial exposure patterns when estimating specific cancer risks at individual or population level. Nevertheless, the risk factors, especially environmental, are still too often considered in isolation in epidemiological studies. Moreover, major statistical difficulties occur when exposures to several factors are highly correlated due, for instance, to common sources shared by several pollutants. Suitable statistical methods must then be used to deal with these multicollinearity issues. In this work, we focused on the specific problem of estimating a disease risk from highly correlated environmental exposure covariates and a censored survival outcome. We extended Bayesian profile regression mixture (PRM) models to this context by assuming an instantaneous excess hazard ratio disease sub-model. The proposed hierarchical model incorporates an underlying truncated Dirichlet process mixture as an attribution sub-model. A specific adaptive Metropolis-Within-Gibbs algorithm-including label switching moves-was implemented to infer the model. This allows simultaneously clustering individuals with similar risks and similar exposure characteristics and estimating the associated risk for each group. Our Bayesian PRM model was applied to the estimation of the risk of death by lung cancer in a cohort of French uranium miners who were chronically and occupationally exposed to multiple and correlated sources of ionizing radiation. Several groups of uranium miners with high risk and low risk of death by lung cancer were identified and characterized by specific exposure profiles. Interestingly, our case study illustrates a limit of MCMC algorithms to fit full Bayesian PRM models even if the updating schemes for the cluster labels incorporate label-switching moves. Then, although this paper shows that Bayesian PRM models are promising tools for exposome research, it also opens new avenues for methodological research in this class of probabilistic models.

A Bayesian hierarchical approach to account for left-censored and missing radiation doses prone to classical measurement error when analyzing lung cancer mortality due to γ-ray exposure in the French cohort of uranium miners

Epidemiological data on cohorts of occupationally exposed uranium miners are currently used to assess health risks associated with chronic exposure to low doses of ionizing radiation. Nevertheless, exposure uncertainty is ubiquitous and questions the validity of statistical inference in these cohorts. This paper highlights the flexibility and relevance of the Bayesian hierarchical approach to account for both missing and left-censored (i.e. only known to be lower than a fixed detection limit) radiation doses that are prone to measurement error, when estimating radiation-related risks. Up to the authors' knowledge, this is the first time these three sources of uncertainty are dealt with simultaneously in radiation epidemiology. To illustrate the issue, this paper focuses on the specific problem of accounting for these three sources of uncertainty when estimating the association between occupational exposure to low levels of γ-radiation and lung cancer mortality in the post-55 sub-cohort of French uranium miners. The impact of these three sources of dose uncertainty is of marginal importance when estimating the risk of death by lung cancer among French uranium miners. The corrected excess hazard ratio (EHR) is 0.81 per 100 mSv (95% credible interval: [0.28; 1.75]). Interestingly, even if the 95% credible interval of the corrected EHR is wider than the uncorrected one, a statistically significant positive association remains between γ-ray exposure and the risk of death by lung cancer, after accounting for dose uncertainty. Sensitivity analyses show that the results obtained are robust to different assumptions. Because of its flexible and modular nature, the Bayesian hierarchical models proposed in this work could be easily extended to account for high proportions of missing and left-censored dose values or exposure data, prone to more complex patterns of measurement error.

A cautionary comment on the generation of Berkson error in epidemiological studies

Exposure measurement error can be seen as one of the most important sources of uncertainty in studies in epidemiology. When the aim is to assess the effects of measurement error on statistical inference or to compare the performance of several methods for measurement error correction, it is indispensable to be able to generate different types of measurement error. This paper compares two approaches for the generation of Berkson error, which have recently been applied in radiation epidemiology, in their ability to generate exposure data that satisfy the properties of the Berkson model. In particular, it is shown that the use of one of the methods produces results that are not in accordance with two important properties of Berkson error.

Shared and unshared exposure measurement error in occupational cohort studies and their effects on statistical inference in proportional hazards models

Exposure measurement error represents one of the most important sources of uncertainty in epidemiology. When exposure uncertainty is not or only poorly accounted for, it can lead to biased risk estimates and a distortion of the shape of the exposure-response relationship. In occupational cohort studies, the time-dependent nature of exposure and changes in the method of exposure assessment may create complex error structures. When a method of group-level exposure assessment is used, individual worker practices and the imprecision of the instrument used to measure the average exposure for a group of workers may give rise to errors that are shared between workers, within workers or both. In contrast to unshared measurement error, the effects of shared errors remain largely unknown. Moreover, exposure uncertainty and magnitude of exposure are typically highest for the earliest years of exposure. We conduct a simulation study based on exposure data of the French cohort of uranium miners to compare the effects of shared and unshared exposure uncertainty on risk estimation and on the shape of the exposure-response curve in proportional hazards models. Our results indicate that uncertainty components shared within workers cause more bias in risk estimation and a more severe attenuation of the exposure-response relationship than unshared exposure uncertainty or exposure uncertainty shared between individuals. These findings underline the importance of careful characterisation and modeling of exposure uncertainty in observational studies.

Citrulline directly modulates muscle protein synthesis via the PI3K/MAPK/4E-BP1 pathway in a malnourished state: evidence from in vivo, ex vivo, and in vitro studies

Citrulline (CIT) is an endogenous amino acid produced by the intestine. Recent literature has consistently shown CIT to be an activator of muscle protein synthesis (MPS). However, the underlying mechanism is still unknown. Our working hypothesis was that CIT might regulate muscle homeostasis directly through the mTORC1/PI3K/MAPK pathways. Because CIT undergoes both interorgan and intraorgan trafficking and metabolism, we combined three approaches: in vivo, ex vivo, and in vitro. Using a model of malnourished aged rats, CIT supplementation activated the phosphorylation of S6K1 and 4E-BP1 in muscle. Interestingly, the increase in S6K1 phosphorylation was positively correlated (P < 0.05) with plasma CIT concentration. In a model of isolated incubated skeletal muscle from malnourished rats, CIT enhanced MPS (from 30 to 80% CIT vs. Ctrl, P < 0.05), and the CIT effect was abolished in the presence of wortmannin, rapamycin, and PD-98059. In vitro, on myotubes in culture, CIT led to a 2.5-fold increase in S6K1 phosphorylation and a 1.5-fold increase in 4E-BP1 phosphorylation. Both rapamycin and PD-98059 inhibited the CIT effect on S6K1, whereas only LY-294002 inhibited the CIT effect on both S6K1 and 4E-BP1. These findings show that CIT is a signaling agent for muscle homeostasis, suggesting a new role of the intestine in muscle mass control.

New insights into handling missing values in environmental epidemiological studies

Missing data are unavoidable in environmental epidemiologic surveys. The aim of this study was to compare methods for handling large amounts of missing values: omission of missing values, single and multiple imputations (through linear regression or partial least squares regression), and a fully Bayesian approach. These methods were applied to the PARIS birth cohort, where indoor domestic pollutant measurements were performed in a random sample of babies' dwellings. A simulation study was conducted to assess performances of different approaches with a high proportion of missing values (from 50% to 95%). Different simulation scenarios were carried out, controlling the true value of the association (odds ratio of 1.0, 1.2, and 1.4), and varying the health outcome prevalence. When a large amount of data is missing, omitting these missing data reduced statistical power and inflated standard errors, which affected the significance of the association. Single imputation underestimated the variability, and considerably increased risk of type I error. All approaches were conservative, except the Bayesian joint model. In the case of a common health outcome, the fully Bayesian approach is the most efficient approach (low root mean square error, reasonable type I error, and high statistical power). Nevertheless for a less prevalent event, the type I error is increased and the statistical power is reduced. The estimated posterior distribution of the OR is useful to refine the conclusion. Among the methods handling missing values, no approach is absolutely the best but when usual approaches (e.g. single imputation) are not sufficient, joint modelling approach of missing process and health association is more efficient when large amounts of data are missing.

Global determinants of mortality in under 5s: 10 year worldwide longitudinal study

OBJECTIVE

To assess at country level the association of mortality in under 5s with a large set of determinants.

DESIGN

Longitudinal study.

SETTING

193 United Nations member countries, 2000-09.

METHODS

Yearly data between 2000 and 2009 based on 12 world development indicators were used in a multivariable general additive mixed model allowing for non-linear relations and lag effects.

MAIN OUTCOME MEASURE

National rate of deaths in under 5s per 1000 live births

RESULTS

The model retained the variables: gross domestic product per capita; percentage of the population having access to improved water sources, having access to improved sanitation facilities, and living in urban areas; adolescent fertility rate; public health expenditure per capita; prevalence of HIV; perceived level of corruption and of violence; and mean number of years in school for women of reproductive age. Most of these variables exhibited non-linear behaviours and lag effects.

CONCLUSIONS

By providing a unified framework for mortality in under 5s, encompassing both high and low income countries this study showed non-linear behaviours and lag effects of known or suspected determinants of mortality in this age group. Although some of the determinants presented a linear action on log mortality indicating that whatever the context, acting on them would be a pertinent strategy to effectively reduce mortality, others had a threshold based relation potentially mediated by lag effects. These findings could help designing efficient strategies to achieve maximum progress towards millennium development goal 4, which aims to reduce mortality in under 5s by two thirds between 1990 and 2015.

The timing of dialysis initiation affects the incidence of renal replacement therapy

BACKGROUND

Variations in the timing of dialysis initiation may explain some geographical variations in renal replacement therapy (RRT) incidence, but this effect has never been quantified.

METHODS

Using data from the French Renal Epidemiology and Information Network registry, we quantified the association between RRT incidence in 2006-07 and median estimated glomerular filtration rate (eGFR) values before starting dialysis at the administrative district level with geographically appropriate methods.

RESULTS

Crude RRT incidence varied from 80.4 to 238.6 pmi between administrative districts, and median eGFR at dialysis initiation from 5.9 to 11.8 ml/min/1.73 m(2). Age- and sex-adjusted RRT incidence, associated with a 1.2-ml/min/1.73m(2) increase in median eGFR, rose 8% (4-13%) before and 9% (5-13%) after controlling for the effect of nine potential socioeconomic and medical risk factors.

CONCLUSION

The impact of increased eGFR at initiation should be taken into account in guidelines recommending earlier dialysis start.

Occupational risk factors for acute leukaemia: a case-control study

A case-control study has been performed for occupational risk factors of acute leukaemia, based on 185 cases more than 30 years old and 513 matched controls. There was a significant excess of polyvalent farming and electronic engineers among professions of cases, and, in addition of metal workers when considering the professions pursued for more than 5 years. The corresponding exposures were analysed through a detailed questionnaire, and assessed by an industrial hygienist after blinding the case-control status. The odds ratios (OR) were computed after adjustment on matching variables and prior chemo- or radiotherapy treatment, and after stratification for the level and total duration of exposure. There was no excess of professional exposure to ionizing radiation among cases. A significant relationship was observed between acute leukaemia and high or medium exposure to benzene, as well as over 10 years high or medium exposure to exhaust gas. In addition a significant relationship was observed with exposure to pesticides--insecticides and/or weed killers--and to electric and magnetic fields (EMF). The relationship with pesticides was significant when considering high or medium exposure to weed killers and more than 10 years exposure to both subtypes of pesticides. The relationship with pesticides and EMF remained significant when confounding factors were taken into consideration and after adjustment on co-exposure to benzene. The cytological studies showed that acute leukaemias following exposure to benzene (high or medium) and to EMF were only of myelogenous subtypes, whereas those following exposure to pesticides were divided between lymphoblastic and myeloblastic subtypes. Cytogenetic studies failed to show increased frequency of chromosomal abnormalities, as described in acute leukaemias secondary to anti-cancer treatments. Our study adds credence to the hypothesis that pesticides and EMF are leukaemogenic agents, together with benzene.