Poisson regression with missing durations of exposure

In this paper, we develop Poisson-type regression methods that require the durations of exposure be measured only on a possibly nonrandom subset of the cohort members. These methods can be used to make inferences about the incidence density during exposure as well as the ratio of incidence densities during exposure versus not during exposure. Numerical studies demonstrate that the proposed methods yield reliable results in practical settings. We describe an application to a population-based case-control study assessing the transient increase in the risk of primary cardiac arrest during leisure-time physical activity.     

Interval estimation of the attributable risk for multiple exposure levels in case-control studies

In case-control studies, exposure to a risk factor often occurs at several levels, so the attributable risk at each level is of interest. In this paper, estimation for the 2 X 2 table (case-control status versus dichotomous exposure) and the 2 X k table (case-control status versus exposure at several levels) are reviewed along with an example. A method for finding confidence intervals for attributable risk in the 2 X k table is proposed, and its application to estimates adjusted across strata (the 2 X k X s case) is indicated. The results of a Monte Carlo study of the procedure demonstrate that the nominal and actual coverage probabilities agree satisfactorily for practical applications.     

A Bayesian semiparametric approach for incorporating longitudinal information on exposure history for inference in case-control studies

In a typical case-control study, exposure information is collected at a single time point for the cases and controls. However, case-control studies are often embedded in existing cohort studies containing a wealth of longitudinal exposure history about the participants. Recent medical studies have indicated that incorporating past exposure history, or a constructed summary measure of cumulative exposure derived from the past exposure history, when available, may lead to more precise and clinically meaningful estimates of the disease risk. In this article, we propose a flexible Bayesian semiparametric approach to model the longitudinal exposure profiles of the cases and controls and then use measures of cumulative exposure based on a weighted integral of this trajectory in the final disease risk model. The estimation is done via a joint likelihood. In the construction of the cumulative exposure summary, we introduce an influence function, a smooth function of time to characterize the association pattern of the exposure profile on the disease status with different time windows potentially having differential influence/weights. This enables us to analyze how the present disease status of a subject is influenced by his/her past exposure history conditional on the current ones. The joint likelihood formulation allows us to properly account for uncertainties associated with both stages of the estimation process in an integrated manner. Analysis is carried out in a hierarchical Bayesian framework using reversible jump Markov chain Monte Carlo algorithms. The proposed methodology is motivated by, and applied to a case-control study of prostate cancer where longitudinal biomarker information is available for the cases and controls.     

A score test for determining sample size in matched case-control studies with categorical exposure

The paper considers the problem of determining the number of matched sets in 1 : M matched case-control studies with a categorical exposure having k + 1 categories, k > or = 1. The basic interest lies in constructing a test statistic to test whether the exposure is associated with the disease. Estimates of the k odds ratios for 1 : M matched case-control studies with dichotomous exposure and for 1 : 1 matched case-control studies with exposure at several levels are presented in Breslow and Day (1980), but results holding in full generality were not available so far. We propose a score test for testing the hypothesis of no association between disease and the polychotomous exposure. We exploit the power function of this test statistic to calculate the required number of matched sets to detect specific departures from the null hypothesis of no association. We also consider the situation when there is a natural ordering among the levels of the exposure variable. For ordinal exposure variables, we propose a test for detecting trend in disease risk with increasing levels of the exposure variable. Our methods are illustrated with two datasets, one is a real dataset on colorectal cancer in rats and the other a simulated dataset for studying disease-gene association.     

Analysis of matched case-control data in presence of nonignorable missing exposure.

The present article deals with informative missing (IM) exposure data in matched case-control studies. When the missingness mechanism depends on the unobserved exposure values, modeling the missing data mechanism is inevitable. Therefore, a full likelihood-based approach for handling IM data has been proposed by positing a model for selection probability, and a parametric model for the partially missing exposure variable among the control population along with a disease risk model. We develop an EM algorithm to estimate the model parameters. Three special cases: (a) binary exposure variable, (b) normally distributed exposure variable, and (c) lognormally distributed exposure variable are discussed in detail. The method is illustrated by analyzing a real matched case-control data with missing exposure variable. The performance of the proposed method is evaluated through simulation studies, and the robustness of the proposed method for violation of different types of model assumptions has been considered.     

Misclassification of ELF occupational exposure resulting from spatial variation of the magnetic field

The adequacy of a single hip- or chest-worn magnetic field dosimeter to reliably classify subjects with respect to their occupational ELF magnetic field exposure is investigated. Hip-worn dosimeters consistently underestimate both whole-body average exposure and head exposure, tentatively regarded here as two possible definitions of the “true” exposure measurement. The approximate resulting bias in the relative risk estimate in hypothetical case-control studies is evaluated. A chest-worn dosimeter is found to be generally superior to a hip-worn one in assessing exposure during the occupational tasks considered here. © 1993 Wiley-Liss. Inc.     

A meta-analysis of case-control and cohort studies with interval-censored exposure data: application to chorionic villus sampling

Chorionic villus sampling (CVS) is a valued method of prenatal diagnosis that is often preferred over amniocentesis because it can be performed earlier, but which has also raised concern over a possible association with increased risk of terminal transverse limb deficiency (TTLD). We present and apply a meta-analytic method for estimating a combined dose-response effect from a series of case-control and cohort studies in which the exposure variable is interval-censored. Assuming coarsening at random for the interval-censoring, and calling upon the familiar result of Cornfield to pool case-control and cohort information on the association between a rare binary outcome and a multilevel exposure variable, we form a likelihood-based model to assess the effect of gestational age at the time of CVS on the presence or absence of a rare birth defect. Effect estimates are computed with a variant of the EM algorithm termed the method of weights, which enables the use of standard weighted regression software. Our findings suggest that CVS exposure at early gestational age leads to an increased risk of TTLD.     

Synthesis of evidence from epidemiological studies with interval-censored exposure due to grouping

We describe a method for assessing dose-response effects from a series of case-control and cohort studies in which the exposure information is interval censored. The interval censoring of the exposure variable is dealt with through the use of retrospective models in which the exposure is treated as a multinomial response and disease status as a binary covariate. Polychotomous logistic regression models are adopted in which the dose-response relationship between exposure and disease may be modeled in a discrete or continuous fashion. Partial conditioning is possible to eliminate some of the nuisance parameters. The methods are applied to the motivating study of the relationship between chorionic villus sampling and the occurrence of terminal transverse limb reduction.     

A method for analysing case-control studies with ordinal exposure variables

A method is proposed for analysing case-control studies with ordinal or continuous, but unruly, exposure levels. A test is proposed which is an appropriate linear combination of stratum-specific Wilcoxon tests. An estimator for the mean percentile shift between the case and control exposure levels is given. Methods for assessing heterogeneity of the mean percentile shift across strata are also discussed. The performance of the test as a function of the number of controls per case is studied for both local and distant alternatives. The asymptotic relative efficiency compared to the best parametric test with the same number of controls is evaluated and its performance is compared to tests based on a dichotomized exposure variable. Finally, the method is illustrated by two numerical examples.     

Optimal design and efficiency of two-phase case-control studies with error-prone and error-free exposure measures

This paper addresses optimal design and efficiency of two-phase (2P) case-control studies in which the first phase uses an error-prone exposure measure, Z, while the second phase measures true, dichotomous exposure, X, in a subset of subjects. Optimal design of a separate second phase, to be added to a preexisting study, is also investigated. Differential misclassification is assumed throughout. Results are also applicable to 2P cohort studies with error-prone and error-free measures of disease status but error-free exposure measures. While software based on the mean score method of Reilly and Pepe (1995, Biometrika 82, 299--314) can find optimal designs given pilot data, the lack of simple formulae makes it difficult to generalize about efficiency compared to one-phase (1P) studies based on X alone. Here, formulae for the optimal ratios of cases to controls and first- to second-phase sizes, and the optimal second-phase stratified sampling fractions, given a fixed budget, are given. The maximum efficiency of 2P designs compared to a 1P design is deduced and is shown to be bounded from above by a function of the sensitivities and specificities of Z. The efficiency of 'balanced' separate second-phase designs (Breslow and Cain, 1988, Biometrika 75, 11--20)-in which equal numbers of subjects are chosen from each first-phase strata-compared to optimal design is deduced, enabling situations where balanced designs are nearly optimal to be identified.     

Correlation between daily life aluminium exposure and breast cancer risk: A systematic review

BackgroundEpidemiological data indicate that the role of environmental factors on breast cancer (BC) incidence remains undetermined. Our daily life exposure to aluminium (Al) is suspected to influence BC development. This review proposes a state of the art on the association between Al and BC risk combined with a critical point of view on the subject.MethodsWe searched the PubMed database using terms related to Al and BC up to November 18, 2022. Reports were eligible if they were cohort or case-control studies or meta-analyses.FindingsSix studies focused on the relationship between deodorant and antiperspirant use and BC incidence and didn’t produce consistent results. Among 13 studies relating Al content in mammary tissues and BC risk, results are not unanimous to validate higher Al content in tumor tissues compared to healthy ones. We detail parameters that could explain this conclusion: the absence of statistical adjustments on BC risk factors in studies, the confusion between deodorant and antiperspirant terms, the non-assessment of global Al exposure, and the focus on Al in mammary tissues whereas a profile of several metals seems more appropriate. The clinical studies are retrospective. They were carried out on small cohorts and without a long follow-up. On the other hand, studies on cell lines have shown the carcinogenic potential of aluminum. Moreover, studies considered BC as a unique group whereas BC is a heterogeneous disease with multiple tumor subtypes determining the tumor aggressiveness.ConclusionIn light of the precautionary principle and based on the data obtained, it is better to avoid antiperspirants that contain Al. Deodorants without aluminum are not implicated in breast cancer, either clinically or fundamentally.     

Magnetic field exposure assessment: a comparison of various methods

The accurate and valid measurement of personal exposure to magnetic fields poses a major challenge for epidemiologic studies. When considering the various methods to assess exposure, it is unclear which measures are most relevant for studies of human disease, if any. Given these uncertainties, the Electromagnetic Fields and Breast Cancer on Long Island Study (EBCLIS) undertook a pilot study to develop the data collection protocol for a case-control study of breast cancer and magnetic fields. The pilot study used and compared various methods to assess residential exposures to magnetic fields, and related these measures to personal exposures. It included 31 women without breast cancer (mean age, 63+/-7 yr) who lived in their present homes for at least 15 yr. The pilot study consisted of an in-home interview, spot and 24-h magnetic field waveforms and broadband recordings, ground currents, wire coding, and personal 24-h broadband measurements. From the regression analyses, the model that best predicted personal magnetic field exposures included 24-h measurements in the bedroom and in the most lived-in room; as well as ground current test loads taken at the center of this most lived in room (r(2)=86%). The addition of other variables in this regression model yielded only small and nonsignificant increases in r(2). As a direct result of this pilot, EBCLIS will include ground current measurements in its protocol, which have not previously been collected as part of an epidemiologic study. Ground currents may be important because they may be richer in 180 Hz components than are the other currents in a power system. EBCLIS will have the opportunity to examine the ground-current hypothesis in the context of female breast cancer.     

Birth defects after maternal exposure to corticosteroids: prospective cohort study and meta-analysis of epidemiological studies

BACKGROUND: Corticosteroids are first-line drugs for the treatment of a variety of conditions in women of childbearing age. Information regarding human pregnancy outcome with corticosteroids is limited. METHODS: We collected prospectively and followed up 184 women exposed to prednisone in pregnancy and 188 pregnant women who were counseled by Motherisk for nonteratogenic exposure. The primary outcome was the rate of major birth defects. A meta-analysis of all epidemiological studies was conducted. The Mantel-Haenszel summary odds ratio was calculated for the pooled studies with 95% confidence intervals. A cumulative summary odds ratio was also calculated by combining studies in chronological order. Chi-squared for homogeneity was determined to establish the comparability of the studies. RESULTS: In our prospective study, there was no statistical difference in the rate of major anomalies between the corticosteroid-exposed and control groups. In the meta-analysis, the Mantel-Haenszel summary odds ratio for major malformations with all cohort studies was 1.45 [95% CI 0.80, 2.60] and 3.03 [95% CI 1.08, 8. 54] when Heinonen et al. ('77) was removed. This suggests a marginally increased risk of major malformations after first-trimester exposure to corticosteroids. In addition, summary odds ratio for case-control studies examining oral clefts was significant (3.35 [95% CI 1.97, 5.69]). CONCLUSIONS: Although prednisone does not represent a major teratogenic risk in humans at therapeutic doses, it does increase by an order of 3.4-fold the risk of oral cleft, which is consistent with the existing animal studies.     

Excess Relative Risk as an Effect Measure in Case-Control Studies of Rare Diseases

Epidemiologists often use ratio-type indices (rate ratio, risk ratio and odds ratio) to quantify the association between exposure and disease. By comparison, less attention has been paid to effect measures on a difference scale (excess rate or excess risk). The excess relative risk (ERR) used primarily by radiation epidemiologists is of peculiar interest here, in that it involves both difference and ratio operations. The ERR index (but not the difference-type indices) is estimable in case-control studies. Using the theory of sufficient component cause model, the author shows that when there is no mechanistic interaction (no synergism in the sufficient cause sense) between the exposure under study and the stratifying variable, the ERR index (but not the ratio-type indices) in a rare-disease case-control setting should remain constant across strata and can therefore be regarded as a common effect parameter. By exploiting this homogeneity property, the related attributable fraction indices can also be estimated with greater precision. The author demonstrates the methodology (SAS codes provided) using a case-control dataset, and shows that ERR preserves the logical properties of the ratio-type indices. In light of the many desirable properties of the ERR index, the author advocates its use as an effect measure in case-control studies of rare diseases.     

A note on estimating crude odds ratios in case-control studies with differentially misclassified exposure

Morrissey and Spiegelman (1999, Biometrics 55, 338 344) provided a comparative study of adjustment methods for exposure misclassification in case-control studies equipped with an internal validation sample. In addition to the maximum likelihood (ML) approach, they considered two intuitive procedures based on proposals in the literature. Despite appealing ease of computation associated with the latter two methods, efficiency calculations suggested that ML was often to be recommended for the analyst with access to a numerical routine to facilitate it. Here, a reparameterization of the likelihood reveals that one of the intuitive approaches, the inverse matrix method, is in fact ML under differential misclassification. This correction is intended to alert readers to the existence of a simple closed-form ML estimator for the odds ratio in this setting so that they may avoid assuming that a commercially inaccessible optimization routine must be sought to implement ML.     

Amyotrophic lateral sclerosis and occupational exposure to electromagnetic fields

In an hypothesis-generating case-control study of amyotrophic lateral sclerosis, lifetime occupational histories were obtained. The patients (n = 28) were clinic based. The occupational exposure of interest in this report is electromagnetic fields (EMFs). This is the first and so far the only exposure analyzed in this study. Occupational exposure up to 2 years prior to estimated disease symptom onset was used for construction of exposure indices for cases. Controls (n = 32) were blood and nonblood relatives of cases. Occupational exposure for controls was through the same age as exposure for the corresponding cases. Twenty (71%) cases and 28 (88%) controls had at least 20 years of work experience covering the exposure period. The occupational history and task data were used to classify blindly each occupation for each subject as having high, medium/high, medium, medium/low, or low EMF exposure, based primarily on data from an earlier and unrelated study designed to obtain occupational EMF exposure information on workers in “electrical” and “nonelectrical” jobs. By using the length of time each subject spent in each occupation through the exposure period, two indices of exposure were constructed: total occupational exposure (E₁) and average occupational exposure (E₂). For cases and controls with at least 20 years of work experience, the odds ratio (OR) for exposure at the 75th percentile of the E₁ case exposure data relative to minimum exposure was 7.5 (P < 0.02; 95% Cl, 1.4–38.1) and the corresponding OR for E₂ was 5.5 (P < 0.02; 95% CI, 1.3–22.5). For all cases and controls, the ORs were 2.5 (P < 0.1; 95% CI, 0.9–8.1) for E₁ and 2.3 (P = 0.12; 95% CI, 0.8–6.6) for E₂. This study should be considered an hypothesis-generating study. Larger studies, using incident cases and improved exposure assessment, should be undertaken. Bioelectromagnetics 18:28–35, 1997. © 1997 Wiley-Liss, Inc.     

Biomarkers for human radiation exposure

There is a concern over the potential use of radioactive isotopes as a weapon of terror. The detonation of a radiation dispersal device, the so-called “dirty bomb” can lead to public panic. In order to estimate risks associated with radiation exposure, it is important to understand the biological effects of radiation exposure. Based on this knowledge, biomarkers to monitor potentially exposed populations after a radiological accident can be developed and would be extremely valuable for emergency response. While the traditional radiation exposure biomarkers based on cytogenetic assays serve as standard, the development of rapid and noninvasive tests for radiation exposure is needed. The genomics based knowledge is providing new avenues for investigation. The examination of gene expression after ionizing radiation exposure could serve as a potential molecular marker for biodosimetry. Microarray based studies are identifying new radiation responsive genes that could potentially be used as biomarkers of human exposure to radiation after an accident.     

Passive smoking and lung cancer: current evidence and ongoing studies at the International Agency for Research on Cancer

The evidence available from 3 cohort and 11 case-control studies investigating the relationship between exposure to environmental tobacco smoke (ETS) and lung cancer in non-smokers is reviewed. While it appears most likely that a causal relationship exists, the size of the effect, under different circumstances of exposures, remains to be accurately estimated. This requires studies using valid instruments (e.g., questionnaires) to quantitate exposures, and free as far as possible from biases. An investigation addressing this point is in progress under the coordination of the International Agency for Research on Cancer.     

Case-control methods in the presence of multiple failure times and competing risks

The link between cohort and incident case-control studies has been considered by many authors. In particular, under the Cox proportional hazards model, follow-up data (implicit or explicit) can be analyzed as a case-control study by randomly selecting controls from the risk sets of each incident case, thereby obviating the necessity of working with the entire cohort when interest is primarily on exposure effects. This paper extends this linkage to competing risks and to diseases with multiple incidence or recurrence times by matching to each event (case) a sample of controls from the appropriate risk set. Illustrations are given.     

The challenges of exposure assessment in health studies of Gulf War veterans

A variety of exposures have been investigated in Gulf War veterans' health studies. These have most commonly been by self-report in a postal questionnaire but modelling and bio-monitoring have also been employed. Exposure assessment is difficult to do well in studies of any workplace environment. It is made more difficult in Gulf War studies where there are a number and variety of possible exposures, no agreed metrics for individual exposures and few contemporary records associating the exposure with an individual. In some studies, the exposure assessment was carried out some years after the war and in the context of media interest. Several studies have examined different ways to test the accuracy of exposure reporting in Gulf War cohorts. There is some evidence from Gulf War studies that self-reported exposures were subject to recall bias but it is difficult to assess the extent. Occupational exposure-assessment methodology can provide insights into the exposure-assessment process and how to do it well. This is discussed in the context of the Gulf War studies. Alternative exposure-assessment methodologies are presented, although these may not be suitable for widespread use in veteran studies. Due to the poor quality of and accessibility of objective military exposure records, self-assessed exposure questionnaires are likely to remain the main instrument for assessing the exposure for a large number of veterans. If this is to be the case, then validation methods with more objective methods need to be included in future study designs.