Walter Schill

Attributable risk estimation from case-control data via logistic regression

By fitting an unconditional logistic regression model to unmatched case-control data, an estimate of the joint population attributable risk for the factor included is obtained. This estimate and its asymptotic variance can easily be computed from the intercept parameter and its asymptotic variance. A generalization to the analysis of stratified data with large strata enables the calculation of stratum-specific attributable risks and their variances via stratum-specific intercept parameters. If sampling of cases is independent of strata, an estimate of the summary attributable risk and its asymptotic variance may be obtained as a weighted sum of the stratum-specific attributable risks.

LOGISTIC ANALYSIS OF STUDIES WITH TWO‐STAGE SAMPLING: A COMPARISON OF FOUR APPROACHES

This paper discusses the analysis of two-stage studies where covariates are missing or measured with error at the first stage of sampling and are validated at the second stage in a subsample. Four recently developed approaches, the weighted pseudo-likelihood method of Flanders and Greenland (1991), the pseudo-conditional likelihood methods of Breslow and Cain (1988) and Schill et al. (1993) and the maximum likelihood estimate obtained via the EM-algorithm (Wacholder and Weinberg, 1994) are reviewed, and some connections between them are established. It is shown that, with respect to odds ratio estimation, case-control designs can be analysed as if first-stage sampling had been prospective. The procedures are numerically compared with respect to asymptotic relative efficiency in a missing value setting.

Elevated Cancer Mortality in a German Cohort of Bitumen Workers: Extended Follow-Up Through 2004

The mortality follow-up in a cohort of German asphalt workers covered an additional 6 years. Male workers (N = 7919) were classified into four exposure categories: (1) exposure to bitumen only, (2) to bitumen and coal tar, (3) neither to tar nor to bitumen, and (4) unknown exposure. Exposure-specific standardized mortality ratios (SMR) and associated 95% confidence intervals (CI) based on age- and calendar period-specific national mortality rates were calculated. To compare exposed and unexposed workers, relative risks were estimated by Poisson regression. By the end of 2004, 835 workers had died. The SMR for lung cancer was 1.77 (95% CI 1.46–2.16). Head and neck cancer showed an SMR of 2.36 (95% CI 1.78–3.07). Bladder cancer mortality was elevated threefold. Significantly elevated cancer-related SMRs were also found for all malignant tumors. In addition, elevated mortality rates of nonmalignant causes such as alcoholism, liver cirrhosis, and unnatural causes of deaths including accidents were observed. After stratification by exposure group, cancer mortality was elevated among bitumen-exposed and unexposed subjects. In the internal analysis, the association between lung cancer and bitumen exposure was weakened as compared with the previous follow-up (relative risk [RR] = 1.15; 95% CI 0.72–1.84). The follow-up demonstrated an excess of cancer in this cohort of asphalt workers. However, the observed mortality patterns were not clear. Although exposure to bitumen cannot be ruled out as being responsible for the observed results, a higher prevalence of alcohol and tobacco consumption may partially explain the observed risk increases. Exposure assessment in future studies should account for multiple occupational agents and nonoccupational factors to rule out that the observed differences in SMR are not due simply to random variation.

Does additional confounder information alter the estimated risk of bleeding associated with phenprocoumon use—results of a two-phase study

Claims databases are an important source for pharmacoepidemiological studies although they often lack information on some confounders. Two‐phase methodology was used to estimate the bleeding risk in patients treated with phenprocoumon from claims data combined with additional information on body mass index (BMI) and smoking.

Subacute toxicity of 1,1,1-trichloroethane, noise, and their combination in rats

The metabolism of the xenobiotics 1,1,1-trichloroethane (TCE) or 1,1,2-trichloro-1,2,2-trifluoroethane and endogeneous substrates may be changed under physiological stress situations. We studied long-term effects on rats exposed to TCE, noise pollution, and their combination. The experiments were performed in a special set-up where four parallel groups of rats were simultaneously exposed to defined conditions the chemical vapor; the noise pollution of 90 dB; their combination; and a control group without any exposure. The vapor of TCE was applied at a concentration of 200 ppm/8 hr or of 2000 ppm/12 hr for 84 days each. The experiments were performed with TCE from two different commercial sources. One of those TCE preparations caused effects at the high dosage level in terms of enhanced levels of the relation of liver to body weight; liver microsomal protein content; liver microsomal monooxygenase activity; and 3,4-dihydroxyphenylglycol excretion in urine. Eight other physiological and biochemical parameters were not changed.

The 2-phase case-control design: an efficient way to use expert-time.

OBJECTIVES The objective of this paper is to show the benefits of using a 2-phase case-control (2PCC) design in identifying dose-response relationships between cumulative occupational exposure as assessed by experts and lung cancer incidence in an actual study. METHODS A population-based case-control study including 246 cases and 531 controls was conducted in an area with high lung cancer rates in Northeast France. Detailed occupational and personal risk factors were obtained in face-to-face interviews. Cumulative expert-based exposure scores were obtained from a subset of 215 cases and 269 controls stratified on smoking and a prior algorithmic exposure score for asbestos, crystalline silica, and polycyclic aromatic hydrocarbons (PAH) in the framework of a 2PCC design. This subset deliberately under-sampled large strata among controls but not among cases. Logistic regression models adapted to 2PCC studies were applied and corresponding computations of attributable fractions and their confidence intervals developed. RESULTS Based on this 2PCC design, statistically significant dose-response relationships were obtained for asbestos, crystalline silica, PAH, and diesel motor exhaust. Simulations within this study showed that 2PCC studies were always more powerful than random samples. CONCLUSION The 2PCC design may be the design of choice when resources allow only a limited number of subjects with a full expert-based exposure assessment.

Perturbation by Single and Double Pulses as Analytical Tool for Analyzing

The functional structure of the circadian oscillator and its molecular compounds has frequently been analyzed by applying pulsed perturbations of various kinds and registering the response of the oscillator — mainly the phase shifting response [1,2]. This approach has been extensively exploited in the case of the circadian rhythm of Gonyaulax.

Flexible Two-Phase studies for rare exposures: Feasibility, planning and efficiency issues of a new variant

The two-phase design consists of an initial (Phase One) study with known disease status and inexpensive covariate information. Within this initial study one selects a subsample on which to collect detailed covariate data. Two-phase studies have been shown to be efficient compared to standard case-control designs. However, potential problems arise if one cannot assure minimum sample sizes in the rarest categories or if recontact of subjects is difficult. In the case of a rare exposure with an inexpensive proxy, the authors propose the flexible two-phase design for which there is a single time of contact, at which a decision about full covariate ascertainment is made based on the proxy. Subjects are screened until the desired numbers of cases and controls have been selected for full data collection. Strategies for optimizing the cost/efficiency of this design and corresponding software are presented. The design is applied to two examples from occupational and genetic epidemiology. By ensuring minimum numbers for the rarest disease-covariate combination(s), we obtain considerable efficiency gains over standard two-phase studies with an improved practical feasibility. The flexible two-phase design may be the design of choice in the case of well targeted studies of the effect of rare exposures with an inexpensive proxy.