Man-made mineral fibers and lung cancer. Epidemiologic evidence regarding the causal hypothesis.

Reviews of the epidemiologic literature point to a causal connection between lung cancer and exposure to airborne man-made mineral fibers. The present critical re-review starts with the requirements for epidemiologic evidence to be informative regarding a hypothesis on cancer etiology. The previous reviews relate lung cancer mortality to exposure that is too recent to be relevant. The relation to relevant (distant) exposure in the available data involves notable confounding by coexposure to other agents in the work environment, by the lower socioeconomic status of the exposed workers, and possibly by smoking. Moreover, analyses of trends in standardized mortality ratios according to timing and duration of exposure involve a lack of mutual comparability between the ratios. Given these problems, the available evidence is inadequate for testing the causal hypothesis. However, reanalyses of the available data, augmentation of the data with reanalyses, and new studies could eliminate the existing inadequacies

The impact of self-reported exposure to whole-body-vibrations on the risk of disability pension among men: a 15 year prospective study

<p>Abstract</p> <p>Background</p> <p>Whole-body-vibrations are often associated with adverse health effect but the long term effects are less known. This study investigates the association between occupational exposures to whole-body vibrations, and subsequent transition to disability pension.</p> <p>Methods</p> <p>A total of 4215 male employees were followed up for subsequent disability pension retirement. Exposure to whole-body-vibration was self-reported while new cases of disability pension were retrieved from a national register.</p> <p>Results</p> <p>The hazard ratio (HR) for disability pension retirement among men exposed to whole-body-vibrations was 1.61 (95% confidence interval (CI) 1.07-2.40) after adjustment for age, smoking habits, BMI, physical job demands and awkward work postures. In our model, with the available explanatory variables, 5.6% of the male disability pension cases were attributable to whole-body-vibrations.</p> <p>Conclusions</p> <p>Exposure to whole-body-vibrations predicts subsequent disability pension retirement. Continued reduction of whole-body-vibrations may reduce the number of new cases of disability pension.</p

Optimizing the diagnostic work-up of acute uncomplicated urinary tract infections

<p>Abstract</p> <p>Background</p> <p>Most diagnostic tests for acute uncomplicated urinary tract infections (UTIs) have been previously studied in so-called single-test evaluations. In practice, however, clinicians use more than one test in the diagnostic work-up. Since test results carry overlapping information, results from single-test studies may be confounded. The primary objective of the Amsterdam Cystitis/Urinary Tract Infection Study (ACUTIS) is to determine the (additional) diagnostic value of relevant tests from patient history and laboratory investigations, taking into account their mutual dependencies. Consequently, after suitable validation, an easy to use, multivariable diagnostic rule (clinical index) will be derived.</p> <p>Methods</p> <p>Women who contact their GP with painful and/or frequent micturition undergo a series of possibly relevant tests, consisting of patient history questions and laboratory investigations. Using urine culture as the reference standard, two multivariable models (diagnostic indices) will be generated: a model which assumes that patients attend the GP surgery and a model based on telephone contact only. Models will be made more robust using the bootstrap. Discrimination will be visualized in high resolution histograms of the posterior UTI probabilities and summarized as 5^th, 10^th, 25^th50^th, 75^th, 90^th, and 95^thcentiles of these, Brier score and the area under the receiver operating characteristics curve (ROC) with 95% confidence intervals. Using the regression coefficients of the independent diagnostic indicators, a diagnostic rule will be derived, consisting of an efficient set of tests and their diagnostic values.</p> <p>The course of the presenting complaints is studied using 7-day patient diaries. To learn more about the natural history of UTIs, patients will be offered the opportunity to postpone the use of antibiotics.</p> <p>Discussion</p> <p>We expect that our diagnostic rule will allow efficient diagnosis of UTIs, necessitating the collection of diagnostic indicators with proven added value. GPs may use the rule (preferably after suitable validation) to estimate UTI probabilities for women with different combinations of test results. Finally, in a subcohort, an attempt is made to identify which indicators (including antibiotic treatment) are useful to prognosticate recovery from painful and/or frequent micturition.</p

Experience with multiple control groups in a large population-based case–control study on genetic and environmental risk factors

We discuss the analytic and practical considerations in a large case–control study that had two control groups; the first control group consisting of partners of patients and the second obtained by random digit dialling (RDD). As an example of the evaluation of a general lifestyle factor, we present body mass index (BMI). Both control groups had lower BMIs than the patients. The distribution in the partner controls was closer to that of the patients, likely due to similar lifestyles. A statistical approach was used to pool the results of both analyses, wherein partners were analyzed with a matched analysis, while RDDs were analyzed without matching. Even with a matched analysis, the odds ratio with partner controls remained closer to unity than with RDD controls, which is probably due to unmeasured confounders in the comparison with the random controls as well as intermediary factors. However, when studying injuries as a risk factor, the odds ratio remained higher with partner control subjects than with RRD control subjects, even after taking the matching into account. Finally we used factor V Leiden as an example of a genetic risk factor. The frequencies of factor V Leiden were identical in both control groups, indicating that for the analyses of this genetic risk factor the two control groups could be combined in a single unmatched analysis. In conclusion, the effect measures with the two control groups were in the same direction, and of the same order of magnitude. Moreover, it was not always the same control group that produced the higher or lower estimates, and a matched analysis did not remedy the differences. Our experience with the intricacies of dealing with two control groups may be useful to others when thinking about an optimal research design or the best statistical approach

Propensity scores in the presence of effect modification: A case study using the comparison of mortality on hemodialysis versus peritoneal dialysis

Purpose. To control for confounding bias from non-random treatment assignment in observational data, both traditional multivariable models and more recently propensity score approaches have been applied. Our aim was to compare a propensity score-stratified model with a traditional multivariable-adjusted model, specifically in estimating survival of hemodialysis (HD) versus peritoneal dialysis (PD) patients. Methods. Using the Dutch End-Stage Renal Disease Registry, we constructed a propensity score, predicting PD assignment from age, gender, primary renal disease, center of dialysis, and year of first renal replacement therapy. We developed two Cox proportional hazards regression models to estimate survival on PD relative to HD, a propensity score-stratified model stratifying on the propensity score and a multivariable-adjusted model, and tested several interaction terms in both models. Results. The propensity score performed well: it showed a reasonable fit, had a good c-statistic, calibrated well and balanced the covariates. The main-effects multivariable-adjusted model and the propensity score-stratified univariable Cox model resulted in similar relative mortality risk estimates of PD compared with HD (0.99 and 0.97, respectively) with fewer significant covariates in the propensity model. After introducing the missing interaction variables for effect modification in both models, the mortality risk estimates for both main effects and interactions remained comparable, but the propensity score model had nearly as many covariates because of the additional interaction variables. Conclusion. Although the propensity score performed well, it did not alter the treatment effect in the outcome model and lost its advantage of parsimony in the presence of effect modification

Colon cancer controls versus population controls in case-control studies of occupational risk factors

BACKGROUND: Since updated population registers do not exist in many countries it is often difficult to sample valid population controls from the study base to a case-control study. Use of patient controls is an alternative option if the exposure experience under study for these patients are interchangeable with the experience for population controls. Patient controls may even be preferable from population controls under certain conditions. In this study we examine if colon cancer patients can serve as surrogates for proper population controls in case-control studies of occupational risk factors. METHODS: The study was conducted from 1995 to 1997. Incident colon cancer controls (N = 428) aged 35–69 years with a histological verified diagnosis and population controls (N = 583) were selected. Altogether 254 (59%) of the colon cancer controls and 320 (55%) of the population controls were interviewed about occupational, medical and life style conditions. RESULTS: No statistical significant difference for educational level, medical history or smoking status was seen between the two control groups. There was evidence of a higher alcohol intake, less frequent work as a farmer and less exposure to pesticides among colon cancer controls. CONCLUSIONS: Use of colon cancer controls may provide valid exposure estimates in studies of many occupational risk factors for cancer, but not for studies on exposure related to farming