Biomedical subjects

I Bray

Publications and source records attributed to I Bray.

At least 19 recordsLinked to original sources

PubMed2000

Projections of alcohol- and tobacco-related cancer mortality in Central Europe.

Central European mortality rates for cancer sites related to tobacco and alcohol have increased rapidly in recent decades. From a public health point of view, it is of considerable interest to know whether these past increases in cancer mortality will continue into the future. Cancer mortality rates for the period 1965-1994 in Bulgaria, Czech Republic and Slovakia (analysed together), Hungary, Poland, and Romania were analysed for cancers of the larynx, oral cavity and pharynx, oesophagus, bladder, kidney, and pancreas. Using a Bayesian age-period-cohort approach, we have calculated smoothed observed rates. The effects of period and cohort were extrapolated to estimate mortality projections for 1995-99, 2004-09, and 2005-09. Mortality rates for all sites are projected to increase in most countries. Hungary has the highest projected rates for most sites, and particularly rapid increases are expected for cancers of the oral cavity and pharynx and of the larynx in Hungarian men. The smoothed 1990-94 male mortality rates for these two sites of 16. 32/100,000 and 8.70/100,000, respectively, are projected to reach 35. 17/100,000 for cancer of the oral cavity and pharynx and 14.12/100, 000 for cancer of the larynx by the period 2000-04. For kidney cancer, former Czechoslovakia has the highest observed and projected mortality rates. The smoothed 1990-94 rate of 8.37/100,000 is expected to increase 24% to 10.38/100,000 by 2000-04. Our results indicate that further increases may be expected on top of the already high cancer mortality levels in Central Europe. Policies to reduce alcohol consumption and prevent smoking in younger generations are necessary to reduce mortality as these cohorts age.

Adult↗

PubMed2000

Estimating birth prevalence of Down's syndrome.

BACKGROUND: Estimates of maternal age-specific prevalence of Down's syndrome are needed for the assessment of environmental factors, for counselling and monitoring screening programmes. The estimates should relate to populations of women who have not received prenatal screening. This is normally achieved by using data collected before the widespread use of screening. The problem of under-ascertainment in some data-sets has been recognised in the literature, but has not been dealt with satisfactorily in the statistical models used to estimate live-birth prevalence. METHODS: In this paper we develop a model that takes explicit account of under-ascertainment and apply this model to data from nine published studies. The primary aim of our analysis is to provide an improved model for live-birth prevalence. A secondary aim is to examine the ascertainment rates in the nine studies. RESULTS: The proposed model provides a good fit to all but one of the nine studies, although exclusion of this study does not affect the estimated risks. The estimate of risk weighted across the maternal age distribution is 1.41 in 1000 live-births [90% confidence interval (CI) 1.37-1.49]. DISCUSSION: Comparing this figure with those obtained from published rate schedules suggests that the proposed model predicts rates that are some 10% higher than those obtained when ascertainment is assumed to be complete in all studies. The predicted rates are similar to those calculated when only those studies known to have high levels of acertainment are included.

Adolescent↗

PubMed2000

Empirical Bayes adjustments for multiple results in hypothesis-generating or surveillance studies.

Traditional methods of adjustment for multiple comparisons (e.g., Bonferroni adjustments) have fallen into disuse in epidemiological studies. However, alternative kinds of adjustment for data with multiple comparisons may sometimes be advisable. When a large number of comparisons are made, and when there is a high cost to investigating false positive leads, empirical or semi-Bayes adjustments may help in the selection of the most promising leads. Here we offer an example of such adjustments in a large surveillance data set of occupation and cancer in Nordic countries, in which we used empirical Bayes (EB) adjustments to evaluate standardized incidence ratios (SIRs) for cancer and occupation among craftsmen and laborers. For men, there were 642 SIRs, of which 138 (21%) had a P < 0.05 (13% positive with SIR > 1.0 and 8% negative with SIR < or = 1.0) when testing the null hypothesis of no cancer/occupation association; some of these were probably due to confounding by nonoccupational risk factors (e.g., smoking). After EB adjustments, there were 95 (15%) SIRs with P < 0.05 (10% positive and 5% negative). For women, there were 373 SIRs, of which 37 (10%) had P < 0.05 before adjustment (6% positive and 4% negative) and 13 (3%) had P < 0.05 after adjustment (2% positive and 1% negative). Several known associations were confirmed after EB adjustment (e.g., pleural cancer among plumbers, original SIR 3.2 (95% confidence interval, 2.5-4.1), adjusted SIR 2.0 (95% confidence interval, 1.6-2.4). EB can produce more accurate estimates of relative risk by shrinking imprecise outliers toward the mean, which may reduce the number of false positives otherwise flagged for further investigation. For example, liver cancer among chimney sweepers was reduced from an original SIR of 2.2 (range, 1.1-4.4) to an adjusted SIR of 1.1 (range, 0.9-1.4). A potentially important future application for EB is studies of gene-environment-disease interactions, in which hundreds of polymorphisms may be evaluated with dozens of environmental risk factors in large cohort studies, producing thousands of associations.

Analysis of Variance↗

PubMed1998

Joint estimation of Down syndrome risk and ascertainment rates: a meta-analysis of nine published data sets.

In this paper we present an analysis of nine data sets in which ascertainment and maternal age risk of Down syndrome are estimated jointly using maximum likelihood. We include data on 4825 Down syndrome cases from nine previously published data sets. These include data from studies carried out before the introduction of prenatal screening and from recent studies involving women who had not received prenatal testing. Our results show that, allowing for under-ascertainment, there is a good degree of consistency between the different data sets. We compare the three- and five-parameter constant plus exponential model with a three-parameter logistic model for maternal age-specific risk. We show that the three-parameter logistic model provides a good fit to the data and compare rates from this model with those derived from published studies of uncertain completeness (Cuckle et al., 1987) and those from data sets believed to be complete (Halliday et al., 1995; Hecht and Hook, 1994, 1996). In general, our results agree closely with those of the latter, but achieve greater precision because of the inclusion of additional data. Our derived rates are considerably higher than those of Cuckle et al. (1987), which are embedded in many computer systems for generating risks.

Down Syndrome↗

PubMed1998