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Biomedical subjects

D Clayton

Publications and source records attributed to D Clayton.

At least 91 records · Page 5Linked to original sources
PubMed1992

A longitudinal study of 100 consecutive admissions for carbon monoxide poisoning to the Royal Adelaide Hospital.

A longitudinal study of one hundred consecutive admissions to the Royal Adelaide Hospital for carbon monoxide poisoning was conducted from 1986 to 1989. Twenty-five patients left hospital with persistent symptoms and signs of this poisoning. Five subsequently recovered. Twenty-four other patients, who were well when they left hospital, did not attend for a review one month after discharge. Extensive neuropsychiatric testing at this time showed 32% (24 of 76) had obvious sequelae of their exposure. Overall, the frequency of neuropsychiatric sequelae in the patients who only received oxygen at atmospheric pressure was 63% (N = 8) on discharge and 67% (N = 6) on one month follow-up. The frequency of sequelae among those who were given one hyperbaric oxygen treatment only was 46% (N = 24) on discharge and 50% (N = 20) on one month follow-up. In contrast, the frequency of sequelae in patients who had two or more hyperbaric oxygen treatments was only 13% (N = 68) on discharge (P less than 0.005) and 18% (N = 50) on follow-up (P less than 0.005). the frequency of sequelae was also significantly greater if hyperbaric oxygen was delayed (P less than 0.05). No markers of severe poisoning could be identified.

Adolescent↗
PubMed1992

Empirical Bayes methods for testing associations with large numbers of candidate genes in the presence of environmental risk factors, with applications to HLA associations in IDDM.

Standard regression models for disease incidence data can be used to test for associations between a disease and measured genetic and environmental factors and their interactions. Complications arise when the gene is not observed, requiring segregation and linkage analysis approaches, or when the candidate gene(s) are found to be highly polymorphic, as in the HLA region. We propose a Bayesian approach to the latter problem, in which the log relative risks for all alleles at a given locus are taken to be independent and exchangeable, assuming there is no preferential zygotic assortment and negligible recombination. Multi-locus problems can be addressed either by adding exchangeable interaction terms or by adopting a multivariate prior for haplotype effects. Some simulations based on our current work on family studies of IDDM are discussed.

Alleles↗
PubMed1991

Familial aggregation of Alzheimer's disease and related disorders: a collaborative re-analysis of case-control studies.

Case-control studies of Alzheimer's disease were re-analysed to examine the association of Alzheimer's disease with family history in first degree relatives of dementia, Down's syndrome and Parkinson's disease. Overall, the relative risk of Alzheimer's disease for those with at least one first degree relative with dementia was 3.5 (95% confidence interval 2.6-4.6). Stratification according to age of onset of Alzheimer's disease showed that the relative risk decreased with increasing onset age. However, among patients with an onset of disease after 80 years, there were still significantly more subjects with one or more first degree relatives with dementia as compared to controls (relative risk 2.6; 95% confidence interval 1.3-5.2). The relative risk of Alzheimer's disease was significantly lower in patients who had one first degree relative with dementia (relative risk 2.6; 95% confidence interval 2.0-3.5) as compared to those who had two or more affected relatives (relative risk 7.5; 95% confidence interval 3.3-16.7). Furthermore, the re-analysis showed a significant association between Alzheimer's disease and family history of Down's syndrome (relative risk 2.7; 95% confidence interval 1.2-5.7), which was strongest in those patients who had a positive family history of dementia. The relative risk of Alzheimer's disease for those with a positive family history of Parkinson's disease was 2.4 (95% confidence interval 1.0-5.8).

Age Factors↗
PubMed1991

Maternal age and Alzheimer's disease: a collaborative re-analysis of case-control studies. EURODEM Risk Factors Research Group.

To investigate the possible association between Alzheimer's disease and late maternal age at index birth, we conducted a collaborative re-analysis of existing case-control data sets. Of the 11 studies participating in the EURODEM project, four were included in the analyses regarding maternal age. In all four studies, cases were matched to controls by age and gender, and only population controls were considered. Analyses were conducted on the individual data sets, on the pooled sample, and on subgroups defined by gender, age at onset, and familial aggregation of dementia. Maternal age of 40 years and over was found to be suggestively associated with a higher risk of Alzheimer's disease (overall relative risk = 1.7; 95% confidence intervals: 1.0-2.9). In subgroup analyses, the association was statistically significant for women and for sporadic cases. Adjustments for education or analyses restricted to case-control pairs matched by type of respondent did not modify these results noticeably. The association was confirmed by a test of consistency with the Down's syndrome risk model; results of this test were again more definite for sporadic Alzheimer's disease. In addition, three of the four studies also suggested an increased risk for maternal age at index birth between 15 and 19 years (overall relative risk = 1.5; 95% confidence intervals: 0.8-3.0). Although consistency across studies was not always complete, only some of the increased relative risks reached statistical significance, and information regarding maternal age obtained through a next-of-kin interview may have limitations, our study suggests that both early and late maternal age should be further investigated as possible risk factors for Alzheimer's disease.

Adolescent↗
PubMed1990

Individual variation between general practitioners in labelling of hypertension.

Variation in labelling of hypertension by individual general practitioners was studied during a continuous opportunistic screening programme for hypertension in a single general practice with 12 principals. All the general practitioners agreed to label as hypertensive patients with systolic pressures of greater than or equal to 200 mm Hg or diastolic pressures of greater than or equal to 110 mm Hg on three consecutive readings. The overall number of patients labelled hypertensive at the beginning of the screening programme was 505 and this rose to 801 after five years. There was a large variation in the numbers of patients recorded as hypertensive at the start of the screening period, with numbers ranging from eight to 112 for individual practitioners. The variation persisted during the screening period, with the numbers of patients detected by individual general practitioners ranging from four to 46. The average systolic and diastolic pressures recorded among these patients also varied between doctors, and only 24 out of 187 patients had their high pressures recorded on three occasions and so fully met the criteria for diagnosing hypertension. Clearly, general practitioners are following their own individual criteria in defining hypertension and taking into account factors other than just the measured blood pressure.

Adult↗
PubMed1989

Role of advanced statistical techniques in cancer mapping.

Maps are spatial representations of a single-dimensional quantity. When cancer is mapped by geographic region, it is necessary to choose what this quantity is to be. Some cancer atlases have chosen a measure of effect, such as incidence, mortality, or relative risk. These are certainly the quantities which interest us most, but when the number of cases in a given region is small, their estimates can be very imprecise, and unreliable. The usual alternative is to map the statistical significance of departure from the overall map average. This has the advantage of de-emphasizing areas with low precision, but it can conversely highlight areas with high populations, even if they differ only minutely from the overall mean. Attempts to combine the two quantities on one map, for example by starring significant areas with relative risks above a certain level, are clumsy, and detract from the simplicity of the map. The empirical Bayes approach provides an alternative. Rather than plotting rates or risks which are individually estimated, the goal is to plot quantities which are estimated in such a way that those which are imprecise are improved by estimates from other appropriate areas. In the simplest case, this is equivalent to plotting for each map region the weighted average of the estimate for the region and the mean of the whole map, with more weight given to the regional estimate if it is based on a large population, and lower weight given if it is based on a small population. More sophisticated models are also described, and the methods are illustrated by the example of lip cancer in Scotland.

Adult↗
PubMed1988

The analysis of event history data: a review of progress and outstanding problems.

This paper reviews methods for the analysis of event history data by both parametric (exponential/Poisson) and semi-parametric methods. It identifies a need for software for handling the data structures of complex event histories and shows that, with such software, most Markov and semi-Markov models of event history data may be dealt with in the framework of generalized linear models. Finally, the emergent 'frailty' models for associated risks are discussed together with their implications for statistical software.

Data Interpretation, Statistical↗
PubMed1987

Features of a seminal proteinase inhibitor- zona pellucida-binding component on murine spermatozoa.

Murine cauda epididymal sperm contain sites on the plasma membrane over the apical portion of the acrosome that recognize proteinase inhibitors and the homologous zona pellucida. Ten times more of the component can be extracted from cauda and ductus sperm than from equal numbers of caput and corpus sperm. Likewise, few sperm from the upper epididymal regions are able to bind seminal inhibitor, while the majority of sperm from the cauda and ductus do bind. Cauda epididymal and ductus sperm lose little of their ability to bind inhibitor after a 4-hour in vitro incubation in either a capacitating or a noncapacitating medium. The percentage of naturally inseminated sperm with the seminal inhibitor bound to their surface decreases to about 10 after 4 hours in utero. Approximately 80% of these sperm show positive fluorescence when given the opportunity to rebind the the inhibitor, and these sperm do have an intact plasma membrane over the apical portion of the acrosome. Furthermore, after 4 hours in utero, the inhibitor bound in the same region of the sperm head as it did on freshly ejaculated sperm. The seminal inhibitor inhibits the binding of sperm to the zona if added during the first 15 minutes of incubation but has no effect on attachment. The data indicate that sperm gain the ability to bind the seminal inhibitor during the epididymal sojourn. Furthermore, this binding capacity is not lost during in vitro or in utero incubation. The site is not involved in sperm-zona attachment but does participate in the binding of sperm to the zona.

Acrosome↗
PubMed1987

Models for temporal variation in cancer rates. I: Age-period and age-cohort models.

A main concern of descriptive epidemiologists is the presentation and interpretation of temporal variations in cancer rates. In its simplest form, this problem is that of the analysis of a set of rates arranged in a two-way table by age group and calendar period. We review the modern approach to the analysis of such data which justifies traditional methods of age standardization in terms of the multiplicative risk model. We discuss the use of this model when the temporal variations are due to purely secular (period) influences and when they are attributable to generational (cohort) influences. Finally we demonstrate the serious difficulties which attend the interpretation of regular trends. The methods described are illustrated by examples for incidence rates of bladder cancer in Birmingham, U.K., mortality from bladder cancer in Italy, and mortality from lung cancer in Belgium.

Adult↗
PubMed1987

Models for temporal variation in cancer rates. II: Age-period-cohort models.

Our first paper reviewed methods for modelling variation in cancer incidence and mortality rates in terms of either period effects or cohort effects in the general multiplicative risk model. There we drew attention to the difficulty of attributing regular trends to either period or cohort influences. In this paper we turn to the more realistic problem in which neither period nor cohort effects alone lead to an adequate description of the data. We describe the age-period-cohort model and show how its ambiguities surrounding regular trends 'intensify'. We recommend methods for presenting the results of analyses based upon this model which minimize the serious risk of misleading implications and critically review previous suggestions. The discussion is illustrated by an analysis of breast cancer mortality in Japan with special reference to the phenomenon of 'Clemmesen's hook'.

Age Factors↗
PubMed1987

Empirical Bayes estimates of age-standardized relative risks for use in disease mapping.

There have been many attempts in recent years to map incidence and mortality from diseases such as cancer. Such maps usually display either relative rates in each district, as measured by a standardized mortality ratio (SMR) or some similar index, or the statistical significance level for a test of the difference between the rates in that district and elsewhere. Neither of these approaches is fully satisfactory and we propose a new approach using empirical Bayes estimation. The resulting estimators represent a weighted compromise between the SMR, the overall mean relative rate, and a local mean of the relative rate in nearby areas. The compromise solution depends on the reliability of each individual SMR and on estimates of the overall amount of dispersion of relative rates over different districts.

Age Factors↗