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Biomedical subjects

Patrick Royston

Publications and source records attributed to Patrick Royston.

6 recordsLinked to original sources
PubMed2003

Novel designs for multi-arm clinical trials with survival outcomes with an application in ovarian cancer.

With the increasing pace of drug development, it is not unusual for several promising treatment regimens to be ready simultaneously for testing in a randomized phase III setting. Various limiting factors, including the time needed to transfer research results to clinical practice and a narrow 'window of opportunity', may make it unfeasible to perform trials to test such regimens sequentially against a control treatment in a traditional two-arm parallel group design. We present an approach to trial design based on eliminating inferior contenders at an early stage, allowing through to a second stage only treatments that show a predefined degree of advantage against a control treatment. The first stage of testing utilizes a marker known to be a valid intermediate outcome measure or surrogate for the definitive outcome. The experimental arms are compared pairwise with control according to this intermediate outcome measure. Arms that survive the comparison enter a second stage of patient accrual culminating in comparisons against control on the outcome measure of primary interest. We show how the design may be realized in practice by considering hypothetically distinct trials at stages 1 and 2, each with their own operating characteristics. The overall operating characteristics are computed from the stage 1 and 2 size and power and the correlation between the treatment effects on the intermediate and primary outcome measures according to a bivariate Normal approximation. The correlation is estimated by bootstrapping individual patient data from previous trials. We illustrate the general approach in a design of a real trial of four new chemotherapy regimens for advanced ovarian cancer. The intermediate outcome measure is progression-free survival. An international randomized controlled trial using the new design is already under way.

Clinical Trials as Topic↗
PubMed2003

Non-linear models for the relation between cardiovascular risk factors and intake of wine, beer and spirits.

It is generally accepted that moderate consumption of alcohol is associated with a reduced risk of coronary heart disease (CHD). It is not clear however whether this benefit is derived through the consumption of a specific beverage type, for example, wine. In this paper the associations between known CHD risk factors and different beverage types are investigated using a novel approach with non-linear modelling. Two types of model are proposed which are designed to detect differential effects of beverage type. These may be viewed as extensions of Box and Tidwell's power-linear model. The risk factors high density lipoprotein cholesterol, fibrinogen and systolic blood pressure are considered using data from a large longitudinal study of British civil servants (Whitehall II). The results for males suggest that gram for gram of alcohol, the effect of wine differs from that of beer and spirits, particularly for systolic blood pressure. In particular increasing wine consumption is associated with slightly more favourable levels of all three risk factors studied. For females there is evidence of a differential relationship only for systolic blood pressure. These findings are tentative but suggest that further research is required to clarify the similarities and differences between the results for males and females and to establish whether either of the models is the more appropriate. However, having clarified these issues, the apparent benefit of consuming wine instead of other alcoholic beverages may be relatively small.

Adult↗
PubMed2002

Simplifying a prognostic model: a simulation study based on clinical data.

Prognostic models are designed to predict a clinical outcome in individuals or groups of individuals with a particular disease or condition. To avoid bias many researchers advocate the use of full models developed by prespecifying predictors. Variable selection is not employed and the resulting models may be large and complicated. In practice more parsimonious models that retain most of the prognostic information may be preferred. We investigate the effect on various performance measures, including mean square error and prognostic classification, of three methods for estimating full models (including penalized estimation and Tibshirani's lasso) and consider two methods (backwards elimination and a new proposal called stepdown) for simplifying full models. Simulation studies based on two medical data sets suggest that simplified models can be found that perform nearly as well as, or sometimes even better than, full models. Optimizing the Akaike information criterion appears to be appropriate for choosing the degree of simplification.

Aortic Aneurysm, Abdominal↗
PubMed2002

Flexible parametric proportional-hazards and proportional-odds models for censored survival data, with application to prognostic modelling and estimation of treatment effects.

Modelling of censored survival data is almost always done by Cox proportional-hazards regression. However, use of parametric models for such data may have some advantages. For example, non-proportional hazards, a potential difficulty with Cox models, may sometimes be handled in a simple way, and visualization of the hazard function is much easier. Extensions of the Weibull and log-logistic models are proposed in which natural cubic splines are used to smooth the baseline log cumulative hazard and log cumulative odds of failure functions. Further extensions to allow non-proportional effects of some or all of the covariates are introduced. A hypothesis test of the appropriateness of the scale chosen for covariate effects (such as of treatment) is proposed. The new models are applied to two data sets in cancer. The results throw interesting light on the behaviour of both the hazard function and the hazard ratio over time. The tools described here may be a step towards providing greater insight into the natural history of the disease and into possible underlying causes of clinical events. We illustrate these aspects by using the two examples in cancer.

Antineoplastic Agents↗
PubMed2002

Autosomal genome-wide scan for coronary artery calcification loci in sibships at high risk for hypertension.

Coronary artery disease (CAD) is the leading cause of mortality in the developed world. Although several CAD risk factors, including measures of lipid metabolism, obesity, and blood pressure, have a genetic basis, many genes for CAD susceptibility have yet to be identified. Coronary atherosclerosis is the major cause of CAD, but many with coronary atherosclerosis lack symptoms. Thus, a major limitation of using symptomatic CAD endpoints (eg, sudden coronary death, myocardial infarction) as a study outcome is substantial disease misclassification. Coronary artery calcification (CAC) is part of the atherosclerotic process and is an independent predictor of CAD endpoints. In the present study, CAC was noninvasively quantified by electron beam computed tomography. We performed genome-wide multipoint mode-of-inheritance-free linkage analysis on affected sib pairs, defined as being > or = the 70th sex- and age-specific percentile for CAC quantity, in a sample of 29 families enriched for hypertension. Almost 95% of participants were asymptomatic for CAD. Our LOD score (log10 odds in favor of linkage) results provide evidence that chromosomal regions 6p21.3 (maximum LOD score=2.22, P=0.00070) and 10q21.3 (maximum LOD score=3.24, P=0.000057) may harbor genes associated with subclinical coronary atherosclerosis.

Adult↗