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Biomedical subjects

S Esbjerg

Publications and source records attributed to S Esbjerg.

4 recordsLinked to original sources
PubMed2000

Multi-state models for bleeding episodes and mortality in liver cirrhosis.

Data from a controlled clinical trial in liver cirrhosis are used to illustrate that multi-state models may be a useful tool in the analysis of data where survival is the ultimate outcome of interest but where intermediate, transient states are identified. We compare models for the marginal survival time distribution with models including transient states, both with respect to their clinical interpretation and with respect to the precision of survival probability estimates obtained from the various models.

Antihypertensive Agents↗
PubMed1999

Reporting delay and corrected incidence of multiple sclerosis.

The incidence of multiple sclerosis can be adjusted for reporting delay in a way similar to that for AIDS incidence as described in this paper. Two models are applied to data from the Danish Multiple Sclerosis Registry. The first simply describes the delay distribution, the second is a regression model. For the latter it is shown how goodness-of-fit assessment for both time-dependent and time-independent covariates can be handled using ideas from the Cox proportional hazards model. The goodness-of-fit analysis shows that people with onset age below 40 years and people with onset age from 40 years and above should be analysed separately and this is done throughout the paper. The incidences are adjusted with the two estimated delays and an estimate of the variance for the adjusted incidence is given. Finally the crude incidences are compared with the adjusted ones. We find that the incidence has been increasing since 1965 but mostly for people with onset age below 40 years.

Adult↗
PubMed1999

The graft versus leukemia effect after bone marrow transplantation: a case study using structural nested failure time models.

Over the last decade, J. M. Robins has developed a set of tools for assessing, from observational data, the causal effects of a time-dependent treatment or exposure in the presence of time-dependent covariates that may be simultaneously confounders and intermediate variables. This report concerns a case study of the application of one these techniques, G-estimation using structural nested failure time models, to the problem of assessing the effect of graft versus host disease on leukemia relapse after bone marrow transplantation.

Biometry↗