Regression modeling of competing risk using R: an in depth guide for clinicians.

We describe how to conduct a regression analysis for competing risks data. The use of an add-on package for the R statistical software is described, which allows for the estimation of the semiparametric proportional hazards model for the subdistribution of a competing risk analysis as proposed by Fine and Gray. J Am Stat Assoc 1999; 94: 496-509.

Competing risk analysis using R: an easy guide for clinicians.

In the last decade with widespread use of quantitative analyses in medical research, close co-operation between statisticians and physicians has become essential from the experimental design through all phases of complex statistical analysis. On the other hand, easy-to-use statistical packages allow clinicians to perform basic statistical analyses themselves. Since the software they most commonly use does not perform in depth competing risk analysis, we recommend an add-on package for the R statistical software. We provide all the instructions for downloading it from internet and illustrate how to use it for analysis of a sample dataset of patients who underwent haematopoietic stem cell transplantation for acute leukaemia.

Prevalence of carotid stenosis in type 2 diabetic patients asymptomatic for cerebrovascular disease.

Stroke, with an incidence of 2.5 x 10(3) yr(-1) (95% CI, 2.3-2.8 x 10(3) yr(-1)), is the third most frequent cause of death and the first cause of disability in western society. Diabetes is an important risk factor for ischaemic stroke, second only to hypertension, whereas it does not seem to be associated with an increased risk of haemorrhagic stroke. The incidence of stroke in men and women between 45 and 74 yr has been found to be 2.5 and 3.5 times higher in diabetics than in non-diabetic subjects, with a relative risk higher in females than in males with diabetes and greater in both sexes in the 50-to-60-yr age group but decreased in subjects who were 70 and above. It is known that there is an association between ischaemic stroke and carotid stenosis. However, the prevalence of carotid stenosis in Type 2 diabetes mellitus (T2DM) patients has not been well investigated, mainly in the Italian diabetic population. Therefore, the aim of this study was to evaluate the prevalence of carotid artery stenosis in a population of T2DM patients asymptomatic for cerebrovascular disease selected from the files of the Diabetes Clinics, and from the computerised files of General Practitioners (GPs). Three hundred and sixty-five subjects were examined: 187 were non-diabetic (89 males, 98 females) and 178 were T2DM patients (82 males, 96 females). The mean age of all the subjects was 67 +/- 7.8 yr; 66 +/- 7.9 for the non-diabetic subjects and 67 +/- 7.5 yr in the diabetic subjects. In the echo-Doppler examination of the carotid, a degree of stenosis ranging 10-99% was recorded in 143/365 subjects (39.1%), 49/187 non-diabetics (26.2%) and 94/178 diabetics (52.8%). The differences were highly significant (p < 0.001). Severe stenosis was recorded in 17/143 subjects (12%); 12 of these were diabetic (70%) and 5 non-diabetic (30%). The diabetics were three times more likely to develop carotid stenosis than the non-diabetics with an odds ratio of 3.152, (95% CI, 2.032-4.889).