Estimating life expectancy of demented and institutionalized subjects from interval-censored observations of a multi-state model

Joly, Durand, Helmer and Commenges have a new paper in Statistical Modelling. This concerns the estimation of life expectancy in patients with dementia. Unlike similar analysis by Van den Hout and Matthews, here there are 5 states rather than 3 since they consider instiutionalization as an additional event. Age at death is known up to right-censoring but other transitions are interval censored. Like previous papers by Joly and Commenges, a penalized likelihood approach is taken. The penalized likelihood is approximated by cubic M-splines, with the degree of penalization chosen via an approximate cross-validation score. This allows smooth, flexible non-homogeneous intensities. A Markov assumption is assumed but semi-Markov models can also be fitted provided the model is progressive.

Life expectancies are found by integrating the estimated transition probabilities. Like Van den Hout and Matthews, a parametric bootstrap approach based on simulating from the asymptotic normal distribution of the parameters is used to obtain confidence bands. However, these will typically underestimate variability because the penalization factor is taken to be fixed.

Patient death as a censoring event or competing risk event in models of nursing home placement

Szychowski et al have a new paper in Statistics in Medicine. This looks at competing risks data where the event of interest is placement in a nursing home with death the other competing event. They compare the classical cause-specific-hazards regression approach with that of the Fine-Gray proportional subdistribution hazards model. The data were from a RCT on the effectiveness of an enhanced counseling and support invervention. The estimate of the effect of the intervention was similar in both cases (some evidence of a benefit in delaying admission to a nursing home). The authors attribute the similarity to a lack of a significant effect of the intervention on CSH of death. They recommend that both CSH and proportional subdistribution hazards approaches to covariate effect modelling should be considered.