Direct Cost Related to Stroke: A Longitudinal Analysis of Survivors After Discharge From a Rehabilitation Hospital.

BACKGROUND: After discharge from a rehabilitation hospital, stroke survivors and their families may face considerable stroke-related direct costs. The total amount could be ascribed to the costs of formal and informal care and to the equipment or materials needed for care. OBJECTIVES: This study aims to describe the direct costs incurred after a stroke by survivors during their first poststroke year and to analyze the basic predictors of these costs. METHODS: Stroke survivors (N = 415) were enrolled for this study during discharge from rehabilitation hospitals (baseline) and interviewed at 3, 6, 9, and 12 months after discharge for a longitudinal study. The trend of the direct costs incurred during the follow-up (from T1 to T4; n = 239) was evaluated using a linear mixed-effects model. The mixed-effects model was used to identify the baseline predictors of the incurred direct costs from the stroke survivors. RESULTS: During the first year after discharge, stroke survivors spent approximately $3700 on stroke-related direct (ie, medical and nonmedical) costs. The highest direct costs occurred during the first 6 months, although there was not a significant change over time. The higher direct costs incurred were predicted by the linear effect of time, by the educational level (higher vs low), and by the lower Barthel Index score, whereas a higher perceived cost was predicted only by the linear effect of time and by the lower Barthel Index score. CONCLUSION: In the first poststroke year, direct costs have remained stable over time and can be predicted by the level of education and physical functioning. The identification of specific direct cost predictors would be helpful for developing more socially and economically tailored interventions for stroke survivors in their first year after their stroke.

Survival probabilities with time-dependent treatment indicator: quantities and non-parametric estimators.

The 'landmark' and 'Simon and Makuch' non-parametric estimators of the survival function are commonly used to contrast the survival experience of time-dependent treatment groups in applications such as stem cell transplant versus chemotherapy in leukemia. However, the theoretical survival functions corresponding to the second approach were not clearly defined in the literature, and the use of the 'Simon and Makuch' estimator was criticized in the biostatistical community. Here, we review the 'landmark' approach, showing that it focuses on the average survival of patients conditional on being failure free and on the treatment status assessed at the landmark time. We argue that the 'Simon and Makuch' approach represents counterfactual survival probabilities where treatment status is forced to be fixed: the patient is thought as under chemotherapy without possibility to switch treatment or as under transplant since the beginning of the follow-up. We argue that the 'Simon and Makuch' estimator leads to valid estimates only under the Markov assumption, which is however less likely to occur in practical applications. This motivates the development of a novel approach based on time rescaling, which leads to suitable estimates of the counterfactual probabilities in a semi-Markov process. The method is also extended to deal with a fixed landmark time of interest.