A prediction model for one- and three-year mortality in dementia: results from a nationwide hospital-based cohort of 50,993 patients in the Netherlands

Abstract

OBJECTIVE: to develop a model to predict one- and three-year mortality in patients with dementia attending a hospital, through hospital admission or day/memory clinic. DESIGN: we constructed a cohort of dementia patients through data linkage of three Dutch national registers: the hospital discharge register (HDR), the population register and the national cause of death register. SUBJECTS: patients with dementia in the HDR aged between 60 and 100 years registered between 1 January 2000 and 31 December 2010. METHODS: logistic regression analysis techniques were used to predict one- and three-year mortality after a first hospitalisation with dementia. The performance was assessed using the c-statistic and the Hosmer-Lemeshow test. Internal validation was performed using bootstrap resampling. RESULTS: 50,993 patients were included in the cohort. Two models were constructed, which included age, sex, setting of care (hospitalised versus day clinic) and the presence of comorbidity using the Charlson comorbidity index. One model predicted one-year mortality and the other three-year mortality. Model discrimination according to the c-statistic for the models was 0.71 (95% CI 0.71-0.72) and 0.72 (95% CI 0.72-0.73), respectively. CONCLUSION: both models display acceptable ability to predict mortality. An important advantage is that they are easy to apply in daily practise and thus are helpful for individual decision-making regarding diagnostic/therapeutic interventions and advance care planning.