Development of Prediction Models for Mortality in Japanese Heart Failure Patients

Heart failure (HF) is characterized by high morbidity and mortality. The older patient age, multiple comorbidities, and multiple patterns of disease progression are important targets of HF patient management. The prediction of HF patients' clinical course is difficult because the effects of demographic and clinical factors and their interactions are incompletely understood. In the previous studies, investigators have developed many models to predict adverse outcomes in patients with HF and these prognostic models would be beneficial for the development of treatment strategy for HF patients. However, all previous model were developed using US and European patients' data, application of these models for Japanese HF patients is not clear. Our objectives were to identify studies that evaluate the use of previous risk prediction models for mortality in Japanese patients with HF and to develop the original risk prediction model. To achieve our objectives, we performed a systematic review to identify studies evaluating the efficacy of risk prediction models for mortality in Japanese HF patients, and assessed their model performance by Cox proportional hazard model, Kaplan-Meier method, and the c statistic using the nation-wide registry database. (This study is supported by Practical Research Project for Life-Style related Diseases including Cardiovascular Diseases and Diabetes Mellitus in AMED).