Risk factor structure of heart failure in patients with cancer after treatment with anticancer agents' assessment by big data from a Japanese electronic health record

Abstract

As the prognosis of cancer patients has been improved, comorbidity of heart failure (HF) in cancer survivors is a serious concern, especially in the aged population. This study aimed to examine the risk factors of HF development after treatment by anticancer agents, using a machine learning-based analysis of a massive dataset obtained from the electronic health record (EHR) in Japan. This retrospective, cohort study, using a dataset from 2008 to 2017 in the Diagnosis Procedure Combination (DPC) database in Japan, enrolled 140,327 patients. The structure of risk factors was determined using multivariable analysis and classification and regression tree (CART) algorithm for time-to-event data. The mean follow-up period was 1.55 years. The prevalence of HF after anticancer agent administration were 4.0%. HF was more prevalent in the older than the younger. As the presence of cardiovascular diseases and various risk factors predicted HF, CART analysis of the risk factors revealed that the risk factor structures complicatedly differed among different age groups. The highest risk combination was hypertension, diabetes mellitus, and atrial fibrillation in the group aged ≤ 64 years, and the presence of ischemic heart disease was a key in both groups aged 65-74 years and 75 ≤ years. The machine learning-based approach was able to develop complicated HF risk structures in cancer patients after anticancer agents in different age population, of which knowledge would be essential for realizing precision medicine to improve the prognosis of cancer patients.

Keywords: Anticancer agents; Electronic health record; Epidemiology; Heart failure; Machine learning.

Fig. 1

Enrollment of patients treated for cancer and identification of incidences of HF in this study. Patients with cancer were enrolled in this study on the first day of anticancer agent administration. Patients with or without HF diagnosis were selected as depicted

Fig. 2

Cumulative probability of HF after anticancer treatment stratified by age. Cumulative probability of HF within 5 years of anticancer therapy in different age groups:  ≤ 64 years, 65–74 years, and  ≥ 75 years

Fig. 3

CART analysis of risk factors for HF development. Risk factors for HF development in indicated age groups according to CART analysis. Patients were stratified according to the presence (y) or absence (n) of the corresponding risk factors. The number (N) of all patients and those who developed HF after starting the administration of anticancer agents (HF) are shown. The combinatorial risk, assessed by the relative hazard ratio (RHR), was expressed relative to the lowest hazard ratio in each age group. The combinatorial risk was stratified and color-coded into low- (1 ≤ RHR < 2, yellow), medium- (2 ≤ RHR < 3, orange), and high-risk (3 ≤ RHR, red) groups. The rightmost panels indicate RHR (red bars) and 95% confidence intervals (blue bars). *P < 0.05 and ***P < 0.001 compared to the lowest risk group (RHR = 1) in each age group

Fig. 4

Graphical summary of risk structures for HF development. The risk factors for HF after treatment with anticancer agents formed context-dependent structures that were distinct among different age groups