Association Between Comorbidity Clusters and Mortality in Patients With Cancer: Predictive Modeling Using Machine Learning Approaches of Data From the United States and Hong Kong.

Journal: JMIR cancer
Published Date: Jul 16, 2025

Abstract

BACKGROUND: Patients with cancer and cancer survivors often experience multiple chronic health conditions, which can impact symptom burden and treatment outcomes. Despite the high prevalence of multimorbidity, research on cancer prognosis has predominantly focused on cancers in isolation. There is growing interest in machine learning techniques for cancer studies. However, these methods have not been applied in the context of supportive care for patients with cancer who have multimorbidity. Furthermore, few studies have investigated the associations between comorbidity clusters and mortality outcomes.

Authors

  • Chun Sing Lam
    School of Pharmacy, Faculty of Medicine, Chinese University of Hong Kong, 8th Floor, Lo Kwee-Seong Integrated Biomedical Sciences Building, Area 39, The Chinese University of Hong Kong, Shatin, N.T, Hong Kong, China, 852 39436833.
  • Rong Hua
    Division of Esophageal Surgery, Department of Thoracic Surgery, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China.
  • Herbert Ho-Fung Loong
    Department of Clinical Oncology, Faculty of Medicine, Chinese University of Hong Kong, Hong Kong, China.
  • Chun-Kit Ngan
    Worcester Polytechnic Institute, USA.
  • Yin Ting Cheung
    School of Pharmacy, Faculty of Medicine, Chinese University of Hong Kong, 8th Floor, Lo Kwee-Seong Integrated Biomedical Sciences Building, Area 39, The Chinese University of Hong Kong, Shatin, N.T, Hong Kong, China, 852 39436833.

Keywords

External Resources

Popular Topics
Recent Journals