Developing a Simple Conceptual Causal Model for Predicting Early Recurrence and Mortality after Curative Surgery for Colorectal Cancer Patients

  • Samira Ahmadi Social Determinants of Health Research Center, Health and Metabolic Diseases Research Institute, Zanjan University of Medical Sciences, Zanjan, Iran.
  • Shayesteh Alinia Department of Statistics and Epidemiology, School of Medicine, Zanjan University of Medical Sciences, Zanjan, Iran.
  • Zahra Mohammadi Department of Statistics and Epidemiology, School of Medicine, Zanjan University of Medical Sciences, Zanjan, Iran.
  • Farzaneh Rastkar Shirvandeh Student Research Committee, Department of Statistics and Epidemiology, School of Medicine, Zanjan University of Medical Sciences, Zanjan, Iran
  • Mohammad Asghari-Jafarabadi Cabrini Research, Cabrini Health, VIC 3144, Australia.
  • Leila Mahmoudi Department of Statistics and Epidemiology, School of Medicine, Zanjan University of Medical Sciences, Zanjan, Iran.
  • Malihe Safari Department of Biostatistics, Medicine School, Arak University of Medical Sciences, Arak, Iran.
  • Ghodratollah Roshanaei Modeling of Non-Communicable Diseases Research Canter, Department of Biostatistics, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran.
Keywords: Generalized structural equation model; Conceptual causal model; Accelerated failure time; Early recurrence; Colorectal cancer

Abstract

Introduction: Colorectal cancer (CRC) represents the second leading cause of cancer-related mortality. This study focused on the development of a robust conceptual causal model designed to predict early recurrence and mortality following curative surgery in colorectal cancer patients.

Methods: In this retrospective cohort study, we included 284 patients with colorectal cancer (CRC) who underwent surgery at the Imam Khomeini (RA) Clinic in Hamadan, Iran, between 2001 and 2017. Demographic characteristics, treatment modalities, and other relevant data were extracted from patient records. Predictors were analyzed using Generalized Structural Equation Modeling (GSEM) for survival analysis, employing an accelerated failure time (AFT) approach. Both unadjusted and adjusted time ratios (TRs) were calculated using STATA software.

Results: The results of our developed causal model indicated that receiving chemotherapy was significantly associated with a shorter survival time ratio (TR = 0.415, 95% CI: 0.290-0.593), and recurrence time (TR = 0.363, 95% CI: 0.190-0.696). Conversely, patients who underwent multiple chemotherapy sessions exhibited a longer survival time (TR = 2.130, 95% CI: 1.790-2.534) and recurrence time (TR = 2.206, 95% CI: 1.609- 3.023). Age had a direct impact on the recurrence time (TR = 0.758, 95% CI: 0.602-0.955). Additionally, age had a significant direct effect on the receipt of chemotherapy, the cancer site, and the receipt of radiotherapy.

Conclusion: In summary, our study's causal model reveals that chemotherapy shortens survival time but multiple sessions can extend both survival and recurrence times. Age significantly affects recurrence time and chemotherapy receipt. These findings highlight the importance of personalized treatment strategies in colorectal cancer management

 

Published
2025-01-18
Section
Articles