Prognostic Factors for Recurrence And Survival of Patients with Breast Cancer Using A Multi-state Model

A Multi state Model of Breast Cancer

Authors

  • Maryam Rastegar 1-Department of Biostatistics, School of Health, Mashhad University of Medical Sciences, Mashhad, Iran/ 2-Department of Epidemiology & Biostatistics, Zahedan University of Medical Sciences, Zahedan, Iran
  • Zahra Arab Borzu Department of Epidemiology & Biostatistics, Zahedan University of Medical Sciences, Zaheda
  • Ahmad Reza Baghestani Physiotherapy Research Center, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
  • Roqayeh Aliyari Ophthalmic Epidemiology Research Center, Shahroud University of Medical Sciences, Shahroud, Iran
  • Ali Akhavan Isfahan University of Medical Sciences, Isfahan, Iran
  • Anahita Saeedi Department of Biostatistics, School of Public Health and Health Sciences, University of Massachusetts, Amherst, MA, USA

DOI:

https://doi.org/10.31661/gmj.v13i.3043

Keywords:

Multi-state Model; Survival Probability; Prognostic Factors; Breast Cancer

Abstract

Background: In many medical studies, patients may experience various events. The analysis in such studies is often administrated using multi-state models. The current study aimed to investigate the effect of risk factors and transition probability on recurrence and death in patients with breast cancer. Materials and Methods: This study was a retrospective cohort study on 814 women with breast cancer admitted to Shahid Ramezanzadeh Radiotherapy Center in Yazd province in Iran between the years 2004 -2012 and were followed until 2016. A multi-state model is applied for data analysis in the R 3.4.1 programming language. Results: Of the 814 patients, 40(5%) experienced recovery after initial treatment and 177(20.7%) experienced the death after initial treatment. For the first year, the transition probabilities from the initial treatment to recovery were estimated at 1.4%, to death was 17% and for recovery to death, it was 29%. The mean sojourn times were estimated as 2.93 and 9.8 years for the treatment and recovery, respectively. Conclusion: Multi-state models predict the transition probabilities in different states of disease, in addition, transition probabilities, mean sojourn time, and hazard ratio in each state can help physicians find suitable care for patients with breast cancer.

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Published

2024-09-17

Issue

Vol. 13 (2024): 2024: In Progress

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Original Article

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