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  • 标题:Survival Analysis of Breast Cancer Patients after Surgery with an Intermediate Event: Application of Illness-Death Model
  • 其他标题:Survival Analysis of Breast Cancer Patients after Surgery with an Intermediate Event: Application of Illness-Death Model
  • 本地全文:下载
  • 作者:Morteza HAJIHOSSEINI ; Javad FARADMAL ; Abdolazim SADIGHI-PASHAKI
  • 期刊名称:Iranian Journal of Public Health
  • 印刷版ISSN:2251-6085
  • 电子版ISSN:2251-6093
  • 出版年度:2015
  • 卷号:44
  • 期号:12
  • 页码:1677-1684
  • 语种:English
  • 出版社:Tehran University of Medical Sciences
  • 摘要:Background: Breast cancer (BC) is the second most commonly diagnosed cancer after lung cancer. Survival of BC patients is affected by intermediate events. This study was aimed to investigate the disease course of primary non-metastatic BC patients with first recurrence of the tumor (FRT) as the intermediate event using the illness- death model.Methods: This retrospective cohort study was conducted on 529 Iranian females with BC underwent surgery, from 1995 to 2013. Patients, tumor and treatment characteristics were collected from medical records of the patients. The illness-death model were used to investigate the relationship between these factors and survival time. Data were analyzed using version 3.1.1 of R software. Results: The risk of FRT in patients who had tumors size in the range of 2-5 cm and >5 cm was 1.3 and 3.5 times higher than that of patients with tumor size ≤2 cm, respectively (P<0.001). Furthermore, risk of death in patients aged ≥50 years was 1.6 times higher compared to patients aged less than 50 years (P =0.012). Risk of death after metastasis in patients with tumor size >5 cm was 2.1 times higher than patients with tumor size ≤2 cm (P =0.019).Conclusions: The stage of the disease and tumor size have statistically significant effects on patients’ survival before occurrence of the FRT. Furthermore, illness-death model was found to be a useful tool in modeling the disease course of BC patients. Keywords: Breast cancer, Intermediate events, Illness- death model, Survival analysis
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