Showing 3 results for Competing Risk
M Asghari Jafarabadi, E Hajizadeh, A Kazemnejad, Sr Fatemi,
Volume 6, Issue 3 (12-2010)
Abstract
Background & Objectives: Cholera is always being considered as a public health threat in poor and developing countries. However outbreaks of cholera are not very common in central area of Iran in 2008 district health authority reported a cluster of diarrhea cases. We investigated this cluster to identify the etiological agent, source of transmission and propose control measures.
Methods: We analyzed the data of total of 1219 patients with colorectal cancer who registered between 1 January 2002 to 1 October 2007. Data were analyzed using univariate and multivariate Accelerated Failure Time (AFT) parametric survival model with frailty, utilizing STATA statistical software.
Results: In the univariate analysis for age at diagnosis, gender, marital status, race and education level, the survival of patients with colon cancer were approximately between half to one fourth and for BMI, alcohol history, Inflammatory Bowel Disease (IBD), familial history of cancer and the pathologic stage of tumor, the survival of patients with colon cancer were significantly (between 0.12 to 0.56 times) shorter than those patients with rectal cancer. In the multivariate analysis, for age at diagnosis (45-65 years), there was significant difference between colon and rectum cancer. But for BMI, alcohol history, IBD and pathologic stage there were not significant differences. The adjusted survival and 1, 2, 3, 4 and 5 year survival of patients with rectal cancer were better than those with colon cancer.
Conclusions: Site-specific evaluation of colon and rectum could give a better perspective of factors affecting these cancers. It may help to design of clinical trials, better diagnosis of diseases and optimal administration of specific treatments.
Ma Akhoond, A Kazemnejad, E Hajizadeh, Sr Fatemi, A Motlagh,
Volume 6, Issue 4 (3-2011)
Abstract
Background & objectives: Competing risk data is one of the multivarite survival data. Competing risk data can be modelled using copula function. In this study we propose a bayesian modelling approach of competing risk data using the copula function.
Methods: We used the data from colorectal cancer registyrarty in Tehran. After constructing likelihood function using Clayton copula by choosing appropriate prior distribution for parameters, we obtained the posterior distribution of parameters using the Metropolis-Hastings algorithms and Slice sampling.
Results: The results of univariate analysis showed that sex, histology of tumor, extent of wall penetration, lymph node metastasis, distant metastasis and pathological stage of tumor were significantly associated with colon cancer and sex, histology of tumor, lymph node metastasis, distant metastasis and pathological stage of tumor were were significantly related to rectal cancer. In the multivariate analysis, age at diagnosis, tumor grade and distant metastasis were significant prognostic factors for colon cancer and tumor grade and size of the tumor were significant prognostic factors of rectal cancer
Conclusions: As we showed some variables may have different impacts on colon and rectum cancers, consequently, further studies are needed to be conducted considering risk factors of these cancers separately.
Malihe Safari, Salman Khazaei, , Mohammad Abbasi, Ghodratollah Roshanaei,
Volume 17, Issue 2 (9-2021)
Abstract
Background and Objectives: The incidence of rectal cancer is increasing in developing societies, especially in younger age groups. The aim of this study was to evaluate the factors affecting the survival of patients with rectal cancer in the presence of competing risks.
Methods: In this retrospective cohort study, the data of 121 patients with rectal cancer during 2001-2017 were studied. Death related to cancer progression was considered as the interest outcome and other causes of death were considered as competing risks. Cause-specific and sub-distribution hazard models were used to investigate the factors affecting patient survival in the presence of competing risk.
Results: The mean (SD) age of the patients was 53.4 (13.9) years and 68 patients (56.2%) were male. The results of log-rank test showed that sex, age, metastasis, type of first treatment, rate of penetration into intestinal wall, tumor location, number of lymphomas involved and tumor size had significant effects on the patient survival (P<0.05). Based on cause-specific and sub-distribution hazard models, tumor stage, lymph node metastasis, and tumor grade had significant effects on death hazard due to the cancer progression (P<0.05).
Conclusion: Due to the need to consider competing risks, the results of both competing risk methods showed that tumor grade, lymph node metastasis and stage increased the instantaneous hazard and hazard of cancer death. Therefore, to determine the specific risk factors for each cause of death in the survival analysis, competing risk methods should be used if there is more than one cause of death.
