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3 results on '"Mahmood Reza, Ghadimi"'

1. Prognostic factors for the survival of patients with esophageal cancer in Northern Iran

Author

Mahmood Reza Ghadimi, Mahboobeh Rasouli, Mahmood Mahmoodi, and Kazem Mohammad

Subjects
Esophageal Cancer, Survival Analysis, Univariate Gamma Frailty Model, Parametric Model, Medicine
Abstract

Background: Esophageal cancer is the 8 th most common cancer and the 6 th leading cause of cancer-related death, worldwide. In Iran, the high incidence rates of this type of cancer have been reported from the Caspian Sea region. This study aimed at assessing the factors affecting survival of patients with esophageal cancer in neighbor provinces around Caspian Sea using parametric and semi-parametric models with univariate gamma frailty model. Methods: In this study, we performed a prospective review of 359 patients presenting with esophageal cancer from 1990 to 1991. The data were obtained using the Cancer Registry information existed in Babol research center in Iran. Study participants were followed-up until 2006 for a period of 15 years. Hazard ratio was used to interpret the risk of death. The Akaike Information Criterion (AIC) was considered as a criterion to select the best model(s). Results: Of the 359 patients, 225 (62.7%) were male with a mean age of 60.0 years and 134 (37.3%) were female with a mean age of 55.3 at the time of diagnosis. 1- , 3- and 5-year survival rates after diagnosis were 23%, 15% and 13% , respectively. Comparison between Cox and parametric models of AIC showed that the overall fitting was improved under parametric models. Among parametric models, the log-logistic model with gamma frailty provided better performance than other models. Using this model, we found that gender (p=0.012) and family history of cancer (p= 0.003) were significant predictors. Conclusions: Since the proportionality assumption of the Cox model was not held (p = 0.01), the Cox regression model was not an appropriate choice for analyzing our data. According to our findings, log logistic model with gamma frailty could be considered as a useful statistical model in survival analysis of patients with esophageal cancer rather than Cox and log-normal models.

Published
2011

2. Factors affecting survival of patients with oesophageal cancer: a study using inverse Gaussian frailty models

Author

Mahmood Reza, Ghadimi, Mahmood, Mahmoodi, Kazem, Mohammad, Mahboobeh, Rasouli, Hojjat, Zeraati, and Akbar, Fotouhi

Subjects
Male, Models, Statistical, Esophageal Neoplasms, Iran, Middle Aged, Prognosis, Sex Factors, Risk Factors, Humans, Female, Developing Countries, Aged, Follow-Up Studies, Proportional Hazards Models, Retrospective Studies
Abstract

Oesophageal cancer is one of the most common causes of cancer mortality in developing countries, including Iran. This study aimed to assess factors affecting survival of patients with oesophageal cancer using parametric analysis with frailty models.Data on 359 patients with oesophageal cancer was collected from the Babol Cancer Registry for the period 1990-1991. By 2006, the patients had been followed up for a period of 15 years. Hazard ratio was used to interpret the risk of death. To explore factors affecting the survival of patients, log-normal and log-logistic models with frailty were examined. The Akaike Information Criterion (AIC) was used for selecting the best model(s). Cox regression was not suitable for this patient group, as the proportionality assumption of the Cox model was not satisfied by our data (p = 0.007).Multivariate analysis according to parametric models showed that family history of cancer might increase the risk of death from cancer significantly. Based on AIC scores, the log-logistic model with inverse Gaussian frailty seemed more appropriate for our data set, and we propose that the model might prove to be a useful statistical model for the survival analysis of patients with oesophageal cancer. The results suggested that gender and family history of cancer were significant predictors of death from cancer.Early preventative care for patients with a family history of cancer may be important to decrease the risk of death in patients with oesophageal cancer. Male gender may be associated with a lower risk of death.

Published
2012

3. Survival analysis of patients with esophageal cancer using parametric cure model

Author

Mahboube, Rasouli, Mahmood Reza, Ghadimi, Mahmood, Mahmoodi, Kazem, Mohammad, Hojjat, Zeraati, and Mostafa, Hosseini

Subjects
Male, Survival Rate, Treatment Outcome, Esophageal Neoplasms, Humans, Female, Registries, Iran, Middle Aged, Survival Analysis, Follow-Up Studies, Proportional Hazards Models
Abstract

Esophageal cancer is a major cause of mortality and morbidity in the Caspian littoral north-eastern part of Iran. The aim of this study was to calculate cure function as well as to identify the factors that are related to this function among patients with esophageal cancer in this geographical area.Three hundred fifty nine cases of esophageal cancer registered in the Babol cancer registry during the period of 1990 to 1991 (inclusive) were followed up for 15 years up to 2006. Parametric cure model was used to calculate cure fraction and investigate the factors responsible for probability of cure among patients.Sample of subjects encompassed 62.7% men and 37.3% women, with mean ages of diagnosis was 60.0 and 55.3 years, respectively. The median survival time reached about 9 months and estimated survival rates in 1, 3, and 5 years following diagnosis were 23%, 15% and 13%, respectively. Results show the family history affects the cured fraction independently of its effect on early outcome and has a significant effect on the probability of uncured. The average cure fraction was estimated to be 0.10.As the proportionality assumption of Cox model does not meet in certain circumstances, a parametric cure model can provide a better fit and a better description of survival related outcome.

Published
2012

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