Iranian Journal of

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Background and Objectives: The aim of this study was to analyze the risks of local recurrence, second primary tumor, and metastasis in oral squamous cell carcinoma (OSCC) patients and to present their prognosis after treatment.

Methods: In this retrospective cohort study, 147 patients with oral squamous cell carcinoma (OSCC) who were older than 40 years were included using the data of 1973–2010 Surveillance, Epidemiology, and End Results (SEER) Program in the United States. The variables included gender, race, stage, histologic grade, tumor site, treatment modalities, and dates of diagnosis and death. Markov Multistate model was used for analysis.

Results: At a median follow-up of 33 months, local recurrence, second primary tumor, and distant metastasis rates were 34.01%, 85.03%, and 17.01% respectively and 40.13% of the patients died. Patients with cervical lymph nodes were at risk of second primary tumor 1.37 (1.05-2.05) times higher than early stage patients and were 2.33 (1.29-4.18) times more likely to die. After one year, the risk of death for patients with local recurrence or second primary tumor was almost similar but after 5 years, the risk of death was higher for local recurrence than second primary tumor.

Conclusion: Awareness of the next state and its time with respect to the patient’s clinical status can be one of the appropriate methods for timely diagnosis and treatment to reduce the mortality rate of OSCC patients.

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Background and Objectives: Breast cancer is the leading cause of death from cancer among women. In developing countries, the patients’ survival is less than developed countries. Metastasis, as an intermediate event, affects the survival of breast cancer patients. This study aimed to evaluate the survival of patients after surgery considering metastasis, as the intermediate event, using the illness-death model.
Methods: In this study, 165 cases of Iranian breast cancer patients who underwent surgery during 2006-2014 were investigated. The patients’ characteristics and their intermediate and final status were collected from their medical records. The illness-death model was used to assess prognostic factors in all stages of disease.
Results: The risk of metastasis in patients with tumor size between 2-5 cm was 3.8 times higher than patients whose tumors were below 2 cm (P=0.009). Patients who had 3 to 6 lymph nodes involved were 3.1 times more likely to have metastases that those with less than 2 lymph nodes (P=0.003). Also, the grade of tumor and HER-2 had a significant role in metastasis (P=0.04).
Conclusion: Using the illness-death model that is suitable for the analysis of such data, it was found that lymph node involved and tumor size had a significant role in metastasis. So, early detection of cancer is required to prevent metastasis and death.

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Background and Objectives: In survival analysis, using the Cox model to determine the effective factors requires the assumptions whose failure of leads to biased results. The aim of this paper was to determine the factors affecting the survival of metastatic gastric cancer patients using the non-parametric method of Randomized Survival Forest (RSF) model and to compare its result with the Cox model.
 
Methods: In this retrospective cohort study, 201 patients with metastatic gastric cancer were evaluated in Hamadan Province. Patient survival was calculated from diagnosis to death or end of study. Demographic characteristics (such as gender and age) and clinical variables (including stage, tumor size, etc.) were extracted from the patient records. Factors affecting survival were determined using the Cox model and RSF. Data analysis was performed using the R3.4.3 software and RandomForestSRC and survival packages.
 
Results: The mean (SD) age of patients was 61.5 (12.9) years old. The Cox model showed that chemotherapy (p=0.033) was effective in survival, and the results of fitting the RSF model showed that the most important variables affecting survival were type of surgery, location of metastasis, chemotherapy, age, tumor grade, surgery, number of involved lymph nodes, sex and radiotherapy. Based on the model appropriateness, the RSF model with log-rank split rule had a better performance compared to the Cox model.
 
Conclusion: If the number of variables is high and there is a relationship between the variables, the RSF method identifies the important and effective variables on survival with high accuracy without requiring restrictive assumptions compared to the Cox model.