ArticleAsian Pacific journal of cancer prevention : APJCP2017
Cox Regression and Parametric Models: Comparison of How They Determine Factors Influencing Survival of Patients with Non-Small Cell Lung Carcinoma
Article in Asian Pacific journal of cancer prevention : APJCP, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- NUF2 Is a Potential Immunological and Prognostic Marker for Non-Small-Cell Lung Cancer.Journal of immunology research · 2022Article
- A three-mRNA status risk score has greater predictive ability compared with a lncRNA-based risk score for predicting prognosis in patients with hepatocellular carcinoma.Oncology letters · 2020Article
- [Survival and prognostic factors of non-small-cell lung cancer among young people in central Tunisia].The Pan African medical journal · 2020Article
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4 authors.
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Abstract
Background and objectives: The present study of survival rate of patients with non-small cell carcinoma (NSCLC) compared the efficiency of Cox semi-parametric vs. parametric models in determination of influencing factors. Methods: In this retrospective cohort study, data were gathered from 190 patients with a confirmed diagnosis of NSCLC referred to Shahid Sadoughi and Shohadaye Kargar Hospitals in Yazd, Iran during 2005 to 2014. To identify and compare factors influencing the survival rate, a Cox semi-parametric model was fitted to the data. Data analysis was performed using the R software version R3.3.1, and the significance level was set at 0.05. Results: The average age was 64.5 years. About 40% of patients had stage 4 disease. The median survival was 8 months. After comparing the models, the more efficient was the log-normal distribution (AIC=889.3829), with which disease stage, type of therapy, and age were significant factors. Among the different types of therapy, chemotherapy and radiotherapy yielded higher survival rates, and increased age was associated with lower survival. Conclusion: The most efficient model was a log-normal model. Implementation of optimal therapies at early stages can improve the survival of patients.
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