Iranian Journal of Health Sciences، جلد ۱۳، شماره ۳، صفحات ۰-۰

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عنوان انگلیسی Advanced Survival Analysis of Iranian Lung Cancer Patients: Prospective Cohort Study of Prognostic Factors
چکیده انگلیسی مقاله
Background and purpose: Addressing survival in lung cancer patients is crucial because it directly informs prognosis, guides personalized treatment strategies, and highlights disparities in healthcare access. Understanding survival patterns and their determinants is key to improving patient outcomes, allocating resources effectively, and advancing oncological research for better therapies and early detection methods. Thus, given the existing gaps in literature regarding different survival rates and disparities in the impact of demographical and clinical factors such as age, gender, residence, and tumor type on survival, the present study aimed to assess up-to-date and comprehensive data from lung cancer (LC) patients in Mazandaran province by employing a diverse set of more sophisticated survival models.
Materials and Methods: This prospective cohort study consisted of 708 LC patients diagnosed between 2017 and 2019 and followed up until February 2023 from the Cancer Registry Center of Mazandaran University of Medical Sciences using census-based sampling. For survival analysis, non-parametric, semi-parametric, and parametric models such as Kaplan-Meier survival curves, log-rank test, Univariate, multivariate cox proportional-hazards regression, multivariate cox regression with time-varying covariates, and Exponential PH model with Gamma Frailty Distribution models were used on variables including age, gender, residential area, and tumor type.
Results: Out of 708 LC patients, 431 (61.02%) patients died during the follow up period. Mean age of LC patients was 64 ± 12.42 years. Majority of patients were male (75%), 198 (27.97%) patients were older than 70 years old, and 31 (4.38%), 24 (3.39%), and 53 (7.49%) patients had well differentiated, moderately differentiated, and poorly differentiated tumors, respectively. The Exponential PH model with Gamma Frailty Distribution was selected and presented as the best fitting parametric model. The overall survival rate was 69% at 6 month, 54% at 1 year, 44% at 2 years, and 39% at 3 years. Tumor type was the most significant predictor of survival (HR: 1.98, 95%CI: 1.32-2.95 for small cell LC in comparison to non-small LC). However, age, gender, and residential location had no significant association with survival. Also, time-varying analysis uncovered that the influence of tumor type diminishes over the course of follow-up (HR: 0.998, 95%CI: 0.997-0.998).
Conclusion: This study highlights the importance of utilizing advanced models and time-varying analyses to identify factors influencing the survival of lung cancer patients.
کلیدواژه‌های انگلیسی مقاله Lung Neoplasm, Survival Analysis, Proportional Hazards Models

نویسندگان مقاله | Mahmood Moosazadeh
Gastrointestinal Cancer Research Center, Non-Communicable Diseases Institute, Mazandaran University of Medical Sciences, Sari, Iran.


| Ali Asghar Nadi Ghara
Health Sciences Research Center, Mazandaran University of Medical Sciences, Sari, Iran.


| Mobina Gheibi
Gastrointestinal Cancer Research Center, Non-Communicable Diseases Institute, Mazandaran University of Medical Sciences, Sari, Iran.


| Ghasem Janbabaei
Hematologic Malignancies Research Center, Research Institute for Oncology, Hematology and Cell Therapy, Tehran University of Medical Sciences, Tehran, Iran.


| Akbar Hedayatizadeh Omran
Gastrointestinal Cancer Research Center, Non-Communicable Diseases Institute, Mazandaran University of Medical Sciences, Sari, Iran.


| Reza Alizadeh-Navaei
Gastrointestinal Cancer Research Center, Non-Communicable Diseases Institute, Mazandaran University of Medical Sciences, Sari, Iran.


| Ramin Shekarriz
Department of Hematology and Oncology, Gastrointestinal Cancer Research Center, Non-Communicable Diseases Institute, Mazandaran University of Medical Sciences, Sari, Iran.


| Ehsan Zaboli
Department of Hematology and Oncology, Gastrointestinal Cancer Research Center, Non-Communicable Diseases Institute, Mazandaran University of Medical Sciences, Sari, Iran.


| Mohammad Eslami Jouybari
Department of Hematology and Oncology, Gastrointestinal Cancer Research Center, Non-Communicable Diseases Institute, Mazandaran University of Medical Sciences, Sari, Iran.


| Erfan Ghadirzadeh
Gastrointestinal Cancer Research Center, Non-Communicable Diseases Institute, Mazandaran University of Medical Sciences, Sari, Iran.



نشانی اینترنتی http://jhs.mazums.ac.ir/browse.php?a_code=A-10-1179-1&slc_lang=en&sid=1
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