Advanced Survival Analysis of Iranian Patients With Lung Cancer: A Prospective Cohort Study of Prognostic Factors Publisher



Moosazadeh M ; Nadi Ghara AA ; Gheibi M ; Janbabaei G ; Hedayatizadehomran A ; Alizadehnavaei R ; Shekarriz R ; Zaboli E ; Eslamijouybari M ; Ghadirzadeh E
Source: Iranian Journal of Health Sciences Published:2025

Abstract

Background and Purpose: Addressing survival in lung cancer (LC) patients is crucial because it directly informs prognosis, guides personalized treatment strategies, and highlights disparities in health care access. Understanding survival patterns and their determinants is crucial for enhancing patient outcomes, allocating resources efficiently, and advancing oncological research to develop more effective 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 aims to assess upto-date and comprehensive data from patients with LC living in Mazandaran Province, Iran by employing a diverse set of more sophisticated survival models. Materials and Methods: This prospective cohort study consisted of 708 patients with LC diagnosed between 2017 and 2019 and followed up until February 2023, registered in 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, logrank test, univariate, multivariate Cox proportional-hazards regression, multivariate Cox regression with time-varying covariates, and exponential proportional hazards (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%) died during the follow-up period. The mean age of LC patients was 64±12.42 years. The majority of patients were male (75%). Among them, 198 patients (27.97%) were older than 70 years old, and 31(4.38%), 24(3.39%), and 53(7.49%) 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 months, 54% at 1 year, 44% at 2 years, and 39% at 3 years. Tumor type was the most significant predictor of survival (hazard ratio [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. Additionally, time-varying analysis revealed 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 LC patients. © 2025 Elsevier B.V., All rights reserved.