EXPLORATORY ANALYSIS OF SURVIVAL RATE MORTALITY AMONG ELDERLY LUNG CANCER PATIENTS UTILIZING DIFFERENT TREATMENT PLANS

Abstract

Regardless of medical innovations and improvements of cancer treatment modalities, the survival rate of lung cancer remains low. Nearly 44% of patients diagnosed with lung cancer survive for one year after the initial diagnosis is confirmed. The objective of this study was to explore the impact of different lung cancer treatment plans on survival and mortality rates. The SEER database was used to extract the study population. Descriptive statistics and trend charts from 2000 to 2016 were generated. Linear regression was applied among lung cancer patients to evaluate the association between the length of survival and treatment utilization. In addition, logistic regression was applied to explore the association between treatment types and odds of dying among lung cancer patients. Over 800,000 patients, 50 years or older, diagnosed with lung cancer were included in the study. Overall, the number of lung cancer cases increased by 7% from 2000 to 2016. The average annual frequency was 48,529 cases per year. Lung cancer was more prevalent among patients aged between 70 to 79 years old. The majority of the study population were Whites (84%), and males accounted for 53%. Survival, mortality, and treatment utilization varied over the years based on age, gender, race, clinical characteristics, and social status. Five-year survival rate was less than 10% among the study population, and 84% of included lung cancer patients died. Chemotherapy was more commonly used, followed by radiation then surgical interventions. Based on the regression analysis, chemotherapy and surgery showed a survival advantage. In addition, patients who had surgery and radiotherapy had lower odds of dying compared to those who did not. The findings of this study highlight the importance of considering treatment types and individual patient characteristics that may impact survival and mortality rates among elderly lung cancer patients. These findings can inform decision-making and help improve cancer treatment outcomes.