Exploring Novel Technologies in Lung Cancer Diagnosis: Do We Have Room for Improvement?

Using Population-Based Cancer Registration Data and Period Analysis to Accurately Assess and Predict 5-Year Relative Survival for Lung Cancer Patients in Eastern China

Background

The assessment of long-term survival of lung cancer patients based on data from population-based caner registries, using period analysis, was scarce in China. We aimed to accurately assess the long-term survival of lung cancer patients, and to predict the long-term survival in the future, using cancer registry data from Taizhou City, eastern China.

Methods

Four cancer registries with high-quality data were selected. Patients diagnosed with lung cancer during 2004–2018 were included. The long-term survival was evaluated using period analysis, with further stratification by sex, age at diagnosis and region. Additionally, projected 5-year relative survival (RS) of lung cancer patients for 2019-2023 was evaluated, using model-based period analysis.

Results

The 5-year RS of lung cancer patients diagnosed during 2014–2018 was 40.2% (31.5% for men and 56.2% for women). A moderate age gradient was observed for the period estimate, with the estimate decreasing from 50.5 to 26.5% in the age group of 15–44 years and ≥75 years, respectively. The 5-year RS of urban area was higher than that of rural area (52.3% vs. 38.9%). The overall projected 5-year RS of lung cancer patients was 52.7% for 2019–2023, with estimate of 43.0 and 73.2% for men and women, respectively. A moderate age gradient was also observed for the projected estimate. Moreover, estimate reached nearly 50% for rural and urban areas.

Conclusion

Period analysis tended to provide the up-to-date and precise survival estimates for lung cancer patients, which is worth further application, and provides important evidence for prevention and intervention of lung cancer.