Incidence trends and risk prediction nomogram of metachronous second primary lung cancer in lung cancer survivors

Background: This study was designed to estimate the trends in 5-year incidence of metachronous second primary lung cancer(SPLC) and to establish a risk prediction model to identify candidates who were at high risk of developing metachronous SPLC. Methods: Incidence data between 2004 and 2007 were obtained from SEER database, including 42453 participants who survived ≥ 2 years after the initial diagnosis of lung cancer. Joinpoint regression analysis was used to calculate the 5-year incidence rates of metachronous SPLC per 100 000 population. Related risk factors of the survivors who developed MSPLC during five years were identified through logistic regression analysis, followed by establishment of risk prediction nomogram. Discrimination (C-index), calibration and decision analysis were further performed to assess the validation and clinical net benefit of risk prediction nomogram. Results: A total of 1412 survivors with lung cancer developed MSPLC during five years, with 3546 per 100 000 population of age-adjusted 5-year incidence. Age, histology, tumor stage, and radiation were recognized as risk factors of metachronous SPLC, as indicated by logistic regression analysis. The risk prediction nomogram of metachronous SPLC harbored moderate discrimination(C-index = 0.67) and good calibration, with the risk of 0.01 to 0.11.The decision curve analysis showed that clinical net benefit of this risk prediction nomogram in a range of risk thresholds (0.01 to 0.06) was higher compared to all-screening or no-screening strategies. Conclusions: Collectively, the cumulative risk of metachronous SPLC of the survivors increased over time. The risk prediction nomogram was available to select high-risk survivors who should regularly undergo computed tomography screening.