Dataset Information

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

ABSTRACT: 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.

SUBMITTER: Hu ZG

PROVIDER: S-EPMC6296553 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

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

Hu Zhi Gang ZG Li Wen Xin WX Ruan Yu Shu YS Zeng Fan Jun FJ

PloS one 20181217 12

<h4>Background</h4>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.<h4>Methods</h4>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 i ...[more]

PMID: 30557376

Similar Datasets

Project description:BackgroundWith advancing therapeutics, lung cancer (LC) survivors are rapidly increasing in number. Although mounting evidence suggests LC survivors have high risk of second primary lung cancer (SPLC), there is no validated prediction model available for clinical use to identify high-risk LC survivors for SPLC.MethodsUsing data from 6325 ever-smokers in the Multiethnic Cohort (MEC) study diagnosed with initial primary lung cancer (IPLC) in 1993-2017, we developed a prediction model for 10-year SPLC risk after IPLC diagnosis using cause-specific Cox regression. We evaluated the model's clinical utility using decision curve analysis and externally validated it using 2 population-based data-Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO) and National Lung Screening Trial (NLST)-that included 2963 and 2844 IPLC (101 and 93 SPLC cases), respectively.ResultsOver 14 063 person-years, 145 (2.3%) ever-smoking IPLC patients developed SPLC in MEC. Our prediction model demonstrated a high predictive accuracy (Brier score = 2.9, 95% confidence interval [CI] = 2.4 to 3.3) and discrimination (area under the receiver operating characteristics [AUC] = 81.9%, 95% CI = 78.2% to 85.5%) based on bootstrap validation in MEC. Stratification by the estimated risk quartiles showed that the observed SPLC incidence was statistically significantly higher in the 4th vs 1st quartile (9.5% vs 0.2%; P < .001). Decision curve analysis indicated that in a wide range of 10-year risk thresholds from 1% to 20%, the model yielded a larger net-benefit vs hypothetical all-screening or no-screening scenarios. External validation using PLCO and NLST showed an AUC of 78.8% (95% CI = 74.6% to 82.9%) and 72.7% (95% CI = 67.7% to 77.7%), respectively.ConclusionsWe developed and validated a SPLC prediction model based on large population-based cohorts. The proposed prediction model can help identify high-risk LC patients for SPLC and can be incorporated into clinical decision making for SPLC surveillance and screening.

Dataset Information

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

Publications

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

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets