ArticleJournal of the National Cancer Institute2022
Development and Validation of a Risk Prediction Model for Second Primary Lung Cancer.
Article in Journal of the National Cancer Institute, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 16 citations in OpenAlex.
- Navigating the Complexity of Lung Cancer Surveillance Practices: Qualitative Pilot Study on Provider Perspectives.JMIR cancer · 2026Article
- Leveraging large language models to extract smoking history from clinical notes for lung cancer surveillance.NPJ digital medicine · 2025Article
- Clinical features and prognostic nomogram development for cancer-specific death in patients with dual primary lung cancer: a population-based study from SEER database.Journal of cardiothoracic surgery · 2025Article
- Racial and ethnic differences in second primary lung cancer risk among lung cancer survivors.JNCI cancer spectrum · 2024Article
- Article
- Software Application Profile: dynamicLM-a tool for performing dynamic risk prediction using a landmark supermodel for survival data under competing risks.International journal of epidemiology · 2023Article
- Second Primary Lung Cancer Among Lung Cancer Survivors Who Never Smoked.JAMA network open · 2023Article
- Combining Asian and European genome-wide association studies of colorectal cancer improves risk prediction across racial and ethnic populations.Nature communications · 2023Article
- Optimizing Lung Cancer Screening With Risk Prediction: Current Challenges and the Emerging Role of Biomarkers.Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2023Review
- Article
- The Survival Impact of Second Primary Lung Cancer in Patients With Lung Cancer.Journal of the National Cancer Institute · 2022Article
- Postoperative radiotherapy might be a risk factor for second primary lung cancer: A population-based study.Frontiers in oncology · 2022Article
Corrections and comments
- Erratum issued
Authors and funding
20 authors at 8 institutions in 2 countries.
Funding
Abstract
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.
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