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Risk model-based management for second primary lung cancer among lung cancer survivors through a validated risk prediction model.

Eunji ChoiSophia J LuoVictoria Y DingJulie T WuAshok V KumarJason WampflerMartin C TammemägiLynne R WilkensJacqueline V AredoLeah M BackhusJoel W NealAnn N LeungNeal D FreedmanRayjean J HungChristopher I AmosLoïc Le MarchandIona ChengHeather A WakeleePing YangSummer S Han
Published in: Cancer (2023)
Lung cancer survivors have a high risk of developing second primary lung cancer (SPLC). However, no evidence-based guidelines for SPLC surveillance are available for lung cancer survivors. Recently, an SPLC risk-prediction model was developed and validated using data from population-based epidemiological cohorts and clinical trials, but real-world validation has been lacking. Using a large, real-world cohort of lung cancer survivors, we showed the high predictive accuracy and risk-stratification ability of the SPLC risk-prediction model. Furthermore, we demonstrated the potential to enhance efficiency in detecting SPLC using risk model-based surveillance strategies compared to the existing consensus-based clinical guidelines, including the National Comprehensive Cancer Network.
Keyphrases
  • young adults
  • clinical trial
  • public health
  • clinical practice
  • squamous cell carcinoma
  • risk assessment
  • electronic health record
  • quality improvement
  • open label
  • study protocol
  • deep learning
  • squamous cell