{
  "abstract": "Background Numerous lung cancer risk prediction models have been developed and validated worldwide. It is imperative to offer a comprehensive overview and comparative analysis of their performances.Methods We conducted an extensive literature search to identify studies developing and/or validating lung cancer risk prediction models. Then we summarised and compared the external performance of these models, focusing on discriminative accuracy (C-index) and calibration performance (E:O ratio).Results After an initial screening of 10 210 articles, 35 studies on 21 distinct prediction models were identified, which used 42 different types of predictors spanning seven categories. Notable performance variations were observed in external validations. In North American cohorts, the C-index ranged from 0.60 to 0.87, with E:O ratios from 0.62 to 3.70. Among the European cohorts, the Trøndelag health study HUNT and CanPredict exhibited C-indices surpassing 0.870. Conversely, the Bach, lung cancer risk assessment tool (LCRAT), prostate, lung, colorectal and ovarian cancer screening (PLCO) m2012 and PLCOall2014 performed poorly in electronic health records of the Qresearch database subgroup, with C-indices falling below 0.60. PLCOm2012 reached the best E:O ratio of 1.00 (95% CI: 0.93 to 1.08) in the UK Biobank subgroup. In Asian cohorts, the C-index ranged from 0.54 to 0.87. Only three models, Korean Men, LCRAT and Liverpool lung project incidence risk model (LLPi), achieved a C-index exceeding 0.80. LCRAT demonstrated the best calibration, while Hoggart performed the worst.Conclusions Performance of lung cancer risk prediction models, despite being well developed and validated, varies in diverse populations. Significant regional imbalance persists in the development of these models. Rigorous external validation or recalibration study in the target population is crucial in accordance with the guidance prior to model implementation.PROSPERO registration number CRD42022324602.",
  "authors": [
    {
      "affiliations": [
        "Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China"
      ],
      "name": "Longyao Zhang"
    },
    {
      "affiliations": [
        "Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China"
      ],
      "name": "Xiang Wang"
    },
    {
      "affiliations": [
        "Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China"
      ],
      "name": "Qiuyuan Chen"
    },
    {
      "affiliations": [
        "Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China"
      ],
      "name": "Mengsheng Zhao"
    },
    {
      "affiliations": [
        "Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China"
      ],
      "name": "Can Ju"
    },
    {
      "affiliations": [
        "Department of Environmental Health, Harvard University T H Chan School of Public Health, Boston, Massachusetts, USA",
        "Pulmonary and Critical Care Division, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA"
      ],
      "name": "David C Christiani"
    },
    {
      "affiliations": [
        "Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China",
        "China International Cooperation Center (CICC) for Environment and Human Health, Nanjing Medical University, Nanjing, Jiangsu, China"
      ],
      "name": "Feng Chen"
    },
    {
      "affiliations": [
        "Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China",
        "China International Cooperation Center (CICC) for Environment and Human Health, Nanjing Medical University, Nanjing, Jiangsu, China",
        "Changzhou Medical Center, Nanjing Medical University, Changzhou, Jiangsu, China",
        "China Information Center, The Second People's Hospital of Changzhou, the Third Affiliated Hospital of Nanjing Medical University, Changzhou, Jiangsu, China"
      ],
      "name": "Ruyang Zhang"
    },
    {
      "affiliations": [
        "Center for Public Health and Epidemic Preparedness and Response, Peking University, Beijing, China",
        "Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Peking University, Beijing, China"
      ],
      "name": "Yongyue Wei"
    }
  ],
  "title": "Lung cancer risk assessment by prediction model: a global perspective",
  "uid": "276345c0-3c95-5b3e-807d-d9b0cbe9ed86"
}