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Assessment of Lung Cancer Risk on the Basis of a Biomarker Panel of Circulating Proteins
- Source :
- Dipòsit Digital de la UB, Universidad de Barcelona, JAMA Oncology, 4(10). American Medical Association
- Publication Year :
- 2018
-
Abstract
- IMPORTANCE: There is an urgent need to improve lung cancer risk assessment because current screening criteria miss a large proportion of cases. OBJECTIVE: To investigate whether a lung cancer risk prediction model based on a panel of selected circulating protein biomarkers can outperform a traditional risk prediction model and current US screening criteria. DESIGN, SETTING, AND PARTICIPANTS: Prediagnostic samples from 108 ever-smoking patients with lung cancer diagnosed within 1 year after blood collection and samples from 216 smoking-matched controls from the Carotene and Retinol Efficacy Trial (CARET) cohort were used to develop a biomarker risk score based on 4 proteins (cancer antigen 125 [CA125], carcinoembryonic antigen [CEA], cytokeratin-19 fragment [CYFRA 21-1], and the precursor form of surfactant protein B [Pro-SFTPB]). The biomarker score was subsequently validated blindly using absolute risk estimates among 63 ever-smoking patients with lung cancer diagnosed within 1 year after blood collection and 90 matched controls from 2 large European population-based cohorts, the European Prospective Investigation into Cancer and Nutrition (EPIC) and the Northern Sweden Health and Disease Study (NSHDS). MAIN OUTCOMES AND MEASURES: Model validity in discriminating between future lung cancer cases and controls. Discrimination estimates were weighted to reflect the background populations of EPIC and NSHDS validation studies (area under the receiver-operating characteristics curve [AUC], sensitivity, and specificity). RESULTS: In the validation study of 63 ever-smoking patients with lung cancer and 90 matched controls (mean [SD] age, 57.7 [8.7] years; 68.6% men) from EPIC and NSHDS, an integrated risk prediction model that combined smoking exposure with the biomarker score yielded an AUC of 0.83 (95% CI, 0.76-0.90) compared with 0.73 (95% CI, 0.64-0.82) for a model based on smoking exposure alone (P = .003 for difference in AUC). At an overall specificity of 0.83, based on the US Preventive Services Task Force screening criteria, the sensitivity of the integrated risk prediction (biomarker) model was 0.63 compared with 0.43 for the smoking model. Conversely, at an overall sensitivity of 0.42, based on the US Preventive Services Task Force screening criteria, the integrated risk prediction model yielded a specificity of 0.95 compared with 0.86 for the smoking model. CONCLUSIONS AND RELEVANCE: This study provided a proof of principle in showing that a panel of circulating protein biomarkers may improve lung cancer risk assessment and may be used to define eligibility for computed tomography screening.
- Subjects :
- 0301 basic medicine
Oncology
Male
Cancer Research
medicine.medical_specialty
Lung Neoplasms
Tomography Scanners, X-Ray Computed
Risk factors in diseases
Proteolipids
Biomarker panel
Risk Assessment
Risk factors in diseas
03 medical and health sciences
0302 clinical medicine
X ray computed
Risk Factors
Internal medicine
medicine
Biomarkers, Tumor
Humans
Mass Screening
Prospective Studies
Protein Precursors
Lung cancer
Prospective cohort study
Tumor marker
Aged
Aged, 80 and over
Keratin-19
business.industry
Factors de risc en les malalties
Brief Report
Membrane Proteins
Non-Smokers
respiratory system
Middle Aged
medicine.disease
respiratory tract diseases
Carcinoembryonic Antigen
030104 developmental biology
ROC Curve
030220 oncology & carcinogenesis
CA-125 Antigen
Càncer de pulmó
Female
Risk assessment
business
Subjects
Details
- Language :
- English
- ISSN :
- 23742445
- Database :
- OpenAIRE
- Journal :
- Dipòsit Digital de la UB, Universidad de Barcelona, JAMA Oncology, 4(10). American Medical Association
- Accession number :
- edsair.doi.dedup.....7253bf33234fa97a4725bf4dd16636d5