期刊
NEW ENGLAND JOURNAL OF MEDICINE
卷 368, 期 8, 页码 728-736出版社
MASSACHUSETTS MEDICAL SOC
DOI: 10.1056/NEJMoa1211776
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资金
- National Cancer Institute (NCI)
- Division of Cancer Prevention
- Intramural Research Program of the Division of Cancer Epidemiology and Genetics
- Cancer Imaging Program, Division of Cancer Treatment and Diagnosis [U01-CA-80098, U01-CA-79778]
BACKGROUND The National Lung Screening Trial (NLST) used risk factors for lung cancer (e. g., >= 30 pack-years of smoking and <15 years since quitting) as selection criteria for lung-cancer screening. Use of an accurate model that incorporates additional risk factors to select persons for screening may identify more persons who have lung cancer or in whom lung cancer will develop. METHODS We modified the 2011 lung-cancer risk-prediction model from our Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial to ensure applicability to NLST data; risk was the probability of a diagnosis of lung cancer during the 6-year study period. We developed and validated the model (PLCOM2012) with data from the 80,375 persons in the PLCO control and intervention groups who had ever smoked. Discrimination (area under the receiver-operating-characteristic curve [AUC]) and calibration were assessed. In the validation data set, 14,144 of 37,332 persons (37.9%) met NLST criteria. For comparison, 14,144 highest-risk persons were considered positive (eligible for screening) according to PLCOM2012 criteria. We compared the accuracy of PLCOM2012 criteria with NLST criteria to detect lung cancer. Cox models were used to evaluate whether the reduction in mortality among 53,202 persons undergoing low-dose computed tomographic screening in the NLST differed according to risk. RESULTS The AUC was 0.803 in the development data set and 0.797 in the validation data set. As compared with NLST criteria, PLCOM2012 criteria had improved sensitivity (83.0% vs. 71.1%, P<0.001) and positive predictive value (4.0% vs. 3.4%, P = 0.01), without loss of specificity (62.9% and. 62.7%, respectively; P = 0.54); 41.3% fewer lung cancers were missed. The NLST screening effect did not vary according to PLCOM2012 risk (P = 0.61 for interaction). CONCLUSIONS The use of the PLCOM2012 model was more sensitive than the NLST criteria for lung-cancer detection.
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