Selection Criteria for Lung-Cancer Screening
Low-dose CT scanning reduces lung-cancer mortality. Further improvements are possible if the screened population includes a larger proportion of high-risk persons. The authors added features to the criteria for screening that improved sensitivity and positive predictive value. The National Lung Scre...
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| Published in: | The New England journal of medicine Vol. 368; no. 8; pp. 728 - 736 |
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| Main Authors: | , , , , , , , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Waltham, MA
Massachusetts Medical Society
21.02.2013
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| Subjects: | |
| ISSN: | 0028-4793, 1533-4406, 1533-4406 |
| Online Access: | Get full text |
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| Abstract | Low-dose CT scanning reduces lung-cancer mortality. Further improvements are possible if the screened population includes a larger proportion of high-risk persons. The authors added features to the criteria for screening that improved sensitivity and positive predictive value.
The National Lung Screening Trial (NLST) showed that lung-cancer screening with the use of low-dose computed tomography (CT) resulted in a 20% reduction in mortality from lung cancer.
1
Some organizations now recommend adoption of lung-cancer screening in clinical practice for high-risk persons if high-quality imaging, diagnostic methods, and treatment are available.
2
–
4
Most of these recommendations identify persons to be screened by applying the NLST criteria, which include an age between 55 and 74 years, a history of smoking of at least 30 pack-years, a period of less than 15 years since cessation of smoking, or some variant of these . . . |
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| AbstractList | 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.
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 (PLCO(M2012)) 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 PLCO(M2012) criteria. We compared the accuracy of PLCO(M2012) 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.
The AUC was 0.803 in the development data set and 0.797 in the validation data set. As compared with NLST criteria, PLCO(M2012) 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 PLCO(M2012) risk (P=0.61 for interaction).
The use of the PLCO(M2012) model was more sensitive than the NLST criteria for lung-cancer detection. Low-dose CT scanning reduces lung-cancer mortality. Further improvements are possible if the screened population includes a larger proportion of high-risk persons. The authors added features to the criteria for screening that improved sensitivity and positive predictive value. The National Lung Screening Trial (NLST) showed that lung-cancer screening with the use of low-dose computed tomography (CT) resulted in a 20% reduction in mortality from lung cancer. 1 Some organizations now recommend adoption of lung-cancer screening in clinical practice for high-risk persons if high-quality imaging, diagnostic methods, and treatment are available. 2 – 4 Most of these recommendations identify persons to be screened by applying the NLST criteria, which include an age between 55 and 74 years, a history of smoking of at least 30 pack-years, a period of less than 15 years since cessation of smoking, or some variant of these . . . 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.BACKGROUNDThe 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.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 (PLCO(M2012)) 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 PLCO(M2012) criteria. We compared the accuracy of PLCO(M2012) 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.METHODSWe 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 (PLCO(M2012)) 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 PLCO(M2012) criteria. We compared the accuracy of PLCO(M2012) 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.The AUC was 0.803 in the development data set and 0.797 in the validation data set. As compared with NLST criteria, PLCO(M2012) 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 PLCO(M2012) risk (P=0.61 for interaction).RESULTSThe AUC was 0.803 in the development data set and 0.797 in the validation data set. As compared with NLST criteria, PLCO(M2012) 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 PLCO(M2012) risk (P=0.61 for interaction).The use of the PLCO(M2012) model was more sensitive than the NLST criteria for lung-cancer detection.CONCLUSIONSThe use of the PLCO(M2012) model was more sensitive than the NLST criteria for lung-cancer detection. BackgroundThe 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.MethodsWe 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.ResultsThe 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).ConclusionsThe use of the PLCOM2012 model was more sensitive than the NLST criteria for lung-cancer detection. |
| Author | Katki, Hormuzd A Commins, John Chaturvedi, Anil K Tammemägi, Martin C Hocking, William G Kvale, Paul A Berg, Christine D Caporaso, Neil Riley, Tom L Church, Timothy R Silvestri, Gerard A |
| Author_xml | – sequence: 1 givenname: Martin C surname: Tammemägi fullname: Tammemägi, Martin C organization: From the Department of Community Health Sciences, Brock University, St. Catharines, ON, Canada (M.C.T.); the Division of Cancer Epidemiology and Genetics (H.A.K., N.C., A.K.C.) and the Early Detection Research Group, Division of Cancer Prevention (C.D.B.), National Cancer Institute, National Institutes of Health, and Information Management Services (T.L.R., J.C.) — all in Rockville, MD; Marshfield Clinic Research Foundation, Marshfield, WI (W.G.H.); the School of Public Health, University of Minnesota, Minneapolis (T.R.C.); Henry Ford Health System, Detroit (P.A.K.); and Pulmonary and Critical Care Medicine, Medical University of South Carolina, Charleston (G.A.S.) – sequence: 2 givenname: Hormuzd A surname: Katki fullname: Katki, Hormuzd A organization: From the Department of Community Health Sciences, Brock University, St. Catharines, ON, Canada (M.C.T.); the Division of Cancer Epidemiology and Genetics (H.A.K., N.C., A.K.C.) and the Early Detection Research Group, Division of Cancer Prevention (C.D.B.), National Cancer Institute, National Institutes of Health, and Information Management Services (T.L.R., J.C.) — all in Rockville, MD; Marshfield Clinic Research Foundation, Marshfield, WI (W.G.H.); the School of Public Health, University of Minnesota, Minneapolis (T.R.C.); Henry Ford Health System, Detroit (P.A.K.); and Pulmonary and Critical Care Medicine, Medical University of South Carolina, Charleston (G.A.S.) – sequence: 3 givenname: William G surname: Hocking fullname: Hocking, William G organization: From the Department of Community Health Sciences, Brock University, St. Catharines, ON, Canada (M.C.T.); the Division of Cancer Epidemiology and Genetics (H.A.K., N.C., A.K.C.) and the Early Detection Research Group, Division of Cancer Prevention (C.D.B.), National Cancer Institute, National Institutes of Health, and Information Management Services (T.L.R., J.C.) — all in Rockville, MD; Marshfield Clinic Research Foundation, Marshfield, WI (W.G.H.); the School of Public Health, University of Minnesota, Minneapolis (T.R.C.); Henry Ford Health System, Detroit (P.A.K.); and Pulmonary and Critical Care Medicine, Medical University of South Carolina, Charleston (G.A.S.) – sequence: 4 givenname: Timothy R surname: Church fullname: Church, Timothy R organization: From the Department of Community Health Sciences, Brock University, St. Catharines, ON, Canada (M.C.T.); the Division of Cancer Epidemiology and Genetics (H.A.K., N.C., A.K.C.) and the Early Detection Research Group, Division of Cancer Prevention (C.D.B.), National Cancer Institute, National Institutes of Health, and Information Management Services (T.L.R., J.C.) — all in Rockville, MD; Marshfield Clinic Research Foundation, Marshfield, WI (W.G.H.); the School of Public Health, University of Minnesota, Minneapolis (T.R.C.); Henry Ford Health System, Detroit (P.A.K.); and Pulmonary and Critical Care Medicine, Medical University of South Carolina, Charleston (G.A.S.) – sequence: 5 givenname: Neil surname: Caporaso fullname: Caporaso, Neil organization: From the Department of Community Health Sciences, Brock University, St. Catharines, ON, Canada (M.C.T.); the Division of Cancer Epidemiology and Genetics (H.A.K., N.C., A.K.C.) and the Early Detection Research Group, Division of Cancer Prevention (C.D.B.), National Cancer Institute, National Institutes of Health, and Information Management Services (T.L.R., J.C.) — all in Rockville, MD; Marshfield Clinic Research Foundation, Marshfield, WI (W.G.H.); the School of Public Health, University of Minnesota, Minneapolis (T.R.C.); Henry Ford Health System, Detroit (P.A.K.); and Pulmonary and Critical Care Medicine, Medical University of South Carolina, Charleston (G.A.S.) – sequence: 6 givenname: Paul A surname: Kvale fullname: Kvale, Paul A organization: From the Department of Community Health Sciences, Brock University, St. Catharines, ON, Canada (M.C.T.); the Division of Cancer Epidemiology and Genetics (H.A.K., N.C., A.K.C.) and the Early Detection Research Group, Division of Cancer Prevention (C.D.B.), National Cancer Institute, National Institutes of Health, and Information Management Services (T.L.R., J.C.) — all in Rockville, MD; Marshfield Clinic Research Foundation, Marshfield, WI (W.G.H.); the School of Public Health, University of Minnesota, Minneapolis (T.R.C.); Henry Ford Health System, Detroit (P.A.K.); and Pulmonary and Critical Care Medicine, Medical University of South Carolina, Charleston (G.A.S.) – sequence: 7 givenname: Anil K surname: Chaturvedi fullname: Chaturvedi, Anil K organization: From the Department of Community Health Sciences, Brock University, St. Catharines, ON, Canada (M.C.T.); the Division of Cancer Epidemiology and Genetics (H.A.K., N.C., A.K.C.) and the Early Detection Research Group, Division of Cancer Prevention (C.D.B.), National Cancer Institute, National Institutes of Health, and Information Management Services (T.L.R., J.C.) — all in Rockville, MD; Marshfield Clinic Research Foundation, Marshfield, WI (W.G.H.); the School of Public Health, University of Minnesota, Minneapolis (T.R.C.); Henry Ford Health System, Detroit (P.A.K.); and Pulmonary and Critical Care Medicine, Medical University of South Carolina, Charleston (G.A.S.) – sequence: 8 givenname: Gerard A surname: Silvestri fullname: Silvestri, Gerard A organization: From the Department of Community Health Sciences, Brock University, St. Catharines, ON, Canada (M.C.T.); the Division of Cancer Epidemiology and Genetics (H.A.K., N.C., A.K.C.) and the Early Detection Research Group, Division of Cancer Prevention (C.D.B.), National Cancer Institute, National Institutes of Health, and Information Management Services (T.L.R., J.C.) — all in Rockville, MD; Marshfield Clinic Research Foundation, Marshfield, WI (W.G.H.); the School of Public Health, University of Minnesota, Minneapolis (T.R.C.); Henry Ford Health System, Detroit (P.A.K.); and Pulmonary and Critical Care Medicine, Medical University of South Carolina, Charleston (G.A.S.) – sequence: 9 givenname: Tom L surname: Riley fullname: Riley, Tom L organization: From the Department of Community Health Sciences, Brock University, St. Catharines, ON, Canada (M.C.T.); the Division of Cancer Epidemiology and Genetics (H.A.K., N.C., A.K.C.) and the Early Detection Research Group, Division of Cancer Prevention (C.D.B.), National Cancer Institute, National Institutes of Health, and Information Management Services (T.L.R., J.C.) — all in Rockville, MD; Marshfield Clinic Research Foundation, Marshfield, WI (W.G.H.); the School of Public Health, University of Minnesota, Minneapolis (T.R.C.); Henry Ford Health System, Detroit (P.A.K.); and Pulmonary and Critical Care Medicine, Medical University of South Carolina, Charleston (G.A.S.) – sequence: 10 givenname: John surname: Commins fullname: Commins, John organization: From the Department of Community Health Sciences, Brock University, St. Catharines, ON, Canada (M.C.T.); the Division of Cancer Epidemiology and Genetics (H.A.K., N.C., A.K.C.) and the Early Detection Research Group, Division of Cancer Prevention (C.D.B.), National Cancer Institute, National Institutes of Health, and Information Management Services (T.L.R., J.C.) — all in Rockville, MD; Marshfield Clinic Research Foundation, Marshfield, WI (W.G.H.); the School of Public Health, University of Minnesota, Minneapolis (T.R.C.); Henry Ford Health System, Detroit (P.A.K.); and Pulmonary and Critical Care Medicine, Medical University of South Carolina, Charleston (G.A.S.) – sequence: 11 givenname: Christine D surname: Berg fullname: Berg, Christine D organization: From the Department of Community Health Sciences, Brock University, St. Catharines, ON, Canada (M.C.T.); the Division of Cancer Epidemiology and Genetics (H.A.K., N.C., A.K.C.) and the Early Detection Research Group, Division of Cancer Prevention (C.D.B.), National Cancer Institute, National Institutes of Health, and Information Management Services (T.L.R., J.C.) — all in Rockville, MD; Marshfield Clinic Research Foundation, Marshfield, WI (W.G.H.); the School of Public Health, University of Minnesota, Minneapolis (T.R.C.); Henry Ford Health System, Detroit (P.A.K.); and Pulmonary and Critical Care Medicine, Medical University of South Carolina, Charleston (G.A.S.) |
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| Snippet | Low-dose CT scanning reduces lung-cancer mortality. Further improvements are possible if the screened population includes a larger proportion of high-risk... 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... BackgroundThe National Lung Screening Trial (NLST) used risk factors for lung cancer (e.g., ≥30 pack-years of smoking and <15 years since quitting) as... |
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| SubjectTerms | Area Under Curve Biological and medical sciences Cancer screening Chronic obstructive pulmonary disease Computed tomography General aspects Humans Logistic Models Lung cancer Lung Neoplasms - diagnostic imaging Mass Screening Medical research Medical sciences Medical screening Methods Ovarian cancer Patient Selection Pneumology Prevention and actions Prostate Public health. Hygiene Public health. Hygiene-occupational medicine Radiography, Thoracic Risk Assessment - methods Risk Factors Sensitivity and Specificity Smoking Tomography, X-Ray Computed Tumors of the respiratory system and mediastinum |
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| Title | Selection Criteria for Lung-Cancer Screening |
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