HHS Public Access Author manuscript Author Manuscript
JAMA. Author manuscript; available in PMC 2016 June 09. Published in final edited form as: JAMA. 2016 June 7; 315(21): 2300–2311. doi:10.1001/jama.2016.6255.
Development and validation of risk models to select eversmokers for CT lung-cancer screening Hormuzd A. Katki, Ph.D.1,*, Stephanie A. Kovalchik, Ph.D.2, Christine D. Berg, M.D.1,3, Li C. Cheung, M.S.4, and Anil K. Chaturvedi, Ph.D.1,* 1Division
of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, DHHS, Bethesda, MD, USA
Author Manuscript
2Institute
of Sport, Exercise and Active Living, Victoria University, Melbourne, Australia
3Department
of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins Medicine, Baltimore, MD, USA 4Information
Management Services Inc., Calverton, MD, USA
Abstract
Author Manuscript
Importance—The US Preventive Services Task Force (USPSTF) recommends computedtomography (CT) lung-cancer screening for ever-smokers ages 55-80 years who smoked at least 30 pack-years with no more than 15 years since quitting. However, selecting ever-smokers for screening using individualized lung-cancer risk calculations may be more effective and efficient than current USPSTF recommendations. Objective—Comparison of modeled outcomes from risk-based CT lung-screening strategies versus USPSTF recommendations.
Author Manuscript
Design/Setting/Participants—Empirical risk models for lung-cancer incidence and death in the absence of CT screening using data on ever-smokers from the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial (PLCO; 1993-2009) control group. Covariates included age, education, sex, race, smoking intensity/duration/quit-years, Body Mass Index, family history of lung-cancer, and self-reported emphysema. Model validation in the chest radiography groups of the PLCO and the National Lung Screening Trial (NLST; 2002-2009), with additional validation of the death model in the National Health Interview Survey (NHIS; 1997-2001), a representative sample of the US. Models applied to US ever-smokers ages 50-80 (NHIS 2010-2012) to estimate outcomes of risk-based selection for CT lung-screening, assuming screening for all ever-smokers yields the percent changes in lung-cancer detection and death observed in the NLST. Exposure—Annual CT lung-screening for 3 years.
*
Corresponding authors:HAK: Division of Cancer Epidemiology and Genetics, National Cancer Institute, 9609 Medical Center Dr., Room 7E606, Bethesda, MD 20892, Phone: 240-276-7423, Fax: 240-276-7838, [email protected]; AKC: Division of Cancer Epidemiology and Genetics, National Cancer Institute, 9609 Medical Center Dr., Room 6E238, Bethesda, MD 20892, Phone: 240-276-7193, [email protected]. Conflicts of Interest: Dr. Christine Berg receives consulting fees from Medial ES, LLC, a company that is developing algorithms from routine blood tests that may indicate an increased risk of malignancy. Access to Data: Hormuzd A. Katki had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Katki et al.
Page 2
Author Manuscript
Main Outcomes and Measures—Model validity: calibration (number of model-predicted cases divided by number of observed cases (Estimated/Observed)) and discrimination (AreaUnder-Curve (AUC)). Modeled screening outcomes: estimated number of screen-avertable lungcancer deaths, estimated screening effectiveness (number needed to screen (NNS) to prevent 1 lung-cancer death).
Author Manuscript
Results—Lung-cancer incidence and death risk models were well-calibrated in PLCO and NLST. The lung-cancer death model calibrated and discriminated well for US ever-smokers ages 50-80 (NHIS 1997-2001: Estimated/Observed=0.94, 95%CI=0.84-1.05; AUC=0.78, 95%CI=0.76-0.80). Under USPSTF recommendations, the models estimated 9.0 million US eversmokers would qualify for lung-cancer screening and 46,488 (95%CI=43,924-49,053) lung-cancer deaths were estimated as screen-avertable over 5 years (estimated NNS=194, 95%CI=187-201). In contrast, risk-based selection screening the same number of ever-smokers (9.0 million) at highest 5-year lung-cancer risk (≥1.9%), was estimated to avert 20% more deaths (55,717; 95%CI=53,033-58,400) and was estimated to reduce the estimated NNS by 17% (NNS=162, 95%CI=157-166). Conclusions and Relevance—Among a cohort of US ever-smokers age 50-80 years, application of a risk-based model for CT screening for lung cancer compared with a model based on USPSTF recommendations was estimated to be associated with a greater number of lungcancer deaths prevented over 5 years along with a lower NNS to prevent 1 lung-cancer death. Keywords precision medicine; risk-based medicine; heterogeneity of treatment effect; risk modeling; precision prevention; smoking; USPSTF
Author Manuscript
INTRODUCTION 1
Lung-cancer is the most common cause of cancer death in the United States. The National Lung Screening Trial (NLST) demonstrated a 20% reduction in lung-cancer mortality with 3 rounds of low-dose computed tomography (CT) screening as compared with chest 2 radiography, over a mean follow-up of 6.4 years. Consequently, the US Preventive Services Task Force (USPSTF) and the US Centers for Medicare and Medicaid Services (CMS) now recommend annual CT screening for a risk-factor-based subgroup of smokers—current and former smokers ages 55-80 years and 55-77 years, respectively, with at least 30 pack-years 3 of smoking and, for former smokers, no more than 15 years since quitting. ,4 These were largely based on the entry criteria for the NLST as well as microsimulation models that 5 considered subgroups defined by age/pack-year/quit-year criteria. ,6
Author Manuscript
Selecting individuals at highest lung-cancer risk, as determined by individual risk calculations (i.e. risk-based selection) rather than by risk-factor-based subgroups, might lead 3 10 to more efficient screening. ,7- In the NLST, 88% of CT-prevented lung-cancer deaths occurred in the 60% of participants at highest risk, while the 20% of participants at lowest 11 risk accounted for only 1% of CT-prevented lung-cancer deaths. The cost-effectiveness of 12 CT screening also increased with lung-cancer risk in the NLST. Risk-based selection more precisely delineates the benefits and harms of screening by accommodating detailed
JAMA. Author manuscript; available in PMC 2016 June 09.
Katki et al.
Page 3 3
Author Manuscript
information on all lung-cancer risk factors. Risk-based selection also enforces consistency of screening recommendations by accommodating “equal management of people at equal 13 risk”. However, to our knowledge, there are currently no risk tools for lung-cancer that have been validated in representative samples of the US population. Likewise, empirical evidence is lacking for the superiority of risk-based lung-cancer screening in the US. In this study, we sought to develop and validate empirical lung-cancer incidence and death risk models generalizable to US smokers, as well as an empirical model for risk of falsepositive CT screen. Models were applied to a contemporary cohort of US ever-smokers to investigate estimated outcomes from various risk-based selection strategies versus current USPSTF recommendations, for “NLST-like” screening (3 yearly CT screens) with 5-years follow-up.
Author Manuscript
METHODS Data sources
Author Manuscript
Data was used from two lung-cancer screening trials in the US—The Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial and the NLST— as well as data from the NHIS, a representative sample of the US population. From 1993-2001, the PLCO trial randomized 154,901 US men and women ages 55-74 years to receive four annual posterior-anterior chest radiographs (three in never-smokers) or the standard of care, and 14 concluded that chest radiography screening did not reduce lung-cancer mortality. The most recent follow-up data for PLCO was available through December 2009. From 2002-2004, the NLST randomized 53,454 US smokers ages 55-74, with at least 30 pack-years of smoking and no more than 15 years since smoking cessation to receive three annual rounds 2 of low-dose CT or posterior-anterior chest radiography. The NLST dataset included outcomes accrued through January 15, 2009, the latest date for censoring lung-cancer death for the primary analysis. The NHIS is an annual cross-sectional, multi-stage probability sample of approximately 87,500 individuals representing the non-institutionalized civilian 15 US population. NHIS data collected through 2004 have been linked with the National 16 Death Index (NDI), with follow-up through December 31, 2006. The National Institutes of Health Office of Human Subjects Research deemed this study exempt from IRB review. Statistical Analyses
Author Manuscript
Development and validation of risk models—Absolute risk models were developed to predict five-year cumulative risk of lung-cancer incidence and lung-cancer death using data on ever-smokers within the control group of the PLCO trial. PLCO data allowed us to develop valid models for both USPSTF-eligible and –ineligible smokers. Cox hazard-ratio models on time since interview were used, and accounted for life expectancy by fitting a 17 11 hazard-ratio model for competing causes of death. Compared to previous work , each submodel (lung-cancer incidence, lung-cancer death, and death by other causes) now includes more self-reported demographic (age, gender, race, education, body-mass index(BMI)), self-reported clinical (history of emphysema and lung-cancer family-history), and self-reported smoking (cigarettes per day, smoking duration, and smoking pack-years
JAMA. Author manuscript; available in PMC 2016 June 09.
Katki et al.
Page 4
Author Manuscript
and quit-years) variables. Variables and parameterization for continuous variables were selected using the Akaike Information Criterion. See Supplemental Methods for details. Validation of the lung-cancer death model for US ever-smokers ages 50-80 years used NHIS surveys 1997-2001 because age at smoking initiation was not systematically collected before 1997. Via NDI linkage through 2006, each NHIS participant had at least five years of follow-up for lung-cancer death. Multiple-imputation was used to account for the
JAMA. Author manuscript; available in PMC 2016 June 09. Published in final edited form as: JAMA. 2016 June 7; 315(21): 2300–2311. doi:10.1001/jama.2016.6255.
Development and validation of risk models to select eversmokers for CT lung-cancer screening Hormuzd A. Katki, Ph.D.1,*, Stephanie A. Kovalchik, Ph.D.2, Christine D. Berg, M.D.1,3, Li C. Cheung, M.S.4, and Anil K. Chaturvedi, Ph.D.1,* 1Division
of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, DHHS, Bethesda, MD, USA
Author Manuscript
2Institute
of Sport, Exercise and Active Living, Victoria University, Melbourne, Australia
3Department
of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins Medicine, Baltimore, MD, USA 4Information
Management Services Inc., Calverton, MD, USA
Abstract
Author Manuscript
Importance—The US Preventive Services Task Force (USPSTF) recommends computedtomography (CT) lung-cancer screening for ever-smokers ages 55-80 years who smoked at least 30 pack-years with no more than 15 years since quitting. However, selecting ever-smokers for screening using individualized lung-cancer risk calculations may be more effective and efficient than current USPSTF recommendations. Objective—Comparison of modeled outcomes from risk-based CT lung-screening strategies versus USPSTF recommendations.
Author Manuscript
Design/Setting/Participants—Empirical risk models for lung-cancer incidence and death in the absence of CT screening using data on ever-smokers from the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial (PLCO; 1993-2009) control group. Covariates included age, education, sex, race, smoking intensity/duration/quit-years, Body Mass Index, family history of lung-cancer, and self-reported emphysema. Model validation in the chest radiography groups of the PLCO and the National Lung Screening Trial (NLST; 2002-2009), with additional validation of the death model in the National Health Interview Survey (NHIS; 1997-2001), a representative sample of the US. Models applied to US ever-smokers ages 50-80 (NHIS 2010-2012) to estimate outcomes of risk-based selection for CT lung-screening, assuming screening for all ever-smokers yields the percent changes in lung-cancer detection and death observed in the NLST. Exposure—Annual CT lung-screening for 3 years.
*
Corresponding authors:HAK: Division of Cancer Epidemiology and Genetics, National Cancer Institute, 9609 Medical Center Dr., Room 7E606, Bethesda, MD 20892, Phone: 240-276-7423, Fax: 240-276-7838, [email protected]; AKC: Division of Cancer Epidemiology and Genetics, National Cancer Institute, 9609 Medical Center Dr., Room 6E238, Bethesda, MD 20892, Phone: 240-276-7193, [email protected]. Conflicts of Interest: Dr. Christine Berg receives consulting fees from Medial ES, LLC, a company that is developing algorithms from routine blood tests that may indicate an increased risk of malignancy. Access to Data: Hormuzd A. Katki had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Katki et al.
Page 2
Author Manuscript
Main Outcomes and Measures—Model validity: calibration (number of model-predicted cases divided by number of observed cases (Estimated/Observed)) and discrimination (AreaUnder-Curve (AUC)). Modeled screening outcomes: estimated number of screen-avertable lungcancer deaths, estimated screening effectiveness (number needed to screen (NNS) to prevent 1 lung-cancer death).
Author Manuscript
Results—Lung-cancer incidence and death risk models were well-calibrated in PLCO and NLST. The lung-cancer death model calibrated and discriminated well for US ever-smokers ages 50-80 (NHIS 1997-2001: Estimated/Observed=0.94, 95%CI=0.84-1.05; AUC=0.78, 95%CI=0.76-0.80). Under USPSTF recommendations, the models estimated 9.0 million US eversmokers would qualify for lung-cancer screening and 46,488 (95%CI=43,924-49,053) lung-cancer deaths were estimated as screen-avertable over 5 years (estimated NNS=194, 95%CI=187-201). In contrast, risk-based selection screening the same number of ever-smokers (9.0 million) at highest 5-year lung-cancer risk (≥1.9%), was estimated to avert 20% more deaths (55,717; 95%CI=53,033-58,400) and was estimated to reduce the estimated NNS by 17% (NNS=162, 95%CI=157-166). Conclusions and Relevance—Among a cohort of US ever-smokers age 50-80 years, application of a risk-based model for CT screening for lung cancer compared with a model based on USPSTF recommendations was estimated to be associated with a greater number of lungcancer deaths prevented over 5 years along with a lower NNS to prevent 1 lung-cancer death. Keywords precision medicine; risk-based medicine; heterogeneity of treatment effect; risk modeling; precision prevention; smoking; USPSTF
Author Manuscript
INTRODUCTION 1
Lung-cancer is the most common cause of cancer death in the United States. The National Lung Screening Trial (NLST) demonstrated a 20% reduction in lung-cancer mortality with 3 rounds of low-dose computed tomography (CT) screening as compared with chest 2 radiography, over a mean follow-up of 6.4 years. Consequently, the US Preventive Services Task Force (USPSTF) and the US Centers for Medicare and Medicaid Services (CMS) now recommend annual CT screening for a risk-factor-based subgroup of smokers—current and former smokers ages 55-80 years and 55-77 years, respectively, with at least 30 pack-years 3 of smoking and, for former smokers, no more than 15 years since quitting. ,4 These were largely based on the entry criteria for the NLST as well as microsimulation models that 5 considered subgroups defined by age/pack-year/quit-year criteria. ,6
Author Manuscript
Selecting individuals at highest lung-cancer risk, as determined by individual risk calculations (i.e. risk-based selection) rather than by risk-factor-based subgroups, might lead 3 10 to more efficient screening. ,7- In the NLST, 88% of CT-prevented lung-cancer deaths occurred in the 60% of participants at highest risk, while the 20% of participants at lowest 11 risk accounted for only 1% of CT-prevented lung-cancer deaths. The cost-effectiveness of 12 CT screening also increased with lung-cancer risk in the NLST. Risk-based selection more precisely delineates the benefits and harms of screening by accommodating detailed
JAMA. Author manuscript; available in PMC 2016 June 09.
Katki et al.
Page 3 3
Author Manuscript
information on all lung-cancer risk factors. Risk-based selection also enforces consistency of screening recommendations by accommodating “equal management of people at equal 13 risk”. However, to our knowledge, there are currently no risk tools for lung-cancer that have been validated in representative samples of the US population. Likewise, empirical evidence is lacking for the superiority of risk-based lung-cancer screening in the US. In this study, we sought to develop and validate empirical lung-cancer incidence and death risk models generalizable to US smokers, as well as an empirical model for risk of falsepositive CT screen. Models were applied to a contemporary cohort of US ever-smokers to investigate estimated outcomes from various risk-based selection strategies versus current USPSTF recommendations, for “NLST-like” screening (3 yearly CT screens) with 5-years follow-up.
Author Manuscript
METHODS Data sources
Author Manuscript
Data was used from two lung-cancer screening trials in the US—The Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial and the NLST— as well as data from the NHIS, a representative sample of the US population. From 1993-2001, the PLCO trial randomized 154,901 US men and women ages 55-74 years to receive four annual posterior-anterior chest radiographs (three in never-smokers) or the standard of care, and 14 concluded that chest radiography screening did not reduce lung-cancer mortality. The most recent follow-up data for PLCO was available through December 2009. From 2002-2004, the NLST randomized 53,454 US smokers ages 55-74, with at least 30 pack-years of smoking and no more than 15 years since smoking cessation to receive three annual rounds 2 of low-dose CT or posterior-anterior chest radiography. The NLST dataset included outcomes accrued through January 15, 2009, the latest date for censoring lung-cancer death for the primary analysis. The NHIS is an annual cross-sectional, multi-stage probability sample of approximately 87,500 individuals representing the non-institutionalized civilian 15 US population. NHIS data collected through 2004 have been linked with the National 16 Death Index (NDI), with follow-up through December 31, 2006. The National Institutes of Health Office of Human Subjects Research deemed this study exempt from IRB review. Statistical Analyses
Author Manuscript
Development and validation of risk models—Absolute risk models were developed to predict five-year cumulative risk of lung-cancer incidence and lung-cancer death using data on ever-smokers within the control group of the PLCO trial. PLCO data allowed us to develop valid models for both USPSTF-eligible and –ineligible smokers. Cox hazard-ratio models on time since interview were used, and accounted for life expectancy by fitting a 17 11 hazard-ratio model for competing causes of death. Compared to previous work , each submodel (lung-cancer incidence, lung-cancer death, and death by other causes) now includes more self-reported demographic (age, gender, race, education, body-mass index(BMI)), self-reported clinical (history of emphysema and lung-cancer family-history), and self-reported smoking (cigarettes per day, smoking duration, and smoking pack-years
JAMA. Author manuscript; available in PMC 2016 June 09.
Katki et al.
Page 4
Author Manuscript
and quit-years) variables. Variables and parameterization for continuous variables were selected using the Akaike Information Criterion. See Supplemental Methods for details. Validation of the lung-cancer death model for US ever-smokers ages 50-80 years used NHIS surveys 1997-2001 because age at smoking initiation was not systematically collected before 1997. Via NDI linkage through 2006, each NHIS participant had at least five years of follow-up for lung-cancer death. Multiple-imputation was used to account for the
