Doctor of Philosophy, University of Miami, Industrial Engineering (2017)
Master of Science, University of Tehran, Industrial Engineering (2013)
Bachelor of Science, Sharif University of Technology, Industrial and System Engineering (2011)
A comparative modeling analysis of risk-based lung cancer screening strategies.
Journal of the National Cancer Institute
Risk-prediction models have been proposed to select individuals for lung cancer screening. However, their long-term effects are uncertain. This study evaluates long-term benefits and harms of risk-based screening compared to current United States Preventive Services Task Force (USPSTF) recommendations.Four independent natural-history models performed a comparative modeling study evaluating long-term benefits and harms of selecting individuals for lung cancer screening through risk-prediction models. 363 risk-based screening strategies varying by screening starting and stopping age, risk-prediction model used for eligibility (Bach, PLCOm2012, LCDRAT), and risk-threshold were evaluated for a 1950 U.S. birth-cohort. Among the evaluated outcomes were percentage of individuals ever screened, screens required, lung cancer deaths averted, life-years gained and overdiagnosis.Risk-based screening strategies requiring similar screens among individuals aged 55-80 as the USPSTF-criteria (corresponding risk-thresholds: Bach: 2.8%, PLCOm2012: 1.7%, LCDRAT: 1.7%) averted considerably more lung cancer deaths (Bach: 693, PLCOm2012: 698, LCDRAT: 696, USPSTF: 613). However, life-years gained were only modestly higher (Bach: 8,660, PLCOm2012: 8,862, LCDRAT, 8,631,USPSTF: 8,590) and risk-based strategies had more overdiagnosis (Bach: 149, PLCOm2012: 147, LCDRAT: 150, USPSTF: 115). Sensitivity analyses suggests excluding individuals with limited life-expectancies (<5 years) from screening retains the life-years gained by risk-based screening, while reducing overdiagnosis by > 65.3%.Risk-based lung cancer screening strategies prevent considerably more lung cancer deaths than current recommendations. However, they yield modest additional life-years and increased overdiagnosis due to predominantly selecting older individuals. Efficient implementation of risk-based lung cancer screening requires careful consideration of life-expectancy for determining optimal individual stopping ages.
View details for DOI 10.1093/jnci/djz164
View details for PubMedID 31566216
Cost-Effectiveness Analysis of Lung Cancer Screening in the United States: A Comparative Modeling Study.
Annals of internal medicine
Recommendations vary regarding the maximum age at which to stop lung cancer screening: 80 years according to the U.S. Preventive Services Task Force (USPSTF), 77 years according to the Centers for Medicare & Medicaid Services (CMS), and 74 years according to the National Lung Screening Trial (NLST).To compare the cost-effectiveness of different stopping ages for lung cancer screening.By using shared inputs for smoking behavior, costs, and quality of life, 4 independently developed microsimulation models evaluated the health and cost outcomes of annual lung cancer screening with low-dose computed tomography (LDCT).The NLST; Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial; SEER (Surveillance, Epidemiology, and End Results) program; Nurses' Health Study and Health Professionals Follow-up Study; and U.S. Smoking History Generator.Current, former, and never-smokers aged 45 years from the 1960 U.S. birth cohort.45 years.Health care sector.Annual LDCT according to NLST, CMS, and USPSTF criteria.Incremental cost-effectiveness ratios (ICERs) with a willingness-to-pay threshold of $100 000 per quality-adjusted life-year (QALY).The 4 models showed that the NLST, CMS, and USPSTF screening strategies were cost-effective, with ICERs averaging $49 200, $68 600, and $96 700 per QALY, respectively. Increasing the age at which to stop screening resulted in a greater reduction in mortality but also led to higher costs and overdiagnosis rates.Probabilistic sensitivity analysis showed that the NLST and CMS strategies had higher probabilities of being cost-effective (98% and 77%, respectively) than the USPSTF strategy (52%).Scenarios assumed 100% screening adherence, and models extrapolated beyond clinical trial data.All 3 sets of lung cancer screening criteria represent cost-effective programs. Despite underlying uncertainty, the NLST and CMS screening strategies have high probabilities of being cost-effective.CISNET (Cancer Intervention and Surveillance Modeling Network) Lung Group, National Cancer Institute.
View details for DOI 10.7326/M19-0322
View details for PubMedID 31683314
- An evolutionary simulation optimization framework for interruptible load management in the smart grid SUSTAINABLE CITIES AND SOCIETY 2018; 41: 802–9