Title: Optimizing Personalized Screening and Diagnostic Decisions for Lung Cancer Based on Dynamic Risk Assessment and Life Expectancy

Abstract: Lung cancer is the leading cause of cancer related deaths in the United States and worldwide. Most patients are diagnosed with advanced stage disease for which available treatment interventions offer minimal survival benefit. Early detection through screening is vital to achieve cure and minimize lung cancer morbidity and mortality. Low- dose computed tomography (LDCT) has become the standard lung cancer screening modality based on data from randomized clinical trials. In 2021, the US Preventive Services Task Force (USPSTF) relaxed its lung cancer screening eligibility criteria (based on age and smoking history) providing coverage to younger and lighter smokers. Even though the eligibility expansion is expected to enhance benefits in specific population groups, many newly eligible individuals would have low lung cancer risk making it less likely to benefit from screening, but will be subject to potential harms such as false-positive findings and risks from invasive diagnostic procedures, emotional and psychological distress, and cost. Thus, it is imperative to accurately identify individuals that are likely to benefit from screening. Management of indeterminate findings is challenging, given the high rates of benign nodules detected by LDCT. Existing lung cancer screening and diagnostic guidelines ignore important risk-factors, whereas promising risk prediction models assessing screening eligibility of individuals and malignancy of indeterminate findings omit life-expectancy and remain underutilized. This research aims to develop individualized, dynamic risk-based screening and diagnostic strategies through stochastic, dynamic decision models. This project leverages the individualizEd luNG cAncer screeninG dEcisions (ENGAGE) framework – a previously developed and validated framework – that offers individualized screening decisions by dynamically assessing the risk and life expectancy of ever-smoked individuals. We will expand the current version of ENGAGE, which is based on age, sex, and smoking history, to incorporate non-smoking risk factors including race, family history and history of pulmonary disease among others, into the decision-making process. We will develop microsimulation models to simulate the progression of pulmonary nodules and overlay a partially observable Markov decision process to optimize the diagnostic management of pulmonary nodules at the patient level, based on a risk assessment for the nodule’s malignancy and information collected from serial LDCT, biopsy, PET/CT or a diagnostic blood-based biomarker. We will integrate the diagnostic module into ENGAGE to derive state-of-the-art individualized screening and diagnostic recommendations, and compare the effectiveness, efficiency, and cost-effectiveness of the updated ENGAGE framework against current practice. This project presents a new direction in lung cancer screening research paving the road towards individualized secondary cancer prevention. The expansion of the ENGAGE framework to facilitate a personalized risk-based program that integrates smoking and non-smoking risk factors, along with life expectancy, will form the basis for the development of optimal, cost-effective lung cancer screening guidelines tailored to individuals.

Link: Toumazis (R37CA271187), NIH RePORTER

Title: Development of a risk prediction and natural history models for ovarian cancer

Abstract: Ovarian cancer is the leading cause of death from any gynecologic malignancy and the 10th most common cancer in US women. Seventy-eight percent of cases are diagnosed after the cancer has spread to a different part of the body (i.e. at the regional and distant stages) when survival is poor, whereas the 5-year relative survival is over 90% for cases diagnosed at the localized stage. At this moment, no screening modality has been proven to be effective for the general population. The goals of this project are two-fold: (i) to identify individuals at high risk of developing ovarian cancer through the development of a risk prediction model; and (ii) to provide insights on the disease progression of the main histological subtypes of ovarian cancer by developing comprehensive histology-specific natural history models. Findings from this project could be used to identify the main drivers of ovarian cancer risk and subsequently find high-risk groups who may benefit the most from risk reducing interventions (such as salpingectomy and oophorectomy) and/or from participating in a risk-based screening program, and evaluate the impact of current and future preventive interventions on ovarian cancer incidence, morbidity, and mortality.

Link: Duncan Family Institute, FY22 Seed Funding

Title: Cost-effectiveness Evaluation of the 2021 US Preventive Services Task Force Recommendation for Lung Cancer Screening

Journal: JAMA Oncology

Authors:

• Iakovos Toumazis, Department of Health Services Research, MD Anderson, Houston, Texas
• Koen de Nijs, Erasmus Medical Center, Rotterdam, the Netherlands
• Pianpian Cao, Department of Epidemiology, University of Michigan, Ann Arbor
• Mehrad Bastani, Feinstein Institute for Medical Research, Northwell Health, New York, New York
• Vidit Munshi, Department of Radiology, Massachusetts General Hospital, Boston
• Kevin ten Haaf, Erasmus Medical Center, Rotterdam, the Netherlands
• Jihyoun Jeon, Department of Epidemiology, University of Michigan, Ann Arbor
• G. Scott Gazelle, Department of Radiology, Massachusetts General Hospital, Boston
• Eric J. Feuer, Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, Maryland
• Harry J. de Koning, Erasmus Medical Center, Rotterdam, the Netherlands
• Rafael Meza, Department of Epidemiology, University of Michigan, Ann Arbor
• Chung Yin Kong, Department of Medicine, Mount Sinai Hospital, New York, New York
• Summer S. Han, Quantitative Sciences Unit, Department of Medicine, Stanford University, Stanford, California
• Sylvia K. Plevritis, Department of Biomedical Data Sciences, Stanford University, Stanford, California

Abstract:

Importance The US Preventive Services Task Force (USPSTF) issued its 2021 recommendation on lung cancer screening, which lowered the starting age for screening from 55 to 50 years and the minimum cumulative smoking exposure from 30 to 20 pack-years relative to its 2013 recommendation. Although costs are expected to increase because of the expanded screening eligibility criteria, it is unknown whether the new guidelines for lung cancer screening are cost-effective.

Objective To evaluate the cost-effectiveness of the 2021 USPSTF recommendation for lung cancer screening compared with the 2013 recommendation and to explore the cost-effectiveness of 6 alternative screening strategies that maintained a minimum cumulative smoking exposure of 20 pack-years and an ending age for screening of 80 years but varied the starting ages for screening (50 or 55 years) and the number of years since smoking cessation (≤15, ≤20, or ≤25).

Design, Setting, and Participants A comparative cost-effectiveness analysis using 4 independently developed microsimulation models that shared common inputs to assess the population-level health benefits and costs of the 2021 recommended screening strategy and 6 alternative screening strategies compared with the 2013 recommended screening strategy. The models simulated a 1960 US birth cohort. Simulated individuals entered the study at age 45 years and were followed up until death or age 90 years, corresponding to a study period from January 1, 2005, to December 31, 2050.

Exposures Low-dose computed tomography in lung cancer screening programs with a minimum cumulative smoking exposure of 20 pack-years.

Main Outcomes and Measures Incremental cost-effectiveness ratio (ICER) per quality-adjusted life-year (QALY) of the 2021 vs 2013 USPSTF lung cancer screening recommendations as well as 6 alternative screening strategies vs the 2013 USPSTF screening strategy. Strategies with a mean ICER lower than $100 000 per QALY were deemed cost-effective.

Results The 2021 USPSTF recommendation was estimated to be cost-effective compared with the 2013 recommendation, with a mean ICER of $72 564 (range across 4 models, $59 493-$85 837) per QALY gained. The 2021 recommendation was not cost-effective compared with 6 alternative strategies that used the 20 pack-year criterion. Strategies associated with the most cost-effectiveness included those that expanded screening eligibility to include a greater number of former smokers who had not smoked for a longer duration (ie, ≤20 years and ≤25 years since smoking cessation vs ≤15 years since smoking cessation). In particular, the strategy that screened former smokers who quit within the past 25 years and began screening at age 55 years was associated with screening coverage closest to that of the 2021 USPSTF recommendation yet yielded greater cost-effectiveness, with a mean ICER of $66 533 (range across 4 models, $55 693-$80 539).

Conclusions and Relevance This economic evaluation found that the 2021 USPSTF recommendation for lung cancer screening was cost-effective; however, alternative screening strategies that maintained a minimum cumulative smoking exposure of 20 pack-years but included individuals who quit smoking within the past 25 years may be more cost-effective and warrant further evaluation.

Link: Toumazis I, de Nijs K, Cao P, et al. Cost-effectiveness Evaluation of the 2021 US Preventive Services Task Force Recommendation for Lung Cancer Screening. JAMA Oncol. Published online October 21, 2021. doi:10.1001/jamaoncol.2021.4942

Accompanied Editorial: Mulshine JL, Pyenson B. The Long, Slow Road to Lung Cancer Cure. JAMA Oncol. Published online October 21, 2021. doi:10.1001/jamaoncol.2021.4711

Title: A Cost-Effectiveness Analysis of Lung Cancer Screening with Low-Dose Computed Tomography and a Diagnostic Biomarker

Journal: JNCI Cancer Spectrum

Authors:

• Iakovos Toumazis, Departments of Biomedical Data Sciences and Radiology, Stanford University, Stanford, California
• S Ayca Erdogan, Department of Radiology, Stanford University, Stanford, California
• Mehrad Bastani, Departments of Biomedical Data Sciences and Radiology, Stanford University, Stanford, California
• Ann Leung , Department of Radiology, Stanford University, Stanford, California
• Sylvia K. Plevritis, Departments of Biomedical Data Sciences and Radiology, Stanford University, Stanford, California

Abstract:

Background The Lung Computed Tomography Screening Reporting and Data System (Lung-RADS) reduces the false-positive rate of lung cancer screening but introduces prolonged periods of uncertainty for indeterminate findings. We assess the cost-effectiveness of a screening program that assesses indeterminate findings earlier via a hypothetical diagnostic biomarker introduced in place of Lung-RADS 3 and 4A guidelines.

Methods We evaluated the performance of the US Preventive Services Task Force (USPSTF) recommendations on lung cancer screening with and without a hypothetical non-invasive diagnostic biomarker using a validated microsimulation model. The diagnostic biomarker assesses the malignancy of indeterminate nodules, replacing Lung-RADS 3 and 4A guidelines, and is characterized by a varying sensitivity profile that depends on nodule’s size, specificity, and cost. We tested the robustness of our findings through univariate sensitivity analyses.

Results A lung cancer screening program per the USPSTF guidelines that incorporates a diagnostic biomarker with at least medium sensitivity profile and 90% specificity, that costs ≤$250, is cost-effective with an incremental cost-effectiveness ratio lower than $100,000 per quality-adjusted life year, and improves lung cancer-specific mortality reduction while requiring fewer screening exams than the USPSTF guidelines with Lung-RADS. A screening program with a biomarker costing ≥$750 is not cost-effective. The health benefits accrued and costs associated with the screening program are sensitive to the disutility of indeterminate findings and specificity of the biomarker, respectively.

Conclusions Lung cancer screening that incorporates a diagnostic biomarker, in place of Lung-RADS 3 and 4A guidelines, could improve the cost-effectiveness of the screening program and warrants further investigation.

Link: Toumazis I, Erdogan SA, Bastani M, Leung A, Plevritis SK, "A Cost-Effectiveness Analysis of Lung Cancer Screening with Low-Dose Computed Tomography and a Diagnostic Biomarker,"" JNCI Cancer Spectrum, 2021; pkab081, doi: 10.1093/jncics/pkab081

Title: Evaluation of Alternative Diagnostic Follow-up Intervals for Lung Reporting and Data System Criteria on the Effectiveness of Lung Cancer Screening

Journal: Cancer

Authors:

• Mehrad Bastani, Departments of Biomedical Data Sciences and Radiology, Stanford University, Stanford, California
• Iakovos Toumazis, Departments of Biomedical Data Sciences and Radiology, Stanford University, Stanford, California
• Julien Hedou, Department of Biomedical Data Sciences, Stanford University, Stanford, California
• Ann Leung , Department of Radiology, Stanford University, Stanford, California
• Sylvia K. Plevritis, Departments of Biomedical Data Sciences and Radiology, Stanford University, Stanford, California

Abstract:

Purpose The ACR developed the Lung CT Screening Reporting and Data System (Lung-RADS) to standardize the diagnostic follow-up of suspicious screening findings. A retrospective analysis showed that Lung-RADS would have reduced the false-positive rate in the National Lung Screening Trial, but the optimal timing of follow-up examinations has not been established. In this study, we assess the effectiveness of alternative diagnostic follow-up intervals on lung cancer screening.

Methods We used the Lung Cancer Outcome Simulator to estimate population-level outcomes of alternative diagnostic follow-up intervals for Lung-RADS categories 3 and 4A. The Lung Cancer Outcome Simulator is a microsimulation model developed within the Cancer Intervention and Surveillance Modeling Network Consortium to evaluate outcomes of national screening guidelines. Here, among the evaluated outcomes are percentage of mortality reduction, screens performed, lung cancer deaths averted, screen-detected cases, and average number of screens and follow-ups per death averted.

Results The recommended 3-month follow-up interval for Lung-RADS category 4A is optimal. However, for Lung-RADS category 3, a 5-month, instead of the recommended 6-month, follow-up interval yielded a higher mortality reduction (0.08% for men versus 0.05% for women), and a higher number of deaths averted (36 versus 27), a higher number of screen-detected cases (13 versus 7), and a lower number of combined low-dose CTs and diagnostic follow-ups per death avoided (8 versus 5), per one million general population. Sensitivity analysis of nodule progression threshold verifies a higher mortality reduction with a 1-month earlier follow-up for Lung-RADS 3.

Conclusions One-month earlier diagnostic follow-ups for individuals with Lung-RADS category 3 nodules may result in a higher mortality reduction and warrants further investigation.

Link: Bastani M, Toumazis I, Hedou' J, Leung A, Plevritis SK. Evaluation of Alternative Diagnostic Follow-up Intervals for Lung Reporting and Data System Criteria on the Effectiveness of Lung Cancer Screening. J Am Coll Radiol. 2021 Aug 19:S1546-1440(21)00642-6. doi: 10.1016/j.jacr.2021.08.001. Epub ahead of print. PMID: 34419477.

Title: A risk-based framework for assessing real-time lung cancer screening eligibility that incorporates life expectancy and past screening findings

Journal: Cancer

Authors:

• Iakovos Toumazis, Departments of Biomedical Data Sciences and Radiology, Stanford University, Stanford, California
• Oguzhan Alagoz, Department of Industrial and Systems Engineering, University of Wisconsin-Madison, Madison, Wisconsin
• Ann Leung , Department of Radiology, Stanford University, Stanford, California
• Sylvia K. Plevritis, Departments of Biomedical Data Sciences and Radiology, Stanford University, Stanford, California

Abstract:

Background Current lung cancer risk-based screening approaches use a single risk-threshold, disregard life-expectancy, and ignore past screening findings. We address these limitations with a comprehensive analytical framework, the individualized lung cancer screening decision (ENGAGE) tool that aims to optimize lung cancer screening for US ever-smokers under dynamic risk assessment by incorporating life expectancy and past screening findings over time.

Methods ENGAGE employs a partially observable Markov decision process framework that integrates published risk prediction and disease progression models, to dynamically assess the trade-off between the expected health benefits and harms associated with screening. ENGAGE evaluates lung cancer risk annually and provides real-time screening eligibility that maximizes the expected quality-adjusted life-years (QALYs) of ever-smokers. We compare ENGAGE against the 2013 U.S. Preventive Services Task Force (USPSTF) lung cancer screening guideline and single-threshold risk-based screening paradigms.

Results Compared with the 2013 USPSTF guidelines, ENGAGE expands screening coverage among ever-smokers (ENGAGE: 78%, USPSTF: 61%), while reducing the number of screening examinations per person (ENGAGE:10.43, USPSTF:12.07, P < .001), yields higher effectiveness in terms of increased lung cancer-specific mortality reduction (ENGAGE: 19%, USPSTF: 15%, P < .001) and improves screening efficiency (ENGAGE: 696, USPSTF: 819 screens per death avoided, P < .001). When compared against a single-threshold risk-based screening strategy, ENGAGE increases QALY requiring 30% fewer screens per death avoided (ENGAGE: 696, single-threshold: 889, P < .001), and reduces false positives by 40%.

Conclusions ENGAGE provides a comprehensive framework for dynamic risk-based assessment of lung cancer screening eligibility by incorporating life expectancy and past screening findings that can serve to guide future policies on the effectiveness and efficiency of screening.

Link: Toumazis I, Alagoz O, Leung A, Plevritis SK. "A risk-based framework for assessing real-time lung cancer screening eligibility that incorporates life expectancy and past screening findings." Cancer. 2021 Aug 12. doi: 10.1002/cncr.33835. Epub ahead of print. PMID: 34383299.

Accompanied Editorial: Gould MK. Personalized lung cancer screening: Are we ready to ENGAGE? Cancer. 2021 Aug 12. doi: 10.1002/cncr.33839. Epub ahead of print. PMID: 34383308.

Title: Evaluation of the Benefits and Harms of Lung Cancer Screening With Low-Dose Computed Tomography - Modeling Study for the US Preventive Services Task Force

Journal: JAMA

Authors:

• Rafael Meza, Department of Epidemiology, University of Michigan, Ann Arbor
• Jihyoun Jeon, Department of Epidemiology, University of Michigan, Ann Arbor
• Iakovos Toumazis, Departments of Biomedical Data Sciences and Radiology, Stanford University, Stanford, California
• Kevin ten Haaf, Erasmus Medical Center, Rotterdam, the Netherlands
• Pianpian Cao, Department of Epidemiology, University of Michigan, Ann Arbor
• Mehrad Bastani, Departments of Biomedical Data Sciences and Radiology, Stanford University, Stanford, California
• Summer S. Han, Quantitative Sciences Unit, Department of Medicine, Stanford University, Stanford, California
• Erik F. Blom, , Erasmus Medical Center, Rotterdam, the Netherlands
• Daniel E. Jonas, RTI International–University of North Carolina Evidence-based Practice Center, Chapel Hill
• Eric J. Feuer, Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, Maryland
• Sylvia K. Plevritis, Departments of Biomedical Data Sciences and Radiology, Stanford University, Stanford, California
• Harry J. de Koning, Erasmus Medical Center, Rotterdam, the Netherlands
• Chung Yin Kong, Department of Radiology, Massachusetts General Hospital, Boston

Abstract:

Importance The US Preventive Services Task Force (USPSTF) is updating its 2013 lung cancer screening guidelines, which recommend annual screening for adults aged 55 through 80 years who have a smoking history of at least 30 pack-years and currently smoke or have quit within the past 15 years.

Objective To inform the USPSTF guidelines by estimating the benefits and harms associated with various low-dose computed tomography (LDCT) screening strategies.

Design, Setting, and Participants Comparative simulation modeling with 4 lung cancer natural history models for individuals from the 1950 and 1960 US birth cohorts who were followed up from aged 45 through 90 years.

Exposures Screening with varying starting ages, stopping ages, and screening frequency. Eligibility criteria based on age, cumulative pack-years, and years since quitting smoking (risk factor–based) or on age and individual lung cancer risk estimation using risk prediction models with varying eligibility thresholds (risk model–based). A total of 1092 LDCT screening strategies were modeled. Full uptake and adherence were assumed for all scenarios.

Main Outcomes and Measures Estimated lung cancer deaths averted and life-years gained (benefits) compared with no screening. Estimated lifetime number of LDCT screenings, false-positive results, biopsies, overdiagnosed cases, and radiation-related lung cancer deaths (harms).

Results Efficient screening programs estimated to yield the most benefits for a given number of screenings were identified. Most of the efficient risk factor–based strategies started screening at aged 50 or 55 years and stopped at aged 80 years. The 2013 USPSTF–recommended criteria were not among the efficient strategies for the 1960 US birth cohort. Annual strategies with a minimum criterion of 20 pack-years of smoking were efficient and, compared with the 2013 USPSTF–recommended criteria, were estimated to increase screening eligibility (20.6%-23.6% vs 14.1% of the population ever eligible), lung cancer deaths averted (469-558 per 100 000 vs 381 per 100 000), and life-years gained (6018-7596 per 100 000 vs 4882 per 100 000). However, these strategies were estimated to result in more false-positive test results (1.9-2.5 per person screened vs 1.9 per person screened with the USPSTF strategy), overdiagnosed lung cancer cases (83-94 per 100 000 vs 69 per 100 000), and radiation-related lung cancer deaths (29.0-42.5 per 100 000 vs 20.6 per 100 000). Risk model–based vs risk factor–based strategies were estimated to be associated with more benefits and fewer radiation-related deaths but more overdiagnosed cases.

Conclusions and Relevance Microsimulation modeling studies suggested that LDCT screening for lung cancer compared with no screening may increase lung cancer deaths averted and life-years gained when optimally targeted and implemented. Screening individuals at aged 50 or 55 years through aged 80 years with 20 pack-years or more of smoking exposure was estimated to result in more benefits than the 2013 USPSTF–recommended criteria and less disparity in screening eligibility by sex and race/ethnicity.

Link: Meza R., Jeon J., Toumazis I., ten Haaf K., Cao P., Bastani M., Han S.S., Blom E.F., Jonas D.E., Feuer E.J., Plevritis S.K., de Koning H.J., Kong C.Y., "Evaluation of the Benefits and Harms of Lung Cancer Screening With Low-Dose Computed Tomography - Modeling Study for the US Preventive Services Task Force," JAMA, 2021;325(10):988-997, doi:10.1001/jama.2021.1077

Title: Cost-effectiveness of laparoscopic disease assessment in patients with newly diagnosed advanced ovarian cancer

Journal: Gynecologic Oncology

Authors:

• Ross F. Harrison, The University of Texas MD Anderson Cancer Center, Houston, TX
• Scott B. Cantor, The University of Texas MD Anderson Cancer Center, Houston, TX
• Charlotte C. Sun, The University of Texas MD Anderson Cancer Center, Houston, TX
• Mariana Villanueva, The University of Texas MD Anderson Cancer Center, Houston, TX
• Shannon N. Westin, The University of Texas MD Anderson Cancer Center, Houston, TX
• Nicole D. Fleming, The University of Texas MD Anderson Cancer Center, Houston, TX
• Iakovos Toumazis, The University of Texas MD Anderson Cancer Center, Houston, TX
• Anil K. Sood, The University of Texas MD Anderson Cancer Center, Houston, TX
• Karen H. Lu, The University of Texas MD Anderson Cancer Center, Houston, TX
• Larissa A. Meyer, The University of Texas MD Anderson Cancer Center, Houston, TX

Abstract:

Objective To determine if laparoscopy is a cost-effective way to assess disease resectability in patients with newly diagnosed advanced ovarian cancer.

Methods A cost-effectiveness analysis from a health care payer perspective was performed comparing two strategies: (1) a standard evaluation strategy, where a conventional approach to treatment planning was used to assign patients to either primary cytoreduction (PCS) or neoadjuvant chemotherapy with interval cytoreduction (NACT), and (2) a laparoscopy strategy, where patients considered candidates for PCS would undergo laparoscopy to triage between PCS or NACT based on the laparoscopy-predicted likelihood of complete gross resection. A microsimulation model was developed that included diagnostic work-up, surgical and adjuvant treatment, perioperative complications, and progression-free survival (PFS). Model parameters were derived from the literature and our published data. Effectiveness was defined in quality-adjusted PFS years. Results were tested with deterministic and probabilistic sensitivity analysis (PSA). The willingness-to-pay (WTP) threshold was set at $50,000 per year of quality-adjusted PFS.

Results The laparoscopy strategy led to additional costs (average additional cost $7034) but was also more effective (average 4.1 months of additional quality-adjusted PFS). The incremental cost-effectiveness ratio (ICER) of laparoscopy was $20,376 per additional year of quality-adjusted PFS. The laparoscopy strategy remained cost-effective even as the cost added by laparoscopy increased. The benefit of laparoscopy was influenced by mitigation of serious complications and their associated costs. The laparoscopy strategy was cost-effective across a range of WTP thresholds.

Conclusions Performing laparoscopy is a cost-effective way to improve primary treatment planning for patients with untreated advanced ovarian cancer.

Link: Harrison R.F., Cantor S.B., Sun C.C., Villanueva M., Westin S.N., Fleming N.D., Toumazis I., Sood A.K., Lu K.H., Meyer L.A., "Cost-effectiveness of laparoscopic disease assessment in patients with newly diagnosed advanced ovarian cancer," Gynecologic Oncology, In Press, 2021, doi:10.1016/j.ygyno.2021.01.024

Title: Risk-based lung cancer screening: A systematic review

Journal: Lung Cancer

Authors:

• Iakovos Toumazis, Stanford University, Stanford, CA
• Mehrad Bastani, Stanford University, Stanford, CA
• Summer S. Han, Stanford University, Stanford, CA
• Sylvia K. Plevritis, Stanford University, Stanford, CA

Abstract:

Lung cancer remains the leading cause of cancer related deaths worldwide. Lung cancer screening using low-dose computed tomography (LDCT) has been shown to reduce lung cancer specific mortality. In 2013, the United States Preventive Services Task Force (USPSTF) recommended annual lung cancer screening with LDCT for smokers aged between 55 years to 80 years, with at least 30 pack-years of smoking exposure that currently smoke or who have quit smoking within 15 years. Risk-based lung cancer screening is an alternative approach that defines screening eligibility based on the personal risk of individuals. Selection of individuals for lung cancer screening based on their personal lung cancer risk has been shown to improve the sensitivity and specificity associated with the eligibility criteria of the screening program as compared to the 2013 USPSTF criteria. Numerous risk prediction models have been developed to estimate the lung cancer risk of individuals incorporating sociodemographic, smoking, and clinical risk factors associated with lung cancer, including age, smoking history, sex, race/ethnicity, personal and family history of cancer, and history of emphysema and chronic obstructive pulmonary disease (COPD), among others. Some risk prediction models include biomarker information, such as germline mutations or protein-based biomarkers as independent risk predictors, in addition to clinical, smoking, and sociodemographic risk factors. While, the majority of lung cancer risk prediction models are suitable for selecting high-risk individuals for lung cancer screening, some risk models have been developed to predict the probability of malignancy of screen-detected solidary pulmonary nodules or to optimize the screening frequency of eligible individuals by incorporating past screening findings. In this systematic review, we provide an overview of existing risk prediction models and their applications to lung cancer screening. We discuss potential strengths and limitations of lung cancer screening using risk prediction models and future research directions.

Link: Toumazis I., Bastani M., Han S.S., Plevritis S.K., "Risk-based lung cancer screening: A systematic review," Lung Cancer, Vol 147, pp. 154-186, 2020, doi:10.1016/j.lungcan.2020.07.007

Title: Disparities of national lung cancer screening guidelines in the U.S. population

Journal: Journal of the National Cancer Institute

Authors:

• Summer S. Han, Stanford University, Stanford, CA
• Eric Chow, Stanford University, Stanford, CA
• Kevin ten Haaf, Erasmus MC University Medical Center, Rotterdam, the Netherlands
• Iakovos Toumazis, Stanford University, Stanford, CA
• Pianpian Cao, University of Michigan, Ann Arbor, MI
• Mehrad Bastani, Stanford University, Stanford, CA
• Martin C. Tammemägi, Brock University, St Catharines, Ontario, Canada
• Jihyoun Jeon, University of Michigan, Ann Arbor, MI
• Eric J. Feuer, NCI, Bethesda, MD
• Rafael Meza, University of Michigan, Ann Arbor, MI
• Sylvia K. Plevritis, Stanford University, Stanford, CA

Abstract:

Background: Current U.S. Preventive Services Task Force (USPSTF) lung cancer screening guidelines are based on smoking history and age (55-80 y). These guidelines may miss those at higher risk, even at lower exposures of smoking or younger ages, due to other risk factors such as race, family history or comorbidity. In this study, we characterized the demographic and clinical profiles of those selected by risk-based screening criteria but missed by USPSTF guidelines in younger (50-54 y) and older (71-80 y) age groups.

Methods: We used data from the National Health Interview Survey, the CISNET Smoking History Generator, and results of logistic prediction models to simulate life-time lung cancer risk-factor data for 100,000 individuals in the 1950-1960 birth cohorts. We calculated age-specific 6-year lung cancer risk for each individual from ages 50-90 y using the PLCOm2012 model, and evaluated age-specific screening eligibility by USPSTF guidelines and by risk-based criteria (varying thresholds between 1.3%-2.5%).

Results: In the 1950 birth cohort, 5.4% would have been ineligible for screening by USPSTF criteria in their younger ages, but eligible based on risk-based criteria. Similarly, 10.4% of the cohort would be ineligible for screening by USPSTF in older ages. Notably, high proportions of Blacks were ineligible for screening by USPSTF criteria at younger (15.6%) and older (14.2%) ages, which were statistically significantly greater than those of Whites (4.8% and 10.8%, respectively, P < 0.001). Similar results were observed with other risk thresholds and for the 1960 cohort.

Conclusion: Further consideration is needed to incorporate comprehensive risk factors, including race/ethnicity, into lung cancer screening to reduce potential racial disparities.

Link: Han S.S., Chow E., ten Haaf K., Toumazis I., Cao P., Bastani M., Tammemägi M.C., Jeon J., Feuer E.J., Meza R., Plevritis S.K., "Disparities of national lung cancer screening guidelines in the U.S. population," JNCI, 2020, doi:10.1093/jnci/djaa013

Title: Cost-Effectiveness Analysis of Lung Cancer Screening in the United States: A Comparative Modeling Study

Journal: Annals of Internal Medicine

Authors:

• Steven D. Criss, Massachusetts General Hospital, Harvard Medical School, Boston, MA
• Pianpian Cao, University of Michigan, Ann Arbor, MI
• Mehrad Bastani, Stanford University, Stanford, CA
• Kevin ten Haaf, Erasmus MC University Medical Center, Rotterdam, the Netherlands
• Yufan Chen, Massachusetts General Hospital, Harvard Medical School, Boston, MA
• Deirdre F. Sheehan, Massachusetts General Hospital, Harvard Medical School, Boston, MA
• Erik F. Blom, Erasmus MC University Medical Center, Rotterdam, the Netherlands
• Iakovos Toumazis, Stanford University, Stanford, CA
• Jihyoun Jeon, University of Michigan, Ann Arbor, MI
• Harry J. de Koning, Erasmus MC University Medical Center, Rotterdam, the Netherlands
• Sylvia K. Plevritis, Stanford University, Stanford, CA
• Rafael Meza, University of Michigan, Ann Arbor, MI
• Chung Yin Kong, Massachusetts General Hospital, Harvard Medical School, Boston, MA

Abstract:

Background: 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).

Objective: To compare the cost-effectiveness of different stopping ages for lung cancer screening.

Design: 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).

Data Sources: 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.

Target Population: Current, former, and never-smokers aged 45 years from the 1960 U.S. birth cohort.

Time Horizon: 45 years.

Perspective: Health care sector.

Intervention: Annual LDCT according to NLST, CMS, and USPSTF criteria.

Outcome Measures: Incremental cost-effectiveness ratios (ICERs) with a willingness-to-pay threshold of $100 000 per quality-adjusted life-year (QALY).

Results of Base-Case Analysis: The 4 models showed that the NLST, CMS, and USPSTF screening strategies were costeffective, 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.

Results of Sensitivity Analysis: 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%). Limitation: Scenarios assumed 100% screening adherence, and models extrapolated beyond clinical trial data.

Conclusion: 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.

Link: Criss S.D., Cao P., Bastani M., ten Haaf K., Chen Y., Sheehan D.F., Blom E.F., Toumazis I., Jeon J., de Koning H.J., Plevritis S.K., Meza R., Kong C.Y., "Cost-Effectiveness Analysis of Lung Cancer Screening in the United States: A Comparative Modeling Study," Ann Intern Med., 2019, doi:10.7326/M19-0322

Title: A comparative modeling analysis of risk-based lung cancer screening strategies

Journal: JNCI

Authors:

• Kevin ten Haaf, Erasmus MC University Medical Center, Rotterdam, the Netherlands
• Mehrad Bastani, Stanford University, Stanford, CA
• Pianpian Cao, University of Michigan, Ann Arbor, MI
• Jihyoun Jeon, University of Michigan, Ann Arbor, MI
• Iakovos Toumazis, Stanford University, Stanford, CA
• Summer S. Han, Stanford University, Stanford, CA
• Sylvia K. Plevritis, Stanford University, Stanford, CA
• Erik F. Blom, Erasmus MC University Medical Center, Rotterdam, the Netherlands
• Chung Yin Kong, Massachusetts General Hospital, Harvard Medical School, Boston, MA
• Martin C. Tammemägi, Brock University, St Catharines, Ontario, Canada
• Eric J. Feuer, NCI, Bethesda, MD
• Rafael Meza, University of Michigan, Ann Arbor, MI
• Harry J. de Koning, Erasmus MC University Medical Center, Rotterdam, the Netherlands

Abstract:

Background. 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.

Methods. 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.

Results. 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%.

Conclusions. 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.

Link: ten Haaf K., Bastani M., Cao P., Jeon J., Toumazis I., Han S.S., Plevritis S.K., Blom E.F., Kong C.Y., Tammemägi M.C., Feuer E.J., Meza R., de Koning H.J., "A comparative modeling analysis of risk-based lung cancer screening strategies," JNCI, 2019, djz164

Title: Cost-Effectiveness Analysis of Lung Cancer Screening Accounting for the Effect of Indeterminate Findings

Journal: JNCI Cancer Spectrum

Authors:

• Iakovos Toumazis, Stanford University, Stanford, CA
• Emily B. Tsai, Stanford University, Stanford, CA
• S. Ayca Erdogan, Stanford University, Stanford, CA
• Summer S. Han, Stanford University, Stanford, CA
• Wenshuai Wan, Stanford University, Stanford, CA
• Ann Leung, Stanford University, Stanford, CA
• Sylvia K. Plevritis, Stanford University, Stanford, CA

Abstract:

Background. Numerous health policy organizations recommend lung cancer screening, but no consensus exists on the optimal policy. Moreover, the impact of Lung-RADS guidelines to manage small pulmonary nodules of unknown significance (a.k.a indeterminate nodules) on the cost-effectiveness of lung cancer screening is not well established.

Methods. We assess the cost-effectiveness of 199 screening strategies that vary in terms of age and smoking eligibility criteria, using a microsimulation model. We simulate lung cancer related events throughout the lifetime of U.S.-representative current and former smokers. We conduct sensitivity analyses to test key model inputs and assumptions.

Results. The cost-effectiveness efficiency frontier consists of 5 annual and 5 biennial screening strategies. Current guidelines are not on the frontier. Assuming 4% disutility associated with indeterminate findings, biennial screening for smokers aged 50–70 with ≥40 pack-years and '<'10 years since smoking cessation is the cost-effective strategy using $100,000 willingness-to-pay threshold with the highest health benefit. Among all health utilities, the cost-effectiveness of screening is most sensitive to changes in the disutility of indeterminate findings. As the disutility of indeterminate findings decreases, screening eligibility criteria become less stringent and eventually annual screening for smokers aged 50–70 with ≥30 pack-years and '<'10 years since smoking cessation is the cost-effective strategy with the highest health benefit.

Conclusions. The disutility associated with indeterminate findings impacts the cost-effectiveness of lung cancer screening. Efforts to quantify and better understand the impact of indeterminate findings on the effectiveness and cost-effectiveness of lung cancer screening are warranted.

Link: Toumazis I., Tsai E.B., Erdogan S.A., Han, S.S., Wan, W., Leung, A., Plevritis, S.K., "Cost-Effectiveness Analysis of Lung Cancer Screening Accounting for the Effect of Indeterminate Findings", JNCI Cancer Spectrum, 2019.

Title: Development and validation of a multivariable lung cancer risk prediction model that includes low-dose computed tomography screening results: A secondary analysis of data from the National Lung Screening Trial

Journal: JAMA Network Open

Authors:

• Martin C. Tammemägi, Brock University, St Catharines, Ontario, Canada
• Kevin ten Haaf, Erasmus MC University Medical Center, Rotterdam, the Netherlands
• Iakovos Toumazis, Stanford University, Stanford, CA
• Chung Yin Kong, Massachusetts General Hospital, Harvard Medical School, Boston, MA
• Summer Han, Stanford University, Stanford, CA
• Jihyoun Jeon, University of Michigan, Ann Arbor, MI
• John Commins, Information Management Systems, Rockville, Maryland
• Thomas Riley, Information Management Systems, Rockville, Maryland
• Rafael Meza, University of Michigan, Ann Arbor, MI

Abstract:

Importance. Low-dose computed tomography lung cancer screening is most effective when applied to high-risk individuals.

Objectives. To develop and validate a risk prediction model that incorporates low-dose computed tomography screening results.

Design, Setting, and Participants. A logistic regression risk model was developed in National Lung Screening Trial (NLST) Lung Screening Study (LSS) data and was validated in NLST American College of Radiology Imaging Network (ACRIN) data. The NLST was a randomized clinical trial that recruited participants between August 2002 and April 2004, with follow-up to December 31, 2009. This secondary analysis of data from the NLST took place between August 10, 2013, and November 1, 2018. Included were LSS (n = 14 576) and ACRIN (n = 7653) participants who had 3 screens, adequate follow-up, and complete predictor information.

Main Outcomes and Measures. Incident lung cancers occurring 1 to 4 years after the third screen (202 LSS and 96 ACRIN). Predictors included scores from the validated PLCOm2012 risk model and Lung CT Screening Reporting & Data System (Lung-RADS) screening results.

Results. Overall, the mean (SD) age of 22 229 participants was 61.3 (5.0) years, 59.3% were male, and 90.9% were of non-Hispanic white race/ethnicity. During follow-up, 298 lung cancers were diagnosed in 22 229 individuals (1.3%). Eight result combinations were pooled into 4 groups based on similar associations. Adjusted for PLCOm2012 risks, compared with participants with 3 negative screens, participants with 1 positive screen and last negative had an odds ratio (OR) of 1.93 (95% CI, 1.34-2.76), and participants with 2 positive screens with last negative or 2 negative screens with last positive had an OR of 2.66 (95% CI, 1.60-4.43); when 2 or more screens were positive with last positive, the OR was 8.97 (95% CI, 5.76-13.97). In ACRIN validation data, the model that included PLCOm2012 scores and screening results (PLCO2012results) demonstrated significantly greater discrimination (area under the curve, 0.761; 95% CI, 0.716-0.799) than when screening results were excluded (PLCOm2012) (area under the curve, 0.687; 95% CI, 0.645-0.728) (P < .001). In ACRIN validation data, PLCO2012results demonstrated good calibration. Individuals who had initial negative scans but elevated PLCOm2012 six-year risks of at least 2.6% did not have risks decline below the 1.5% screening eligibility criterion when subsequent screens were negative.

Conclusions and Relevance. According to this analysis, some individuals with elevated risk scores who have negative initial screens remain at elevated risks, warranting annual screening. Positive screens seem to increase baseline risk scores and may identify high-risk individuals for continued screening and enrollment into clinical trials.

Link: Tammemägi M.C., ten Haaf K., Toumazis I., Kong C.Y., Han S.S., Jeon J., Commins J., Riley T., Meza R., "Development and validation of a multivariable lung cancer risk prediction model that includes low-dose computed tomography screening results: A secondary analysis of data from the National Lung Screening Trial", JAMA Network Open, 2019, 2(3):e190204

Title: Personalized lung cancer screening strategies using a partially observable Markov decision process

Presenting Author: Iakovos Toumazis, Postdoctoral Research Fellow, Departments of Biomedical Data Science & Radiology, Stanford University, iakovos.toumazis[at]stanford.edu

Co-Author(s):

• Oguzhan Alagoz, University of Wisconsin-Madison, Madison, WI
• Ann Leung, Stanford University, Stanford, CA
• Sylvia K. Plevritis, Stanford University, Stanford, CA

Abstract:The US Preventive Services Task Force recommends lung cancer (LC) screening for high risk individuals aged 55-80 with at least 30 pack-years, and no more than 15 years since smoking cessation. Many other risk factors are associated with LC incidence, yet screening eligibility is solely based on age and smoking history, leading to sub-optimal screening strategies. We propose a partially observable Markov decision process (POMDP) that provides individualized optimal screening strategies for current and former smokers. Decisions are made based on the risk of the individuals accounting for previous screening results and changes in individuals’ smoking behavior.

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Title: The Effect of Indeterminate Findings on the Cost-effectiveness of Lung Cancer Screening

Presenting Author: Iakovos Toumazis, Postdoctoral Research Fellow, Departments of Biomedical Data Science & Radiology, Stanford University, iakovos.toumazis[at]stanford.edu

Co-Author(s):

• Emily Tsai, University of California, Los Angeles, Los Angeles, CA
• Ayca Erdogan, San Jose State University, San Jose, CA
• Summer Han, Stanford University, Stanford, CA
• Wenshuai Wan, University of Pennsylvania, Philadelphia, PA
• Ann Leung, Stanford University, Stanford, CA
• Sylvia K. Plevritis, Stanford University, Stanford, CA

Abstract:The US Preventive Services Task Force recommends lung cancer (LC) screening for high risk individuals, yet the effect of indeterminate findings on the cost-effectiveness of LC screening is not established. We use a microsimulation model to estimate the cost-effectiveness of alternative LC screening strategies for the US general population under alternative levels of disutility associated with indeterminate findings. We find that as the effect of the disutility of indeterminate findings increases, the eligibility criteria for LC screening become more stringent and if large enough then biennial screening is cost-effective whereas, annual screening is cost-ineffective.

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Title: Evaluation of Alternative Diagnostic Test Intervals and Thresholds for LungRADS Criteria on the Effectiveness of Lung Cancer Screening

Presenting Author: Mehrad Bastani, Postdoctoral Research Fellow, Departments of Biomedical Data Science & Radiology, Stanford University

Co-Author(s):

• Sylvia K. Plevritis, Stanford University, Stanford, CA
• Iakovos Toumazis, Stanford University, Stanford, CA
• Ann Leung, Stanford University, Stanford, CA

Abstract:U.S. Preventive Services Task Force recently recommended a low-dose computed tomography (LDCT) lung screening for high-risk current and former smokers based on the National Lung Screening Trial (NLST). In response to the high rates of false-positive observed in NLST (27.3%), the American College of Radiology developed Lung-RADS, a standardized system for reporting and following-up LDCT findings. Several studies have shown reduction in false-positive rate when Lung-RADs is applied to NLST. To complement these studies, we evaluate the effect of alternative diagnostic testing intervals and actionable nodule size thresholds of Lung-RADs on the mortality reduction associated with LC screening.

Title: Impact Of False-Positives On The Cost-effectiveness of Lung Cancer Screening

Presenting Author: Iakovos Toumazis, Postdoctoral Research Fellow, Department of Radiology, Stanford University, iakovos.toumazis[at]stanford.edu

Co-Author(s):

• Emily Tsai, University of California, Los Angeles, Los Angeles, CA
• Ayca Erdogan, San Jose State University, San Jose, CA
• Summer Han, Stanford University, Stanford, CA
• Wenshuai Wan, University of Pennsylvania, Philadelphia, PA
• Ann Leung, Stanford University, Stanford, CA
• Sylvia K. Plevritis, Stanford University, Stanford, CA

Abstract:We assess the benefits and costs of various screening strategies for lung cancer (LC) using a data driven microsimulation model. We simulate individuals’ LC progression in the presence and absence of screening strategies, which vary in terms of starting and stopping age, screening frequency, and smoking criteria. We identify the efficiency frontier and show that the cost-effectiveness of LC screening is significantly affected by the management of false-positive results. We examine the effect of the number of subsequent exams and disutility associated with false-positives and conduct univariate sensitivity analyses to test the robustness of our findings to changes in key input model parameters.

Title: Evaluating the impact of varied compliance to lung cancer screening recommendations using a microsimulation model

Journal: Cancer Causes & Control

Authors:

• Summer Han, Stanford University, Stanford, CA
• Ayca Erdogan, San Jose State University, San Jose, CA
• Iakovos Toumazis, Stanford University, Stanford, CA
• Ann Leung, Stanford University, Stanford, CA
• Sylvia K. Plevritis, Stanford University, Stanford, CA

Abstract:

Background The US preventive services task force (USPSTF) recently recommended that individuals aged 55–80 with heavy smoking history be annually screened by low-dose computed tomography (LDCT), thereby extending the stopping age from 74 to 80 compared to the national lung screening trial (NLST) entry criterion. This decision was made partly with model-based analyses from cancer intervention and surveillance modeling network (CISNET), which assumed perfect compliance to screening. Methods As part of CISNET, we developed a microsimulation model for lung cancer (LC) screening and calibrated and validated it using data from NLST and the prostate, lung, colorectal, and ovarian cancer screening trial (PLCO), respectively. We evaluated population-level outcomes of the lifetime screening program recommended by the USPSTF by varying screening compliance levels. Results Validation using PLCO shows that our model reproduces observed PLCO outcomes, predicting 884 LC cases [Expected(E)/Observed(O) = 0.99; CI 0.92–1.06] and 563 LC deaths (E/O = 0.94 CI 0.87–1.03) in the screening arm that has an average compliance rate of 87.9% over four annual screening rounds. We predict that perfect compliance to the USPSTF recommendation saves 501 LC deaths per 100,000 persons in the 1950 U.S. birth cohort; however, assuming that compliance behaviors extrapolated and varied from PLCO reduces the number of LC deaths avoided to 258, 230, and 175 as the average compliance rate over 26 annual screening rounds changes from 100 to 46, 39, and 29%, respectively. Conclusion The implementation of the USPSTF recommendation is expected to contribute to a reduction in LC deaths, but the magnitude of the reduction will likely be heavily influenced by screening compliance.

Link: Han S.S., Erdogan S.A, Toumazis I., Leung A., Plevritis S.K., "Evaluating the impact of varied compliance to lung cancer screening recommendations using a microsimulation model", Cance Causes & Control, Online First

Title: Personalized, Dynamic Risk-based Lung Cancer Screening

Principal Investigator: Iakovos Toumazis, Postdoctoral Research Fellow, Department of Radiology, Stanford University, iakovos.toumazis[at]stanford.edu

Description: This project focuses on the problem of optimizing lung cancer screening for asymptomatic individuals at risk. The objective of this research is to develop stochastic, dynamic models incorporating past screening exams and the dynamic status of lung cancer risk factors to provide cost-effective, personalized, risk-based screening decisions. The anticipated findings of this proposal will improve the overall effectiveness of screening and enhance the shared decision making process between physicians and patients forming a basis for maximizing health benefit and reducing the harms associated with lung cancer screening.

For more information click here.

Title: Evaluating The Impact Of Diagnostic Biomarkers On The Cost-effective Efficiency Frontier Of Alternative Lung Cancer Screening Strategies

Presenting Author: Iakovos Toumazis, Postdoctoral Research Fellow, Department of Radiology, Stanford University, iakovost[at]stanford.edu

Co-Author(s):

• Ayca Erdogan, San Jose State University, San Jose, CA, ayca.erdogan[at]sjsu.edu
• Sylvia K. Plevritis, Stanford University, Stanford, CA, sylvia.plevritis[at]stanford.edu

Abstract: We investigate the benefits and costs of various screening strategies for lung cancer when computerized tomography is combined with a hypothetical diagnostic biomarker test using a data driven microsimulation model. The model simulates individuals’ lung cancer progression in the presence and absence of a biomarker test under different screening strategies, which vary in terms of start age, stop age and frequency of screening. We identify the cost-effective frontier and show that adding a biomarker test may potentially increase the health benefit and decrease the total cost of screening under specific screening strategies. A sensitivity analysis is conducted on the test’s accuracy and cost.

Title: Personalized Treatment Decisions For Metastatic Colorectal Cancer Patients

Presenting Author: Iakovos Toumazis, Postdoctoral Research Fellow, Department of Radiology, Stanford University, iakovost[at]stanford.edu

Co-Author(s):

• Murat Kurt, Merck Research Labs, murat.kurt7[at]gmail.com
• Toumazi Artemis, French National Institute of Health and Medical Research (INSERM), Paris, France, artemis.toumazi[at]gmail.com
• Loukia G. Karacosta, Postdoctoral Research Fellow, Department of Radiology, Stanford University, loukia[at]stanford.edu
• Changhyun Kwon, Associate Professor, University of South Florida, chkwon[at]usf.edu

Abstract: Colorectal cancer (CRC) is the third most lethal cancer in the US affecting both genders. Metastatic CRC (mCRC) is inoperable and rarely curable. Chemotherapy is the only treatment option for mCRC patients. Treatments' toxicity and tumor's drug resistance are identified as main reasons for treatment's failure. We formulated the chemotherapy scheduling problem as a finite-horizon, discrete-time Markov decision process that jointly optimize the duration and sequence of the available drugs. We calibrated our model using a clinical database developed from published clinical trials. The resulting optimal policy improves survival without compromising quality of life.

As a member of the CISNET Lung group, Iakovos Toumazis attended the Semi-Annual meeting at the Massachusetts General Hospital (MGH) in Boston, MA.

As a member of the CISNET Lung group, Iakovos Toumazis attended the Annual meeting at the NCI in Rockville, MD.

Title: Sequencing Chemotherapy Agents for Metastatic Colorectal Cancer Patients

Presenting Author: Iakovos Toumazis, Postdoctoral Research Fellow, Department of Radiology, Stanford University, iakovost[at]stanford.edu

Co-Author(s):

• Murat Kurt, Merck Research Labs, murat.kurt7[at]gmail.com
• Toumazi Artemis, Claude Bernard University Lyon 1, Department of Mathematics, artemis.toumazi[at]gmail.com
• Loukia G. Karacosta, Postdoctoral Research Fellow, Department of Radiology, Stanford University, loukia[at]stanford.edu
• Changhyun Kwon, Associate Professor, University of South Florida, chkwon[at]usf.edu
• Daniel A. Goldstein,Fellow, Department of Hematology and Medical Oncology, Winship Cancer Institute, Emory University, daniel.alexander.goldstein[at]emory.edu

Abstract: Colorectal cancer is the third most lethal cancer in the US affecting both genders. Despite advancements in chemotherapy treatment, long-term survival for the advanced stage of the disease remains poor. With the goal of improving the effectiveness of chemotherapy treatment for metastatic colorectal cancer patients we developed a Markov decision process model that jointly optimize the duration and sequence of the available drugs. The obtained optimal policy improves survival by at least 6 months.

Title: Sequencing Chemotherapy Agents for Metastatic Colorectal Cancer Patients

Presenting Author: Iakovos Toumazis, Postdoctoral Research Fellow, Department of Radiology, Stanford University, iakovost[at]stanford.edu

Co-Author(s):

• Murat Kurt, Merck Research Labs, murat.kurt7[at]gmail.com
• Toumazi Artemis, Claude Bernard University Lyon 1, Department of Mathematics, Claude Bernard University Lyon 1, France, artemis.toumazi[at]gmail.com
• Loukia G. Karacosta, Postdoctoral Research Fellow, Department of Radiology, Stanford University, loukia[at]stanford.edu
• Changhyun Kwon, Associate Professor, University of South Florida, Tampa FL, chkwon[at]usf.edu
• Daniel A. Goldstein, Fellow, Department of Hematology and Medical Oncology, Winship Cancer Institute, Emory University, Atlanta GA, daniel.alexander.goldstein[at]emory.edu

Abstract:
Purpose: Advancements in chemotherapy treatment have improved long term survival for metastatic colorectal cancer (mCRC) while raising financial concerns. We analyze the cost-effectiveness of clinically accepted combinations of up to three lines of therapies from 8 chemotherapy regimens to evaluate the progress made in colorectal cancer treatment and examine how treatment sequencing affects the effectiveness of treatment plans.
Methods: We considered the process of administering chemotherapy treatments for mCRC patients where treatments are discontinued when they lead to disease progression or 2 adverse events (AE). Upon an AE, treatment in use is paused for 2 weeks to clean the adverse effects from the event. We calibrated probability distributions for survival, disease progression, and the occurrence of AEs using published data from over 500 clinical trials and evaluated the effectiveness of treatment sequences with respect to quality-adjusted life-years (QALYs) and costs. All outcomes were discounted at a 3% annual rate. We analyzed the sensitivity of the incremental cost effectiveness ratios (ICERs) to costs and various parameters. We assessed the probabilistic efficiency behavior of the sequences, and calculated the number of AEs and occurrences of disease progressions under each of them through simulations.
Results: We tested 178 different sequences including single and two-lines of chemotherapy regimens and 8 of them formed the efficient frontier. The mean cost/QALY ranged from $5,963 to $87,430 for the efficient sequences. Under none of the efficient treatment plans, the mean number of AEs was more than 2.5 and the events were spaced more than 30 weeks apart on average. The ICER of the treatment plan consisting of FOLFOX+Bevacizumab, FOLFIRI+Bevacizumab and CapeOx was $153,820/QALY over LV5FU alone, and it was most sensitive to treatment disutility, drug cost, and the AE likelihood. While all treatment plans were efficient with at least 50% chance, those on the frontier were more robust in that all of them were efficient with at least 87% chance with more than half of them being efficient with at least 97% chance.
Conclusions: Improvements in health outcomes may come at a high incremental cost for mCRC patients and be highly dependent on sequencing of treatments. While single and two lines of therapies can be efficient based on cost/QALY, majority of the efficient sequences consist of three-lines of therapies.

Toumazis will present the project titled "A Dynamic Programming Approach to Palliative Chemotherapy Scheduling for Metastic Colorectal Cancer Patient," during the 2015 Healthcare Special Interest Group meeting at MSOM conference. The workshop will be held on Sunday June 28, 2015 at the Rotman School of Management, University of Toronto, Ontario, Canada.
The program will consist of 35-minute presentations of papers followed by 10 minutes of discussion. The selection criteria of the papers favor cutting-edge collaborative work between academics and clinicians/healthcare administrators with important methodological and practical impact.

Toumazis will present the winning paper, "Scheduling Palliative Chemotherapy Treatments for Metastatic Colorectal Cancer Patients," during the Healthcare Systems Process Improvement Conference in Orlando, Florida (February 18-20, 2015).
The paper was evaluated based on different criteria, depending on the type of submission, including: potential impact on the field or significance of the work; originality; technical quality (e.g., design, measurement, and analysis methods); presentation quality (writing, data presentation, graphics); length; integration with existing evidence; and any ethical concerns.

Some of the highlights of the paper are:

• We model the treatment decision making process for metastatic colorectal cancer patients.
• Sequence of treatments and their respective duration are jointly optimized.
• Risk of increasing toxicity levels and developing drug resistance are incorporated in the model.
• Real clinical data were used to calibrate the model.
• The proposed optimal treatment schedule prolongs the expected survival of patients.
• The optimal treatment plan maintains quality of life at high levels.

Credit should be given to the co-authors of the paper: Murat Kurt, Artemis Toumazi, Loukia G. Karacosta, and Changhyun Kwon.

Dissertation Title: "Dynamic Programming approaches to the palliative chemotherapy scheduling problem for metastatic colorectal cancer patients"

When the student has identified a research topic, has become thoroughly acquainted with previous work in that area, and explored the topic well enough to have developed a credible research plan, the student then writes a dissertation proposal.
A copy of the proposal must be submitted to each member of the Ph.D. Committee, and is defended approximately two weeks later in an oral examination that lasts approximately two hours.
The student should schedule the defense after the major professor is satisfied that the topic is significant, research plans are sound, and the student’s qualifications are adequate to address the problem. The student should not hesitate to discuss the proposal with members of the Committee in advance.

Title: Eliciting Cholesterol Management Guidelines' Valuation of Future Life

Presenting Author: Iakovos Toumazis, Universtiy at Buffalo (SUNY), Buffalo, NY

Co-Author(s):

• Brian Denton, Associate Professor, University of Michigan, btdenton[at]umich.edu
• Murat Kurt, Assistant Professor, University at Buffalo (SUNY), muratkur[at]buffalo.edu
• Osman Ozaltin, Assistant Professor, North Carolina State University, oyozalti[at]ncsu.edu
• Nilay Shah, Mayo Clinic, Division of Health Care Policy and Resea, Shah.Nilay[at]mayo.edu

Abstract: Lipid abnormalities increase the risk of heart attack and stroke. Treatment guidelines are developed to deal with the complexity of treating these abnormalities. We consider the trade-off between the benefits and side effects of statins, and develop an inverse stochastic dynamic program to elicit time valuation of current guidelines. We use clinical data to illustrate the outcomes on Type 2 diabetes patients.

Title: Eliciting Lipid Management Guidelines' Valuation of Future Life

Presenting Author: Iakovos Toumazis, Universtiy at Buffalo (SUNY), Buffalo, NY

Co-Author(s):

• Osman Ozaltin, Assistant Professor, North Carolina State University, oyozalti[at]ncsu.edu
• Murat Kurt, Assistant Professor, University at Buffalo (SUNY), muratkur[at]buffalo.edu
• Brian Denton, Associate Professor, University of Michigan, btdenton[at]umich.edu

Abstract:
Purpose: Discount factors are critical in assessing the cost effectiveness of treatments as they reflect the time value of costs and benefits. We considered the trade-off between the benefits and side effects of statins to elicit the discounted present value of each future life year for current lipid management guidelines.
Method: We formulated the statin initiation problem for Type 2 diabetes patients as a Markov decision process where the state of the process is defined as the patient's total cholesterol and high density lipoprotein (HDL) levels, and the statin initiation decision is revisited annually. We considered six guidelines: Adult Treatment Panel (ATP) III, Canadian, British, European Union, Australian and New Zealand. For each guideline, we used inverse optimization to find the discounted present value of each future life year that makes the guideline non-dominated with respect to total expected QALYs prior to a first major cardiovascular event and the risk of a first major cardiovascular event. For patients diagnosed with Type 2 diabetes at age 40, we used Mayo Clinic electronic medical records to model the progression of their total cholesterol, HDL, triglycerides, systolic blood pressure, and HbA1c. We incorporated the adverse effects of statins into the model using a constant disutility factor.
Result: Among all guidelines we considered, the underlying present values of future life years for males were never more than those of females. The present value of a life year for males varied from 20% to 70% of that for females between ages 45 and 65. All guidelines were consistent in discounting future with time-varying annual discount factors. Guidelines which initiate statins at earlier ages, such as ATP III, valued the far future more than those which initiate statins relatively later. For males, all guidelines exhibited a sharp decrease in discounting life years after age 45; for females this threshold was at age 55. While no guideline discounted the value of a life year immediately following the diagnosis of Type 2 diabetes, all guidelines were consistent with a present value of < 0.001 years beyond age 80.
Conclusion: Our analyses show that guidelines discount future life years with time-variant annual discount factors and show a substantial difference between the implied present value of life years for males and females.

The Ph.D. Advanced Examination, sometimes called the "Prelim” or “A-exam”, is taken near the end of formal course work, before substantial dissertation research has begun.
The format of the exam consists of questions from the individual committee members to which written responses are required. Although questions do not necessarily have to pertain to the student's intended dissertation research, one of the exam’s purposes is to gauge the student's capability for pursuing research in his or her area of interest.

Co-chairs:

• Changhyun Kwon, Assistant Professor, University at Buffalo, chkwon[at]buffalo.edu
• Murat Kurt, Assistant Professor, University at Buffalo, muratkur[at]buffalo.edu

Member:

• Rachael Hageman Blair, Assistant Professor, Department of Biostatistics, hageman[at]buffalo.edu

Title: Advanced Risk Measures Applied in Hazardous Materials Routing

Presenting Author: Iakovos Toumazis, PhD Student, University at Buffalo, iakovost[at]buffalo.edu

Co-Author: Changhyun Kwon, Assistant Professor, University at Buffalo, chkwon[at]buffalo.edu

Abstract: New classes of risk measures are introduced and analyzed for local route planning in hazardous materials transportation. In particular, value-at-risk, conditional value-at-risk, and a general class of spectral risk measures are considered for risk-averse and flexible routing methods. Tractable computational methods are suggested.