1
|
Toumazis I, Cao P, de Nijs K, Bastani M, Munshi V, Hemmati M, Ten Haaf K, Jeon J, Tammemägi M, Gazelle GS, Feuer EJ, Kong CY, Meza R, de Koning HJ, Plevritis SK, Han SS. Risk Model-Based Lung Cancer Screening : A Cost-Effectiveness Analysis. Ann Intern Med 2023; 176:320-332. [PMID: 36745885 PMCID: PMC11025620 DOI: 10.7326/m22-2216] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/08/2023] Open
Abstract
BACKGROUND In their 2021 lung cancer screening recommendation update, the U.S. Preventive Services Task Force (USPSTF) evaluated strategies that select people based on their personal lung cancer risk (risk model-based strategies), highlighting the need for further research on the benefits and harms of risk model-based screening. OBJECTIVE To evaluate and compare the cost-effectiveness of risk model-based lung cancer screening strategies versus the USPSTF recommendation and to explore optimal risk thresholds. DESIGN Comparative modeling analysis. DATA SOURCES National Lung Screening Trial; Surveillance, Epidemiology, and End Results program; U.S. Smoking History Generator. TARGET POPULATION 1960 U.S. birth cohort. TIME HORIZON 45 years. PERSPECTIVE U.S. health care sector. INTERVENTION Annual low-dose computed tomography in risk model-based strategies that start screening at age 50 or 55 years, stop screening at age 80 years, with 6-year risk thresholds between 0.5% and 2.2% using the PLCOm2012 model. OUTCOME MEASURES Incremental cost-effectiveness ratio (ICER) and cost-effectiveness efficiency frontier connecting strategies with the highest health benefit at a given cost. RESULTS OF BASE-CASE ANALYSIS Risk model-based screening strategies were more cost-effective than the USPSTF recommendation and exclusively comprised the cost-effectiveness efficiency frontier. Among the strategies on the efficiency frontier, those with a 6-year risk threshold of 1.2% or greater were cost-effective with an ICER less than $100 000 per quality-adjusted life-year (QALY). Specifically, the strategy with a 1.2% risk threshold had an ICER of $94 659 (model range, $72 639 to $156 774), yielding more QALYs for less cost than the USPSTF recommendation, while having a similar level of screening coverage (person ever-screened 21.7% vs. USPSTF's 22.6%). RESULTS OF SENSITIVITY ANALYSES Risk model-based strategies were robustly more cost-effective than the 2021 USPSTF recommendation under varying modeling assumptions. LIMITATION Risk models were restricted to age, sex, and smoking-related risk predictors. CONCLUSION Risk model-based screening is more cost-effective than the USPSTF recommendation, thus warranting further consideration. PRIMARY FUNDING SOURCE National Cancer Institute (NCI).
Collapse
Affiliation(s)
- Iakovos Toumazis
- Department of Health Services Research, The University of Texas MD Anderson Cancer Center, Houston, Texas (I.T., M.H.)
| | - Pianpian Cao
- Department of Epidemiology, University of Michigan, Ann Arbor, Michigan (P.C., J.J.)
| | - Koen de Nijs
- Erasmus MC-University Medical Center, Rotterdam, the Netherlands (K. de N., K. ten H., H.J. de K.)
| | - Mehrad Bastani
- Feinstein Institutes for Medical Research, Northwell Health, Manhasset, New York (M.B.)
| | - Vidit Munshi
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts (V.M., G.S.G.)
| | - Mehdi Hemmati
- Department of Health Services Research, The University of Texas MD Anderson Cancer Center, Houston, Texas (I.T., M.H.)
| | - Kevin Ten Haaf
- Erasmus MC-University Medical Center, Rotterdam, the Netherlands (K. de N., K. ten H., H.J. de K.)
| | - Jihyoun Jeon
- Department of Epidemiology, University of Michigan, Ann Arbor, Michigan (P.C., J.J.)
| | - Martin Tammemägi
- Department of Health Sciences, Brock University, St. Catharines, Ontario, Canada (M.T.)
| | - G Scott Gazelle
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts (V.M., G.S.G.)
| | - Eric J Feuer
- Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, Maryland (E.J.F.)
| | - Chung Yin Kong
- Division of General Internal Medicine, Department of Medicine, Mount Sinai Hospital, New York, New York (C.Y.K.)
| | - Rafael Meza
- Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, and Department of Integrative Oncology, BC Cancer Research Institute, British Columbia, Canada (R.M.)
| | - Harry J de Koning
- Erasmus MC-University Medical Center, Rotterdam, the Netherlands (K. de N., K. ten H., H.J. de K.)
| | - Sylvia K Plevritis
- Department of Biomedical Data Sciences, Stanford University, Stanford, California (S.K.P.)
| | - Summer S Han
- Quantitative Sciences Unit, Department of Medicine, Stanford University, Stanford, California (S.S.H.)
| |
Collapse
|
2
|
Duarte A, Corbett M, Melton H, Harden M, Palmer S, Soares M, Simmonds M. EarlyCDT Lung blood test for risk classification of solid pulmonary nodules: systematic review and economic evaluation. Health Technol Assess 2022; 26:1-184. [PMID: 36534989 PMCID: PMC9791464 DOI: 10.3310/ijfm4802] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND EarlyCDT Lung (Oncimmune Holdings plc, Nottingham, UK) is a blood test to assess malignancy risk in people with solid pulmonary nodules. It measures the presence of seven lung cancer-associated autoantibodies. Elevated levels of these autoantibodies may indicate malignant disease. The results of the test might be used to modify the risk of malignancy estimated by existing risk calculators, including the Brock and Herder models. OBJECTIVES The objectives were to determine the diagnostic accuracy, clinical effectiveness and cost-effectiveness of EarlyCDT Lung; and to develop a conceptual model and identify evidence requirements for a robust cost-effectiveness analysis. DATA SOURCES MEDLINE (including Epub Ahead of Print, In-Process & Other Non-Indexed Citations, Ovid MEDLINE Daily and Ovid MEDLINE), EMBASE, Cochrane Central Register of Controlled Trials, Science Citation Index, EconLit, Cochrane Database of Systematic Reviews, Database of Abstracts of Reviews of Effects, Health Technology Assessment database, NHS Economic Evaluation Database ( NHS EED ) and the international Health Technology Assessment database were searched on 8 March 2021. REVIEW METHODS A systematic review was performed of evidence on EarlyCDT Lung, including diagnostic accuracy, clinical effectiveness and cost-effectiveness. Study quality was assessed with the quality assessment of diagnostic accuracy studies-2 tool. Evidence on other components of the pulmonary nodule diagnostic pathway (computerised tomography surveillance, Brock risk, Herder risk, positron emission tomography-computerised tomography and biopsy) was also reviewed. When feasible, bivariate meta-analyses of diagnostic accuracy were performed. Clinical outcomes were synthesised narratively. A simulation study investigated the clinical impact of using EarlyCDT Lung. Additional reviews of cost-effectiveness studies evaluated (1) other diagnostic strategies for lung cancer and (2) screening approaches for lung cancer. A conceptual model was developed. RESULTS A total of 47 clinical publications on EarlyCDT Lung were identified, but only five cohorts (695 patients) reported diagnostic accuracy data on patients with pulmonary nodules. All cohorts were small or at high risk of bias. EarlyCDT Lung on its own was found to have poor diagnostic accuracy, with a summary sensitivity of 20.2% (95% confidence interval 10.5% to 35.5%) and specificity of 92.2% (95% confidence interval 86.2% to 95.8%). This sensitivity was substantially lower than that estimated by the manufacturer (41.3%). No evidence on the clinical impact of EarlyCDT Lung was identified. The simulation study suggested that EarlyCDT Lung might potentially have some benefit when considering intermediate risk nodules (10-70% risk) after Herder risk analysis. Two cost-effectiveness studies on EarlyCDT Lung for pulmonary nodules were identified; none was considered suitable to inform the current decision problem. The conceptualisation process identified three core components for a future cost-effectiveness assessment of EarlyCDT Lung: (1) the features of the subpopulations and relevant heterogeneity, (2) the way EarlyCDT Lung test results affect subsequent clinical management decisions and (3) how changes in these decisions can affect outcomes. All reviewed studies linked earlier diagnosis to stage progression and stage shift to final outcomes, but evidence on these components was sparse. LIMITATIONS The evidence on EarlyCDT Lung among patients with pulmonary nodules was very limited, preventing meta-analyses and economic analyses. CONCLUSIONS The evidence on EarlyCDT Lung among patients with pulmonary nodules is insufficient to draw any firm conclusions as to its diagnostic accuracy or clinical or economic value. FUTURE WORK Prospective cohort studies, in which EarlyCDT Lung is used among patients with identified pulmonary nodules, are required to support a future assessment of the clinical and economic value of this test. Studies should investigate the diagnostic accuracy and clinical impact of EarlyCDT Lung in combination with Brock and Herder risk assessments. A well-designed cost-effectiveness study is also required, integrating emerging relevant evidence with the recommendations in this report. STUDY REGISTRATION This study is registered as PROSPERO CRD42021242248. FUNDING This project was funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 26, No. 49. See the NIHR Journals Library website for further project information.
Collapse
Affiliation(s)
- Ana Duarte
- Centre for Health Economics, University of York, York UK
| | - Mark Corbett
- Centre for Reviews and Dissemination, University of York, York UK
| | - Hollie Melton
- Centre for Reviews and Dissemination, University of York, York UK
| | - Melissa Harden
- Centre for Reviews and Dissemination, University of York, York UK
| | - Stephen Palmer
- Centre for Health Economics, University of York, York UK
| | - Marta Soares
- Centre for Health Economics, University of York, York UK
| | - Mark Simmonds
- Centre for Reviews and Dissemination, University of York, York UK
| |
Collapse
|
3
|
Toumazis I, de Nijs K, Cao P, Bastani M, Munshi V, ten Haaf K, Jeon J, Gazelle GS, Feuer EJ, de Koning HJ, Meza R, Kong CY, Han SS, Plevritis SK. Cost-effectiveness Evaluation of the 2021 US Preventive Services Task Force Recommendation for Lung Cancer Screening. JAMA Oncol 2021; 7:1833-1842. [PMID: 34673885 PMCID: PMC8532037 DOI: 10.1001/jamaoncol.2021.4942] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
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.
Collapse
Affiliation(s)
- Iakovos Toumazis
- Department of Health Services Research, University of Texas MD Anderson Cancer Center, Houston
| | - 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
| | | | - Jihyoun Jeon
- Department of Epidemiology, University of Michigan, Ann Arbor
| | | | - Eric J. Feuer
- Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, Maryland
| | | | - Rafael Meza
- Department of Epidemiology, University of Michigan, Ann Arbor
| | - Chung Yin Kong
- Division of General Internal Medicine, 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
| |
Collapse
|
4
|
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; 18:1614-1623. [PMID: 34419477 DOI: 10.1016/j.jacr.2021.08.001] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Revised: 07/28/2021] [Accepted: 08/02/2021] [Indexed: 11/23/2022]
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.
Collapse
Affiliation(s)
- Mehrad Bastani
- Postdoctoral Research Fellow, Departments of Biomedical Data Science and Department of Radiology, Stanford University, Stanford, California
| | - Iakovos Toumazis
- Postdoctoral Research Fellow, Departments of Biomedical Data Science and Department of Radiology, Stanford University, Stanford, California
| | - Julien Hedou'
- Research Assistant, Department of Biomedical Data Science, Stanford University, Stanford, California
| | - Ann Leung
- Professor, Department of Radiology, Stanford University, Stanford, California
| | - Sylvia K Plevritis
- Departments of Biomedical Data Science and Department of Radiology, Stanford University, Stanford, California.
| |
Collapse
|
5
|
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 Spectr 2021; 5:pkab081. [PMID: 34738073 PMCID: PMC8564700 DOI: 10.1093/jncics/pkab081] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Revised: 08/12/2021] [Accepted: 08/20/2021] [Indexed: 12/17/2022] Open
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 noninvasive 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 nodules' 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 or less, 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 or more 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.
Collapse
Affiliation(s)
- Iakovos Toumazis
- Departments of Biomedical Data Science and Radiology, Stanford University, Stanford, CA, USA
| | - S Ayca Erdogan
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - Mehrad Bastani
- Departments of Biomedical Data Science and Radiology, Stanford University, Stanford, CA, USA
| | - Ann Leung
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - Sylvia K Plevritis
- Departments of Biomedical Data Science and Radiology, Stanford University, Stanford, CA, USA
| |
Collapse
|
6
|
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; 127:4432-4446. [PMID: 34383299 DOI: 10.1002/cncr.33835] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2020] [Revised: 02/12/2021] [Accepted: 03/18/2021] [Indexed: 12/19/2022]
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. LAY SUMMARY A novel decision-analytical screening framework was developed for lung cancer, the individualized lung cancer screening decision (ENGAGE) tool to provide personalized screening schedules for ever-smokers. ENGAGE captures the dynamic nature of lung cancer risk and incorporates life expectancy into the screening decision-making process. ENGAGE integrates past screening findings and changes in smoking behavior of individuals and provides informed screening decisions that outperform existing screening guidelines and single-threshold risk-based screening approaches. A personalized lung cancer screening program facilitated by a tool such as ENGAGE could enhance the efficiency of lung cancer screening.
Collapse
Affiliation(s)
- Iakovos Toumazis
- Department of Biomedical Data Science, Stanford University, Stanford, California.,Department of 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
- Department of Biomedical Data Science, Stanford University, Stanford, California.,Department of Radiology, Stanford University, Stanford, California
| |
Collapse
|
7
|
Ten Haaf K, Bastani M, Cao P, Jeon J, Toumazis I, Han SS, Plevritis SK, Blom EF, Kong CY, Tammemägi MC, Feuer EJ, Meza R, de Koning HJ. A Comparative Modeling Analysis of Risk-Based Lung Cancer Screening Strategies. J Natl Cancer Inst 2021; 112:466-479. [PMID: 31566216 PMCID: PMC7225672 DOI: 10.1093/jnci/djz164] [Citation(s) in RCA: 65] [Impact Index Per Article: 21.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2019] [Revised: 06/27/2019] [Accepted: 08/14/2019] [Indexed: 12/22/2022] Open
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 with current United States Preventive Services Task Force (USPSTF) recommendations. METHODS Four independent natural history models were used to perform a comparative modeling study evaluating long-term benefits and harms of selecting individuals for lung cancer screening through risk-prediction models. In total, 363 risk-based screening strategies varying by screening starting and stopping age, risk-prediction model used for eligibility (Bach, PLCOm2012, or Lung Cancer Death Risk Assessment Tool [LCDRAT]), and risk threshold were evaluated for a 1950 US 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 ages 55-80 years 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 = 8660; PLCOm2012 = 8862; LCDRAT = 8631; USPSTF = 8590), and risk-based strategies had more overdiagnosed cases (Bach = 149; PLCOm2012 = 147; LCDRAT = 150; USPSTF = 115). Sensitivity analyses suggest excluding individuals with limited life expectancies (<5 years) from screening retains the life-years gained by risk-based screening, while reducing overdiagnosis by more than 65.3%. CONCLUSIONS Risk-based lung cancer screening strategies prevent considerably more lung cancer deaths than current recommendations do. However, they yield modest additional life-years and increased overdiagnosis because of predominantly selecting older individuals. Efficient implementation of risk-based lung cancer screening requires careful consideration of life expectancy for determining optimal individual stopping ages.
Collapse
Affiliation(s)
- Kevin Ten Haaf
- Department of Public Health, Erasmus MC-University Medical Center Rotterdam, Rotterdam, Zuid-Holland, the Netherlands
| | - Mehrad Bastani
- Department of Radiology, Stanford University, Palo Alto, CA
| | - Pianpian Cao
- Department of Epidemiology, University of Michigan, Ann Arbor, MI
| | - Jihyoun Jeon
- Department of Epidemiology, University of Michigan, Ann Arbor, MI
| | | | - Summer S Han
- Department of Radiology, Stanford University, Palo Alto, CA.,Department of Medicine, Stanford University, Palo Alto, CA (SSH)
| | | | - Erik F Blom
- Department of Public Health, Erasmus MC-University Medical Center Rotterdam, Rotterdam, Zuid-Holland, the Netherlands
| | - Chung Yin Kong
- Harvard Medical School, Boston, MA.,Department of Radiology, Massachusetts General Hospital, Boston, MA
| | - Martin C Tammemägi
- Department of Health Sciences, Brock University, St. Catharines, ON, Canada
| | - Eric J Feuer
- Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, MD
| | - Rafael Meza
- Department of Epidemiology, University of Michigan, Ann Arbor, MI
| | - Harry J de Koning
- Department of Public Health, Erasmus MC-University Medical Center Rotterdam, Rotterdam, Zuid-Holland, the Netherlands
| |
Collapse
|
8
|
Tyuryumina EY, Neznanov AA, Turumin JL. A Mathematical Model to Predict Diagnostic Periods for Secondary Distant Metastases in Patients with ER/PR/HER2/Ki-67 Subtypes of Breast Cancer. Cancers (Basel) 2020; 12:cancers12092344. [PMID: 32825078 PMCID: PMC7563940 DOI: 10.3390/cancers12092344] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2020] [Revised: 08/13/2020] [Accepted: 08/17/2020] [Indexed: 02/07/2023] Open
Abstract
Previously, a consolidated mathematical model of primary tumor (PT) growth and secondary distant metastasis (sdMTS) growth in breast cancer (BC) (CoMPaS) was presented. The aim was to detect the diagnostic periods for visible sdMTS via CoMPaS in patients with different subtypes ER/PR/HER2/Ki-67 (Estrogen Receptor/Progesterone Receptor/Human Epidermal growth factor Receptor 2/Ki-67 marker) of breast cancer. CoMPaS is based on an exponential growth model and complementing formulas, and the model corresponds to the tumor-node-metastasis (TNM) staging system and BC subtypes (ER/PR/HER2/Ki-67). The CoMPaS model reflects (1) the subtypes of BC, such as ER/PR/HER2/Ki-67, and (2) the growth processes of the PT and sdMTSs in BC patients without or with lymph node metastases (MTSs) in accordance with the eighth edition American Joint Committee on Cancer prognostic staging system for breast cancer. CoMPaS correctly describes the growth of the PT in the ER/PR/HER2/Ki-67 subtypes of BC patients and helps to calculate the different diagnostic periods, depending on the tumor volume doubling time of sdMTS, when sdMTSs might appear. CoMPaS and the corresponding software tool can help (1) to start the early treatment of small sdMTSs in BC patients with different tumor subtypes (ER/PR/HER2/Ki-67), and (2) to consider the patient almost healthy if sdMTSs do not appear during the different diagnostic periods.
Collapse
Affiliation(s)
- Ella Ya. Tyuryumina
- International Laboratory for Intelligent Systems and Structural Analysis, Faculty of Computer Science, National Research University Higher School of Economics, 109028 Moscow, Russia;
- Correspondence:
| | - Alexey A. Neznanov
- International Laboratory for Intelligent Systems and Structural Analysis, Faculty of Computer Science, National Research University Higher School of Economics, 109028 Moscow, Russia;
| | | |
Collapse
|
9
|
Wolff HB, Alberts L, van der Linden N, Bongers ML, Verstegen NE, Lagerwaard FJ, Hofman FN, Uyl-de Groot CA, Senan S, El Sharouni SY, Kastelijn EA, Schramel FMNH, Coupé VMH. Cost-effectiveness of stereotactic body radiation therapy versus video assisted thoracic surgery in medically operable stage I non-small cell lung cancer: A modeling study. Lung Cancer 2020; 141:89-96. [PMID: 31982640 DOI: 10.1016/j.lungcan.2020.01.011] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2019] [Revised: 12/13/2019] [Accepted: 01/11/2020] [Indexed: 12/25/2022]
Abstract
OBJECTIVES Stage I non-small cell lung cancer (NSCLC) can be treated with either Stereotactic Body Radiotherapy (SBRT) or Video Assisted Thoracic Surgery (VATS) resection. To support decision making, not only the impact on survival needs to be taken into account, but also on quality of life, costs and cost-effectiveness. Therefore, we performed a cost-effectiveness analysis comparing SBRT to VATS resection with respect to quality adjusted life years (QALY) lived and costs in operable stage I NSCLC. MATERIALS AND METHODS Patient level and aggregate data from eight Dutch databases were used to estimate costs, health utilities, recurrence free and overall survival. Propensity score matching was used to minimize selection bias in these studies. A microsimulation model predicting lifetime outcomes after treatment in stage I NSCLC patients was used for the cost-effectiveness analysis. Model outcomes for the two treatments were overall survival, QALYs, and total costs. We used a Dutch health care perspective with 1.5 % discounting for health effects, and 4 % discounting for costs, using 2018 cost data. The impact of model parameter uncertainty was assessed with deterministic and probabilistic sensitivity analyses. RESULTS Patients receiving either VATS resection or SBRT were estimated to live 5.81 and 5.86 discounted QALYs, respectively. Average discounted lifetime costs in the VATS group were €29,269 versus €21,175 for SBRT. Difference in 90-day excess mortality between SBRT and VATS resection was the main driver for the difference in QALYs. SBRT was dominant in at least 74 % of the probabilistic simulations. CONCLUSION Using a microsimulation model to combine available evidence on survival, costs, and health utilities in a cost-effectiveness analysis for stage I NSCLC led to the conclusion that SBRT dominates VATS resection in the majority of simulations.
Collapse
Affiliation(s)
- Henri B Wolff
- Department of Epidemiology and Biostatistics, Amsterdam Public Health Research Institute, Amsterdam UMC, Amsterdam, the Netherlands.
| | - Leonie Alberts
- Department of Pulmonology, St. Antonius Hospital, Nieuwegein, the Netherlands
| | - Naomi van der Linden
- Department of Health Technology Assessment, Erasmus School of Health Policy & Management, Erasmus University Rotterdam, Rotterdam, the Netherlands
| | - Mathilda L Bongers
- Department of Epidemiology and Biostatistics, Amsterdam Public Health Research Institute, Amsterdam UMC, Amsterdam, the Netherlands
| | - Naomi E Verstegen
- Department of Radiation Oncology, Amsterdam UMC, Amsterdam, the Netherlands
| | - Frank J Lagerwaard
- Department of Radiation Oncology, Amsterdam UMC, Amsterdam, the Netherlands
| | - Frederik N Hofman
- Department of Cardiothoracic Surgery, St. Antonius Hospital, Nieuwegein, the Netherlands
| | - Carin A Uyl-de Groot
- Department of Health Technology Assessment, Erasmus School of Health Policy & Management, Erasmus University Rotterdam, Rotterdam, the Netherlands; Institute for Medical Technology Assessment, Erasmus University Rotterdam, Rotterdam, the Netherlands
| | - Suresh Senan
- Department of Radiation Oncology, Amsterdam UMC, Amsterdam, the Netherlands
| | - Sherif Y El Sharouni
- Department of Radiotherapy, University Medical Centre Utrecht, Utrecht, the Netherlands
| | | | | | - Veerle M H Coupé
- Department of Epidemiology and Biostatistics, Amsterdam Public Health Research Institute, Amsterdam UMC, Amsterdam, the Netherlands
| |
Collapse
|
10
|
Toumazis I, Tsai EB, Erdogan SA, Han SS, Wan W, Leung A, Plevritis SK. Cost-Effectiveness Analysis of Lung Cancer Screening Accounting for the Effect of Indeterminate Findings. JNCI Cancer Spectr 2019; 3:pkz035. [PMID: 31942534 PMCID: PMC6947892 DOI: 10.1093/jncics/pkz035] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2018] [Revised: 04/08/2019] [Accepted: 05/07/2019] [Indexed: 12/17/2022] Open
Abstract
Background Numerous health policy organizations recommend lung cancer screening, but no consensus exists on the optimal policy. Moreover, the impact of the Lung CT screening reporting and data system 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 US-representative current and former smokers. We conduct sensitivity analyses to test key model inputs and assumptions. Results The cost-effectiveness efficiency frontier consists of both annual and biennial screening strategies. Current guidelines are not on the frontier. Assuming 4% disutility associated with indeterminate findings, biennial screening for smokers aged 50–70 years with at least 40 pack-years and less than 10 years since smoking cessation is the cost-effective strategy using $100 000 willingness-to-pay threshold yielding 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 years with at least 30 pack-years and less than 10 years since smoking cessation is the cost-effective strategy yielding 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.
Collapse
Affiliation(s)
| | - Emily B Tsai
- Department of Radiology, Stanford University, Stanford, CA
| | - S Ayca Erdogan
- Department of Radiology, Stanford University, Stanford, CA
| | - Summer S Han
- Stanford Center for Biomedical Informatics Research, Departments of Medicine and Neurosurgery
| | - Wenshuai Wan
- Department of Radiology, Stanford University, Stanford, CA
| | - Ann Leung
- Department of Radiology, Stanford University, Stanford, CA
| | | |
Collapse
|
11
|
Prediagnostic detection of mesothelioma by circulating calretinin and mesothelin - a case-control comparison nested into a prospective cohort of asbestos-exposed workers. Sci Rep 2018; 8:14321. [PMID: 30254313 PMCID: PMC6156219 DOI: 10.1038/s41598-018-32315-3] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2018] [Accepted: 09/05/2018] [Indexed: 12/12/2022] Open
Abstract
Malignant mesothelioma (MM) is strongly associated with a previous asbestos exposure. To improve timely detection of MM in asbestos workers, better screening tools – like minimally-invasive biomarkers – are desirable. Between 2008 and 2018 2,769 patients with benign asbestos-related diseases were recruited to participate in annual screens. Using a nested case-control design the protein markers calretinin and mesothelin were determined by enzyme-linked immunosorbent assays in prediagnostic plasma samples of 34 MM cases as well as 136 matched controls from the cohort. Conditional on a pre-defined specificity of 98% for calretinin and 99% for mesothelin the markers reached individual sensitivities of 31% and 23%, respectively, when including the incident cases with samples taken between one and 15 months before diagnosis. The combination of both markers increased the sensitivity to 46% at 98% specificity. Marker complementation increased with earlier sampling. The marker combination improves the sensitivity of the individual markers, indicating a useful complementation and suggesting that additional markers may further improve the performance. This is the first prospective cohort study to evaluate a detection of MM by calretinin and its combination with mesothelin up to about a year before clinical diagnosis. Whether an earlier diagnosis will result in reduced mortality has yet to be demonstrated.
Collapse
|
12
|
Tyuryumina EY, Neznanov AA. Consolidated mathematical growth model of the primary tumor and secondary distant metastases of breast cancer (CoMPaS). PLoS One 2018; 13:e0200148. [PMID: 29979733 PMCID: PMC6034839 DOI: 10.1371/journal.pone.0200148] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2018] [Accepted: 06/20/2018] [Indexed: 11/28/2022] Open
Abstract
The goal of this research is to improve the accuracy of predicting the breast cancer (BC) process using the original mathematical model referred to as CoMPaS. The CoMPaS is the original mathematical model and the corresponding software built by modelling the natural history of the primary tumor (PT) and secondary distant metastases (MTS), it reflects the relations between the PT and MTS. The CoMPaS is based on an exponential growth model and consists of a system of determinate nonlinear and linear equations and corresponds to the TNM classification. It allows us to calculate the different growth periods of PT and MTS: 1) a non-visible period for PT, 2) a non-visible period for MTS, and 3) a visible period for MTS. The CoMPaS has been validated using 10-year and 15-year survival clinical data considering tumor stage and PT diameter. The following are calculated by CoMPaS: 1) the number of doublings for the non-visible and visible growth periods of MTS and 2) the tumor volume doubling time (days) for the non-visible and visible growth periods of MTS. The diameters of the PT and secondary distant MTS increased simultaneously. In other words, the non-visible growth period of the secondary distant MTS shrinks, leading to a decrease of the survival of patients with breast cancer. The CoMPaS correctly describes the growth of the PT for patients at the T1aN0M0, T1bN0M0, T1cN0M0, T2N0M0 and T3N0M0 stages, who does not have MTS in the lymph nodes (N0). Additionally, the CoMPaS helps to consider the appearance and evolution period of secondary distant MTS (M1). The CoMPaS correctly describes the growth period of PT corresponding to BC classification (parameter T), the growth period of secondary distant MTS and the 10-15-year survival of BC patients considering the BC stage (parameter M).
Collapse
Affiliation(s)
- Ella Ya. Tyuryumina
- International Laboratory for Intelligent Systems and Structural Analysis, Faculty of Computer science, National Research University Higher School of Economics, Moscow, Russia
- * E-mail:
| | - Alexey A. Neznanov
- International Laboratory for Intelligent Systems and Structural Analysis, Faculty of Computer science, National Research University Higher School of Economics, Moscow, Russia
| |
Collapse
|
13
|
Han SS, Erdogan SA, Toumazis I, Leung A, Plevritis SK. Evaluating the impact of varied compliance to lung cancer screening recommendations using a microsimulation model. Cancer Causes Control 2017; 28:947-958. [PMID: 28702814 DOI: 10.1007/s10552-017-0907-x] [Citation(s) in RCA: 37] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2015] [Accepted: 05/25/2017] [Indexed: 12/19/2022]
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.
Collapse
Affiliation(s)
- Summer S Han
- Quantitative Sciences Unit, Stanford Center for Biomedical Research (BMIR), Neurosurgery and Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - S Ayca Erdogan
- Department of Industrial and Systems Engineering, San Jose State University, San Jose, CA, USA
| | - Iakovos Toumazis
- Department of Radiology and Biomedical Data Science, Stanford University School of Medicine, 1201 Welch Rd, Stanford, CA, 94305, USA
| | - Ann Leung
- Department of Radiology, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - Sylvia K Plevritis
- Department of Radiology and Biomedical Data Science, Stanford University School of Medicine, 1201 Welch Rd, Stanford, CA, 94305, USA.
| |
Collapse
|
14
|
van der Meijde E, van den Eertwegh AJM, Linn SC, Meijer GA, Fijneman RJA, Coupé VMH. The Melanoma MAICare Framework: A Microsimulation Model for the Assessment of Individualized Cancer Care. Cancer Inform 2016; 15:115-27. [PMID: 27346945 PMCID: PMC4912231 DOI: 10.4137/cin.s38122] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2015] [Revised: 03/31/2016] [Accepted: 04/03/2016] [Indexed: 12/17/2022] Open
Abstract
Recently, new but expensive treatments have become available for metastatic melanoma. These improve survival, but in view of the limited funds available, cost-effectiveness needs to be evaluated. Most cancer cost-effectiveness models are based on the observed clinical events such as recurrence- free and overall survival. Times at which events are recorded depend not only on the effectiveness of treatment but also on the timing of examinations and the types of tests performed. Our objective was to construct a microsimulation model framework that describes the melanoma disease process using a description of underlying tumor growth as well as its interaction with diagnostics, treatments, and surveillance. The framework should allow for exploration of the impact of simultaneously altering curative treatment approaches in different phases of the disease as well as altering diagnostics. The developed framework consists of two components, namely, the disease model and the clinical management module. The disease model consists of a tumor level, describing growth and metastasis of the tumor, and a patient level, describing clinically observed states, such as recurrence and death. The clinical management module consists of the care patients receive. This module interacts with the disease process, influencing the rate of transition between tumor growth states at the tumor level and the rate of detecting a recurrence at the patient level. We describe the framework as the required input and the model output. Furthermore, we illustrate model calibration using registry data and data from the literature.
Collapse
Affiliation(s)
- Elisabeth van der Meijde
- Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, the Netherlands
| | | | - Sabine C Linn
- Division of Molecular Pathology, Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Gerrit A Meijer
- Professor, Division of Diagnostic Oncology, Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Remond J A Fijneman
- Division of Diagnostic Oncology, Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Veerle M H Coupé
- Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, the Netherlands
| |
Collapse
|
15
|
Casswell EJ, Pringle E, Thuang C, Sanders MD, Graham EM. Clinical and Histological Features of Small Cell Lung Cancer Paraneoplastic Inflammatory Uveitis. Ocul Immunol Inflamm 2015; 24:503-7. [PMID: 26173097 DOI: 10.3109/09273948.2015.1012296] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
PURPOSE Paraneoplastic ocular inflammation can be associated with the autoantibody against collapsin response-mediator protein-5 (anti-CRMP-5). We describe the clinical and histological features of 2 rare cases of small cell lung carcinoma (SCLC) presenting with intraocular inflammation: the first was anti-CRMP-5 positive and the second preceded the auto-antibody's discovery but with remarkably similar features. The previously unreported retinal histology is described. METHODS Case notes review. RESULTS Both cases presented with bilateral visual loss, constricted visual fields, vitritis, and pale, swollen optic discs. Fundal fluorescein angiographies showed optic disc leakage. Retinal histology of both cases revealed predominantly inner retinal inflammation. Following their diagnosis with SCLC, serology for case 1 was positive for anti-CRMP-5 but case 2 pre-dated its discovery. CONCLUSIONS CRMP-5 inflammatory eye disease presents with a distinct pattern of clinical and histological features, which may be the first sign of their underlying cancer. Retinal histology revealed predominantly inner retinal inflammation.
Collapse
Affiliation(s)
| | | | - Caroline Thuang
- c Department of Ocular Biology and Therapeutics , UCL Institute of Ophthalmology , London , UK
| | - Mike D Sanders
- d National Hospital of Neurology & Neurosurgery, Queen's Square , London , UK , and
| | | |
Collapse
|
16
|
Kanarek NF, Hooker CM, Mathieu L, Tsai HL, Rudin CM, Herman JG, Brock MV. Survival after community diagnosis of early-stage non-small cell lung cancer. Am J Med 2014; 127:443-9. [PMID: 24486286 PMCID: PMC4601577 DOI: 10.1016/j.amjmed.2013.12.023] [Citation(s) in RCA: 40] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/05/2013] [Revised: 12/10/2013] [Accepted: 12/20/2013] [Indexed: 12/20/2022]
Abstract
BACKGROUND "Rush to surgery" among patients with worse symptoms, delays related to morbidity, and inclusion of patients with advanced disease in study populations have produced a mixed picture of importance of time to treatment to survival of non-small cell lung cancer. Our objective was to assess the contribution of diagnosis to first surgery interval to survival among patients diagnosed in the community with early-stage non-small cell lung cancer. METHODS Patients with early-stage lung cancer (N = 174) at the Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins who were diagnosed and treated from 2003 to 2009 and followed through 2011 made up a prospective study of overall survival. Diagnosis to first surgery interval was examined overall, as 2 segments (referral interval and treatment interval), as short and longer intervals, and as a continuous variable. RESULTS The majority of patients were female (55%) and aged more than 65 years (61%). The average mean referral and treatment delays were 61.2 and 5.9 days, respectively. Cox method hazard analysis revealed that older age (years) at diagnosis (hazard ratio [HR], 1.02; 95% confidence interval [CI], 1.00-1.05), stage IIB (HR, 2.17; 95% CI, 1.12-4.21), large (>4 cm) (HR, 3.68; 95% CI, 1.05-12.93) or unknown tumor size (HR, 4.45; 95% CI, 1.21-16.38), and weeks from diagnosis to first surgery interval (HR, 1.04; 95% CI, 1.00-1.09) predicted worse overall survival. The threshold period of less than 42 days from diagnosis to surgery did not reach statistical significance. CONCLUSIONS Patients seem to benefit from rapid reduction of tumor burden with surgery. Reasons for delay were not available. Nevertheless, referral delay experienced in the community is unduly long. In addition to patient choices, an unconscious patient or physician bias that lung cancer is untreatable or an inevitable consequence of smoking may be operating and needs further investigation.
Collapse
Affiliation(s)
- Norma F Kanarek
- Department of Environmental Health Sciences, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Md; Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, Md.
| | - Craig M Hooker
- Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, Md; Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Md
| | - Luckson Mathieu
- Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, Md
| | - Hua-Ling Tsai
- Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, Md
| | - Charles M Rudin
- Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, Md
| | - James G Herman
- Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, Md
| | - Malcolm V Brock
- Department of Surgery, Johns Hopkins University School of Medicine, Bunting Blaustein Cancer Research Building, Baltimore, Md
| |
Collapse
|
17
|
Gallaher J, Babu A, Plevritis S, Anderson ARA. Bridging population and tissue scale tumor dynamics: a new paradigm for understanding differences in tumor growth and metastatic disease. Cancer Res 2014; 74:426-435. [PMID: 24408919 DOI: 10.1158/0008-5472.can-13-0759] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
To provide a better understanding of the relationship between primary tumor growth rates and metastatic burden, we present a method that bridges tumor growth dynamics at the population level, extracted from the SEER database, to those at the tissue level. Specifically, with this method, we are able to relate estimates of tumor growth rates and metastatic burden derived from a population-level model to estimates of the primary tumor vascular response and the circulating tumor cell (CTC) fraction derived from a tissue-level model. Variation in the population-level model parameters produces differences in cancer-specific survival and cure fraction. Variation in the tissue-level model parameters produces different primary tumor dynamics that subsequently lead to different growth dynamics of the CTCs. Our method to bridge the population and tissue scales was applied to lung and breast cancer separately, and the results were compared. The population model suggests that lung tumors grow faster and shed a significant number of lethal metastatic cells at small sizes, whereas breast tumors grow slower and do not significantly shed lethal metastatic cells until becoming larger. Although the tissue-level model does not explicitly model the metastatic population, we are able to disengage the direct dependency of the metastatic burden on primary tumor growth by introducing the CTC population as an intermediary and assuming dependency. We calibrate the tissue-level model to produce results consistent with the population model while also revealing a more dynamic relationship between the primary tumor and the CTCs. This leads to exponential tumor growth in lung and power law tumor growth in breast. We conclude that the vascular response of the primary tumor is a major player in the dynamics of both the primary tumor and the CTCs, and is significantly different in breast and lung cancer.
Collapse
Affiliation(s)
- Jill Gallaher
- Integrated Mathematical Oncology, Moffitt Cancer Center, Tampa, FL 33612
| | - Aravind Babu
- Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA 94305
| | - Sylvia Plevritis
- Department of Radiology, Stanford University School of Medicine, Stanford, CA 94305
| | | |
Collapse
|
18
|
Fleischhacker M, Dietrich D, Liebenberg V, Field JK, Schmidt B. The role of DNA methylation as biomarkers in the clinical management of lung cancer. Expert Rev Respir Med 2014; 7:363-83. [DOI: 10.1586/17476348.2013.814397] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
|
19
|
Pesch B, Brüning T, Johnen G, Casjens S, Bonberg N, Taeger D, Müller A, Weber DG, Behrens T. Biomarker research with prospective study designs for the early detection of cancer. BIOCHIMICA ET BIOPHYSICA ACTA-PROTEINS AND PROTEOMICS 2013; 1844:874-83. [PMID: 24361552 DOI: 10.1016/j.bbapap.2013.12.007] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/30/2013] [Revised: 11/06/2013] [Accepted: 12/10/2013] [Indexed: 01/02/2023]
Abstract
This article describes the principles of marker research with prospective studies along with examples for diagnostic tumor markers. A plethora of biomarkers have been claimed as useful for the early detection of cancer. However, disappointingly few biomarkers were approved for the detection of unrecognized disease, and even approved markers may lack a sound validation phase. Prospective studies aimed at the early detection of cancer are costly and long-lasting and therefore the bottleneck in marker research. They enroll a large number of clinically asymptomatic subjects and follow-up on incident cases. As invasive procedures cannot be applied to collect tissue samples from the target organ, biomarkers can only be determined in easily accessible body fluids. Marker levels increase during cancer development, with samples collected closer to the occurrence of symptoms or a clinical diagnosis being more informative than earlier samples. Only prospective designs allow the serial collection of pre-diagnostic samples. Their storage in a biobank upgrades cohort studies to serve for both, marker discovery and validation. Population-based cohort studies, which may collect a wealth of data, are commonly conducted with just one baseline investigation lacking serial samples. However, they can provide valuable information about factors that influence the marker level. Screening programs can be employed to archive serial samples but require significant efforts to collect samples and auxiliary data for marker research. Randomized controlled trials have the highest level of evidence in assessing a biomarker's benefit against usual care and present the most stringent design for the validation of promising markers as well as for the discovery of new markers. In summary, all kinds of prospective studies can benefit from a biobank as they can serve as a platform for biomarker research. This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge.
Collapse
Affiliation(s)
- B Pesch
- Institute for Prevention and Occupational Medicine of the German Social Accident Insurance (IPA), Ruhr University Bochum, Germany.
| | - T Brüning
- Institute for Prevention and Occupational Medicine of the German Social Accident Insurance (IPA), Ruhr University Bochum, Germany; Protein Research Unit Ruhr within Europe (PURE), Ruhr University Bochum, Germany
| | - G Johnen
- Institute for Prevention and Occupational Medicine of the German Social Accident Insurance (IPA), Ruhr University Bochum, Germany
| | - S Casjens
- Institute for Prevention and Occupational Medicine of the German Social Accident Insurance (IPA), Ruhr University Bochum, Germany
| | - N Bonberg
- Protein Research Unit Ruhr within Europe (PURE), Ruhr University Bochum, Germany
| | - D Taeger
- Institute for Prevention and Occupational Medicine of the German Social Accident Insurance (IPA), Ruhr University Bochum, Germany
| | - A Müller
- Protein Research Unit Ruhr within Europe (PURE), Ruhr University Bochum, Germany
| | - D G Weber
- Institute for Prevention and Occupational Medicine of the German Social Accident Insurance (IPA), Ruhr University Bochum, Germany
| | - T Behrens
- Institute for Prevention and Occupational Medicine of the German Social Accident Insurance (IPA), Ruhr University Bochum, Germany; Protein Research Unit Ruhr within Europe (PURE), Ruhr University Bochum, Germany
| |
Collapse
|