Variation in Model-Based Economic Evaluations of Low-Dose Computed Tomography Screening for Lung Cancer: A Methodological Review |
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| Institution: | 1. Exeter Test Group, University of Exeter Medical School, St Luke’s Campus, Exeter, England, UK;2. Health Economics Group, University of Exeter Medical School, St Luke’s Campus, Exeter, England, UK;3. PenTAG, University of Exeter Medical School, St Luke’s Campus, Exeter, England, UK;4. University of Exeter, Exeter, England, UK;1. Health Economic Assessment Network, Paris, France;2. French National Center for Scientific Research, Paris, France;3. Sciences Po, Center of the Sociology of Organizations, Paris, France;4. Sociology and Anthropology Department, Paris 8 University, Paris, France;5. Rhumatology Department, Cochin Hospital, Paris, France;6. French League Against Rheumatism (AFLAR), Paris, France;7. UCB Pharma, Colombes, France;8. Rhumatology Department, Grenobles Alpes University Hospital, Echirolles, France;9. Kantar Health, Gentilly, France;1. School of Rehabilitation Sciences, McMaster University, Hamilton, Ontario, Canada;2. School of Physiotherapy, Western University, London, Ontario, Canada;3. Department of Rehabilitation Medicine and Department of Plastic, Reconstructive, and Hand Surgery, Erasmus Medical Centre, Rotterdam, The Netherlands;4. Hand and Wrist Center, Xpert Clinic and Handtherapie Nederland, Rotterdam, The Netherlands;1. ORISE, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, MD, USA;2. Oncology Center of Excellence, US Food and Drug Administration, Silver Spring, MD, USA;3. Office of Biostatistics, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, MD, USA;1. School of Population Health, Curtin University, Perth, Australia;2. Department of Community Medicine, University of Tromsø, Tromsø, Norway;3. Division of Health Services, Norwegian Institute of Public Health, Oslo, Norway;1. Duke University, Durham, NC, USA;2. Durham VA Medical Center, Durham, NC, USA;3. University of North Carolina, Chapel Hill, NC;4. Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, NC, USA;5. Department of Medicine, Duke University Medical Center, Durham, NC, USA;6. Duke Older Americans Independence Center, Duke University Medical Center, Durham, NC, USA;7. Greenville VA Medical Center, Greenville, NC, USA;1. Duke Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University School of Medicine, Durham, NC, USA;2. Department of Veterans Affairs, Durham VA Medical Center, Durham, NC, USA;3. Duke University Medical Center, Durham, NC, USA;4. Department of Veterans Affairs, VA Boston Healthcare System, Boston, MA, USA;5. Duke Cancer Institute, Durham, NC, USA;6. Duke Department of Population Health Sciences, Duke University School of Medicine, Durham, NC, USA;7. Section of Hematology/Oncology, Raymond G. Murphy New Mexico Veterans Affairs Medical Center, Albuquerque, NM, USA;8. Division of Practice Advancement and Clinical Education, UNC Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA;9. Department of Veterans Affairs, National Oncology Program, Durham, NC, USA |
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| Abstract: | ObjectivesThere is significant heterogeneity in the results of published model-based economic evaluations of low-dose computed tomography (LDCT) screening for lung cancer. We sought to understand and demonstrate how these models differ.MethodsAn expansion and update of a previous systematic review (N = 19). Databases (including MEDLINE and Embase) were searched. Studies were included if strategies involving (single or multiple) LDCT screening were compared with no screening or other imaging modalities, in a population at risk of lung cancer. More detailed data extraction of studies from the previous review was conducted. Studies were critically appraised using the Consensus Health Economic Criteria list.ResultsA total of 16 new studies met the inclusion criteria, giving a total of 35 studies. There are geographic and temporal differences and differences in screening intervals and eligible populations. Studies varied in the types of models used, for example, decision tree, Markov, and microsimulation models. Most conducted a cost-effectiveness analysis (using life-years gained) or cost-utility analysis. The potential for overdiagnosis was considered in many models, unlike with other potential consequences of screening. Some studies report considering lead-time bias, but fewer mention length bias. Generally, the more recent studies, involving more complex modeling, tended to meet more of the critical appraisal criteria, with notable exceptions.ConclusionsThere are many differences across the economic evaluations contributing to variation in estimates of the cost-effectiveness of LDCT screening for lung cancer. Several methodological factors and evidence needs have been highlighted that will require consideration in future economic evaluations to achieve better agreement. |
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| Keywords: | decision model economic evaluation low-dose computed tomography lung cancer |
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