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Review

A systematic review and checklist presenting the main challenges for health economic modeling in personalized medicine: towards implementing patient-level models

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Pages 17-25 | Received 19 Sep 2016, Accepted 13 Dec 2016, Published online: 27 Dec 2016

References

  • Schleidgen S, Klingler C, Bertram T, et al. What is personalized medicine: sharpening a vague term based on a systematic literature review. BMC Med Ethics. 2013;14:1–12.
  • Van Til JA, IJzerman MJ. Why should regulators consider using patient preferences in benefit-risk assessment?. Pharmacoeconomics. 2014;32:1–4.
  • Gheita TA, Gheita HA, Kenawy SA. The potential of genetically guided treatment in Behçet’s disease. Pharmacogenomics. 2016;17:1165–1174.
  • Liu Y, Hegde P, Zhang F, et al. Prostate cancer – a biomarker perspective. Front Endocrinol (Lausanne). 2012;3:72.
  • Towse A, Garrison LP Jr. Economic incentives for evidence generation: promoting an efficient path to personalized medicine. Value in Health: the Journal of the International Society for Pharmacoeconomics and Outcomes Research. 2013;16:S39–43.
  • Booth CM, Tannock IF. Randomised controlled trials and population-based observational research: partners in the evolution of medical evidence. Br J Cancer. 2014;110:551–555.
  • Ferrante Di Ruffano L, Davenport C, Eisinga A, et al. A capture-recapture analysis demonstrated that randomized controlled trials evaluating the impact of diagnostic tests on patient outcomes are rare. J Clin Epidemiol. 2012;65:282–287.
  • Horgan D, Lawler M, Brand A. Getting Personal: accelerating Personalised and Precision Medicine Integration into Clinical Cancer Research and Care in Clinical Trials. Public Health Genomics. 2015;18:325–328.
  • Lawler M, Sullivan R. Personalised and Precision Medicine in Cancer Clinical Trials: panacea for Progress or Pandora’s Box?. Public Health Genomics. 2015;18:329–337.
  • Crown WH. Potential application of machine learning in health outcomes research and some statistical cautions. Value in Health. 2015;18:137–140.
  • IJzerman MJ, Manca A, Keizer J, et al. Implementation of comparative effectiveness research in personalized medicine applications in oncology: current and future perspectives. Comp Effectiveness Res. 2015;5:65.
  • Marshall DA, Burgos-Liz L, Pasupathy KS, et al. Transforming Healthcare Delivery: integrating Dynamic Simulation Modelling and Big Data in Health Economics and Outcomes Research. PharmacoEconomics. 2015;34:115–126.
  • Annemans L, Redekop K, Payne K. Current methodological issues in the economic assessment of personalized medicine. Value in Health: the Journal of the International Society for Pharmacoeconomics and Outcomes Research. 2013;16:S20–6.
  • Miller JD, Foley KA, Russell MW. Current Challenges in Health Economic Modeling of Cancer Therapies: A Research Inquiry. American Health Drug Benefits. 2014;7:153–162.
  • Phillips KA, Liang S-Y, Van Bebber S, et al. To the translation of genomic information into clinical practice and health policy: utilization, preferences, and economic value. Curr Opin Mol Ther. 2008;10:260–266.
  • Ginsburg GS, Kuderer NM. Comparative effectiveness research, genomics-enabled personalized medicine, and rapid learning health care: a common bond. J Clinical Oncology: Official Journal Am Soc Clin Oncol. 2012;30:4233–4242.
  • Postma MJ, Boersma C, Vandijck D, et al. Health technology assessments in personalized medicine: illustrations for cost–effectiveness analysis. Expert Rev Pharmacoecon Outcomes Res. 2011;11:367–369.
  • Sailer AM, Van Zwam WH, Wildberger JE, et al. Cost-effectiveness modelling in diagnostic imaging: a stepwise approach. Eur Radiol. 2015;25:3629–3637.
  • Ferrusi IL, Leighl NB, Kulin NA. Marshall DA. Do economic evaluations of targeted therapy provide support for decision makers? . J Oncol Practice.. 2011;7:36s–45s.
  • Golubnitschaja O, Yeghiazaryan K, Costigliola V, et al. Risk assessment, disease prevention and personalised treatments in breast cancer: is clinically qualified integrative approach in the horizon?. Epma J. 2013;4:6.
  • Hulme C, Browne C, Mansfield J, et al. Determining cost-effectiveness of advanced cancer care: a systematic review of economic models. BMJ Support Palliat Care. 2011;1:A21–A2.
  • Mullins CD, Montgomery R, Tunis S. Uncertainty in assessing value of oncology treatments. Oncologist. 2010;15(Suppl 1):58–64.
  • Lee KA, Dziadkowiec O, Meek P. A systems science approach to fatigue management in research and health care. Nurs Outlook. 2014;62:313–321.
  • Marshall DA, Burgos-Liz L, IJzerman MJ, et al. Applying dynamic simulation modeling methods in health care delivery research—the SIMULATE checklist: report of the ISPOR simulation modeling emerging good practices task force. Value in Health. 2015;18:5–16.
  • Marshall DA, Burgos-Liz L, IJzerman MJ, et al. Selecting a dynamic simulation modeling method for health care delivery research-part 2: report of the ISPOR dynamic simulation modeling emerging good practices task force. Value in Health: the Journal of the International Society for Pharmacoeconomics and Outcomes Research. 2015;18:147–160.
  • Beaulieu M, De Denus S, Lachaine J. Systematic review of pharmacoeconomic studies of pharmacogenomic tests. Pharmacogenomics. 2010;11:1573–1590. Epub 2010/12/03
  • Phillips KA, Van Bebber SL. A systematic review of cost-effectiveness analyses of pharmacogenomic interventions. Pharmacogenomics. 2004;5:1139–1149. Epub 2004/12/09
  • Plumpton CO, Roberts D, Pirmohamed M, et al. A systematic review of economic evaluations of pharmacogenetic testing for prevention of adverse drug reactions. PharmacoEconomics. 2016;34:1–23.
  • Verhoef TI, Redekop WK, Darba J, et al. A systematic review of cost-effectiveness analyses of pharmacogenetic-guided dosing in treatment with coumarin derivatives. Pharmacogenomics. 2010;11:989–1002. Epub 2010/07/07
  • Wolfswinkel JF, Furtmueller E, Wilderom CPM. Using grounded theory as a method for rigorously reviewing literature. Eur J Inf Syst. 2013;22:45–55.
  • Nalejska E, Mączyńska E, Lewandowska MA. Prognostic and predictive biomarkers: tools in personalized oncology. Mol Diagn Ther. 2014;18:273–284.
  • Peer X, An G. Agent-based model of fecal microbial transplant effect on bile acid metabolism on suppressing Clostridium difficile infection: an example of agent-based modeling of intestinal bacterial infection. J Pharmacokinet Pharmacodyn. 2014;41:493–507.
  • Schubert KO, Clark SR, Baune BT. The use of clinical and biological characteristics to predict outcome following First Episode Psychosis. Aust N Z J Psychiatry. 2015;49:24–35.
  • Guerriero C, Cairns J, Roberts I, et al. The cost-effectiveness of smoking cessation support delivered by mobile phone text messaging: txt2stop. Eur J Health Econ. 2013;14:789–797.
  • Lee T, Biddle AK, Lionaki S, et al. Personalized prophylactic anticoagulation decision analysis in patients with membranous nephropathy. Kidney Int. 2014;85:1412–1420.
  • Soeteman DI, Stout NK, Ozanne EM, et al. Modeling the effectiveness of initial management strategies for ductal carcinoma in situ. J Natl Cancer Inst. 2013;105:774–781.
  • Al-Badriyeh D, Slavin M, Liew D, et al. Pharmacoeconomic evaluation of voriconazole versus posaconazole for antifungal prophylaxis in acute myeloid leukaemia. J Antimicrob Chemother. 2010;65:1052–1061.
  • Cutler CS, Lee SJ, Greenberg P, et al. A decision analysis of allogeneic bone marrow transplantation for the myelodysplastic syndromes: delayed transplantation for low-risk myelodysplasia is associated with improved outcome. Blood. 2004;104:579–585.
  • Desai K, Sansom SL, Ackers ML, et al. Modeling the impact of HIV chemoprophylaxis strategies among men who have sex with men in the United States: HIV infections prevented and cost-effectiveness. Aids. 2008;22:1829–1839.
  • Herman WH, Hoerger TJ, Brandle M, et al. for the Diabetes Prevention Program Research G. The cost-effectiveness of lifestyle modification or metformin in preventing type 2 diabetes in adults with impaired glucose tolerance.. Ann Intern Med. 2005;142:323–332.
  • Hertenstein B, Heil G, Heimpel H. Allogenic bone marrow transplantation of chemotherapy for patients with acute myeloid leukemia in first complete remission: a decision analysis approach. Ann Hematol. 1996;72:223–230.
  • Kasuya M, Meguro K. Health economic effect of donepezil treatment for CDR 0.5 converters to Alzheimer’s disease as shown by the Markov model. Arch Gerontol Geriatr. 2010;50:295–299.
  • Kurosawa S, Yamaguchi T, Miyawaki S, et al. A Markov decision analysis of allogeneic hematopoietic cell transplantation versus chemotherapy in patients with acute myeloid leukemia in first remission. Blood. 2011;117:2113–2120.
  • Lee SJ, Kuntz KM, Horowitz MM, et al. Unrelated donor bone marrow transplantation for chronic myelogenous leukemia: a decision analysis. Ann Intern Med. 1997;127:1080–1088.
  • Paltiel AD, Freedberg KA, Scott CA, et al. HIV preexposure prophylaxis in the United States: impact on lifetime infection risk, clinical outcomes, and cost-effectiveness. Clin Infect Dis. 2009;48:806–815.
  • Rein DB, Smith BD, Wittenborn JS, et al. The cost-effectiveness of birth-cohort screening for hepatitis C antibody in U.S. primary care settings. Ann Intern Med. 2012;156:263–270.
  • Ayer T, Alagoz O, Stout NK. OR Forum—A POMDP approach to personalize mammography screening decisions. Oper Res. 2012;60:1019–1034.
  • Carles M, Vilaprinyo E, Cots F, et al. Cost-effectiveness of early detection of breast cancer in Catalonia (Spain). BMC Cancer. 2011;11:192.
  • Chen A, Dowdy DW, Garcia-Lerma JG. Clinical effectiveness and cost-effectiveness of HIV pre-exposure prophylaxis in men who have sex with men: risk calculators for real-world decision-making. Plos One. 2014;9:e108742.
  • Djalalov S, Yong J, Beca J, et al. Genetic testing in combination with preventive donepezil treatment for patients with amnestic mild cognitive impairment: an exploratory economic evaluation of personalized medicine. Mol Diagn Ther. 2012;16:389–399.
  • Eckman MH, Rosand J, Greenberg SM, et al. Cost-effectiveness of using pharmacogenetic information in warfarin dosing for patients with nonvalvular atrial fibrillation. Ann Intern Med. 2009;150:73–83.
  • Ferket BS, Van Kempen BJH, Heeringa J, et al. Personalized prediction of lifetime benefits with statin therapy for asymptomatic individuals: a modeling study. Plos Med. 2012;9:e1001361.
  • Greeley SAW, John PM, Winn AN, et al. The cost-effectiveness of personalized genetic medicine: the case of genetic testing in neonatal diabetes. Diabetes Care. 2011;34:622–627.
  • Guzauskas GF, Hughes DA, Bradley SM, et al. A risk-benefit assessment of prasugrel, clopidogrel, and genotype-guided therapy in patients undergoing percutaneous coronary intervention. Clin Pharmacol Ther. 2012;91:829–837.
  • Handorf EA, McElligott S, Vachani A, et al. Cost effectiveness of personalized therapy for first-line treatment of stage IV and recurrent incurable adenocarcinoma of the lung. J Oncol Pract. 2012;8:267–274.
  • Hochheiser LI, Juusola JL, Monane M, et al. Economic utility of a blood-based genomic test for the assessment of patients with symptoms suggestive of obstructive coronary artery disease. Popul Health Manag. 2014;17:287–296.
  • Juusola JL, Brandeau ML, Owens DK, et al. The cost-effectiveness of preexposure prophylaxis for HIV prevention in the United States in men who have sex with men. Ann Intern Med. 2012;156:541–550.
  • Kievit W, De Bruin JH, Adang EM, et al. Cost effectiveness of a new strategy to identify HNPCC patients. Gut. 2005;54:97–102.
  • Kobayashi T, Goto R, Ito K, et al. Prostate cancer screening strategies with re-screening interval determined by individual baseline prostate-specific antigen values are cost-effective. Eur J Surg Oncol. 2007;33:783–789.
  • Krieckaert CL, Nair SC, Nurmohamed MT, et al. Personalised treatment using serum drug levels of adalimumab in patients with rheumatoid arthritis: an evaluation of costs and effects. Ann Rheum Dis. 2015;74:361–368.
  • Ladabaum U, Wang G, Terdiman J, et al. Strategies to identify the Lynch syndrome among patients with colorectal cancer: a cost-effectiveness analysis. Ann Intern Med. 2011;155:69–79.
  • Ladapo JA, Jaffer FA, Hoffmann U, et al. Clinical outcomes and cost-effectiveness of coronary computed tomography angiography in the evaluation of patients with chest pain. J Am Coll Cardiol. 2009;54:2409–2422.
  • Leunis A, Redekop WK, Van Montfort KA, et al. The development and validation of a decision-analytic model representing the full disease course of acute myeloid leukemia. Pharmacoeconomics. 2013;31:605–621.
  • Lieberthal RD, Dudash K, Axelrod R, et al. An economic model to value companion diagnostics in non-small-cell lung cancer. Per Med. 2013;10:139–147.
  • De Lima Lopes G Jr., Segel JE, Tan DS, et al. Cost-effectiveness of epidermal growth factor receptor mutation testing and first-line treatment with gefitinib for patients with advanced adenocarcinoma of the lung. Cancer. 2012;118:1032–1039.
  • Liu S, Schwarzinger M, Carrat F, et al. Cost effectiveness of fibrosis assessment prior to treatment for chronic hepatitis C patients. Plos One. 2011;6:e26783.
  • Mvundura M, Grosse SD, Hampel H, et al. The cost-effectiveness of genetic testing strategies for Lynch syndrome among newly diagnosed patients with colorectal cancer. Genet Med. 2010;12:93–104.
  • O’Donoghue C, Eklund M, Ozanne EM, et al. Aggregate cost of mammography screening in the United States: comparison of current practice and advocated guidelines. Ann Intern Med. 2014;160:145.
  • Perlis RH, Patrick A, Smoller JW, et al. When is pharmacogenetic testing for antidepressant response ready for the clinic? A cost-effectiveness analysis based on data from the STAR*D study. Neuropsychopharmacology. 2009;34:2227–2236.
  • Petta S, Cabibbo G, Enea M, et al. Group WEFs. Personalized cost-effectiveness of boceprevir-based triple therapy for untreated patients with genotype 1 chronic hepatitis C. Dig Liver Dis. 2014;46:936–942.
  • Ramsey SD, Burke W, Clarke L. An economic viewpoint on alternative strategies for identifying persons with hereditary nonpolyposis colorectal cancer. Genet Med. 2003;5:353–363.
  • Van Ravesteyn NT, Miglioretti DL, Stout NK, et al. What level of risk tips the balance of benefits and harms to favor screening mammography starting at age 40?. Ann Intern Med. 2012;156:609–617.
  • Reyes CM, Allen BA, Terdiman JP, et al. Comparison of selection strategies for genetic testing of patients with hereditary nonpolyposis colorectal carcinoma: effectiveness and cost-effectiveness. Cancer. 2002;95:1848–1856.
  • Schousboe JT, Kerlikowske K, Loh A, et al. Personalizing mammography by breast density and other risk factors for breast cancer: analysis of health benefits and cost-effectiveness. Ann Intern Med. 2011;155:10–20.
  • Sullivan SD, Garrison LP Jr., Rinde H, et al. Cost-effectiveness of risk stratification for preventing type 2 diabetes using a multi-marker diabetes risk score. J Med Econ. 2011;14:609–616.
  • Sung L, Buckstein R, Doyle JJ, et al. Treatment options for patients with acute myeloid leukemia with a matched sibling donor: a decision analysis. Cancer. 2003;97:592–600.
  • Vilaprinyo E, Forné C, Carles M, et al. Interval Cancer Study G. Cost-effectiveness and harm-benefit analyses of risk-based screening strategies for breast cancer. Plos One. 2014;9:e86858.
  • Kermack WO, McKendrick AGA. Contribution to the mathematical theory of epidemics. Proceedings of the Royal Society of London A: Mathematical, Physical and Engineering Sciences; 1927;115:700–721.
  • Kaelbling LP, Littman ML, Cassandra AR. Planning and acting in partially observable stochastic domains. Artif Intell. 1998;101:99–134.
  • Zucchelli E, Jones AM, TRice N The evaluation of health policies through microsimulation methods. Health, Econometrics and Data Group (HEDG) Working Papers., 2010.
  • Karnon J, Stahl J, Brennan A, et al. Force I-SMGRPT. Modeling using discrete event simulation: a report of the ISPOR-SMDM modeling good research practices task force–4.. Value in Health: the Journal of the International Society for Pharmacoeconomics and Outcomes Research. 2012;15:821–827.
  • Gail M, Rimer B. Risk-based recommendations for mammographic screening for women in their forties. J Clinical Oncology: Official Journal Am Soc Clin Oncol. 1998;16:3105–3114. Epub 1998/09/17