IDEAS home Printed from https://ideas.repec.org/a/spr/pharme/v39y2021i8d10.1007_s40273-021-01034-5.html
   My bibliography  Save this article

Estimation of Transition Probabilities for State-Transition Models: A Review of NICE Appraisals

Author

Listed:
  • Tushar Srivastava

    (University of Sheffield)

  • Nicholas R. Latimer

    (University of Sheffield)

  • Paul Tappenden

    (University of Sheffield)

Abstract

State transition models are used to inform health technology reimbursement decisions. Within state transition models, the movement of patients between the model health states over discrete time intervals is determined by transition probabilities (TPs). Estimating TPs presents numerous issues, including missing data for specific transitions, data incongruence and uncertainty around extrapolation. Inappropriately estimated TPs could result in biased models. There is limited guidance on how to address common issues associated with TP estimation. To assess current methods for estimating TPs and to identify issues that may introduce bias, we reviewed National Institute for Health and Care Excellence Technology Appraisals published from 1 January, 2019 to 27 May, 2020. Twenty-eight models (from 26 Technology Appraisals) were included in the review. Several methods for estimating TPs were identified: survival analysis (n = 11); count method (n = 9); multi-state modelling (n = 7); logistic regression (n = 2); negative binomial regression (n = 2); Poisson regression (n = 1); and calibration (n = 1). Evidence Review Groups identified several issues relating to TP estimation within these models, including important transitions being excluded (n = 5); potential selection bias when estimating TPs for post-randomisation health states (n = 2); issues concerning the use of multiple data sources (n = 4); potential biases resulting from the use of data from different populations (n = 2), and inappropriate assumptions around extrapolation (n = 3). These issues remained unresolved in almost every instance. Failing to address these issues may bias model results and lead to sub-optimal decision making. Further research is recommended to address these methodological problems.

Suggested Citation

  • Tushar Srivastava & Nicholas R. Latimer & Paul Tappenden, 2021. "Estimation of Transition Probabilities for State-Transition Models: A Review of NICE Appraisals," PharmacoEconomics, Springer, vol. 39(8), pages 869-878, August.
    • Handle: RePEc:spr:pharme:v:39:y:2021:i:8:d:10.1007_s40273-021-01034-5
    DOI: 10.1007/s40273-021-01034-5
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s40273-021-01034-5
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s40273-021-01034-5?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Briggs, Andrew & Sculpher, Mark & Claxton, Karl, 2006. "Decision Modelling for Health Economic Evaluation," OUP Catalogue, Oxford University Press, number 9780198526629.
    2. Risha Gidwani & Louise B. Russell, 2020. "Correction to: Estimating Transition Probabilities from Published Evidence: A Tutorial for Decision Modelers," PharmacoEconomics, Springer, vol. 38(11), pages 1277-1277, November.
    3. Nicky J. Welton & A. E. Ades, 2005. "Estimation of Markov Chain Transition Probabilities and Rates from Fully and Partially Observed Data: Uncertainty Propagation, Evidence Synthesis, and Model Calibration," Medical Decision Making, , vol. 25(6), pages 633-645, November.
    4. Risha Gidwani & Louise B. Russell, 2020. "Estimating Transition Probabilities from Published Evidence: A Tutorial for Decision Modelers," PharmacoEconomics, Springer, vol. 38(11), pages 1153-1164, November.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Abreha, Fasika Molla & Salmasi, Luca & Ianuale, Nicola & Pegoraro, Enrico, 2021. "A Bayesian Cost-effectiveness analysis of Holobalance, Holograms for personalized virtual coaching and motivation in an ageing population with balance disorders," MPRA Paper 109301, University Library of Munich, Germany.
    2. Marta Soares & Luísa Canto e Castro, 2012. "Continuous Time Simulation and Discretized Models for Cost-Effectiveness Analysis," PharmacoEconomics, Springer, vol. 30(12), pages 1101-1117, December.
    3. Marta O. Soares & Luísa Canto e Castro, 2012. "Continuous Time Simulation and Discretized Models for Cost-Effectiveness Analysis," PharmacoEconomics, Springer, vol. 30(12), pages 1101-1117, December.
    4. Chiranjeev Sanyal & Don Husereau, 2020. "Systematic Review of Economic Evaluations of Services Provided by Community Pharmacists," Applied Health Economics and Health Policy, Springer, vol. 18(3), pages 375-392, June.
    5. Arantzazu Arrospide & Oliver Ibarrondo & Iván Castilla & Igor Larrañaga & Javier Mar, 2022. "Development and Validation of a Discrete Event Simulation Model to Evaluate the Cardiovascular Impact of Population Policies for Obesity," Medical Decision Making, , vol. 42(2), pages 241-254, February.
    6. Mark Oppe & Daniela Ortín-Sulbarán & Carlos Vila Silván & Anabel Estévez-Carrillo & Juan M. Ramos-Goñi, 2021. "Cost-effectiveness of adding Sativex® spray to spasticity care in Belgium: using bootstrapping instead of Monte Carlo simulation for probabilistic sensitivity analyses," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 22(5), pages 711-721, July.
    7. Kaitlyn Hastings & Clara Marquina & Jedidiah Morton & Dina Abushanab & Danielle Berkovic & Stella Talic & Ella Zomer & Danny Liew & Zanfina Ademi, 2022. "Projected New-Onset Cardiovascular Disease by Socioeconomic Group in Australia," PharmacoEconomics, Springer, vol. 40(4), pages 449-460, April.
    8. Andrea Marcellusi & Raffaella Viti & Loreta A. Kondili & Stefano Rosato & Stefano Vella & Francesco Saverio Mennini, 2019. "Economic Consequences of Investing in Anti-HCV Antiviral Treatment from the Italian NHS Perspective: A Real-World-Based Analysis of PITER Data," PharmacoEconomics, Springer, vol. 37(2), pages 255-266, February.
    9. Risha Gidwani & Louise B. Russell, 2020. "Estimating Transition Probabilities from Published Evidence: A Tutorial for Decision Modelers," PharmacoEconomics, Springer, vol. 38(11), pages 1153-1164, November.
    10. Zixian, Liu & Xin, Ni & Yiliu, Liu & Qinglu, Song & Yukun, Wang, 2011. "Gastric esophageal surgery risk analysis with a fault tree and Markov integrated model," Reliability Engineering and System Safety, Elsevier, vol. 96(12), pages 1591-1600.
    11. Round, Jeff, 2012. "Is a QALY still a QALY at the end of life?," Journal of Health Economics, Elsevier, vol. 31(3), pages 521-527.
    12. Xinyue Dong & Xiaoning He & Jing Wu, 2022. "Cost Effectiveness of the First‐in‐Class ARNI (Sacubitril/Valsartan) for the Treatment of Essential Hypertension in a Chinese Setting," PharmacoEconomics, Springer, vol. 40(12), pages 1187-1205, December.
    13. Joseph F. Levy & Marjorie A. Rosenberg, 2019. "A Latent Class Approach to Modeling Trajectories of Health Care Cost in Pediatric Cystic Fibrosis," Medical Decision Making, , vol. 39(5), pages 593-604, July.
    14. Jisoo A Kwon & Georgina M Chambers & Fabio Luciani & Lei Zhang & Shamin Kinathil & Dennis Kim & Hla-Hla Thein & Willings Botha & Sandra Thompson & Andrew Lloyd & Lorraine Yap & Richard T Gray & Tony B, 2021. "Hepatitis C treatment strategies in prisons: A cost-effectiveness analysis," PLOS ONE, Public Library of Science, vol. 16(2), pages 1-13, February.
    15. Qi Cao & Erik Buskens & Hans L. Hillege & Tiny Jaarsma & Maarten Postma & Douwe Postmus, 2019. "Stratified treatment recommendation or one-size-fits-all? A health economic insight based on graphical exploration," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 20(3), pages 475-482, April.
    16. Jorge Luis García & James J. Heckman, 2021. "Early childhood education and life‐cycle health," Health Economics, John Wiley & Sons, Ltd., vol. 30(S1), pages 119-141, November.
    17. repec:jss:jstsof:38:i08 is not listed on IDEAS
    18. Stephen Morris & Kurinchi S Gurusamy & Jessica Sheringham & Brian R Davidson, 2015. "Cost-Effectiveness Analysis of Endoscopic Ultrasound versus Magnetic Resonance Cholangiopancreatography in Patients with Suspected Common Bile Duct Stones," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-12, March.
    19. Eleanor Heather & Katherine Payne & Mark Harrison & Deborah Symmons, 2014. "Including Adverse Drug Events in Economic Evaluations of Anti-Tumour Necrosis Factor-α Drugs for Adult Rheumatoid Arthritis: A Systematic Review of Economic Decision Analytic Models," PharmacoEconomics, Springer, vol. 32(2), pages 109-134, February.
    20. Manuel Gomes & Robert Aldridge & Peter Wylie & James Bell & Owen Epstein, 2013. "Cost-Effectiveness Analysis of 3-D Computerized Tomography Colonography Versus Optical Colonoscopy for Imaging Symptomatic Gastroenterology Patients," Applied Health Economics and Health Policy, Springer, vol. 11(2), pages 107-117, April.
    21. Isaac Corro Ramos & Maureen P. M. H. Rutten-van Mölken & Maiwenn J. Al, 2013. "The Role of Value-of-Information Analysis in a Health Care Research Priority Setting," Medical Decision Making, , vol. 33(4), pages 472-489, May.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:pharme:v:39:y:2021:i:8:d:10.1007_s40273-021-01034-5. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.