Literature DB >> 28854143

Biases in Individualized Cost-effectiveness Analysis: Influence of Choices in Modeling Short-Term, Trial-Based, Mortality Risk Reduction and Post-Trial Life Expectancy.

David van Klaveren1,2, John B Wong2,3, David M Kent2, Ewout W Steyerberg1.   

Abstract

BACKGROUND: The benefits and costs of a treatment are typically heterogeneous across individual patients. Randomized clinical trials permit the examination of individualized treatment benefits over the trial horizon but extrapolation to lifetime horizon usually involves combining trial-based individualized estimates of short-term risk reduction with less detailed (less granular) population life tables. However, the underlying assumption of equal post-trial life expectancy for low- and high-risk patients of the same sex and age is unrealistic. We aimed to study the influence of unequal granularity between models of short-term risk reduction and life expectancy on individualized estimates of cost-effectiveness of aggressive thrombolysis for patients with an acute myocardial infarction.
METHODS: To estimate life years gained, we multiplied individualized estimates of short-term risk reduction either with less granular and with equally granular post-trial life expectancy estimates. Estimates of short-term risk reduction were obtained from GUSTO trial data (30,510 patients) using logistic regression analysis with treatment, sex, and age as predictor variables. Life expectancy estimates were derived from sex- and age-specific US life tables.
RESULTS: Based on sex- and age-specific, short-term risk reductions but average population life expectancy (less granularity), we found that aggressive thrombolysis was cost-effective (incremental cost-effectiveness ratio below $50,000) for women above age 49 y and men above age 53 y (92% and 69% of the population, respectively). Considering sex- and age-specific short-term mortality risk reduction and correspondingly sex- and age-specific life expectancy (equal granularity), aggressive thrombolysis was cost-effective for men above age 45 y and women above age 50 y (95% and 76% of the population, respectively).
CONCLUSIONS: Failure to model short-term risk reduction and life expectancy at an equal level of granularity may bias our estimates of individualized cost-effectiveness and misallocate resources.

Entities:  

Keywords:  formulary decision making; outcomes research; translating research into practice

Mesh:

Substances:

Year:  2017        PMID: 28854143      PMCID: PMC5638644          DOI: 10.1177/0272989X17696994

Source DB:  PubMed          Journal:  Med Decis Making        ISSN: 0272-989X            Impact factor:   2.583


  25 in total

1.  Optimisation versus certainty: understanding the issue of heterogeneity in economic evaluation.

Authors:  Warren Stevens; Charles Normand
Journal:  Soc Sci Med       Date:  2004-01       Impact factor: 4.634

2.  Reflecting heterogeneity in patient benefits: the role of subgroup analysis with comparative effectiveness.

Authors:  Mark Sculpher
Journal:  Value Health       Date:  2010-06       Impact factor: 5.725

Review 3.  Good research practices for cost-effectiveness analysis alongside clinical trials: the ISPOR RCT-CEA Task Force report.

Authors:  Scott Ramsey; Richard Willke; Andrew Briggs; Ruth Brown; Martin Buxton; Anita Chawla; John Cook; Henry Glick; Bengt Liljas; Diana Petitti; Shelby Reed
Journal:  Value Health       Date:  2005 Sep-Oct       Impact factor: 5.725

4.  Value of information on preference heterogeneity and individualized care.

Authors:  Anirban Basu; David Meltzer
Journal:  Med Decis Making       Date:  2007 Mar-Apr       Impact factor: 2.583

5.  Consolidated Health Economic Evaluation Reporting Standards (CHEERS)--explanation and elaboration: a report of the ISPOR Health Economic Evaluation Publication Guidelines Good Reporting Practices Task Force.

Authors:  Don Husereau; Michael Drummond; Stavros Petrou; Chris Carswell; David Moher; Dan Greenberg; Federico Augustovski; Andrew H Briggs; Josephine Mauskopf; Elizabeth Loder
Journal:  Value Health       Date:  2013 Mar-Apr       Impact factor: 5.725

6.  Treatment of myocardial infarction in a coronary care unit. A two year experience with 250 patients.

Authors:  T Killip; J T Kimball
Journal:  Am J Cardiol       Date:  1967-10       Impact factor: 2.778

7.  The danger of applying group-level utilities in decision analyses of the treatment of localized prostate cancer in individual patients.

Authors:  M E Cowen; B J Miles; D F Cahill; R B Giesler; J R Beck; M W Kattan
Journal:  Med Decis Making       Date:  1998 Oct-Dec       Impact factor: 2.583

8.  Targeting of low-dose CT screening according to the risk of lung-cancer death.

Authors:  Anil K Chaturvedi; Hormuzd A Katki; Stephanie A Kovalchik; Martin Tammemagi; Christine D Berg; Neil E Caporaso; Tom L Riley; Mary Korch; Gerard A Silvestri
Journal:  N Engl J Med       Date:  2013-07-18       Impact factor: 91.245

9.  Cost effectiveness of thrombolytic therapy with tissue plasminogen activator as compared with streptokinase for acute myocardial infarction.

Authors:  D B Mark; M A Hlatky; R M Califf; C D Naylor; K L Lee; P W Armstrong; G Barbash; H White; M L Simoons; C L Nelson
Journal:  N Engl J Med       Date:  1995-05-25       Impact factor: 91.245

10.  Individualized cost-effectiveness analysis.

Authors:  John P A Ioannidis; Alan M Garber
Journal:  PLoS Med       Date:  2011-07-12       Impact factor: 11.069

View more
  2 in total

1.  Targeting of the diabetes prevention program leads to substantial benefits when capacity is constrained.

Authors:  Natalia Olchanski; David van Klaveren; Joshua T Cohen; John B Wong; Robin Ruthazer; David M Kent
Journal:  Acta Diabetol       Date:  2021-01-30       Impact factor: 4.280

2.  Risk-Targeted Lung Cancer Screening: A Cost-Effectiveness Analysis.

Authors:  Vaibhav Kumar; Joshua T Cohen; David van Klaveren; Djøra I Soeteman; John B Wong; Peter J Neumann; David M Kent
Journal:  Ann Intern Med       Date:  2018-01-02       Impact factor: 25.391

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.