Literature DB >> 21310855

Can life expectancy and QALYs be improved by a framework for deciding whether to apply clinical guidelines to patients with severe comorbid disease?

R Scott Braithwaite1.   

Abstract

BACKGROUND: Guidelines with short-term harms and long-term benefits are often applied to chronically ill patients who may not benefit. The payoff time framework has been proposed (i.e., do not apply a guideline if a patient's life expectancy (LE) is shorter than when a guideline's cumulative incremental benefits first exceed its cumulative incremental harms), but its health impact is unclear.
OBJECTIVE: To investigate whether the payoff time framework improves LE and/or quality-adjusted life-years (QALY) for chronically ill patients.
METHODS: I evaluate impact of the payoff time framework on LE and QALYs, assuming (1) high and constant background mortality rate from chronic illness (≥ 10% per year), (2) immediate guideline-related harm with probability < 1, and (3) constant guideline-related benefit that occurs over an extended time. I apply the framework to questions of whether to screen chronically ill 50-year-old women for colorectal cancer using colonoscopy, and whether to advocate intensive glucose control for chronically ill diabetics.
RESULTS: If a guideline's payoff time is greater than a patient's LE, then withholding that guideline will increase LE and QALYs for that patient. For a 50-year-old chronically ill woman with background mortality > 0.15 per year (corresponding to LE < 6.5 years), withholding CR screening will increase LE. For a diabetic with background mortality > 0.11 per year (corresponding to LE < 9.4 years), withholding CR screening will increase QALYs.
CONCLUSION: The payoff time framework may indicate when withholding a guideline with short-term harms and long-term benefits may increase LE and/or QALY.

Entities:  

Mesh:

Substances:

Year:  2011        PMID: 21310855     DOI: 10.1177/0272989X10386117

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


  7 in total

Review 1.  Individualizing cancer screening in older adults: a narrative review and framework for future research.

Authors:  Elizabeth Eckstrom; David H Feeny; Louise C Walter; Leslie A Perdue; Evelyn P Whitlock
Journal:  J Gen Intern Med       Date:  2012-09-28       Impact factor: 5.128

2.  Modeling Individual Patient Preferences for Colorectal Cancer Screening Based on Their Tolerance for Complications Risk.

Authors:  Glen B Taksler; Adam T Perzynski; Michael W Kattan
Journal:  Med Decis Making       Date:  2016-11-23       Impact factor: 2.583

3.  Lessons learned from the first wave of aging with HIV.

Authors:  Amy C Justice; R Scott Braithwaite
Journal:  AIDS       Date:  2012-07-31       Impact factor: 4.177

4.  Lag time to benefit for preventive therapies.

Authors:  Holly M Holmes; Lillian Min; Cynthia Boyd
Journal:  JAMA       Date:  2014-04-16       Impact factor: 56.272

5.  Predictive accuracy of the Veterans Aging Cohort Study index for mortality with HIV infection: a North American cross cohort analysis.

Authors:  Amy C Justice; Sharada P Modur; Janet P Tate; Keri N Althoff; Lisa P Jacobson; Kelly A Gebo; Mari M Kitahata; Michael A Horberg; John T Brooks; Kate Buchacz; Sean B Rourke; Anita Rachlis; Sonia Napravnik; Joseph Eron; James H Willig; Richard Moore; Gregory D Kirk; Ronald Bosch; Benigno Rodriguez; Robert S Hogg; Jennifer Thorne; James J Goedert; Marina Klein; John Gill; Steven Deeks; Timothy R Sterling; Kathryn Anastos; Stephen J Gange
Journal:  J Acquir Immune Defic Syndr       Date:  2013-02-01       Impact factor: 3.731

6.  Using the Payoff Time in Decision-Analytic Models: A Case Study for Using Statins in Primary Prevention.

Authors:  Alexander Thompson; Bruce Guthrie; Katherine Payne
Journal:  Med Decis Making       Date:  2017-04-25       Impact factor: 2.583

7.  Does patient-centered care mean that informed consent is necessary for clinical performance measures?

Authors:  R Scott Braithwaite; Arthur Caplan
Journal:  J Gen Intern Med       Date:  2014-04       Impact factor: 5.128

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.