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Original Research |

Personalized Estimates of Benefit From Preventive Care Guidelines: A Proof of Concept

Glen B. Taksler, PhD; Melanie Keshner, MSN, FNP; Angela Fagerlin, PhD; Negin Hajizadeh, MD, MPH; and R. Scott Braithwaite, MD, MSc
[+] Article and Author Information

From New York University School of Medicine, New York, New York, and University of Michigan, Ann Arbor, Ann Arbor, Michigan.

Grant Support: By seed funds from New York University School of Medicine.

Potential Conflicts of Interest: Disclosures can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M12-2938.

Reproducible Research Statement: Study protocol: Available in Supplement 1. Statistical code: Template available from Dr. Taksler (e-mail, glentaksler@gmail.com). Nonacademic researchers may be required to sign a written use agreement. Data set: Not available.

Requests for Single Reprints: Glen B. Taksler, PhD, Departments of Population Health and Medicine, New York University School of Medicine, 550 First Avenue, Translational Research Building, 6th Floor, New York, NY 10016; e-mail, glentaksler@gmail.com.

Current Author Addresses: Drs. Taksler, Hajizadeh, and Braithwaite and Ms. Keshner: Departments of Population Health and Medicine, New York University School of Medicine, 550 First Avenue, Translational Research Building, 6th Floor, New York, NY 10016.

Dr. Fagerlin: Division of General Internal Medicine, University of Michigan, 2800 Plymouth Road, Building 16, Room 421W, Ann Arbor, MI 48109.

Author Contributions: Conception and design: G.B. Taksler, M. Keshner, N. Hajizadeh, R.S. Braithwaite.

Analysis and interpretation of the data: G.B. Taksler, M. Keshner, N. Hajizadeh, R.S. Braithwaite.

Drafting of the article: G.B. Taksler, N. Hajizadeh, R.S. Braithwaite.

Critical revision of the article for important intellectual content: G.B. Taksler, A. Fagerlin, R.S. Braithwaite.

Final approval of the article: G.B. Taksler, M. Keshner, A. Fagerlin, R.S. Braithwaite.

Provision of study materials or patients: M. Keshner.

Statistical expertise: G.B. Taksler.

Administrative, technical, or logistic support: G.B. Taksler.

Collection and assembly of data: G.B. Taksler, M. Keshner.


Ann Intern Med. 2013;159(3):161-168. doi:10.7326/0003-4819-159-3-201308060-00005
Text Size: A A A

Background: The U.S. Preventive Services Task Force (USPSTF) makes recommendations for 60 distinct clinical services, but clinicians rarely have time to fully evaluate and implement the recommendations.

Objective: To complete a proof of concept for prioritization and personalization of USPSTF recommendations, using patient-specific clinical characteristics.

Design: Mathematical model.

Data Sources: USPSTF recommendations and supporting evidence and National Vital Statistics Reports.

Target Population: Nonpregnant adults.

Time Horizon: Lifetime.

Perspective: Individual.

Intervention: USPSTF grade A and B recommendations.

Outcome Measures: Personalized gain in life expectancy associated with each recommendation.

Results of Base-Case Analysis: Increases in life expectancy varied more than 100-fold across USPSTF recommendations, and the rank order of benefits varied considerably among patients. For an obese man aged 62 years who smoked and had hypercholesterolemia, hypertension, and a family history of colorectal cancer, the model's top 3 recommendations (from most to least gain in life expectancy) were tobacco cessation (adding 2.8 life-years), weight loss (adding 1.6 life-years), and blood pressure control (adding 0.8 life-year). Lower-ranked recommendations were a healthier diet, aspirin use, cholesterol reduction, colonoscopy, screening for abdominal aortic aneurysm, and HIV testing (each adding 0.1 to 0.3 life-years). For a person with the same characteristics plus uncontrolled type 2 diabetes mellitus, the model's top 3 recommendations were diabetes control, tobacco cessation, and weight loss (each adding 1.4 to 1.8 life-years).

Results of Sensitivity Analysis: Robust to variation of model inputs and satisfied face validity criteria.

Limitation: Expected adherence rates and quality of life were not considered.

Conclusion: Models of personalized preventive care may illustrate how magnitude and rank order of benefit associated with preventive guidelines vary across recommendations and patients. These predictions may help clinicians to prioritize USPSTF recommendations at the patient level.

Primary Funding Source: New York University School of Medicine.

Chinese translation

Figures

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Figure 1.

Personalized preventive care model.

A 4-step process was used to create a personalized model of preventive health care recommendations. Detailed methods are available in Supplement 1. AAA = abdominal aortic aneurysm; BMI = body mass index; LDL = low-density lipoprotein; USPSTF = U.S. Preventive Services Task Force.

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Figure 2.

Rank order of personalized preventive care recommendations.

This figure shows personalized life expectancy for 2 hypothetical patients, plus an estimate of how much longer each patient may expect to live by following various preventive care recommendations. Estimates are shown for adherence to each individual recommendation; adherence to several recommendations may change life expectancy by less than the sum of individual recommendations. AAA = abdominal aortic aneurysm.

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Comments

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Personalized estimates of benefit from preventive care guidelines: a proof of concept.
Posted on August 27, 2013
Jan Matthys
University of Ghent, Department of General Practice and Primary Health Care, University Hospital, De Pintelaan 185, 6K3, 9000 Gent, Belgium.
Conflict of Interest: None Declared

Dear editor,

Prioritization of preventive interventions for patients with comorbidities via a mathematical model is interesting and actual (1,2), and is more in line when taking the patient’s preferences and expectations into account. Prioritization might be an alternative for the total cardiovascular risk approach (Framingham, SCORE…). Hereby it is known that in most people, atherosclerotic cardiovascular disease is the product of a number of risk factors, (3) where interaction may play an important role.In that sense we were surprised to read in the legend of the central fig 2 ‘adherence to several recommendations may change life expectancy by less than the sum of individual recommendations’: in this context we cannot agree with this statement because it is not scientifically proven and intuitively, one could assume that the reverse seems even more possible: adherence to more recommendations may change life expectancy by more than the sum of individual recommendations. Further, we must not forget that the most effective approaches have been shown to be multilevel—targeting more than one factor with more than one intervention. (3,4) A single factor approach might be expected to have limited effectiveness if the factors determining adherence interact and potentiate each other’s influence, as they are likely to do. (3) Anyway, apart from aforementioned comments, the shift of focus from population burden of preventable morbidity and mortality to individual priorities makes this article very refreshing.

1. Taksler GB, Keshner M, Fagerlin A, Hajizadeh N, Braithwaite RS. Personalized estimates of benefit from preventive care guidelines: a proof of concept. Ann Intern Med. 2013;159:161-8.

2. Owens DK, Goldhaber-Fiebert JD. Prioritizing guideline-recommended interventions. Ann Intern Med. 2013;159:223-4.

3. ESC/EAS Guidelines for the management of dyslipidemias: the Task Force for the management of dyslipidaemias of the European Society of Cardiology (ESC) and the European Atherosclerosis Society (EAS). Reiner Z, Catapano AL, De Backer G et al. ESC Committee for Practice Guidelines (CPG) 2008-2010 and 2010-2012 Committees. Eur Heart J. 2011; 32:1769-818.

4. Wood DA, Kotseva K, Connolly S, Jennings C, Mead A, Jones J et al. Nurse-coordinated multidisciplinary, family-based cardiovascular disease prevention programme (EUROACTION) for patients with coronary heart disease and asymptomatic individuals at high risk of cardiovascular disease: a paired, cluster-randomized controlled trial. EUROACTION Study Group. Lancet. 2008;371:1999-2012.

Reply to Dr. Matthys
Posted on December 3, 2013
Glen B. Taksler, PhD, R. Scott Braithwaite, MD, MSc
Medicine Institute, Cleveland Clinic (GBT), Departments of Population Health and Medicine, New York University School of Medicine (RSB)
Conflict of Interest: None Declared
We thank Dr. Matthys for this thoughtful feedback. We agree with Dr. Matthys that combinations of interventions may have synergies (that is, greater than additive effects) when delivered together, as was also mentioned in the editorial that accompanied our article (1). We chose cautious language because combinations of interventions may not only confer greater than additive effects, but also may confer less than additive effects.

(1) Owens DK, Goldhaber-Fiebert JD. Prioritizing guideline-recommended interventions. Ann Intern Med. 2013;159:223-4.
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Summary for Patients

Personalized Estimates of Benefit From Preventive Care Guidelines

The full report is titled “Personalized Estimates of Benefit From Preventive Care Guidelines. A Proof of Concept.” It is in the 6 August 2013 issue of Annals of Internal Medicine (volume 159, pages 161-168). The authors are G.B. Taksler, M. Keshner, A. Fagerlin, N. Hajizadeh, and R.S. Braithwaite.

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