Evidence map›Paper›PMID 34287630›Full record

ArticleJAMA network open2021

Clinician Conceptualization of the Benefits of Treatments for Individual Patients.

Daniel J Morgan, Lisa Pineles, Jill Owczarzak, Larry Magder, Laura Scherer, Jessica P Brown, Chris Pfeiffer, Chris Terndrup, Luci Leykum, David Feldstein and 6 more

Open access · goldAbstract read
In one paragraph

Article in JAMA network open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
2.0field-weighted citation impact, top 12% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors at 10 institutions in 1 country.

Daniel J MorganDepartment of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore.
Lisa PinelesDepartment of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore.
Jill OwczarzakDepartment of Health, Behavior and Society, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.
Larry MagderDepartment of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore.
Laura SchererAdult and Child Consortium of Health Outcomes Research and Delivery Science (ACCORDS), University of Colorado School of Medicine, Aurora.
Jessica P BrownDepartment of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore.
Chris PfeifferDivision of General Internal Medicine and Geriatrics, Department of Medicine, Oregon Health and Science University, Portland.
Chris TerndrupDivision of General Internal Medicine and Geriatrics, Department of Medicine, Oregon Health and Science University, Portland.
Luci LeykumDepartment of Medicine, Dell Medical School, the University of Texas at Austin.
David FeldsteinDepartment of Medicine, University of Wisconsin School of Medicine and Public Health, Madison.
Andrew FoyDepartment of Medicine, Penn State College of Medicine, Hershey, Pennsylvania.
Deborah StevensDepartment of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore.
Christina KochDepartment of Medicine, University of Maryland School of Medicine, Baltimore.
Max MasnickGenomic Medicine Institute, Geisinger, Danville, Pennsylvania.
Scott WeisenbergNew York University Grossman School of Medicine, New York.
Deborah KorensteinMemorial Sloan Kettering Cancer Center, New York, New York.
University of Maryland, Baltimore · USOregon Health & Science University · USJohns Hopkins University · USMemorial Sloan Kettering Cancer Center · USNew York University · USOutcomes Research Consortium · USPennsylvania State University · USSouth Texas Veterans Health Care System · USUniversity of Wisconsin–Madison · USVA Maryland Health Care System · US

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Nicholas D Socci · 1985 to 2026
$347.4M
Incorporating Bayesian reasoning into physician testing and treatment decisionsDP2LM012890 · NLM · UNIVERSITY OF MARYLAND BALTIMORE · PI MORGAN, DANIEL J · 2017 to 2017
$2.3M
NCI NIH HHS P30 CA008748
6 · The paper itself

Abstract

Importance: Knowing the expected effect of treatment on an individual patient is essential for patient care. Objective: To explore clinicians' conceptualizations of the chance that treatments will decrease the risk of disease outcomes. Design, Setting, and Participants: This survey study of attending and resident physicians, nurse practitioners, and physician assistants was conducted in outpatient clinical settings in 8 US states from June 2018 to November 2019. The survey was an in-person, paper, 26-item survey in which clinicians were asked to estimate the probability of adverse disease outcomes and expected effects of therapies for diseases common in primary care. Main Outcomes and Measures: Estimated chance that treatments would benefit an individual patient. Results: Of 723 clinicians, 585 (81%) responded, and 542 completed all the questions necessary for analysis, with a median (interquartile range [IQR]) age of 32 (29-44) years, 287 (53%) women, and 294 (54%) White participants. Clinicians consistently overestimated the chance that treatments would benefit an individual patient. The median (IQR) estimated chance that warfarin would prevent a stroke in the next year was 50% (5%-80%) compared with scientific evidence, which indicates an absolute risk reduction (ARR) of 0.2% to 1.0% based on a relative risk reduction (RRR) of 39% to 50%. The median (IQR) estimated chance that antihypertensive therapy would prevent a cardiovascular event within 5 years was 30% (10%-70%) vs evidence of an ARR of 0% to 3% based on an RRR of 0% to 28%. The median (IQR) estimated chance that bisphosphonate therapy would prevent a hip fracture in the next 5 years was 40% (10%-60%) vs evidence of ARR of 0.1% to 0.4% based on an RRR of 20% to 40%. The median (IQR) estimated chance that moderate-intensity statin therapy would prevent a cardiovascular event in the next 5 years was 20% (IQR 5%-50%) vs evidence of an ARR of 0.3% to 2% based on an RRR of 19% to 33%. Estimates of the chance that a treatment would prevent an adverse outcome exceeded estimates of the absolute chance of that outcome for 60% to 70% of clinicians. Clinicians whose overestimations were greater were more likely to report using that treatment for patients in their practice (eg, use of warfarin: correlation coefficient, 0.46; 95% CI, 0.40-0.53; P < .001). Conclusions and Relevance: In this survey study, clinicians significantly overestimated the benefits of treatment to individual patients. Clinicians with greater overestimates were more likely to report using treatments in actual patients.

Indexed as

Treatment OutcomeAdultAmbulatory CareConcept FormationFemaleHumansMaleNurse PractitionersPhysician AssistantsPhysiciansPrimary Health CareProbabilityRisk Reduction BehaviorUnited States

Identifiers

PMID34287630
PMCPMC8295738
OpenAlexW3184881502

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.