Evidence map›Paper›PMID 27577622›Full record

ArticleJournal of oncology practice2016

Communicating Value in Health Care Using Radar Charts: A Case Study of Prostate Cancer.

Nikhil G Thaker, Tariq N Ali, Michael E Porter, Thomas W Feeley, Robert S Kaplan, Steven J Frank

Open access · bronzeAbstract read
In one paragraph

Article in Journal of oncology practice, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
13.8field-weighted citation impact, top 2% 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

21 citing papers in PubMed, 53 citations in OpenAlex.

  1. Article
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  3. Bringing value to cancer research.Frontiers in oncology · 2025
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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

6 authors at 3 institutions in 1 country.

Nikhil G ThakerThe University of Texas MD Anderson Cancer Center, Houston, TX; Arizona Oncology, The US Oncology Network, Tucson, AZ; The Hospital of the University of Pennsylvania, Philadelphia, PA; and Harvard Business School, Boston, MA.
Tariq N AliThe University of Texas MD Anderson Cancer Center, Houston, TX; Arizona Oncology, The US Oncology Network, Tucson, AZ; The Hospital of the University of Pennsylvania, Philadelphia, PA; and Harvard Business School, Boston, MA.
Michael E PorterThe University of Texas MD Anderson Cancer Center, Houston, TX; Arizona Oncology, The US Oncology Network, Tucson, AZ; The Hospital of the University of Pennsylvania, Philadelphia, PA; and Harvard Business School, Boston, MA.
Thomas W FeeleyThe University of Texas MD Anderson Cancer Center, Houston, TX; Arizona Oncology, The US Oncology Network, Tucson, AZ; The Hospital of the University of Pennsylvania, Philadelphia, PA; and Harvard Business School, Boston, MA.
Robert S KaplanThe University of Texas MD Anderson Cancer Center, Houston, TX; Arizona Oncology, The US Oncology Network, Tucson, AZ; The Hospital of the University of Pennsylvania, Philadelphia, PA; and Harvard Business School, Boston, MA.
Steven J FrankThe University of Texas MD Anderson Cancer Center, Houston, TX; Arizona Oncology, The US Oncology Network, Tucson, AZ; The Hospital of the University of Pennsylvania, Philadelphia, PA; and Harvard Business School, Boston, MA sjfrank@mdanderson.org.
The University of Texas MD Anderson Cancer Center · USThe US Oncology Network · USHospital of the University of Pennsylvania · US

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Kathrin Milbury · 1985 to 2026
$290.8M
NCI NIH HHS P30 CA016672
6 · The paper itself

Abstract

purposeThe transformation from volume to value will require communication of outcomes and costs of therapies; however, outcomes are usually nonstandardized, and cost of therapy differs among stakeholders. We developed a standardized value framework by using radar charts to visualize and communicate a wide range of patient outcomes and cost for three forms of prostate cancer treatment. MATERIALS AND

methodsWe retrospectively reviewed data from men with low-risk prostate cancer who were treated with low-dose rate brachytherapy (LDR-BT), proton beam therapy, or robotic-assisted prostatectomy. Patient-reported outcomes comprised the Expanded Prostate Cancer Index Composite-50 domains for sexual function, urinary incontinence and/or bother, bowel bother, and vitality 12 months after treatment. Costs were measured by time-driven activity-based costing for the first 12 months of the care cycle. Outcome and cost data were plotted on a single radar chart for each treatment modality.

resultsOutcome and cost data from patients who were treated with robotic-assisted prostatectomy (n = 381), proton beam therapy (n = 165), and LDR-BT (n = 238) were incorporated into the radar chart. LDR-BT seemed to deliver the highest overall value of the three treatment modalities; however, incorporation of patient preferences regarding outcomes may allow other modalities to be considered high-value treatment options.

conclusionStandardization and visualization of outcome and cost metrics may allow more comprehensive and collaborative discussions about the value of health care services. Communicating the value framework by using radar charts may be an effective method to present total value and the value of all outcomes and costs in a manner that is accessible to all stakeholders. Variations in plotting of costs and outcomes will require future focus group initiatives.

Indexed as

Cost-Benefit AnalysisProstatic NeoplasmsResearch DesignBrachytherapyHealth Care CostsHumansMalePatient Reported Outcome MeasuresProstatectomyProton TherapyQuality of LifeTreatment Outcome

Identifiers

PMID27577622
PMCPMC5508207
OpenAlexW2517816123

What OpenQuestion holds

Textmetadata
LicenceTDM
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.