Literature DB >> 19012353

Improving understanding of adjuvant therapy options by using simpler risk graphics.

Brian J Zikmund-Fisher1, Angela Fagerlin, Peter A Ubel.   

Abstract

BACKGROUND: To help oncologists and breast cancer patients make informed decisions about adjuvant therapies, online tools such as Adjuvant! provide tailored estimates of mortality and recurrence risks. However, the graphical format used to display these results (a set of 4 horizontal stacked bars) may be suboptimal. The authors tested whether using simpler formats would improve comprehension of the relevant risk statistics.
METHODS: A total of 1,619 women, aged 40-74 years, completed an Internet-administered survey vignette about adjuvant therapy decisions for a patient with an estrogen receptor-positive tumor. Participants were randomized to view 1 of 4 risk graphics, a base version that mirrored the Adjuvant! format, an alternate graph that showed only 2 options (those that included hormonal therapy), a graph that used a pictograph format, or a graph that included both changes. Outcome measures included comprehension of key statistics, time required to complete the task, and graph-perception ratings.
RESULTS: The simplifying format changes significantly improved comprehension, especially when both changes were implemented together. Compared with participants who viewed the base 4-option bar graph, respondents who, instead, viewed a 2-option pictograph version were more accurate when they reported the incremental risk reduction achievable from adding chemotherapy to hormonal therapy (77% vs 51%; P< .001), answered that question more quickly (median time, 28 seconds vs 42 seconds; P< .001), and liked the graph more (mean, 7.67 vs 6.88; P< .001).
CONCLUSIONS: Although most patients will only view risk calculators such as Adjuvant! in consultation with their clinicians, simplifying design graphics could significantly improve patients' comprehension of statistics essential for informed decision making about adjuvant therapies.

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Year:  2008        PMID: 19012353      PMCID: PMC2716049          DOI: 10.1002/cncr.23959

Source DB:  PubMed          Journal:  Cancer        ISSN: 0008-543X            Impact factor:   6.860


  17 in total

1.  Judgments of change and proportion in graphical perception.

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2.  Reducing aversion to side effects in preventive medical treatment decisions.

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3.  Risk communication with patients with breast cancer: cautionary notes about printing Adjuvant! estimates.

Authors:  Jeffrey Belkora; Hope S Rugo; Dan H Moore; David Hutton; Laura Esserman
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4.  Further insight into the perception of quantitative information: judgments of gist in treatment decisions.

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5.  Reducing the influence of anecdotal reasoning on people's health care decisions: is a picture worth a thousand statistics?

Authors:  Angela Fagerlin; Catharine Wang; Peter A Ubel
Journal:  Med Decis Making       Date:  2005 Jul-Aug       Impact factor: 2.583

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8.  Communicating risk information: the influence of graphical display format on quantitative information perception-Accuracy, comprehension and preferences.

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9.  Measuring numeracy without a math test: development of the Subjective Numeracy Scale.

Authors:  Angela Fagerlin; Brian J Zikmund-Fisher; Peter A Ubel; Aleksandra Jankovic; Holly A Derry; Dylan M Smith
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10.  Alternate methods of framing information about medication side effects: incremental risk versus total risk of occurrence.

Authors:  Brian J Zikmund-Fisher; Angela Fagerlin; Todd R Roberts; Holly A Derry; Peter A Ubel
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  42 in total

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Review 3.  Communicating genetic risk information for common disorders in the era of genomic medicine.

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Review 5.  Decision making and cancer.

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6.  Tables or bar graphs? Presenting test results in electronic medical records.

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7.  Informing, Reassuring, or Alarming? Balancing Patient Needs in the Development of a Postsurgical Symptom Reporting System in Cancer.

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Review 8.  Risky feelings: why a 6% risk of cancer does not always feel like 6%.

Authors:  Brian J Zikmund-Fisher; Angela Fagerlin; Peter A Ubel
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9.  More Is Not Always Better: Intuitions About Effective Public Policy Can Lead to Unintended Consequences.

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10.  Oncologist use of the Adjuvant! model for risk communication: a pilot study examining patient knowledge of 10-year prognosis.

Authors:  Jeffrey K Belkora; Hope S Rugo; Dan H Moore; David W Hutton; Daniel F Chen; Laura J Esserman
Journal:  BMC Cancer       Date:  2009-04-28       Impact factor: 4.430

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