Evidence map›Paper›PMID 32349762›Full record

ArticleBMC medical informatics and decision making2020

Development of a patient decision aid for the management of superficial basal cell carcinoma (BCC) in adults with a limited life expectancy.

Alexandra Junn, Neha R Shukla, Lily Morrison, Meghan Halley, Mary-Margaret Chren, Louise C Walter, Dominick L Frosch, Dan Matlock, Jeanette S Torres, Eleni Linos

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC medical informatics and decision making, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.0field-weighted citation impact, top 23% 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

8 citing papers in PubMed, 17 citations in OpenAlex.

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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

10 authors at 7 institutions in 1 country.

Alexandra JunnProgram for Clinical Research, Department of Dermatology, University of California San Francisco, San Francisco, USA.
Neha R ShuklaProgram for Clinical Research, Department of Dermatology, University of California San Francisco, San Francisco, USA.
Lily MorrisonDepartment of Dermatology, Stanford University, CCSR Building Room 4235, 269 Campus Drive, Stanford, USA.
Meghan HalleyDepartment of Dermatology, Stanford University, CCSR Building Room 4235, 269 Campus Drive, Stanford, USA.
Mary-Margaret ChrenDepartment of Dermatology, Vanderbilt University Medical Centre, Tennessee, Nashville, USA.
Louise C WalterDivision of Geriatrics, Department of Medicine, University of California, San Francisco, USA.
Dominick L FroschPalo Alto Medical Foundation Research Institute, Palo Alto, USA.
Dan MatlockDivision of Geriatric Medicine, Department of Medicine, University of Colorado School of Medicine, Aurora, USA.
Jeanette S TorresProgram for Clinical Research, Department of Dermatology, University of California San Francisco, San Francisco, USA.
Eleni LinosDepartment of Dermatology, Stanford University, CCSR Building Room 4235, 269 Campus Drive, Stanford, USA. linos@stanford.edu.ORCID 0000-0002-5856-6301
University of California, San Francisco · USStanford University · USGeriatric Research Education and Clinical Center · USPalo Alto Institute · USSan Francisco VA Medical Center · USUniversity of California, Los Angeles · USVanderbilt University Medical Center · US

Funding

Targeted Advertising for Cancer PreventionDP2CA225433 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI LINOS, ELENI · 2017 to 2019
$2.9M
Patient Oriented Research in Vulnerable Populations with Skin DiseaseK24AR075060 · NIAMS · STANFORD UNIVERSITY · PI Eleni Linos · 2019 to 2026
$1.6M
Involving older adults in decision making for skin cancerK76AG054631 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI LINOS, ELENI · 2016 to 2018
$644k
Online Advertising for Skin Cancer PreventionR21CA212201 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI LINOS, ELENI · 2017 to 2018
$379k
NCI NIH HHS DP2 CA225433NCI NIH HHS R21 CA212201NIAMS NIH HHS K24 AR075060NIA NIH HHS K76 AG054631
6 · The paper itself

Abstract

backgroundBasal cell carcinoma (BCC) is a slow-growing, rarely lethal skin cancer that affects people 65 years or older. A range of treatment options exist for BCC, but there is little evidence available to guide patients and providers in selecting the best treatment options.

objectivesThis study outlines the development of a patient decision aid (PDA) for low-risk BCC that can be used by patients and providers to assist in shared decision-making.

methodsIn accordance with the International Patient Decision Aids Standards (IPDAS) Collaboration framework, feedback from focus groups and semi-structured interviews with patients and providers, an initial prototype of the PDA was developed. This was tested using cognitive interviews and iteratively updated.

resultsWe created eighteen different iterations using feedback from 24 patients and 34 providers. The key issues identified included: 1) Addressing fear of cancer; 2) Communicating risk and uncertainty; 3) Values clarification; and 4) Time lag to benefit. LIMITATIONS: The PDA does not include all possible treatment options and is currently paper based.

conclusionsOur PDA has been specifically adapted and designed to support patients with a limited life expectancy in making decisions about their low risk BCC together with their doctors.

Indexed as

Decision Support TechniquesSkin NeoplasmsAdultAgedAged, 80 and overBasal Cell CarcinomaClinical Decision-MakingFocus GroupsHumansInterviews as TopicLife ExpectancyMiddle AgedPatientsBasal cell carcinomaDecision aidOlder adultsShared decision making

Identifiers

PMID32349762
PMCPMC7191775
OpenAlexW3022083246

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.