Evidence map›Paper›PMID 34896693›Full record

ArticleBreast (Edinburgh, Scotland)2022

A scoping review of interactive and personalized web-based clinical tools to support treatment decision making in breast cancer.

Amy Zhao, Maya Larbi, Kristen Miller, Suzanne O'Neill, Jinani Jayasekera

Abstract readScoping Review
In one paragraph

Article in Breast (Edinburgh, Scotland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 4 pooled it
–field-weighted citation impact
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, 4 syntheses or guidelines pooled it.

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  12. The impact of a web-based prognostic calculator on prognostic confidence in outpatient palliative care.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2024
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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

5 authors.

Amy ZhaoDepartment of Oncology, Georgetown University Medical Center and Cancer Prevention and Control Program, Georgetown-Lombardi Comprehensive Cancer Center, Washington, DC, USA.
Maya LarbiDepartment of Oncology, Georgetown University Medical Center and Cancer Prevention and Control Program, Georgetown-Lombardi Comprehensive Cancer Center, Washington, DC, USA; Towson University, Maryland, USA.
Kristen MillerMedStar Health National Center for Human Factors in Healthcare, Washington, DC, USA.
Suzanne O'NeillDepartment of Oncology, Georgetown University Medical Center and Cancer Prevention and Control Program, Georgetown-Lombardi Comprehensive Cancer Center, Washington, DC, USA.
Jinani JayasekeraDepartment of Oncology, Georgetown University Medical Center and Cancer Prevention and Control Program, Georgetown-Lombardi Comprehensive Cancer Center, Washington, DC, USA. Electronic address: jcj74@georgetown.edu.

Funding

A Simulation Model-based Framework to Support Oncology Guidelines and PracticeK99CA241397 · NCI · GEORGETOWN UNIVERSITY · PI JAYASEKERA, JINANI · 2020 to 2021
$351k
A Simulation Modeling Study to Support Personalized Breast Cancer Prevention and Early Detection in High-Risk WomenR03CA259896 · NCI · GEORGETOWN UNIVERSITY · PI MANDELBLATT, JEANNE · 2021 to 2022
$156k
NCI NIH HHS K99 CA241397NCI NIH HHS R03 CA259896
6 · The paper itself

Abstract

The increasing attention on personalized breast cancer care has resulted in an explosion of new interactive, tailored, web-based clinical decision tools for guiding treatment decisions in clinical practice. The goal of this study was to review, compare, and discuss the clinical implications of current tools, and highlight future directions for tools aiming to improve personalized breast cancer care. We searched PubMed, Embase, PsychInfo, Cochrane Database of Systematic Reviews, Web of Science, and Scopus to identify web-based decision tools addressing breast cancer treatment decisions. There was a total of 17 articles associated with 21 unique tools supporting decisions related to surgery, radiation therapy, hormonal therapy, bisphosphonates, HER2-targeted therapy, and chemotherapy. The quality of the tools was assessed using the International Patient Decision Aid Standard instrument. Overall, the tools considered clinical (e.g., age) and tumor characteristics (e.g., grade) to provide personalized outcomes (e.g., survival) associated with various treatment options. Fewer tools provided the adverse effects of the selected treatment. Only one tool was field-tested with patients, and none were tested with healthcare providers. Future studies need to assess the feasibility, usability, acceptability, as well as the effects of personalized web-based decision tools on communication and decision making from the patient and clinician perspectives.

Indexed as

Breast NeoplasmsDecision MakingFemaleHealth PersonnelHumansInternetBreast cancerTreatmentWeb-based decision tools

Identifiers

PMID34896693
PMCPMC8669108

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.