Evidence map›Paper›PMID 37422656›Full record

ArticleSystematic reviews2023

Can routinely collected administrative data effectively be used to evaluate and validate endpoints used in breast cancer clinical trials? Protocol for a scoping review of the literature.

Hely Shah, Dianna Wolfe, Mark Clemons, Michelle Liu, Kednapa Thavorn, Areti-Angeliki Veroniki, Carole Lunny, Greg Pond, Sharon McGee, Becky Skidmore and 2 more

Abstract read
In one paragraph

Article in Systematic reviews, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–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

1 citing paper in PubMed.

  1. Article
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

12 authors.

Hely ShahDepartment of Oncology, Ottawa Hospital, Ottawa, ON, Canada.
Dianna WolfeOttawa Hospital Research Institute, Ottawa, ON, Canada.
Mark ClemonsDepartment of Oncology, Ottawa Hospital, Ottawa, ON, Canada.
Michelle LiuOttawa Hospital Research Institute, Ottawa, ON, Canada.
Kednapa ThavornOttawa Hospital Research Institute, Ottawa, ON, Canada.
Areti-Angeliki VeronikiKnowledge Translation Program, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, ON, Canada.
Carole LunnyKnowledge Translation Program, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, ON, Canada.
Greg PondDepartment of Oncology, McMaster University, Hamilton, ON, Canada.
Sharon McGeeDepartment of Oncology, Ottawa Hospital, Ottawa, ON, Canada.
Becky SkidmoreOttawa Hospital Research Institute, Ottawa, ON, Canada.
Angel ArnaoutDepartment of Oncology, Ottawa Hospital, Ottawa, ON, Canada.
Brian HuttonOttawa Hospital Research Institute, Ottawa, ON, Canada. bhutton@ohri.ca.ORCID 0000-0001-5662-8647

Funding

Canadian Cancer Society 707645
6 · The paper itself

Abstract

backgroundRandomized controlled trials (RCTs) are a critical component of evidence-based medicine and the evolution of patient care. However, the costs of conducting a RCT can be prohibitive. A promising approach toward reduction of costs and lessening of the burden of intensive and lengthy patient follow-up is the use of routinely collected healthcare data (RCHD), commonly called real-world data. We propose a scoping review to identify existing RCHD case definitions of breast cancer progression and survival and their diagnostic performance.

methodsWe will search MEDLINE, EMBASE, and CINAHL to identify primary studies of women with either early-stage or metastatic breast cancer, managed with established therapies, that evaluated the diagnostic accuracy of one or more RCHD-based case definitions or algorithms of disease progression (i.e., recurrence, progression-free survival, disease-free survival, or invasive disease-free survival) or survival (i.e., breast-cancer-free survival or overall survival) compared with a reference standard measure (e.g., chart review or a clinical trial dataset). Study characteristics and descriptions of algorithms will be extracted along with measures of the diagnostic accuracy of each algorithm (e.g., sensitivity, specificity, positive predictive value, negative predictive value), which will be summarized both descriptively and in structured figures/tables. DISCUSSION: Findings from this scoping review will be clinically meaningful for breast cancer researchers globally. Identification of feasible and accurate strategies to measure patient-important outcomes will potentially reduce RCT budgets as well as lessen the burden of intensive trial follow-up on patients. SYSTEMATIC REVIEW REGISTRATION: Open Science Framework ( https://doi.org/10.17605/OSF.IO/6D9RS ).

Indexed as

Breast NeoplasmsDisease-Free SurvivalFemaleHumansScoping Reviews as TopicAdministrative dataBreast cancerReal-world dataRecurrenceScoping review

Identifiers

PMID37422656
PMCPMC10329388

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.