Evidence map›Paper›PMID 33087880›Full record

ArticleEuropean journal of human genetics : EJHG2021

Measuring clinical utility in the context of genetic testing: a scoping review.

Shantel E Walcott, Fiona A Miller, Kourtney Dunsmore, Tanya Lazor, Brian M Feldman, Robin Z Hayeems

Abstract readScoping Review
In one paragraph

Article in European journal of human genetics : EJHG, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 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

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. 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

6 authors.

Shantel E WalcottInstitute of Health Policy Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.
Fiona A MillerInstitute of Health Policy Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.ORCID http://orcid.org/0000-0003-4953-6255
Kourtney DunsmoreInstitute of Health Policy Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.ORCID http://orcid.org/0000-0001-6367-4596
Tanya LazorInstitute of Health Policy Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.
Brian M FeldmanInstitute of Health Policy Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.
Robin Z HayeemsInstitute of Health Policy Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada. robin.hayeems@sickkids.ca.ORCID http://orcid.org/0000-0003-3269-8004

Funding

CIHR PJT-152880
6 · The paper itself

Abstract

Standardized approaches to measuring clinical utility will enable more robust evaluations of genetic tests. To characterize how clinical utility has been measured, this scoping review examined outcomes used to operationalize this concept in the context of genetic testing, spanning relevant literature (2015-2017). The search strategy and analysis were guided by the Fryback and Thornbury hierarchical model of efficacy (FT Model). Through searches in Ovid MEDLINE, EMBASE and Web of Science, 194 publications were identified for inclusion. Two coders reviewed titles, abstracts, and full texts to determine eligibility. Results were analyzed using thematic and frequency analyses. This review generated a catalog of outcomes mapped to the efficacy domains of the FT Model. The degree of representation observed in each domain varied by the clinical purpose and clinical indication of genetic testing. Diagnostic accuracy (68%), technical (28.4%), and patient outcome (28.4%) efficacy studies were represented at the highest rate. Findings suggest that the FT Model is suitable for the genetics context however domain refinements may be warranted. More diverse clinical settings, robust study designs, and novel strategies for measuring clinical utility are needed.

Indexed as

Genetic TestingHumansOutcome Assessment, Health CareSensitivity and Specificity

Identifiers

PMID33087880
PMCPMC7940410

What OpenQuestion holds

Textmetadata
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.