Evidence map›Paper›PMID 25491637›Full record

ArticleEuropean journal of human genetics : EJHG2015

Capturing the clinical utility of genomic testing: medical recommendations following pediatric microarray.

Robin Z Hayeems, Ny Hoang, Sebastien Chenier, Dimitri J Stavropoulos, Shuye Pu, Rosanna Weksberg, Cheryl Shuman

Abstract read
In one paragraph

Article in European journal of human genetics : EJHG, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

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

  1. How variants of uncertain significance affect clinical decisions: A systematic review.Genetics in medicine : official journal of the American College of Medical Genetics · 2026
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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

7 authors.

Robin Z Hayeems1] Program in Child Health Evaluative, Research Institute, The Hospital for Sick Children, Toronto, ON, Canada [2] Institute of Health Policy Management and Evaluation, The University of Toronto, Toronto, ON, Canada.
Ny Hoang1] Division of Clinical and Metabolic Genetics, The Hospital for Sick Children, Toronto, ON, Canada [2] Program in Genetics and Genome Biology, Research Institute, The Hospital for Sick Children, Toronto, ON, Canada.
Sebastien ChenierCentre Hospitalier Universitaire de Sherbrooke, Sherbrooke, QC, Canada.
Dimitri J StavropoulosDepartment of Paediatric Laboratory Medicine, The Hospital for Sick Children and The University of Toronto, Toronto, ON, Canada.
Shuye PuTerrence Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada.
Rosanna Weksberg1] Division of Clinical and Metabolic Genetics, The Hospital for Sick Children, Toronto, ON, Canada [2] Program in Genetics and Genome Biology, Research Institute, The Hospital for Sick Children, Toronto, ON, Canada [3] Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada [4] Institute of Medical Sciences, University of Toronto, Toronto, ON, Canada.
Cheryl Shuman1] Division of Clinical and Metabolic Genetics, The Hospital for Sick Children, Toronto, ON, Canada [2] Program in Genetics and Genome Biology, Research Institute, The Hospital for Sick Children, Toronto, ON, Canada [3] Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Interpretation of pediatric chromosome microarray (CMA) results presents diagnostic and medical management challenges. Understanding management practices triggered by CMA will inform clinical utility and resource planning. Using a retrospective cohort design, we extracted clinical and management-related data from the records of 752 children with congenital anomalies and/or developmental delay who underwent CMA in an academic pediatric genetics clinic (2009-2011). Frequency distributions and relative rates (RR) of post-CMA medical recommendations in children with reportable and benign CMA results were calculated. Medical recommendations were provided for 79.6% of children with reportable results and 62.0% of children with benign results. Overall, recommendations included specialist consultation (40.8%), imaging (32.5%), laboratory investigations (17.2%), surveillance (4.6%), and family investigations (4.9%). Clinically significant variants and variants of uncertain clinical significance were associated with higher and slightly higher rates of management recommendations, respectively, compared with benign/no variants (RR=1.34; 95% CI (1.22-1.47); RR=1.23; 95% CI (1.09-1.38)). Recommendation rates for clinically significant versus uncertain results depended upon how uncertainty was classified (RRbroad=1.09; 95% CI (0.99-1.2); RRnarrow=1.12; 95% CI (1.02-1.24)). Recommendation rates also varied by the child's age and provider type. In conclusion, medical recommendations follow CMA for the majority of children. Compared with benign CMA results, clinically significant CMA variants are a significant driver of pediatric medical recommendations. Variants of uncertain clinical significance drive recommendations, but to a lesser extent. As a broadening range of specialists will need to respond to CMA results, targeted capacity building is warranted.

Indexed as

Chromosome AberrationsOligonucleotide Array Sequence AnalysisAdolescentChildChild, PreschoolCongenital AbnormalitiesDevelopmental DisabilitiesDiagnostic ImagingDiagnostic Tests, RoutineFemaleGenetic TestingHumansMalePediatricsPedigreeReferral and Consultation

Identifiers

PMID25491637
PMCPMC4538218

What OpenQuestion holds

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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.