Evidence map›Paper›PMID 28749474›Full record

ArticleGenetics in medicine : official journal of the American College of Medical Genetics2018

Racial/ethnic differences in multiple-gene sequencing results for hereditary cancer risk.

Jennifer L Caswell-Jin, Tanya Gupta, Evan Hall, Iva M Petrovchich, Meredith A Mills, Kerry E Kingham, Rachel Koff, Nicolette M Chun, Peter Levonian, Alexandra P Lebensohn and 2 more

Open access · bronzeAbstract read
PubMed Publisher
In one paragraph

Article in Genetics in medicine : official journal of the American College of Medical Genetics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 122 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
122citing papers in PubMed, 1 pooled it
13.2field-weighted citation impact, top 1% 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

122 citing papers in PubMed, 1 synthesis or guideline pooled it, 214 citations in OpenAlex.

  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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  11. Homologous Recombination Deficiency and Survival in Ovarian High-Grade Serous Carcinoma by Self-Reported Race.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2025
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62 more citing papers are in PubMed but not listed here.

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 at 1 institution in 1 country.

Jennifer L Caswell-JinDepartment of Medicine, Division of Medical Oncology, Stanford University, Stanford, California, USA.
Tanya GuptaDepartment of Medicine, Division of Medical Oncology, Stanford University, Stanford, California, USA.
Evan HallDepartment of Medicine, Division of Medical Oncology, Stanford University, Stanford, California, USA.
Iva M PetrovchichDepartment of Medicine, Division of Medical Oncology, Stanford University, Stanford, California, USA.
Meredith A MillsDepartment of Medicine, Division of Medical Oncology, Stanford University, Stanford, California, USA.
Kerry E KinghamDepartment of Medicine, Division of Medical Oncology, Stanford University, Stanford, California, USA.
Rachel KoffDepartment of Medicine, Division of Medical Oncology, Stanford University, Stanford, California, USA.
Nicolette M ChunDepartment of Medicine, Division of Medical Oncology, Stanford University, Stanford, California, USA.
Peter LevonianDepartment of Medicine, Division of Medical Oncology, Stanford University, Stanford, California, USA.
Alexandra P LebensohnDepartment of Medicine, Division of Medical Oncology, Stanford University, Stanford, California, USA.
James M FordDepartment of Medicine, Division of Medical Oncology, Stanford University, Stanford, California, USA.
Allison W KurianDepartment of Medicine, Division of Medical Oncology, Stanford University, Stanford, California, USA.
Stanford University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PurposeWe examined racial/ethnic differences in the usage and results of germ-line multiple-gene sequencing (MGS) panels to evaluate hereditary cancer risk.MethodsWe collected genetic testing results and clinical information from 1,483 patients who underwent MGS at Stanford University between 1 January 2013 and 31 December 2015.ResultsAsians and Hispanics presented for MGS at younger ages than whites (48 and 47 vs. 55; P = 5E-16 and 5E-14). Across all panels, the rate of pathogenic variants (15%) did not differ significantly between racial groups. Rates by gene did differ: in particular, a higher percentage of whites than nonwhites carried pathogenic CHEK2 variants (3.8% vs. 1.0%; P = 0.002). The rate of a variant of uncertain significance (VUS) result was higher in nonwhites than whites (36% vs. 27%; P = 2E-4). The probability of a VUS increased with increasing number of genes tested; this effect was more pronounced for nonwhites than for whites (1.1% absolute difference in VUS rates testing BRCA1/2 vs. 8% testing 13 genes vs. 14% testing 28 genes), worsening the disparity.ConclusionIn this diverse cohort undergoing MGS testing, pathogenic variant rates were similar between racial/ethnic groups. By contrast, VUS results were more frequent among nonwhites, with potential significance for the impact of MGS testing by race/ethnicity.

Indexed as

Biomarkers, TumorGenetic Predisposition to DiseaseHigh-Throughput Nucleotide SequencingAdultAgedEthnicityFemaleGenetic TestingHumansMaleMiddle AgedNeoplastic Syndromes, HereditaryRacial GroupsRisk AssessmentSequence Analysis, DNAYoung AdultBiomarkers, Tumor

Identifiers

PMID28749474
OpenAlexW2736788632

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.