Evidence map›Paper›PMID 26467025›Full record

ArticleHuman mutation2016

A Standardized DNA Variant Scoring System for Pathogenicity Assessments in Mendelian Disorders.

Izabela Karbassi, Glenn A Maston, Angela Love, Christina DiVincenzo, Corey D Braastad, Christopher D Elzinga, Alison R Bright, Domenic Previte, Ke Zhang, Charles M Rowland and 15 more

Registry-linked trialOpen access · hybridAbstract read
In one paragraph

Article in Human mutation, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07644455 (Evaluation of the Accuracy of Vacuum-assisted Percutaneous Biopsy in Predicting Mammary Anatomopathological Response in Breast Cancer Patients Undergoing Neoadjuvant Chemotherapy), which is not on this map. Cited by 36 papers.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed
4.7field-weighted citation impact, top 5% 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.

NCT07644455 nanot yet recruitingnot on this mapstarted 2026, after this paper: background citation

Evaluation of the Accuracy of Vacuum-assisted Percutaneous Biopsy in Predicting Mammary Anatomopathological Response in Breast Cancer Patients Undergoing Neoadjuvant Chemotherapy

TypeinterventionalSponsorInstituto do Cancer do Estado de São PauloRan2026 to 2026Enrolled100ConditionsBreast CancerArmsPre-Neoadjuvant Chemotherapy Clipping, Vacuum-Assisted Biopsy (VAB)
3 · Its place in the literature

Who cites it

36 citing papers in PubMed, 70 citations in OpenAlex.

  1. Distinct rates of VUS reclassification are observed when subclassifying VUS by evidence level.Genetics in medicine : official journal of the American College of Medical Genetics · 2025
    Article
  2. Article
  3. Article
  4. Article
  5. Biomedicines · 2024
    Review
  6. Article
  7. Article
  8. Article
  9. The landscape of reported VUS in multi-gene panel and genomic testing: Time for a change.Genetics in medicine : official journal of the American College of Medical Genetics · 2023
    Article
  10. Article
  11. Article
  12. Review
  13. The Clinical Variant Analysis Tool: Analyzing the evidence supporting reported genomic variation in clinical practice.Genetics in medicine : official journal of the American College of Medical Genetics · 2022
    Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. A NovelAnnals of laboratory medicine · 2021
    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

25 authors at 1 institution in 1 country.

Izabela KarbassiQuest Diagnostics, Athena Diagnostics, Marlborough, Massachusetts.
Glenn A MastonQuest Diagnostics, Athena Diagnostics, Marlborough, Massachusetts.
Angela LoveQuest Diagnostics, Athena Diagnostics, Marlborough, Massachusetts.
Christina DiVincenzoQuest Diagnostics, Athena Diagnostics, Marlborough, Massachusetts.
Corey D BraastadQuest Diagnostics, Athena Diagnostics, Marlborough, Massachusetts.
Christopher D ElzingaQuest Diagnostics, Athena Diagnostics, Marlborough, Massachusetts.
Alison R BrightQuest Diagnostics, Athena Diagnostics, Marlborough, Massachusetts.
Domenic PreviteQuest Diagnostics, Athena Diagnostics, Marlborough, Massachusetts.
Ke ZhangQuest Diagnostics, Nichols Institute, San Juan Capistrano, California.
Charles M RowlandQuest Diagnostics, Celera, Alameda, California.
Michele McCarthyQuest Diagnostics, Athena Diagnostics, Marlborough, Massachusetts.
Jennifer L LapierreQuest Diagnostics, Athena Diagnostics, Marlborough, Massachusetts.
Felicita DuboisQuest Diagnostics, Athena Diagnostics, Marlborough, Massachusetts.
Katelyn A MedeirosQuest Diagnostics, Athena Diagnostics, Marlborough, Massachusetts.
Sat Dev BatishQuest Diagnostics, Athena Diagnostics, Marlborough, Massachusetts.
Jeffrey JonesQuest Diagnostics, Athena Diagnostics, Marlborough, Massachusetts.
Khalida LiaquatQuest Diagnostics, Athena Diagnostics, Marlborough, Massachusetts.
Carol A HoffmanQuest Diagnostics, Athena Diagnostics, Marlborough, Massachusetts.
Malgorzata JaremkoQuest Diagnostics, Athena Diagnostics, Marlborough, Massachusetts.
Zhenyuan WangQuest Diagnostics, Athena Diagnostics, Marlborough, Massachusetts.
Weimin SunQuest Diagnostics, Nichols Institute, San Juan Capistrano, California.
Arlene Buller-BurckleQuest Diagnostics, Nichols Institute, San Juan Capistrano, California.
Charles M StromQuest Diagnostics, Nichols Institute, San Juan Capistrano, California.
Steven B KeilesQuest Diagnostics, Nichols Institute, San Juan Capistrano, California.
Joseph J HigginsQuest Diagnostics, Athena Diagnostics, Marlborough, Massachusetts.
Quest Diagnostics (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We developed a rules-based scoring system to classify DNA variants into five categories including pathogenic, likely pathogenic, variant of uncertain significance (VUS), likely benign, and benign. Over 16,500 pathogenicity assessments on 11,894 variants from 338 genes were analyzed for pathogenicity based on prediction tools, population frequency, co-occurrence, segregation, and functional studies collected from internal and external sources. Scores were calculated by trained scientists using a quantitative framework that assigned differential weighting to these five types of data. We performed descriptive and comparative statistics on the dataset and tested interobserver concordance among the trained scientists. Private variants defined as variants found within single families (n = 5,182), were either VUS (80.5%; n = 4,169) or likely pathogenic (19.5%; n = 1,013). The remaining variants (n = 6,712) were VUS (38.4%; n = 2,577) or likely benign/benign (34.7%; n = 2,327) or likely pathogenic/pathogenic (26.9%, n = 1,808). Exact agreement between the trained scientists on the final variant score was 98.5% [95% confidence interval (CI) (98.0, 98.9)] with an interobserver consistency of 97% [95% CI (91.5, 99.4)]. Variant scores were stable and showed increasing odds of being in agreement with new data when re-evaluated periodically. This carefully curated, standardized variant pathogenicity scoring system provides reliable pathogenicity scores for DNA variants encountered in a clinical laboratory setting.

Indexed as

Genetic Predisposition to DiseaseGenetic VariationSoftwareComputational BiologyGenomicsHumansObserver VariationReproducibility of ResultsWeb Browserclinical laboratory techniquesdatabasesdecision support techniquesmutationnucleic acidpolymorphism

Identifiers

PMID26467025
PMCPMC4737317
OpenAlexW2167588661

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

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.