Evidence map›Paper›PMID 30553750›Full record

ArticleThe Journal of molecular diagnostics : JMD2019

Rapid Next-Generation Sequencing Method for Prediction of Prostate Cancer Risks.

Viacheslav Y Fofanov, Kinnari Upadhyay, Alexander Pearlman, Johnny Loke, Vivian O, Yongzhao Shao, Stephen Freedland, Harry Ostrer

Abstract read
In one paragraph

Article in The Journal of molecular diagnostics : JMD, 2019. 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
0.4field-weighted citation impact, top 33% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  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

8 authors at 4 institutions in 1 country.

Viacheslav Y FofanovSchool of Informatics, Computing and Cyber Systems, Northern Arizona State University, Flagstaff, Arizona.
Kinnari UpadhyayDepartment of Pathology, Albert Einstein College of Medicine, Bronx, New York.
Alexander PearlmanDepartment of Pathology, Albert Einstein College of Medicine, Bronx, New York.
Johnny LokeDepartment of Pathology, Albert Einstein College of Medicine, Bronx, New York.
Vivian ODepartment of Pathology, Albert Einstein College of Medicine, Bronx, New York.
Yongzhao ShaoDepartment of Population Health, New York University School of Medicine, New York, New York.
Stephen FreedlandCedars-Sinai Medical Center, Los Angeles, California; Durham VA Medical Center, Durham, North Carolina.
Harry OstrerDepartment of Pathology, Albert Einstein College of Medicine, Bronx, New York. Electronic address: harry.ostrer@einstein.yu.edu.
Albert Einstein College of Medicine · USCedars-Sinai Medical Center · USNew York University · USNorthern Arizona University · US

Funding

Genomics and Predictive Modeling of Prostate Cancer Heath DisparityU01CA158431 · NCI · ALBERT EINSTEIN COLLEGE OF MEDICINE, INC · PI OSTRER, HARRY · 2011 to 2015
$1.6M
NCI NIH HHS U01 CA158431
6 · The paper itself

Abstract

Prostate cancer is the most commonly diagnosed male cancer and the second leading cause of cancer deaths among men in the United States, with approximately 220,000 new diagnoses and approximately 27,000 deaths each year. Men with clinical low-risk disease can receive active surveillance to safely preserve quality of life, provided that the risk of an undetected aggressive cancer can be managed. Thus, prediction of a tumor's metastatic potential, ideally using only a biopsy sample, is critical to choosing appropriate treatment. We previously proposed and verified a metastasis potential score (MPS) based on regions prone to copy number alterations in metastatic prostate cancer; MPS is highly predictive of metastatic potential in primary tumors. We developed a novel, targeted postligation amplification sequencing approach, which we call the next-generation copy number alteration assay, to efficiently interrogate 902 genomic sites that belong to 194 genomic regions used in the MPS calculation. The assay is designed to work with the latest generation of sequencing platforms to produce estimates of copy number alteration events. The assay's technical reproducibility, robustness to low starting genomic material, and accuracy have been verified. The assay performed very well on cell lines, a cohort of prostate cancer surgical research samples, and matched punched biopsy samples, making it a significant step toward incorporating sequencing techniques for prostate cancer evaluation.

Indexed as

DNA Copy Number VariationsGenetic TestingHigh-Throughput Nucleotide SequencingHumansMalePrognosisProstatic NeoplasmsQuality of LifeRisk FactorsTime Factors

Identifiers

PMID30553750
PMCPMC6334266
OpenAlexW2905178226

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.