In one paragraphArticle in JCO precision oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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 registryThe 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 literatureWho cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
4 · The recordCorrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what moneyAuthors and funding
27 authors.
Hari SankaranBiometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD.ORCID 0000-0003-0666-2630 Yuri KotliarovBiometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD.ORCID 0000-0002-6558-8883 Yingdong ZhaoBiometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD.
Lyndsay N HarrisCancer Diagnosis Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD.ORCID 0000-0002-9774-6719 Chris KarlovichMolecular Characterization Laboratory, Frederick National Laboratory for Cancer Research, Frederick, MD.ORCID 0000-0002-4617-2161 Ting-Chia ChangMolecular Characterization Laboratory, Frederick National Laboratory for Cancer Research, Frederick, MD.ORCID 0000-0001-6296-5797 Victoria WangDana Farber Cancer Institute-ECOG-ACRIN Biostatistical Center, Boston, MA.
Sarah J ShinDivision of Cancer Treatment and Diagnosis, Developmental Therapeutics Clinic, National Cancer Institute, Bethesda, MD.
Nita L SeibelDivision of Cancer Treatment and Diagnosis, Clinical Investigations Branch, National Cancer Institute, Bethesda, MD.ORCID 0000-0001-6259-7955 Biswajit DasMolecular Characterization Laboratory, Frederick National Laboratory for Cancer Research, Frederick, MD.ORCID 0000-0001-7225-2926 Brent CoffeyCenter for Biomedical Informatics and Information Technology, National Cancer Institute, Bethesda, MD.
David PattonCenter for Biomedical Informatics and Information Technology, National Cancer Institute, Bethesda, MD.ORCID 0000-0003-3855-0166 Ming-Chung LiBiometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD.ORCID 0009-0002-7053-5652 Jessica LiBiometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD.
Ana F BestBiometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD.ORCID 0000-0002-4467-1725 P Mickey WilliamsMolecular Characterization Laboratory, Frederick National Laboratory for Cancer Research, Frederick, MD.ORCID 0000-0002-3309-5988 Alice P ChenDivision of Cancer Treatment and Diagnosis, Developmental Therapeutics Clinic, National Cancer Institute, Bethesda, MD.ORCID 0000-0002-2919-4326 Lisa M McShaneBiometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD.ORCID 0000-0001-8195-3206 Funding
Project-006U10CA180820 · NCI · ECOG-ACRIN MEDICAL RESEARCH FOUNDATION · PI Peter J ODwyer · 2014 to 2026
$167.6MStatistics CoreU10CA180794 · NCI · DANA-FARBER CANCER INST · PI PAUL J CATALANO · 2014 to 2026
$111.2MColumbus NCORP RFA-CA-18-016UG1CA189954 · NCI · COLUMBUS COMMUNITY CLINICAL ONCOLOGY PRG · PI Aruna Gowda, Malolan S Rajagopalan · 2014 to 2026
$9.8MNCTN Lead Academic Participating Site at Dana-Farber/Partners Cancer CareUG1CA233180 · NCI · DANA-FARBER CANCER INST · PI Harold John Burstein · 2019 to 2026
$8.6MUT Southwestern NCI National Clinical Trials Network (NCTN) LAPS - Supplemental Funds YR4UG1CA233302 · NCI · UT SOUTHWESTERN MEDICAL CENTER · PI David Eric Gerber · 2019 to 2026
$6.4MMedical College of Wisconsin Lead Academic Participating Site RenewalUG1CA233198 · NCI · MEDICAL COLLEGE OF WISCONSIN · PI William H Bradley, Elizabeth M Gore · 2019 to 2026
$5.0MNCTN LAPS at Johns HopkinsUG1CA233196 · NCI · JOHNS HOPKINS UNIVERSITY · PI DEBORAH K ARMSTRONG, Julie Renee Brahmer · 2019 to 2026
$4.6MThe Duke University - Duke Cancer Institute National Clinical Trials Network LAPS (UG1) Support GrantUG1CA233253 · NCI · DUKE UNIVERSITY · PI John H Strickler, Alexandra Thomas · 2019 to 2026
$3.7MNCI NIH HHS U10 CA180794NCI NIH HHS U10 CA180820NCI NIH HHS UG1 CA189954NCI NIH HHS UG1 CA233180NCI NIH HHS UG1 CA233196NCI NIH HHS UG1 CA233198NCI NIH HHS UG1 CA233253NCI NIH HHS UG1 CA233302
6 · The paper itselfAbstract
purposeMotivated by the rising incidence of cancers at younger ages, this study compares tumor genomic alterations between adolescents and young adults (AYAs; 18-39 years) and non-AYAs (40 years and older) and explores the relationship with continuous age in patients with relapsed/refractory ovarian, breast, and colorectal cancers accrued to the NCI-MATCH trial.
methodsTumor genomic profiles generated by a next-generation sequencing 143-gene panel (NCI-MATCH assay, v2) were analyzed for association with age (AYA/total: 21/455 ovarian, 27/576 breast, 43/759 colorectal cancers). For each gene, AYA and non-AYA DNA alteration proportions were compared (Fisher exact test) and alteration association with continuous age (logistic regression) was evaluated (false discovery rate‑adjusted
resultsNo significant AYA versus non-AYA differences were observed in the prevalence of gene mutations (single nucleotide variant [SNV]/indel). A significant association of gene amplification with AYAs (odds ratio [OR], 95% CI) was
conclusionComparing AYAs with non-AYAs among patients having relapsed/refractory disease, no significant differences in SNV/indel prevalence were observed, but
Indexed as
Breast NeoplasmsColorectal NeoplasmsNeoplasm Recurrence, LocalOvarian NeoplasmsAdolescentAdultAge FactorsFemaleGenomicsHumansMaleMutationUnited StatesYoung Adult
Identifiers
PMID42566732
PMCPMC13465699
What OpenQuestion holds
Textmetadata
Read underepoch 390