Evidence map›Paper›PMID 11714444›Full record

ArticleJapanese journal of cancer research : Gann2001

Association of allelic losses at 3p25.1, 13q12, or 17p13.3 with poor prognosis in breast cancers with lymph node metastasis.

S Haga, M Emi, A Hirano, Y Utada, T Kajiwara, F Akiyama, G Sakamoto, K Takahashi, T Tada, F Kasumi and 2 more

Open access · bronzeAbstract read
In one paragraph

Article in Japanese journal of cancer research : Gann, 2001. 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
0.2field-weighted citation impact, top 47% 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

0 citing papers in PubMed, 4 citations in OpenAlex.

No citing paper in PubMed yet.

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 4 institutions in 1 country.

S HagaDepartment of Molecular Biology, Institute of Gerontology, Nippon Medical School, Nakahara-ku, Kawasaki 211-8533.
M Emi
A Hirano
Y Utada
T Kajiwara
F Akiyama
G Sakamoto
K Takahashi
T Tada
F Kasumi
Y Miki
Y Nakamura
The Cancer Institute Hospital · JPTokyo Women's Medical University Hospital · JPNippon Medical School · JPTokyo University of Science · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To identify specific allelic losses that might correlate with postoperative mortality of patients with node-positive breast carcinomas, we examined tumors from a cohort of 263 such patients, who were followed clinically for 5 years postoperatively, for allelic losses among 18 microsatellite markers. Patients whose tumors had lost an allele at 3p25.1, 13q12, or 17p13.3 had significantly higher risks of mortality than those whose tumors retained both alleles at those loci. At 3p25.1, the 5-year mortality rate was 33.8% among patients with losses vs. 16.8% with retention (P = 0.0154); at 13q12, 30.3% vs. 13.0% (P = 0.0241); and at 17p13.3, 30.4% vs. 16.2% (P = 0.0243). Combined losses at 3p25.1 and 17p13.3 increased the predicted postoperative mortality risk by a factor of 4.9 (5-year mortality rate of 38.2% vs. 8.0%, P = 0.0006), and combined losses at 3p25.1 and 13q12 raised the predicted postoperative mortality risks by a factor of 2.9 (34.7% vs. 12.7%, P = 0.0441). These data indicate that loss of heterozygosity (LOH) at any one or a pair of loci at 3p25.1, 13q12, or 17p13.3 is a significant predictor of postoperative mortality for breast-cancer patients.

Indexed as

AdultAgedBreast NeoplasmsChromosomes, Human, Pair 13Chromosomes, Human, Pair 17Chromosomes, Human, Pair 3FemaleHumansLoss of HeterozygosityLymphatic MetastasisMicrosatellite RepeatsMiddle AgedMultivariate AnalysisNeoplasm InvasivenessPrognosisSurvival Rate

Identifiers

PMID11714444
PMCPMC5926661
OpenAlexW2027730931

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.