Evidence map›Paper›PMID 20300634›Full record

ArticlePloS one2010

Gene expression profile for predicting survival in advanced-stage serous ovarian cancer across two independent datasets.

Kosuke Yoshihara, Atsushi Tajima, Tetsuro Yahata, Shoji Kodama, Hiroyuki Fujiwara, Mitsuaki Suzuki, Yoshitaka Onishi, Masayuki Hatae, Kazunobu Sueyoshi, Hisaya Fujiwara and 7 more

Abstract read
In one paragraph

Article in PloS one, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 83 papers, 7 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
83citing papers in PubMed, 7 pooled it
–field-weighted citation impact
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

83 citing papers in PubMed, 7 syntheses or guidelines pooled it.

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23 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

17 authors.

Kosuke YoshiharaDepartment of Obstetrics and Gynecology, Niigata University Graduate School of Medical and Dental Sciences, Niigata, Japan.
Atsushi Tajima
Tetsuro Yahata
Shoji Kodama
Hiroyuki Fujiwara
Mitsuaki Suzuki
Yoshitaka Onishi
Masayuki Hatae
Kazunobu Sueyoshi
Hisaya Fujiwara
Yoshiki Kudo
Kohei Kotera
Hideaki Masuzaki
Hironori Tashiro
Hidetaka Katabuchi
Ituro Inoue
Kenichi Tanaka

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAdvanced-stage ovarian cancer patients are generally treated with platinum/taxane-based chemotherapy after primary debulking surgery. However, there is a wide range of outcomes for individual patients. Therefore, the clinicopathological factors alone are insufficient for predicting prognosis. Our aim is to identify a progression-free survival (PFS)-related molecular profile for predicting survival of patients with advanced-stage serous ovarian cancer. METHODOLOGY/PRINCIPAL

findingsAdvanced-stage serous ovarian cancer tissues from 110 Japanese patients who underwent primary surgery and platinum/taxane-based chemotherapy were profiled using oligonucleotide microarrays. We selected 88 PFS-related genes by a univariate Cox model (p<0.01) and generated the prognostic index based on 88 PFS-related genes after adjustment of regression coefficients of the respective genes by ridge regression Cox model using 10-fold cross-validation. The prognostic index was independently associated with PFS time compared to other clinical factors in multivariate analysis [hazard ratio (HR), 3.72; 95% confidence interval (CI), 2.66-5.43; p<0.0001]. In an external dataset, multivariate analysis revealed that this prognostic index was significantly correlated with PFS time (HR, 1.54; 95% CI, 1.20-1.98; p = 0.0008). Furthermore, the correlation between the prognostic index and overall survival time was confirmed in the two independent external datasets (log rank test, p = 0.0010 and 0.0008). CONCLUSIONS/SIGNIFICANCE: The prognostic ability of our index based on the 88-gene expression profile in ridge regression Cox hazard model was shown to be independent of other clinical factors in predicting cancer prognosis across two distinct datasets. Further study will be necessary to improve predictive accuracy of the prognostic index toward clinical application for evaluation of the risk of recurrence in patients with advanced-stage serous ovarian cancer.

Indexed as

Gene Expression Regulation, NeoplasticAdultAgedAged, 80 and overDisease-Free SurvivalDisease ProgressionFemaleHumansJapanMiddle AgedOvarian NeoplasmsPlatinumPrognosisProportional Hazards ModelsTaxoidsTreatment OutcomePlatinumTaxoids

Identifiers

PMID20300634
PMCPMC2837379

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Registered trials

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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.