ArticleOncology2016
Clinical and Emergent Biomarkers and Their Relationship to the Prognosis of Ovarian Cancer.
Article in Oncology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.
- Prognostic value of progesterone receptor expression in ovarian cancer: a meta-analysis.Oncotarget · 2017Pooled it
- Linear and non-linear proteome-wide association studies provide novel insight into venous thromboembolism.Nature communications · 2025Article
- Trefoil factor family proteins as potential diagnostic markers for mucinous invasive ovarian carcinoma.Frontiers in oncology · 2022Article
- TFF3 Expression as Stratification Marker in Borderline Epithelial Tumors of the Ovary.Pathology oncology research : POR · 2018Article
- Comprehensive Evaluation of TFF3 Promoter Hypomethylation and Molecular Biomarker Potential for Prostate Cancer Diagnosis and Prognosis.International journal of molecular sciences · 2017Article
- Trefoil factor 3 expression in epithelial ovarian cancer exerts a minor effect on clinicopathological parameters.Molecular and clinical oncology · 2016Article
Corrections and comments
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Authors and funding
8 authors at 4 institutions in 1 country.
Funding
Abstract
objectiveOvarian cancer is the most lethal gynecological malignancy, but information relevant to prognosis and outcomes remain unknown. Here, we used statistical methods to focus specifically on interactions between candidate prognostic variables. METHODS AND
resultsUnivariate, multivariate, and elastic net modeling of 42 variables were applied to a cohort of 542 ovarian cancer patients with 393 episodes of cancer recurrence/death. In univariate analyses, overexpression of TFF3, MDM2, and p53 were associated with improved recurrence-free survival. In multivariate analyses adjusted for age, histology, stage, grade, ascites, and residual disease, overexpression of PR appeared to provide a protective effect [hazard ratio for >50% of cells positive, 0.64 (95% confidence interval 0.44-0.94) compared to <1%], and TFF3 showed a nonlinear association. Importantly, we observed no interactions among variables. However, patients with tumors with moderate TFF3 expression were at a marginally increased risk of recurrence, and patients with tumors with high expression were at a similar to slightly lower risk, compared to those with tumors with no TFF3 expression.
conclusionsAlthough no interactions among variables were observed, this study provides important precedent for seeking interactions between clinical and tumor variables in future studies.
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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.