Evidence map›Paper›PMID 39518051›Full record

ArticleCancers2024

Serous Ovarian Carcinoma: Detailed Analysis of Clinico-Pathological Characteristics as Prognostic Factors.

Lamia Sabry Aboelnasr, Hannah Meehan, Srdjan Saso, Ernesto Yagüe, Mona El-Bahrawy

Abstract read
In one paragraph

Article in Cancers, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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.

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

5 authors.

Lamia Sabry AboelnasrDepartment of Metabolism, Digestion and Reproduction, Imperial College London, London W12 0NN, UK.ORCID 0000-0003-2887-6410
Hannah MeehanImperial College NHS Healthcare Trust, London W12 0NN, UK.
Srdjan SasoDepartment of Metabolism, Digestion and Reproduction, Imperial College London, London W12 0NN, UK.
Ernesto YagüeDivision of Cancer, Imperial College London, London W12 0NN, UK.
Mona El-BahrawyDepartment of Metabolism, Digestion and Reproduction, Imperial College London, London W12 0NN, UK.ORCID 0000-0002-3414-9618

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND/

objectivesSerous ovarian carcinoma (SOC) is the most common subtype of epithelial ovarian cancer, with high-grade (HGSOC) and low-grade (LGSOC) subtypes presenting distinct clinical behaviours. This study aimed to evaluate histopathologic features in SOC, correlating these with prognostic outcomes, and explore the potential clinical implications.

methodsWe analysed 51 SOC cases for lymphovascular space invasion (LVSI), tumour border configuration (TBC), microvessel density (MVD), tumour budding (TB), the tumour-stroma ratio (TSR), the stromal type, tumour-infiltrating lymphocytes (TILs), and tertiary lymphoid structures (TLSs). A validation cohort of 54 SOC cases from The Cancer Genome Atlas (TCGA) was used for comparison.

resultsIn the discovery set, significant predictors of aggressive behaviour included LVSI, high MVD, high TB, and low TILs. These findings were validated in the validation set where the absence of TLSs, lower peritumoural TILs, immature stromal type, and low TSR were associated with worse survival outcomes. The stromal type was identified as an independent prognostic predictor in SOC across both datasets. Inter-observer variability analysis demonstrated substantial to almost perfect agreement for these features, ensuring the reproducibility of the findings.

conclusionsThe histopathological evaluation of immune and stromal features, such as TILs, TLSs, TB, TSR, and stromal type, provides critical prognostic information for SOC. Incorporating these markers into routine pathological assessments could enhance risk stratification and guide treatment, offering practical utility, particularly in low-resource settings when molecular testing is not feasible.

Indexed as

histopathological parametersmetastaticprognostic factorsserous ovarian carcinomatumour microenvironment

Identifiers

PMID39518051
PMCPMC11545192

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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.