Evidence map›Paper›PMID 39359789›Full record

ReviewAnnals of medicine and surgery (2012)2024

Predictive models and biomarkers for survival in stage III breast cancer: a review of clinical applications and future directions.

Emmanuel Ifeanyi Obeagu, Getrude Uzoma Obeagu

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Annals of medicine and surgery (2012), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
–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

17 citing papers in PubMed.

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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

2 authors.

Emmanuel Ifeanyi ObeaguDepartment of Medical Laboratory Science, Kampala International University.ORCID https://orcid.org/0000-0002-4538-0161
Getrude Uzoma ObeaguSchool of Nursing Science, Kampala International University, Ishaka, Uganda.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Stage III breast cancer, characterized by locally advanced tumors and potential regional lymph node involvement, presents a formidable challenge to both patients and healthcare professionals. Accurate prediction of survival outcomes is crucial for guiding treatment decisions and optimizing patient care. This publication explores the potential clinical utility of predictive tools, encompassing genetic markers, imaging techniques, and clinical parameters, to improve survival outcome predictions in stage III breast cancer. Multimodal approaches, integrating these tools, hold the promise of delivering more precise and personalized predictions. Despite the inherent challenges, such as data standardization and genetic heterogeneity, the future offers opportunities for refinement, driven by precision medicine, artificial intelligence, and global collaboration. The goal is to empower healthcare providers to make informed treatment decisions, ultimately leading to improved survival outcomes and a brighter horizon for individuals facing this challenging disease.

Indexed as

biomarkersbreast cancercancerclinical parametersgenetic markers

Identifiers

PMID39359789
PMCPMC11444610

What OpenQuestion holds

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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.