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Record W7117543750 · doi:10.5812/gct-165824

Breast Cancer: A Comprehensive Review from Diagnosis to Survivorship

2025· article· W7117543750 on OpenAlexaff
Thuy Trang Nguyen, Hamidreza Galavi, Mohammadamin Norouzi, Ramin Saravani

Bibliographic record

VenueGene Cell and Tissue · 2025
Typearticle
Language
FieldMedicine
TopicCancer Risks and Factors
Canadian institutionsSimon Fraser UniversityUniversity of British Columbia
Fundersnot available
KeywordsSurvivorship curveBreast cancerDiseaseEpidemiologyPublic healthCancerMalignancy

Abstract

fetched live from OpenAlex

Context: Breast cancer (BC) is the most prevalent malignancy among women worldwide and represents a major public health concern. In 2020, approximately 2.3 million new cases were reported globally. Despite advances in diagnostic and therapeutic approaches, BC remains a complex disease with significant clinical and survivorship challenges. Objectives: This study aims to provide an overview of BC by summarizing its biological hallmarks, major risk factors, diagnostic approaches, treatment modalities, and the long-term needs of BC survivors. Data Sources: Relevant information was obtained from previously published scientific literature, epidemiological reports, and clinical studies addressing BC biology, diagnosis, treatment, and survivorship. Study Selection: Studies focusing on the incidence, molecular characteristics, risk factors, diagnostic methods, treatment strategies, and survivorship issues related to BC were considered. Data Extraction: Key data regarding BC hallmarks, associated risk factors, diagnostic tools, treatment options, and post-treatment needs were extracted and synthesized narratively. Results: Breast cancer is characterized by six major hallmarks, including evasion of programmed cell death, unlimited proliferative capacity, enhanced angiogenesis, resistance to growth-inhibitory signals, self-sufficiency in growth signaling, and metastatic potential. Identified risk factors include female sex, increasing age, family history, estrogen exposure, tobacco use, alcohol consumption, high-fat diet, and lifestyle factors. Diagnosis relies on physical examination, imaging techniques — particularly mammography — and tissue sampling, with image-guided core needle biopsy playing a central role. Treatment typically involves a multimodal approach combining surgery, chemotherapy (CT), radiotherapy, targeted therapy, and hormonal therapy, with more advanced disease requiring more intensive treatment. Survivors often face ongoing physical, psychological, and long-term health challenges. Conclusions: Although significant progress has been made in the diagnosis and treatment of BC, it remains a multifaceted disease requiring comprehensive management. In addition to effective therapeutic strategies, addressing the long-term physical and emotional needs of BC survivors is essential to improve overall outcomes and quality of life.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.817
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.021
GPT teacher head0.309
Teacher spread0.288 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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