Breast Cancer: A Comprehensive Review from Diagnosis to Survivorship
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".