Hair loss: alopecia fears and realities for survivors of breast cancer—a narrative review
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: Breast cancer is the leading cause of cancer among women, with over 2.3 million women being diagnosed in 2022. In addition to the emotional and physical toll that comes with a new cancer diagnosis, treatments such as chemotherapies, endocrine therapies, and radiation therapies may cause undesirable side effects. Side effects from cancer treatments can be detrimental to the quality of life of patients and their support systems. This narrative review consolidates current research on the impacts of alopecia on breast cancer survivors and provides a comprehensive overview of the various preventative options and treatments available. METHODS: Current literature on alopecia and breast cancer was searched using PubMed and Google Scholar. The search strategy utilized a combination of keywords related to breast cancer, alopecia, body image, and alopecia prevention and treatment. Retrievable and English articles from January 2000 to April 2024 were included in the review. KEY CONTENT AND FINDINGS: Women with breast cancer cited alopecia, or hair loss, as the third-most undesirable side effect from chemotherapy, only trailing behind nausea and vomiting. Other studies have further supported this notion, expressing that alopecia negatively impacts patients' body image, social functioning, and sense of self. Further research has indicated that alopecia could hinder individuals from accessing essential cancer therapies. Breast cancer patients use a variety of coping strategies for cancer treatment-induced alopecia, including preventive measures, treatments to accelerate hair regrowth, camouflaging tools, and psychosocial supports. CONCLUSIONS: Alopecia, as a result of cancer treatment, has many significant and distressing effects on breast cancer patients. Customized interventions may help breast cancer patients feel more comfortable about themselves, after experiencing chemotherapy-induced alopecia. These findings indicate the need for further research on preventative options and treatments for cancer treatment-induced alopecia.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".