Prospective cohort study of chemotherapy-induced alopecia with or without scalp cooling.
Bibliographic record
Abstract
9138 Background: Scalp cooling can prevent chemotherapy-induced alopecia. Success varies according to the type of chemotherapy. A controversy exists regarding the use of scalp cooling because of the lack of efficacy data with modern chemotherapy regimen and safety data. We present a prospective cohort study design to measure alopecia. Methods: The prospective study was conducted at the Centre des Maladies du Sein Deschênes-Fabia (CMS) in Quebec City (where scalp cooling is offered routinely and 85% of women use it) and at the Centre Hospitalier Universitaire de Montreal (CHUM), in Montreal (where scalp cooling is not available). Women were eligible if they were going to receive neoadjuvant or adjuvant chemotherapy for breast cancer. The study involved completion of questionnaires (on degree of alopecia, hair type, hair care, use of head accessories, tolerance to scalp cooling and questions related to sick leave from work) and having pictures taken at baseline, cycle 3 and at the last cycle of chemotherapy. For the last 43 patients, the EORTC QLQ-C30/BR23 and an adaptation for Hairdex were added. Results: A total of 136 patients were recruited (110 at CMS over 2 years and 26 at the CHUM over a 9-month period). Preliminary efficacy results are shown in the Table (data on quality of life have not yet been analyzed). Hair preservation was defined as a SUCCESS for hair loss (since the beginning of chemotherapy) characterized as “not at all”, “a little” or “moderate” and “FAILURE” when characterized as “a lot” or “all” or “hair shaved”. Overall, in the scalp cooling group, 34% were considered a “success” using hairdresser evaluation and 49% using patient evaluation; for the non scalp-cooling group, these rates were 9% and 4% respectively. Conclusions: Scalp cooling appears to be efficacious for preventing chemotherapy-induced alopecia in this exploratory cohort study. [Table: see text]
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".