Efficacy of the DigniCap System in preventing chemotherapy‐induced alopecia in breast cancer patients is not related to patient characteristics or side effects of the device
Bibliographic record
Abstract
BACKGROUND: The DigniCap System is an effective scalp cooling device for the prevention of chemotherapy-induced alopecia in early breast cancer patients. AIM: This prospective study was designed to confirm the efficacy and tolerability of the device, to explore potential factors associated with its efficacy and to collect data on patient perceptions and satisfaction. METHODS: Between January 2016 and June 2018, 163 early breast cancer patients eligible for adjuvant chemotherapy were enrolled. Hair loss was assessed using the Dean scale, where a score of 0-2 (hair loss ≤50%) was defined as successful. RESULTS: Hair preservation was successful in 57% of patients in the overall series. The proportion was even higher (81%) in the patient subgroup treated with a paclitaxel and trastuzumab regimen. Side effects (feeling cold, headache, head heaviness, scalp and cervical pain) were mild to moderate and did not correlate with the rate of hair loss. Lifestyle, anthropometric factors and hair characteristics failed to be associated with device efficacy. CONCLUSIONS: The DigniCap System was well tolerated and found to be effective in preventing alopecia in early breast cancer patients. Our study failed to identify factors other than type of chemotherapy regimen associated with hair preservation.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".