Sensor-Controlled Scalp Cooling to Prevent Chemotherapy-Induced Alopecia in Female Cancer Patients
Bibliographic record
Abstract
BACKGROUND: Scalp cooling has been used since the 1970s to prevent chemotherapy-induced alopecia, one of the most common and psychologically troubling side effects of chemotherapy. Currently available scalp cooling systems demonstrate varying results in terms of effectiveness and tolerability. METHODS: For the present prospective study, 55 women receiving neoadjuvant, adjuvant, or palliative chemotherapy were enrolled. The aim was to assess the effectiveness of a sensor-controlled scalp cooling system (DigniCap: Sysmex Europe GmbH, Norderstedt, Germany) to prevent chemotherapy-induced alopecia in breast or gynecologic cancer patients receiving 1 of 7 regimens. Clinical assessments, satisfaction questionnaires, and alopecia evaluations [World Health Organization (who) grading for toxicity] were completed at baseline, at each cycle, and at completion of chemotherapy. RESULTS: Of the 55 patients, 78% underwent scalp cooling until completion of chemotherapy. In multivariate analysis, younger women and those receiving paclitaxel weekly or paclitaxel-carboplatin experienced less alopecia. The compound successful outcome ("no head covering" plus "who grade 0/1") was observed in all patients 50 years of age and younger receiving 4 cycles of docetaxel-cyclophosphamide or 6 cycles of paclitaxel-carboplatin. Conversely, alopecia was experienced by all women receiving triplet polychemotherapy (6 cycles of docetaxel-doxorubicin-cyclophosphamide). For women receiving sequential polychemotherapy regimens (3 cycles of fluorouracil-epirubicin-cyclophosphamide followed by 3 cycles of docetaxel or 4 cycles of doxorubicin-cyclophosphamide followed by 4 cycles of docetaxel), the subgroup 50 years of age and younger experienced a 43% success rate compared with a 10% rate for the subgroup pf older women receiving the same regimens. CONCLUSIONS: The ability of scalp cooling to prevent chemotherapy-induced alopecia varies with the chemotherapy regimen and the age of the patient. Use of a compound endpoint with subjective and objective measures provides insightful and practical information when counselling patients.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".