The Association of Insomnia with Febrile Neutropenia, Leucopenia, and Infection in Women Receiving Adjuvant Chemotherapy for Breast Cancer
Bibliographic record
Abstract
Background/Objectives: Insomnia is associated with immune function. This study evaluated the association between insomnia and febrile neutropenia in women treated with adjuvant chemotherapy for breast cancer. Methods: This secondary analysis used data from the Canadian Cancer Trial Group MA.21 trial, which compared three chemotherapy regimens (CEF, EC/T dose-dense, or AC/T) in 2104 women with high-risk locoregional breast cancer. A total of 1731 patients completed the EORTC QLQ-C30 questionnaire. We compared “insomnia patients” with patients considered “good sleepers” based on the sleep item of this questionnaire. The primary endpoint was the occurrence of febrile neutropenia. Secondary endpoints were the occurrences of leucopenia and infection. Chemotherapy dose reduction was added as a secondary outcome in an unplanned analysis. Results: Patients with insomnia (16.3%) had a significantly higher rate of febrile neutropenia than good sleepers (12.2%; p = 0.01). After controlling for various confounders, the contribution of insomnia in explaining febrile neutropenia remained statistically significant (OR 1.45, 95% CI 1.07–1.97, p = 0.02). Chemotherapy dose reductions were significantly more frequent in patients with insomnia (30.6%) than in good sleepers (21.8%; p < 0.0001). The relationship remained significant in the multivariate analysis (OR 1.67, 95% CI 1.30–2.15, p < 0.0001). Conclusions: In the MA21 trial, insomnia was associated with febrile neutropenia. Furthermore, chemotherapy dose reductions were more common in women with insomnia. These results suggest that the role of insomnia in potential cancer outcomes needs to be confirmed in other studies, given the possible implication of dose reductions on the prognosis of women receiving chemotherapy for breast cancer.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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 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".