Long-term Peripheral Neuropathy in Breast Cancer Patients Treated With Adjuvant Chemotherapy: NRG Oncology/NSABP B-30
Bibliographic record
Abstract
Background: The long-term effects of chemotherapy are sparsely reported. Peripheral neuropathy (PN) is one of the most frequent toxicities associated with taxane use for the treatment of early-stage breast cancer. We investigated the impact of the three different docetaxel-based regimens and patient characteristics on long-term, patient-reported outcomes of PN and the impact of PN on long-term quality of life (QOL). Methods: The National Surgical Adjuvant Breast and Bowel Project Protocol B-30 was a randomized trial comparing sequential doxorubicin (A) and cyclophosphamide (C) followed by docetaxel (T) (AC→T), concurrent ACT, or AT in women with node-positive, early-stage breast cancer. The AC→T group had a higher cumulative dose of T. PN was one of the symptoms assessed in a QOL substudy. Statistical methods included simple and mixed ordinal logistic regression and general linear models. All statistical tests were two-sided. Results: Of 1512 patients, 41.9% reported PN two years after treatment initiation. Treatment with AT and ACT was associated with less severe long-term PN compared with AC→T (odds ratio [OR] = 0.45, 95% confidence interval [CI] = 0.35 to 0.58; OR = 0.59, 95% CI = 0.46 to 0.75). Preexisting PN, older age, obesity, mastectomy, and greater number of positive nodes were also associated with higher risk of long-term PN. Patients who reported worse PN symptoms at 24 months had statistically significantly worse QOL (Ptrend < .001). Conclusions: The administration of docetaxel is associated with long-term PN. The lower rate of long-term PN in AT and ACT patients might be an important consideration in supporting choosing these therapies for individuals with preexisting neuropathic symptoms or other risk factors for neuropathy.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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".