Incidence of Taxane-Induced Pain and Distress in Patients Receiving Chemotherapy for Early-Stage Breast Cancer: A Retrospective, Outcomes-Based Survey
Bibliographic record
Abstract
INTRODUCTION: With the widespread use of sequential anthracycline/taxane-based chemotherapy for early-stage breast cancer, clinicians are becoming rapidly aware of toxicities associated with those regimens. Despite the low incidence reported in the literature of significant arthralgia and myalgia with those regimens, it is clinically evident that a substantial proportion of patients develop such toxicities. We performed a pilot study to investigate the extent of this problem. PATIENTS AND METHODS: Patients who had received prior adjuvant or neoadjuvant chemotherapy [doxorubicin-cyclophosphamide followed by paclitaxel (AC-T), doxorubicin-cyclophosphamide followed by docetaxel (AC-D), or 5-fluourouracil-epirubicin-cyclophosphamide followed by docetaxel (FEC-D)] completed a retrospective outcomes-based survey. The survey utilized the Functional Assessment of Cancer Therapy-Taxane Scale, the Memorial Symptom Assessment Scale, and a modified Brief Pain Inventory. RESULTS: Interviews were conducted with 82 patients. Interviewees had received AC-T (43%), FEC-D (43%), and AC-D (14%). Pain as a side effect of either the anthracycline or the taxane chemotherapy was reported by 87% of patients. Most of the patients (79%) indicated that their worst pain occurred during the taxane component of treatment. Compared with paclitaxel, docetaxel was reported to cause more pain. Narcotics for pain management were required by 35 of 82 patients (43%). CONCLUSIONS: A significant number of patients receiving sequential anthracycline/taxane-based chemotherapy for early-stage breast cancer experience pain, particularly during the taxane component. Prospective patient-reported outcome assessments are needed to help individualize treatment interventions and to improve symptom management in this population.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".