The effect of trastuzumab on taxane-induced peripheral neuropathy in women with breast cancer: a population-based cohort study
Bibliographic record
Abstract
Abstract Background: Recent pre-clinical evidence suggests a protective role of trastuzumab following nerve injury. Therefore, a population-based database study was utilized to examine whether trastuzumab can prevent taxane-induced peripheral neuropathy (TIPN). Methods: We performed a population-based retrospective cohort study to evaluate the neuroprotective effect of trastuzumab. The population-level cohort for this study included all incident cases of breast cancer diagnosed in Ontario from January 1, 2007-December 31, 2017 in patients aged ≥ 66 years who received taxane (paclitaxel or docetaxel) chemotherapy. There were no restrictions on specific paclitaxel or docetaxel regimens. Two years of follow-up data were available for all patients. The primary outcome was incident neuropathic pain which was measured by the number of new prescriptions commonly used as first-line treatments for neuropathic pain. The secondary outcome was healthcare utilization related to peripheral neuropathy. Healthcare utilization was characterized as outpatient visits, emergency department visits, and hospitalizations.Results: We included 3905 patients (> 66 years old) with stage I-III breast cancer treated with taxane-containing chemotherapy (paclitaxel/docetaxel) regimens between 2007-2017. 74% patients received taxane-based chemotherapy alone, while 26% received taxane-based chemotherapy plus trastuzumab. Only 4% of patients received treatment for TIPN for more than 6 months. The incidence of neuropathic pain medication prescription was lower in the paclitaxel plus trastuzumab group when compared to the paclitaxel only group (15.1% vs 20.5%, p=0.026). There was no difference in the proportion of patients who needed emergency department visits, hospitalizations, or outpatient visits for neuropathy symptoms between the two groups.Conclusions: These findings provide a real-world estimate of clinically significant TIPN and evidence of a small protective effect conferred by trastuzumab against these symptoms.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".