Retrospective Evaluation of the Analgesic Effects of Molecular Target Agents Against Cancer Pain and Oxaliplatin-Induced Chronic Peripheral Neuropathy
Bibliographic record
Abstract
Epidermal growth factor receptor (EGFR) has received significant attention for its therapeutic potential for pain relief. The relief of neuropathic pain after treatment with anti-EGFR antibodies or tyrosine kinase inhibitors has been previously described. However, few reports have investigated the association of cancer-related nociceptive pain or chronic chemical induced peripheral neuropathy with the analgesic effects of EGFR inhibition. Therefore, we conducted a retrospective survey of 191 patients with colorectal cancer receiving chemotherapy plus molecular targeting drugs to examine the analgesic effects of anti-EGFR antibodies against either cancer pain or oxaliplatin-induced peripheral neuropathy. We identified a significant difference in the improvement rates of nociceptive pain between panitumumab- and bevacizumab-treated patients (100% vs. 9.1%; p < 0.01), but not oxaliplatin-induced peripheral neuropathy. In conclusion, panitumumab may be effective at reducing cancer-related nociceptive pain.
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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".