Practice patterns in the diagnosis and management of chemotherapy-induced peripheral neuropathy in adolescents and young adults with cancer: a survey of oncologists
Bibliographic record
Abstract
PURPOSE: Chemotherapy-induced peripheral neuropathy (CIPN) affects > 78% of oncology patients and causes detrimental side effects. There may be practice heterogenicity in CIPN management amongst oncologists treating pediatric, adolescent young adult (AYA), and adult patients with cancer. We sought to evaluate the practice patterns of oncologists regarding their management of CIPN in AYAs with cancer. METHODS: A survey was developed and sent to pediatric and medical oncologists from across the United States. Scenarios included an 18-year-old receiving vincristine (VCR) with mild neuropathy (Scenario 1) and moderate/severe neuropathy (Scenario 2). Respondents were asked how they would manage each patient. Differences between pediatric and medical oncologists' management were assessed. RESULTS: A total of 179 responses were submitted by 132 (73.7%) pediatric, 44 (24.6%) medical oncologists, and 3 (1.6%) oncologists who care for both pediatric and adult patients. Over half of respondents for Scenario 1 would refer the patient to physical therapy (PT) (56.8%), 38.1% would prescribe a pharmacologic agent, and 27.8% would dose reduce/omit vincristine. For Scenario 2, most (81.8%) would dose reduce/omit vincristine, 69.3% would refer for PT, and 44.9% would start a pharmacologic agent. On multivariable analyses, medical oncologists were more likely to dose reduce/omit vincristine for Scenario 1 (OR, 7.68; 95% CI, 3.24-18.22) and Scenario 2 (OR, 5.52; 95% CI, 1.37-22.18, and less likely to refer to PT for Scenario 1 (OR, 0.12; 95% CI, 0.05-0.31) and Scenario 2 (OR, 0.18; 95% CI, 0.08-0.41). CONCLUSION: Our survey suggests a broad spectrum of CIPN management in AYAs with cancer. The heterogenicity in practices and significant differences between pediatric and medical oncologists underscores an urgent need to better understand the source of heterogeneity in CIPN management practices and barriers to evidence-based care delivery.
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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 | 0.005 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".