Chemotherapy-induced Peripheral Neuropathy Among Paediatric Oncology Patients
Bibliographic record
Abstract
BACKGROUND: Vinca alkaloids and platinum-containing chemotherapeutic drugs have the potential to cause chemotherapy-induced peripheral neuropathy (CIPN). This study determined the frequency of CIPN among children who were treated for acute lymphoblastic leukemia (ALL), lymphoma, brain tumour or Wilms tumour. PROCEDURE: This retrospective cohort study reviewed 252 patients treated at the Children's hospital of Eastern Ontario from 2001-2011. Patients were considered to have CIPN if they developed clinical symptoms of CIPN such as limb paraesthesia, weakness and/or ataxia during chemotherapy and their treating neurologist or oncologist deemed that their symptoms were due to a peripheral cause. Patients were excluded if their treatment regime did not include chemotherapy. RESULTS: The overall frequency of CIPN was 18.3% (46/252). Tumour-specific CIPN rates were: 18.9% (29/154) for ALL; 9.4% (3/32) for lymphoma; 17.9% (5/28) for Wilms tumour; and 23.7% (9/38) for brain tumour patients. Nerve conduction studies were completed for 17% of patients (all tumour types) and were abnormal in all but one patient. Among surviving CIPN patients (41/46), 93% showed no clinical deficits at their last examination, which was on average 56 months from time of diagnosis to last follow-up visit. CONCLUSIONS: The frequency of CIPN was less than that previously reported in adults receiving chemotherapy. Children with CIPN have a favourable outcome with most showing clinical improvement during the maintenance phase of treatment or after chemotherapy completion.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| 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) | 0.002 | 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".