Le cancer chez l’enfant
Bibliographic record
Abstract
Resume Objectif : Presenter les cancers pediatriques les plus frequents et determiner les particularites de la prise en charge du cancer chez l’enfant comparativement a la population adulte. Decrire le role du pharmacien en hemato-oncologie pediatrique. Sources des donnees : Les donnees proviennent d’une revue de la litterature medicale parue depuis l’annee 2000, effectuee a l’aide de la base de donnees PubMed et de Google Scholar. Elles ont aussi ete extraites d’ouvrages de reference sur le sujet. Le nom des differentes pathologies decrites dans cet article ont servi de mots cles ainsi que les termes cancer, oncology, pediatric et children. Selection des etudes et extraction des donnees : Les donnees proviennent en majeure partie d’articles de revues, de lignes directrices, de protocoles de traitement et de recommandations d’experts. Analyse des donnees : Cet article decrit les huit cancers les plus frequents touchant l’enfant. Pour chacun d’eux, il indique l’incidence, la survie, les signes et symptomes, les facteurs de risques, la facon de poser le diagnostic ainsi que les modalites de traitement. Conclusion : Le cancer qui frappe l’enfant est different de celui qui affecte l’adulte. Les diagnostics, le pronostic, les objectifs de traitement, les modalites therapeutiques, la tolerance aux differentes therapies, la necessite du suivi a long terme et l’approche du patient sont tout a fait particuliers a cette population. Abstract Objective: To discuss the most common malignancies in children. To explore the management of cancer in pediatrics in contrast to the adult population. To describe the role of the pharmacist in managing pediatric patients with cancer. Data sources: Literature was accessed through PubMed and Google Scholar (January 2000 – March 2013) using the search terms cancer, oncology, pediatric, and children. Reference citations from publications identified were reviewed. Study selection and data extraction: English and French language articles were reviewed. Data were obtained from review articles, guidelines, treatment protocols and expert recommendations. Data synthesis: This article describes the eight most common malignancies affecting children, discussing incidence, diagnosis, signs and symptoms, risk factors, prognosis and treatment modalities. Conclusion: Malignancies in children are different from those affecting adults. Specific approaches are needed toward this special population in terms of long-term follow-up. Key words: Cancer, child, hematology, oncology, pediatric
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 | 0.004 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".