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Record W2148853193 · doi:10.1200/jco.2005.04.4602

Treatment Complications in Children Diagnosed With Neuroblastoma During a Screening Program

2006· article· en· W2148853193 on OpenAlexaffabout
Stéphane Barrette, Mark L. Bernstein, Jean‐Marie Leclerc, Martin Champagne, Yvan Samson, Josée Brossard, William G. Woods

Bibliographic record

VenueJournal of Clinical Oncology · 2006
Typearticle
Languageen
FieldMedicine
TopicNeuroblastoma Research and Treatments
Canadian institutionsMontreal Children's Hospital
FundersNational Cancer InstituteAmerican Society of Clinical Oncology
KeywordsMedicineNeuroblastomaPediatricsChemotherapySurgery

Abstract

fetched live from OpenAlex

PURPOSE: The Québec Neuroblastoma Screening Program was put in place to investigate the possibility of decreasing mortality from high-risk neuroblastoma through early screening. We assess treatment complications in the patients diagnosed during this screening program. PATIENTS AND METHODS: A total of 476,603 patients born during the screening period were eligible. Parents of 425,838 children (89%) agreed to participate in the 3-week screening, and 73% agreed to participate in the 6-month screening. Forty-five patients had neuroblastoma. We reviewed the medical and research charts for all patients diagnosed by screening. Follow-up was available from 8 to 13 years after screening. RESULTS: Forty-five patients were diagnosed by screening. All patients were treated according to the Pediatric Oncology Group recommendations of the time. All patients had surgery, and 29 patients received chemotherapy. No patient died from neuroblastoma. Eleven patients suffered complications from treatment. Two patients had life-threatening complications. CONCLUSION: In view of the lack of impact of screening programs on neuroblastoma mortality, evidence that many of the tumors detected through screening can be observed without treatment and the serious complications that may arise from therapy, we do not support neuroblastoma screening programs for children.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.090
Threshold uncertainty score0.341

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.076
GPT teacher head0.456
Teacher spread0.380 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations23
Published2006
Admission routes2
Has abstractyes

Explore more

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