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Record W2013191848 · doi:10.1002/pbc.23325

Natural course of low risk neuroblastoma

2011· article· en· W2013191848 on OpenAlexafffund
Somruetai Shuangshoti, Shanop Shuangshoti, Issarang Nuchprayoon, Somjai Kanjanapongkul, Paula Marrano, Meredith S. Irwin, Paul S. Thorner

Bibliographic record

VenuePediatric Blood & Cancer · 2011
Typearticle
Languageen
FieldMedicine
TopicNeuroblastoma Research and Treatments
Canadian institutionsUniversity of TorontoHospital for Sick Children
FundersHospital for Sick ChildrenChulalongkorn University
KeywordsNeuroblastomaMedicineEpidemiologyDiseaseHistologyStage (stratigraphy)Risk stratificationInternal medicinePathologyOncologyPediatricsBiologyGenetics

Abstract

fetched live from OpenAlex

BACKGROUND: Neuroblastoma is characterized by heterogeneity of histology, biology, and clinical behavior. Most epidemiology studies are based on Western and Japanese populations; there are very few studies on neuroblastoma from Southeast Asia. PROCEDURE: Cases of Thai children with neuroblastoma were retrospectively reviewed to determine if the epidemiology of the disease differs from Western populations. Sixty-two cases were assembled from two pathology centers in Bangkok. Histologic prognostic category and MYCN copy number were determined. RESULTS: The median age at diagnosis was 2.9 years. Only 11% of cases presented at less than 1 year of age and 12% cases had low stage disease (1, 2, and 4S). The majority of tumors had unfavorable histology (48/62); this was at least partly due to the higher age at diagnosis for most patients. MYCN amplification was detected in 18/52 (35%) tumors, all in stage 3 or 4 tumors. We assigned patients to high, intermediate and low risk categories using the Children's Oncology Group risk stratification criteria. In contrast to Western studies, the majority of cases (50/59 or 85%) in our series had high risk disease. CONCLUSIONS: Since there is no evidence to date that the biology of neuroblastoma varies by geographic region, the paucity of low risk cases in our study may reflect spontaneous resolution/differentiation of tumors that are not clinically detected. Moreover, a delay in diagnosis of intermediate risk cases could result in higher tumor burden at the time of diagnosis, increasing the proportion of high risk cases observed.

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 score0.049
Threshold uncertainty score0.558

Codex and Gemma teacher scores by category

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

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 head0.015
GPT teacher head0.274
Teacher spread0.258 · 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

Citations18
Published2011
Admission routes2
Has abstractyes

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