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Record W2051901634 · doi:10.1158/1538-7445.am2013-2532

Abstract 2532: Pediatric osteosarcoma patients are taller than average from birth to age twelve: a report from the Children's Oncology Group.

2013· article· en· W2051901634 on OpenAlexaffabout
Logan G. Spector, Kathryn Ritter, Ellen W. Demerath, Charles A. Sklar, Julie A. Ross, Mark Krailo, Rajaram Nagarajan, David Malkin, Tracy L. Bergemann, Sharon A. Savage, William L. Johnson

Bibliographic record

VenueCancer Research · 2013
Typearticle
Languageen
FieldMedicine
TopicSarcoma Diagnosis and Treatment
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsMedicinePercentileOsteosarcomaPediatricsPopulationIncidence (geometry)AnthropometryDemographyInternal medicinePathology

Abstract

fetched live from OpenAlex

Abstract Osteosarcoma (OS) is the most common form of bone cancer in children and displays a peak incidence that coincides with the pubertal growth spurt. Consequently a number of studies have investigated whether cases are taller at diagnosis than the general pediatric population; a recent analysis which pooled seven such studies found that cases were disproportionately in the 51st-89th and especially the >90th percentiles of height-for-age (HFA). However, no study to our knowledge has examined whether OS patients exhibit greater HFA at earlier ages. During 2008-2010 we enrolled 290 OS cases <20 years of age diagnosed at Children's Oncology Group institutions in the United States and Canada in a genetic epidemiologic study. In addition to collecting buccal cell samples for genetic analysis we requested permission to obtain length/height data from medical records from birth to diagnosis. Records were obtained for 153 male and 111 female participants. Anthropometrics and date of measurement were doubly entered into a custom database, and inconsistencies were resolved by a third abstraction. Between 1 and 46 measurements (median = 11) were recorded up to the earlier of diagnosis or 12 years of age. Mixed effects cubic spline models were applied to length/height to produce individual growth curves using Stata. Sex was included as a main effect and as interactions with the model slope terms to account for gender differences in growth. Individual estimates of length/height at every three months of age between birth and age two years, and at each year of age thereafter, were computed and transformed to Z-scores according to the CDC 2000 reference. OS cases of both sexes were consistently longer or taller than reference data at all ages, as at no age did the 95% confidence interval around mean Z-score include 0 (i.e. the population mean and median). Under 2 years of age length was examined; mean Z-score at birth was 0.56 (71st %ile), rose to 0.72 (76th %ile) at 0.5 years, and fell to 0.31 (62nd %ile) at 2 years. Over 2 years of age height was examined; mean Z-score was 0.48 (68th %ile) at 4 years, dipped to 0.33 (63rd %ile) at 8-9 years, and rose to 0.49 (69th %ile) at 12 years. No differences in mean Z-score at each age were observed by age at diagnosis (sex specific inter-quartile range of age at diagnosis vs. other), location of tumor (long bone of the lower limb vs. other), or race (White non-Hispanic vs. other). Our data clearly indicate that pediatric OS patients are substantially longer/taller than the United States national norm at all ages before puberty. Citation Format: Logan G. Spector, Kathryn Ritter, Ellen W. Demerath, Charles Sklar, Julie A. Ross, Mark Krailo, Rajaram Nagarajan, David Malkin, Tracy L. Bergemann, Sharon A. Savage, William Johnson. Pediatric osteosarcoma patients are taller than average from birth to age twelve: a report from the Children's Oncology Group. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 2532. doi:10.1158/1538-7445.AM2013-2532

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.024
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.050
GPT teacher head0.364
Teacher spread0.314 · 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 source (direct Gemma or distilled Codex), 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

Citations2
Published2013
Admission routes2
Has abstractyes

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