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Late morbidity and mortality among survivors of neuroblastoma treated with contemporary therapy: A report from the Childhood Cancer Survivor Study.

2021· article· en· W3169225089 on OpenAlexaff
Danielle Novetsky Friedman, Pamela J. Goodman, Wendy M. Leisenring, Lisa Diller, Susan L. Cohn, Emily S. Tonorezos, Rebecca M. Howell, Susan A. Smith, Suzanne L. Wolden, Joseph Philip Neglia, Kirsten K. Ness, Todd M. Gibson, Paul C. Nathan, Leslie L. Robison, Kevin C. Oeffinger, Gregory T. Armstrong, Charles A. Sklar, Tara O. Henderson

Bibliographic record

VenueJournal of Clinical Oncology · 2021
Typearticle
Languageen
FieldMedicine
TopicNeuroblastoma Research and Treatments
Canadian institutionsHospital for Sick Children
FundersNational Institutes of Health
KeywordsMedicineHazard ratioCumulative incidenceConfidence intervalStandardized mortality ratioProportional hazards modelIncidence (geometry)Internal medicineNeuroblastomaMortality rateRisk of mortalityRadiation therapyPediatricsSurgeryDemographyCohort

Abstract

fetched live from OpenAlex

10044 Background: Survival rates for neuroblastoma vary widely based on risk group. Therapies have evolved over the past four decades to de-intensify treatment for individuals with low/intermediate risk disease and intensify therapy for those with high risk disease. Risk stratification is predicted to result in differential outcomes in late morbidity and mortality; the magnitude of these differences has not been well studied. Methods: We evaluated late mortality, subsequent malignant neoplasms (SMN) and chronic health conditions (CHC) graded according to CTCAE v4.03 among 491 5-year CCSS survivors of neuroblastoma diagnosed 1987-1999 at ≥1 year of age. Using age, stage at diagnosis, and treatment, survivors were classified into risk groups (low [n=182]; intermediate [n=70]; high [n=239]). Standardized mortality ratios (SMR) and standardized incidence ratios (SIR) of SMN were calculated using rates from NCHS and SEER, respectively. Cox regression models estimated hazard ratios (HR) and 95% confidence intervals (CI) for CHC compared to 1,029 CCSS siblings. Results: Among survivors (48% male; median age 22 years, range 7-42; median follow-up 19 years, range 5-29), 80.4% with low risk disease were treated with surgery alone, while 77.8% with high risk disease received surgery, radiation, chemotherapy ± transplant. The 15-year cumulative incidence of all-cause mortality was 9.2% (CI: 7.1-11.4), with a recurrence-related mortality of 7.3% (CI: 5.3-9.3) and SMN-related mortality of 0.3% (CI: 0-0.7). All-cause mortality was significantly higher in all risk groups: (low, SMR=5.8 [CI: 2.6-13.0]; intermediate, SMR=5.7 [CI: 1.4-23.5]; high, SMR=38.6 [CI: 27.9-53.5]). The risk of SMN was elevated among high risk survivors (SIR=25.1, CI: 16.7-37.6), but did not differ from the US population for survivors of low or intermediate risk disease. Table describes the HR of CHCs (grades 1-5 and 3-5) in survivors, by risk group, as compared with siblings, as well as categories of CHCs for which survivors were at increased risk. Conclusions: Long-term survivors of neuroblastoma have a high risk of late morbidity and mortality; risk is particularly pronounced among survivors of high risk disease. Vigilant lifelong medical surveillance will be required for this relatively young population as they age.[Table: see text]

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)0.001
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 score0.023
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.154
GPT teacher head0.453
Teacher spread0.298 · 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

Citations3
Published2021
Admission routes1
Has abstractyes

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