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Record W3186276457 · doi:10.3390/cancers13153646

Natural History of Untreated Retinoblastoma

2021· article· en· W3186276457 on OpenAlexaff
Junyang Zhao, Zhaoxun Feng, Brenda L. Gallie

Bibliographic record

VenueCancers · 2021
Typearticle
Languageen
FieldMedicine
TopicOcular Oncology and Treatments
Canadian institutionsKrembil FoundationUniversity of TorontoHospital for Sick ChildrenUniversity of Ottawa
Fundersnot available
KeywordsRetinoblastomaMedicineNatural historyPediatricsMetastasisDiseaseMedical recordAbandonment (legal)SurgeryInternal medicineCancer

Abstract

fetched live from OpenAlex

Treatment abandonment is a leading cause of death in children with retinoblastoma worldwide. We studied children who abandoned treatment upfront at diagnosis to delineate the natural history of untreated retinoblastoma. Studied were children who received no treatment, diagnosed between 2007 and 2017 at 29 Chinese centers. Data were retrospectively collected from medical chart reviews and interviews with each patient’s family. During the study period, 44 children received no treatment after diagnosis of retinoblastoma. Clinical or radiologic evidence of orbital extension was available for 25 children, and radiologic evidence of systemic metastasis was available for 12 children. Median times from diagnosis of intraocular tumor to orbital disease was 13.7 months, orbital disease to metastasis was 2.6 months, and metastasis to death was 2.0 months. Children with brain metastasis had shorter survival than those with metastasis to other sites (median 1.0 vs. 3.1 months; p = 0.015). Overall, 36% of patients died within 12 months of diagnosis, 77% within 24 months, 95% within 36 months and 100% within 48 months. While multiple factors influence refusal of treatment, insights into the natural history of retinoblastoma derived from real-world evidence can inform clinicians and parents that retinoblastoma is life-threatening and encourage urgent treatment at diagnosis.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.350
Threshold uncertainty score0.583

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)0.0000.000

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 head0.012
GPT teacher head0.263
Teacher spread0.251 · 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 designNot applicable
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

Citations24
Published2021
Admission routes1
Has abstractyes

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