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Record W3081065365 · doi:10.1016/j.ophtha.2020.05.050

A Multicenter, International Collaborative Study for American Joint Committee on Cancer Staging of Retinoblastoma

2020· article· en· W3081065365 on OpenAlexaff
Ankit Singh Tomar, Paul T. Finger, Brenda L. Gallie, Ashwin Mallipatna, Tero Kivelä, Chengyue Zhang, Junyang Zhao, Matthew W. Wilson, Jonathan Kim, Vikas Khetan, Suganeswari Ganesan, А.А. Yarovoy, V.А. Yarovaya, Е.S. Kotova, Yacoub A. Yousef, Kalle Nummi, Tatiana L. Ushakova, Olga V. Yugay, V. G. Polyakov, Marco A. Ramírez‐Ortiz, Elizabeth Esparza-Aguiar, Guillermo Chantada, Paula Schaiquevich, Adriana Fandiño, Jason C. Yam, Winnie Lau, Carol P. Lam, Phillipa Sharwood, Sonia Moorthy, Quah Boon Long, Vera Adobea Essuman, Lorna Renner, Jaume Català, Genoveva Correa-Llano

Bibliographic record

VenueOphthalmology · 2020
Typearticle
Languageen
FieldMedicine
TopicOcular Oncology and Treatments
Canadian institutionsHospital for Sick ChildrenPrincess Margaret Cancer Centre
FundersKræftfonden
KeywordsMedicineEnucleationCancer stagingRetinoblastomaCancerMetastasisCancer registryOncologyRetrospective cohort studyInternal medicinePathologicalSurgery

Abstract

fetched live from OpenAlex

PURPOSE: To evaluate the ability of the 8th edition of the American Joint Committee on Cancer (AJCC) Cancer Staging Manual to estimate metastatic and mortality rates for children with retinoblastoma (RB). DESIGN: International, multicenter, registry-based retrospective case series. PARTICIPANTS: A total of 2190 patients from 18 ophthalmic oncology centers from 13 countries over 6 continents. METHODS: Patient-specific data fields for RB were designed and selected by subcommittee. All patients with RB with adequate records to allow tumor staging by the AJCC criteria and follow-up for metastatic disease were studied. MAIN OUTCOME MEASURES: Metastasis-related 5- and 10-year survival data after initial tumor staging were estimated with the Kaplan-Meier method depending on AJCC clinical (cTNM) and pathological (pTNM) tumor, node, metastasis category and age, tumor laterality, and presence of heritable trait. RESULTS: Of 2190 patients, the records of 2085 patients (95.2%) with 2905 eyes were complete. The median age at diagnosis was 17.0 months. A total of 1260 patients (65.4%) had unilateral RB. Among the 2085 patients, tumor categories were cT1a in 55 (2.6%), cT1b in 168 (8.1%), cT2a in 197 (9.4%), cT2b in 812 (38.9%), cT3 in 835 (40.0%), and cT4 in 18 (0.9%). Of these, 1397 eyes in 1353 patients (48.1%) were treated with enucleation. A total of 109 patients (5.2%) developed metastases and died. The median time (n = 92) from diagnosis to metastasis was 9.50 months. The 5-year Kaplan-Meier cumulative survival estimates by clinical tumor categories were 100% for category cT1a, 98% (95% confidence interval [CI], 97-99) for cT1b and cT2a, 96% (95% CI, 95-97) for cT2b, 89% (95% CI, 88-90) for cT3 tumors, and 45% (95% CI, 31-59) for cT4 tumors. Risk of metastasis increased with increasing cT (and pT) category (P < 0.001). Cox proportional hazards regression analysis confirmed a higher risk of metastasis in category cT3 (hazard rate [HR], 8.09; 95% CI, 2.55-25.70; P < 0.001) and cT4 (HR, 48.55; 95% CI, 12.86-183.27; P < 0.001) compared with category cT1. Age, tumor laterality, and presence of heritable traits did not influence the incidence of metastatic disease. CONCLUSIONS: Multicenter, international, internet-based data sharing facilitated analysis of the 8th edition AJCC RB Staging System for metastasis-related mortality and offered a proof of concept yielding quantitative, predictive estimates per category in a large, real-life, heterogeneous patient population with RB.

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)0.006
metaresearch head score (Gemma)0.009
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 score0.021
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.009
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
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 head0.053
GPT teacher head0.385
Teacher spread0.332 · 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".

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Citations65
Published2020
Admission routes1
Has abstractno

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