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Outcomes of patients with bilateral retinoblastoma: A report from the RIVERBOAT Consortium.

2022· article· en· W4286294233 on OpenAlexaff
Debra L. Friedman, Emma Schremp, Tatsuki Koyama, Lili Sun, Lori Ann F. Kehler, Anthony B. Daniels, Robert J. Hayashi, Amish C. Shah, Helen Dimaras, Rajaram Nagarajan, Mary Lou Schmidt, Murali Chintagumpala, Cynthia E. Herzog, Sandra Luna‐Fineman, Claire Elyse Fraley, Joanna Weinstein, Thomas A. Olson, Bruce Crooks, Cindy L. Schwartz, Joseph Philip Neglia

Bibliographic record

VenueJournal of Clinical Oncology · 2022
Typearticle
Languageen
FieldMedicine
TopicOcular Oncology and Treatments
Canadian institutionsIzaak Walton Killam Health CentreHospital for Sick Children
FundersNational Institutes of Health
KeywordsMedicineEnucleationRetinoblastomaVisual acuityPediatricsSurgery

Abstract

fetched live from OpenAlex

10045 Background: Retinoblastoma (RB) is the most common tumor of the eye in childhood. Intraocular RB cure rates approach 100%. Therefore, treatment advances have focused on globe salvage preserving functional vision. The Research Into Visual Endpoints and RB Health Outcomes After Treatment (RIVERBOAT) consortium was established to examine patient health outcomes, including vision, in the contemporary therapy era. Methods: Patients with RB treated at consortium centers from 2007 to the present were identified. Medical record abstraction was performed for disease presentation, treatment, and outcomes. A subset of the patients returned to centers and completed functional vision questionnaires (Child Vision Function Questionnaire for ages 0 – 7 and Cardiff Visual Ability Questionnaire for Children for ages >8) and had visual acuity assessed. For participants who could not yet return for a study evaluation, medical record abstraction alone was performed. Results: Among 463 participants enrolled to date, 193 (42%) had bilateral disease. Two each had metastatic RB, trilateral RB, and secondary osteosarcoma. One patient each with metastatic RB and trilateral RB is deceased, with overall survival for the cohort of 99%. The eye group distribution (International Intraocular Retinoblastoma Classification) was 14% A, 22% B, 14% C, 28% D, 19% E and 3% not classified. Primary enucleation was performed in 43 (22%), secondary enucleation in 48 (25%) and bilateral enucleation in 1(0.5%). Intravenous chemotherapy (IV) alone was administered in 58%, intra-arterial chemotherapy (IAC) alone in 4%, with 31% receiving both. Among 145 patients who did not require secondary or bilateral enucleation, the distribution was 16% A, 21% B, 16% C, 28% D, 15% E, and 4% non-classified eyes. This salvage was achieved with IV alone, IAC alone, or both in 55%, 5% and 30% respectively and with ophthalmic therapy only in 10%. The mean percentage of patients receiving IAC per year increased from 6% in 2008 – 2013 to 11% in 2014 – 2022 and was stable at 11% in 2018 – 2022. Among 53 patients who have reported functional vision to date, the mean scores were 0.81 for < 3 years 0.80 for 3-7 years and -1.31 for those >8 years, all considered to be good functional vision. Among 50 eyes in 37 of these 53 patients, 33 had normal vision (20/20-20/40) across A to E groups. Moderate vision loss (> 20/40 – 20/70) was noted in 1 C and 1 B eye and low vision (> 20/70 - < 20/200) in 6 group B, C or D eyes. Nine B or D eyes were legally blind (>20/200). No patients had two legally blind eyes. Conclusions: In this cohort of RB patients with bilateral disease treated between 2007 and 2022, 52% have been successfully treated without enucleation. Self-reported functional vision in 53 of these patients with all group eyes was good. Only 6 of 50 eyes in 37 patients met criteria for legal blindness and 66% of eyes had normal vision. With cohort accrual ongoing, we will determine if these promising outcomes continue.

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)0.003
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 score0.051
Threshold uncertainty score0.101

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.055
GPT teacher head0.408
Teacher spread0.353 · 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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Citations0
Published2022
Admission routes1
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