MétaCan
Menu
Back to cohort
Record W4414355411 · doi:10.3390/diseases13090307

A Comprehensive Review of the Epidemiology, Pathophysiology, Risk Factors, and Treatment Strategies for Retinoblastoma

2025· review· en· W4414355411 on OpenAlexaff
Alpana Kumari, Pankaj Kumar, K. Suresh Babu, Vivek Kumar Garg, Harpal S. Buttar, Katrin Sak, Kiran Yadav, Vikas Yadav

Bibliographic record

VenueDiseases · 2025
Typereview
Languageen
FieldMedicine
TopicOcular Oncology and Treatments
Canadian institutionsUniversity of Ottawa
FundersChandigarh University
KeywordsRetinoblastomaDiseaseGeneChromosomeBAP1Retinoblastoma proteinIdentification (biology)

Abstract

fetched live from OpenAlex

), which is located on chromosome 13q14.2, is mutated in retinoblastoma (RB), the most common malignant intraocular tumor in children. About 8000 new cases of retinoblastoma are diagnosed globally each year, accounting for approximately 1 in 17,000 live births. RB is prototypically considered hereditary by nature as thirty to forty percent of cases have autosomal dominant inheritance, and the remaining sixty to seventy percent have non-inherited sporadic inheritance. RB is the most treatable juvenile malignancy, with a high percentage of survival; nevertheless, advanced tumors restrict the amount of globe salvage and are frequently linked to high-risk histological characteristics that indicate spread. Investigating the disease's molecular causes has also helped to understand its subsequent processes, which has resulted in the identification of biomarkers and relevant targeted treatments. Additionally, advancements in molecular biology techniques facilitated the creation of effective strategies for early disease detection, genetic counseling, and prevention. In the present review, we discuss the risk factors, epidemiology, pathology, and therapeutic approaches for retinoblastoma. We specifically focus on the genetic and molecular characteristics of retinoblastoma, including mutations that cause key signaling pathways involved in the DNA repair, cellular plasticity, and cell proliferation to become dysregulated.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.002

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 head0.067
GPT teacher head0.401
Teacher spread0.335 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations9
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueDiseasesSame topicOcular Oncology and TreatmentsFrench-language works237,207