Global Retinoblastoma Treatment Outcomes
Bibliographic record
Abstract
PURPOSE: To compare metastasis-related mortality, local treatment failure, and globe salvage after retinoblastoma in countries with different national income levels. DESIGN: International, multicenter, registry-based retrospective case series. PARTICIPANTS: Two thousand one hundred ninety patients, 18 ophthalmic oncology centers, and 13 countries on 6 continents. METHODS: Multicenter registry-based data were pooled from retinoblastoma patients enrolled between January 2001 and December 2013. Adequate data to allow American Joint Committee on Cancer staging, eighth edition, and analysis for the main outcome measures were available for 2085 patients. Each country was classified by national income level, as defined by the 2017 United Nations World Population Prospects, and included high-income countries (HICs), upper middle-income countries (UMICs), and lower middle-income countries (LMICs). Patient survival was estimated with the Kaplan-Meier method. Logistic and Cox proportional hazards regression models were used to determine associations between national income and treatment outcomes. MAIN OUTCOME MEASURES: Metastasis-related mortality and local treatment failure (defined as use of secondary enucleation or external beam radiation therapy). RESULTS: Most (60%) study patients resided in UMICs and LMICs. The global median age at diagnosis was 17.0 months and higher in UMICs (20.0 months) and LMICs (20.0 months) than HICs (14.0 months; P < 0.001). Patients in UMICs and LMICs reported higher rates of disease-specific metastasis-related mortality and local treatment failure. As compared with HICs, metastasis-related mortality was 10.3-fold higher for UMICs and 9.3-fold higher for LMICs, and the risk for local treatment failure was 2.2-fold and 1.6-fold higher, respectively (all P < 0.001). CONCLUSIONS: This international, multicenter, registry-based analysis of retinoblastoma management revealed that lower national income levels were associated with significantly higher rates of metastasis-related mortality, local treatment failure, and lower globe salvage.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".