Incidence and geographic distribution of retinoblastoma in Ethiopia
Bibliographic record
Abstract
INTRODUCTION: Retinoblastoma is the most frequent intraocular malignancy of the eye in children, occurring in early childhood. Based on global estimates, Ethiopia is expected to observe over 200 new retinoblastoma cases per year, however without a cancer registry, this number is difficult to confirm. Therefore, the goal of the study was to determine the incidence and geographic distribution of retinoblastoma in Ethiopia. METHODS: A retrospective medical chart review of clinically diagnosed new retinoblastoma patients between January 1, 2017 - December 31, 2020, in four public Ethiopian tertiary hospitals was performed. The incidence of retinoblastoma was calculated by a birth-cohort analysis. RESULTS: There were 221 retinoblastoma patients observed in the study period. The incidence of retinoblastoma was found to be 1 in 52,156 live births. Incidence varied among different regions of Ethiopia. CONCLUSION: The incidence of retinoblastoma observed in this study is likely an underestimate. It is possible that patients were undercounted because they were seen outside of the 4 main retinoblastoma treatment facilities included in this facility, or they experienced barriers to accessing care. Our study suggests a need for a nationwide retinoblastoma registry and more retinoblastoma treatment centers in the country.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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 | 0.000 |
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.
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".