Clinicopathological Features and RB1 Gene Polymorphism in Sudanese Retinoblastoma Patients
Bibliographic record
Abstract
Background: Retinoblastoma is a highly aggressive eye cancer affecting infants and young children, with outcomes dependent on early diagnosis. Mortality remains high in low-resource settings. This study aimed to characterize retinoblastoma among Sudanese patients, including an analysis of clinicopathological features and the status of RB1 gene polymorphisms. Material and Methods: This is cross-sectional study included 99 Sudanese patients diagnosed with retinoblastoma in Khartoum Teaching Eye Hospital and Mecca Eye Complex. Clinicopathological features and demographic data were retrieved from patient’s medical records and histopathology Laboratory Information System (LIS). Genomic DNA was isolated from formalin fixed paraffin embedded (FFPE) retinoblastoma tissue blocks. Detection of RB 1 gene polymorphism was conducted through Polymerase Chain Reaction (PCR). BLAT search genome used to compare the results of breakpoint sequencing with a reference genomic sequence. Results: Total of 99 retinoblastoma patients were included, (53.5%) were female and (46.5%) were male, with (79.8%) having unilateral lesions and (20.2%) bilateral. Nerve invasion was present in (44.4%) of the cases. Half of patients were diagnosed at advance stage (T4) (58.6%) and at high grade were (Grade 3) (69.7%). (15%) of the cases were from Damazin state, followed by Nyala (13.1%). Conclusion: Detection of retinoblastoma in Sudanese patients often occurs at advanced stages and grades, leading to poorer clinical outcomes. Genetic testing is crucial to identify individuals predisposed to this illness, enabling early intervention and management.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".