CLRD-02 PRIMARY CENTRAL NERVOUS TUMORS: CLINICAL EXPERIENCE IN THE SINGLE RADIOTHERAPY UNIT IN THE DRCONGO
Bibliographic record
Abstract
Abstract Introduction Primary and metastatic brain tumor are leading cause of cancer-related mortality and morbidity, and the primary indication for CNS radiotherapy. In Low-, Middle- Income Countries (LMICs), the limited access to advanced diagnostic technologies and comprehensive care exacerbates the morbidity and mortality rate. This study assesses the pattern of patients treated for primary brain tumors the last two years. Methodology The REB approved retrospective study included 18 primary brain tumors cancer patients referred to the radiotherapy Unit of Nganda Center Hospital in the DRCongo, for adjuvant or definitive radiotherapy from June 2022 to December 2024. Clinical information was collected from the archive. Results The patients’age ranged from 6 to 73 years old, the prevalence is equally divided between male and female patients (56 vs 44 %), the majority had access to MRI imaging before treatment (94.44%) with the mean volume of 113.14±64.37 cc. The WHO grade IV&III gliomas (group 1) represented 61.6%, median follow up time 317.5 days (265.00-458.00 days) while the WHO grade I&II gliomas and meningioma (group 2) 38.4%, median follow up time 396 days (342.00-1518.00 days). Seventeen (94%) patients underwent primary treatment with subtotal resection of the disease and radiotherapy given as adjuvant treatment for 83.3 %. The median dose to the PTV for the group 1 was 59Gy (46.00-60.00) and for the second group 54Gy (54.00-54.00). The mean duration of radiotherapy was 43.27±16.79 days (95% CI of the Mean, 33.97-52.57) and the mean progression free survival for the group 1 was 12.17 months (SE 2.99, 95% CI of the Mean 6.31-18.03). Conclusion This retrospective study highlights the need for early diagnosis of the brain tumors and the feasibility and fundamental role of adjuvant radiotherapy for local control in the setting of advanced brain tumors where surgery could not achieve a maximal safe resection.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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; 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".