The STAMPEDE2 trial: A site survey of current patterns of care, access to imaging, and treatment of metastatic prostrate cancer in Nigeria.
Bibliographic record
Abstract
e23059 Background: The STAMPEDE2 trial builds on the foundational STAMPEDE trial, which introduced innovative multi-arm treatment protocols for metastatic prostate cancer. This survey assessed Nigeria’s readiness for the STAMPEDE2 trial by evaluating current clinical practices, radiotherapy infrastructure, systemic therapy usage, and imaging capabilities across its six geopolitical zones. Methods: We mapped the radiotherapy centres and machines currently available (commissioned) and in the pipeline in Nigeria. A structured questionnaire comprising 31 questions in six sections was disseminated to clinical oncologists via Google Forms. The survey ran from July to September 2024, gathering data on radiotherapy availability, systemic therapies, advanced imaging, and readiness for clinical trial participation. Descriptive statistical analysis was conducted using Microsoft Excel. Responses were aggregated from 14 cancer centres across Nigeria, encompassing public and private facilities. Results: The survey identified 23 operational radiotherapy machines distributed across 12 centres, with 19 additional facilities in the pipeline. These centres were predominantly located in urban areas such as Lagos and Abuja. Prostate cancer treatment modalities are available; however, access to novel agents such as abiraterone and enzalutamide was reported in 73% of centres. There is one operational PET/CT facility in Nigeria. Clinicians expressed strong interest in participating in trials, though some gaps in infrastructure, particularly in rural areas, and limited access to advanced treatments like 177Lu-PSMA-617 were noted. Conclusions: The findings underscore Nigeria’s potential readiness for the STAMPEDE2 trial, as well as other clinical trials and collaborative research, bolstered by an expanding radiotherapy infrastructure and clinician enthusiasm for advanced therapeutic approaches. Initiatives like the Cancer Health Fund (CHF) and the National Cancer Access Partnership (NCAP) represent significant steps towards equitable cancer care.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".