Outcome of acute myeloid leukaemia in Nigeria: clinician’s perspective
Bibliographic record
Abstract
The outcome of acute myeloid leukaemia (AML) has remained a major concern even in developed countries. In resource poor countries, it is envisaged that the outcome will be far worse because of late presentations, lack of appropriate diagnostic facilities and supportive care. However, data to validate this is lacking and many of these countries lack an effective cancer registry. This study determined the clinician's perspective of the outcome of care of AML patients in Nigeria and their attitudes to the care of these patients. Structured self-administered questionnaire was used to assess the clinician's perception of outcomes of care, contributory factors and attitude to care of AML patients. Ninety-eight percent of clinicians reported that the outcome of care was suboptimal; 73.3% and 90.6% of the clinicians reported having less than 31% of AML patients surviving induction and post-induction therapies, respectively. Sixty-six-point one percent (66.1%), 50% and 62.7% of the clinicians have never used immunophenotyping, cytogenetic or molecular studies, respectively, in the management of AML patients under their care. Access to blood components other than Red cells was low; 23.3% had access to apheresis platelets and 55% to fresh frozen plasma. Forty-six percent of clinicians will either give half dose of chemotherapy or offer only supportive care. This reported early death rate is three times higher than that reported in developed countries with only 9% likely to survive the first year of induction compared to about 32.9% in Ontario. Approximately 28 units of pooled or apheresis derived platelet may be required in course of therapy but just 10% of clinicians have access to platelet apheresis. Lack of diagnostic facilities, blood components and clinicians' attitudes are contributing factors to the extremely poor outcomes of patients with AML in Nigeria.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".