Treatment abandonment: A report from the collaborative African network for childhood cancer care and research—CANCaRe Africa
Bibliographic record
Abstract
BACKGROUND: 'Treatmentabandonment' is a common and preventable cause of childhood cancer treatment failure in low- and middle-income countries (LMIC). Risk factors and effective interventions in LMIC are reported. Poverty and costs of treatment are perceived as overriding causes in sub-Saharan Africa. The objective of this study was to study potential determinants of treatment abandonment, including aspects of treatment costs in sub-Saharan Africa, to be better informed for planned future interventions. METHODS: A multicentre, prospective, observational, cohort study was conducted in five hospitals in sub-Saharan Africa. Children younger than 16 years with newly diagnosed cancer treated as inpatient with curative intent were included. The occurrence of treatment abandonment and potential determinants including aspects of treatment costs were documented during the first 3 months of treatment. RESULTS: We included 252 patients (median age 6.0, range 0.2-15.0 years, 54% male). The most common cancer was Burkitt lymphoma (63/252, 25%). Seven percent of patients (18 of 252) abandoned treatment. Two thirds (65%, 163/252) of patients had to borrow money to reach the hospital for the diagnosis and start of treatment. Treatment abandonment occurred more frequently in families who had to borrow money (16/163, 10%) versus those who did not (2/89, 2%; p = .026). CONCLUSIONS: Limiting costs for families and improved counselling may reduce treatment abandonment. Development and implementation of interventions to reduce treatment abandonment are required in sub-Saharan Africa.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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) | 0.000 | 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 teacher head, 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".