Socio-economic Status Plays Important Roles in Childhood Cancer Treatment Outcome in Indonesia
Bibliographic record
Abstract
BACKGROUND: The influence of parental socio-economic status on childhood cancer treatment outcome in low-income countries has not been sufficiently investigated. Our study examined this influence and explored parental experiences during cancer treatment of their children in an Indonesian academic hospital. MATERIALS AND METHODS: Medical charts of 145 children diagnosed with cancer between 1999 and 2009 were reviewed retrospectively. From October 2011 until January 2012, 40 caretakers were interviewed using semi-structured questionnaires. RESULTS: Of all patients, 48% abandoned treatment, 34% experienced death, 9% had progressive/ relapsed disease, and 9% overall event-free survival. Prosperous patients had better treatment outcome than poor patients (P<0.0001). Odds-ratio for treatment abandonment was 3.3 (95%CI: 1.4-8.1, p=0.006) for poor versus prosperous patients. Parents often believed that their child's health was beyond doctor control and determined by luck, fate or God (55%). Causes of cancer were thought to be destiny (35%) or God's punishment (23%). Alternative treatment could (18%) or might (50%) cure cancer. Most parents (95%) would like more information about cancer and treatment. More contact with doctors was desired (98%). Income decreased during treatment (55%). Parents lost employment (48% fathers, 10% mothers), most of whom stated this loss was caused by their child's cancer (84% fathers, 100% mothers). Loss of income led to financial difficulties (63%) and debts (55%). CONCLUSIONS: Treatment abandonment was most important reason for treatment failure. Treatment outcome was determined by parental socio-economic status. Childhood cancer survival could improve if financial constraints and provision of information and guidance are better addressed.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".