Healthcare costs of cancer among children, adolescents, and young adults: A scoping review
Bibliographic record
Abstract
OBJECTIVE: To collate and critically review international evidence on the direct health system costs of children and adolescents and young adults (AYA) with cancer. METHODS: We conducted searches in PubMed, MEDLINE, CINAHL, and Scopus. Articles were limited to studies involving people aged 0-39 years at cancer diagnosis and published from 2012 to 2022. Two reviewers screened the articles and evaluated the studies using the Consolidated Health Economic Evaluation Reporting Standards checklist. The reviewers synthesized the findings using a narrative approach and presented the costs in 2022 US dollars for comparability. RESULTS: Overall, the mean healthcare costs for all cancers in the 5 years post diagnosis ranged from US$36,670 among children in Korea to US$127,946 among AYA in the USA. During the first year, the mean costs among children 0-14 years ranged from US$34,953 in Chile to over US$130,000 in Canada. These were higher than the costs for AYA, estimated at US$61,855 in Canada. At the end of life, the mean costs were estimated at over US$300,000 among children and US$235,265 among adolescents in Canada. Leukemia was the most expensive cancer type, estimated at US$50,133 in Chile, to US$152,533 among children in Canada. Overall, more than a third of the total cost is related to hospitalizations. All the included studies were of good quality. CONCLUSIONS: Healthcare costs associated with cancer are substantial among children, and AYA. More research is needed on the cost of cancer in low- and middle-income countries and harmonization of costs across countries.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".