Delays in diagnosis and treatment among children and adolescents with cancer in Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Few studies have investigated delays in diagnosis and treatment among children and adolescents with cancer, especially from the perspective of an entire country. Detailed understanding of delays along the continuum of cancer patient care is important in order to establish appropriate benchmarks for timely oncological care. Our objective was to characterise the different components of delay in 2,896 Canadian children and adolescents (aged 0-19 years) with cancer that were enrolled in the Treatment and Outcome Surveillance component of the Canadian Childhood Cancer Surveillance and Control Program from 1995 to 2000. PROCEDURE: We examined median and standardised means concerning the distribution of delay times across categories of pertinent variables and over time. The word "delay" was used simply to represent a time interval, measured in days, without implying whether this interval exceeded a particular threshold of clinical acceptability. RESULTS: The median times (and inter-quartile ranges) for patient, diagnosis and healthcare system delays for all cancers were 9 (1-31), 30 (13-69) and 12 (4-35) days, respectively. The median total delay was 34 (16-76) days. CONCLUSIONS: Patient and referral delays were the longest time segments influencing timely diagnosis. Differences in delays were observed across age groups, cancer types and geographical regions. There was a significant trend for decreasing delays to diagnosis and treatment.
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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 | 0.000 |
| Science and technology studies | 0.000 | 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 it