METRICS FOR AYA CANCER CARE IN CANADA
Bibliographic record
Abstract
Adolescents and young adults (AYAs, 15-39 years of age) with cancer face unique challenges. Efforts have been made to improve both care and outcomes for this population. Metrics to evaluate AYA cancer care efforts help to ensure that objectives and outcomes are being met. This thesis comprises 7 papers which explore system performance metrics for cancer care and control in AYAs. A scoping review introduces the topic and addresses the current state of indicator metrics for the AYA cancer population. The second paper extends this work and develops a consensus-based list of relevant indicators. The subsequent papers focus on further development of two of the identified indicators for implementation in Canada (identification of patient reported outcome measures (PROMS) for assessing distress; a referral indicator for oncofertility care). This thesis describes 14 indicators in 5 care areas. Two identified indicators were further developed to aid in implementation (“Proportion of AYA patients screened for distress with standardized AYA specific tools” and “Proportion of AYA patients who had fertility preservation discussion before treatment”). Criteria from the National Quality Forum (NQF) were used to assess commonly used PROMs for distress. It was found that although all PROMs had acceptable psychometric properties, only the “Impact of Cancer” scale of the CDS-AYA had strong content validity for AYA with cancer. For Oncofertility, the indicator “Proportion of cases attending a fertility consult visit ≤ 30 days from diagnosis of cancer” was recommended for use. Finally, factors associated with attending such a fertility consult were identified. Important factors for both men and women included: age at diagnosis, risk to fertility, year of diagnosis, treatment with radiation or chemotherapy, region of care, income and residential instability. The information presented in this thesis can be applied to national system performance initiatives to identify and implement metrics to monitor and evaluate cancer care in AYA.
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 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 | 0.016 | 0.064 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.013 | 0.027 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".