How Equitable is Access to Treatment for Lung Cancer Patients? A Population-Based Review of Treatment Practices in Ontario
Bibliographic record
Abstract
AIM: Guideline concordance is one of the metrics used by the Cancer Quality Council of Ontario and Cancer Care Ontario to assess the quality of cancer care and to drive quality improvement. MATERIALS & METHODS: The rates for lung cancer surgical resection and concordance with the Cancer Care Ontario postoperative adjuvant chemotherapy (AC) guideline were assessed by health region during two time periods (2010-2011 and 2012-2013) according to five equity measures (age, sex, neighborhood income, location of residence and size of immigrant population). RESULTS: Of the patients with stage I/II NSCLC, 52.2% to 63.0% underwent surgical resection in the province of Ontario, Canada; for patients with stage IIIA disease, the rate was 26.4%. The probability of a surgical resection decreased substantially with age; only 26.9% of those with potentially resectable (stage I-IIIA) disease over 80 years underwent surgery. The use of postoperative AC increased modestly over the time of the study but the rate of use varied widely by health region (34.6 to 84.6%). Patients in rural areas were as likely to receive AC as urban dwellers; however, older aged patients (≥65 years) and those from the lowest income neighborhoods were significantly less likely to receive AC. CONCLUSION: Surgical rates and the use of AC vary by health region in Ontario and by age and level of neighborhood income despite universal access in a publicly funded health care system. The reasons for this variance are unclear but warrant further study.Presented in part at the 15th World Conference on Lung Cancer, Sydney, Australia, 27-30 October 2013.
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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".