Health care system factors associated with receipt of treatment and treatment intent in stage III non-small cell lung cancer: A population-based study in Ontario
Bibliographic record
Abstract
• Data is lacking on the impact of health system factors on stage III NSCLC treatment, including on the highest level decisions of treatment versus no treatment, and choice of treatment intent. • We report findings from a retrospective, population-based cohort study in a large universal health system in Canada of over 7000 patients diagnosed with stage III NSCLC from 2010 to 2018. • No system factors were associated with treatment versus no treatment. • However, the likelihood of receiving curative-intent treatment amongst those treated varied between health regions after controlling for other system and patient factors. • Our study suggests possible opportunities to improve care outcomes for stage III NSCLC by addressing regional variation in cancer care. Stage III non-small cell lung cancer (NSCLC) is a heterogeneous disease, with a spectrum of anatomic extent, health status, and treatment approaches. Receipt of treatment and its intent should be independent of health system factors where care quality is optimal. We investigated the degree that modifiable health system factors are associated with receipt of treatment and treatment intent in stage III NSCLC in a large, universal health system. This was a population-based, retrospective cohort study with health administrative data from Ontario, Canada, 2010–2018 for those aged ≥ 20 years, with AJCC 7 or 8 stage III NSCLC. We explored system factors associated with NSCLC treatment: region of residence, diagnostic interval, travel distance, advanced radiation (e.g. IMRT, VMAT) and systemic therapy treatment volumes and year of treatment. The relative risk (RR) of (1) any treatment versus no treatment, and (2) palliative versus non-palliative treatment was determined, using multivariable stepwise Poisson regression models. We adjusted for patient, disease and treatment factors. We identified 7,093 people with stage III NSCLC between 2010 and 2018. There were no system factors associated with receipt of treatment versus no treatment in adjusted analysis. The major system factor associated with palliative intent was region of residence (RR: Region ranges from 0.88 to 1.67, p < 0.001). Stratifying by era (2010–2012 vs. 2013–2015 vs. 2016–2018), there was an increase in receipt of curative treatment and use of advanced radiotherapy techniques and immunotherapy over time, but regional variation of treatment intent was similar. Region of residence emerged as the major health system factor associated with treatment intent for stage III NSCLC. This variation remained, even as advances in radiotherapy and systemic therapy were adopted. Our study suggests possible opportunities to improve care outcomes by addressing unexplained regional variation in care.
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 | 0.000 | 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 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".