Rates of surgery and adjuvant chemotherapy use in patients with stage IB to IIIA non-small cell lung cancer: A provincial population-based study.
Bibliographic record
Abstract
134 Background: The current standard of treatment for early-stage (IB to IIIA) non-small cell lung cancer (NSCLC) include surgery and adjuvant chemotherapy. The objective of this study is to identify rates of adherence to guideline recommended surgery and adjuvant chemotherapy treatment for early-stage NSCLC for patients living in Ontario, the most populous province of Canada. Methods: A retrospective population-based study using linked administrative data through ICES was completed that included all adult patients with a diagnosis of stage IB to IIIA NSCLC made from 2010 to 2020 in Ontario. Rates of surgery and chemotherapy completion were calculated using available OHIP (Ontario Health Insurance Plan) billing codes. Logistic multivariate regressions were completed to assess for any predictors for completion of surgery and chemotherapy. Results: A total of 24,237 eligible patients were included. By cancer staging, there were 6,495 (26.8%) stage IB, 7,156 (29.5%) stage II, and 10,586 (43.7%) stage IIIA NSCLC patients. Within 180 days of diagnosis, surgery was completed for 9,929 (41.0%) of patients, by cancer staging were 4090/6495 (63.0%), 3719/7156 (52.0%), and 2120/10586 (20.0%) for IB, II, and IIIA respectively. The median time from diagnosis to surgery was 49 days (IQR 23-77 days). Amongst patients who completed surgery, 3344/9929 (33.7%) underwent at least 1 cycle of adjuvant chemotherapy within 180 days. Having advanced age (p<0.001), high Charlson comorbidity score (p<0.001), and low income (p<0.001) are predictors for poor uptake for both chemotherapy and surgery. Being male also reduces the likelihood of undergoing surgery (p<0.001). Conclusions: In our population-based study, less than half of the patients with early-stage (IB-IIIA) NSCLC underwent surgical resection and chemotherapy. These low treatment rates are concerning and may be contributing to suboptimal outcomes. Our findings indicate that elderly individuals with multiple comorbidities and those with low incomes are at the highest risk of not receiving appropriate chemotherapy and surgery. Our data highlight the need for quality improvement strategies aimed at identifying and enhancing treatment uptake within this patient population.
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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) | 0.000 | 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".