Factors associated with referral to medical oncology (MO) and subsequent use of adjuvant chemotherapy (ACT) among patients with resected non-small cell lung cancer (NSCLC): A population-based study.
Bibliographic record
Abstract
1583 Background: ACT for NSCLC is associated with improved survival in the general population but may be underutilized. Underutilization may relate to lack of referral from surgeon to MO, MO not offering ACT, or patient declining ACT. Here we explore factors associated with referral to MO and use of ACT among patients with resected NSCLC in Ontario Canada. Methods: The Ontario Cancer Registry was used to identify all incident cases of NSCLC diagnosed in Ontario 2004-2006. We linked electronic records of treatment to identify surgery, ACT, and MO consultation. Co-morbidity was classified using the Charlson Comorbidity Index modified for administrative data. A multivariate logistic regression model was used to evaluate factors associated with referral to MO and use of ACT. Results: 3354 cases of NSCLC were resected in Ontario 2004-2006, 1830 (55%) were seen post-operatively by MO and 1032 (31%) were treated with ACT. Cases younger than 70 were more likely to have MO consultation (age 60-69 OR 1.6; 50-59 OR 2.3; 20-49 OR 2.2, p<0.001) as were cases with stage II/III (ORs 2.7 and 2.0, p<0.01) compared to stage I disease. There was substantial geographic variation in the proportion of surgical cases referred to MO (range 32-88%, p<0.001). Among cases seen by MO, patients younger than 70 were more likely to have ACT (age 60-69 OR 3.1; 50-59 OR 4.7; 20-49 OR 6.7, p<0.001) as were cases with stage II/III (ORs 2.7 and 3.0, p<0.001) compared to stage I disease. Less co-morbidity (OR 2.1, p=0.02) and shorter post-operative stay (OR 1.4, p=0.001) were also associated with use of ACT. Among cases seen by MO, there was some geographic variation (range 46-63%, p<0.001) in rates of ACT utilization. Conclusions: The upstream decision to refer to MO is associated with age and stage of disease and these factors have an even greater effect on ACT utilization once patients are seen by MO. While co-morbidity and post-operative length of stay are not associated with referral to MO, they are associated with use of ACT among cases seen by MO. There is substantial geographic variation in referral patterns to MO and less variation in ACT utilization once patients are seen by MO.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.001 | 0.001 |
| 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".