Has the Practice of Radiation Oncology for Locally Advanced and Metastatic Non-Small-Cell Lung Cancer Changed in Canada?
Bibliographic record
Abstract
AIM: Previous surveys have revealed wide variations in the management by radiation oncologists of non-small-cell lung cancer (NSCLC) in Canada. The aim of the present study was to determine the current patterns of practice for locally advanced and metastatic NSCLC among Canadian radiation oncologists. MATERIALS AND METHODS: An online survey was distributed electronically to all members of the Canadian Association of Radiation Oncologists. Those who treat lung cancer were invited to participate. The survey consisted of three scenarios focusing on areas of nsclc treatment in which the radiotherapy (RT) regimen that provides the best therapeutic ratio is unclear. RESULTS: Replies from 41 respondents were analyzed. For an asymptomatic patient with stage IIIB NSCLC unsuitable for radical treatment, 22% recommended immediate RT, and 78% recommended RT only if the patient were to become symptomatic. Those who believed that immediate RT prolongs survival were more likely to recommend it (p = 0.028). For a patient with a bulky stage IIIB tumour and good performance status, 39% recommended palliative treatment, and 61% recommended radical treatment (84% concurrent vs. 16% sequential chemoradiation at 60-66 Gy in 30-33 fractions). Those who believed that chemoradiation has a greater impact on survival were more likely to recommend it (p < 0.001). For a symptomatic patient with stage IV NSCLC, 54% recommended external-beam RT (EBRT) alone, 41% recommended other modalities (brachytherapy, endobronchial therapy, or chemotherapy) with or without EBRT, and 5% recommended best supportive care. A majority (76%) prescribed 20 Gy in 5 fractions for EBRT. CONCLUSIONS: Compared with previous surveys, more radiation oncologists now offer radical treatment for locally advanced NSCLC. Management of nsclc in Canada may be evidence-based, but perception by radiation oncologists of the treatment's impact on survival also influences treatment decisions.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".