Pain and Interventions in Stage IV Non-Small Cell Lung Cancer: A Province-Wide Analysis
Bibliographic record
Abstract
Pain is a common symptom in stage IV non-small cell lung cancer (NSCLC). The objective of the study was to examine the use of interventions and factors associated with interventions for pain. A population-based cohort study in Ontario, Canada was conducted with patients diagnosed with stage IV NSCLC from January 2007 to September 2018. An Edmonton Symptom Assessment System (ESAS) score of ≥4 defined moderate-to-severe pain following diagnosis. The study cohort included 13,159 patients, of which 68.5% reported at least one moderate-to-severe pain score. Most patients were assessed by a palliative care team (85.4%), and the majority received radiation therapy (73.2%). The use of nerve block was rare (0.8%). For patients ≥65 years of age who had drug coverage, 59.6% received an opiate prescription. Patients with moderate-to-severe pain were more likely to receive palliative assessment or radiation therapy compared to patients with none or mild pain. Patients aged ≥70 years and with a greater comorbidity burden were associated with less likelihood to receive radiation therapy. Patients from rural/non-major urban residence and with a greater comorbidity burden were also less likely to receive palliative care assessment. Factors associated with interventions for pain are described to inform future symptom management in this population.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".