Wait times in the management of non–small cell lung carcinoma before, during and after regionalization of lung cancer care: a high-resolution analysis
Bibliographic record
Abstract
Background: Timeliness can have a substantial effect on treatment outcomes, prognosis and quality of life for patients with lung cancer. We sought to evaluate changes in wait times for patients with non-small cell lung carcinoma (NSCLC) and to identify bottlenecks in cancer care. Methods: We included patients who received treatment with curative intent or palliative treatment for NSCLC, diagnosed through mediastinal staging by a thoracic surgeon. Data were collected from 3 cohorts over 3 time periods: before the regionalization of lung cancer care (2005-2007, C1), immediately postregionalization (2011-2013, C2) and 5 years after regionalization (2016-2017, C3). Total wait time and delays along treatment pathways were compared across cohorts using multivariate Cox proportionality models. Results: Our total sample size was 299 patients. Overall, there was no significant difference in total wait time among the 3 cohorts. However, wait time from symptom onset to first physician visit significantly increased in C3 compared with C2 (hazard ratio [HR] 0.41, p < 0.01) and C1 (HR 0.43, p < 0.01). Time from first physician visit to computed tomography (CT) scan significantly decreased in C3 compared with C2 (HR 1.54, p < 0.01). Time from abnormal CT scan to first surgeon visit also significantly decreased in C2 (HR 1.43, p < 0.01) and C3 (HR 4.47, p < 0.01) compared with C1, and between C3 and C2 (HR 2.67, p < 0.01). In contrast, time from first surgeon visit to completion of staging significantly increased in C2 (HR 0.36, p < 0.01) and C3 (HR 0.24, p < 0.01) compared with C1, as well as between C3 and C2 (HR 0.60, p < 0.01). Time to first treatment after completion of staging was significantly shorter for C3 than C1 (HR 1.58, p < 0.01). Conclusion: Trends toward a reduction in wait time are evident 5 years after the regionalization of lung cancer care, primarily led by shorter wait times for CT scans and thoracic surgeon consults. However, wait times can further be reduced by addressing delays in staging completion and patient and provider education to identify the early signs of NSCLC.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".