Delays to surgery in non-small-cell lung cancer.
Bibliographic record
Abstract
BACKGROUND: In Canada, waiting times for referral and surgery exist for both benign and malignant disease. We attempted to evaluate the length of various waiting times for surgery as well as their association with surgical stage in patients with non-small-cell lung cancer (NSCLC). METHODS: This observational study consisted of a retrospective review of data for all patients who underwent an operation with the intent to cure NSCLC between Jan. 1, 1993, and Dec. 31, 2002, at the Montreal General Hospital, McGill University Health Centre, Montréal, Que. Time intervals between multiple preoperative points and surgery were calculated. The patients were then linked via universal health care insurance numbers with data from the centralized provincial inclusive health care database. This allowed the calculation of the precise interval between the patients' first contact with a physician for symptoms related to their malignancy and surgery. Mean time intervals were then compared with surgical stage. RESULTS: We found adequate data for time interval analysis over 10 years for 256 patients who had undergone surgery with intent to cure. The distribution of patients by TNM stage was as follows: stage I, 144 patients (56.3%); stage II, 47 patients (18.4%); stage III, 41 patients (16.0%); and stage IV, 24 patients (9.4%). Mean and median time intervals between initial contact with physician or first onset of symptoms relating to lung cancer and surgery were 208 (standard deviation [SD] 313) days and 109 days, respectively. Mean and median time intervals between initial contact with the thoracic surgeon and surgery were 104 (SD 99) days and 82 days, respectively. No detrimental effect was observed between time to surgery and surgical stage in patients with NSCLC. CONCLUSIONS: Excessive preoperative waiting times before attempts at curative surgical resection for NSCLC exist in our centre. These intervals are exceptionally long, multifactorial and cause for concern.
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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 | 0.000 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".