Management of stages I and II non‐small‐cell lung cancer in a New Zealand study: divergence from international practice and recommendations
Bibliographic record
Abstract
BACKGROUND: Lung cancer survival statistics for New Zealand (NZ) are poor relative to Australia, USA, Canada and some European countries for reasons that are unknown. As patients with early-stage non-small-cell lung cancer (NSCLC) have the highest chance of survival, appropriate management disproportionately influences survival rates. The aim of this study was to assess management of stage I/II NSCLC, whether management differed from international practice, and factors influencing curative management. METHODS: Management of patients with stages I and II NSCLC was determined from an audit of secondary care in Auckland and Northland for patients with lung cancer diagnosed in 2004 (565). RESULTS: Of the 142 cases with stage I or II NSCLC, 79 patients (56%) were treated with curative intent and 61 (44%) were managed palliatively. Of those treated curatively, 69 underwent surgical resection, 9 received definitive radiation therapy and a single patient received concurrent chemo-irradiation. Of those managed palliatively, 21 received anticancer treatment and 40 received supportive care. Increasing age and comorbidity reduced the chances of receiving curative treatment (P < 0.001, P = 0.004, respectively); however, discussion at a multidisciplinary meeting was associated with increased likelihood of curative management (P < 0.001). Disparity between NZ and overseas practice increased with increasing age and comorbidity. Only half of those managed curatively commenced treatment within internationally recommended time frames. CONCLUSION: Relatively fewer patients received potentially curative treatment in this NZ study than in countries with better survival outcomes and many were not managed within recommended time frames. Management differences increased with increasing age and comorbidity, possibly suggesting more nihilistic attitudes in NZ.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 | 0.000 |
| 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 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".