An International Consensus on Actions to Improve Lung Cancer Survival: A Modified Delphi Method Among Clinical Experts in the International Cancer Benchmarking Partnership
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Research from the International Cancer Benchmarking Partnership (ICBP) demonstrates that international variation in lung cancer survival persists, particularly within early stage disease. There is a lack of international consensus on the critical contributing components to variation in lung cancer outcomes and the steps needed to optimise lung cancer services. These are needed to improve the quality of options for and equitable access to treatment, and ultimately improve survival. METHODS: Semi-structured interviews were conducted with 9 key informants from ICBP countries. An international clinical network representing 6 ICBP countries (Australia, Canada, Denmark, England, Ireland, New Zealand, Northern Ireland, Scotland & Wales) was established to share local clinical insights and examples of best practice. Using a modified Delphi consensus model, network members suggested and rated recommendations to optimise the management of lung cancer. Calls to Action were developed via Delphi voting as the most crucial recommendations, with Good Practice Points included to support their implementation. RESULTS: Five Calls to Action and thirteen Good Practice Points applicable to high income, comparable countries were developed and achieved 100% consensus. Calls to Action include (1) Implement cost-effective, clinically efficacious, and equitable lung cancer screening initiatives; (2) Ensure diagnosis of lung cancer within 30 days of referral; (3) Develop Thoracic Centres of Excellence; (4) Undertake an international audit of lung cancer care; and (5) Recognise improvements in lung cancer care and outcomes as a priority in cancer policy. CONCLUSION: The recommendations presented are the voice of an expert international lung cancer clinical network, and signpost key considerations for policymakers in countries within the ICBP but also in other comparable high-income countries. These define a roadmap to help align and focus efforts in improving outcomes and management of lung cancer patients globally.
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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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 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 it