Defining the Need for Radiotherapy for Lung Cancer in the General Population
Bibliographic record
Abstract
BACKGROUND: We have previously used an evidence-based, epidemiologic approach to estimate the proportion of incident cases that should be treated with radiotherapy (RT) for lung cancer. The first objective of the present study was to compare this evidence-based estimate of the appropriate rate of use of RT with the rates observed in selected "benchmark" communities where there are no barriers to the appropriate use of RT and no incentives to the unnecessary use of RT. The second objective of the study was to compare the rates of use of RT in the general populations in the United States and Canada with the estimated appropriate rate. METHODS: We established benchmark rates for the use of RT for lung cancer in Ontario, Canada, where: 1) residents make no direct payments for RT; 2) all RT is provided by site-specialized radiation oncologists in multidisciplinary cancer centers, and 3) radiation oncologists receive a salary in lieu of technical fees. Communities located close to cancer centers without long waiting lists for RT were selected to serve as benchmarks. Prospectively gathered electronic treatment records from all RT cancer centers were linked to the provincial cancer registry to describe the rate of use of RT in Ontario. The public use file of Surveillance, Epidemiology and End Results Registries (SEER) was used to describe the use of RT in the United States. RESULTS: Overall, 41.3% (95% confidence interval [CI], 39.9%, 42.7%) of incident cases of lung cancer received RT as part of their initial management in the benchmark communities compared with the evidence-based estimate of 41.6% (95% CI, 39.2%, 44.1%). The rate of use of RT in the initial management of nonsmall cell lung cancer (NSCLC) in the benchmark communities was 49.3% (95% CI, 47.5%, 51.1%) compared with the evidence-based estimate of 45.9% (95% CI, 41.6%, 50.2%). The use of RT in the initial management of small-cell lung cancer (SCLC) in the benchmark communities was 47.0% (95% CI, 43.3%, 50.7%) compared with the evidence-based estimate of 45.4% (95% CI, 42.4%, 48.4%). In many counties of Ontario, the observed rates of RT use in the initial management of lung cancer were significantly lower than either the benchmark rate or the evidence-based estimate of the appropriate rate. In contrast, rates of use of RT in most counties in the SEER regions of the United States were close to, or higher than, the estimated appropriate rate. CONCLUSIONS: The observed benchmark rate converged on the evidence-based estimate of the appropriate rate of use of RT for lung cancer, suggesting that either measure might reasonably be used as a "standard" against which to compare rates observed in similar populations elsewhere.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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".