Management of Small-Cell Lung Cancer with Radiotherapy—A Pan-Canadian Survey of Radiation Oncologists
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: The management of small-cell lung cancer (sclc) with radiotherapy (rt) varies, with many treatment regimens having been described in the literature. We created a survey to assess patterns of practice and clinical decision-making in the management of sclc by Canadian radiation oncologists (ros). METHODS: A 35-item survey was sent by e-mail to Canadian ros. The questions investigated the role of rt, the dose and timing of rt, target delineation, and use of prophylactic cranial irradiation (pci) in limited-stage (ls) and extensive-stage (es) sclc. RESULTS: Responses were received from 52 eligible ros. For ls-sclc, staging (98%) and simulation or dosimetric (96%) computed tomography imaging were key determinants of rt suitability. The most common dose and fractionation schedule was 40-45 Gy in 15 once-daily fractions (40%), with elective nodal irradiation performed by 31% of ros. Preferred management of clinical T1/2aN0 sclc favoured primary chemoradiotherapy (64%). For es-sclc, consolidative thoracic rt was frequently offered (88%), with a preferred dose and fractionation schedule of 30 Gy in 10 once-daily fractions (70%). Extrathoracic consolidative rt would not be offered by 23 ros (44%). Prophylactic cranial irradiation was generally offered in ls-sclc (100%) and es-sclc (98%) after response to initial treatment. Performance status, baseline cognition, and pre-pci brain imaging were important patient factors assessed before an offer of pci. CONCLUSIONS: Canadian ros show practice variation in sclc management. Future clinical trials and national treatment guidelines might reduce variability in the treatment of early-stage disease, optimization of dose and targeting in ls-sclc, and definition of suitability for pci or consolidative rt.
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.
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 it