Prophylactic Cranial Irradiation for Limited-Stage Small-Cell Lung Cancer Patients: Secondary Findings From the Prospective Randomized Phase 3 CONVERT Trial
Bibliographic record
Abstract
INTRODUCTION: The impact of the dose and fractionation of thoracic radiotherapy on the risk of developing brain metastasis (BM) has not been evaluated prospectively in limited stage SCLC patients receiving prophylactic cerebral irradiation (PCI). METHODS: Data from patients treated with PCI from the CONVERT trial were analyzed. RESULTS: Four hundred forty-nine of 547 patients (82%) received PCI after completion of chemoradiotherapy. Baseline brain imaging consisted of computed tomographic scans in 356 of 449 patients (79%) and magnetic resonance imaging in 83 of 449 (18%) patients. PCI was delivered to 220 of 273 participants (81%) in the twice-daily (BD) group and 229 of 270 in the once-daily (OD) group (85%; p = 0.49). Total median PCI dose was 25 Gy in both the BD and OD groups (p = 0.74). In patients who received PCI, 75 (17%) developed BM (35 [8%] in OD and 40 [9%] in BD) and 173 (39%) other extracranial progression. In the univariate analysis, gross tumor volume (GTV) was associated with an increased risk of BM (p = 0.007) or other radiological progression events (p = 0.006), whereas in a multivariate analysis both thoracic GTV (tGTV) and ECOG performance score were associated with either progression type. The median overall survival (OS) of patients treated with PCI was 29 months. In the univariate analysis of OS, PCI timing from end of chemotherapy, weight loss of more than 10%, and tGTV were prognostic factors associated with OS. In the multivariate analysis, only tGTV was associated with OS. Delay between end of chemotherapy and PCI was not associated with OS. CONCLUSIONS: Patients receiving OD or BD thoracic radiotherapy have the same risk of developing BM. Larger tumors are associated with a higher risk of BM.
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 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".