Use of radiation therapy among patients with Extensive-stage Small-cell lung cancer receiving Immunotherapy: Canadian consensus recommendations
Bibliographic record
Abstract
OBJECTIVES: Thoracic radiation therapy (TRT) and prophylactic cranial irradiation (PCI) are commonly used in the management of extensive-stage small-cell lung cancer (ES-SCLC); however, Phase III trials of first-line immunotherapy often excluded these options. Guidance is needed regarding appropriate use of TRT, PCI, and magnetic resonance imaging (MRI) surveillance while new data are awaited. MATERIALS AND METHODS: In two web-based meetings, a pan-Canadian expert working group of five radiation oncologists and four medical oncologists addressed eight clinical questions regarding use of radiation therapy (RT) and MRI surveillance among patients with ES-SCLC receiving immunotherapy. A targeted literature review was conducted using PubMed and conference proceedings to identify recent (January 2019-April 2022) publications in this setting. Fifteen recommendations were developed; online voting was conducted to gauge agreement with each recommendation. RESULTS: After considering recently available evidence across lung cancer populations and clinical experience, the experts recommended that all patients with a response to chemo-immunotherapy, good performance status (PS), and limited metastases be considered for consolidation TRT (e.g., 30 Gy in 10 fractions). When considered appropriate after multidisciplinary team discussion, TRT can be initiated during maintenance immunotherapy. All patients who respond to concurrent chemo-immunotherapy should undergo restaging with brain MRI to guide decision-making regarding PCI versus MRI surveillance alone. MRI surveillance should be conducted for two years after response to initial therapy. PCI (e.g., 25 Gy in 10 fractions or 20 Gy in 5 fractions) can be considered for patients without central nervous system involvement who have a response to chemo-immunotherapy and good PS. Concurrent treatment with PCI and immunotherapy or with TRT, PCI, and immunotherapy is appropriate after completion of initial therapy. All recommendations were agreed upon unanimously. CONCLUSIONS: These consensus recommendations provide practical guidance regarding appropriate use of RT and immunotherapy in ES-SCLC while awaiting new clinical trial data.
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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 | 0.031 | 0.081 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.008 | 0.003 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".