Radiation therapy in combination with immune checkpoint inhibitors in metastatic lung cancer: Effect of fractionation
Bibliographic record
Abstract
Immunotherapy with checkpoint inhibitors has improved the outcomes of patients with metastatic lung cancer in recent years. Despite improved prognosis, not all patients respond to treatment. Therapeutic interventions to build on the success of immune checkpoint inhibitors are needed. A retrospective review of patient records for patients who had received immune checkpoint inhibitors in a single cancer center over 4 years was undertaken. Demographic and disease characteristics of patients with metastatic non-small cell lung cancer were recorded. Data on other treatments including chemotherapy and radiation therapy were extracted, and survival outcomes were calculated. Most (81.8%) of the 77 metastatic lung cancer patients examined had received palliative radiation therapy within 3 months of starting immune checkpoint inhibitors. While the survival outcomes of these patients did not differ from patients who had not received radiotherapy, patients who had undergone hypofractionated radiotherapy (defined as one or more fractions of 700 cGy or higher) displayed a better overall survival (OS) than the rest of the cohort. Palliative radiation therapy administered in proximity with immune checkpoint inhibitors immunotherapy had no effect on the OS of metastatic lung cancer patients. However, patients receiving palliative radiotherapy with fractions above 700 cGy showed better OS. Further studies are needed to optimize a combination strategy.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".