Outcomes of Radiation Therapy Plus Immunotherapy in Metastatic Renal Cell Carcinoma: Results From the Canadian Kidney Cancer Information System
Bibliographic record
Abstract
PurposeWith the integration of immunotherapy (IO) agents in the management of metastatic renal cell carcinoma (mRCC), there has been interest in the combined use with radiation therapy (RT). However, real world data are limited. The purpose of this study was to evaluate outcomes in patients with mRCC receiving both RT and IO compared with IO alone.Methods and MaterialsData were collected from Canadian Kidney Cancer Information System from January 2011 to September 2019 across 14 academic centers. Patients with mRCC who received IO as first- or second-line therapy were included. RT was categorized as radical dose or palliative dose. Kaplan-Meier estimates were reported for overall survival (OS) and time to treatment failure. Cox proportional hazard models were used adjusted for age and International Metastatic RCC Database Consortium risk categories.ResultsIn total, 505 patients were included in the study: 179 received RT + IO and 326 received IO alone. Two-year OS for the RT + IO group was 55.0% compared with 66.4% in the IO alone cohort (adjusted hazard ratio [aHR], 1.38; P = .07). At 2 years, 12.2% of the RT + IO patients remained on therapy versus 30.9% in the IO alone group (aHR, 1.30; P = .02). For patients receiving first-line therapy, 2-year OS in the RT + IO group was 56.4% versus 78.4% in the IO alone arm, though this difference was not statistically significant (aHR, 1.23; P = .56). For patients receiving radical dose and palliative dose, 2-year OS was 57.0% and 53.9%, respectively (aHR, 0.86; P = .63).ConclusionsIn this descriptive analysis, more than one-third of patients with mRCC received RT and demonstrated inferior outcomes compared with IO alone. Potential explanations include greater presence of adverse metastatic sites in those receiving RT. Prospective clinical trials evaluating potential benefits of RT in an IO era remain an important need.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".