Estimating prognosis at the time of repeat whole brain radiation therapy for multiple brain metastases: The reirradiation score
Bibliographic record
Abstract
Purpose Whole brain radiation therapy (WBRT) remains the standard of care for patients with multiple brain metastases, but more than half of treated patients will develop intracranial progression. Because there is no clear consensus on the optimal therapeutic approach, a prognostic index would be helpful to guide treatment options at progression. We explored whether the recursive partitioning analysis (RPA) score prior to repeat WBRT is predictive of survival. Methods and materials This multi-institutional pooled analysis included patients with 2 or more brain metastases from any solid primary tumor that was treated with 2 courses of WBRT. Information on demographics, disease characteristics, and intervals between courses was collected. RPA class was abstracted or retrospectively assigned, and descriptive statistics calculated. Median survival (MS) was determined using the Kaplan-Meier method and compared using log rank tests. Univariate and multivariate analyses were performed via Cox regression analysis. Results For 205 patients, the median age was 55 years (range, 25-83 years), 68% were female, 40.5% had non-small cell lung cancer, and 31.2% had small cell lung cancer. Prior to the second WBRT, 4.9% of patients were RPA class 1, 36.6% were RPA2, and 58.5% were RPA3, with an MS of 7.5 months (95% confidence interval [CI], 4.7-10.3), 5.2 months (95% CI, 3.7-6.7 months), and 2.9 months (95% CI, 2.2-2.9 months), respectively ( P = .001). On univariate and multivariate analyses, a Karnofsky Performance Status of <80, extracranial metastases, interval between courses <9 months, small cell lung cancer histology, and uncontrolled primary significantly correlated with shorter MS. By assigning a score of 1 to each of these factors, a new prognostic index was created, the reirradiation (ReRT) score. Survival on the basis of ReRT score grouping ranged from 2.2 to 7.2 months and demonstrated significant differences in MS. Conclusions In the largest reported cohort to receive repeat WBRT, application of the RPA score was not predictive of MS. The new ReRT score is a simple tool based on readily available clinical information.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.001 | 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 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".