Outcomes in Elderly Patients with Glioblastoma Multiforme Treated with Short-Course Radiation Alone Compared to Short-Course Radiation and Concurrent and Adjuvant Temozolomide Based on Performance Status and Extent of Resection
Bibliographic record
Abstract
(1) Background: Studies in elderly patients over the age of 65 with glioblastoma have shown survival benefits of short-course radiation therapy with concurrent and adjuvant temozolomide, making it the standard of care adopted at Juravinski Cancer Center. Our study retrospectively examines patients with GBM aged ≥ 70 at the JCC treated with short-course radiation alone compared to those treated with short-course radiation and concurrent and adjuvant TMZ, to determine if there is a difference in outcomes based on performance status. (2) Methods: A retrospective chart review was conducted at JCC using patients diagnosed with GBM in 2014-2017 (treated with the old protocol of short-course RT alone) versus those diagnosed in 2017-2019 (treated with the new protocol of short-course radiation and TMZ). Patient demographics, treatments, outcomes, and baseline KPS were analyzed. (3) Results: No clear benefit and more neurologic decline post treatment were seen in patients with borderline performance status and subtotal resection who underwent concurrent treatment with temozolomide and radiation. The addition of temozolomide was most helpful in patients with good performance status and a gross total resection. Variable outcomes were seen in patients with mixed traits. (4) Conclusions: This study suggests that performance status and extent of resection are significant determinants of patient response to treatment. In the case of elderly patients with borderline performance status and GTR or those with good performance status and STR, also described as "mixed traits", it may be beneficial to pursue single modality treatment, ideally based on MGMT promoter methylation status as opposed to bimodality treatment in order to maintain the best QOL.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".