Glioblastoma: Patterns of Recurrence and Efficacy of Salvage Treatments
Bibliographic record
Abstract
BACKGROUND: It is controversial if distant recurrence of glioblastoma is more common after temozolomide (TMZ) concurrent with radiotherapy (RT). Optimal therapy for patients with recurrent disease after RT/TMZ is unclear. Our purpose was to evaluate recurrence patterns in glioblastoma and the effect of treatment at recurrence upon survival. METHODS: We performed a retrospective review of 67 patients with newly diagnosed glioblastoma treated with RT/TMZ between 2003-2007. Statistical analyses included Kaplan-Meier method for survival, and multivariate Cox proportional hazards model for the effect of salvage treatment on survival. RESULTS: 58 patients (86.6%) recurred locally; 9 patients (13.4%) had a distant non-contiguous focus of new disease. Median survival(MS) was 17 months; median time-to-progression(TTP) 6.8 months. The local and distant groups had comparable prognostic factors. There was no difference in MS(p=0.35) or TTP(p=0.95) by location of recurrence. At relapse, 26 patients(38.8%) received continuous, dose-intense TMZ, 24(35.8%) other therapy(4.5% RT; 20.9% lomustine+/-procarbazine; 4.5% etoposide; 1.5% conventional TMZ; 4.5% TMZ then lomustine), and 17(25.4%) were untreated. Dose-intense TMZ was associated with prolonged MS compared to all other patients(21.5 months vs. 12.4 months, p=0.019, HR=3.86, 95%CI: 1.81-8.22) and similar to MS with other chemotherapy regimens(18.8 months, p=0.40, HR=1.30, 95% CI: 0.65-2.61). CONCLUSION: The pattern of recurrence of glioblastoma treated with RT/TMZ was predominantly local. Second-line treatment with continuous dose-intense TMZ may prolong survival in patients with recurrent glioblastoma. Overall survival is similar to other conventional salvage regimens; however TMZ may be better tolerated. This study is limited by its retrospective nature and potential selection bias. Prospective controlled studies are needed.
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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 | 0.000 |
| 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".