When Temozolomide Alone Fails: Adding Procarbazine in Salvage Therapy of Glioma
Bibliographic record
Abstract
BACKGROUND: Since temozolomide (TMZ) entry into routine practice in the first-line management of glial tumors, post-TMZ recurrences present a growing challenge. Without standard chemotherapy for TMZ failure, care in such palliative settings requires consideration not only of efficacy but of toxicity and convenience. METHODS: At our institution, a combination regimen has been used: oral alkylating agents procarbazine (PCB) (100-150 mg/m2/day) and TMZ (150-200 mg/m2/day) administered on days 1-5 of a 28-day cycle. This treatment has been initiated upon radiological and/or clinical disease progression, and continued until evidence of further progression or toxicity. We retrospectively reviewed our experence with this regimen. RESULTS: Since November 2004, 17 patients (median age 53) were treated for histologically confirmed glioma (glioblastoma multiforme (GBM), N = 12; Grade 3 glioma, N = 3; Grade 2 glioma, N = 2) after a median of 2 recurrences. TMZ was previously given either as adjuvant therapy (post-chemoradiotherapy maintenance in 8 of 13 cases) or as salvage monotherapy (4 cases). Of 16 evaluable cases, 14 (13 high grade tumors) showed O-6-methylguanine-DNA methyltransferase (MGMT) promoter methylation. Two patients achieved partial response and one had complete response by RECIST criteria. Disease progressed after a median of 4 cycles (range 1 to 11+), with an actuarial progression-free survival of 42% after 6 cycles. Grade 3/4 toxicity was rare, and no dose reductions were needed. One patient discontinued treatment due to procarbazine hypersensitivity. CONCLUSION: Combination PCB-TMZ is well-tolerated, with modest activity in TMZ-exposed glioma.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".