Comparison of two dose calculation methods of intra-arterial carboplatin in the treatment of recurrent glioblastoma multiforme.
Bibliographic record
Abstract
e13503 Background: Glioblastoma is a deadly brain cancer, and as part of the natural evolution, its relapses will mostly occur 32 to 36 weeks after the initial diagnosis. The standard of care for recurrent glioblastomas is not well defined and multiple options exist. Intra-arterial chemotherapy as one option is currently practiced at the Centre hospitalier universitaire de Sherbrooke, the only center doing this procedure in Canada. The aim of this study is to evaluate the impact of using the area under the curve (AUC) or body surface area (BSA) dosing formula to guide intra-arterial carboplatin administration. It was designed to explore the relation of two dose calculation methods on efficacy and toxicity, determined by progression-free survival (PFS) and hematologic toxicity, respectively. Methods: A retrospective observational study was conducted, which includes adult in-patients who received intra-arterial carboplatin for recurrent glioblastoma from June 1st, 2000 to December 31st, 2017. It examined the associations of the method used to calculate the doses, in mg or mg/mL x min-1, with clinical outcomes. Results: One hundred ninety patients were included in the analysis. For the primary endpoint, an exposure greater than 6 of AUC was found potentially harmful in terms of efficacy compared to AUC under 6 (HR 0.529, p = 0.0044). In terms of toxicity, a higher AUC is highlighted to correlate with a slightly higher incidence of thrombocytopenia and neutropenia (OR 1.051 p = 0.0271; OR 1.072 p = 0.049). No significant association between toxicity and dose calculated with BSA could be established. Conclusions: AUC greater than 6 is detrimental in terms of effectiveness according to progression free survival. Moreover, AUC could be used to predict neutropenia and thrombocytopenia. However no significant predictions were found using BSA method. We recommend the use of AUC method in intra-arterial carboplatin instead of BSA method since the latter was not statistically related to toxicity. A prospective trial comparing the two dosage methods would be 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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".