Phase III study of PSC‐833 (valspodar) in combination with vincristine, doxorubicin, and dexamethasone (valspodar/VAD) versus VAD alone in patients with recurring or refractory multiple myeloma (E1A95)
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Bibliographic record
Abstract
BACKGROUND: Preliminary studies have shown valspodar (PSC-833: Novartis Pharmaceuticals, East Hanover, NJ) to be a potent inhibitor of multidrug resistance (MDR), one cause of resistance to chemotherapy. An international randomized control study (Phase III) evaluated the use of vincristine, doxorubicin, and dexamethasone (VAD) with (n = 46) and without (n = 48) valspodar in the treatment of patients with recurring or refractory multiple myeloma. METHODS: Patients with documented recurrence or refractory myeloma were stratified based on prior treatment exposure and creatinine and randomized. Because of interaction of valspodar with vincristine and doxorubicin, the doses of these drugs were reduced compared with the VAD-alone arm, and the doxorubicin was further reduced in the last 15 patients when given with valspodar based on pharmacokinetic and toxicity studies. RESULTS: There were no complete or near-complete responses. There were 29% partial responses (PRs) in the VAD-alone arm and 44% with valspodar (P = 0.2). Median progression-free survival was 7 months with VAD alone and 4.9 months with valspodar (P = 0.50). Subjective response was 19% with VAD alone and 17% with valspodar (P = 1.0). Median survival with VAD alone was 18.5 months and 15.3 with the addition of valspodar (P = 0.055). Toxicity of Grade 3 or greater was higher (P < 0.0001) in the valspodar arm (89%) compared with the VAD-alone arm (58%). The reduction of doxorubicin dose reduced toxicity but not significantly (P = 0.11). CONCLUSION: The addition of the MDR-modulating agent valspodar to VAD did not improve treatment outcome. Toxicity was increased in the valspodar-treated group compared with VAD alone.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 it