A phase I study of high-dose rosuvastatin with standard dose erlotinib in patients with advanced solid malignancies
Bibliographic record
Abstract
BACKGROUND: Synergistic cytotoxicity with high-dose statins and erlotinib has been demonstrated in preclinical models across a number of tumour types. In this phase I study, we evaluated the safety and potential anti-tumour activity of escalating doses of rosuvastatin in combination with the standard clinical dose of erlotinib in heavily pretreated patients with advanced solid tumours. METHODS: This was a single-center, phase I open-label study to determine the safety and recommended phase two dose (RPTD) of rosuvastatin in combination with 150 mg/day standard dose of erlotinib. Using a 3 + 3 study design and 28-day cycle, escalating doses of rosuvastatin from 1 to 8 mg/kg/day × 2 weeks (cycle 1) and 3 weeks (subsequent cycles) given concurrently with erlotinib were evaluated. In order to expand the experience and to gain additional safety and pharmacokinetic data, two expansions cohorts using concurrent or alternating weekly dosing regimens at the RPTD were also evaluated. RESULTS: All 24 patients enrolled were evaluable for toxicity, and 22 for response. The dose-limiting toxicity (DLT) of reversible muscle toxicity was seen at the 2 mg/kg/day dose level. Maximal tolerated dose (MTD) was determined to be 1 mg/kg/day. Thirty-three percent of patients developed at least 1 ≥ grade 2 muscle toxicity (rhabdomyolysis: 1/24, myalgia: 7/24) resulting in one study-related death. Durable stable disease for more than 170 days was seen in 25 % of patients that received concurrent treatment and were evaluable for response (n = 16). Plasma erlotinib levels on study were unaffected by the addition of rosuvastatin. CONCLUSIONS: The observed disease stabilization rate of 25 % with combination therapy in this heavily pretreated population is encouraging, however, the high levels of muscle toxicities observed limited this combination strategy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".