Activity of dalotuzumab, a selective anti-IGF1R antibody, in combination with erlotinib in unselected patients with Non-small-cell lung cancer: a phase I/II randomized trial
Bibliographic record
Abstract
BACKGROUND: We investigated the safety and antitumor activity of dalotuzumab, a selective anti-insulin growth factor 1 receptor monoclonal antibody (IGF1R MoAb), plus erlotinib in a sequential phase I/II trial in unselected patients with refractory advanced non-small-cell lung cancer (NSCLC).The phase I trial determined the recommended dose and safety of erlotinib plus dalotuzumab at 5 mg/kg or 10 mg/kg weekly in 20 patients. The phase II trial compared outcomes to erlotinib alone and erlotinib plus dalotuzumab at the mg/kg established in the phase I trial. RESULTS: Erlotinib at 150 mg plus dalotuzumab at 10 mg/kg was safe. The phase II trial included 37 patients in the erlotinib arm and 38 patients in the erlotinib plus dalotuzumab arm. Progression-free survival was 1.6 versus 2.5 months, overall survival was 10.2 and 6.6 months, and the objective response rate was 7.9% and 2.7%, respectively, with no significant differences between the two arms. Grade 3-5 adverse events occurred in 11 (28.9%) versus 13 (35.1%) patients, respectively. The most frequent adverse events were asthenia (36.8% vs. 37.8%), dehydration (5.3% vs. 2.7%), diarrhea (71% vs. 81.1%), hyperglycemia (13.1% vs.18.9%), and skin-related toxicities (92.1% vs. 86.4%). CONCLUSION: The addition of dalotuzumab to erlotinib did not improve efficacy outcome in patients with refractory advanced NSCLC.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".