Clinical benefit rate (CBR) of panitumumab monotherapy among patients with KRAS wild-type metastatic colorectal cancer (mCRC).
Bibliographic record
Abstract
e14176 Background: Panitumumab (Pmab) improves progression free survival as first-, second- and third-line therapy for KRAS wild-type (wt) metastatic colorectal cancer (mCRC). Only in the third-line setting is there evidence of benefit of Pmab monotherapy. In this analysis of an exploratory biomarker study of Pmab monotherapy, the clinical benefit rate of Pmab according to previous lines of therapy is described. Methods: Patients (pts) with KRAS non-mutated, measurable MCRC previously treated with or ineligible for oxaliplatin/5-FU and irinotecan were treated with Pmab 6mg/kg IV q2w until progression or toxicity. The primary endpoint is clinical benefit rate (complete (CR) or partial response (PR) + prolonged stable disease (PSD) > = 24 weeks) by RECIST criteria. Results: The study completed accrual and (40) evaluable patients were treated between September 2009 and December 2011 of which 32 were evaluable for the primary endpoint. Median follow-up was 8.8 months, median age was 64.5 years and 90% were ECOG 0/1. Previous therapy was: 5-FU/Capecitabine(C) only in 12 pts, Irinotecan/5-FU/C only in 2 patients, Oxaliplatin/5-FU/C only in 3 pts, Oxaliplatin/Irinotecan/5-FU/C in 23 pts. 22 patients received prior Bevacizumab. Median number of cycles was 8 and 6 pts required a dose modification. There were 7 (22%) PRs and 7 (22%) pts experienced PSD >=24 weeks. Clinical benefit rate (PR+PSD) according to previous therapy was 33% (3/9) for 5FU/C only, 100% (2/2) Oxaliplatin/FU/C only, 0% (0/2) Irinotecan/FU/C only, and 47% (9/19) for Oxaliplatin/Irinotecan/5FU/C. Conclusions: Pmab monotherapy is well tolerated and response rates vary according to previous lines of therapy. Patients ineligible for irinotecan and/or oxaliplatin experience a high clinical benefit rate with single agent Panitumumab and should be considered for such therapy. Updated study results will be presented.
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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 | 0.002 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".