An analysis of the treatment effect of panitumumab on overall survival from a phase 3, randomized, controlled, multicenter trial (20020408) in patients with chemotherapy refractory metastatic colorectal cancer
Bibliographic record
Abstract
Panitumumab is a fully human monoclonal antibody that targets the epidermal growth factor receptor. Results from the primary analysis of a phase 3, randomized, controlled study showed a statistically significant improvement in progression-free survival for patients receiving panitumumab; however, overall survival was confounded by best supportive care (BSC) patients that crossed over to panitumumab therapy after disease progression. Three post hoc analyses are presented that approximate the panitumumab overall survival treatment effect in both the all-randomized and wild-type (WT) KRAS populations by using the BSC patients with mutant (MT) KRAS as the comparator group to discount the effect of crossover from BSC to panitumumab. The primary post hoc analysis showed a median overall survival of 6.4 months for all KRAS-evaluable patients randomized to panitumumab versus 4.4 months for patients with MT KRAS tumors randomized to BSC, yielding an adjusted hazard ratio (95 % CI) of 0.764 (0.598-0.977). Similar results were observed for the two secondary post hoc analyses. These analyses suggest a positive treatment effect of panitumumab in both the overall and WT KRAS patient populations consistent with an improvement in overall survival relative to BSC.
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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 | 0.019 | 0.017 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.008 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".