RECIST v1.1 and irRECIST outcomes in advanced HCC treated with pembrolizumab (pembro).
Bibliographic record
Abstract
528 Background: IO can cause pseudoprogression (PP): apparent tumor growth followed by stability or favorable response. We assess PP in aHCC treated with pembro (KEYNOTE-224 [ph 2], NCT02702414; KEYNOTE-240 [ph 3], NCT02702401). Methods: aHCC pts with PD on/intolerance to sorafenib received pembro 200 mg IV Q3W until unacceptable toxicity, study withdrawal, 2 y of therapy, or RECIST v1.1 PD; if pt clinically stable at PD, physician could continue therapy and repeat scans to confirm PD per irRECIST. PP=RECIST v1.1 PD then irRECIST response other than PD. Data cutoff: Jan 02, 2019 (KEYNOTE-240); Feb 13, 2018 (KEYNOTE-224). Results: 245/382 pembro-treated pts had RECIST v1.1 PD: 138 irRECIST repeat scan; 105 PD; 33 (8.6%; 33/382) outcomes other than PD. Of 33 PP, 29 had SD, 3 PR, 1 CR (irRECIST; 29 had this at first irRECIST scan; 4 [2 SD, 2 PR] at subsequent scan). For initial RECIST v1.1 PD, 16/33 PP had PD at first postbaseline scan (pembro cycles 2-4); 17/33 PP had PD at pembro cycles 4-18. Median (range) time to RECIST v1.1 PD in the 33 PP was 80 (37-378) days. OS shown in Table. KEYNOTE-240 had 135 PBO-treated pts: 8 (5.9%) PP; small samples bar meaningful interpretation. Conclusions: PP in aHCC, per irRECIST, has a similar incidence to other cancers (eg, melanoma) and does not seem to correlate with OS. Data may help physicians assess when to continue pembro after PD. Clinical trial information: NCT02702414, NCT02702401. [Table: see text]
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".