Abstract A105: Phase 2 trials of linifanib (ABT-869) in advanced hepatocellular, renal cell and non-small cell lung cancer: Associations of response by CT or DCE-MRI with patient outcome
Bibliographic record
Abstract
Abstract Background: Linifanib is a novel orally active and selective inhibitor of VEGF and PDGF families of receptor tyrosine kinases. Linifanib has demonstrated antitumor activity in a variety of advanced solid tumors in phase 1 and 2 trials. The objective of this analysis was to assess associations between pt outcome (PFS or OS) and response by CT (per RECIST or tumor volume change), or DCE-MRI (per Ktrans), in patients (pts) enrolled in ongoing phase 2 linifanib monotherapy trials. Methods: Three open-label, phase 2 monotherapy studies were conducted internationally in advanced/metastatic solid tumor pts with hepatocellular carcinoma (HCC), non-small cell lung cancer (NSCLC) and renal cell carcinoma (RCC). Interim efficacy and safety results have been previously reported. A retrospective exploratory analysis of associations between pt outcome and CT or DCE-MRI response was conducted. An independent centralized review of tumor response assessment by CT (baseline, and Q8 wks) and DCE-MRI (baseline, and 2 wks) was performed using a uniform charter. CT assessed tumor volume and best percent change from baseline and pts were classified as PR, SD, or PD by RECIST. Baseline Ktrans and percent change in Ktrans were derived from DCE-MRI. Statistical analysis was performed using the Cox proportional hazard model and logrank test, and significance considered at the level of P≥0.05. Threshold estimates were determined by the Bootstrapping & Aggregating Thresholds from Trees (BATTing). Results: Across the 3 phase 2 trials, 236 pts were enrolled from 08/07 to 10/08 at 34 centers: 44 pts with HCC, 53 pts with RCC, and 139 pts with NSCLC. Based on the BATTing methodology, 79/191 evaluable pts had a maximum CT tumor volume decrease of >32%. This was associated with improved OS (log-rank p<0.001) and PFS (log-rank p<0.001). Pts with confirmed or unconfirmed PR (n=27) per RECIST had better OS (p=0.021) and PFS (p=0.017) than those who did not achieve a PR (n=181). Among the 236 pts, 117 had DCE-MRI scans at baseline and Day 15. Of these, 68/117 pts (58%) had baseline Ktrans above the BATTing cutoff of 0.055 and this was associated with improved OS (log-rank, p=0.011), but not PFS (log-rank, p=0.835). DCE-MRI response (Ktrans decrease) at 2 wks was not associated with significant improvement in PFS or OS. Conclusions: CT tumor volume reduction and CT response were associated with improved OS and PFS. Greater baseline Ktrans was associated with improved OS but not PFS. Ktrans changes at 2 wks were not associated with improvement in pt outcome. Citation Information: Mol Cancer Ther 2009;8(12 Suppl):A105.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".