Abstract LB-397: Pembrolizumab plus pemetrexed and platinum vs placebo plus pemetrexed and platinum as first-line therapy for metastatic nonsquamous NSCLC: analysis of KEYNOTE-189 by <i>STK11</i> and <i>KEAP1</i> status
Bibliographic record
Abstract
Abstract Background: Mutations in the tumor suppressor genes STK11 (also known as LKB1) and KEAP1 have been associated with poorer clinical outcomes in patients (pts) with NSCLC. In an exploratory analysis, we assessed the prevalence of STK11 and KEAP1 mutations and their association with efficacy in KEYNOTE-189 (NCT02578680). Methods: STK11 and KEAP1 status and tumor mutational burden (TMB) were assessed by whole-exome sequencing (WES) in pts who had available tumor and matched-normal tissue. PD-L1 was assessed by the PD-L1 IHC 22C3 pharmDx assay. The association of STK11 and KEAP1 status with efficacy and their correlation with TMB and PD-L1 expression distributions were evaluated descriptively. Results: WES data from both tumor and normal DNA were evaluable for 289 (47%) of 616 pts, of whom 54 (19%) had an STK11 mutation and 68 (24%) had a KEAP1 mutation; 29 (10%) had both STK11 and KEAP1 mutations. PD-L1 TPS tended to be lower in pts with vs without STK11 mutation (median [IQR] 0% [0-16] vs 15% [0-75]), whereas TMB score tended to be higher in pts with mutation (209 [132-265] vs 146 [89-264]). Similar patterns were seen for pts with vs without KEAP1 mutation (PD-L1 TPS: 1% [0-13] vs 20% [0-75]; TMB: 173 [124-267] vs 147 [89-263]). Although ORR of pembrolizumab plus chemotherapy was lower and PFS and OS shorter in pts with vs without STK11 and KEAP1 mutation, pembrolizumab plus chemotherapy was associated with numerically better outcomes than placebo plus chemotherapy regardless of mutation status (Table). 95% CIs were wide given the modest mutation frequency and the 2:1 randomization in favor of pembrolizumab plus chemotherapy. Conclusions: Data from this exploratory analysis support use of pembrolizumab plus pemetrexed and platinum as standard first-line therapy for pts with metastatic nonsquamous NSCLC regardless of STK11 or KEAP1 status. STK11KEAP1With MutationWithout MutationWith MutationWithout MutationPembro + ChemoPlacebo + ChemoPembro + ChemoPlacebo + ChemoPembro + ChemoPlacebo + ChemoPembro + ChemoPlacebo + Chemo(n = 36)(n = 18)(n = 168)(n = 67)(n = 45)(n = 23)(n = 159)(n = 62)ORR, % (95% CI)31 (16-48)17 (4-41)49 (41-57)16 (8-27)36 (22-51)17 (5-39)48 (40-56)16 (8-28)PFS, median, mo (95% CI)6 (4-9)5 (5-9)10 (8-14)5 (5-5)5 (4-11)5 (5-9)10 (8-14)5 (5-5)PFS, HR (95% CI)0.81 (0.44-1.47)0.38 (0.27-0.52)0.65 (0.38-1.12)0.38 (0.28-0.53)OS, median, mo (95% CI)17 (5-NR)8 (7-NR)23 (20-NR)12 (8-25)13 (7-NR)9 (7-NR)24 (20-NR)12 (8-NR)OS, HR (95% CI)0.75 (0.37-1.50)0.59 (0.41-0.85)0.81 (0.44-1.49)0.57 (0.39-0.84) Citation Format: Shirish M. Gadgeel, Delvys Rodriguez-Abreu, Enriqueta Felip, Emilio Esteban, Giovanna Speranza, Martin Reck, Rina Hui, Michael Boyer, Edward B. Garon, Hidehito Horinouchi, Razvan Cristescu, Deepti Aurora-Garg, Andrey Loboda, Jared Lunceford, Julie Kobie, Mark Ayers, Bilal Piperdi, M. Catherine Pietanza, Marina C. Garassino. Pembrolizumab plus pemetrexed and platinum vs placebo plus pemetrexed and platinum as first-line therapy for metastatic nonsquamous NSCLC: analysis of KEYNOTE-189 by STK11 and KEAP1 status [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr LB-397.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".