Abstract CT223: Long-term survival follow-up of tebentafusp in previously treated metastatic uveal melanoma (mUM)
Bibliographic record
Abstract
Abstract Background: Tebentafusp, a bispecific (gp100 x CD3) ImmTAC, is approved for adult HLA-A*02:01+ patients with unresectable or metastatic uveal melanoma (mUM). In the Ph2 IMCgp100-102 study of pts with previously treated mUM (NCT02570308), tebentafusp demonstrated a median OS of 16.8 months and 1-year OS of 61% after a minimum 2 yrs of follow-up, nearly double the historical observed rates.12, Here we present the final analysis of OS of the Ph2 IMCgp100-102 study. Methods: 127 HLA-A*02:01+ 2L+ pts with mUM were dosed weekly with intravenous tebentafusp following intra-patient dose escalation of 20mcg dose 1, 30mcg dose 2 and 68mcg dose 3+. Primary objective was overall response rate and secondary objectives included safety and OS. OS was estimated by Kaplan-Meier method. Survival for ctDNA evaluable patients was assessed. Analyses are based on a 17 Oct 2022 database lock. Results: With a median follow-up of 46 months, median OS was 16.8 (95% CI: 12.3-21.3) months, consistent with previous reports. Estimated 1-yr, 2-yr, 3-yr and 4-yr OS rates were 61%, 36%, 21% and 11%, respectively. ctDNA clearance by week 9 (n=12) was associated with 100% 1-yr, 73% 2-yr, 45% 3-yr and 23% 4-yr survival. OS for patients with poor prognostic factors compared favorably relative to historical benchmarks (Table 1). Mean and median duration of treatment was 9.9 and 5.6 months. Majority of pts who received a subsequent line of therapy received immunotherapy (48/72; 67%) followed by liver-directed therapy (14/72; 19%). No new safety signals were identified. Conclusions: This study provides the longest follow-up of OS for a soluble TCR therapeutic to date. Tebentafusp continued to show unprecedented survival benefit for 2L+ mUM pts, including the poorest prognostic groups, with estimated OS rates that remain nearly double the historical rates observed in this population at a median follow-up of ~4 years. Early ctDNA clearance was associated with indication of survival benefit. 1. Carvajal et al. Nat Med 2022 2. Sacco et al. J Immunother Canc 2021 Table 1. OS in Ph2 IMCgp100-102 versus historical benchmarks Ph2 IMCgp100-102 Historical benchmarks*,† Population 1-yr 2-yr 3-yr 1-yr 2-yr 3-yr Overall 2L+ 61% 36% 21% 37% 15% 9% Subgroups Age ≥ 65 yrs 51% 31% 25% 38% 12% 6% LDH > ULN 44% 22% 11% 23% 8% 3% Baseline largest liver lesion ≥ 3cm 52% 26% 14% 32% 11% 4% *OS benchmark for 2L+ patients calculated from Rantala et al 2019 †OS benchmarks for pt subgroups (all lines of therapy) estimated from digitized OS curves presented in Khoja et al. 2019 Citation Format: Joseph J. Sacco, Richard D. Carvajal, Marcus O. Butler, Alexander N. Shoushtari, Jessica C. Hassel, Alexandra Ikeguchi, Leonel Hernandez-Aya, Paul Nathan, Omid Hamid, Josep M. Piulats, Matthew Rioth, Douglas B. Johnson, Jason J. Luke, Erique Espinosa, Serge Leyvraz, Laura Collins, Chris Holland, Michelle L. McCully, Takami Sato. Long-term survival follow-up of tebentafusp in previously treated metastatic uveal melanoma (mUM) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 2 (Clinical Trials and Late-Breaking Research); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(8_Suppl):Abstract nr CT223.
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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) | 0.000 | 0.000 |
| 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 | 0.000 | 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".