Efficacy, durability, and safety of faricimab in patients from Asian countries with neovascular age-related macular degeneration: 1-Year subgroup analysis of the TENAYA and LUCERNE trials
Bibliographic record
Abstract
PURPOSE: To evaluate 1-year efficacy, durability, and safety of faricimab among patients from Asian countries in the TENAYA/LUCERNE trials of neovascular age-related macular degeneration (nAMD). METHODS: Treatment-naïve patients with nAMD were randomly assigned (1:1) to faricimab 6.0 mg up to every 16 weeks (Q16W), based on disease activity at weeks 20 and 24, or aflibercept 2.0 mg Q8W. The primary endpoint was change in best-corrected visual acuity (BCVA) from baseline averaged over weeks 40, 44, and 48. RESULTS: In the pooled TENAYA/LUCERNE trials, there were 120 (9.0%) and 1209 (91.0%) patients in the Asian (faricimab n = 61; aflibercept n = 59) and non-Asian country (faricimab n = 604; aflibercept n = 605) subgroups, respectively. In the Asian country subgroup, mean BCVA change from baseline at the primary endpoint visits was 7.1 (95% CI, 4.3-9.8) letters with faricimab and 7.2 (4.4-10.0) letters with aflibercept. In non-Asian country patients, mean vision gains were 6.1 (5.2-7.1) and 5.7 (4.8-6.7) letters with faricimab and aflibercept, respectively. At week 48, 59.6% of Asian country patients in the faricimab group achieved Q16W dosing (vs. 43.9% non-Asian) and 91.2% achieved ≥ Q12W dosing (vs. 77.5% non-Asian). Central subfield thickness reductions were similar between the subgroups, with meaningful and similar reductions from baseline observed at the primary endpoint visits and over time. Faricimab was well tolerated in both subgroups, with an acceptable safety profile. CONCLUSION: Consistent with the global TENAYA/LUCERNE findings, faricimab up to Q16W showed sustained visual and anatomical benefits in patients with nAMD from Asian and non-Asian countries. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT03823287 (TENAYA); NCT03823300 (LUCERNE). Date of registration: January 30, 2019.
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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 | 0.009 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.011 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".