Details

Autor(en) / Beteiligte

• Chia, Mark A
• Keane, Pearse A

Titel

Beyond anti-VEGF: can faricimab reduce treatment burden for retinal disease?

Ist Teil von

• The Lancet (British edition), 2022-02, Vol.399 (10326), p.697-699

Ort / Verlag

England: Elsevier Ltd

Erscheinungsjahr

2022

Link zum Volltext

Quelle

MEDLINE

Beschreibungen/Notizen

• For nAMD, patients often require in excess of 50 injections, sometimes for more than 10 years, or the remainder of their lives.3 For DMO, patients typically require 12–15 injections in the first 3 years, at which time loss to follow-up is close to one-third.4 Treatment burden is thought to be a key reason the benefits of anti-VEGF in clinical trials have never fully translated to clinical practice.2 Given the ageing population and growing obesity epidemic, both nAMD and DMO are projected to increase significantly in the future.5,6 A key question for researchers has therefore evolved; namely, how can we improve the durability of drug therapy? In addition to binding VEGF-A, faricimab targets angiopoietin-2, a ligand operating distinct from the VEGF pathway that regulates vascular destabilisation and inflammation.7 These multicentre, randomised, double-masked, non-inferiority trials compare the safety and efficacy of faricimab with aflibercept, an existing anti-VEGF drug that is widely used.9 Jeffrey Heier and colleagues7 report week 48 results of the identical TENAYA and LUCERNE trials for nAMD. 1329 patients with nAMD (793 [60%] female, 536 [40%] male; 1153 [87%] White, 133 [10%] Hispanic or Latino, 126 [9%] Asian, four [<1%] American Indian or Alaska Native, and ten [1%] Black or African American) were randomly assigned to receive faricimab at an interval between 8 and 16 weeks, or aflibercept every 8 weeks (in both cases preceded by loading doses every 4 weeks). PAK declares fees from DeepMind for consultancy in automated analysis of retinal imaging with deep learning, for Roche in personalised health care, for Novartis in personalised health care, for Apellis in automated analysis of geographic atrophy, and for BitFount in privacy protecting machine learning.