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Record W4391930651 · doi:10.1016/j.ophtha.2024.02.014

TENAYA and LUCERNE

2024· article· en· W4391930651 on OpenAlexaff
Arshad M. Khanani, Aachal Kotecha, Andrew Chang, Shih‐Jen Chen, Youxin Chen, Robyn H. Guymer, Jeffrey S. Heier, Frank G. Holz, Tomohiro Iida, Jane A. Ives, Jennifer I. Lim, Hugh Lin, Stephan Michels, Carlos Quezada-Ruiz, Ursula Schmidt‐Erfurth, David G. Silverman, Rishi P. Singh, Balakumar Swaminathan, Jeffrey R. Willis, Ramin Tadayoni, Ashkan M. Abbey, Elmira Abdulaeva, Prema Abraham, Hansjürgen Agostini, Arturo Alezzandrini, Virgil Alfaro, Arghavan Almony, Lebriz Altay, Payam Amini, Andrew N. Antoszyk, Etelka Aradi, Luís Arias, Jennifer Arnold, Riaz Asaria, Sergei Astakhov, Yury S. Astakhov, Carl C. Awh, Chandra Balaratnasingam, Sanjiv Banerjee, Caroline R. Baumal, Matthias Becker, Rubens Belfort, Galina Bratko, William Bridges, Jamin S. Brown, David M. Brown, M V Budzinskaya, S. Buffet, Stuart C Burgess, Ik Soo Byon, Carlo Cagini, Jorge I. Calzada, Stone Cameron, Peter A. Campochiaro, John S. Carlson, Ângela Carneiro, Clement Chan, Emmanuel Chang, Daniel L. Chao, Nauman Chaudhry, Caroline Chee, Andrew Cheek, San‐Ni Chen, Saradha Chexal, Mark Chittum, David R. Chow, Abosede Cole, B. Connolly, Pierre Loïc Cornut, Stephen Couvillion, Carl J. Danzig, Vesselin Daskalov, Amr Dessouki, François Devin, Michael Dollin, Rosa Dolz, Louise Downey, Richard F. Dreyer, Pravin U. Dugel, David Eichenbaum, Bora Eldem, Robert E. Engstrom, Joan Josep Escobar, Nicole Eter, David Faber, Naomi S. Falk, Leonard Feiner, Alvaro Fernandez Vega, Philip J. Ferrone, Marta S. Figueroa, Howard F. Fine, Mitchell S. Fineman, Gregory M. Fox, Catherine Français, Pablo Moreno Franco, Samantha Fraser‐Bell, Nicholas Fung, Federico Furno Sola, Richard Gale, Alfredo García‐Layana, Julie Gasperini, Maciej Gawęcki, Faruque Ghanchi, Manjot K. Gill, Michel Giunta, David L. Glaser, Michaella Goldstein, Francisco Gomez Ulla, Fumi Gomi, Víctor H. González, J. L. GRAFF, Sunil Gupta, Rainer Guthoff, Anton Haas, Robert L. Hampton, Katja Hatz, Ken Hayashi, Ewa Herba, Vrinda Hershberger, Patrick Higgins, Nancy M. Holekamp, Shigeru Honda, J. G. Howard, Allen Hu, Stephen Huddleston, Hiroko Imaizumi, Yasuo Ito, Yasuki Ito, Sujit Itty, Golnaz Javey, Cameron Javid, T. Kaga, J Kałuzný, Se Woong Kang, Kapil Kapoor, Levent Karabaş, Tsutomu Kawasaki, Patrick Kelty, Ágnes Kerényi, Ramin Khoramnia, Rahul N. Khurana, Kazuhiro Kimura, Kendra Klein-Mascia, Namie Kobayashi, Laurent Kodjikian, Hideki Koizumi, Gregg T. Kokame, Alexey N. Kulikov, Henry Kwong, Robert Kwun, Timothy Y. Y. Lai, Chi‐Chun Lai, Laurent Lalonde, Paolo Lanzetta, Michael Larsen, Adrian Lavina, Won Ki Lee, Ji Eun Lee, Seong Lee, Jaime Levy, Lucas Lindsell, Mimi Liu, Nikolas London, Andrew Lotery, David Lozano Rechy, Alan Luckie, David Maberley, Takatoshi Maeno, Sajjad Mahmood, Fuad Makkouk, Dennis M. Marcus, Alan Margherio, Hélène Massé, Hisashi Matsubara, Raj K. Maturi, Sonia Mehta, Geeta Menon, Jale Menteş, Mark Michels, Yoshinori Mitamura, Paul Mitchell, Quresh Mohamed, Jordi Monés, Rodrigo Montemayor Lobo, Javier Montero, Jeffrey S. Moore, Ryusaburo Mori, Haia Morori-Katz, Rajarshi Mukherjee, Toshinori Murata, Maria Muzyka−Woźniak, Marco Nardi, Niro Narendran, Massimo Nicolò, Jared S. Nielsen, Tetsuya Nishimura, Kousuke Noda, Anna Nowińska, Hideyasu Oh, Matthew Ohr, Annabelle A. Okada, Piotr Oleksy, Shinji Ono, Şengül Özdek, Banu Öztürk, Luís E. Pablo, Kyu Hyung Park, D. Wilk Parke, Maria Cristina Parravano, Praveen J. Patel, Apurva R. Patel, Sunil Patel, Sugat Patel, Daniel Pauleikhoff, Ian Pearce, Joel Pearlman, Iva Petkova, Dante J. Pieramici, N. A. Pozdeyevа, Jawad Qureshi, Dorota Raczyńska, Juan Ramirez Estudillo, Rajiv Rathod, Hessam Razavi, Carl D. Regillo, Gayatri Reilly, Federico Ricci, Ryan Rich, Bożena Romanowska‐Dixon, Irit Rosenblatt, José M. Ruiz‐Moreno, Stefan Sacu, Habiba Saedon, Usman Saeed, Min Sagong, Taiji Sakamoto, Sukhpal S. Sandhu, Laura Sararols, Mario Saravia, Ramin Schadlu, Patricio G. Schlottmann, Tetsuju Sekiryu, András Seres, Figen Şermet, Sumit P. Shah, Rohan Shah, Ankur Shah, Tom Sheidow, Veeral Sheth, Chieko Shiragami, Bartosz L. Sikorski, Rufino Silva, Lawrence J. Singerman, Robert A. Sisk, Torben Lykke Sørensen, Eric H. Souied, David-J. Spinak, Giovanni Staurenghi, Robert L. Steinmetz, Glenn Stoller, Robert Stoltz, Eric Suan, Iván J. Suñer, Suzanne Yzer, Kanji Takahashi, Kei Takayama, Alexandre Chater Taleb, James Talks, Hiroko Terasaki, John F. Thompson, Edit Tóth‐Molnár, Khoi Tran, Raman Tuli, Eduardo Uchiyama, Attila Vajas, Janneke Van Lith-Verhoeven, Balázs Varsányi, Francesco Viola, Gianni Virgili, Gábor Vogt, Michael Völker, David Warrow, Pamela Weber, John A. Wells, Sanjeewa Wickremasinghe, Mark R. Wieland, Geoff Williams, Thomas N. Williams, David T. Wong, King Wong, James S. W. Wong, Ian Chi Kei Wong, Robert Wong, Bogumił Wowra, Charles C. Wykoff, Ayana Yamashita, Kanako Yasuda, Gürsel Yılmaz, Glenn Yiu, Ai Yoneda, Young Hee Yoon, Yoreh Barak, Hyeong Gon Yu, Seung Young Yu, Tatiana Yurieva, Alberto Zambrano, Barbara Zatorska, Carlos Zeolite

Bibliographic record

VenueOphthalmology · 2024
Typearticle
Languageen
FieldMedicine
TopicRetinal Diseases and Treatments
Canadian institutionsRoche (Canada)
FundersF. Hoffmann-La RocheRoche
KeywordsMedicine

Abstract

fetched live from OpenAlex

PURPOSE: To evaluate 2-year efficacy, durability, and safety of the bispecific antibody faricimab, which inhibits both angiopoietin-2 and VEGF-A. DESIGN: TENAYA (ClinicalTrials.gov identifier, NCT03823287) and LUCERNE (ClinicalTrials.gov identifier, NCT03823300) were identically designed, randomized, double-masked, active comparator-controlled phase 3 noninferiority trials. PARTICIPANTS: Treatment-naive patients with neovascular age-related macular degeneration (nAMD) 50 years of age or older. METHODS: Patients were randomized (1:1) to intravitreal faricimab 6.0 mg up to every 16 weeks (Q16W) or aflibercept 2.0 mg every 8 weeks (Q8W). Faricimab fixed dosing based on protocol-defined disease activity at weeks 20 and 24 up to week 60, followed up to week 108 by a treat-and-extend personalized treatment interval regimen. MAIN OUTCOME MEASURES: Efficacy analyses included change in best-corrected visual acuity (BCVA) from baseline at 2 years (averaged over weeks 104, 108, and 112) and proportion of patients receiving Q16W, every 12 weeks (Q12W), and Q8W dosing at week 112 in the intention-to-treat population. Safety analyses included ocular adverse events (AEs) in the study eye through study end at week 112. RESULTS: Of 1326 patients treated across TENAYA/LUCERNE, 1113 (83.9%) completed treatment (n = 555 faricimab; n = 558 aflibercept). The BCVA change from baseline at 2 years was comparable between faricimab and aflibercept groups in TENAYA (adjusted mean change, +3.7 letters [95% confidence interval (CI), +2.1 to +5.4] and +3.3 letters [95% CI, +1.7 to +4.9], respectively; mean difference, +0.4 letters [95% CI, -1.9 to +2.8]) and LUCERNE (adjusted mean change, +5.0 letters [95% CI, +3.4 to +6.6] and +5.2 letters [95% CI, +3.6 to +6.8], respectively; mean difference, -0.2 letters [95% CI, -2.4 to +2.1]). At week 112 in TENAYA and LUCERNE, 59.0% and 66.9%, respectively, achieved Q16W faricimab dosing, increasing from year 1, and 74.1% and 81.2%, achieved Q12W or longer dosing. Ocular AEs in the study eye were comparable between faricimab and aflibercept groups in TENAYA (55.0% and 56.5% of patients, respectively) and LUCERNE (52.9% and 47.5% of patients, respectively) through week 112. CONCLUSIONS: Treat-and-extend faricimab treatment based on nAMD disease activity maintained vision gains through year 2, with most patients achieving extended dosing intervals. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0190.003

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.

Opus teacher head0.017
GPT teacher head0.336
Teacher spread0.319 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

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Citations179
Published2024
Admission routes1
Has abstractyes

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