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Safety and efficacy of zilucoplan in patients with generalised myasthenia gravis (RAISE): a randomised, double-blind, placebo-controlled, phase 3 study
James F. Howard, Saskia Bresch, Angela Genge, Channa Hewamadduma, John L. Hinton, Yessar Hussain, Raúl Juntas‐Morales, Henry J. Kaminski, Angelina Maniaol, Renato Mantegazza, Masayuki Masuda, Kumaraswamy Sivakumar, Marek Śmiłowski, Kimiaki Utsugisawa, Tuan Vu, Michael D. Weiss, Małgorzata Zajda, Babak Boroojerdi, Melissa Brock, Guillemette de la Borderie, Petra W. Duda, Romana Lowcock, Mark Vanderkelen, Maria Isabel Leite, Dylan Sembinelli, Jeanne Teitelbaum, Michael Nicolle, E Bernard, Juliette Svahn, Marco Spinazzi, Tanya Stojkovic, Sophie Demeret, Nicolas Weiss, Loïc Le Guennec, Sihame Messai, Christine Tranchant, Aleksandra Nadaj‐Pakleza, Jean‐Baptiste Chanson, Muhtadi Suliman, Leila Zaidi, Céline Tard, Peggy Lecointe, Jana Zschüntzsch, Jens Schmidt, Stefanie Glaubitz, Rachel Zeng, Matthias Scholl, Markus C. Kowarik, Ulf Ziemann, Markus Krumbholz, Pascal Martin, Christoph Ruschil, Jutta Dünschede, Roswitha Kemmner, Natalie Rumpel, Benjamin Berger, Andreas Totzeck, Tim Hagenacker, Benjamin Stolte, Raffaele Iorio, Amelia Evoli, Silvia Falso, Carlo Antozzi, Rita Frangiamore, Fiammetta Vanoli, Elena Rinaldi, Kazushi Deguchi, Naoya Minami, Yuriko Nagane, Yasushi Suzuki, Sayaka Ishida, Shigeaki Suzuki, Jin Nakahara, Astushi Nagaoka, Shunsuke Yoshimura, Shingo Konno, Youko Tsuya, Akiyuki Uzawa, Tomoya Kubota, Masanori Takahashi, Tatsusada Okuno, Hiroyuki Murai, Nils Erik Gilhus, Marion Boldingh, Tone Hakvåg Rønning, Urszula Chyrchel-Paszkiewicz, Klaudiusz Kumor, Tomasz Zieliński, Krzysztof Banaszkiewicz, Michał Błaż, Agata Kłósek, Mariola Matysiak, Andrzej Szczudlik, Aneta Paśko, L Szczechowski, Marta Banach, Jan Ilkowski, S. Kapetanovic García, Patricia Ortiz Bagan, Ana Belén Cánovas Segura, Joana Turon Sans, Nuria Vidal Fernández, Elena Cortés Vicente, Patricia Rodrigo Armenteros, Mohammad Ashraghi, Ana Cavey, Liam Haslam, Anna Emery, Kore Liow, Sharon Yegiaian, Alexandru Barboi, Rosa Vázquez, Joshua Lennon, Robert M. Pascuzzi, Cynthia Bodkin, Sandra Guingrich, Adam Comer, Mark B. Bromberg, Teresa Janecki, Sami Saba, Marco Tellez, Bakri Elsheikh, Miriam Freimer, Sarah Heintzman, Raghav Govindarajan, Jeffrey T. Guptill, Janice M. Massey, Vern C. Juel, Natalia González, Ali A. Habib, Tahseen Mozaffar, Manisha Kak Korb, Namita Goyal, Hannah Machemehl, Georgios Manousakis, Jeffrey A. Allen, Emily Harper, Constantine Farmakidis, Lilli Saavedra, Mazen M. Dimachkie, Mamatha Pasnoor, Salma Akhter, Said R. Beydoun, Courtney McIlduff, Joan Nye, Bhaskar Roy, Bailey Munro Sheldon, Richard J. Nowak, Benjamin Barnes, Michael H. Rivner, Niraja Suresh, Jessica Shaw, Brittany Harvey, Lucy Lam, Nikki Lynn Thomas, Manisha Chopra, Rebecca Traub, Sarah Jones, Mary Wagoner, Sejla Smajic, Radwa Aly, Jonathan Katz, Henry Chen, Robert G. Miller, Liberty Jenkins, Shaida Khan, Bhupendra Khatri, Lisa Sershon, Pantelis P. Pavlakis, Shara Holzberg, Yuebing Li, Irys Caristo, Robert Marquardt, Debbie Hastings, Jacob Rube, Robert P. Lisak, Aparna Choudhury, Katherine Ruzhansky, Amit Sachdev, Susan Shin, Joan Bratton, Mary Fetter, Naya McKinnon, Jonathan McKinnon, Laura Sissons-Ross, Amos Sahu, B. Jane Distad
Bibliographic record
VenueThe Lancet Neurology · 2023
Typearticle
Languageen
FieldMedicine
TopicMyasthenia Gravis and Thymoma
Canadian institutionsMontreal Neurological Institute and Hospital
FundersUCB PharmaNIHR Sheffield Biomedical Research CentreNational Institute for Health and Care Research
KeywordsMyasthenia gravisPlaceboMedicineDouble blindPhase (matter)AnesthesiaInternal medicineAlternative medicinePhysicsPathology
Abstract
No abstract in any covered source. Its absence is recorded, not treated as a negative.
No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.
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.
metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| 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.
Opus teacher head0.027
GPT teacher head0.299
Teacher spread0.272 · how far apart the two teachers sit on this one work
Validation status
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.
The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreEmpirical
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".
Quick stats
Citations250
Published2023
Admission routes1
Has abstractno