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The Global Kidney Patient Trials Network and the CAPTIVATE Platform Clinical Trial Design

2024· article· en· W4405277114 on OpenAlexaboutno aff
Sradha Kotwal, Vlado Perkovic, Meg Jardine, Dana Kim, Nasir A. Shah, Enmoore Lin, Sarah Coggan, Laurent Billot, Priya Vart, David C. Wheeler, Ian H. de Boer, Hong Zhang, Fan Fan Hou, Yuka Sugawara, Joseph Marion, Roger J. Lewis, Lindsay R. Berry, Anna McGlothlin, Vivekanand Jha, Luca De Nicola, José Luis Górriz, Hiddo J.L. Heerspink, Andres Alvarisqueta, Julio Bittar, Natalia Cluigt, Judith Ana Gaite, Luis Gaite, Silvia Marcela Maurich, Pablo Ramallo, Alejandra Quevedo, Carlos Arias, Jorge Hector Resk, Paula Andrea Marioli, Lawrence P. McMahon, Sridevi Govindarajulu, Nicholas Gray, Simon D. Roger, Adam Flavell, Nigel D. Toussaint, Jessica Stranks, Peak Mann Mah, Parind Vora, Serge Cournoyer, Marie‐France Langlois, M. Lynn Weir, Hong Zhang, Zhihong Liu, Yaozhong Kong, Ping Fu, Lu WanHong, LI Gui-sen, Menghua Chen, Peng Li, Yiwen Liu, Cheng William Hong, Jianqin Wang, Junwu Dong, Zhigang Ma, Rui Yan, Shi Yongjun, Chun Zhang, LV Xue-ai, Xiao-Yong Yu, Yi-Hua Bai, Maura Ravera, Antonio Pisani, Mariacristina Gregorini, Ciro Esposito, Filippo Aucella, Felice Nappi, Cataldo Abaterusso, Loreto Gesualdo, Michele Andreucci, Mariadelina Simeoni, Seiji Itano, Naoki Kashihara, Jun Wada, Masaomi Nangaku, Motoji Naka, Masahiko Takai, Shin Goto, Masafumi Fukagawa, Takashi Yokoo, Shinya Kaname, Masanori Abe, Yusuke Suzuki, Maria Rita Romeo, Emma Pardo, Alfonso González, Josep M. Cruzado, Secundino Cigarrán, Fernando Cereto Castro, Jonay Pantoja Perez, Francisco Jose Tinahones Maduen, María Marqués, Roberto Pecoits-Filho, Sergio Rovner, Ahmed A. Arif, Pablo E. Pérgola, Tuan-Huy Tran, Manuel Montero, Jamal Hammoud, Michael H. Shanik, Pedro Velasquez‐Mieyer, Karin K. Lucas, James Franklin, Arthur Green, Andrew Drabick, Joseph Alello, Robert S. Busch, Nina Patel, Osvaldo Brusco, Jose Gomez-Cortez, Csaba P. Kövesdy, Radica Alicic, Eric A. Kirk, Nauman Shahid, Anand Reddy, Pedro Hernández, Ronald K. Mayfield, Brian T. Layden, Margaret K. Yu, Vinod Malhotra, Billy Hour, Kianoosh Kaveh, Visal Numrungroad, Reginald Gohh, José M. Santiago, Shaunak Dwivedi, S.K.B. Ong, Marwan Edris, Anant Desai, M. Gold, Bram Wieskopf, Shengkun Sun, Emma Dombroski, Maria Ali, Lok Bin Yap, Ly Mai, Dominic Mounsey, Alina Yoffe, Francisco Achiaga, Clara Mok, Emily Walker, Charles Czank, Lisa Rominger, Paula Cisternas, Daniele Rizzi, Joy Ola, David O. Garcia, Jessica Cox, Lyndal Hones, Mei‐Ling Ho, Melissa Tutt, Fred D. Beusenberg, E. Raymond, Christine Adeyari, Yuehan Zheng, Stephanie Pollard, Olga Cabrerizo, Yiping Xiao, Xuejie Bai, Joe Zhou, Divya Lokesh, Larry Larsheid, Naveed Shabbir, Dana Hurndon, Renee Garmack, Liza Shilpakar, Jennifer Casulla, Hui Ping, Haochen Jin, Diane Lickey, Jin Long, Li Bie, Helen Monaghan, Clare Arnott, Gian Luca Di Tanna, Rathika Krishnasamy, Dean Guinness, Jeremy Halewood, David Ioasa, Zhangyi He, Farjaneh Hossain, Ben Varley, Nursafwana Zulkhernain, Michelle Kim, Victoria Gregory

Bibliographic record

VenueJAMA Network Open · 2024
Typearticle
Languageen
FieldMedicine
TopicChronic Kidney Disease and Diabetes
Canadian institutionsnot available
Fundersnot available
KeywordsClinical trialMedicineComputer scienceInternal medicine

Abstract

fetched live from OpenAlex

Importance: Chronic kidney disease (CKD) is a global health priority affecting almost 1 billion people. New therapeutic options and clinical trial innovations such as adaptive platform trials provide an opportunity to efficiently test combination therapies. Objective: To describe the design and baseline results of the Global Kidney Patient Trials Network (GKPTN) and the design and structure of the global adaptive platform clinical trial Chronic Kidney Disease Adaptive Platform Trial Investigating Various Agents for Therapeutic Effect (CAPTIVATE) to find new therapeutic options and treatments for people with kidney disease. Design, Setting, and Participants: The GKPTN is a multicenter registry that started in May 2020 and is ongoing, while CAPTIVATE is a multicenter, multifactorial, phase 3, placebo-controlled adaptive platform randomized clinical trial that includes patients with CKD. The first participant was randomized in September 2024. The GKPTN recruits patients from kidney and endocrinology practices, and CAPTIVATE aims to recruit patients from GKPTN sites where possible. Both the GKPTN and CAPTIVATE recruit patients with nondialysis CKD. Intervention: CAPTIVATE will test several investigational agents or combinations of agents, beginning with a mineralocorticoid receptor antagonist. Main Outcomes and Measures: The GKPTN monitors clinical characteristics, treatment, and outcomes to identify eligible clinical trial participants and provide a contemporary global picture of patients with CKD. The primary outcome of CAPTIVATE is to identify investigational agents or combinations of agents to reduce the rate of chronic estimated glomerular filtration rate (eGFR) decline. The default maximum sample size per treatment arm in each domain, based on bayesian simulations, is 500 participants, providing approximately 90% power to detect a clinically meaningful improvement of 2.6 mL/min/1.73 m2 in eGFR at the end of the 104-week study period. Results: The GKPTN has enrolled 4334 patients across 119 sites in 8 countries (US, Australia, Argentina, China, Italy, Canada, Spain, and Japan). The mean (SD) participant age at enrollment was 64.5 (16.2) years, 2542 participants (58.7%) were female, and diabetic kidney disease was most frequently reported among patients for CKD etiology (1875 [43.3%]). Among the participants, the mean (SD) eGFR was 52.9 (29.3) mL/min/1.73 m2, and the median urinary albumin-to-creatinine ratio was 89 mg/g (coefficient of variation, 20-420 mg/g). In the GKPTN cohort, the mean eGFR decline was steeper among participants with a baseline eGFR of 60 mL/min/1.73 m2 or more (-2.29 [95% CI, -3.14 to -1.44]) compared with those with an eGFR of less than 60 mL/min/1.73 m2 (-1.16 [95% CI, -1.77 to -1.44]) and was progressively steeper in more severe albuminuria subgroups. Conclusions and Relevance: The GKPTN registry and the CAPTIVATE trial have the potential to expand and optimize therapeutic options for people with CKD using an adaptive platform clinical trial design. Trial Registration: ClinicalTrials.gov Identifiers: NCT04389827 and NCT06058585.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.015
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.615
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0150.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.119
GPT teacher head0.400
Teacher spread0.281 · 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 teacher head, not a consensus.

Study designNot applicable
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".

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Citations13
Published2024
Admission routes1
Has abstractyes

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