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Record W4407439191 · doi:10.1055/s-0044-1801671

Caplacizumab Added to Plasma Exchange and Immunosuppression Accelerates Recovery and Improves Survival in Immune-Mediated TTP: an International Real-World Study of the IWG-TTP (The Capla 1000+Project)

2025· article· en· W4407439191 on OpenAlexaff
Paul Coppo, Michaël Bubenheim, Y. Benhamou, Linus A. Völker, Paul Brinkkötter, Lucas Kühne, Paul Knöbl, María Eva Mingot‐Castellano, Cristina Pascual, Javier de la Rubia, Julio del Río-Garma, Shruti Chaturvedi, Camila Masias, Marshall Mazepa, X. Long Zheng, György Sinkovits, Marienn Réti, Christopher J. Patriquin, Katerina Pavenski, T Boechat, João Samuel de Holanda Farias, Eduardo Flávio Oliveira Ribeiro, Michaela Larissa Lobo de Andrade, Agnès Veyradier, Bérangère S. Joly, Rachid Bouzid, Kazuya Sakai, Masanori Matsumoto, Pasquale Agosti, Ilaria Mancini, Flora Peyvandi, Eleni Gavriilaki, Matthew Stubbs, Amjad Hmaid, Spero R. Cataland, Bernhard Lämmle, Marie Scully

Bibliographic record

VenueHämostaseologie · 2025
Typearticle
Languageen
FieldImmunology and Microbiology
TopicComplement system in diseases
Canadian institutionsSt. Michael's HospitalUniversity Health Network
Fundersnot available
KeywordsImmunosuppressionMedicineImmunology

Abstract

fetched live from OpenAlex

Introduction: Immune thrombotic thrombocytopenic purpura (iTTP) results from antibody-mediated severe deficiency of ADAMTS13, the Von Willebrand factor (VWF)-cleaving protease. The anti-VWF nanobody caplacizumab is licensed for adults with iTTP. Prospective controlled trials and national real-world studies have provided evidence that caplacizumab improved outcome of the acute phase of the disease. However, whether caplacizumab decreases mortality, and the optimal timing of caplacizumab initiation, remain to be determined. To address these questions, an international survey, the Capla 1000+project, has been conducted. Method: In this international, multicenter retrospective cohort study, 1015 patients were treated with daily therapeutic plasma exchange (TPE), immunosuppression with corticosteroids±rituximab, and caplacizumab (caplacizumab group), which was compared to historic controls treated with TPE and corticosteroids±rituximab (control group, N=510). Caplacizumab initiation was classified as early (within 3 days; 76% of cases) or delayed (³4 days from first TPE). Results: Three-month survival rate in the caplacizumab group was 98.5%, compared with 94% in controls (p<0.0001). Three-month mortality rate was 4.2-fold higher in controls than in caplacizumab-treated patients (95%CI: 2.22-7.7, p<0.0001), regardless of rituximab use. Death in the caplacizumab group was observed primarily in elderly patients, and age was the prognostic factor most associated with 3-month mortality. Patients receiving caplacizumab showed reduced refractoriness, exacerbations, and required fewer TPE sessions to achieve clinical response versus controls (p<0.0001 all). Time to clinical response in the caplacizumab group was shorter than in controls, and even shorter in patients with early caplacizumab initiation (p<0.0001 both). Caplacizumab-related adverse events were observed in 21% of patients, with major bleeding in 2.4%, which was more common in elderly patients. Clinically relevant non-major bleeding (3.7%), non-clinically relevant non-major bleeding (14%), and inflammatory reaction at the injection site (4.5%) were also reported. Conclusion: This international academic effort provides convincing evidence that Caplacizumab added to TPE and immunosuppression significantly reduces unfavorable outcomes during iTTP, including death, and alleviates the burden of care at the potential expense of bleeding events. Advanced age, however, remains an adverse prognostic factor for survival. Publication History Article published online: 13 February 2025 © 2025. Thieme. All rights reserved. Georg Thieme Verlag KG Oswald-Hesse-Straße 50, 70469 Stuttgart, Germany

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)0.003
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.033
GPT teacher head0.317
Teacher spread0.284 · 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 designObservational
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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Citations0
Published2025
Admission routes1
Has abstractno

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