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Record W4413761497 · doi:10.1038/s41409-025-02684-1

Definition of relapse criteria in patients with rapidly progressive systemic sclerosis treated with autologous haemopoietic stem cell transplantation

2025· letter· en· W4413761497 on OpenAlexaff
Nicoletta Del Papa, Myriam Labopin, Manuela Badoglio, Dominique Farge, Jörg Henes, John A. Snowden, Julia Spierings, Claudia Iannone, Tobias Alexander, Paolo Airó, Norbert Blank, Richard K. Burt, Corrado Campochiaro, Patrícia Carreira, Paola Cipriani, Veronica Codullo, Francesco Del Galdo, Oliver Distler, Armando Gabrielli, Roberto Giacomelli, Serena Guiducci, Anna‐Maria Hoffman‐Vold, Zora Marjanovic, Ulf Müller Ladner, Maria Carolina Oliveira, Ross Penglase, G. Pugnet, Mathieu Puyade, Doron Rimar, Marc Schmalzing, Jan Storek, Marie‐Elise Truchetet, Gabriele Valentini, Serena Vettori, Madelon C Vonk, Alexandre E. Voskuyl, Raffaella Greco

Bibliographic record

VenueBone Marrow Transplantation · 2025
Typeletter
Languageen
FieldMedicine
TopicSystemic Sclerosis and Related Diseases
Canadian institutionsUniversity of Calgary
FundersLeibniz-GemeinschaftSorbonne UniversitéFreie Universität BerlinHumboldt-Universität zu BerlinSheffield Teaching Hospitals NHS Foundation TrustBerlin Institute of HealthInstitut National de la Santé et de la Recherche MédicaleUniversità degli Studi di Milano
KeywordsMedicineTransplantationStem cellAutologous stem-cell transplantationSurgery

Abstract

fetched live from OpenAlex

Systemic sclerosis (SSc) is a rare systemic autoimmune disease characterized by the accumulation of extracellular collagen matrix in tissues and target organs, such as skin, lung, gut, and heart [ 1 ]. The clinical spectrum of SSc is largely heterogeneous, but usually two distinct forms are recognized., i.e., the limited cutaneous (lc) and the diffuse cutaneous (dc) SSc. The two variants strongly differ in the terms of skin extension, type and severity of internal organ involvement, and expected survival. Among patients with dcSSc, a subset may be characterized by a rapidly progressive course with early appearance and quick worsening of skin and internal organ involvement, and consequently a high mortality rate within the first five years after first non-Raynaud phenomenom symptoms [ 2 ]. In these cases of rapidly progressive dcSSc, autologous haematopoietic stem cell transplantation (AHSCT) has been recognized as a standard-of-care therapy option since 2017 [ 3 , 4 , 5 , 6 ]. This statement was the direct consequence of the consistent results obtained in three randomized controlled trials where this procedure had been shown to be superior to traditional immunosuppressive therapy in improving skin involvement, preserving lung function, and reducing mortality rates [ 6 ]. These results have been further confirmed in a recent retrospective study where AHSCT was shown to be superior to rituximab in improving all the above-mentioned outcomes [ 7 ]. Nevertheless, several aspects of AHSCT warrant further consideration. First, transplantation related mortality still exists, although it has been significantly reduced thanks to the important progress made, with better pretransplant evaluation of cardiac and pulmonary involvement and improved selection of patients at lower risk of complications [ 8 ]. Another question to be answered is how long the effects of AHSCT will last. Preliminary data indicate that the incidence of disease progression could happen between 4 and 6 years after transplantation and that disease response varied according to patients [ 9 ]. However, although the observed clinical response after AHSCT has been defined since the early pivotal trials (ASSIT, ASTIS, SCOT) and the absence of response or disease progression after AHSCT is easy to define as its counterpart, no dedicated and validated tools are currently available to precisely define the disease relapse after AHSCT. Acquiring the moment of relapse after prior response to AHSCT may make it easier to adopt therapeutic interventions that may allow to maintain the disease remission induced by AHSCT.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.160
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.014
GPT teacher head0.213
Teacher spread0.198 · 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 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".

Quick stats

Citations4
Published2025
Admission routes1
Has abstractyes

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