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Record W4399045639 · doi:10.1016/j.eclinm.2024.102658

Long-term outcome and prognosis of mixed histiocytosis (Erdheim-Chester disease and Langerhans Cell Histiocytosis)

2024· article· en· W4399045639 on OpenAlexaff
Francesco Pegoraro, Matthias Papo, Fleur Cohen‐Aubart, Francesco Peyronel, Gianmarco Lugli, Irene Trambusti, G. Baulier, Mathilde de Menthon, Tanguy Le Scornet, E. Oziol, Nicole Ferreira-Maldent, Olivier Hermine, Benoit Faucher, Dirk Koschel, Nicole Straetmans, Noémie Abisror, Benjamin Terrier, François Lifermann, Jérôme Razanamahery, Yves Allenbach, Jeremy Keraen, Sophie Bulifon, B. Hervier, Annamaria Buccoliero, Frédéric Charlotte, Quentin Monzani, Samia Boussouar, Natalia Shor, Annalisa Tondo, Stéphane Barète, Ahmed Idbaïh, Abdellatif Tazi, Elena Sieni, Zahir Amoura, Jean‐François Emile, Augusto Vaglio, Julien Haroche

Bibliographic record

VenueEClinicalMedicine · 2024
Typearticle
Languageen
FieldMedicine
TopicHistiocytic Disorders and Treatments
Canadian institutionsHotel Dieu Hospital
FundersMinistero della SaluteSanofiNovartisAstraZenecaNovocureAmgen
KeywordsErdheim–Chester diseaseMedicineHistiocytosisLangerhans cell histiocytosisDermatologyDiseaseHistiocytosis XPathology

Abstract

fetched live from OpenAlex

Background: Erdheim-Chester disease (ECD) is a rare histiocytosis that may overlap with Langerhans Cell Histiocytosis (LCH). This "mixed" entity is poorly characterized. We here investigated the clinical phenotype, outcome, and prognostic factors of a large cohort of patients with mixed ECD-LCH. Methods: This retrospective study was performed at two referral centers in France and Italy (Pitié-Salpêtrière Hospital, Paris; Meyer Children's Hospital, Florence). We included children and adults with ECD diagnosed in 2000-2022 who had biopsy-proven LCH, available data on clinical presentation, treatment and outcome, and a minimum follow-up of one year. Outcomes included differences in clinical presentation and survival between mixed ECD-LCH and isolated ECD; we also investigated response to treatments and predictors of survival in the mixed cohort. Survival was analyzed using the Kaplan-Maier method and differences in survival with the long-rank test. Cox regression models were used to evaluate the potential impact of age and gender on survival and to identify predictors of non-response and survival. Findings: = 0.948). At multivariable analysis, age at diagnosis (HR 1.052, 95% CI 1.008-1.096), associated hematologic conditions (HR 3.030, 95% CI 1.040-8.827), and treatment failure (HR 9.736, 95% CI 2.919-32.481) were associated with an increased risk of death, while lytic bone lesions with a lower risk (HR 0.116, 95% CI 0.031-0.432). Interpretation: mutation and targeted treatments are effective. Age at diagnosis, bone lesion patterns, associated hematologic conditions, and treatment failure are the main predictors of death in mixed ECD-LCH. Funding: None.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.855

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.046
GPT teacher head0.343
Teacher spread0.297 · 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.

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".

Quick stats

Citations20
Published2024
Admission routes1
Has abstractyes

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