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Enregistrement W7108733746 · doi:10.1182/blood-2025-6182

Understanding secondary immunodeficiency management in patients with hematological malignancies

2025· article· en· W7108733746 sur OpenAlexaffabout

Notice bibliographique

RevueBlood · 2025
Typearticle
Langueen
DomaineImmunology and Microbiology
ThématiqueImmunodeficiency and Autoimmune Disorders
Établissements canadiensUniversity of Alberta
Organismes subventionnairesnon disponible
Mots-clésHypogammaglobulinemiaRituximabMultiple myelomaChronic lymphocytic leukemiaLymphomaDiseaseAcute lymphocytic leukemiaAntibodyImmunodeficiency

Résumé

récupéré en direct d'OpenAlex

Abstract Background: Secondary antibody deficiency (SAbD) is a prevalent immune disorder characterized by impaired specific antibody production and hypogammaglobulinemia (HGG) leading to increased vulnerability to infection. Patients with hematological malignancies (HM) frequently develop SAbD, either from the disease itself or its treatment. Understanding current diagnostic and management practices among hematologist-oncologists is critical to improve patient outcomes. Methods: An ongoing survey of Canadian hematologist/oncologists and medical oncologists was launched in May 2025 via the KeyOps platform (Ontario, Canada) with a closing date of August 31, 2025. The 42-item questionnaire assessed approaches to diagnosing and managing SAbD in patients with B-cell HM, including multiple myeloma (MM), chronic lymphocytic leukemia (CLL) and non-Hodgkin lymphoma (NHL). The survey sought to understand the indications for HGG testing, gauge the diagnostic tests and thresholds physicians consider when screening for HGG, explore their approaches to infection prevention in patients with HM, and examine their practices regarding prescription, administration, and monitoring immunoglobulin replacement therapy (IgRT). Results: Data from 20 survey participants were available for analysis at the time of the data cut performed on June 16, 2025. 45% of respondents reported practicing in academic hospitals and 40% were residing in Ontario. The average years of experience in providing care for patients with HM was 12. Testing for HGG at diagnosis was reported by 74% of respondents for MM, 67% for CLL and 56% for NHL. Across all HM, hospitalization for infection and number of self-reported infections were key triggers for HGG evaluation. When testing for HGG, common diagnostic tests included complete blood count and serum Ig levels. HGG was defined by 55% of respondents as IgG < 4 g/L and by 35% as < 5 g/L. Challenges faced in diagnosing HGG included tracking or managing recurrent or severe infections and recognizing the appropriate timing to investigate HGG. Monitoring frequency varied: MM patients were typically tested every 3 months for >24 months (42%), while CLL and NHL patients were monitored for 6-12 months (28%), and, often when symptomatic. Notably, 60% of respondents did not follow specific guidelines, highlighting a knowledge gap. Vaccination was the preferred treatment for infection prevention in HGG patients in this survey. Infection prevention treatment decisions were influenced by the patient's cancer treatment regimen, as noted by 70% of respondents. IgRT was widely used by respondents with an average of 38 patients (range 0-200) per institution receiving prophylactic treatment. 90% of respondents were involved in prescribing IgRT, primarily triggered by infection-related hospitalizations, although over half did not routinely prescribe prophylactic antibiotics prior to starting IgRT. Preferences for route of administration for IgRT were split: 30-40% preferred the intravenous (IV) treatment, 30% subcutaneous (SC) treatment, and 30-40% based the route on the patient-specific factors. The most common initial dose for IgRT was 0.4 g/kg, with 67% using a maintenance dose of 0.2-0.4 g/kg/monthly. Key factors cited in effective IgRT were maintaining target Ig trough levels (41-50%) and reducing self-reported infections (31-38%). For patients on novel B-cell depleting chimeric antigen receptor T cell therapy and bispecific T cell engager therapy, 61% initiated IgRT as soon as HGG was observed. Evaluation of IgRT response typically occurred after 6-12 months. Barriers included IV logistics and SC training. Many respondents (33%) never refer HM patients to other specialists. Half of respondents learned about SID as residents and one-third when they started practicing. The lack of clear guidelines and uncertainty in diagnosis and treatment of SID were the most cited knowledge gaps. Conclusions: While awareness of SAbD exists among hematologist-oncologists, consistent guidelines for diagnosis and management are lacking. IgRT is recognized as effective, yet significant practice variability persists. Targeted, case-based education and development of local care pathways for assessment and management of SAbD may improve outcomes for HM patients.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,470
Score d'incertitude au seuil0,613

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,013
Tête enseignante GPT0,204
Écart entre enseignants0,191 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2025
Routes d'admission2
Résumé présentoui

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