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

Understanding secondary immunodeficiency management in patients with hematological malignancies

2025· article· en· W7108733746 on OpenAlexaffabout

Bibliographic record

VenueBlood · 2025
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmunodeficiency and Autoimmune Disorders
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsHypogammaglobulinemiaRituximabMultiple myelomaChronic lymphocytic leukemiaLymphomaDiseaseAcute lymphocytic leukemiaAntibodyImmunodeficiency

Abstract

fetched live from 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.

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 score0.470
Threshold uncertainty score0.613

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.013
GPT teacher head0.204
Teacher spread0.191 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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