Evidence map›Paper›PMID 41384995›Full record

ArticleJournal of clinical immunology2025

Exploring the Pathogens in Primary Predominantly Antibody Deficiencies of Unknown Genetic Origin.

Barbara Bergmans, Lisanne Fontane Pennock-Janssen, Eugène van Puijenbroek, Roeland van Hout, Jean-Luc Murk, Esther de Vries, unPAD consortium

Abstract read
In one paragraph

Article in Journal of clinical immunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Barbara BergmansTranzo, Tilburg School of Social and Behavioral Sciences, Tilburg University, Tilburg, The Netherlands. b.j.m.bergmans@tilburguniversity.edu.
Lisanne Fontane Pennock-JanssenDepartment of Pediatrics, Jeroen Bosch Ziekenhuis, 's-Hertogenbosch, The Netherlands.
Eugène van PuijenbroekNetherlands Pharmacovigilance Centre Lareb, 's-Hertogenbosch, The Netherlands.
Roeland van HoutCentre for Language Studies, Radboud University, Nijmegen, The Netherlands.
Jean-Luc MurkMicrovida, Elisabeth-TweeSteden Hospital, Tilburg, The Netherlands.
Esther de VriesTranzo, Tilburg School of Social and Behavioral Sciences, Tilburg University, Tilburg, The Netherlands.
unPAD consortium

Funding

The unPAD study has received grants from both the Plasma Protein Therapeutics Association (PPTA) and Takeda Development Center Americas, Inc. a wholly owned subsidiary of Takeda Pharmaceutical Company Limited via an Investigator-Initiated Research grant IISR-2017-104231
6 · The paper itself

Abstract

introductionPrimary 'predominantly antibody deficiencies' (PADs) are rare disorders characterized by increased susceptibility to infections, autoimmunity, allergies, and malignancies. Their low prevalence and heterogeneity often delay diagnosis, increasing morbidity and mortality. This study identifies infection patterns in PAD patients and analyzes predictors of bronchiectasis presence at PAD diagnosis (BPAD), aiming to facilitate early diagnosis and improve prognosis.

methodsUsing fully monitored data on PAD patients without identified genetic origin from the ESID Registry, infection types and pathogens across PADs were compared (chi-square analysis) and predictive factors for BPAD were identified (generalized mixed-effects logistic regression). Additionally, five machine learning classifiers (logistic regression, (bagged) decision tree, random forest and support vector machines) were trained and evaluated by area under the receiver operating characteristics curve (ROC-AUC), confusion matrices and F1-score.

resultsRecurrent respiratory infections were predominant in our cohort of 861 patients from 11 centers. Cultures were conducted in only 5.9-12.3% of infections. Encapsulated bacteria were most frequently isolated. The number of organ systems affected by recurrent infections, occurrence of specific serious bacterial infections, number of identified encapsulated bacteria and common variable immunodeficiency disorders (CVID) diagnosis were predictive of BPAD. Machine learning models achieved moderate discrimination (ROC-AUC range 0.679-0.746). DISCUSSION: This study highlights the predominance of recurrent and encapsulated bacterial respiratory tract infections in PAD and the underutilization of microbiological cultures. Generalized mixed-effects logistic regression best predicted BPAD. Clinicians should consider immunologic evaluation in patients presenting with serious bacterial infections, multi-system recurrent infections or the repeated isolation of encapsulated bacteria in unusually severe or recurrent infections.

Indexed as

BronchiectasisPrimary Immunodeficiency DiseasesRespiratory Tract InfectionsAdultAgedFemaleHumansMachine LearningMaleMiddle AgedRegistriesROC CurveInborn errors of immunityPathogensPredominantly antibody deficiencyPrimary antibody deficiencyRecurrent infectionsSerious infections

Identifiers

PMID41384995
PMCPMC12795866

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.