Dissecting Secondary Immunodeficiency: Identification of Primary Immunodeficiency within B-Cell Lymphoproliferative Disorders

Distinguishing between primary (PID) and secondary (SID) immunodeficiencies, particularly in relation to hematological B-cell lymphoproliferative disorders (B-CLPD), poses a major clinical challenge. We aimed to analyze and define the clinical and laboratory variables in SID patients associated with...

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Published inJournal of clinical immunology Vol. 45; no. 1; p. 32
Main Authors Palacios-Ortega, María, Guerra-Galán, Teresa, Jiménez-Huete, Adolfo, García-Aznar, José María, Pérez-Guzmán, Marc, Mansilla-Ruiz, Maria Dolores, Mendiola, Ángela Villegas, López, Cristina Pérez, Hornero, Elsa Mayol, Rodriguez, Alejandro Peixoto, Cortijo, Ascensión Peña, Polo Zarzuela, Marta, Morales, Marta Mateo, Mandly, Eduardo Anguita, Cárdenas, Maria Cruz, Carrero, Alejandra, García, Carlos Jiménez, Bolaños, Estefanía, Íñigo, Belén, Medina, Fiorella, de la Fuente, Eduardo, Ochoa-Grullón, Juliana, García-Solís, Blanca, García-Carmona, Yolanda, Fernández-Arquero, Miguel, Benavente-Cuesta, Celina, de Diego, Rebeca Pérez, Rider, Nicholas, Sánchez-Ramón, Silvia
Format Journal Article
LanguageEnglish
Published New York Springer US 01.12.2025
Springer Nature B.V
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Abstract Distinguishing between primary (PID) and secondary (SID) immunodeficiencies, particularly in relation to hematological B-cell lymphoproliferative disorders (B-CLPD), poses a major clinical challenge. We aimed to analyze and define the clinical and laboratory variables in SID patients associated with B-CLPD, identifying overlaps with late-onset PIDs, which could potentially improve diagnostic precision and prognostic assessment. We studied 37 clinical/laboratory variables in 151 SID patients with B-CLPD. Patients were classified as “Suspected PID Group” when having recurrent-severe infections prior to the B-CLPD and/or hypogammaglobulinemia according to key ESID criteria for PID. Bivariate association analyses showed significant statistical differences between “Suspected PID”- and “SID”-groups in 10 out of 37 variables analyzed, with “Suspected PID” showing higher frequencies of childhood recurrent-severe infections, family history of B-CLPD, significantly lower serum Free Light Chain (sFLC), immunoglobulin concentrations, lower total leukocyte, and switch-memory B-cell counts at baseline. Rpart machine learning algorithm was performed to potentially create a model to differentiate both groups. The model developed a decision tree with two major variables in order of relevance: sum κ + λ and history of severe-recurrent infections in childhood, with high sensitivity 89.5%, specificity 100%, and accuracy 91.8% for PID prediction. Identifying significant clinical and immunological variables can aid in the difficult task of recognizing late-onset PIDs among SID patients, emphasizing the value of a comprehensive immunological evaluation. The differences between “Suspected PID” and SID groups, highlight the need of early, tailored diagnostic and treatment strategies for personalized patient management and follow up.
AbstractList Distinguishing between primary (PID) and secondary (SID) immunodeficiencies, particularly in relation to hematological B-cell lymphoproliferative disorders (B-CLPD), poses a major clinical challenge. We aimed to analyze and define the clinical and laboratory variables in SID patients associated with B-CLPD, identifying overlaps with late-onset PIDs, which could potentially improve diagnostic precision and prognostic assessment. We studied 37 clinical/laboratory variables in 151 SID patients with B-CLPD. Patients were classified as “Suspected PID Group” when having recurrent-severe infections prior to the B-CLPD and/or hypogammaglobulinemia according to key ESID criteria for PID. Bivariate association analyses showed significant statistical differences between “Suspected PID”- and “SID”-groups in 10 out of 37 variables analyzed, with “Suspected PID” showing higher frequencies of childhood recurrent-severe infections, family history of B-CLPD, significantly lower serum Free Light Chain (sFLC), immunoglobulin concentrations, lower total leukocyte, and switch-memory B-cell counts at baseline. Rpart machine learning algorithm was performed to potentially create a model to differentiate both groups. The model developed a decision tree with two major variables in order of relevance: sum κ + λ and history of severe-recurrent infections in childhood, with high sensitivity 89.5%, specificity 100%, and accuracy 91.8% for PID prediction. Identifying significant clinical and immunological variables can aid in the difficult task of recognizing late-onset PIDs among SID patients, emphasizing the value of a comprehensive immunological evaluation. The differences between “Suspected PID” and SID groups, highlight the need of early, tailored diagnostic and treatment strategies for personalized patient management and follow up.
Distinguishing between primary (PID) and secondary (SID) immunodeficiencies, particularly in relation to hematological B-cell lymphoproliferative disorders (B-CLPD), poses a major clinical challenge. We aimed to analyze and define the clinical and laboratory variables in SID patients associated with B-CLPD, identifying overlaps with late-onset PIDs, which could potentially improve diagnostic precision and prognostic assessment. We studied 37 clinical/laboratory variables in 151 SID patients with B-CLPD. Patients were classified as "Suspected PID Group" when having recurrent-severe infections prior to the B-CLPD and/or hypogammaglobulinemia according to key ESID criteria for PID. Bivariate association analyses showed significant statistical differences between "Suspected PID"- and "SID"-groups in 10 out of 37 variables analyzed, with "Suspected PID" showing higher frequencies of childhood recurrent-severe infections, family history of B-CLPD, significantly lower serum Free Light Chain (sFLC), immunoglobulin concentrations, lower total leukocyte, and switch-memory B-cell counts at baseline. Rpart machine learning algorithm was performed to potentially create a model to differentiate both groups. The model developed a decision tree with two major variables in order of relevance: sum κ + λ and history of severe-recurrent infections in childhood, with high sensitivity 89.5%, specificity 100%, and accuracy 91.8% for PID prediction. Identifying significant clinical and immunological variables can aid in the difficult task of recognizing late-onset PIDs among SID patients, emphasizing the value of a comprehensive immunological evaluation. The differences between "Suspected PID" and SID groups, highlight the need of early, tailored diagnostic and treatment strategies for personalized patient management and follow up.Distinguishing between primary (PID) and secondary (SID) immunodeficiencies, particularly in relation to hematological B-cell lymphoproliferative disorders (B-CLPD), poses a major clinical challenge. We aimed to analyze and define the clinical and laboratory variables in SID patients associated with B-CLPD, identifying overlaps with late-onset PIDs, which could potentially improve diagnostic precision and prognostic assessment. We studied 37 clinical/laboratory variables in 151 SID patients with B-CLPD. Patients were classified as "Suspected PID Group" when having recurrent-severe infections prior to the B-CLPD and/or hypogammaglobulinemia according to key ESID criteria for PID. Bivariate association analyses showed significant statistical differences between "Suspected PID"- and "SID"-groups in 10 out of 37 variables analyzed, with "Suspected PID" showing higher frequencies of childhood recurrent-severe infections, family history of B-CLPD, significantly lower serum Free Light Chain (sFLC), immunoglobulin concentrations, lower total leukocyte, and switch-memory B-cell counts at baseline. Rpart machine learning algorithm was performed to potentially create a model to differentiate both groups. The model developed a decision tree with two major variables in order of relevance: sum κ + λ and history of severe-recurrent infections in childhood, with high sensitivity 89.5%, specificity 100%, and accuracy 91.8% for PID prediction. Identifying significant clinical and immunological variables can aid in the difficult task of recognizing late-onset PIDs among SID patients, emphasizing the value of a comprehensive immunological evaluation. The differences between "Suspected PID" and SID groups, highlight the need of early, tailored diagnostic and treatment strategies for personalized patient management and follow up.
Distinguishing between primary (PID) and secondary (SID) immunodeficiencies, particularly in relation to hematological B-cell lymphoproliferative disorders (B-CLPD), poses a major clinical challenge. We aimed to analyze and define the clinical and laboratory variables in SID patients associated with B-CLPD, identifying overlaps with late-onset PIDs, which could potentially improve diagnostic precision and prognostic assessment. We studied 37 clinical/laboratory variables in 151 SID patients with B-CLPD. Patients were classified as “Suspected PID Group” when having recurrent-severe infections prior to the B-CLPD and/or hypogammaglobulinemia according to key ESID criteria for PID. Bivariate association analyses showed significant statistical differences between “Suspected PID”- and “SID”-groups in 10 out of 37 variables analyzed, with “Suspected PID” showing higher frequencies of childhood recurrent-severe infections, family history of B-CLPD, significantly lower serum Free Light Chain (sFLC), immunoglobulin concentrations, lower total leukocyte, and switch-memory B-cell counts at baseline. Rpart machine learning algorithm was performed to potentially create a model to differentiate both groups. The model developed a decision tree with two major variables in order of relevance: sum κ + λ and history of severe-recurrent infections in childhood, with high sensitivity 89.5%, specificity 100%, and accuracy 91.8% for PID prediction. Identifying significant clinical and immunological variables can aid in the difficult task of recognizing late-onset PIDs among SID patients, emphasizing the value of a comprehensive immunological evaluation. The differences between “Suspected PID” and SID groups, highlight the need of early, tailored diagnostic and treatment strategies for personalized patient management and follow up.
ArticleNumber 32
Author Mansilla-Ruiz, Maria Dolores
Benavente-Cuesta, Celina
García-Solís, Blanca
de la Fuente, Eduardo
Jiménez-Huete, Adolfo
Mandly, Eduardo Anguita
Ochoa-Grullón, Juliana
Cortijo, Ascensión Peña
Carrero, Alejandra
López, Cristina Pérez
Fernández-Arquero, Miguel
Mendiola, Ángela Villegas
Cárdenas, Maria Cruz
Palacios-Ortega, María
Medina, Fiorella
Sánchez-Ramón, Silvia
Morales, Marta Mateo
García, Carlos Jiménez
de Diego, Rebeca Pérez
Bolaños, Estefanía
García-Carmona, Yolanda
Rider, Nicholas
Guerra-Galán, Teresa
Pérez-Guzmán, Marc
Íñigo, Belén
García-Aznar, José María
Hornero, Elsa Mayol
Rodriguez, Alejandro Peixoto
Polo Zarzuela, Marta
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ISSN 0271-9142
1573-2592
IngestDate Sat Oct 26 05:11:07 EDT 2024
Sat Oct 26 16:49:46 EDT 2024
Thu Oct 24 05:34:24 EDT 2024
Wed Oct 30 12:35:16 EDT 2024
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Thu Oct 24 02:50:16 EDT 2024
IsDoiOpenAccess true
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Issue 1
Keywords B cell chronic lymphoproliferative disorders, secondary immunodeficiency
Primary immunodeficiencies
Clinical diagnosis
Artificial intelligence
Early detection
Language English
License 2024. The Author(s).
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PublicationSubtitle International Journal of Inborn Errors of Immunity and Related Diseases
PublicationTitle Journal of clinical immunology
PublicationTitleAbbrev J Clin Immunol
PublicationTitleAlternate J Clin Immunol
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Publisher Springer US
Springer Nature B.V
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Snippet Distinguishing between primary (PID) and secondary (SID) immunodeficiencies, particularly in relation to hematological B-cell lymphoproliferative disorders...
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SubjectTerms Adolescent
Adult
B-Lymphocytes - immunology
Biomedical and Life Sciences
Biomedicine
Cell differentiation
Child
Child, Preschool
Children
Diagnosis, Differential
Female
Humans
Hypogammaglobulinemia
Immune system
Immunodeficiency
Immunologic Deficiency Syndromes - diagnosis
Immunologic Deficiency Syndromes - immunology
Immunological memory
Immunology
Immunoproliferative diseases
Infant
Infections
Infectious Diseases
Internal Medicine
Lymphatic diseases
Lymphocytes
Lymphocytes B
Lymphoproliferative Disorders - diagnosis
Lymphoproliferative Disorders - etiology
Lymphoproliferative Disorders - immunology
Male
Medical Microbiology
Memory cells
Patients
Primary immunodeficiencies
Primary Immunodeficiency Diseases - diagnosis
Primary Immunodeficiency Diseases - etiology
Primary Immunodeficiency Diseases - immunology
Statistical analysis
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Title Dissecting Secondary Immunodeficiency: Identification of Primary Immunodeficiency within B-Cell Lymphoproliferative Disorders
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