Evidence map›Paper›PMID 42649943›Full record

ArticleCancers2026

Pediatric B-Cell Acute Lymphoblastic Leukemia: Comprehensive Genomic Characterization Including SNP-Array and Analysis of Relapse Risk.

Concepción Prats-Martín, Laura Pérez Ortega, Águeda Molinos Quintana, Jordi Ribera, Beatriz Chiclana Rodríguez, Teresa Caballero-Velázquez, Estrella Carrillo Cruz, Henry Antonio Andrade-Ruiz, María Paz Garrastazul Sánchez, María Dolores Madrigal Toscano and 4 more

Abstract read
In one paragraph

Article in Cancers, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

14 authors.

Concepción Prats-MartínDepartment of Hematology, Hospital Universitario Virgen del Rocío, Instituto de Biomedicina de Sevilla (IBIS/CSIC/CIBERONC), Universidad de Sevilla, Avda. Manuel Siurot sn., CP 41013 Sevilla, Spain.
Laura Pérez OrtegaDepartment of Hematology, Hospital Universitario Virgen del Rocío, Instituto de Biomedicina de Sevilla (IBIS/CSIC/CIBERONC), Universidad de Sevilla, Avda. Manuel Siurot sn., CP 41013 Sevilla, Spain.
Águeda Molinos QuintanaDepartment of Hematology, Hospital Universitario Virgen del Rocío, Instituto de Biomedicina de Sevilla (IBIS/CSIC/CIBERONC), Universidad de Sevilla, Avda. Manuel Siurot sn., CP 41013 Sevilla, Spain.ORCID 0000-0003-4972-917X
Jordi RiberaJosep Carreras Leukaemia Research Institute (IJC), ICO-Hospital Germans Trias i Pujol, Universitat Autònoma de Barcelona, 08916 Badalona, Spain.ORCID 0000-0003-4796-6470
Beatriz Chiclana RodríguezDepartment of Hematology, Hospital Universitario Virgen del Rocío, Instituto de Biomedicina de Sevilla (IBIS/CSIC/CIBERONC), Universidad de Sevilla, Avda. Manuel Siurot sn., CP 41013 Sevilla, Spain.
Teresa Caballero-VelázquezDepartment of Hematology, Hospital Universitario Virgen del Rocío, Instituto de Biomedicina de Sevilla (IBIS/CSIC/CIBERONC), Universidad de Sevilla, Avda. Manuel Siurot sn., CP 41013 Sevilla, Spain.ORCID 0000-0001-7487-3793
Estrella Carrillo CruzDepartment of Hematology, Hospital Universitario Virgen del Rocío, Instituto de Biomedicina de Sevilla (IBIS/CSIC/CIBERONC), Universidad de Sevilla, Avda. Manuel Siurot sn., CP 41013 Sevilla, Spain.
Henry Antonio Andrade-RuizMethodological and Statistical Support Unit, Fundación para la Gestión de la Investigación en Salud de Sevilla (FISEVI), 41013 Sevilla, Spain.ORCID 0009-0008-5079-3420
María Paz Garrastazul SánchezDepartment of Hematology, Hospital Universitario Puerta del Mar, 11009 Cádiz, Spain.
María Dolores Madrigal ToscanoDepartment of Hematology, Hospital Universitario Virgen Macarena, 41009 Sevilla, Spain.
María Solé RodríguezDepartment of Hematology, Hospital Universitario Juan Ramón Jiménez, 21005 Huelva, Spain.
Marina Gómez RosaUGC Hematología y Hemoterapia, Hospital Universitario Virgen de Valme, 41014 Sevilla, Spain.
José Antonio Pérez-SimónDepartment of Hematology, Hospital Universitario Virgen del Rocío, Instituto de Biomedicina de Sevilla (IBIS/CSIC/CIBERONC), Universidad de Sevilla, Avda. Manuel Siurot sn., CP 41013 Sevilla, Spain.ORCID 0000-0003-3616-6101
Rosario M Morales-CamachoDepartment of Hematology, Hospital Universitario Virgen del Rocío, Instituto de Biomedicina de Sevilla (IBIS/CSIC/CIBERONC), Universidad de Sevilla, Avda. Manuel Siurot sn., CP 41013 Sevilla, Spain.ORCID 0000-0001-7179-0693

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAccurate identification of pediatric B-cell acute lymphoblastic leukemia (B-ALL) patients at increased risk of relapse remains a major clinical challenge, as relapse occurs in 10-20% of cases, including patients initially classified as low- or intermediate-risk. This study aimed to identify clinical, genomic, and measurable residual disease (MRD) related predictors of relapse in pediatric B-ALL.

methods51 pediatric patients with B-ALL were included and followed for a median of 30.5 months (IQR, 16-45.5). Patients were stratified according to relapse status. At diagnosis, all cases underwent comprehensive genomic characterization based on the 2022 WHO and ICC classifications, including SNP-array analysis to identify copy number alterations (CNA) involving recurrent B-ALL genes (

results86.3% of patients were classified according to the 2022 WHO/ICC classifications, with high hyperdiploidy being the most frequent subtype. During follow-up, 11 patients relapsed. Relapse was significantly associated with high cytogenetic risk (

conclusionsAn integrated diagnostic strategy including SNP-array provides a high diagnostic yield. High-risk cytogenetic abnormalities and positive end-of-induction MRD are independent predictors of relapse in pediatric B-ALL. Their combined assessment at diagnosis and early treatment may improve risk stratification and may support personalized therapeutic approaches.

Indexed as

B-cell acute lymphoblastic leukemiameasurable residual diseasepediatricrelapseSNP-array

Identifiers

PMID42649943
PMCPMC13511422

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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.