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Improving risk-stratification of patients with chronic lymphocytic leukemia using multivariate patient similarity networks
P. Turcsanyi, E. Kriegova, M. Kudelka, M. Radvansky, L. Kruzova, R. Urbanova, P. Schneiderova, H. Urbankova, T. Papajik,
Jazyk angličtina Země Velká Británie
Typ dokumentu časopisecké články, práce podpořená grantem
Grantová podpora
NV16-32339A
MZ0
CEP - Centrální evidence projektů
- MeSH
- chronická lymfatická leukemie diagnóza epidemiologie genetika terapie MeSH
- dospělí MeSH
- hodnocení rizik MeSH
- individualizovaná medicína metody MeSH
- kohortové studie MeSH
- lidé středního věku MeSH
- lidé MeSH
- multivariační analýza MeSH
- mutační analýza DNA MeSH
- neuronové sítě (počítačové) MeSH
- prediktivní hodnota testů MeSH
- prognóza MeSH
- rozhodovací stromy MeSH
- senioři nad 80 let MeSH
- senioři MeSH
- shluková analýza MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- mužské pohlaví MeSH
- senioři nad 80 let MeSH
- senioři MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
BACKGROUND: Better risk-stratification of patients with chronic lymphocytic leukemia (CLL) and identification of subsets of ultra-high-risk (HR)-CLL patients are crucial in the contemporary era of an expanded therapeutic armamentarium for CLL. METHODS: A multivariate patient similarity network and clustering was applied to assess the prognostic values of routine genetic, laboratory, and clinical factors and to identify subsets of ultra-HR-CLL patients. The study cohort consisted of 116 HR-CLL patients (F/M 36/80, median age 63 yrs) carrying del(11q), del(17p)/TP53 mutations and/or complex karyotype (CK) at the time of diagnosis. RESULTS: Three major subsets based on the presence of key prognostic variables as genetic aberrations, bulky lymphadenopathy, splenomegaly, and gender: profile (P)-I (n = 34, men/women with CK + no del(17p)/TP53 mutations), P-II (n = 47, predominantly men with del(11q) + no CK + no del(17p)/TP53 mutations), and P-III (n = 35, men/women with del(17p)/TP53 mutations, with/without del(11q) and CK) were revealed. Subanalysis of major subsets identified three ultra-HR-CLL groups: men with TP53 disruption with/without CK, women with TP53 disruption with CK and men/women with CK + del(11q) with poor short-term outcomes (25% deaths/12 mo). Besides confirming the combinations of known risk-factors, the used patient similarity network added further refinement of subsets of HR-CLL patients who may profit from different targeted drugs. CONCLUSIONS: This study showed for the first time in hemato-oncology the usefulness of the multivariate patient similarity networks for stratification of HR-CLL patients. This approach shows the potential for clinical implementation of precision medicine, which is especially important in view of an armamentarium of novel targeted drugs.
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- $a Turcsanyi, Peter $u Department of Hemato-Oncology, Faculty of Medicine and Dentistry, Palacky University Olomouc and University Hospital Olomouc, Olomouc, Olomouc, Czech Republic. Electronic address: Peter.Turcsanyi@fnol.cz.
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- $a Improving risk-stratification of patients with chronic lymphocytic leukemia using multivariate patient similarity networks / $c P. Turcsanyi, E. Kriegova, M. Kudelka, M. Radvansky, L. Kruzova, R. Urbanova, P. Schneiderova, H. Urbankova, T. Papajik,
- 520 9_
- $a BACKGROUND: Better risk-stratification of patients with chronic lymphocytic leukemia (CLL) and identification of subsets of ultra-high-risk (HR)-CLL patients are crucial in the contemporary era of an expanded therapeutic armamentarium for CLL. METHODS: A multivariate patient similarity network and clustering was applied to assess the prognostic values of routine genetic, laboratory, and clinical factors and to identify subsets of ultra-HR-CLL patients. The study cohort consisted of 116 HR-CLL patients (F/M 36/80, median age 63 yrs) carrying del(11q), del(17p)/TP53 mutations and/or complex karyotype (CK) at the time of diagnosis. RESULTS: Three major subsets based on the presence of key prognostic variables as genetic aberrations, bulky lymphadenopathy, splenomegaly, and gender: profile (P)-I (n = 34, men/women with CK + no del(17p)/TP53 mutations), P-II (n = 47, predominantly men with del(11q) + no CK + no del(17p)/TP53 mutations), and P-III (n = 35, men/women with del(17p)/TP53 mutations, with/without del(11q) and CK) were revealed. Subanalysis of major subsets identified three ultra-HR-CLL groups: men with TP53 disruption with/without CK, women with TP53 disruption with CK and men/women with CK + del(11q) with poor short-term outcomes (25% deaths/12 mo). Besides confirming the combinations of known risk-factors, the used patient similarity network added further refinement of subsets of HR-CLL patients who may profit from different targeted drugs. CONCLUSIONS: This study showed for the first time in hemato-oncology the usefulness of the multivariate patient similarity networks for stratification of HR-CLL patients. This approach shows the potential for clinical implementation of precision medicine, which is especially important in view of an armamentarium of novel targeted drugs.
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- 700 1_
- $a Kriegova, Eva $u Department of Immunology, Faculty of Medicine and Dentistry, Palacky University Olomouc and University Hospital Olomouc, Olomouc, Czech Republic, Olomouc, Czech Republic. Electronic address: eva.kriegova@email.cz.
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- $a Kudelka, Milos $u Department of Computer Science, Faculty of Electrical Engineering and Computer Science, VSB - Technical University of Ostrava, Ostrava, Czech Republic. Electronic address: Milos.Kudelka@vsb.cz.
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- $a Radvansky, Martin $u Department of Computer Science, Faculty of Electrical Engineering and Computer Science, VSB - Technical University of Ostrava, Ostrava, Czech Republic. Electronic address: Martin.Radvansky@vsb.cz.
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- $a Kruzova, Lenka $u Department of Hemato-Oncology, Faculty of Medicine and Dentistry, Palacky University Olomouc and University Hospital Olomouc, Olomouc, Olomouc, Czech Republic. Electronic address: Lenka.Kruzova@fnol.cz.
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- $a Urbanova, Renata $u Department of Hemato-Oncology, Faculty of Medicine and Dentistry, Palacky University Olomouc and University Hospital Olomouc, Olomouc, Olomouc, Czech Republic. Electronic address: Renata.Urbanova@fnol.cz.
- 700 1_
- $a Schneiderova, Petra $u Department of Immunology, Faculty of Medicine and Dentistry, Palacky University Olomouc and University Hospital Olomouc, Olomouc, Czech Republic, Olomouc, Czech Republic. Electronic address: Petra.Schneiderova@fnol.cz.
- 700 1_
- $a Urbankova, Helena $u Department of Hemato-Oncology, Faculty of Medicine and Dentistry, Palacky University Olomouc and University Hospital Olomouc, Olomouc, Olomouc, Czech Republic. Electronic address: Helena.Urbankova@fnol.cz.
- 700 1_
- $a Papajik, Tomas $u Department of Hemato-Oncology, Faculty of Medicine and Dentistry, Palacky University Olomouc and University Hospital Olomouc, Olomouc, Olomouc, Czech Republic. Electronic address: Tomas.Papajik@fnol.cz.
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