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Research

A major issue of research concern is applied statistics in finance (propensity models: financial health of the company, lapse of insurance contracts) and medical research (multiple sclerosis, predictive modelling, biomarker identification). In the field of theoretical statistics,the focus is narrowed to micro panel data and classification and regression analysis, respectively.

I have authored or co-authored a number of scientific publications whose titles and abstracts are listed below. To obtain details, do not hesitate to contact me via email: [javascript protected email address]

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Title: A Distance Based Measure of Data Quality

Author: KRÁĽ, Pavol, SOBÍŠEK, Lukáš, STACHOVÁ, Mária

Year: 2014

Field:

Publication type: paper (Web of Knowledge - JCR, Scopus)

Citation:
KRÁĽ, Pavol, SOBÍŠEK, Lukáš, STACHOVÁ, Mária. A Distance Based Measure of Data Quality. Metodološki zvezki – Advances in Methodology and Statistics [online]. 2014, roč. 11, č. 2, s. 107–120. ISSN 1854-0031. Dostupné z: http://www.stat-d.si/mz/mz11.2/Kral2014.pdf

Abstract:
Data quality can be seen as a very important factor for the validity of information extracted from data sets using statistical or data mining procedures. In the paper we propose a description of data quality allowing us to characterize data quality of the whole data set, as well as data quality of particular variables and individual cases.

On the basis of the proposed description, we define a distance based measure of data quality for individual cases as a distance of the cases from the ideal one. Such a measure can be used as additional information for preparation of a training data set, fitting models, decision making based on results of analyses etc. It can be utilized in different ways ranging from a simple weighting function to belief functions.

Keywords (CZ): index datové kvality, datová nejistota, metrika založená na vzdálenosti, váhavé a překrývající se datové soubory, modelování storna

Keywords (EN): data quality index, data uncertainty, distance based measure, hesitant fuzzy sets, lapse prediction modelling

Title: A Novel Semiautomated Pipeline to Measure Brain Atrophy and Lesion Burden in Multiple Sclerosis: A Long-Term Comparative Study

Author: UHER, Tomas, KRASENSKY, Jan, VANECKOVA, Manuela, SOBISEK, Lukas, SEIDL, Zdenek, HAVRDOVA, Eva, BERGSLAND, Niels, DWYER, Michael G., HORAKOVA, Dana, ZIVADINOV, Robert.

Year: 2017

Field: Medical research

Publication type: paper (Web of Knowledge - JCR, Scopus)

Citation:
UHER, Tomas, KRASENSKY, Jan, VANECKOVA, Manuela, SOBISEK, Lukas, SEIDL, Zdenek, HAVRDOVA, Eva, BERGSLAND, Niels, DWYER, Michael G., HORAKOVA, Dana, ZIVADINOV, Robert. A Novel Semiautomated Pipeline to Measure Brain Atrophy and Lesion Burden in Multiple Sclerosis: A Long-Term Comparative Study. Journal of Neuroimaging, 2017, roč. 27, č. 6, s. 620-629, http://onlinelibrary.wiley.com/doi/10.1111/jon.12445/full

Abstract:
BACKGROUND AND PURPOSE

Lesion burden and brain volume changes are frequent end points in research but nowadays are becoming important in the clinical practice of multiple sclerosis (MS). The objective of this study was to investigate the correlation between magnetic resonance imaging (MRI) measures obtained by in-house developed ScanView software and commonly used volumetric techniques for assessment of T2 lesion and whole brain volumes and their changes.

METHODS

Together 3,340 MRI scans from 209 patients after first demyelinating event suggestive of MS, 181 relapsing-remitting MS patients and 43 controls were analyzed. The average number of MRI scans and follow-up duration was 8.2 and 6.5 years, respectively. All MRI scans were performed in a single center but independently analyzed in two neuroimaging centers. Volumetric analysis by ScanView software was applied in Prague. Commonly used techniques, such as SIENA, SIENAX, and Jim software, were applied in Buffalo. Correlations between MRI measures were evaluated using correlation coefficients. Intraindividual variability of longitudinal MRI data was estimated by mean squared error.

RESULTS

The associations of the cross-sectional and longitudinal MRI measures between commonly used techniques and ScanView were significant (r/rho = .83-.95). The associations of cross-sectional MRI measures were stronger (r/rho = .90-.95) compared with longitudinal ones (r = .83). Standardized intraindividual variability of whole brain % volume change was greater in ScanView compared with SIENA (mean squared error .32 vs. .21; P < .001).

CONCLUSIONS

We found relatively strong correlations of cross-sectional and longitudinal data obtained by both techniques. However, SIENA showed lower intraindividual variability than the ScanView method in measuring whole brain volume loss over time.

Keywords (CZ): MRI, volumetrie, T2 objem lézí, atrofie mozku, roztroušená skleróza

Keywords (EN): MRI, volumetry, T2 lesion volume, brain atrophy, multiple sclerosis

Title: Analysis of financial distress of Czech companies using repeated measurements

Author: STACHOVÁ, Mária, SOBÍŠEK, Lukáš

Year: 2018

Field: Finance

Publication type: Conference contribution (Web of Knowledge - CPCI)

Citation:
STACHOVÁ, Mária, SOBÍŠEK, Lukáš. ANALYSIS OF FINANCIAL DISTRESS OF CZECH COMPANIES USING REPEATED MEASUREMENTS. In: International Days of Statistics and Economics (MSED) [online]. Praha, 06.09.2018 – 08.09.2018. Slaný : Melandrium, Libuše Macáková, 2018, s. 1698–1707. ISBN 978-80-87990-14-8. Dostupné z: https://msed.vse.cz/msed_2018/article/221-Stachova-Maria-paper.pdf

Abstract:
In our contribution, we focus on relationship between financial distress of company and its financial indicators. Our previous studies of Slovak companies show strong correlation. Hence, we verify our findings by fitting a financial distress (bankruptcy) prediction model investigating a comparable set of financial predictors. Used data are collected over four consecutive years and thus their longitudinal character allows us to use RE-EM tree model that is able to incorporate time dynamic of selected predictors. Moreover, we try to investigate if the longer period of the data collection improves the prediction of bankruptcy and in order to verify this hypothesis, we compare the predictive power of selected financial indicators in three overlapping periods of different lengths, namely four, three and two years.

Keywords (CZ): RE-EM model, finanční tíseň podniku, predikce, finanční indikátor

Keywords (EN): RE-EM model, financial distress model, prediction, financial indicators

Title: Analysis of financial distress of Slovak companies using repeated measurements

Author: STACHOVÁ, Mária, KRÁĽ, Pavol, SOBÍŠEK, Lukáš, KAKAŠČÍK, Martin

Year: 2015

Field: Finance

Publication type: Conference contribution (Web of Knowledge - CPCI)

Citation:
STACHOVÁ, Mária, KRÁĽ, Pavol, SOBÍŠEK, Lukáš, KAKAŠČÍK, Martin. Analysis of financial distress of Slovak companies using repeated measurements. In: Applications of Mathematics and Statistics in Economics – AMSE [CD ROM]. Jindřichův Hradec, 02.09.2015 – 06.09.2015. Prague : University of Economics, Prague, Oeconomica Publishing House, 2015. 7 s. ISBN 978-80-245-2099-5

Abstract:
From the previous studies it is obvious that there is a strong relationship between financial distress and quantitative characteristics, e.g. financial ratios of companies. The main goal of our contribution is to investigate if the longer period (four consecutive years) of the data collection improves the ability of financial indicators to predict company bankruptcy using a data set consisting of financial indicators of Slovak companies collected over a short period of time, namely years 2009-2013. We apply two different approaches (RE-EM and CART) to this data set in order to predict a risk of financial distress of companies during the next period.

Keywords (CZ): modely finančního zdraví, finanční analýza ex-ante, opakovaná měření

Keywords (EN): models of financial distress, financial analysis ex-ante, repeated measurements

Title: Analýza longitudinálních dat pomocí smíšeného lineárního modelu v programu R

Author: SOBÍŠEK, Lukáš, STACHOVÁ, Mária, PECÁKOVÁ, Iva

Year: 2015

Field:

Publication type: paper

Citation:
SOBÍŠEK, Lukáš, STACHOVÁ, Mária, PECÁKOVÁ, Iva. Analýza longitudinálních dat pomocí smíšeného lineárního modelu v programu R. Forum Statisticum Slovacum [online]. 2015, roč. 11, č. 6, s. 138–143. ISSN 1336-7420. Dostupné z: http://www.ssds.sk/casopis/archiv/2015/fss0615.pdf

Abstract:
The contribution provides an overview of methodology and software applications that are used in longitudinal data analysis. We focus on the description of functions implemented in the statitistical system R. Namely, the functions lme() and lmer() are described and compared. These tools are used to estimate and apply the linear mixed models in panel data analyses.

Keywords (CZ): smíšený lineární model, analýza longitudinálních dat, nlme, lme4

Keywords (EN): linear mixed models, longitudinal data analysis, nlme, lme4

Title: Aplikace metod shlukové analýzy na data z pojišťoven

Author: SOBÍŠEK, Lukáš, VINTROVÁ, Vanda, VINTR, Tomáš, PASTOREK, Lukáš, ŘEZANKOVÁ, Hana

Year: 2011

Field: Finance

Publication type: paper

Citation:
SOBÍŠEK, Lukáš, VINTROVÁ, Vanda, VINTR, Tomáš, PASTOREK, Lukáš, ŘEZANKOVÁ, Hana. Aplikace metod shlukové analýzy na data z pojišťoven. Forum Statisticum Slovacum. 2011, roč. VII., č. 5, s. 145–151. ISSN 1336-7420

Abstract:
The aim of this paper is to evaluate selected clustering techniques used for revealing the hidden relations in the client data of the insurance company. On the basis of the analyses results and our knowledge of the clustered objects we made an expert estimation of the correctness of the results to compare these methods. We applied self-organizing maps, neural gas algorithm, k-means method, fuzzy c-means method for the analyses. We found that only neural gas algorithm identified clusters with meaningful interpretation.

Keywords (CZ): metody shlukování, samoorganizující se mapy, algoritmus neuronového plynu, metoda k-průměru, metoda fuzzy k-průměrů, U-matice

Keywords (EN): clustering methods, self-organizing maps, neural gas algorithm, k-means method, fuzzy c-means method, U-matrix

Title: AutoClass – klasifikační metoda založená na bayesovském teorému

Author: BARTL, Eduard, ŘEZANKOVÁ, Hana, SOBÍŠEK, Lukáš

Year: 2012

Field:

Publication type: Conference contribution

Citation:
SOBÍŠEK, Lukáš. AutoClass – klasifikační metoda založená na bayesovském teorému. In: Sborník prací vědeckého semináře doktorského studia FIS VŠE [CD-ROM]. Praha, 14.02.2012. Praha : Oeconomica, 2012, s. 233–237. ISBN 978-80-245-1862-6

Abstract:
The main goal of this paper is to present a Bayesian classification method implemented in AutoClass software. This software was created by researchers from NASA. It is a classification tool based on naive Bayesian classifier.

The Bayesian approach to classification differs to classification methods which assign objects into classes uniquely. It is looking for latent classes that characterize each group of objects most accurately. These classes are described by using latent class models. AutoClass offers four latent class models. These models are based on the classical finite mixture model, which assumes conditional independence of variables. Estimation of the probability distribution of model parameters conditional on empirical data is based on the Bayes theorem. Model parameters are estimated simply from data by maximum likelihood method in the event of supervised learning. On the contrary, unsupervised learning uses iterative EM algorithm.

AutoClass was applied and tested in many large data sets not only by researchers at NASA, but also by statistics operating in industry and by academics. The newer versions of AutoClass enables to combine continuous and discrete variables. It handles with missing values. The algorithm allows to classify by variables that are conditionally independent on condition that the model hypothesis is valid. Automatically chooses the number of classes and complexity of the class description.

Keywords (CZ): AutoClass, bayesovská klasifikační metoda, naivní bayesovský klasifikátor, EM algoritmus, model směsí rozdělení

Keywords (EN): AutoClass, Bayesian classification method, naive Bayesian classifier, EM algorithm, finite mixture model

Title: Can longitudinal clustering help to define financial distress criteria?

Author: STACHOVÁ, Mária, SOBÍŠEK, Lukáš

Year: 2018

Field: Finance

Publication type: Conference contribution (Web of Knowledge - CPCI)

Citation:
STACHOVÁ, Mária, SOBÍŠEK, Lukáš. Can longitudinal clustering help to define financial distress criteria? In: Applications of Mathematics and Statistics in Economics – AMSE [CD ROM]. Kutná Hora, 29.08.2018 – 02.09.2018. Prague: University of Economics, Prague, Oeconomica Publishing House, 2018. http://www.amse-conference.eu/old/2018/?page_id=1314

Abstract:
One of the main task in each analysis of companies’ financial status is to correctly define the criteria that can describe the financial health or financial distress of these enterprises. In general, the financial distress is a situation in which company cannot pay or has difficulty to reach its financial obligations. Our data set consists of three financial indicators of Czech enterprises. These longitudinal data are collected over a few consecutive years. We applied the model-based partitioning and the K-means partitioning to these longitudinal data to cluster the time trajectories of these criteria and subsequently we compare the accuracy of these algorithms. We use packages “mixAK” and “kml” of the statistical system R in our analysis.

Keywords (CZ): Finanční tíseň, shlukování longitudinálních dat, K-means shlukování, modelový přístup ke shlukování

Keywords (EN): financial distress, longitudinal data clustering, K-means partitioning, model-based partitioning

Title: Clustering Methods Modelling Real Data

Author: SOBÍŠEK, Lukáš, STACHOVÁ, Mária

Year: 2012

Field: Finance

Publication type: Conference contribution

Citation:
SOBÍŠEK, Lukáš, STACHOVÁ, Mária. Clustering Methods Modelling Real Data. In: Applications of mathematics and statistics in economy [CD-ROM]. Liberec, 30.08.2012 – 01.09.2012. Praha : Oeconomica, 2012, s. 1–10. ISBN 978-80-245-1905-0

Abstract:
Data Mining statistical methods can help people to understand the patterns in certain chunk of information so it is obvious that they have a wide area of applications.

The aim of our contribution is to present different latent class clustering models built using R software, model implemented in AutoClass software and model in Latent Gold software. We compare them each other as well we compare them with classical hierarchical model and bagged clustering method.

These models are applied to customers’ data comes from an insurance company. We follow up our previous works where the others clustering methods were used on the same data set.

Keywords (CZ): modely latentních tříd, hierarchické shlukování metodou bagged

Keywords (EN): latent class clustering, hierarchical clustering, bagged clustering

Title: Cognitive clinico-radiological paradox in early stages of multiple sclerosis

Author: UHER, Tomáš, KRÁSENSKÝ, Jan, SOBÍŠEK, Lukáš, BLÁHOVÁ DUŠÁNKOVÁ, Jana, SEIDL, Zdeněk, HAVRDOVÁ, Eva, SORMANI, Maria Pia, HORÁKOVÁ, Dana, KALINČÍK, Tomáš, VANĚČKOVÁ, Manuela.

Year: 2018

Field: Medical research

Publication type: paper (Web of Knowledge - JCR, Scopus)

Citation:
UHER, Tomáš, KRÁSENSKÝ, Jan, SOBÍŠEK, Lukáš, BLÁHOVÁ DUŠÁNKOVÁ, Jana, SEIDL, Zdeněk, HAVRDOVÁ, Eva, SORMANI, Maria Pia, HORÁKOVÁ, Dana, KALINČÍK, Tomáš, VANĚČKOVÁ, Manuela. Cognitive clinico-radiological paradox in early stages of multiple sclerosis. Annals of Clinical and Translational Neurology, 2018, roč. 5, č. 1, s. 81-91, http://onlinelibrary.wiley.com/doi/10.1002/acn3.512/epdf

Abstract:
Objective: To investigate whether the strength of the association between magnetic resonance imaging (MRI) metrics and cognitive outcomes differs between various multiple sclerosis subpopulations.

Methods: 1052 patients were included in this large cross-sectional study. Brain MRI (T1 and T2 lesion volume and brain parenchymal fraction) and neuropsychological assessment (Brief International Cognitive Assessment for Multiple Sclerosis and Paced Auditory Serial Addition Test) were performed.

Results: Weak correlations between cognitive domains and MRI measures were observed in younger patients (age≤30 years; absolute Spearman ' s rho=0.05-0.21), with short disease duration (<2 years; rho=0.01-0.21), low Expanded Disability Status Scale [EDSS] (≤1.5; rho=0.08-0.18), low T2 lesion volume (lowest quartile; <0.59 ml; rho=0.01-0.20) and high brain parenchymal fraction (highest quartile; >86.66; rho=0.01-0.16). Stronger correlations between cognitive domains and MRI measures were observed in older patients (age>50 years; rho=0.24-0.50), with longer disease duration (>15 years; rho=0.26-0.53), higher EDSS (≥5.0; rho=0.23-0.39), greater T2 lesion volume (highest quartile; >5.33 ml; rho=0.16-0.32) and lower brain parenchymal fraction (lowest quartile; <83.71; rho=0.13-0.46). The majority of these observed results were confirmed by significant interactions (P≤0.01) using continuous variables.

Interpretation: The association between structural brain damage and functional cognitive impairment is substantialy weaker in multiple sclerosis patients with a low disease burden. Therefore, disease stage should be taken into consideration when interpreting associations between structural and cognitive measures in clinical trials, research studies and clinical practice.

Keywords (CZ): MRI, volumetrie, T2 objem lézí, atrofie mozku, roztroušená skleróza

Keywords (EN): MRI, volumetry, T2 lesion volume, brain atrophy, multiple sclerosis

Title: Combining clinical and magnetic resonance imaging markers enhances prediction of 12-year disability in multiple sclerosis

Author: UHER, Tomáš, VANEČKOVÁ, Manuela, SOBÍŠEK, Lukáš, TÝBLOVÁ, Michaela, SEIDL, Zdeněk, KRÁSENSKÝ, Jan, RAMASAMY, Deepa, HAVRDOVÁ, Eva, KALINČIK, Tomáš, HORÁKOVÁ, Dana

Year: 2017

Field: Medical research

Publication type: paper (Web of Knowledge - JCR, Scopus)

Citation:
UHER, Tomáš, VANEČKOVÁ, Manuela, SOBÍŠEK, Lukáš, TÝBLOVÁ, Michaela, SEIDL, Zdeněk, KRÁSENSKÝ, Jan, RAMASAMY, Deepa, HAVRDOVÁ, Eva, KALINČIK, Tomáš, HORÁKOVÁ, Dana. Combining clinical and magnetic resonance imaging markers enhances prediction of 12-year disability in multiple sclerosis. Multiple Sclerosis Journal [online]. 2017, roč. 23, č. 1, s. 51–61. ISSN 1352-4585. DOI: https://doi.org/10.1177/1352458516642314

Abstract:
Background:

Disease progression and treatment efficacy vary among individuals with multiple sclerosis. Reliable predictors of individual disease outcomes are lacking.

Objective:

To examine the accuracy of the early prediction of 12-year disability outcomes using clinical and magnetic resonance imaging (MRI) parameters.

Methods:

A total of 177 patients from the original Avonex-Steroids-Azathioprine study were included. Participants underwent 3-month clinical follow-ups. Cox models were used to model the associations between clinical and MRI markers at baseline or after 12 months with sustained disability progression (SDP) over the 12-year observation period.

Results:

At baseline, T2 lesion number, T1 and T2 lesion volumes, corpus callosum (CC), and thalamic fraction were the best predictors of SDP (hazard ratio (HR) = 1.7–4.6; p ≤  0.001–0.012). At 12 months, Expanded Disability Status Scale (EDSS) and its change, number of new or enlarging T2 lesions, and CC volume % change were the best predictors of SDP over the follow-up (HR = 1.7–3.5; p ≤  0.001–0.017). A composite score was generated from a subset of the best predictors of SDP. Scores of ≥4 had greater specificity (90%–100%) and were associated with greater cumulative risk of SDP (HR = 3.2–21.6; p < 0.001) compared to the individual predictors.

Conclusion:

The combination of established MRI and clinical indices with MRI volumetric predictors improves the prediction of SDP over long-term follow-up and may provide valuable information for therapeutic decisions.

Keywords (CZ): roztroušená skleróza, magnetická rezonance, disabilita, prediktory, mozková atrofie, léze

Keywords (EN): multiple sclerosis, magnetic resonance imaging, disability, predictors, brain atrophy, lesions

Title: Combining clinical and magnetic resonance imaging markers enhances prediction of 12-year employment status in multiple sclerosis patients

Author: KADRNOŽKOVÁ, Lucie, VANĚČKOVÁ, Manuela, SOBÍŠEK, Lukáš, atd.

Year: 2018

Field: Medical research

Publication type: paper (Web of Knowledge - JCR, Scopus)

Citation:
KADRNOŽKOVÁ, Lucie, VANĚČKOVÁ, Manuela, SOBÍŠEK, Lukáš, KRÁSENSKÝ, Jan, BEŇOVÁ, Barbora, KUČEROVÁ, Karolína, MOTÝL, Jiří, ANDĚLOVÁ, Michaela, NOVOTNÁ, Klára, LÍZROVÁ PREININGEROVÁ, Jana, HAVRDOVÁ, Eva, HORÁKOVÁ, Dana, UHER, Tomáš. Combining clinical and magnetic resonance imaging markers enhances prediction of 12-year employment status in multiple sclerosis patients. Journal of the Neurological Science, 2018, roč. 388, Číslo 15, s. 87-93.

Abstract:
Background
Multiple sclerosis (MS) is frequently diagnosed in the most productive years of adulthood and is often associated with worsening employment status. Reliable predictors of employment status change are lacking.

Objective
To identify early clinical and magnetic resonance imaging (MRI) markers of employment status worsening in MS patients at 12-year follow-up.

Methods
A total of 145 patients with early relapsing-remitting MS from the original Avonex-Steroids-Azathioprine (ASA) study were included in this prospective, longitudinal, observational cohort study. Cox models were conducted to identify MRI and clinical predictors (at baseline and during the first 12 months) of worsening employment status (patients either (1) working full-time or part-time with no limitations due to MS and retaining this status during the course of the study, or (2) patients working full-time or part-time with no limitations due to MS and switching to being unemployed or working part-time due to MS).

Results
In univariate analysis, brain parenchymal fraction, T1 lesion volume, and T2 lesion volume were the best MRI predictors of worsening employment status over the 12-year follow-up period. MS duration at baseline (hazard ratio (HR) = 1.10, 95% confidence interval (CI) 1.03-1.18; p = 0.040) was the only significant clinical predictor. Having one extra milliliter of T1 lesion volume was associated with a 53% greater risk of worsening employment status (HR = 1.53, 95% CI 1.16-2.02; p = 0.018). A brain parenchymal fraction decrease of 1% increased the risk of worsening employment status by 22% [HR = 0.78, 95% CI 0.65-0.95; p = 0.034].

Conclusion
Brain atrophy and lesion load were significant unique predictors of worsening employment status in MS patients. Using a combination of clinical and MRI markers may improve the early prediction of an employment status change over long-term follow-up.

Keywords (CZ): roztroušená skleróza, zaměstnanost, magnetická rezonance, práce, longitudinální studie, mozková atrofie, objem lézí

Keywords (EN): Multiple sclerosis, Employment, Magnetic Resonance Imaging, Work, Longitudinal studies, Brain Atrophy, Lesion load

Title: Comparison of Classical Dimensionality Reduction Methods with Novel Approach Based on Formal Concept Analysis

Author: BARTL, Eduard, ŘEZANKOVÁ, Hana, SOBÍŠEK, Lukáš

Year: 2011

Field:

Publication type: paper (Web of Knowledge - JCR, Scopus)

Citation:
BARTL, Eduard, ŘEZANKOVÁ, Hana, SOBÍŠEK, Lukáš. Comparison of Classical Dimensionality Reduction Methods with Novel Approach Based on Formal Concept Analysis. In: 6th International Conference on Rough Sets and Knowledge Technology [online]. Banff, 08.10.2011 – 11.10.2011. Berlin : Springer Verlag, 2011, s. 26–35. ISBN 978-3-642-24424-7. ISSN 0302-9743. DOI: https://doi.org/10.1007/978-3-642-24425-4_6. Dostupné také z: http://www.springerlink.com/content/630v252741850227/

Abstract:
In the paper we deal with dimensionality reduction techniques for a dataset with discrete attributes. Dimensionality reduction is considered as one of the most important problems in data analysis. The main aim of our paper is to show advantages of a novel approach introduced and developed by Belohlavek and Vychodil in comparison of two classical dimensionality reduction methods which can be used for ordinal attributes (CATPCA and factor analysis). The novel technique is fundamentally different from existing ones since it is based on another kind of mathematical apparatus (namely, Galois connections, lattice theory, fuzzy logic). Therefore, this method is able to bring a new insight to examined data. The comparison is accompanied by analysis of two data sets which were obtained by questionnaire survey.

Keywords (CZ): redukce dimenzionality, diskrétní data, factorová analýza, formální konceptuální analýza, dekompozice matice

Keywords (EN): dimensionality reduction, discrete data, factor analysis, formal concept analysis, matrix decomposition

Title: Corporate financial distress prediction of Slovak companies: Z-score models vs. alternatives

Author: KRÁĽ, Pavol, FLEISCHER, Miloš, STACHOVÁ, Mária, NEDELOVÁ, Gabriela, SOBÍŠEK, Lukáš

Year: 2016

Field: Finance

Publication type: Conference contribution (Web of Knowledge - CPCI)

Citation:
KRÁĽ, Pavol, FLEISCHER, Miloš, STACHOVÁ, Mária, NEDELOVÁ, Gabriela, SOBÍŠEK, Lukáš. Corporate financial distress prediction of Slovak companies: Z-score models vs. alternatives. In: AMSE 2016 (Applications of Mathematics and Statistics in Economics) [online]. Banská Štiavnica, 31.08.2016 – 04.09.2016. Banská Bystrica : Občianske združenie Financ, 2016, s. 224–231. ISBN 978-80-89438-04-4. ISSN 2453-9902. Dostupné z: http://amse.umb.sk/proceedings/KralFleischerStachovaNedelovaSobisek.pdf

Abstract:
In the recent paper 'The portability of Altman’s Z-score model to predicting corporate financial distress of Slovak companies' published in 2016 in Technological and Economic Development of Economy, its authors claim that, under some assumptions, 'Altman’s bankruptcy formula is portable into the Slovak economic conditions and useful for predicting financial difficulties'. The main goal of our paper is to compare the ported Z-score prediction models from their paper, which are based on linear discriminant analysis, to prediction models based on other standard supervised classification methods, e.g. logistic regression, decision trees, random forests. In our comparison, we take into account accuracy as well as interpretability of the models. In order to assure comparability of results we use the same data set as it was utilized in the above-mentioned paper.

Keywords (CZ): predikce finanční tísně, alternativní modely, Altmanův model

Keywords (EN): financial distress prediction, alternative models, Altman-like models

Title: Do eyes with and without optic neuritis in multiple sclerosis age equally?

Author: LIZROVA PREININGEROVA, J., GRISHKO, A., SOBISEK, L., ANDELOVA, M., BENOVA, B., KUCEROVA, K., HAVRDOVA KUBALA, E.

Year: 2018

Field: Medical research

Publication type: paper (Web of Knowledge - JCR, Scopus)

Citation:
LIZROVA PREININGEROVA, J., GRISHKO, A., SOBISEK, L., ANDELOVA, M., BENOVA, B., KUCEROVA, K., HAVRDOVA KUBALA, E. Do eyes with and without optic neuritis in multiple sclerosis age equally? Neuropsychiatric desease and treatment. 2018, roč. 14. s. 2281-2285.

Abstract:
Purpose:

Anterior visual pathway reflects axonal loss caused by both optic neuritis (ON) and neurodegeneration in multiple sclerosis (MS). Although the axonal injury post-ON is thought to be complete by 6 months of onset, most studies using optical coherence tomography (OCT) to evaluate retinal changes as a marker of neurodegeneration exclude eyes with a history of ON or consider them separately. The objective of this study was to assess whether the eyes post-ON (>6 months) show in later years different rate of chronic retinal changes than the fellow eyes not affected by ON.

Patients and methods:

Fifty-six patients with MS with a history of ON in one eye (ON eyes) and no ON in the fellow (FL) eye, who were followed by OCT for >2 years, were selected from a cohort of patients with MS. Paired eye analysis was performed.

Results:

Mean interval post-ON at baseline was 5.65 (SD 5.05) years. Mean length of follow-up by OCT was 4.57 years. There was no statistical difference in absolute or relative thinning of retinal nerve fiber layer in peripapillary area between the ON and FL eyes.

Conclusion:

This study has shown that we do not need to exclude eyes with a history of ON from longitudinal studies of neurodegeneration in MS, provided that we use data outside of the frame of acute changes post-ON. Long-term changes of peripapillary retinal nerve fiber layer in ON and FL eyes are equal.

Keywords (CZ): roztroušená skleróza; neurodegenerace; oční koherenční tomograf; sítnici

Keywords (EN): multiple sclerosis; neurodegeneration; optical coherence tomography; retina

Title: Financial distress criteria defined by clustering of longitudinal data

Author: STACHOVÁ, Mária, SOBÍŠEK, Lukáš

Year: 2016

Field: Finance

Publication type: Conference contribution (Web of Knowledge - CPCI)

Citation:
STACHOVÁ, Mária, SOBÍŠEK, Lukáš. Financial distress criteria defined by clustering of longitudinal data. In: The 10th International Days of Statistics and Economics (MSED 2016) [online]. Praha, 08.09.2016 – 10.09.2016. Slaný : Melandrium, 2016, s. 1703–1712. ISBN 978-80-87990-10-0. Dostupné z: https://msed.vse.cz/msed_2016/article/248-Stachova-Maria-paper.pdf

Abstract:
Financial distress is a situation in which a company cannot pay or has a difficulty to pay off its financial obligations. The crucial step in each analysis of companies’ financial status is to define the criteria that would describe the financial difficulties of enterprises with high accuracy. In our analyses of financial distress of Slovak companies, three criteria are considered: (1) the equity, (2) the earnings after taxes and (3) the current ratio value. Our main goal is to investigate if it is possible to identify homogeneous clusters regarding the companies’ financial health by using the financial longitudinal data. The k-means partitioning of companies is based on time trajectories of these criteria. The clustering is made by using statistical system R and the package “kml”. The results show, that recognition of patterns in panel data set can be helpful in the process of financial distress analysis, but it is necessary to add an expert point of view as well.

Keywords (CZ): finanční tíseň, shlukování longitudinálních dat, metoda k-průměrů

Keywords (EN): financial distress, longitudinal data clustering, k-means partitioning

Title: Financial distress criteria defined by model based clustering

Author: STACHOVÁ, Mária, SOBÍŠEK, Lukáš, GERTHOFER, Michal, HELMAN, Karel.

Year: 2017

Field: Finance

Publication type: Conference contribution (Web of Knowledge - CPCI)

Citation:
STACHOVÁ, Mária, SOBÍŠEK, Lukáš, GERTHOFER, Michal, HELMAN, Karel. Financial distress criteria defined by model based clustering. In: International Days of Statistics and Economics (MSED) [online]. Praha, 14.09.2017 – 16.09.2017. Slaný : Melandrium, Libuše Macáková, 2017, s. 1511–1520. ISBN 978-80-87990-12-4. Dostupné z: https://msed.vse.cz/msed_2017/article/28-Stachova-Maria-paper.pdf

Abstract:
In this paper we continue with our previous work that examined possibilities of the companies clustering in order to identify homogeneous clusters regarding to their financial distress. Financial distress can be described as a situation when a company cannot pay or has a difficulty to pay off its financial obligations. In our analysis we consider three criteria to define this situation: the equity, the earnings after taxes and the current ratio value. These financial indicators data were collected over a few consecutive years and thus create a longitudinal data set. We compare a model based partitioning and k-means partitioning to cluster the time trajectories of these three criteria. We use packages “mixAK” and “kml” of the statistical system R.

Keywords (CZ): finanční tíseň, shlukování longitudinálních a panelových dat, modelový přístup ke shlukování

Keywords (EN): financial distress, longitudinal data clustering, model based partitioning

Title: Fingolimod v reálné klinické praxi

Author: TICHÁ, V., SOBÍŠEK, Lukáš, HAVRDOVÁ, E.

Year: 2017

Field: Medical research

Publication type: paper (Web of Knowledge - JCR, Scopus)

Citation:
TICHÁ, V., SOBÍŠEK, Lukáš, HAVRDOVÁ, E. Fingolimod v reálné klinické praxi. Česká a slovenská neurologie a neurochirurgie. 2017, č. 2, s. 213–219. ISSN 1210-7859. DOI: https://doi.org/10.14735/amcsnn2017213 . web: http://www.csnn.eu/ceska-slovenska-neurologie-clanek/fingolimod-v-realne-klinicke-praxi-60567

Abstract:
Cíl:

Retrospektivní zhodnocení klinické účinnosti fingolimodu v prvním a druhém roce léčby u pacientů s aktivní roztroušenou sklerózou.

Soubor a metodika:

Jeden rok bylo léčeno 223 pacientů a 109 z nich dva roky fingolimodem. Na fingolimod bylo převedeno 126 pacientů z interferonu beta nebo glatiramer acetátu, 3 pacienti nebyli dosud léčeni a 94 pacientů bylo převedeno z natalizumabu.

Výsledky:

Četnost relapsů poklesla ve skupině pacientů převedených z interferonu beta nebo glatiramer acetátu o 72 % během prvního roku a o 64 % během prvních 2 let a ve skupině převedené z natalizumabu o 25 % v prvním roce a o 31 % během prvních 2 let. První rok léčby nemělo žádný relaps 66 % pacientů, během 2 let léčby bylo bez relapsu 50,5 % pacientů. Stabilní nebo zlepšené EDSS mělo v obou podskupinách během 1 i 2 let léčby 80 % pacientů. Potvrzenou šestiměsíční progresi EDSS nemělo 94,6 % pacientů z celé skupiny a bez známek klinické aktivity nemoci bylo v prvním roce 64,6 % a prvních 2 letech 50 % pacientů. Při wash-out periodě kratší než 63 dnů po ukončení natalizumabu se vyskytl relaps v prvních 6 měsících u 16,7 % pacientů a při wash-out periodě delší než 63 dnů u 25 % pacientů.

Závěr:

Fingolimod je účinný pro eskalaci léčby u pacientů selhávajících na Disease Modifying Drug nebo jako lék první volby u pacientů s vysokou aktivitou nemoci. Ve většině případů je účinnou alternativou léčby pro ty pacienty, kteří ukončí léčbu natalizumabem.

Keywords (CZ): roztroušená skleróza, fingolimod, natalizumab, eskalace

Keywords (EN): multiple sclerosis, fingolimod, natalizumab, escalation

Title: Identification of multiple sclerosis patients at highest risk of cognitive impairment using an integrated brain magnetic resonance imaging assessment approach

Author: UHER, Tomáš, VANĚČKOVÁ, Manuela, SORMANI, M. T., KRÁSENSKÝ, Jan, SOBÍŠEK, Lukáš, BLÁHOVÁ DUŠÁNKOVÁ, J., SEIDL, Zdeněk, HAVRDOVÁ, Eva, KALINČIK, Tomáš, BENEDICT, R. H. B., HORÁKOVÁ, Dana

Year: 2017

Field: Medical research

Publication type: paper (Web of Knowledge - JCR, Scopus)

Citation:
UHER, Tomáš, VANĚČKOVÁ, Manuela, SORMANI, M. T., KRÁSENSKÝ, Jan, SOBÍŠEK, Lukáš, BLÁHOVÁ DUŠÁNKOVÁ, J., SEIDL, Zdeněk, HAVRDOVÁ, Eva, KALINČIK, Tomáš, BENEDICT, R. H. B., HORÁKOVÁ, Dana. Identification of multiple sclerosis patients at highest risk of cognitive impairment using an integrated brain magnetic resonance imaging assessment approach. European Journal of Neurology [online]. 2017, roč. 24, č. 1, s. 292–301. ISSN 1351-5101. DOI: https://doi.org/10.1111/ene.13200

Abstract:
Background and purpose

While impaired cognitive performance is common in multiple sclerosis (MS), it has been largely underdiagnosed. Here a magnetic resonance imaging (MRI) screening algorithm is proposed to identify patients at highest risk of cognitive impairment. The objective was to examine whether assessment of lesion burden together with whole brain atrophy on MRI improves our ability to identify cognitively impaired MS patients.

Methods

Of the 1253 patients enrolled in the study, 1052 patients with all cognitive, volumetric MRI and clinical data available were included in the analysis. Brain MRI and neuropsychological assessment with the Brief International Cognitive Assessment for Multiple Sclerosis were performed. Multivariable logistic regression and individual prediction analysis were used to investigate the associations between MRI markers and cognitive impairment. The results of the primary analysis were validated at two subsequent time points (months 12 and 24).

Results

The prevalence of cognitive impairment was greater in patients with low brain parenchymal fraction (BPF) (<0.85) and high T2 lesion volume (T2-LV) (>3.5 ml) than in patients with high BPF (>0.85) and low T2-LV (<3.5 ml), with an odds ratio (OR) of 6.5 (95% CI 4.4–9.5). Low BPF together with high T2-LV identified in 270 (25.7%) patients predicted cognitive impairment with 83% specificity, 82% negative predictive value, 51% sensitivity and 75% overall accuracy. The risk of confirmed cognitive decline over the follow-up was greater in patients with high T2-LV (OR 2.1; 95% CI 1.1–3.8) and low BPF (OR 2.6; 95% CI 1.4–4.7).

Conclusions

The integrated MRI assessment of lesion burden and brain atrophy may improve the stratification of MS patients who may benefit from cognitive assessment.

Keywords (CZ): roztroušená skleróza, magnetická rezonance, disabilita, prediktory, mozková atrofie, léze

Keywords (EN): multiple sclerosis, magnetic resonance imaging, disability, predictors, brain atrophy, lesions

Title: Is no evidence of disease activity an achievable goal in MS patients on intramuscular interferon beta-1a treatment over long-term follow-up?

Author: UHER, Tomáš, HAVRDOVÁ, Eva, SOBÍŠEK, Lukáš, KRÁSENSKÝ, Jan, VANĚČKOVÁ, Manuela, SEIDL, Zdeněk, TÝBLOVÁ, Michaela, RAMASAMY, Deepat, ZIVADINOV, Robert, HORÁKOVÁ, Dana

Year: 2017

Field: Medical research

Publication type: paper (Web of Knowledge - JCR, Scopus)

Citation:
UHER, Tomáš, HAVRDOVÁ, Eva, SOBÍŠEK, Lukáš, KRÁSENSKÝ, Jan, VANĚČKOVÁ, Manuela, SEIDL, Zdeněk, TÝBLOVÁ, Michaela, RAMASAMY, Deepat, ZIVADINOV, Robert, HORÁKOVÁ, Dana. Is no evidence of disease activity an achievable goal in MS patients on intramuscular interferon beta-1a treatment over long-term follow-up? Multiple Sclerosis Journal [online]. 2017, roč. 23, č. 2, s. 242–252. ISSN 1352-4585. DOI: https://doi.org/10.1177/1352458516650525

Abstract:
Background:

No evidence of disease activity (NEDA) has been proposed as a new treatment goal in multiple sclerosis (MS). NEDA-3 status is defined as the absence of magnetic resonance imaging (MRI; new/enlarging/enhancing lesions and increased whole brain volume loss in NEDA-4) and clinical disease activity.

Objectives:

To investigate the persistence of NEDA status over long-term follow-up in MS patients treated with weekly intramuscular interferon beta-1a.

Methods:

We included 192 patients after the first demyelinating event suggestive of MS, that is, clinically isolated syndrome (CIS) and 162 relapsing-remitting MS (RRMS) patients.

Results:

NEDA-3 status was observed in 40.1% of CIS and 20.4% of RRMS patients after 1 year. After 4 years, 10.1% of CIS patients had NEDA-3 status. After 10 years, none of the RRMS patients had NEDA-3 status. Only 4.6% of CIS and 1.0% of RRMS patients maintained NEDA-4 status after 4 years. Loss of NEDA-3 status after the first year was associated with a higher risk of disability progression (hazard ratio (HR) = 2.3–4.0; p = 0.005–0.03) over 6 years.

Conclusions:

Despite intramuscular interferon beta-1a treatment, loss of NEDA status occurred in the vast majority of individuals. Loss of NEDA status during the first year was associated with disability progression over long-term follow-up; however, specificity for individual patient was low.

Keywords (CZ): roztroušená skleróza, žádná aktivita nemoci, interferony, magnetická rezonance, atrofie mozku

Keywords (EN): multiple sclerosis, no evidence of disease activity, interferons, magnetic resonance imaging, brain atrophy

Title: Lapse Prediction Using Penalized Logistic Regression

Author: SOBÍŠEK, Lukáš, STACHOVÁ, Mária, KRÁľ, Pavol.

Year: 2017

Field: Finance

Publication type: paper

Citation:
SOBÍŠEK, Lukáš, STACHOVÁ, Mária, KRÁľ, Pavol. Lapse Prediction Using Penalized Logistic Regression. FORUM STATISTICUM SLOVACUM, 2017, roč. 13, č. 1, s. 19-30. http://ssds.sk/sk/fss/fss201701/

Abstract:
The aim of our contribution is to estimate penalized regression models indicating policy lapses two years after inception. Our models are built on real customer’s data set provided by a Czech insurance company. Important lapse factors determined by a fitted lapse model may be used to create a commission strategy. Further, they can be integrated into the underwriting process in terms of the insurer’s refusal to conclude a contract with a customer with a high lapse probability. The models can serve as a benchmark to evaluate the overall performance as well as the performance of subgroups of policies in the company.

Keywords (CZ): benchmark, penalizovaná logistická regrese, predikce stornovosti

Keywords (EN): benchmark, penalized logistic regression, lapse prediction

Title: Lymphocyte populations and their change during five-year glatiramer acetate treatment

Author: PAVELEK, Zbyšek, VYŠATA, Oldřich, SOBÍŠEK, Lukáš, KLÍMOVÁ, Blanka, ANDRÝS, Ctirad, VOKURKOVÁ, Doris, MAZUROVÁ, Radka, ŠŤOURAČ, Pavel, VALIŠ, Martin.

Year: 2018

Field: Medical research

Publication type: paper (Web of Knowledge - JCR, Scopus)

Citation:
PAVELEK, Zbyšek, VYŠATA, Oldřich, SOBÍŠEK, Lukáš, KLÍMOVÁ, Blanka, ANDRÝS, Ctirad, VOKURKOVÁ, Doris, MAZUROVÁ, Radka, ŠŤOURAČ, Pavel, VALIŠ, Martin. Lymphocyte populations and their change during five-year glatiramer acetate treatment. Neurologia i Neurochirurgia Polska, 2018. roč. 52, Číslo: 5: s. 587– 592.

Abstract:
Background

The goal of this study was to determine the characteristics that are affected in patients treated with glatiramer acetate (GA).

Methods

A total of 113 patients were included in this study. Patients were treated with glatiramer acetate (subcutaneous injection, 20 mg, each day). Peripheral blood samples were obtained just prior to treatment as well as 5 years after GA treatment. All the calculations were performed with the statistical system R (r-project.org).

Results

After 5 years of treatment, a significant decrease was found in the absolute and relative CD3+/CD69+ counts, the absolute and relative CD69 counts, the relative CD8+/CD38+ count and the relative CD38 count. A significant increase was found in the absolute and relative CD5+/CD45RA+ counts and the absolute CD5+/CD45RO+ count after 5 years of treatment.

Conclusion

This study presents some parameters that were affected by long-term GA treatment.

Keywords (CZ): Roztroušená skleróza, lymfocyty, Glatiramir acetát, parametry, léčba

Keywords (EN): Multiple sclerosis, Lymphocytes, Glatiramer acetate, Parameters, Treatment

Title: Metody shlukové analýzy založené na Bayesově větě

Author: SOBÍŠEK, Lukáš, STACHOVÁ, Mária

Year: 2012

Field:

Publication type: paper

Citation:
SOBÍŠEK, Lukáš, STACHOVÁ, Mária. Metody shlukové analýzy založené na Bayesově větě. Forum Statisticum Slovacum. 2012, roč. VIII, č. 7, s. 173–180. ISSN 1336-7420

Abstract:
Úlohou zhlukovej analýzy dát, alebo skrátene zhlukovania, je zatriedenie jednotlivých objektov do navzájom disjunktných skupín (zhlukov) tak, aby objekt bol viac podobný ostatným objektom v rámci jedného zhluku, ako objektom vo zvyšných zhlukoch.

Metódy zhlukovania môžeme rozdeliť do dvoch kategórií: modelový prístup model-based a prístup založený na matici vzdialenosti/podobnosti distance-based (napr. hierarchické zhlukovanie, alebo metóda k-means). Metódy založené na matici vzdialenosti/podobnosti popisuje napr. Řezanková [13]. Bayesovské zhlukovanie modeluje dáta ako zmes latentných tried (ďalej iba tried).

Oproti metódam, ktoré priraďujú jednotlivé objekty jednoznačne do tried (ako sú metódy zhlukovej analýzy pre pevné zhlukovanie), bayesovský modelový prístup hľadá v dátach latentné triedy, ktoré čo „najlepšie“ charakterizujú príslušné objekty. Namiesto jednoznačného priradenia je pre objekty odhadnutá pravdepodobnosť príslušnosti k jednotlivým triedam. Pod pojmem trieda sa ukrýva parametrizované pravdepodobnostné rozdelenie.

V príspevku popisujeme všeobecný model latentných tried. Parametre modelu je možné odhadnúť dvomi prístupmi, pomocou naivného bayesovského klasifikátora, alebo pomocou bayesovských sietí [3]. Z dôvodu výrazne nižšej výpočtovej náročnosti je v štatistickom softvéri AutoClass, LatentGold a vo vybraných balíčkoch systému R aplikovaný prvý prístup. Tento prístup v článku popisujeme a ďalej sa zaoberáme špecifikáciami modelov implementovaných vo vymenovaných programov a ich využiteľnosť na rôzne typy dátových množín.

Keywords (CZ): AutoClass, latent gold, R softvér, shluková analýza, Bayesova věta

Keywords (EN): AutoClass, latent gold, R software, cluser analysis, Bayes theorem

Title: Porovnanie metód DBSCAN a CLARA na reálných dátach

Author: MACKOVIČOVÁ, Lenka, SOBÍŠEK, Lukáš, STACHOVÁ, Mária

Year: 2011

Field: Finance

Publication type: paper

Citation:
MACKOVIČOVÁ, Lenka, SOBÍŠEK, Lukáš, STACHOVÁ, Mária. Porovnanie metód DBSCAN a CLARA na reálných dátach. Forum Statisticum Slovacum. 2011, roč. 7, č. 7, s. 124–129. ISSN 1336-7420

Abstract:
The central task of this paper is to present two different clustering algorithms, namely CLARA (based on PAM) and DBSCAN algorithms. Both methods were used on real data set comes from Czech insurance company. These analyses were made using R software and its packages cluster, fpc a and lattice.

Keywords (CZ): algorutmus DBSCAN, algoritmus PAM, algoritmus CLARA, shluková analýza

Keywords (EN): DBSCAN algorithm, PAM algorithm, CLARA algorithm, cluster analysis

Title: Predikcia predčasného ukončenia poistnej zmluvy pomocou podmienených stromových štruktúr.

Author: STACHOVÁ, Mária, SOBÍŠEK, Lukáš

Year: 2013

Field: Finance

Publication type: paper

Citation:
STACHOVÁ, Mária, SOBÍŠEK, Lukáš. Predikcia predčasného ukončenia poistnej zmluvy pomocou podmienených stromových štruktúr. Forum statisticum slovacum. 2013, roč. 9, č. 7, s. 201–206. ISSN 1336-7420

Abstract:
We estimate lapse prediction models built on real customer’s data set, that comes from a Czech insurance company. We focused on conditional inference tree-based models and compared these models with classification tree model (CART) and Breiman’s random forest.

Keywords (CZ): model odhadu předčasného ukončení smlouvy, klasifikační modely rozhodovacích stromů, podmíněné klasifikační struktury

Keywords (EN): lapse prediction model, classification, conditional inference forest

Title: Quantification of Gait Abnormalities in Healthy-Looking Multiple Sclerosis Patients (with Expanded Disability Status Scale 0-1.5)

Author: NOVOTNÁ, K., SOBÍŠEK, Lukáš, HORÁKOVÁ, D., HAVRDOVÁ, E., LIZROVA PREININGEROVA, J.

Year: 2016

Field: Medical research

Publication type: paper (Web of Knowledge - JCR, Scopus)

Citation:
NOVOTNÁ, K., SOBÍŠEK, Lukáš, HORÁKOVÁ, D., HAVRDOVÁ, E., LIZROVA PREININGEROVA, J. Quantification of Gait Abnormalities in Healthy-Looking Multiple Sclerosis Patients (with Expanded Disability Status Scale 0-1.5). European Neurology [online]. 2016, roč. 76, č. 3–4, s. 99–104. ISSN 0014-3022. DOI: https://doi.org/10.1159/000448091. Dostupné také z: https://www.ncbi.nlm.nih.gov/pubmed/27497974

Abstract:
BACKGROUND:

Gait impairment is a common symptom in multiple sclerosis (MS) patients, but there is a lack of evidence about gait performance in the group of MS patients with no apparent disability. The aim of our study was to evaluate gait characteristics in MS patients with no apparent impairment of walking and with an Expanded Disability Status Scale (EDSS 0-1.5), and to determine whether any abnormalities are detectable by common clinical tests.

METHODS:

This was an observational study of 64 MS patients with an EDSS 0-1.5 and 47 age- and sex-matched healthy controls. We measured their performance in the timed 25-foot walk test (T25FWT) and the 2-minute walk test (2MWT). The spatiotemporal parameters of gait were measured using a GAITRite instrument.

RESULTS:

MS patients with no apparent disability (EDSS 0-1.5) performed worse in T25FWT and 2MWT than normal controls. During the self-selected walking speed test on GAITRite, MS patients had a prolonged double support phase, and during the fast walking speed test, they had lower cadence and decreased step length.

Keywords (CZ): roztroušená skleróza, chůze, chůzové testy, disabilita

Keywords (EN): multiple sclerosis, gait, walking tests, disability

Title: Serum lipid profile changes predict neurodegeneration in interferon-ß1a-treated multiple sclerosis patients.

Author: UHER, Tomáš, FELLOWS, Kelly, HORÁKOVÁ, Dana, ZIVADINOV, Robert, VANĚČKOVÁ, Manuela, SOBÍŠEK, Lukáš, TÝBLOVÁ, Michaela, SEIDL, Zdeněk, KRÁSENSKÝ, Jan, BERGSLAND, Niels, WEINSTOCK-GUTTMAN, Bianca, HAVRDOVÁ, Eva, RAMANATHAN, Murali.

Year: 2017

Field: Medical research

Publication type: paper (Web of Knowledge - JCR, Scopus)

Citation:
UHER, Tomáš, FELLOWS, Kelly, HORÁKOVÁ, Dana, ZIVADINOV, Robert, VANĚČKOVÁ, Manuela, SOBÍŠEK, Lukáš, TÝBLOVÁ, Michaela, SEIDL, Zdeněk, KRÁSENSKÝ, Jan, BERGSLAND, Niels, WEINSTOCK-GUTTMAN, Bianca, HAVRDOVÁ, Eva, RAMANATHAN, Murali. Serum lipid profile changes predict neurodegeneration in interferon-ß1a-treated multiple sclerosis patients. Journal of Lipid Research [online]. 2017, roč. 58, č. 2. 40 s. ISSN 0022-2275. DOI: https://doi.org/10.1194/jlr.M072751

Abstract:
The purpose of this work was to determine whether changes in cholesterol profiles after interferon-β (IFN-β)1a treatment initiation following the first demyelinating event suggestive of multiple sclerosis are associated with clinical and MRI outcomes over 4 years. A group of 131 patients (age: 27.9 ± 7.8 years, 63% female) with serial 3-monthly clinical and 12-monthly MRI follow-ups over 4 years were investigated. Serum cholesterol profiles, including total cholesterol (TC), HDL cholesterol (HDL-C), and LDL cholesterol (LDL-C) were obtained at baseline, 1 month, 3 months, and every 6 months thereafter. IFN-β1a initiation caused rapid decreases in serum HDL-C, LDL-C, and TC within 1 month of IFN-β1a initiation (all P < 0.001) that returned slowly toward baseline. In predictive mixed model analyses, greater percent decreases in HDL-C after 3 months of IFN-β1a treatment initiation were associated with less brain atrophy over the 4 year time course, as assessed by percent brain volume change (P < 0.001), percent gray matter volume change (P < 0.001), and percent lateral ventricle volume change (P = 0.005). Decreases in cholesterol biomarkers following IFN-β1a treatment are associated with brain atrophy outcomes over 4 years. Pharmacological interventions targeting lipid homeostasis may be clinically beneficial for disrupting neurodegenerative processes.

Keywords (CZ): cholesterol, léčebná terapie, HDL, zánět, LDL, roztroušená skleróza

Keywords (EN): cholesterol, drug therapy, HDL, inflammation, LDL, multiple sclerosis

Title: Srovnání metod pro redukci dimenzionality aplikovaných na ordinální proměnné

Author: SOBÍŠEK, Lukáš, ŘEZANKOVÁ, Hana

Year: 2011

Field:

Publication type: paper (seznam RVVI)

Citation:
SOBÍŠEK, Lukáš, ŘEZANKOVÁ, Hana. Srovnání metod pro redukci dimenzionality aplikovaných na ordinální proměnné. Acta Oeconomica Pragensia. 2011, roč. 19, č. 1, s. 3–19. ISSN 0572-3043

Abstract:
The data from questionnaires surveys are usually characterized by a great amount of ordinal variables. For multivariate analysis, it is suitable to reduce dimensionality of a task. The aim of this paper is comparison of the results obtained by the analysis of data files with ordinal variables by means of selected methods for dimensionality reduction. The results are in the form of values of individual components (e.g. factor loadings). For the better interpretation and comparability, they were consequently analyzed by fuzzy clustering. On the basis of the obtained clusters of variables we determined the optimal number of dimensions. We applied silhouette and Dunn’s partition coefficients. Further, we tried to merge the results received by individual methods on the basis of technique sCSPA (soft version of cluster-based similarity partitioning algorithm). We considered different groups of methods and searched the best solution. The problems are illustrated by means of two real data files obtained from questionnaires surveys.

Keywords (CZ): redukce dimenzionality, diskrétní faktorová analýza, kategoriální analýza hlavních komponent, vícerměrné škálování, modely latetních tříd, fuzzy shluková analýza

Keywords (EN): dimensionality reduction, discrete factor analysis, categorical principal component analysis, multidimensional scaling, latent class models, fuzzy cluster analysis

Title: Srovnání účinnosti subkutánně podávaného interferonu β-1a 44 μg, dimetyl fumarátu a fingolimodu v reálné klinické praxi – multicentrická observační studie

Author: PAVELEK, Zbyšek, SOBÍŠEK, Lukáš, HORÁKOVÁ, Dana, VALIŠ, Martin.

Year: 2018

Field: Medical research

Publication type: paper (Web of Knowledge - JCR, Scopus)

Citation:
PAVELEK, Zbyšek, SOBÍŠEK, Lukáš, HORÁKOVÁ, Dana, VALIŠ, Martin. Srovnání účinnosti subkutánně podávaného interferonu β-1a 44 μg, dimetyl fumarátu a fingolimodu v reálné klinické praxi – multicentrická observační studie. Cesk Slov Neurol N, 2018. roč. 81, Číslo: 114(4): s. 457– 465.

Abstract:
Úvod:
Roztroušená skleróza je chronické zánětlivé a neurodegenerativní onemocnění postihující CNS. Mezi etablované léky pro relaps-remitentní RS (RR RS) patří interferon (IFN) β-1a44 μg, dimetyl fumarát (DMF) a fingolimod. Cílem projektu, resp. výstupem z analýzy z registru ReMuS, bylo srovnat účinnost subkutánně podávaného IFN β-1a 44 μg, DMF a fingolimodu u pacientů s RR RS, u nichž byla zahájena tato léčba do 90 dní od počátku relapsu, v reálné klinické praxi v ČR.

Soubor a metodika:
Do projektu bylo zahrnuto celkem 279 pacientů s RR RS, kteří prodělali při léčbě 1. linie (IFN β-1a 22 μg 3× týdně, IFN β-1a 30 μg 1× týdně , IFN β-1b 250 μg obden, teriflunomid 14 mg denně, glatiramer acetát 20 mg denně nebo glatiramer acetát 40 mg 3× týdně) jeden relaps a kterým byla léčba změněna buď na IFN β-1a 44 μg nebo DMF či fingolimod. Sledovanými parametry byly roční počet relapsů (annualized relapse rate; ARR), doba do dalšího relapsu, zastoupení pacientů bez relapsu a změna Expanded Disability Status Scale (EDSS) po roce od změny léčby u jednotlivých preparátů.

Výsledky:
Po změně terapie došlo u všech třech sledovaných preparátů během roční observace k signifikantnímu zlepšení analyzovaných parametrů. Při porovnání skupiny pacientů s léčbou IFN β-1a 44 μg (83 pa cientů) vs. fingolimod nebo DMF (196 pa cientů) bylo ve druhé skupině významnější zlepšení v parametru ARR a změna EDSS. Po spárování pacientů na terapii IFN β-1a 44 μg se skupinou léčenou DMF nebo fingolimodem v poměru 1 : 1 metodou propensity score matching (83 vs. 83 pacientů) zůstal signifi kantní vliv na zlepšení sledovaných parametrů před změnou terapie a po ní v obou skupinách, neprokázali jsme ale již signifikantní rozdíl efektu mezi skupinami.

Závěr: IFN β-1a 44 μg, DMF i fingolimod prokázaly svou účinnost v rámci eskalace léčby na vybrané skupině pacientů v parametrech změna EDSS a čas do dalšího relapsu.

Keywords (CZ): roztroušená skleróza, interferon β-1a 44 μg, dimetyl fumarát, fingolimod

Keywords (EN): Multiple sclerosis, interferon β-1a 44 μg, dimethyl fumarate, fingolimod

Title: Thalamic Iron Differentiates Primary-Progressive and Relapsing-Remitting Multiple Sclerosis.

Author: BURGETOVÁ, A., DUŠEK. P., VANĚČKOVÁ, M., HORÁKOVÁ, D., LANGKAMMER, C., KRÁSENSKÝ, J., SOBÍŠEK, L., MATRAS, P., MAŠEK, M., SEIDL, Z.

Year: 2017

Field: Medical research

Publication type: paper (Web of Knowledge - JCR, Scopus)

Citation:
BURGETOVÁ, A., DUŠEK. P., VANĚČKOVÁ, M., HORÁKOVÁ, D., LANGKAMMER, C., KRÁSENSKÝ, J., SOBÍŠEK, L., MATRAS, P., MAŠEK, M., SEIDL, Z. Thalamic Iron Differentiates Primary-Progressive and Relapsing-Remitting Multiple Sclerosis. Americal Journal of Neuroradiology. 2017, roč. 38, č.6 , s. 1079-1086. DOI: https://doi.org/10.3174/ajnr.A5166

Abstract:
BACKGROUND AND PURPOSE: Potential differences between primary progressive and relapsing remitting multiple sclerosis are the subject of ongoing controversial discussions. The aim of this work was to determine whether and how primary-progressive and relapsing-remitting multiple sclerosis subtypes differ regarding conventional MR imaging parameters, cerebral iron deposits, and their association with clinical status.

MATERIALS AND METHODS: We analyzed 24 patients with primary-progressive MS, 80 with relapsing-remitting MS, and 20 healthy controls with 1.5T MR imaging for assessment of the conventional quantitative parameters: T2 lesion load, T1 lesion load, brain parenchymal fraction, and corpus callosum volume. Quantitative susceptibility mapping was performed to estimate iron concentration in the deep gray matter.

RESULTS: Decreased susceptibility within the thalamus in relapsing-remitting MS compared with primary-progressive MS was the only significant MR imaging difference between these MS subtypes. In the relapsing-remitting MS subgroup, the Expanded Disability Status Scale score was positively associated with conventional parameters reflecting white matter lesions and brain atrophy and with iron in the putamen and caudate nucleus. A positive association with putaminal iron and the Expanded Disability Status Scale score was found in primary-progressive MS.

CONCLUSIONS: Susceptibility in the thalamus might provide additional support for the differentiation between primary-progressive and relapsing-remitting MS. That the Expanded Disability Status Scale score was associated with conventional MR imaging parameters and iron concentrations in several deep gray matter regions in relapsing-remitting MS, while only a weak association with putaminal iron was observed in primary-progressive MS suggests different driving forces of disability in these MS subtypes.

Keywords (CZ): roztroušení skleróza, MRI, QSM, železo, hluboká šedá hmota, léze, EDSS, primárně progresivní RS, relaps remitentní RS

Keywords (EN): Multiple sclerosis, MRI, QSM, Iron, Deep gray matter, Lesion load, Expanded Disability Status Scale, Primary progressive MS, Relapsing remitting MS

Title: Towards personalized therapy for multiple sclerosis: prediction of individual treatment response.

Author: KALINČÍK Tomáš, MANOUCHEHRINIA, Ali, SOBÍŠEK, Lukáš, a kol.

Year: 2017

Field: Medical research

Publication type: paper (Web of Knowledge - JCR, Scopus)

Citation:
KALINČÍK Tomáš, MANOUCHEHRINIA, Ali, SOBÍŠEK, Lukáš, a kol. Towards personalized therapy for multiple sclerosis: prediction of individual treatment response. Brain, 2017, roč. 140, č. 9, s. 2426–2443, https://doi.org/10.1093/brain/awx185

Abstract:
Timely initiation of effective therapy is crucial for preventing disability in multiple sclerosis; however, treatment response varies greatly among patients. Comprehensive predictive models of individual treatment response are lacking. Our aims were:

(i) to develop predictive algorithms for individual treatment response using demographic, clinical and paraclinical predictors in patients with multiple sclerosis; and

(ii) to evaluate accuracy, and internal and external validity of these algorithms. This study evaluated 27 demographic, clinical and paraclinical predictors of individual response to seven disease-modifying therapies in MSBase, a large global cohort study.

Treatment response was analysed separately for disability progression, disability regression, relapse frequency, conversion to secondary progressive disease, change in the cumulative disease burden, and the probability of treatment discontinuation. Multivariable survival and generalized linear models were used, together with the principal component analysis to reduce model dimensionality and prevent overparameterization. Accuracy of the individual prediction was tested and its internal validity was evaluated in a separate, non-overlapping cohort. External validity was evaluated in a geographically distinct cohort, the Swedish Multiple Sclerosis Registry.

In the training cohort (n= 8513), the most prominent modifiers of treatment response comprised age, disease duration, disease course, previous relapse activity, disability, predominant relapse phenotype and previous therapy. Importantly, the magnitude and direction of the associations varied among therapies and disease outcomes. Higher probability of disability progression during treatment with injectable therapies was predominantly associated with a greater disability at treatment start and the previous therapy. For fingolimod, natalizumab or mitoxantrone, it was mainly associated with lower pretreatment relapse activity. The probability of disability regression was predominantly associated with pre-baseline disability, therapy and relapse activity. Relapse incidence was associated with pretreatment relapse activity, age and relapsing disease course, with the strength of these associations varying among therapies. Accuracy and internal validity (n= 1196) of the resulting predictive models was high (480%) for relapse incidence during the first year and for disability outcomes, moderate for relapse incidence in Years 2–4 and for the change in the cumulative disease burden, and low for conversion to secondary progressive disease and treatment discontinuation.

External validation showed similar results, demonstrating high external validity for disability and relapse outcomes, moderate external validity for cumulative disease burden and low external validity for conversion to secondary progressive disease and treatment discontinuation. We conclude that demographic, clinical and paraclinical information helps predict individual response to disease- modifying therapies at the time of their commencement.

Keywords (CZ): roztroušená skleróza; predikce; disabilita; relapsy; precizní medicína

Keywords (EN): multiple sclerosis; prediction; disability; relapses; precision medicine

Title: Use of Panel Data Analysis for V4 Households Poverty Risk Prediction

Author: SOBÍŠEK, Lukáš, STACHOVÁ, Mária

Year: 2016

Field:

Publication type: Conference contribution (Web of Knowledge - CPCI, Scopus - CP)

Citation:
SOBÍŠEK, Lukáš, STACHOVÁ, Mária. Use of Panel Data Analysis for V4 Households Poverty Risk Prediction. In: 2nd European Conference on Data Analysis, ECDA 2014 [online]. Bremen, 02.07.2014 – 04.07.2014. Berlín : Springer, 2016, s. 599–608. Studies in Classification, Data Analysis, and Knowledge Organization. ISBN 978-3-319-25224-7. ISSN 1431-8814. DOI: https://doi.org/10.1007/978-3-319-25226-1_51

Abstract:
One of the main approaches to tracking causality between income, social inclusion and living conditions is based on regression models estimated using various statistical methods. This approach takes into account quantitative and qualitative information about individuals or households that is collected in different periods of time (years in particular), thus allowing it to be transformed into multidimensional data sets, called panel data. Regression models based on panel data are able to describe the dynamics over time periods, so that the patterns can be related to changes in other characteristics. This paper utilises one of these approaches to panel data analysis RE-EM trees which are used to predict the risk-of-poverty rate of households located in the four “Visegrad” countries. The risk-of-poverty rate of individual households is computed on the basis of cluster analysis results, and it takes into account household living conditions as well as income. Subsequently, the risk-of-poverty rate is used as the outcome for the prediction model above. Certain household characteristics were chosen as predictors including: information about the “head” of the household (age, education level, marital status, etc.) and information about the number of members in the household. The results show slight differences in poverty determinants among Visegrad countries. The determinants with the highest impact on the risk-of-poverty rate are: number of household members (Czech Republic, Hungary and Slovakia) and education level (Poland).

Keywords (CZ): predikce míry chudoby domácností zemí V4, RE-EM rozhodovací algoritmy, shluková analýza

Keywords (EN): prediction of poverty rate of household in V4, RE-EM trees, cluster analysis

Title: Utilization of Mixed Effects Models and RE‐EM Tree Method in Financial Distress Prediction

Author: SOBÍŠEK, Lukáš, HELMAN, Karel, STACHOVÁ, Mária.

Year: 2017

Field: Finance

Publication type: paper

Citation:
SOBÍŠEK, Lukáš, HELMAN, Karel, STACHOVÁ. Utilization of Mixed Effects Models and RE‐EM Tree Method in Financial Distress Prediction. FORUM STATISTICUM SLOVACUM, 2017, roč. 13, č. 2, s. 48-56. http://ssds.sk/casopis/archiv/2017/fss0217.pdf#page=50

Abstract:
There are several approaches to financial analysis ex‐ante. Some of them are based on static classification models, e.g. logistic regression, classification trees or discriminant analysis. These analyses are carried out to study a relationship between financial health indicators of companies. These financial indicators are often collected over several consecutive years, thus the data have the form of panel data. In our paper, we focus on regression analysis of panel data to predict financial health of companies. We fit generalized mixed effects model in order to improve the prediction ability the RE‐EM classifier.

Keywords (CZ): Zobecněný regresní model se smíšenými efekty, finanční zdraví podniku, RE‐EM model

Keywords (EN): Generalized regression mixed effect model, financial health of companies, RE-EM tree model

Title: Utilization of Repeatedly Measured Financial Ratios in Corporate Financial Distress Prediction in Slovakia

Author: KRÁĽ, Pavol, STACHOVÁ, Mária, SOBÍŠEK, Lukáš

Year: 2014

Field: Finance

Publication type: Conference contribution (Web of Knowledge - CPCI)

Citation:
KRÁĽ, Pavol, STACHOVÁ, Mária, SOBÍŠEK, Lukáš. Utilization of Repeatedly Measured Financial Ratios in Corporate Financial Distress Prediction in Slovakia. In: AMSE [CD ROM]. Jerzmanovice, 27.08.2014 – 31.08.2014. Wroclaw : Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu, 2014, s. 156–163. ISBN 978-83-7695-421-9

Abstract:
One of the main approaches to financial analysis ex-ante is based on static classification models constructed using various statistical methods, e.g. discriminant analysis, logistic regression, decision trees. This approach takes into account quantitative characteristics of selected companies at the given time point, most typically three or four years prior the time of possible bankruptcy. If these characteristics are collected during a longer time period we can improve financial distress prediction models via incorporating dynamics into them. In the presented paper we focus on a simple case when only measurements of financial ratios in two consecutive time points are available. The main goal of our paper is to present how changes in financial ratios can be utilized in models predicting corporate financial distress. We illustrate our approach on two different data sets of Slovak companies in two different periods. Finally, we compare classification ability of models incorporating changes in financial ratios between two consecutive data points to classification ability of models estimated using a single time point data.

Keywords (CZ): finanční analýza ex-ante, dynamika finančních poměrových ukazatelů

Keywords (EN): financial analysis ex - ante, changes in financial ratios, bankruptcy models

Title: What Variability of Treatment Effect of Fampridine Can We Expect in People with Multiple Sclerosis?

Author: NOVOTNÁ, Klára, PREININGEROVÁ LÍZROVÁ, Klára, SOBÍŠEK, Lukáš, HAVRDOVÁ, Eva.

Year: 2017

Field: Medical research

Publication type: paper (Web of Knowledge - JCR, Scopus)

Citation:
NOVOTNÁ, Klára, PREININGEROVÁ LÍZROVÁ, Klára, SOBÍŠEK, Lukáš, HAVRDOVÁ, Eva. What Variability of Treatment Effect of Fampridine Can We Expect in People with Multiple Sclerosis? Journal of Multiple Sclerosis, 2017, roč. 4, č. 3, s. 1-5, https://www.omicsonline.org/open-access/what-variability-of-treatment-effect-of-fampridine-can-we-expect-in-people-with-multiple-sclerosis-2376-0389-1000206.pdf

Abstract:
Background:

Gait impairment represents one of the most common symptoms of multiple sclerosis (MS). Fampridine is the first symptomatic treatment aimed at improving gait.An objective measurement of the mobility improvement from treatment initiation has been recommended to evaluate treatment response.

Objective:

In this retrospective observational study, we evaluated what improvement in walking speed can be expected in people with multiple sclerosis (MS) treated with Fampridine in clinical practice, with respect to specific disability levels (EDSS 4.0-7.0).

Methods:

The mobility tests including the Timed 25 foot walk test (T25FW), Timed Up and Go test (TUG) and Step test (ST) were performed just before and 3 h after administration of Fampridine 10 mg tablet.

Results:

One hundred and thirty one (131) people with MS (15 with primary progressive, 40 with secondary progressive and 76 people with relapsing-remitting MS). The mean age was 48 years (SD 9.8), mean MS duration was 19, 8 years, 58% were women. The range of treatment response of Fampridine, measured with the T25FW test, varied from 11-41%. Contrary to prior reports, the baseline T25FW and the percentage of improvement in T25FW was significantly correlated.

Conclusion:

Assessment of treatment response outside of a clinical trial is challenging and may require different outcome measures compared to RCT. For MS patients with moderate disability seems TUG test or Step test more appropriate for quantifying treatment response.

Keywords (CZ): Roztroušená skleróza; Chůze; Disabilita; Symptomatická léčba; Fampridine

Keywords (EN): Multiple sclerosis; Gait; Disability; Symptomatic treatment; Fampridine