Prevalence of Anxiety among Hungarian Subjects with Parkinson’s Disease

Kovács, Márton; Makkos, Attila; Weintraut, Rita; Karádi, Kázmér; Janszky, József; Kovács, Norbert

doi:https://doi.org/10.1155/2017/1470149

Behavioural Neurology

On this page

Abstract Introduction Materials and Methods Results Discussion Conclusions Abbreviations Ethical Approval Conflicts of Interest Authors’ Contributions Acknowledgments Supplementary Materials References Copyright Related Articles

Research Article | Open Access

Volume 2017 | Article ID 1470149 | https://doi.org/10.1155/2017/1470149

Prevalence of Anxiety among Hungarian Subjects with Parkinson’s Disease

Márton Kovács,¹Attila Makkos,¹Rita Weintraut,¹Kázmér Karádi,¹József Janszky,^1,2and Norbert Kovács^1,2

Academic Editor: Luigi Trojano

Received10 May 2017

Revised27 Jul 2017

Accepted03 Aug 2017

Published26 Sept 2017

Abstract

Although anxiety is one of the most frequent symptoms of Parkinson’s disease (PD), only a few clinical tools can efficiently and reliably detect its presence. The aim of the present study was to validate the Hungarian patient-rated version of Parkinson Anxiety Scale (PAS). A total of 190 PD patients were enrolled into the clinimetric validation phase of the study and another 590 participated in the cross-sectional screening phase. The presence of anxiety disorder was diagnosed based on the Diagnostic and Statistical Manual of Mental Disorders criteria. The cutoff value for PAS which best discriminated the presence of anxiety from the absence was 12.5 points (sensitivity of 88.6%, specificity of 79.9). The area under the curve was 0.847 whereas the ROC analysis yielded the statistical significance level (). The optimal threshold values for mild (Hoehn and Yahr Stage, HYS 1 and 2), moderate (HYS 3), and severe (HYS 4 and 5) disease stages were 10.5, 12.5, and 13.5 points, respectively. Based on the general threshold anxiety occurred in 35.8% of the patients (persistent anxiety: 29.2%, episodic anxiety: 20.7%, and avoidant anxiety disorder: 16.8%). We demonstrate that the PAS is a valid, highly reliable, and sensitive tool for assessing anxiety.

1. Introduction

Among the nonmotor symptoms of Parkinson’s disease (PD), the affective problems have utmost importance. According to epidemiological studies, the frequency of anxiety disorders is higher than that of depressive problems being between 25–49% [1, 2]. The spectrum of anxiety is extremely wide including panic attacks, agoraphobia without panic disorder, social phobia, and generalized anxiety disorder. Besides the general problems of anxiety, PD patients frequently experience disease-specific symptomatology including distress, worry, fear, agitation, embarrassment, and social withdrawal due to motor symptoms and complications of antiparkinsonian medication [3, 4]. Besides producing immense suffering, anxiety has a serious impact on the daily living and health-related quality of life (HRQoL) [5].

In the clinical setup, reliable and highly sensitive tools are required to identify anxiety problems and monitor the therapeutic response. Commonly applied instruments, such as Hamilton Anxiety Rating Scale (HAM-A), the Beck Anxiety Inventory, and the Hospital Anxiety and Depression Scale, have unsatisfactory discriminating abilities [6]. With the help of The Michael J. Fox Foundation, the Parkinson Anxiety Scale (PAS) was recently developed and validated to overcome the limitation of the abovementioned anxiety scales and to provide a license-free clinical and research tool for the PD population [7].

The PAS is a 12-item tool which can be either rated by a trained professional (observer version) or by the patients themselves (patient-rated version). The PAS make up three different subscales describing the persistent anxiety (5 items), episodic anxiety (4 items), and avoidance behavior (3 items) [7]. Each item can be scored on a 5-point Likert scale, with “0” meaning “not or never” and “4” meaning “severe or almost always” implying a maximum of total score of 48 points. According to its developers, the assessment of the self-rated version can be completed in less than 2 minutes, whereas the observer-rated version may take up to 5 minutes. Based on a multinational, multicenter, and cross-sectional validation study enrolling 360 PD patients, the PAS had better clinimetric properties than any other existing scale making it a brief and nevertheless valid and highly reliable tool.

The PAS scale was originally developed in four languages simultaneously (English, Spanish, French, and Dutch) and subsequently translated into Italian [8]. Since the prevalence and perceived difficulties associated with anxiety differ among cultures, the cross-cultural validation of the PAS is clearly needed. Because Hungarian is a Finno-Ugric language originating from the Uralic language family vastly different from the Anglo-Saxon and Latin languages, we aimed to validate the Hungarian version of the PAS. Subsequently, we utilized this Hungarian version of PAS scale for determining the prevalence and severity of anxiety in a large pool of Hungarian subjects with PD in a cross-sectional study.

2. Materials and Methods

2.1. Patients

While in the validation part of the study, 190 consecutive patients fulfilling the clinical criteria for PD were enrolled, another 590 PD subjects participated in the subsequent part assessing the prevalence of anxiety. Each subject gave written informed consent in accordance with the ethical approval of the Regional and Institutional Ethical Committee of the University of Pécs (5624/2015), and subsequently they were examined by a neurologist specializing in movement disorders. Besides recording demographic data (age, sex, and level of education), disease-specific data were noted (age at onset; disease duration; the presence of motor complications; duration of fluctuation in years; type of PD, being either tremor dominant, akinetic rigid, or mixed type; and antiparkinsonian medication). Patients were evaluated in ON state while receiving their usual antiparkinsonian and other medications, and subsequently levodopa equivalent dosage (LED) calculations were performed [9].

2.2. Validation of the Hungarian Parkinson Anxiety Scale

Two native Hungarian speakers fluent in English translated independently the PAS into Hungarian, and an English-speaking psychologist back-translated the PAS into English. Subsequently, the original and the back-translated versions were compared and any discrepancies were fixed to achieve the first Hungarian patient-rated and observer-rated PAS. Cognitive debriefing was applied on 25 patients before field testing.

The self-rated version of PAS was administered to 190 consecutive PD patients. Exclusion criteria for participation were the following: (1)Clinical diagnosis of PD in accordance with the UK Brain Bank criteria could not be met [10](2)Presence of major neurocognitive disorder in accordance with the Diagnostic and Statistical Manual of Mental Disorders (Fifth edition, DSM-5) criteria [11](3)The presence of any neurological or psychiatric condition possibly interfering the study

2.3. Neurological and Neuropsychological Assessments

The severity of PD-related symptoms was globally assessed by the Hungarian-validated version of the MDS-UPDRS [12, 13]. The recently published MDS-UPDRS is a validated scale to assess nonmotor (nM-EDL, Part I) and motor experiences of daily living (M-EDL, Part II), motor examination (ME, Part III), and motor complications (MC, Part IV) [13]. As a part of the MDS-UPDRS, the Hoehn and Yahr Scale (HYS) was also taken to detect the overall severity of PD. Disease severity was categorized as mild (HYS 1 and 2), moderate (HYS 3), and severe (HYS 4 and 5) [14, 15].

The nM-EDL part of the MDS-UPDRS has items evaluating the presence and severity of 13 NMS including depression and anxiety [13]. These items are intended to serve as screening tools for the presence of these nonmotor symptoms [16]. To assess nonmotor symptoms globally, the Nonmotor Symptoms Scale (NMSS) [17, 18] was also included. This scale is obtained by trained professionals and capable of simultaneously capturing the severity and frequency of 30 nonmotor symptoms typical for PD. Severity of depression was assessed by the Hungarian-validated versions of the Montgomery Depression Scale (MADRS) [19] and the Beck Depression Inventory; whereas, the severity of anxiety was measured by the Hamilton Anxiety Scale (HAM-A) [20] and the PAS, and apathy was rated by the Lille Apathy Rating Scale (LARS) [21].

Patients were screened for the presence of mild and major neurocognitive disorders by validated neurocognitive tests [22] (Montreal Cognitive Assessment, cutoff scores <23.5 and <20.5, respectively, and Mattis Dementia Rating Scale, cutoff scores <139.5 and <132.5 points, resp.) [23, 24]. Health-related quality of life (HRQoL) was measured by the Hungarian-validated version of the disease-specific PDQ-39 Summary Index (PDQ-39 SI) [25, 26]. Subsequently, the presence of anxiety in accordance with the DSM-5 criteria [11] was assessed by a trained neuropsychiatrist in the validation phase.

2.4. Statistical Analysis

For variables following the normal distribution (e.g., age, disease duration), means ± standard deviations (SD) were calculated. Data quality was defined as the proportion of computable data. The criterion for an acceptable amount of missing data is <10% [27]. For acceptability, the floor and ceiling effect should be kept <15% [28], and the skewness should range between −1 and +1 [29].

Before the structure of the scale was explored by a factor analysis, the value of Kaiser-Meyer-Olkin measure of sampling accuracy (KMO) was calculated. A KMO >0.60 is a minimum requirement; whereas, KMOs >0.90 are considered as excellent for factor analysis. We accepted only those factors having an eigenvalue >1 and a Scree test for factor analysis.

In the clinimetrics, reliability is the overall consistency of a measure. A measure is said to have a high reliability if it produces similar results under consistent conditions [30]. In our study, the internal consistency was evaluated by four different approaches [31]: (i)Cronbach’s α should be >0.70 [32].(ii)Corrected item-total correlation should be >0.30 for each item.(iii)Item homogeneity coefficient should be >0.30.(iv)Test-retest properties (Intraclass Correlation Coefficient, ICC should be >0.6) [33]. The retest properties of the PAS were analyzed on a subset of patients () one day after the initial examination.

The validity of an assessment is the degree to which it measures what it is supposed to measure. Therefore, it corresponds to how a measurement is well founded and accurately describes the real world [30]. In our study, the construct validity was evaluated by three different methods: (i)Convergent validity: convergent validity refers to the degree to which a measure is correlated with other measures that it is theoretically predicted to correlate [30]. The total score and the subscores of PAS were compared to the “Anxiety” item of MDS-UPDRS and HAM-A. For correlation, Spearman’s rank correlation coefficients were calculated. The values of correlation coefficients (r_S) can indicate weak (0–0.299), moderate (0.300–0.599), and high (0.600–1.000) association [34].(ii)Internal validity: the correlation between the domains (subscales) should not be too low (r_S< 0.300) or too high (r_S> 0.700) either [35].(iii)Divergent validity: divergent validity tests whether concepts or measurements that are supposed to be unrelated are, in fact, unrelated [30]. We tested the discriminative validity of the PAS against apathy (Lille Apathy Rating Scale), depressive syndromes (BDI and MADRS), and cognitive functioning (MoCA) by calculating Spearman rank correlation coefficients [7].

The precision of the PAS was estimated by the standard error of measurement (SEM), where the value of SEM should be less than the half of the standard deviation.

In order to establish a cutoff value for the total score of the PAS, which can reliably differentiate PD patients with and without anxiety, we applied receiver operating curve (ROC) analysis. Patients were categorized by the DSM-5 criteria for anxiety disorders. This categorization served as the state variable and the PAS total score as the test variable. The best cutoff value was estimated as the point on the ROC curve closest to the point of (0.1). It was calculated as the minimum value of the square root of (1 − sensitivity)² + (1 − specificity)². Besides, the area under the curve, specificity, sensitivity, and positive and negative likelihood ratios were calculated for the best cutoff value. After establishing the optimal threshold for the whole population, separate cutoff limits were calculated for the different disease severity categories.

All statistical analyses were carried out using IBM SPSS software package (version 24.0.0.1, IBM Inc., Chicago, USA). Statistical significance level was set to 5%. Because the SPSS Suite did not have built-in functions for calculating positive and negative likelihood ratios, we utilized the syntax available on the IBM website (http://www-01.ibm.com/support/docview.wss?uid=swg21483380, assessed on Jan 15, 2013).

2.5. Determining the Prevalence of Anxiety among Hungarian PD Patients

Utilizing the newly determined cutoff score for the presence of anxiety, a large pool of PD patients were screened (). The presence and severity of anxiety was assessed by the patient-rated version of PAS.

3. Results

3.1. Validation of the Hungarian Parkinson Anxiety Scale

The subject population consisted of 190 PD patients without major neurocognitive disorder, and their clinical characteristics are demonstrated in Table 1. As for the quality of data, there was no missing data. The skewness of the scale was within the limit (0.828). Only a few patients had a total score of 0 on PAS (4.6%) and no one achieved a maximum score; therefore, the floor and ceiling effects were acceptable.

The KMO value was sufficiently high (0.909) to enable a factor analysis. The Scree test supported a three-factor solution explaining 67.6% of the variance. Using the Principal Component Analysis extraction method with Promax rotation, we identified the same factor structure as it was originally described.

The value of Cronbach’s α for the total score and the persistent, episodic, and avoidance domains was acceptable (0.935, 0.897, 0.828, and 0.724, resp.). All the items reached the 0.30 threshold value for the item-total correlation. Item homogeneity index values were acceptable for all subdomains and the total score of PAS. The total score of PAS demonstrated high Spearman’s rank correlation coefficient with both HAM-A and MDS-UPDRS “Anxiety” item (0.618 and 0.602). The internal validity for the subdomains of PAS was acceptable (r_S values in the range of 0.300–0.700). The test-retest validity was also acceptable (ICC = 0.824). As far as the discriminative properties were considered, the total score of PAS had poor correlation with LARS (rho = 0.226, ), MoCA (rho = −0.185, ), and moderate correlation with depression (MADRS rho = 0.536, , and BDI rho = 0.586, , overall population). In patients without anxiety, the rho values were 0.219 and 0.317 for MADRS and BDI; whereas, in the presence of anxiety, these values increased to 0.504 and 0.584, respectively. These discriminant values were similar to those of the original PAS validation study [7] and the Italian language validation study [8]. The precision was acceptable for both the domains and the total score of PAS.

Based on the DSM-5 criteria, 78 patients (41.1%) had an anxiety disorder. Generalized anxiety was found in 52 (27.3%), agoraphobia and social phobia in 48 patients (25.3%), and panic disorder in 31 patients (16.3%).

The cutoff value for PAS which best discriminated the presence of anxiety from the absence was 12.5 points. Therefore a PAS score ≥ 13 points may suggest the presence of anxiety (sensitivity of 88.6%, specificity of 79.9%, positive likelihood ratio: 2.64, and negative likelihood ratio: 0.17). The area under the curve (AUC) was 0.847 whereas the ROC analysis yielded the statistical significance level (). The optimal threshold values for mild, moderate, and severe disease stages were slightly different (10.5, 12.5, and 13.5 points, resp.). Subsequently, we also calculated the most optimal threshold values for each subscale (Table 2).

3.2. Prevalence of Anxiety among Hungarian PD Patients

In most cases, it took approximately 2–5 minutes to administer the scale if the patients completed by themselves. Based on the general threshold (12.5 points), anxiety occurred in 211 patients (35.8%). While persistent anxiety was found in 172 (29.2%), only 122 patients (20.7%) had episodic anxiety and another 99 patients (16.8%) had an avoidant anxiety disorder. Demographic and disease-specific data of the PD patients with and without anxiety are demonstrated in Table 3. Patients with anxiety had more severe PD-related symptoms (higher scores on all domains of MDS-UPDRS), depressive symptoms (BDI and MADRS), worse neurocognitive performance (MDRS and MoCA), and worse HRQoL (measured by PDQ-39).

4. Discussion

The aim of the present study was to validate the Hungarian patient-reported version of the PAS by assessing its fundamental clinimetric properties and subsequently determining the prevalence and severity of anxiety among Hungarian PD patients. After a standardized translation and back-translation of the scale, we initiated a hospital-based validation study on a large diversity of patients having disease severity from minimal to severe. Our results demonstrated excellent data quality, high reliability and validity, and good precision. These findings are consistent with the results of the original [7] and the Italian [8] validation studies.

The original validation study revealed the cutoff score of 13.5 points for the most optimal discrimination between the PD patients having and not having an anxiety disorder for both the patient-reported and observed-rated versions. However, a considerably smaller threshold (8.5 points) was calculated in the Italian validation study for the observer-rated version. This inconsistency was presumably contributed to some clinical and methodological factors. While the Italian sample included only patients with early disease stages (HYS 1 and 2), the original validation study not only had higher sample size (362 versus 101) but their subjects also had longer disease duration (10.4 versus 8.3 years), wider disease spectrum (HYS 1–4), and more pronounced Parkinsonian symptoms (UPDRS score: 24.7 versus 13.3 points). Moreover, the prevalence rate of anxiety disorders diagnosed by the DSM criteria used as “gold standard” was also dissimilar between the two aforementioned validation studies (27% versus 38.6%).

Our calculated threshold value (12.5) is much closer to that of the original validation study (13.5 points). Acknowledging the conclusions of the Italian validation study by hypothesizing the role of disease severity in the differences of anxiety threshold value, we included PD patients with a high diversity of disease stages (HYS 1–5) and calculated distinct threshold values for the different disease severity stages.

Based on the obtained cutoff threshold, we identified the prevalence of anxiety among Hungarian PD patients of which 35.8% is in the range of the internationally published range [1, 2]. Similar to previous findings, we also demonstrated that the presence of anxiety was associated with worse motor performance, cognitive performance, and more severely impaired health-related quality of life [36, 37].

5. Conclusions

The Hungarian patient-rated version of the Parkinson Anxiety Scale is a valid, highly reliable, and sensitive tool for assessing the presence and severity of the anxiety symptoms. Although our uniform threshold value may efficiently identify patients with anxiety, different threshold values may be utilized for different disease stages.

Abbreviations

AUC:	Area under the curve
BDI:	Beck Depression Inventory
DSM-5:	Diagnostic and Statistical Manual of Mental Disorders, Fifth edition
HAM-A:	Hamilton Anxiety Scale
HYS:	Hoehn and Yahr Stage
ICC:	Intraclass Correlation Coefficient
LARS:	Lille Apathy Rating Scale
LED:	Levodopa equivalent dosage
MADRS:	Montgomery-Asberg Depression Rating Scale
MDS-UPDRS:	Movement Disorders Society-sponsored version of Unified Parkinson’s Disease Rating Scale
MDS-UPDRS MC:	Motor complications (Part IV of MDS-UPDRS)
MDS-UPDRS ME:	Motor examination (Part III of MDS-UPDRS)
MDS-UPDRS M-EDL:	Motor experiences of daily living (Part II of MDS-UPDRS)
MDS-UPDRS nM-EDL:	Nonmotor experiences of daily living (Part I of MDS-UPDRS)
MoCA:	Montreal Cognitive Assessment
PD:	Parkinson’s disease
PAS:	Parkinson Anxiety Scale
ROC:	Receiver operation curve analysis
SD:	Standard deviation.

Ethical Approval

Informed consent was obtained from all individual participants included in the study as approved by the Regional and Institutional Ethical Committee of the University of Pécs (5624/2015).

Conflicts of Interest

Regarding this study, there is no conflict of interest. Attila Makkos reported no financial disclosure. Márton Kovács reported no financial disclosure. József Janszky received <1000 EUR consultation fees from Hungarian subsidiaries of UCB, Valeant, and Eisai. Regarding this pilot study, the authors did not receive any corporate funding. Norbert Kovács received <1000 EUR consultation fees from Hungarian subsidiaries of Medtronic, Boehringer Ingelheim, Novartis, GlaxoSmithKline, UCB, Krka, and AbbVie. Regarding this study, the author did not receive any corporate funding.

Authors’ Contributions

Márton Kovács and Attila Makkos contributed equally to this work.

Acknowledgments

This study was supported by the New National Excellence Program (ÚNKP-16-IV), the Hungarian Brain Research Program—Grant no. KTIA_13_NAP-A-II/10 government-based funds (Norbert Kovács and József Janszky), and EFOP-3.6.1-16-2016-00004 (Attila Makkos and Márton Kovács). The present scientific contribution is dedicated to the 650th anniversary of the foundation of the University of Pécs, Hungary.

Supplementary Materials

The validated Hungarian Parkinson Anxiety Scale.

Supplementary Material

References

M. P. Broen, N. E. Narayen, M. L. Kuijf, N. N. Dissanayaka, and A. F. Leentjens, “Prevalence of anxiety in Parkinson’s disease: a systematic review and meta-analysis,” Movement Disorders, vol. 31, no. 8, pp. 1125–1133, 2016.
View at: Publisher Site | Google Scholar
N. N. Dissanayaka, A. Sellbach, S. Matheson et al., “Anxiety disorders in Parkinson’s disease: prevalence and risk factors,” Movement Disorders, vol. 25, no. 7, pp. 838–845, 2010.
View at: Publisher Site | Google Scholar
N. N. Dissanayaka, J. D. O'Sullivan, N. A. Pachana et al., “Disease-specific anxiety symptomatology in Parkinson’s disease,” International Psychogeriatrics, vol. 28, no. 7, pp. 1153–1163, 2016.
View at: Publisher Site | Google Scholar
S. E. Starkstein, M. Dragovic, K. Dujardin et al., “Anxiety has specific syndromal profiles in Parkinson disease: a data-driven approach,” The American Journal of Geriatric Psychiatry, vol. 22, no. 12, pp. 1410–1417, 2014.
View at: Publisher Site | Google Scholar
F. J. Carod-Artal, S. Ziomkowski, H. Mourao Mesquita, and P. Martinez-Martin, “Anxiety and depression: main determinants of health-related quality of life in Brazilian patients with Parkinson’s disease,” Parkinsonism & Related Disorders, vol. 14, no. 2, pp. 102–108, 2008.
View at: Publisher Site | Google Scholar
N. N. Dissanayaka, E. Torbey, and N. A. Pachana, “Anxiety rating scales in Parkinson’s disease: a critical review updating recent literature,” International Psychogeriatrics, vol. 27, no. 11, pp. 1777–1784, 2015.
View at: Publisher Site | Google Scholar
A. F. Leentjens, K. Dujardin, G. M. Pontone, S. E. Starkstein, D. Weintraub, and P. Martinez-Martin, “The Parkinson Anxiety Scale (PAS): development and validation of a new anxiety scale,” Movement Disorders, vol. 29, no. 8, pp. 1035–1043, 2014.
View at: Publisher Site | Google Scholar
G. Santangelo, F. Falco, A. D'Lorio et al., “Anxiety in early Parkinson’s disease: validation of the Italian observer-rated version of the Parkinson Anxiety Scale (OR-PAS),” Journal of the Neurological Sciences, vol. 367, pp. 158–161, 2016.
View at: Publisher Site | Google Scholar
C. L. Tomlinson, R. Stowe, S. Patel, C. Rick, R. Gray, and C. E. Clarke, “Systematic review of levodopa dose equivalency reporting in Parkinson’s disease,” Movement Disorders, vol. 25, no. 15, pp. 2649–2653, 2010.
View at: Publisher Site | Google Scholar
I. Litvan, K. P. Bhatia, D. J. Burn et al., “Movement Disorders Society Scientific Issues Committee report: SIC task force appraisal of clinical diagnostic criteria for Parkinsonian disorders,” Movement Disorders, vol. 18, no. 5, pp. 467–486, 2003.
View at: Publisher Site | Google Scholar
American Psychiatric Association, Diagnostic and Statistical Manual of Mental Disorders, American Psychiatric Publishing, Arlington, VA, 5th edition, 2013.
K. Horvath, A. Zsuzsanna, P. Acs et al., “Validation of the Hungarian MDS-UPDRS: why do we need a new Parkinson scale?” Ideggyógyászati Szemle, vol. 67, no. 3-4, pp. 129–134, 2014.
View at: Google Scholar
C. G. Goetz, B. C. Tilley, S. R. Shaftman et al., “Movement Disorder Society-sponsored revision of the Unified Parkinson’s Disease Rating Scale (MDS-UPDRS): scale presentation and clinimetric testing results,” Movement Disorders, vol. 23, no. 15, pp. 2129–2170, 2008.
View at: Publisher Site | Google Scholar
K. Horváth, Z. Aschermann, P. Ács et al., “Minimal clinically important difference on the motor examination part of MDS-UPDRS,” Parkinsonism & Related Disorders, vol. 21, no. 12, pp. 1421–1426, 2015.
View at: Publisher Site | Google Scholar
K. Horváth, Z. Aschermann, M. Kovács et al., “Minimal clinically important differences for the experiences of daily living parts of Movement Disorder Society-sponsored Unified Parkinson’s Disease Rating Scale,” Movement Disorders, vol. 32, no. 5, pp. 789–793, 2017.
View at: Publisher Site | Google Scholar
K. Horváth, Z. Aschermann, P. Acs et al., “Is the MDS-UPDRS a good screening tool for detecting sleep problems and daytime sleepiness in Parkinson’s disease?” Parkinsons Disease, vol. 2014, article 806169, 8 pages, 2014.
View at: Publisher Site | Google Scholar
P. Martinez-Martin, C. Rodriguez-Blazquez, K. Abe et al., “International study on the psychometric attributes of the non-motor symptoms scale in Parkinson disease,” Neurology, vol. 73, no. 19, pp. 1584–1591, 2009.
View at: Publisher Site | Google Scholar
M. Kovács, A. Makkos, Z. Aschermann et al., “Impact of sex on the nonmotor symptoms and the health-related quality of life in Parkinson’s disease,” Parkinsons Disease, vol. 2016, article 7951840, 12 pages, 2016.
View at: Publisher Site | Google Scholar
G. Deli, Z. Aschermann, P. Ács et al., “Bilateral subthalamic stimulation can improve sleep quality in Parkinson’s disease,” Journal of Parkinson's Disease, vol. 5, no. 2, pp. 361–368, 2015.
View at: Publisher Site | Google Scholar
A. F. Leentjens, K. Dujardin, L. Marsh, I. H. Richard, S. E. Starkstein, and P. Martinez-Martin, “Anxiety rating scales in Parkinson’s disease: a validation study of the Hamilton Anxiety Rating Scale, the Beck Anxiety Inventory, and the Hospital Anxiety and Depression Scale,” Movement Disorders, vol. 26, no. 3, pp. 407–415, 2011.
View at: Publisher Site | Google Scholar
R. Weintraut, K. Karádi, T. Lucza et al., “Lille Apathy Rating Scale and MDS-UPDRS for screening apathy in Parkinson’s disease,” Journal of Parkinson’s Disease, vol. 6, no. 1, pp. 257–265, 2016.
View at: Publisher Site | Google Scholar
B. Kaszás, N. Kovács, I. Balás et al., “Sensitivity and specificity of Addenbrooke’s Cognitive Examination, Mattis Dementia Rating Scale, Frontal Assessment Battery and Mini Mental State Examination for diagnosing dementia in Parkinson’s disease,” Parkinsonism & Related Disorders, vol. 18, no. 5, pp. 553–556, 2012.
View at: Publisher Site | Google Scholar
T. Lucza, K. Karádi, J. Kállai et al., “Screening mild and major neurocognitive disorders in Parkinson’s disease,” Behavioural Neurology, vol. 2015, Article ID 983606, 10 pages, 2015.
View at: Publisher Site | Google Scholar
T. Lucza, K. Karádi, S. Komoly et al., “Neurocognitive disorders in Parkinson’s disease,” Orvosi Hetilap, vol. 156, no. 23, pp. 915–926, 2015.
View at: Publisher Site | Google Scholar
N. Kovács, Z. Aschermann, P. Ács et al., “Levodopa/carbidopa intestinalis gél kezelés hatása az életminőségre [the impact of levodopa-carbidopa intestinal gel on health-related quality of life in Parkinson’s disease],” Ideggyógyászati Szemle, vol. 67, no. 7-8, pp. 245–250, 2014.
View at: Google Scholar
K. Horváth, Z. Aschermann, M. Kovács et al., “Changes in quality of life in Parkinson’s disease: how large must they be to be relevant?” Neuroepidemiology, vol. 48, no. 1-2, pp. 1–8, 2017.
View at: Publisher Site | Google Scholar
J. C. Hobart, A. Riazi, D. L. Lamping, R. Fitzpatrick, and A. J. Thompson, “Improving the evaluation of therapeutic interventions in multiple sclerosis: development of a patient-based measure of outcome,” Health Technology Assessment, vol. 8, no. 9, pp. 1–48, 2004, iii.
View at: Publisher Site | Google Scholar
C. A. McHorney and A. R. Tarlov, “Individual-patient monitoring in clinical practice: are available health status surveys adequate?” Quality of Life Research, vol. 4, no. 4, pp. 293–307, 1995.
View at: Publisher Site | Google Scholar
R. D. Hays, R. Anderson, and D. Revicki, “Psychometric considerations in evaluating health-related quality of life measures,” Quality of Life Research, vol. 2, no. 6, pp. 441–449, 1993.
View at: Publisher Site | Google Scholar
J. Nunnally and I. Bernstein, Psychometric Theory, McGraw-Hill, New York, 1994.
N. Kovács, K. Horváth, Z. Aschermann et al., “Independent validation of Parkinson’s disease Sleep Scale 2nd version (PDSS-2),” Sleep and Biological Rhythms, vol. 14, no. 1, pp. 63–73, 2016.
View at: Publisher Site | Google Scholar
N. Aaronson, J. Alonso, A. Burnam et al., “Assessing health status and quality-of-life instruments: attributes and review criteria,” Quality of Life Research, vol. 11, no. 3, pp. 193–205, 2002.
View at: Google Scholar
K. Horváth, Z. Aschermann, P. Acs et al., “Test-retest validity of Parkinson’s Disease Sleep Scale 2nd version (PDSS-2),” Journal of Parkinson's Disease, vol. 4, no. 4, pp. 687–691, 2014.
View at: Publisher Site | Google Scholar
P. Martinez-Martin, K. R. Chaudhuri, J. M. Rojo-Abuin et al., “Assessing the non-motor symptoms of Parkinson’s disease: MDS-UPDRS and NMS Scale,” European Journal of Neurology, 2013.
View at: Google Scholar
J. Hobart, D. Lamping, R. Fitzpatrick, A. Riazi, and A. Thompson, “The Multiple Sclerosis Impact Scale (MSIS-29): a new patient-based outcome measure,” Brain, vol. 124, Part 5, pp. 962–973, 2001.
View at: Publisher Site | Google Scholar
N. N. Dissanayaka, R. A. Lawson, A. J. Yarnall et al., “Anxiety is associated with cognitive impairment in newly-diagnosed Parkinson’s disease,” Parkinsonism & Related Disorders, vol. 36, pp. 63–68, 2017.
View at: Publisher Site | Google Scholar
M. P. Broen, S. Köhler, A. J. Moonen et al., “Modeling anxiety in Parkinson’s disease,” Movement Disorders, vol. 31, no. 3, pp. 310–316, 2016.
View at: Publisher Site | Google Scholar

Copyright

Copyright © 2017 Márton Kovács et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

PDF Download Citation

Download other formats

Order printed copies

Views

1190

Downloads

1468

Citations