Literature DB >> 27819413

The KMDS-NATION Study: Korean Movement Disorders Society Multicenter Assessment of Non-Motor Symptoms and Quality of Life in Parkinson's Disease NATION Study Group.

Do Young Kwon1, Seong Beom Koh1, Jae Hyeok Lee2, Hee Kyung Park3, Han Joon Kim4, Hae Won Shin5, Jinyoung Youn6, Kun Woo Park1, Sun Ah Choi7, Sang Jin Kim8, Seong Min Choi9, Ji Yun Park10, Beom S Jeon4, Ji Young Kim11, Sun Ju Chung12, Chong Sik Lee12, Jeong Ho Park13, Tae Beom Ahn14, Won Chan Kim15, Hyun Sook Kim15, Sang Myung Cheon16, Hee Tae Kim17, Jee Young Lee18, Ji Sun Kim19, Eun Joo Kim20, Jong Min Kim21, Kwang Soo Lee22, Joong Seok Kim22, Min Jeong Kim23, Jong Sam Baik24, Ki Jong Park25, Hee Jin Kim26, Mee Young Park27, Ji Hoon Kang28, Sook Kun Song28, Yong Duk Kim29, Ji Young Yun30, Ho Won Lee31, Hyung Geun Oh32, Jinwhan Cho6, In Uk Song33, Young H Sohn34, Phil Hyu Lee34, Jae Woo Kim35.   

Abstract

BACKGROUND AND
PURPOSE: Nonmotor symptoms (NMS) in Parkinson's disease (PD) have multisystem origins with heterogeneous manifestations that develop throughout the course of PD. NMS are increasingly recognized as having a significant impact on the health-related quality of life (HrQoL). We aimed to determine the NMS presentation according to PD status, and the associations of NMS with other clinical variables and the HrQoL of Korean PD patients.
METHODS: We surveyed patients in 37 movement-disorders clinics throughout Korea. In total, 323 PD patients were recruited for assessment of disease severity and duration, NMS, HrQoL, and other clinical variables including demographics, cognition, sleep scale, fatigability, and symptoms.
RESULTS: In total, 98.1% of enrolled PD subjects suffered from various kinds of NMS. The prevalence of NMS and scores in each NMS domain were significantly higher in the PD group, and the NMS worsened as the disease progressed. Among clinical variables, disease duration and depressive mood showed significant correlations with all NMS domains (p<0.001). NMS status impacted HrQoL in PD (rS=0.329, p<0.01), and the association patterns differed with the disease stage.
CONCLUSIONS: The results of our survey suggest that NMS in PD are not simply isolated symptoms of degenerative disease, but rather exert significant influences throughout the disease course. A novel clinical approach focused on NMS to develop tailored management strategies is warranted to improve the HrQoL in PD patients.

Entities:  

Keywords:  Parkinson's disease; non-motor symptoms; quality of life

Year:  2016        PMID: 27819413      PMCID: PMC5063863          DOI: 10.3988/jcn.2016.12.4.393

Source DB:  PubMed          Journal:  J Clin Neurol        ISSN: 1738-6586            Impact factor:   3.077


INTRODUCTION

Parkinson's disease (PD) is a multisystem disorder that is characterized by a combination of various motor symptoms and nonmotor symptoms (NMS). The motor symptoms associated with PD are well known and are commonly treated by clinicians.123 In contrast, recent studies of NMS have yielded mixed results despite these symptoms increasingly being recognized as an important part of PD symptoms and a significant cause of disability and, consequently, poor quality of life in PD patients.4567 The various NMS in PD can be classified into four domains: neuropsychiatric, sensory, autonomic, and sleep symptoms.8 Among these, rapid-eye-movement sleep behavior disorder (RBD), constipation, depression, and olfactory dysfunction appear during the premotor stages of PD and are often referred to as prodromal signs.4791011 However, other NMS such as cognitive impairment, genitourinary dysfunction, gastrointestinal (GI) dysfunction, sleep disturbance, and visual hallucinations are associated with advancing age and disease severity.7 Accordingly, patients with advanced PD tend to have more severe NMS.6 The health-related quality of life (HrQoL) is considered critical in patients with neurodegenerative disorders, and recent PD research has increasingly focused on factors that affect HrQoL. HrQoL is closely associated with the severity of NMS,121314 and NMS of PD are known to have a greater impact on HrQoL than do motor symptoms.6 Therefore, it is important to determine the NMS status of PD patients in large populations in order to better understand the impact of PD. In this Nonmotor symptoms And qualiTy of life In ParkinsON's disease (NATION) study, we investigated NMS characteristics and their impact on HrQoL using a nationwide multicenter design. We aimed to determine the prevalence and severity of NMS according to the disease stage, status, and motor subtypes, and also the factors that influence each NMS domain and affect HrQoL.

METHODS

Study design

The NATION study was a cross-sectional investigation that included data from 37 movement-disorders clinics widely distributed throughout South Korea. Principal investigators of participating clinics who were members of the Korean Movement Disorders Society (KMDS) were invited to take part in the study. Each clinic was confirmed to have the ability to implement the study protocol based on its previous participation in clinical studies. The study protocol was approved by the institutional review board of each institute, and all subjects were required to provide informed consent in compliance with the regulations of that board.

Subjects

The study included PD patients and healthy controls who were recruited between March 2012 and January 2013. PD was diagnosed based on the UK Parkinson's Disease Society Brain Bank criteria, and patients were consecutively enrolled according to disease status as follows: 1) de novo group, any stage of PD with no prior anti-PD medications, 2) mild-to-moderate group [modified Hoehn & Yahr (H&Y) stage of ≤3] taking anti-PD medication, and 3) severe group (modified H&Y stage 4 or 5) taking anti-PD medication. To increase the reliability of PD diagnosis, all PD patients were reassessed 6 months after the initial enrollment date. Normal controls were recruited from volunteer caregivers of the patients at the inpatient and outpatient clinics who had no evidence of neurological or serious medical illnesses in their medical history or a neurological examination. The following exclusion criteria were applied: 1) history of systemic disease that might affect NMS or HrQoL (e.g., cancer or organ failure); 2) history of medication that might affect parkinsonism, NMS, or HrQoL; and 3) psychiatric illness or dementia [Mini Mental State Examination (MMSE) score of <20 points] restricting the understanding of the questionnaire.

Methods

We assessed the following demographic characteristics of the patients: sex, age, age at onset, duration of disease, marital state, occupation, and economic status. The modified H&Y stage and the Unified Parkinson's Disease Rating Scale (UPDRS) were used to evaluate the overall severity of disease, including motor disabilities.1516 The clinical motor phenotype was classified according to Jancovic et al.17 The presence of motor complications (motor fluctuation and dyskinesia) was also assessed based on interviews and medical records. NMS were assessed based on the Korean version of the Nonmotor Symptoms Scale (K-NMSS),18 Parkinson's Disease Sleep Scale (PDSS), Beck Depression Scale (BDI), Beck Anxiety Inventory (BAI), and Parkinson Fatigue Scale (PFS). The Korean version of the MMSE (K-MMSE),19 the Korea version of the Montreal Cognitive Assessment (MoCA-K),20 and the Korean version of the Frontal Lobe Assessment Battery (K-FAB)21 were used to evaluate cognitive function. The Korean version of the Neuropsychiatric Inventory Questionnaire (K-NPI)22 was used to assessed behavioral and psychological symptoms. HrQoL was assessed using the Parkinson's Disease Questionnaire-39 (PDQ-39).23 The motor phenotype was determined according to the UPDRS motor score. Each domain of the K-NMSS was used to assess the severity of NMS.

Statistical analysis

The SPSS software package (version 15.0K for Windows, SPSS Inc., Chicago, IL, USA) was applied for all statistical evaluations. ANOVA was used for comparisons of groups conforming to normal distributions, while the Mann-Whitney U and Kruskal-Wallis tests were used to compare variables that did not conform to a normal distribution. All comparisons between groups for each variable were carried out using Fisher's exact test, and linear-by-linear associations were determined with Bonferroni's post-hoc analysis. Spearman's rank correlation coefficients were used to identify associations with other variables. Logistic regression analysis was used to assess the relative contributions of clinical variables to the total K-NMSS score. A difference was considered significant when the p value was <0.05.

RESULTS

Demographic and clinical background information

In total, 323 PD patients [153 men, 170 women; age, 66.80±9.64 (mean±SD) years; median age, 69 years] and 94 healthy controls (33 men, 61 women; age, 62.96±9.39 years; median age, 64 years) were enrolled in the study. The demographic and clinical characteristics of the participants are presented in Supplementary Table 1 (in the online-only Data Supplement). The most common occupation was farming (n=286, 64.4%). The PD patients were divided into three subgroups: de novo PD (n=121), early PD (n=142), and advanced PD (n=60), in which the H&Y stages were 1.88±0.75, 2.05±0.61, and 4.12±0.32, respectively. The PD patients were classified according to motor phenotype into the 1) tremor-dominant (TD) group (n=27), 2) intermediate group (n=32), and 3) postural instability and gait disturbance (PIGD) group (n=264). As indicated in Supplementary Table 1 (in the online-only Data Supplement), there were significant differences between PD patients and healthy control in scores on the PDSS, BDI, BAI, PFS, K-MMSE, MoCA-K, K-FAB, and K-NPI. The PDSS scores did not differ significantly between the PD subgroups. The BDI scores indicated that the depression severity was significantly greater in the advanced PD group than in the de novo PD and early PD groups. Analysis of the BAI scores indicated that anxiety was more severe in the advanced PD group than in the de novo PD group; however, the BAI score did not differ significantly between the de novo PD and early PD groups or between the early PD and advanced PD groups. The PFS score was higher in the advanced PD group than in the de novo PD group, but did not differ significantly between the de novo PD and early PD groups or between the early PD and advanced PD groups. Analysis of the K-MMSE scores indicated that global cognitive dysfunction occurred more frequently in the advanced PD group than in the de novo PD and early PD groups, but that its prevalence did not differ significantly between the de novo PD and early PD groups. However, comparison of the MoCA-K and K-FAB scores showed significant differences only between the early PD and advanced PD groups. These results are summarized in Supplementary Table 2 (in the online-only Data Supplement).

NMS scale scores in the PD and control groups

The prevalence of NMS and mean scores on the K-NMSS in the PD and normal control groups are presented in Table 1. The prevalence of NMS was significantly higher in PD patients (98.1%) than in the control group (73.4%) for all K-NMSS domains. All of the K-NMSS domain scores were significantly higher in PD patients than in the normal controls. The mean number of NMS in PD patients was 5.27 out of 12 domains. The mean number of affected K-NMSS domains was higher in advanced PD patients (6.73) than in de novo PD patients (4.38) and early PD patients (5.40). The most common K-NMSS domains affecting PD patients were the sleep/fatigue (82%), mood/cognition problems (79.3%), attention/memory problems (77.4%), and urinary dysfunction (73.7%), with perception problems/hallucination (23.8%), weight change (25.4%), and excessive sweating (29.7%) being less frequent. In addition, compared with the control group, the PD patients showed higher prevalence ratios for perception problems/hallucination, weight change, pain, GI dysfunction, and taste/smell function, with PD-to-control ratios of 7.44, 5.91, 3.77, 3.15, and 3.04, respectively. The total score on the K-NMSS was higher (51.1±53.0) in the group with a higher PD onset age (>65 years, n=211) than in the group with an age at onset of <5 years (36.6±35.8). The former group also had higher scores in the dysautonomic domain, including (in descending order) cardiovascular, GI, and urinary dysfunctions, sleep/fatigue, and perception problems/hallucination.
Table 1

Prevalence and mean scores of NMSS domains between control and PD patients

NMSS domainNMS prevalenceNMSS score (mean±SD)
Controls (n=94), number (%)PD patients (n=323), number (%)Ratio prevalencep-valueControlsPD patientsRatio scorep-value
Cardiovascular (including falls)30 (31.9)152 (59.0)1.850.003*0.91±2.03 (0)2.15±3.82 (0)2.360.013*
Sleep/fatigue55 (58.5)262 (82.0)1.40<0.001*2.70±3.74 (1)7.89±9.66 (5)2.92<0.001*
Mood/cognition46 (48.9)253 (79.3)1.62<0.001*2.91±6.49 (0)10.78±13.49 (6)3.7<0.001*
Perceptual/hallucinations3 (3.2)73 (23.8)7.440.005*0.04±0.25 (0)1.46±4.86 (0)36.5<0.001*
Attention/memory47 (50.0)248 (77.4)1.550.007*2.10±3.42 (0.5)4.97±6.27 (3)2.37<0.001*
Gastrointestinal17 (18.1)174 (57.0)3.15<0.001*0.57±1.74 (0)3.75±5.86 (1)6.58<0.001*
Urinary41 (44.7)234 (73.7)1.650.002*2.31±4.07 (0)7.43±9.16 (4)3.22<0.001*
Sexual function16 (17.0)116 (36.2)2.130.048*1.57±4.83 (0)2.77±6.00 (0)1.76<0.001*
Pains7 (7.4)84 (27.9)3.77<0.001*0.18±0.75 (0)1.33±2.82 (0)7.39<0.001*
Taste/smell function10 (10.6)100 (32.2)3.04<0.001*0.22±0.78 (0)1.49±2.87 (0)6.77<0.001*
Weight change4 (4.3)80 (25.4)5.91<0.001*0.09±0.48 (0)0.81±2.12 (0)9<0.001*
Excessive sweating9 (9.6)93 (29.7)3.09<0.001*0.22±0.84 (0)1.24±2.66 (0)5.64<0.001*
Total69 (73.4)316 (98.1)1.34<0.001*13.84±16.95 (8)46.07±48.17 (33)3.33<0.001*

Ratio prevalence; PD patients:controls NMS prevalence ratio. Ratio score; PD patients:controls NMSS mean score ratio. NMSS score: data=mean±SD (median).

*Significant p<0.05, Wilcoxon rank sum test for median values.

NMS: nonmotor symptoms, NMSS: non-motor symptom scale, PD: Parkinson's disease.

NMS scale based on PD stage

The total number of affected K-NMSS domains increased with the PD stage. There were considerable differences in the total number of affected domains even in the de novo PD and control groups. Each K-NMSS domain score was significantly higher in the advanced PD group than in the de novo PD and early PD groups, with the exception of pain (Table 2, Fig. 1).
Table 2

NMSS scores according to the subgroup of PD patients

De novo PD (n=121)Early PD (n=142)Advanced PD (n=60)p valuep valuep value§
Cardiovascular (including falls)1.31±2.881.86±3.414.53±5.340.663<0.001*<0.001*
Sleep/fatigue5.71±7.606.89±7.4914.60±11.530.780<0.001*<0.001*
Mood/cognition7.93±10.639.33±12.7919.95±16.321.000<0.001*<0.001*
Perceptual/hallucinations0.33±1.161.21±3.644.58±9.040.519<0.001*<0.001*
Attention/memory3.77±4.644.67±6.348.08±7.860.713<0.001*<0.001*
Gastrointestinal2.42±3.933.13±4.937.90±8.720.926<0.001*<0.001*
Urinary5.34±7.266.91±8.5512.85±11.700.451<0.001*<0.001*
Sexual function2.33±5.661.88±4.175.73±8.871.000<0.001*<0.001*
Pains1.30±2.911.04±2.322.03±3.571.0000.0710.294
Taste/smell function0.77±2.041.35±2.533.23±4.120.272<0.001*<0.001*
Weight change0.65±1.920.53±1.441.82±3.321.000<0.001*0.001*
Excessive sweating0.61±1.801.27±2.552.43±3.760.1240.011*<0.001*
Total35.51±31.9640.00±40.1987.75±67.010.506<0.001*<0.001*

Data=mean±SD.

*Significant p<0.05, †Comparison between de novo and early PD, ‡Comparison between early PD and advanced PD, §Comparison between de novo and advanced PD.

NMSS: non-motor symptom scale, PD: Parkinson's disease.

Fig. 1

Scores of domain (or items) of NMSS according to the subgroup of PD patients (de novo:early:advanced). CV: cardiovascular, GI: gastrointestinal, NMSS: non-motor symptom scale, PD: Parkinson's disease.

NMS prevalence according to motor subtype

The prevalence of NMS and NMS domain scores according to motor subtype are presented in Table 3. Only the GI symptoms were more frequent in the PIGD than the TD subtype. Additionally, the GI score was the only symptom that was significantly worse in the PIGD than the TD subtype. Although the scores in the other NMS domains tended to be worse in the PIGD subtype than in the TD subtype, the results were not statistically significant. The number of affected NMS domains did not differ significantly with the motor PD subtype.
Table 3

NMS prevalence and scores according to the motor subtype of PD patients

NMS prevalence (%)NMS scores
PIGD (n=264)Intermed. (n=32)TD (n=27)p valuePIGD (n=264)Intermediate (n=32)TD (n=27)p value
Cardiovascular (including falls)135 (48.9%)16 (50%)13 (48.1%)0.9892.26±3.782.53±3.982.26±4.880.932
Sleep/fatigue229 (83%)28 (87.5%)19 (70.4%)0.1898.78±9.665.97±6.667.22±9.740.227
Mood/cognition219 (79.3%)26 (81.3%)21 (77.8%)0.94611.82±14.59.53±10.719.93±13.040.582
Perceptual/hallucinations70 (25.4%)5 (15.6%)6 (22.2%)0.4621.85±5.560.63±1.840.96±2.030.333
Attention/memory220 (79.7%)23 (71.9%)18 (66.7%)0.2045.88±7.303.28±3.334.11±5.830.077
Gastrointestinal171 (62.0%)11 (34.4%)9 (33.3%)<0.001*4.45±6.232.38±4.832.07±5.620.040*
Urinary210 (76.2%)19 (59.4%)20 (74.1%)0.6048.19±9.625.38±6.646.37±8.700.195
Sexual function104 (37.7%)12 (37.5%)6 (22.2%)0.5793.31±6.432.23±5.131.03±3.190.194
Pains83 (30.1%)5 (15.6%)6 (22.2%)0.4691.47±2.931.06±2.691.00±2.750.571
Taste/smell function49 (32.3%)13 (40.6%)7 (25.9%)0.7831.46±2.811.97±2.811.85±3.770.549
Weight change74 (26.8%)6 (18.8%)7 (25.9%)0.8900.89±2.160.78±2.511.07±2.770.880
Excessive sweating84 (30.4%)8 (25.0%)8 (29.6%)0.8171.42±2.890.75±1.811.37±3.070.449

*p<0.05, †Statistical significances were tested by Two-by-K cross tabulation method (Pearson chi-square).

NMSS: non-motor symptom scale, PIGD: postural instability and gait disturbance type, TD: tremor-dominant type.

NMS scale domain and association with clinical variables

After adjusting for age, all K-NMSS domains were significantly correlated with disease duration and all NMS, with the exception of the mood/cognition domain, which was correlated with the total PD motor score (UPDRS part III score) and the total levodopa equivalent dosage (LED). However, after adjusting for disease duration, the total LED was not correlated with any of the K-NMSS domains (Supplementary Fig. 1 and Table 3 in the online-only Data Supplement). Table 4 presents the association between K-NMSS and each clinical variable based on multiple regression analysis. The disease duration and a depressive mood on BDI significantly affected all of the K-NMSS domains. Specific variables were significantly correlated in each domain: LED with sleep/fatigue and sexual dysfunction; cognitive status on K-MMSE with cardiovascular symptoms; PDSS with attention/memory problems, perception problems/hallucination, and urinary dysfunction; anxiety on BAI with attention/memory problems and excessive sweating; and fatigue on PFS with attention/memory problems, weight change, and taste and olfactory dysfunctions.
Table 4

Association of each domain of non-motor symptoms scale with clinical variables by multiple regression analyses (disease duration, HYS, UPDRS 3, LED, MMSE, BDI, BAI, PAF)

NMSS domainVariablesβ±SEp value
CardiovascularDisease duration0.007±0.0040.083
BDI0.113±0.021<0.001
MMSE-0.114±0.0530.032
Sleep/fatigueDisease duration0.037±0.008<0.001
LED-0.006±0.0030.059
BDI0.420±0.040<0.001
Mood/cognitionDisease duration0.028±0.0120.019
BDI0.726±0.062<0.001
Perceptual problems/hallucinationsDisease duration0.012±0.0050.020
UPDRS 30.040±0.0200.049
BDI0.135±0.028<0.001
PFS-0.035±0.0110.001
PDSS-0.029±0.007<0.001
Attention/memoryDisease duration0.016±0.0060.008
BDI0.223±0.034<0.001
BAI0.105±0.0440.017
PFS-0.032±0.0160.050
PDSS-0.026±0.0090.003
GastrointestinalDisease duration0.011±0.0060.080
BDI0.187±0.031<0.001
PDSS-0.0140.080
UrinaryDisease duration0.023±0.0100.021
BDI0.231±0.049<0.001
PDSS-0.049±0.012<0.001
Sexual functionDisease duration0.033±0.008<0.001
LED-0.002±0.0010.003
BDI0.119±0.0340.001
MMSE0.165±0.0880.060
Miscellaneous_painDisease duration0.005±0.0030.084
BDI0.051±0.0160.001
Miscellaneous_taste or smellDisease duration0.015±0.003<0.001
BDI0.070±0.016<0.001
PFS-0.011±0.0060.096
Miscellaneous_weight changeDisease duration0.004±0.0020.057
BDI0.081±0.012<0.001
PFS-0.010±0.0050.039
Miscellaneous_excessive sweatingDisease duration0.009±0.0030.002
BDI0.038±0.0160.014
BAI0.060±0.016<0.001

BAI: Beck anxiety inventory, BDI: Beck depression inventory, MMSE: Mini Mental State Examination, NMSS: non-motor symptom scale, PDSS: Parkinson's disease sleep scale, PFS: Parkinson fatigue scale.

NMS scale and HrQoL

The total K-NMSS scores were significantly correlated with HrQoL as assessed using a PD-specific questionnaire (PDQ-39) (Fig. 2) (Supplementary Table 4 in the online-only Data Supplement). The sleep/fatigue and mood/cognition domains in K-NMSS were the most important factors affecting the HrQoL in PD subjects (rS=0.528 and rS=0.573, respectively). In the PD subgroup analysis, sleep/fatigue and mood/cognition were the primary factors in the de novo and early PD groups. Attention/memory and mood/cognition were the most important factors for HrQoL in the advanced PD group, while miscellaneous variables and the sleep/fatigue domain were less likely to be correlated with HrQoL status. Finally, the perception problems/hallucination domain negatively impacted HrQoL in advanced PD but not in de novo or early PD.
Fig. 2

Correlations between NMSS total score and PDQ39 SI (rS=0.329, p<0.001). NMSS: non-motor symptom scale, PDQ39: Parkinson's Disease Questionnaire-39, PDQ39 SI: PDQ39 summary index.

DISCUSSION

Our analysis of various aspects of the clinical presentation of NMS in PD has demonstrated that PD subjects show significant differences in the scores on mood, cognition, and sleep questionnaires compared with healthy controls. These findings suggest that PD is not simply a movement disorder, but instead is a systemic disorder that includes both motor symptoms and NMS, which would be due to the degeneration of nigrostriatal-extranigral systems.2425 Although the importance of NMS in PD has been recognized recently, these symptoms have remained underreported by patients and overlooked by clinicians.526 Because NMS greatly impact the quality of life and can be a great burden for patients and their families,6827 it is important to assess the complexity of NMS. The NMS of PD are heterogeneous and present with a variety of manifestations that can be classified in several ways, such as according to disease stage based on pathological progression,28 according to symptomatic similarities, or according to major causative neurotransmitters.293031 We identified tendencies of the NMS in the present study regardless of the specific underlying mechanism. The PD group showed both a higher prevalence and a higher score in all K-NMSS domains compared with the controls. Sleep/fatigue, mood/cognition, attention/memory, and urinary dysfunctions were the most commonly reported NMS in PD patients. However, these domains were not specific to the study groups, being also prevalent in the control group, which indicates that the prevalence rates of NMS need to be interpreted cautiously in clinical practice. Our analysis of a prevalence ratio revealed that the PD group exhibited a higher ratio for perception problems/hallucination, miscellaneous symptoms (weight change, taste/smell, and pain), and GI dysfunction compared with the other domains, indicating that these domains are more specific to PD. Accordingly, there were several prevalent NMS that were correlated with the participants' age, such as urinary and sleep symptoms, which were not specific to the PD patients. In our study, 98.1% of the PD patients showed at least one nonmotor symptom, and most commonly presented with sleep/fatigue issues, which is similar to the results of an Italian study.12 While urinary dysfunction was the fourth most common of the NMS in our study, several previous studies have found urinary dysfunction (nocturia or urgency) to be the most common NMS domain.5632 In our survey, the prevalence of urinary dysfunction (73.7%) was not lower than in previous studies (54.5–68.4%),83233 but the affective symptom scores in the baseline characteristics were high, although not compatible with a diagnosis of mood disorders, which can explain why sleep/fatigue and mood/cognition symptoms were more common than urinary dysfunction. This is similar to a previous study finding that more of the K-NMSS domains were affected as the disease progressed.12 It is also compatible with research findings that NMS are intrinsic to PD but are also correlated with the involved structures and related to drugs taken as the disease progresses.72434 We identified significant differences in the number and prevalence of involved NMS even in the de novo and early stages of PD compared with controls. Meanwhile, there were no statistically significant differences in K-NMSS domains in early PD stages and similar stages in the de novo PD group, which indicated that NMS in PD largely appear in later stages rather than being evenly distributed throughout the disease course.35 Previous investigations have found obvious differences in clinical manifestations, prognosis, and drug responsiveness according to the PD motor phenotype.3637 Although the pathophysiological basis is still unknown, disparity in the patterns of dopaminergic cell loss, differences in other neurotransmitter systems, deposition of amyloid plaque, and brain atrophy have been proposed as explanations for differences in PD subtypes.38394041 In the present study, the affected K-NMSS domains did not differ significantly according to the PD phenotype between groups, with the exception of GI dysfunction. This contrasts with Khoo et al.42 reporting that even in early PD, a larger number of NMS were involved in the PIGD group. Another recent study found no significant difference in a larger PIGD and TD group comparison.43 In our study, there was a tendency—although not statistically significant—for the prevalence and number of affected NMS domains to both be higher in the PIGD subtype. However, there was a significant difference in the numbers of PD phenotypes, in that 82.3% of the recruited patients were of the PIGD subtype. When the results were adjusted for age, nearly all of the K-NMSS domains were correlated with disease duration, total LED, and motor status as assessed by UPDRS part III scores. However, after adjusting for the disease duration, the total LED was not correlated with any NMS. These results indicate that disease duration is more important than the LED to NMS in PD. The presentation of NMS varies, and patients present at various stages. Several NMS such as olfaction problems, RBD, constipation, and depression have been suggested to be preclinical features of neurodegenerative diseases.81011 In addition to these intrinsic features, additional NMS can develop as the disease progresses, and these can significantly affect the patient's condition.372444 It is therefore possible that the disease duration contributes to the prevalence and severity of NMS.454647 The NMS of PD can also be influenced by accompanying problems. Some NMS of PD are known to result from dopaminergic deficits, while other NMS do not respond to dopaminergic treatment.48 Duration and depressive mood consistently affected all K-NMSS domains, and each K-NMSS domain was influenced by specific clinical variables in the present study, as indicated in Table 4. Clinicians are primarily focused on motor symptoms, which may result in them overlooking NMS or HrQoL.49 However, NMS are a major determining factor of HrQoL in PD.133250 Gallagher et al.6 insisted that NMS can have a greater effect than motor features on some aspects of HrQoL in PD. Mood/cognition and sleep/fatigue were the main factors associated with HrQoL in all of the PD subjects in the present survey. These results are similar to other studies finding that depression is a major detrimental factor for HrQoL in PD.1451 The subgroup analysis indicated that the mood/cognition domain is a common factor that can determine HrQoL for the overall PD group, but that sleep/fatigue contribute to de novo and early PD only, while the perception problems/hallucination and attention/memory domains are specific for advanced PD. These observations suggest that the presentation of NMS differs according to disease stage, and that NMS attributed to HrQoL status are also influenced by disease stage. This result is comparable to a previous report of HrQoL associated with NMS varying according to the disease duration, and mood, sleep, fatigue, and autonomic symptoms negatively affecting NMS with regard to HrQoL in PD.6 The burden experienced by PD patients is correlated with the number of NMS.27 Some NMS, such as depression, constipation, and urinary and sleep dysfunctions, can be improved by the active treatment of parkinsonian features.8 Accordingly, HrQoL can also improve during NMS treatment.42652 For these reasons, increasing the recognition of nonmotor aspects of PD is warranted for improving the HrQoL of affected subjects, and tailored treatment strategies for diverse stages of PD should consider NMS. There were some limitations to this study. First, we did not analyze the presence of motor complications in the advanced PD group. Since motor complications in PD are significantly associated with NMS,53 it is important to assess the effects of drug-related motor complications. However, we analyzed the correlations between the LED and K-NMSS domains in order to elucidate the effects of this drug on NMS in PD. Second, most of the enrolled PD subjects were the PIGD type, which does not adequately represent the whole PD population; however, the PD phenotype analysis formed only a small part of our study, and the results are applicable to a large PD population. This was a multicenter, nationwide, representative study of Korean patients with a case-control comparison design. The diagnostic accuracy of the study was increased by reconfirming the clinical diagnoses at 6 months after the initial diagnoses. Another strong point is that our nationwide Korean survey is one of the first large cross-sectional studies to elucidate the overall features and influences of nonmotor aspects of PD. The results from this study have highlighted the impact of NMS, which could allow the earlier detection of this degenerative disease, and thereby facilitate better therapeutic plans and improve the HrQoL of PD patients.
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Review 1.  The Movement Disorder Society Evidence-Based Medicine Review Update: Treatments for the motor symptoms of Parkinson's disease.

Authors:  Susan H Fox; Regina Katzenschlager; Shen-Yang Lim; Bernard Ravina; Klaus Seppi; Miguel Coelho; Werner Poewe; Olivier Rascol; Christopher G Goetz; Cristina Sampaio
Journal:  Mov Disord       Date:  2011-10       Impact factor: 10.338

Review 2.  Identifying prodromal Parkinson's disease: pre-motor disorders in Parkinson's disease.

Authors:  Ronald B Postuma; Dag Aarsland; Paolo Barone; David J Burn; Christopher H Hawkes; Wolfgang Oertel; Tjalf Ziemssen
Journal:  Mov Disord       Date:  2012-04-15       Impact factor: 10.338

3.  The nondeclaration of nonmotor symptoms of Parkinson's disease to health care professionals: an international study using the nonmotor symptoms questionnaire.

Authors:  K Ray Chaudhuri; Cristina Prieto-Jurcynska; Yogini Naidu; Tanya Mitra; Belen Frades-Payo; Susanne Tluk; Anne Ruessmann; Per Odin; Graeme Macphee; Fabrizio Stocchi; William Ondo; Kapil Sethi; Anthony H V Schapira; Juan Carlos Martinez Castrillo; Pablo Martinez-Martin
Journal:  Mov Disord       Date:  2010-04-30       Impact factor: 10.338

4.  Association of rural life setting and poorer quality of life in Parkinson's disease patients: a cross-sectional study in Croatia.

Authors:  N Klepac; S Pikija; T Kraljić; M Relja; V Trkulja; S Juren; I Pavlicek; T Babić
Journal:  Eur J Neurol       Date:  2007-02       Impact factor: 6.089

5.  The impact of non-motor symptoms on health-related quality of life of patients with Parkinson's disease.

Authors:  Pablo Martinez-Martin; Carmen Rodriguez-Blazquez; Monica M Kurtis; K Ray Chaudhuri
Journal:  Mov Disord       Date:  2011-01-24       Impact factor: 10.338

6.  Parkinsonism: onset, progression and mortality.

Authors:  M M Hoehn; M D Yahr
Journal:  Neurology       Date:  1967-05       Impact factor: 9.910

7.  The burden of non-motor symptoms in Parkinson's disease using a self-completed non-motor questionnaire: a simple grading system.

Authors:  K Ray Chaudhuri; A Sauerbier; J M Rojo; K Sethi; A H V Schapira; R G Brown; A Antonini; F Stocchi; P Odin; K Bhattacharya; Y Tsuboi; K Abe; A Rizos; Carmen Rodriguez-Blazquez; P Martinez-Martin
Journal:  Parkinsonism Relat Disord       Date:  2015-01-05       Impact factor: 4.891

8.  Nonmotor symptoms as presenting complaints in Parkinson's disease: a clinicopathological study.

Authors:  Sean S O'Sullivan; David R Williams; David A Gallagher; Luke A Massey; Laura Silveira-Moriyama; Andrew J Lees
Journal:  Mov Disord       Date:  2008-01       Impact factor: 10.338

9.  Course in Parkinson disease subtypes: A 39-year clinicopathologic study.

Authors:  A H Rajput; A Voll; M L Rajput; C A Robinson; A Rajput
Journal:  Neurology       Date:  2009-07-21       Impact factor: 9.910

10.  Relationship between Motor Symptoms, Cognition, and Demographic Characteristics in Treated Mild/Moderate Parkinson's Disease.

Authors:  Jay S Schneider; Stephanie Sendek; Chengwu Yang
Journal:  PLoS One       Date:  2015-04-23       Impact factor: 3.240

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  4 in total

1.  Pain in atypical parkinsonism, vascular parkinsonism, and Parkinson's disease.

Authors:  Young Hee Sung; Suk Yun Kang
Journal:  Neurol Sci       Date:  2022-03-26       Impact factor: 3.830

2.  Validation of the Korean Version of the Scale for Outcomes in Parkinson's Disease-Autonomic.

Authors:  Ji-Young Kim; In-Uk Song; Seong-Beom Koh; Tae-Beom Ahn; Sang Jin Kim; Sang-Myung Cheon; Jin Whan Cho; Yun Joong Kim; Hyeo-Il Ma; Mee-Young Park; Jong Sam Baik; Phil Hyu Lee; Sun Ju Chung; Jong-Min Kim; Han-Joon Kim; Young-Hee Sung; Do Young Kwon; Jae-Hyeok Lee; Jee-Young Lee; Ji Sun Kim; Ji Young Yun; Hee Jin Kim; Jin Young Hong; Mi-Jung Kim; Jinyoung Youn; Ji Seon Kim; Eung Seok Oh; Hui-Jun Yang; Won Tae Yoon; Sooyeoun You; Kyum-Yil Kwon; Hyung-Eun Park; Su-Yun Lee; Younsoo Kim; Hee-Tae Kim; Joong-Seok Kim
Journal:  J Mov Disord       Date:  2017-01-18

3.  Non-Motor Symptom Burdens Are Not Associated with Iron Accumulation in Early Parkinson's Disease: a Quantitative Susceptibility Mapping Study.

Authors:  Chaewon Shin; Seon Lee; Jee Young Lee; Jung Hyo Rhim; Sun Won Park
Journal:  J Korean Med Sci       Date:  2018-03-26       Impact factor: 2.153

4.  Prediction of age at onset in Parkinson's disease using objective specific neuroimaging genetics based on a sparse canonical correlation analysis.

Authors:  Ji Hye Won; Mansu Kim; Jinyoung Youn; Hyunjin Park
Journal:  Sci Rep       Date:  2020-07-15       Impact factor: 4.379

  4 in total

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