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February 26, 2013; 80 (9) Article

Nonmotor fluctuations in Parkinson disease

Severity and correlation with motor complications

Alexander Storch, Christine B. Schneider, Martin Wolz, Yannic Stürwald, Angelika Nebe, Per Odin, Andreas Mahler, Gerd Fuchs, Wolfgang H. Jost, K. Ray Chaudhuri, Rainer Koch, Heinz Reichmann, Georg Ebersbach
First published January 30, 2013, DOI: https://doi.org/10.1212/WNL.0b013e318285c0ed
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Abstract

Objective: To evaluate frequency, severity, and correlation of nonmotor symptoms (NMS) with motor complications in fluctuating Parkinson disease (PD).

Methods: The Multicenter NonMotor Fluctuations in PD cross-sectional study used clinical examination of 10 NMS (dysphagia, anxiety, depression, fatigue, excessive sweating, inner restlessness, pain, concentration/attention, dizziness, bladder urgency) quantified using a visual analogue scale (VAS) in motor-defined on (NMSOn) and off state (NMSOff) combined with motor assessments and self-ratings at home in 100 patients with advanced PD.

Results: All NMS except dysphagia, excessive sweating, and bladder urgency fluctuated in conjunction to motor fluctuations with more frequent and severe symptoms in off compared to on state. The proportions of patients experiencing autonomic/sensory NMS in both motor states were similar to those with these NMS exclusively in off state (ratios 0.4–1.3), while for mental/psychic NMS the proportions with exclusive manifestation in off state were higher (ratios 1.8–3.1). Demographic and clinical characteristics correlated neither with NMS frequency patterns and severities nor with ΔNMSOn/Off severities (defined as the differences of VAS scores between on and off). Severities of NMSon, NMSOff, and ΔNMSOn/Off did not correlate with motor function. Presence of anxiety, depression, fatigue, and pain had negative impact on health-related quality of life (HRQOL) measured by Parkinson's Disease Questionnaire–8 scoring independent of their occurrence with respect to motor state. Fluctuations of these NMS but not of fatigue deteriorated HRQOL.

Conclusion: Patterns of NMS fluctuations are heterogeneous and complex, but psychic NMS fluctuate more frequently and severely. Demographic parameters and motor function do not correlate with NMS or nonmotor fluctuation severities in fluctuating PD.

GLOSSARY

BDI=
Beck Depression Inventory;
CAPIT-PD=
Core Assessment Program for Intracerebral Transplantations in PD;
HRQOL=
health-related quality of life;
MMSE=
Mini-Mental State Examination;
NMF=
nonmotor fluctuations;
NMS=
nonmotor symptoms;
NoMoFlu-PD=
NonMotor Fluctuations in PD;
PD=
Parkinson disease;
PDQ-8=
Parkinson's Disease Questionnaire–8;
STN-DBS=
subthalamic nucleus deep brain stimulation;
UPDRS=
Unified Parkinson’s Disease Rating Scale;
VAS=
visual analogue scale;
WOQ-9=
9-item Wearing-off Questionnaire

Nonmotor symptoms (NMS) including neuropsychiatric, sleep, autonomic, and sensory domains afflict up to 88% of patients with Parkinson disease (PD).1 NMS overall burden has been shown to be the key determinant of health-related quality of life (HRQOL)2 and has a greater effect on HRQOL compared to the burden of motor symptoms.3 In contrast to motor fluctuations, nonmotor fluctuations (NMF) related to on/off phenomena are poorly researched. Motor signs are present in most cases of response fluctuations but are frequently accompanied by vegetative, sensory, and psychiatric symptoms.4,–,8 NMF have been described to be present in up to 100% of patients with motor fluctuations7 and can be more troublesome and disabling than motor disturbances.7,9,10

Differentiation between NMF related to motor oscillations and NMS which are not influenced by on/off fluctuations bears important therapeutic implications since adjustments of dopaminergic medication might be helpful in the former whereas specific symptomatic treatment might be first choice in the latter conditions. The NonMotor Fluctuations in PD (NoMoFlu-PD) study was designed to assess the relationship between a broad range of NMS including the major correlates of poor HRQOL and response fluctuations in a large cohort of patients with advanced PD.

METHODS

Subjects.

Subjects across all ages and disease severities fulfilling UK PD Brain Bank criteria11 with documented motor fluctuations were enrolled at 5 Movement Disorder centers between July 2010 and February 2011. Motor complications included end-of-dose akinesia, “on-off” phenomenon, peak-of-dose and diphasic dyskinesia, and dystonia. Patients were excluded if they had an identifiable cause of parkinsonism or signs of atypical parkinsonian disorders, psychosis, or dementia (Mini-Mental State Examination [MMSE] ≤ 23 points) or other relevant conditions interfering with the study protocol.

Standard protocol approvals, registrations, and patient consents.

All patients provided written informed consent and the study was approved by institutional review boards at participating sites.

Assessments.

We assessed basic demographic data including type of motor complication, modified Hoehn & Yahr score,12 MMSE,13 Unified Parkinson’s Disease Rating Scale (UPDRS),14 NMS Questionnaire,15 the 9-item Wearing-off Questionnaire (WOQ-9),16 Beck Depression Inventory (BDI-1A),17 and Parkinson's Disease Questionnaire–8 (PDQ-8).18 To investigate motor and nonmotor fluctuations, we assessed UPDRS motor score (UPDRS III)14 and NMS in “defined-off” state (NMSOff) after the patient being off any antiparkinsonian medication and no subthalamic nucleus deep brain stimulation (STN-DBS) for 12 hours (usually, but not restricted to the morning), and “best-on” state (NMSOn) representing the condition in which the patient and the investigator agree that the functional benefits are the most beneficial (not restricted to a pharmacologic test condition or first medication intake). Motor states were defined as proposed by the Core Assessment Program for Intracerebral Transplantations in PD (CAPIT-PD) committee.19 Differences of NMS between on and off states were defined as ΔNMSOn/Off. Since there are no standard scales for assessments of NMS states within an actual on or off state, we used a standardized clinical examination by experienced movement disorder physicians using a semi-structured interview combined with a visual analogue scale (VAS) displayed to the patients during the examination ranging from 0% (no symptoms) to 100% (most severe symptom possible). All investigators were movement disorder specialists trained in the use of the interview/VAS and UPDRS rating by members of the NoMoFlu-PD steering committee. The NoMoFlu-PD steering committee selected 10 key NMS3 plus one reverted question (in the following order; see table e-1 on the Neurology® Web site at www.neurology.org for standard questions): dysphagia/choking (including challenge test by drinking 200 mL of water similar to the test described in references 20 and 21), anxiety/panic, depressive symptoms, fatigue, excessive sweating, happiness, inner restlessness, pain, concentration/attention, dizziness, and bladder urgency approximately 15–20 minutes after drinking the water. We included the question on happiness only for reverted wording during the examination process to reduce response biases.22 Interitem correlations ranged from −0.26 to 0.48 for on and −0.44 to 0.57 for off state showing no indications for redundancy.

We extended our study by asking the patients to answer the above mentioned questions using the VAS during 5 on and 5 off states without any help at home. For comparison with motor symptoms severity, motor symptoms were rated by the patients using the same VAS.

Statistical analyses.

Statistical comparisons of data between motor states and frequency pattern analysis were calculated using χ2, Fisher exact test, Wilcoxon rank order test, Mann-Whitney U test, paired or unpaired t test, or one-way analysis of variance as appropriate. Pearson correlations were used to examine correlations with r>|0.5| considered a relevant correlation. Data were analyzed using the software programs SPSS 18.0 (SPSS Inc., Chicago, IL) and SAS 9.2 (SAS Institute, Cary, NC). If not mentioned otherwise, all data are displayed as mean ± SD or number (%); significance level was set at p < 0.05 (2-tailed test). Pairwise deletion was applied to missing data. Due to the explorative character of the study and the high number of statistical tests, an α adjusting of p values has not been carried out (unless mentioned otherwise).

RESULTS

Study population.

Demographic and clinical characteristics of the study population are displayed in table 1 (for concomitant diseases/medication, see table e-2). All patients displayed at least 2 types of motor complications; median number of motor complications was 4 (10th/90th percentile: 2/6). Table e-3 summarizes the various types of motor complications. According to WOQ-9 results,16 all patients experienced wearing-off with at least 2 symptoms with improvement after the next dose of antiparkinsonian medication (median: 4 fluctuating symptoms; 10th/90th percentile: 3/6; table e-4). All patients declared that they had at least 2 NMS when explored using the NMS Questionnaire with a median number of 12 symptoms (10th/90th percentile: 5/17; table e-5).

View this table:
Table 1

Demographic and clinical dataa

Frequency patterns of NMS fluctuations.

Frequency patterns of the 4 possible distributions of NMS occurrence with respect to motor states (on−/off−, NMS not present; on+/off−, NMS present only in motor on; on−/off+, NMS present only in motor off; on+/off+, NMS present in motor on and off) are displayed in figure 1. The most frequent NMS was fatigue, with 88% of patients reporting this symptom, followed by problems with concentration/attention (67%), while dysphagia was least frequent (29%). Interestingly, the percentage sizes of on−/off+ populations were similar to those of on+/off+ populations for most NMS (ratios of on−/off+ divided by on+/off+: 0.4–1.3) with fatigue (ratio: 2.2) and psychiatric symptoms (ratios 1.8–3.1) as the major exceptions (figure 1A). There were small numbers of patients in the on+/off− population for all NMS (3%–10%; figure 1A). We detected a high concordance between VAS and WOQ-9 results for the 4 NMS investigated by both techniques (68%–89% of accordant results for symptom frequency and 76%–85% for symptom fluctuation, p < 0.01 [Fisher exact tests with Bonferroni adjustment]).

Figure 1
Figure 1 Frequencies of nonmotor symptoms with respect to motor states

(A) Patterns of frequencies of nonmotor symptoms (NMS) with respect to motor states. Displayed are the frequencies of all investigated NMS (in percent) for each of the 4 possible NMS distributions with respect to the motor states (NMS not present; NMS present only in motor on; NMS present only in motor off; NMS present in motor on and in off). Italic numbers are p values from Fisher exact test with Bonferroni adjustment comparing the whole NMS patterns (all p values <0.05 are displayed). (B) Distribution of NMS in on and off state evaluated by structured clinical examination. The p values from McNemar tests comparing on with off frequency are displayed. (C) Distribution of NMS in on and off state from self-ratings at home (mean frequencies from maximal 5 self-ratings per motor state). The p values from Wilcoxon rank tests comparing on and off mean frequency are displayed. The p values are unadjusted concerning α inflation.

Comparing the frequencies of NMSOn and NMSOff, all NMS except dysphagia, excessive sweating, and bladder urgency were more frequent in off compared to on state, with the largest increase of anxiety (+230%) followed by fatigue (+186%; figure 1B). There were no differences of NMS frequencies between patients with and without STN-DBS.

Severities of NMS fluctuations.

Comparing the severities of NMSOn and NMSOff, all NMS except excessive sweating were more severe in off compared to on state (table 2). Analyses of ΔNMSOn/Off severities revealed a mixed distribution of data for all NMS with a high percentage of patients reporting no relevant changes (<10% on VAS) and 18%–76% of patients documenting more severe symptoms in off compared to on state (table 3). There was a small number of patients (3%–14%) showing more severe NMS in on compared to off state (table 3). There were no differences of NMS severities between patients with and without STN-DBS.

View this table:
Table 2

Severity of nonmotor symptoms (NMS) in on and off statea

View this table:
Table 3

Changes in severity of nonmotor symptoms (NMS) between on and off state (ΔNMSOn/Off)a

We found no correlations of severities of NMSOn, NMSOff, or ΔNMSOn/Off with age, sex, disease duration, fluctuation duration, UPDRS-IIIOn, UPDRS-IIIOff, ΔUPDRS-IIIOn/Off, UPDRS 32 and 33 sumscore (dyskinesias), or PDQ-8 summary index. BDI and PDQ-8 item 3 (depression) scores correlated with depression in off state r = 0.530 (p < 0.0001) and r = 0.575 (p < 0.0001), but not with other NMS in both motor states. There were no correlations of NMSOn, NMSOff, or ΔNMSOn/Off severities with treatments (levodopa, dopamine agonists, amantadine, or DBS), except for the difference in anxiety between on and off (correlating with DBS), depression in off (DBS), as well as bladder urgency in on (levodopa therapy, DBS), off (dopamine agonists therapy), and difference on/off (levodopa therapy; p < 0.05 for all comparisons; Mann-Whitney U test). In all cases, symptom severity was higher in patients untreated with the respective therapy.

NMS fluctuations and QOL.

Presence of anxiety, depression, fatigue, and pain (independent of whether the NMS is present in on or off state) was associated with worse HRQOL as measured by PDQ-8 summary score (figure 2A). Presence of anxiety, depression, and pain was associated with the worst HRQOL scores (figure 2A). Analyses of HRQOL with respect to NMS frequency patterns revealed differences of PDQ-8 scores between NMS states for anxiety, depression, fatigue, and pain (figure e-1). In general, HRQOL is worst in patients with NMS occurrence in both motor states, with fatigue as the major exception: HRQOL is worse in patients experiencing fatigue only in on state compared to patients with fatigue in both motor states.

Figure 2
Figure 2 Nonmotor fluctuations and health-related quality of life

(A) Median and interquartile range of the Parkinson's Disease Questionnaire–8 (PDQ-8) summary index scores with respect to nonmotor symptoms (NMS) occurrence independent of motor state. Italic numbers above the bars represent p values from Mann-Whitney U tests comparing patients with the respective NMS with those without the NMS. (B) Median and interquartile range of the PDQ-8 summary index scores for NMS nonfluctuators (difference of visual analogue scale [VAS] between on and off state ≤10%) compared to fluctuators (difference of VAS between on and off state >10%) with respect to the 10 NMS. Numbers within bars are number of patients in the group, italic numbers above the bars represent p values from Mann-Whitney U tests comparing nonfluctuators with fluctuators. There were no differences between the 2 NMS/nonmotor fluctuations groups for all NMS with respect to Unified Parkinson’s Disease Rating Scale (UPDRS)–III in on or off state, ΔUPDRS-III, age, sex, and disease duration (unpaired t test). The p values are unadjusted concerning α inflation.

PDQ-8 summary index was higher in patients with fluctuations of dysphagia, anxiety, depression, and pain (ΔNMSOn/Off >10%) compared to patients with no fluctuations of these NMS (figure 2B). The greatest difference in PDQ-8 index was recorded in patients with fluctuating depression followed by pain and dysphagia. We found no correlations of severities of NMSOn, NMSOff, or ΔNMSOn/Off with PDQ-8 scores.

NMS self-evaluation at home (diaries).

The patients rated their motor and nonmotor symptoms using the VAS at a maximum of 5 on and 5 off states at home (table 2). NMS ratings were very similar to those generated during clinical examination with respect to frequencies and severities with no differences on the cohort level except for dysphagia (figure 1, B and C; table 2). On the individual patient level, there was a wide statistical spread of correlations between the 5 ratings at home for all NMS (Pearson coefficients 0.016–0.948). Correlation coefficients of self-ratings with clinical examination ratings ranged mainly within the test-retest variations of self-evaluations (table e-6), showing that differences between clinical and self-rating are within the regular variation range of NMS severities.

DISCUSSION

Although occurrence of NMS in motor off state has been described previously,4,–,8 there are few studies in small cohorts in which severity of fluctuations of mood,23 anxiety,24 and pain25 was quantitatively assessed. We report systematic assessment of frequencies and severities of autonomic dysfunction, pain, and fatigue as major determinants of poor HRQOL3 in relation to motor fluctuations in a large PD cohort. One major difference from most previous studies is that we used a systematic interview including challenge tests for dysphagia and bladder function to estimate the active NMS state within the present motor state in combination with self-ratings at home.

NMS are recognized to be integral to PD and validated scales have been introduced to assess presence and severity of various manifestations.26,27 In contrast, there are few validated instruments to measure frequency changes of NMS in association with drug response fluctuations such as the WOQ-98,24 and no standard scale for assessment of the active NMS state within an effective on or off state is available (the NMS Scale determines NMS severity × frequency over the last month28). We thus assessed severity of a broad range of NMS by a structured interview combined with a VAS. Such scales were already used in other studies to assess single aspects of NMS fluctuations23,25 and can supplement standard examination of motor changes in on/off conditions.29 Since one major aim of the present study was to correlate NMF severity with motor function, quantitative examination of the active NMS severity state was essential. One limitation of VAS for evaluating NMS, however, is that some subjects might not have sufficient normative experience to be able to rate NMS on VAS.

All NMS except autonomic dysfunctions fluctuated with motor oscillations and were more frequent in off compared to on state. The proportion of patients with exclusive appearance or worsening of NMS during off state was strongly determined by the type of NMS: the number of patients experiencing an NMS related to autonomic or sensory function only in off state was similar to the number of patients manifesting these NMS in both motor states, while for NMS pertaining to mental and psychic domains the proportion of patients with exclusive manifestation in off state was considerably higher. Exclusive occurrence of NMS or worsening during on state was infrequent. Fluctuation severity of any NMS (ΔNMSOn/Off) did not correlate to the amplitude of motor changes (ΔUPDRS-IIIOn/Off).

Anxiety and depression frequently manifest in relationship to motor fluctuations7,8 and acute effects of dopamine replacement therapy on mood and anxiety have been reported.23,24,30 Although fluctuations of anxiety and mood are frequently combined, they can also occur independently and also in absence of motor fluctuations.31 In this study, the propensity to experience worsening of mood in the off state was higher in patients with higher BDI scores but in about two-thirds of patients, anxiety and depressive mood was exclusively confined to off state. This was also recently reported in the PROMS-PD study, where anxious and depressive symptoms were highly associated with on-off states as well as sudden off periods.32 BDI scores only correlated with depression severity in off but not in on state, suggesting that depression scoring in fluctuating patients mainly reflects the mood in off. Differentiation of mood fluctuations related to on/off oscillations from clinical depression should therefore be performed in routine clinical assessments.

Many fluctuating patients report that fatigue is the most bothersome symptom associated with off state and slowness in thinking and tiredness are highly associated with wearing-off.8 Fatigue has emerged as a key NMS of PD and its prevalence reached almost 50% even in patients with early PD.33 Remarkably, fatigue followed by problems with concentration/attention was the most frequent NMS in our study. Both NMS were not related to depression scores and occurred only during off states in most patients. Pain was confined to off states or increased during off in most patients with painful conditions. Causes of pain were not systematically assessed but presumably some cases with exclusive manifestation of pain in off had central pain related to hypodopaminergic transmission whereas worsening of preexisting pain during off states can occur in a variety of pain syndromes.34 Pain fluctuations translated into poor HRQOL.

Autonomic NMS were not fluctuating in frequency and only mildly in severity. Although dysphagia is generally included into the NMS complex,35,36 this symptom mainly relies on motor function of pharyngeal voluntary muscles. The absence of any fluctuations of this NMS is even more unexpected. Separate analysis of patients with and without STN-DBS revealed similar results in both groups. The differences between clinical dysphagia ratings and self-evaluations at home are most likely due to the swallowing test in the outpatient clinic, which was not recommended at home to avoid aspiration. Bladder urgency was one of the most frequent NMS in previous studies with a large increase in off state.26,27 We assessed bladder urgency not by history but by interview and challenge test. Urgency thus occurred exclusively during off state only in some patients but was present in both motor states in the same proportion of patients. The differences between clinical ratings and self-evaluations at home could be due to regular passing urine just before visiting the outpatient clinic to avoid urgency during the consultation, which might not be regularly done before the ratings at home.

Our study has several limitations. First, motor off state was defined as the condition after 12-hour medication/DBS withdrawal as proposed by the CAPIT-PD consortium.19,37 This withdrawal period might be insufficient in patients on long-acting dopamine agonist treatment, particularly in patients without chronic levodopa therapy (17%). The results might thus underestimate the severity of NMS in spontaneous “worst-off” conditions. The on/off states definition using motor symptoms as the defining criteria also implies that NMF occurring without coincident changes of motor symptoms could not be detected. Second, we enrolled a rather heterogeneous population with various types of motor fluctuators and STN-DBS patients potentially confounding our results. However, statistical analyses of the subcohorts with and without STN-DBS did not reveal differences with respect to NMF frequencies and severities. In our previous study on immediate effects of STN-DBS on NMS using a similar approach, we observed similar effects of STN-DBS on NMS severities compared to the present results.38 Third, patients were seen in specialist movement disorders settings and patients with dementia were not included in this study, and as such the results may not be representative of patients in other clinical settings or with severe cognitive disturbances. Another limitation is the selection of the NMS due to time constraints in examining patients during off state. We chose NMS with major impact on HRQOL,3 which are likely fluctuating during the day (meaning that we excluded, for example, sleep disturbances and constipation). This limitation together with the heterogeneity of NMF patterns restricts the interpretation of the results to the 10 investigated NMS.

Our study systematically explored the impact of a wide spectrum of NMF on HRQOL in PD. Similar to the results of the PRIAMO study33 and other reports,3 neuropsychiatric NMS, such as anxiety, depression, and fatigue, as well as pain, had negative impacts on HRQOL independent of their occurrence with respect to the motor state. Interestingly, fluctuations of all these NMS but not of fatigue deteriorated HRQOL. Thus, only the presence but not fluctuations of fatigue as a frequent and highly fluctuating NMS seem to worsen HRQOL. These discrepancies might be related to differential translation of NMS occurrence into HRQOL impairment between both motor states. In addition, NMS with high frequencies in off state and thus fluctuations might be experienced not only as negative, but also as a positive event, providing some relief from these NMS in on state. This mixture of experiencing NMF together with a potential insensitivity of the PDQ-8 in determining HRQOL change in fluctuating PD might also explain the relatively mild effects of NMF on HRQOL. Although we tested NMF in the artificial environment of specialized movement disorder outpatient clinics and thus the results are not necessarily transferable to the patient's daily life, the strong correlation of the clinical assessment with the self-evaluations at home strongly suggests a high relevance of the data for normal daily life.

AUTHOR CONTRIBUTIONS

Dr. Storch was responsible for study concept and design, acquisition of data, statistical analyses and interpretation of data, chairing the NoMoFlu-PD steering committee, and drafting the manuscript. Dr. Ebersbach was responsible for study concept and design, acquisition of data, interpretation of data, and drafting the manuscript. He was member of the NoMoFlu-PD steering committee. Dr. Schneider, Dr. Odin, Dr. Fuchs, and Dr. Jost were responsible for the study concept and design, acquisition of data, interpretation of data, and important critical revision of manuscript. They were members of the NoMoFlu-PD steering committee. Dr. Schneider was responsible for the study concept and design, acquisition of data, interpretation of data, and important critical revision of manuscript. Dr. Wolz, Y. Schürwald, Dr. Nebe, Dr. Mahler, and Dr. Reichmann were responsible for acquisition of data and important critical revision of the manuscript. Dr. Koch was responsible for statistical analysis and important critical revision of the manuscript. Dr. Chaudhuri was responsible for interpretation of the data and important critical revision of the manuscript. He was a member of the NoMoFlu-PD steering committee. Drs. Storch, Schneider, and Koch had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

STUDY FUNDING

Supported in part by an unrestricted research grant from Boehringer Ingelheim Pharma GmbH & Co. KG, Ingelheim, Germany. The financial sponsors of the study had no role in the study design, data collection, data analysis, data interpretation, or writing of the report. The corresponding author had the final responsibility for the decision to submit for publication.

DISCLOSURE

A. Storch has received unrestricted research grants from Boehringer Ingelheim, Teva, and UCB; honoraria for presentations or advisory boards from Cephalon, Lundbeck, Teva, UCB, Meda, Abbott, GlaxoSmithKline, Orion, Bayer HealthCare, Medtronic, and Archimedes; and consultancy fees from Boehringer Ingelheim and Merz. C. Schneider reports no disclosures. M. Wolz has received honoraria for presentations from GlaxoSmithKline, Valeant, Pfizer, TEVA, Medtronic, and UCB Pharma. Y. Stürwald and A. Nebe report no disclosures. P. Odin has received honoraria for presentations and advisory boards from Boehringer, GlaxoSmithKline, Cephalon, Orion, Novartis, Solvay, Abbott, UCB, and Pfizer. A. Mahler has received honoraria for presentations/advisory boards from Boehringer, GSK, IMPAX, Janssen Cilag, Lilly, Lundbeck, Shire, Novartis, and Otsuka. G. Fuchs has received honoraria for presentations and advisory boards meetings from Boehringer Ingelheim, Desitin, Eisai, GlaxoSmithKline, Hoffmann LaRoche, Merz, Orion, Novartis, Pfizer, UCB-Pharma, and Valeant. W. Jost has received honoraria from Abbott, Boehringer, Desitin, GlaxoSmithKline, MEDA, Orion, and TEVA (for presentations or advisory boards). R. Chaudhuri has received honoraria for academic lectures at sponsored symposiums from UCB, Britannia, GSK, Abbott, Teva, Medtronic, and Boehringer-Ingelheim, and educational grants for research from UCB, Abbott, Boehringer-Ingelheim, and Britannia. R. Koch reports nothing to disclose. H. Reichmann was acting on advisory boards and gave lectures and received research grants from Cephalon, Pfizer, GSK, Boehringer/Ingelheim, Bayer Health Care, UCB Schwarz Pharma, TEVA/Lundbeck, Orion, Novartis, Hofmann LaRoche, Desitin, Valeant, and Cephalon. G. Ebersbach has received honoraria from Axxonis (consultancy), Boehringer Ingelheim, Desitin, GlaxoSmithKline, Valeant, Orion, UCB, and Novartis (all for presentations and advisory boards). Go to Neurology.org for full disclosures.

ACKNOWLEDGMENT

The authors thank the following NoMoFlu-PD Study Group collaborators as contributors: Lisa Klingelhöfer, MD, Mareike Fauser, Carolin Melzer (Division of Neurodegenerative Diseases, Department of Neurology, Dresden University of Technology, Dresden, Germany, obtaining informed consent, collection of clinical data); Simone Schmidt, Annett Wolz (Division of Neurodegenerative Diseases, Department of Neurology, Dresden University of Technology, Dresden, Germany, study coordination); Cecile Bosredon (Division of Neurodegenerative Diseases, Department of Neurology, Dresden University of Technology, Dresden, Germany, and German Centre for Neurodegenerative Diseases [DZNE], Dresden, study coordination); Arne Gies (Department of Neurology, Klinikum Bremerhaven, Bremerhaven, Germany, obtaining informed consent, collection of clinical data).

Footnotes

  • Go to Neurology.org for full disclosures. Funding information and disclosures deemed relevant by the authors, if any, are provided at the end of the article.

  • Editorial, page 784

  • Supplemental data at www.neurology.org

  • Received April 3, 2012.
  • Accepted October 24, 2012.

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