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Original Contribution |

Impulse Control Disorders in Parkinson Disease:  A Cross-Sectional Study of 3090 Patients FREE

Daniel Weintraub, MD; Juergen Koester, PhD; Marc N. Potenza, MD, PhD; Andrew D. Siderowf, MD, MSCE; Mark Stacy, MD; Valerie Voon, MD; Jacqueline Whetteckey, MD; Glen R. Wunderlich, PhD; Anthony E. Lang, MD, FRCPC
[+] Author Affiliations

Author Affiliations: University of Pennsylvania School of Medicine, Philadelphia (Drs Weintraub and Siderowf); Philadelphia Veterans Affairs Medical Center, Philadelphia (Dr Weintraub); Boehringer Ingelheim Pharma GmbH & Co KG, Ingelheim, Germany (Dr Koester); Yale University School of Medicine, New Haven, Connecticut (Dr Potenza); Duke University Medical Center, Durham, North Carolina (Dr Stacy); University of Toronto, Toronto, Ontario, Canada (Drs Voon and Lang); Boehringer Ingelheim Pharmaceuticals Inc, Ridgefield, Connecticut (Dr Whetteckey); and Boehringer Ingelheim (Canada) Ltd, Burlington, Ontario (Dr Wunderlich). Dr Voon is now with the University of Cambridge, Cambridge, England.


Arch Neurol. 2010;67(5):589-595. doi:10.1001/archneurol.2010.65.
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Context  An association between dopamine-replacement therapies and impulse control disorders (ICDs) in Parkinson disease (PD) has been suggested in preliminary studies.

Objectives  To ascertain point prevalence estimates of 4 ICDs in PD and examine their associations with dopamine-replacement therapies and other clinical characteristics.

Design  Cross-sectional study using an a priori established sampling procedure for subject recruitment and raters blinded to PD medication status.

Patients  Three thousand ninety patients with treated idiopathic PD receiving routine clinical care at 46 movement disorder centers in the United States and Canada.

Main Outcome Measures  The Massachusetts Gambling Screen score for current problem/pathological gambling, the Minnesota Impulsive Disorders Interview score for compulsive sexual behavior and buying, and Diagnostic and Statistical Manual of Mental Disorders research criteria for binge-eating disorder.

Results  An ICD was identified in 13.6% of patients (gambling in 5.0%, compulsive sexual behavior in 3.5%, compulsive buying in 5.7%, and binge-eating disorder in 4.3%), and 3.9% had 2 or more ICDs. Impulse control disorders were more common in patients treated with a dopamine agonist than in patients not taking a dopamine agonist (17.1% vs 6.9%; odds ratio [OR], 2.72; 95% confidence interval [CI], 2.08-3.54; P < .001). Impulse control disorder frequency was similar for pramipexole and ropinirole (17.7% vs 15.5%; OR, 1.22; 95% CI, 0.94-1.57; P = .14). Additional variables independently associated with ICDs were levodopa use, living in the United States, younger age, being unmarried, current cigarette smoking, and a family history of gambling problems.

Conclusions  Dopamine agonist treatment in PD is associated with 2- to 3.5-fold increased odds of having an ICD. This association represents a drug class relationship across ICDs. The association of other demographic and clinical variables with ICDs suggests a complex relationship that requires additional investigation to optimize prevention and treatment strategies.

Trial Registration  clinicaltrials.gov Identifier: NCT00617019

Impulse control disorders (ICDs), including problem or pathological gambling, compulsive buying, compulsive sexual behavior, and binge or compulsive eating, have been reported in Parkinson disease (PD).1 Preliminary cross-sectional prevalence estimates of ICDs in this population range from 1.7% to 6.1% for gambling,25 2.0% to 4.0% for compulsive sexual behavior,2,4,6 and 0.4% to 3.0% for compulsive buying2,4,6; there has been no formal prevalence estimate for eating disorders in PD.

Case reporting and cross-sectional studies suggest an association between dopamine agonist treatment and ICDs in PD.24,6 Impulse control disorders in PD have also been reported in the context of levodopa treatment7 and after deep-brain stimulation surgery.8 However, studies to date have typically assessed convenience samples of patients at single sites, had relatively small sample sizes, assessed only a subset of commonly reported ICDs in PD, and have not broadly assessed clinical or demographic correlates.

Given the clinical significance of ICDs in PD and persisting questions concerning the association with dopamine-replacement therapies and other clinical correlates, a cross-sectional study (the DOMINION Study) of approximately 3000 patients was undertaken to assess the point frequency of ICDs in PD and their association with dopamine-replacement therapies and other clinical measures. We hypothesized that ICDs would be more common in patients treated with dopamine agonists than those not, with no differences among dopamine agonists.

STUDY DESIGN AND PARTICIPANTS

A semi-structured interview using formal diagnostic criteria assessed current (anytime in the past 6 months) frequency of 4 ICDs (problem/pathological gambling, compulsive sexual behavior, compulsive buying, and binge-eating disorder) in treated patients with idiopathic PD. All participants were informed that the primary purpose of the study was to examine the frequency of ICDs in PD and their association with PD medications. Participants answered study questions individually, but corroborative information from informants was included when available. Prior to study initiation, each site developed a fixed subject recruitment strategy designed to minimize selection bias (eg, recruiting or excluding patients on the basis of known ICD or dopamine agonist treatment status). Specifically, patients with PD were recruited during regularly scheduled clinic visits, based on a set selection process individualized for each site (eg, attempting to assess every third scheduled patient during a particular half-day clinic) and by a member of the research staff with no knowledge of patients' current ICD or PD medication status. Each site obtained independent institutional review board approval.

Subjects were diagnosed as having idiopathic PD by a movement disorder specialist, aged 30 to 75 years, and recruited from 46 movement disorders centers in the United States (n = 33) and Canada (n = 13). Inclusion criteria required treatment with a PD medication for at least 1 year with demonstrated response, and dopamine agonist treatment could not have been initiated or terminated in the 6 months prior to evaluation. Changes in other PD medications and adjustments to dopamine agonist dosage in the 6 months prior to evaluation were allowed. The recorded PD medications and dosages were those being taken at the time of assessment. Written informed consent was provided by each patient prior to study participation.

PROCEDURES AND MEASUREMENTS

The following semi-structured diagnostic instruments were administered by trained research staff to capture clinically significant symptoms: (1) the Massachusetts Gambling Screen,9 for problem or pathological gambling (pathological gambling, ≥5 criteria endorsed; problem gambling, 3-4 criteria endorsed); (2) the Minnesota Impulsive Disorders Interview10 for compulsive buying and sexual behavior (both disorders, positive response to gateway question plus ≥1 secondary question for that subsection); and (3) the Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition, Text Revision)11 proposed research criteria for binge-eating disorder (positive response to both gateway questions and ≥3 secondary questions). Demographic and clinical data were obtained from patients in a semistructured interview and verified by medical record review when necessary. Modified Hoehn and Yahr staging12 was obtained from a movement disorders clinician or by medical record review.

STATISTICAL ANALYSIS

A Cochran-Mantel-Haenszel test with country stratification was performed and odds ratios (ORs) with 95% confidence intervals (CIs) were calculated for between-group comparisons in ICD frequencies. Breslow-Day tests were applied for homogeneity of odds. Other between-group patient characteristics were compared using the Cochran-Mantel-Haenszel test or Wilcoxon-Mann-Whitney test.

As initial analyses identified between-country differences in ICD frequencies and dopamine agonist prescribing, all additional analyses were stratified by country. Because nearly all patients treated with dopamine agonists were taking either pramipexole or ropinirole, the within–dopamine agonist class statistical comparison was made for patients taking pramipexole vs ropinirole as their sole dopamine agonist. For secondary analyses, variables associated with the presence of an ICD on univariate analysis at P < .10 were entered into stepwise logistic regression models to determine the independent effects of different correlates.

The 2 primary hypotheses were hierarchically ordered (a noninferiority hypothesis of no difference in overall ICD frequency for different dopamine agonists, followed by the hypothesis that overall ICD frequency would be higher in patients treated with dopamine agonists than those not treated with them), so an α adjustment was not required. Sample size calculation for the first hypothesis was based on the assumption that 50% of PD patients would be taking a dopamine agonist, of whom one-third would be taking pramipexole. Given a noninferiority margin of 5% (ie, an OR of 2) as the accepted limit in signal detection required to establish noninferiority with a type I error probability of 0.025 (1-sided) and a power of 80%, approximately 1500 patients treated with dopamine agonists and 3000 patients overall were required.

The following values were used to calculate levodopa equivalent daily dosages (LEDDs) for dopamine agonist, levodopa, and total (dopamine agonist + levodopa) dosages: 100 mg of regular levodopa = 133.3 mg of controlled-release levodopa = 80 mg of levodopa + catechol O-methyltransferase inhibitor = 1 mg of pergolide = 1 mg of pramipexole = 4 mg of ropinirole. Dopamine agonist and LEDDs were divided into quartiles to examine dosing effects (dopamine agonist, >0-≤150 mg, >150-≤300 mg, >300-≤450 mg, and >450 mg; and levodopa, >0-≤300 mg, >300-≤600 mg, >600-≤900 mg, and >900 mg). Analyses were performed using SAS software, release 8.02 (SAS Institute, Cary, North Carolina). P < .05 was considered significant.

DESCRIPTION OF STUDY POPULATION

Three thousand ninety patients participated in this study (Table 1). Nearly all (n = 3031 [98.1%]) were taking either levodopa or a dopamine agonist. Two-thirds (n = 2040 [66.0%]) were taking 1 or more DAs, and 86.8% (n = 2682) were taking levodopa, including 37.0% (n = 991) not taking a dopamine agonist. For the 59 (1.9%) patients taking neither a dopamine agonist nor levodopa, they took the following PD medications: a monoamine oxidase B inhibitor (n = 35), amantadine (n = 20), and/or an anticholinergic medication (n = 9).

Table Graphic Jump LocationTable 1. Demographic and Clinical Correlates of ICDs

For patients taking a dopamine agonist, the mean daily dosages and LEDDs, respectively, were 3.1 mg (SD, 1.7 mg) and 306.9 mg (SD, 168.2 mg) of pramipexole; 11.1 mg (SD, 6.6 mg) and 277.9 mg (SD, 164.9 mg) of ropinirole; and 2.9 mg (SD, 1.7 mg) and 286.6 mg (SD, 169.3 mg) of pergolide. On pairwise comparison, patients taking pramipexole had a higher dopamine agonist LEDD than those taking ropinirole (z = −4.1, P < .001).

CURRENT ICD FREQUENCIES AND DEMOGRAPHIC AND CLINICAL CHARACTERISTICS

At least 1 active ICD was identified in 13.6% of patients, with 3.9% of patients overall (or 28.7% of patients with an ICD) experiencing 2 or more ICDs. Five percent experienced problem/pathological gambling, 3.5% compulsive sexual behavior, 5.7% compulsive buying, and 4.3% binge-eating disorder.

DEMOGRAPHIC AND CLINICAL CHARACTERISTICS BY ICD STATUS

Compared with patients without an ICD, those with an active ICD were younger and more likely to be unmarried, reside in the United States, have more formal education, smoke cigarettes, report familial gambling problems (both historical and current), and acknowledge alcohol abuse in first-degree relatives (Table 1). Men were more likely than women to have diagnosed compulsive sexual behavior (5.2% vs 0.5%; OR, 11.98; 95% CI, 4.87-29.48; P < .001) and less likely to be diagnosed with compulsive buying (4.5% vs 7.8%; OR, 0.55; 95% CI, 0.40-0.74; P < .001) and binge-eating disorder (3.4% vs 5.8%; OR, 0.57; 95% CI, 0.40-0.81; P = .002). Compared with Canadian patients, US patients had increased frequencies of 2 ICDs: 5.5% vs 3.6% for problem/pathological gambling (OR, 1.58; 95% CI, 1.05-2.38; P = .03) and 6.7% vs 3.2% for compulsive buying (OR, 2.16; 95% CI, 1.42-3.28; P < .001). Patients with a history of gambling problems in a first-degree relative compared with patients without such a history had higher rates of problem/pathological gambling (12.7% vs 4.7%; OR, 2.97; 95% CI, 1.71-5.17; P < .001), compulsive buying (10.3% vs 5.5%, OR, 1.97; 95% CI, 1.08-3.58; P = .02), and binge-eating disorder (9.5% vs 4.0%; OR, 2.49; 95% CI, 1.34-4.64; P = .003).

CURRENT ICD FREQUENCIES IN THOSE TREATED AND NOT TREATED WITH DOPAMINE AGONISTS

Patients treated with dopamine agonists had a higher frequency of ICDs compared with those not treated with dopamine agonists (17.1% vs 6.9%, P < .001) (Table 2), a pattern observed across all 4 ICDs. An ICD was present in 17.7% of patients taking both a dopamine agonist and levodopa, 14.0% taking a dopamine agonist without levodopa, and 7.2% taking levodopa without a dopamine agonist. On multivariate analysis, the odds of having an ICD was higher in patients treated with a dopamine agonist than in levodopa-treated patients not taking a dopamine agonist (OR, 2.60; 95% CI, 1.97-3.43; P < .001). The combination of dopamine agonist and levodopa use, compared with dopamine agonist use alone, increased the odds of having an ICD (OR, 1.42; 95% CI, 1.02-1.98; P < .001). Of the 59 patients not taking a dopamine agonist or levodopa, 1 (1.7%) was diagnosed with an ICD.

Table Graphic Jump LocationTable 2. ICD Frequencies by Dopamine Agonist Treatment Status
CURRENT ICD FREQUENCIES BY DOPAMINE AGONIST TYPE

There was no statistically significant difference in overall ICD frequency between pramipexole- (n = 1286 [17.7%]) and ropinirole- (n = 651 [15.5%]) treated patients (OR, 1.22; 95% CI, 0.94-1.57; P = .14). This finding remained after controlling for either dopamine agonist LEDD or total LEDD, and was observed across all 4 ICD types. The overall ICD frequency in pergolide-treated patients (n = 50) was 22.0%.

MULTIVARIABLE ANALYSIS OF ICD CORRELATES

Examining the entire study population (N = 3090), demographic and clinical variables associated with a current ICD on multivariable analysis were younger age (≤65 years), being unmarried, living in the United States, current cigarette smoking, and a family history of gambling problems (Table 3). Both dopamine agonist and levodopa use were independently associated with an active ICD, with the OR nearly twice as high for dopamine agonist use.

Table Graphic Jump LocationTable 3. Multivariable Analyses of ICD Correlates in Entire Study Population

Examining only patients taking a dopamine agonist (n = 2040), on univariate analysis the median dopamine agonist LEDD in ICD and non-ICD patients was numerically the same (300 mg), but the interquartile range was higher for ICD patients (200-450 mg vs 150-400 mg, overall P = .002). The median levodopa LEDD was higher in patients with an ICD (450 mg vs 375 mg, P < .001). On multivariable analysis, there was no dopamine agonist dosage effect, but any levodopa use (OR, 1.43; 95% CI, 1.03-2.00; P = .03) and higher levodopa dosages (P = .008) were associated with a current ICD.

On univariate analysis, the median levodopa LEDD was higher in the ICD than the non-ICD group in patients taking levodopa but not a dopamine agonist (n = 991) (621 mg vs 461 mg, P = .003). On multivariable analysis, higher levodopa dosages were associated with a current ICD (P = .002).

This is the largest and most detailed study of the frequency and correlates of ICDs in PD. Specific strengths of the study include systematic evaluation of a very large number of PD patients in routine clinical care; concurrent evaluation of gambling, sex, shopping, and eating ICDs using standardized assessment instruments; use of a priori–defined recruitment procedure to minimize sampling bias; and blinding of ICD raters to PD medication status. Important new findings demonstrate (1) that nongambling ICDs occur at a similar frequency as compulsive gambling in PD; (2) a strong class association between dopamine agonist use and all ICDs; (3) an association between levodopa use and ICDs; (4) an association between higher levodopa dosages, but not dopamine agonist dosages, and ICDs; and (5) an independent association between numerous clinical and demographic variables and ICDs.

Although initial ICD case reporting in PD focused on pathological gambling,13 the 4 ICDs examined in this study occurred at similar frequencies, ranging from 3.5% (compulsive sexual behavior) to 5.7% (compulsive buying). Overall, the results suggest that ICDs as a group are not uncommon in PD. As some patients either did not acknowledge symptoms or had an ICD history during PD but were currently in remission, the cumulative prevalence of ICDs sometime during PD is likely higher than point prevalence reported here. In addition, this protocol did not assess the frequency of other compulsive behaviors reported to occur in this population, such as punding14 and dopamine dysregulation syndrome,15 which may differ from ICDs in terms of their phenomenology and association with PD medications.

More than one-fourth of ICD patients had 2 or more ICDs, which is consistent with previous case reporting that comorbid ICDs commonly occur in patients with PD.16,17 This highlights the importance of inquiring about multiple ICDs when assessing patients with PD.

Although ICD frequency was similar for men and women, between-sex differences for individual ICDs existed. Men were both more (compulsive sexual behavior) and less (compulsive buying and binge eating) likely than women to have particular ICDs. These findings mirror patterns in the general population.1820 Gender effects may explain the relatively low overall rate of compulsive sexual behavior, given its low frequency in women in this study (0.5%).

Impulse control disorders as a group, and compulsive gambling and buying specifically, were significantly more common in US than Canadian patients, even after controlling for possible confounding variables. These findings differ from earlier non-PD studies showing no consistent between-country differences in problem/pathological gambling prevalence estimates.21 It is possible that new environmental factors (eg, increased availability of casino gambling in the United States) or differences between PD populations in the United States and Canada contributed to the observed differences.

Consistent with previous case reporting and smaller cross-sectional studies,2,3,6 the odds of having an individual ICD were 2 to 3.3 times higher in patients treated with dopamine agonists compared with patients not treated with them, ranging from 2.53 (compulsive buying) to 3.34 (binge-eating disorder), which is also consistent with previous case reporting and smaller cross-sectional studies.2,3,6 Overall and individual ICD frequencies were similar for pramipexole- and ropinirole-treated patients. These results, similar to those reported previously,2,16,17,22 suggest that dopamine agonists as a class are associated with ICDs. In this study, after controlling for levodopa exposure and other covariates, no dopamine agonist dosing effect was found, though there are reports to the contrary.2,16 As the study was cross-sectional, a selection bias for current dopamine agonist dosage may have existed that obscured a dosing effect (eg, patients with an ICD history on higher dopamine agonist dosages may have become asymptomatic after decreasing their dopamine agonist dosage).

A possible neurobiological explanation for the association between dopamine agonist treatment and ICDs centers around dopamine-receptor binding profiles. Dopamine2(D2) and D1 receptors, abundant in the dorsal striatum,23 may mediate the motor effects of dopamine-replacement therapies, whereas D3 receptors are abundant in the ventral striatum,23 a brain region associated with both behavioral addictions24 and substance use disorders.25 Second generation nonergot dopamine agonists (eg, pramipexole and ropinirole) demonstrate relative selectivity for D3 receptors compared with D2 and D1 receptors.26

The independent association between levodopa treatment and ICDs has not been reported in previous cross-sectional studies. In patients taking a dopamine agonist, concurrent levodopa use increased the odds of an ICD by approximately 50%. In contrast to dopamine agonist treatment, higher levodopa dosages were also associated with ICDs. This observation of a significant, but less robust, association between levodopa treatment and ICDs is consistent with the dopamine-receptor binding profile of dopamine (the physiologically active metabolite of levodopa), which demonstrates greater selectivity for D1 and D2 receptors than the D3 receptor compared with nonergot dopamine agonists.26

There were multiple demographic and clinical correlates of ICDs. Although younger patients are more likely to be treated with a dopamine agonist, the age effect remained after controlling for dopamine agonist exposure. Both younger age and being unmarried have been associated with ICDs in the general population.18,27,28 Elevated frequencies of tobacco smoking have been reported in association with ICDs in the general population.29 This finding, in conjunction with the association of a family history of gambling problems, is consistent with the proposition that there are shared neurobiological, genetic, or environmental contributions to the development of ICDs.3032 These findings, together with sex differences for individual disorders, suggest that multiple factors may contribute to ICD development in patients with PD. This may be used in clinical settings to help identify individuals at increased risk.

Use of movement disorder centers as study sites limits the generalizability of our results. In addition, the study was not designed to define the etiological risk factors of ICDs in PD, as it was not a prospective randomized study of different dopamine-replacement therapies. Given that there may be a significant lag time between initiation of dopamine-replacement therapies and onset of ICD behaviors and that PD patients frequently undergo changes in dopamine-replacement therapies over time, conducting a prospective study was not feasible and might have produced data that were difficult to interpret. Lack of inclusion of an early untreated PD group and a non-PD control group prevents comparison of prevalence estimates for ICDs in untreated and treated PD patients and the general population. Most studies of ICDs in treated PD patients that have included a matched non-PD control group or used comparative data from epidemiological studies reported cross-sectional5,33 or cumulative34 frequencies that were significantly higher in the PD group than in the general population. Also, structured diagnostic interviews were not used to diagnose ICDs, and the severity of ICD symptoms was not rated. Finally, because PD patients typically undergo long-term changes in treatment and we used a 6-month time frame for an ICD diagnosis, it was not possible to accurately ascertain the impact of the duration of dopamine agonist treatment or recent changes in non–dopamine agonist treatment on ICD status.

This study demonstrates that 4 clinically significant ICDs occur in PD, they are associated with dopamine replacement-therapies (both dopamine agonists and levodopa), and they have other clinical and demographic correlates that may represent risk factors. Dopamine agonists are increasingly used in clinical settings to treat disorders other than PD, and initial case reporting suggests that ICDs may occur with dopamine agonist treatment in patients with restless legs syndrome16 and fibromyalgia.35 Larger epidemiologic studies in these other populations are needed to examine the possible relationships between dopamine agonist treatment, other clinical features, and ICDs.

Correspondence: Daniel Weintraub, MD, University of Pennsylvania, 3615 Chestnut St, Room 330, Philadelphia, PA, 19104 (daniel.weintraub@uphs.upenn.edu).

Accepted for Publication: December 21, 2009.

Author Contributions: Drs Weintraub, Potenza, Siderowf, Stacy, Voon, and Lang comprised the Scientific Advisory Board for the study and saw and approved the final version of the manuscript. Drs Weintraub and Lang were study coordinating investigators for the DOMINION Study and approved the study protocol, assisted in monitoring of the study, and approved the final clinical trial report. Drs Koester, Whetteckey, and Wunderlich saw and approved the final version of the manuscript. Dr Weintraub had full access to the data and takes responsibility for the integrity of the data and the accuracy of the data analysis. Analyses were conducted by Dr Koester. Study concept and design: Weintraub, Koester, Potenza, Stacy, Voon, Whetteckey, Wunderlich, and Lang. Acquisition of data: Weintraub, Stacy, Wunderlich, and Lang. Analysis and interpretation of data: Weintraub, Koester, Potenza, Siderowf, Stacy, Voon, Wunderlich, and Lang. Drafting of the manuscript: Weintraub. Critical revision of the manuscript for important intellectual content: Weintraub, Koester, Potenza, Siderowf, Stacy, Voon, Whetteckey, Wunderlich, and Lang. Statistical analysis: Weintraub, Koester, and Voon. Obtained funding: Wunderlich. Administrative, technical, and material support: Koester, Wunderlich, and Lang. Study supervision: Weintraub, Siderowf, Stacy, and Wunderlich.

Financial Disclosure: Dr Weintraub has received consulting fees, honoraria, or grant support from Boehringer Ingelheim, BrainCells, Merck Serono, Novartis, Ovation, and Wyeth. Dr Potenza has received consulting fees or honoraria from Boehringer Ingelheim, has consulted for and has financial interests in Somaxon, has received research support from Mohegan Sun Casino and Forest Laboratories pharmaceuticals, and has consulted for law offices and the federal public defender's office on issues related to ICDs. He has also received support from the National Center for Responsible Gaming and its affiliate, the Institute for Research on Gambling Disorders. Dr Siderowf has received consulting fees or honoraria from Boehringer Ingelheim, Merck Serono, and Teva. Dr Stacy has received consulting fees or honoraria from Allergan, Boehringer Ingelheim, Osmotica, Biogen, General Electric, Kyowa, Neurologix, Novartis, Synosia, and Teva. Dr Lang has received consulting fees or honoraria from Boehringer Ingelheim, Ceregene, Eisai, Medtronic, Novartis, Prestwick, Merck Serono, Solvay, Taro, and Teva.

Funding/Support: This study, the DOMINION Study, was funded by Boehringer Ingelheim and designed jointly by Boehringer Ingelheim and the Scientific Advisory Board (consisting of Drs Weintraub, Potenza, Siderowf, Stacy, Voon, and Lang).

Role of the Sponsor: Data collected by the sites were entered into a central database and analyzed by Boehringer Ingelheim (by Dr Koester based on Scientific Advisory Board recommendations). Boehringer Ingelheim and the coordinating investigators (Drs Weintraub and Lang) vouch for the data and data analyses. The Scientific Advisory Board prepared an initial draft of the manuscript, and all authors contributed to the submitted version through an iterative review process. Boehringer Ingelheim placed no limitations on data analyses or manuscript preparation. Analyses were conducted by the study sponsor (Dr Koester) and per journal policy an independent analysis of the data was conducted by Peggy Auinger, MS, of the University of Rochester School of Medicine and Dentistry.

Additional Contributions: We acknowledge the efforts of the following principal investigators and research staff of the DOMINION Study Group at the 46 participating centers as well the trial data manager, Joanne Zuck, MPH. United States: R. Pahwa, University of Kansas School of Medicine, Kansas City; W. Ondo, Baylor College of Medicine, Houston, Texas; B. Scott, Duke University School of Medicine, Durham, North Carolina; P. Barbour, Lehigh Valley Hospital, Allentown, Pennsylvania; J. Friedman, NeuroHealth Inc, Warwick, Rhode Island; J. Morgan, Medical College of Georgia, Augusta; E. Driver-Dunckley, Mayo Clinic Arizona, Scottsdale; M. Menza, University of Medicine and Dentistry, New Jersey (Robert Wood Johnson Medical School), Piscataway; H. Fernandez, University of Florida School of Medicine, Gainesville; D. Weintraub, University of Pennsylvania and Veterans Affairs Medical Center, Philadelphia; N. Leopold, Crozer Chester Medical Center, Upland, Pennsylvania; D. Jennings, Molecular NeuroImaging LLC, New Haven, Connecticut; T. Simuni, Northwestern University School of Medicine, Chicago, Illinois; L. Marsh, The Johns Hopkins University School of Medicine, Baltimore, Maryland; W. Marks, Veterans Affairs Medical Center, San Francisco, California; M. Nirenberg, Weill Medical College of Cornell University, New York, New York; D. Margolin, Margolin Brain Institute, Fresno, California; S. Isaacson, Parkinson Disease and Movement Disorders of Boca Raton, Boca Raton, Florida; A. Diamond, Colorado Neurology, Englewood, Colorado; G. Liang, The Parkinson's Institute, Sunnyvale, California; J. Schneider, Thomas Jefferson University, Jefferson Medical College, Philadelphia, Pennsylvania; H. Shill, Sun Health Research Institute, Sun City, Arizona; M. Baron, Veterans Affairs Medical Center, Richmond, Virginia; J. Murphy, Associate Neurologists PC, Danbury, Connecticut; P. LeWitt, Clinical Neuroscience Center, Southfield, Michigan; D. Higgins, Albany Medical College, Albany, New York; J. Sutton, Pacific Neuroscience Medical Group Inc, Oxnard, California; M. Thomas, Neurology Specialists of Dallas, Dallas, Texas; T. Davis, Vanderbilt University School of Medicine, Nashville, Tennessee; W. Grainger, Neurological Physicians of Arizona, Mesa; W. McDonald, Emory University School of Medicine, Atlanta, Georgia; and D. Kreitzman, Parkinson's Disease and Movement Disorders of Long Island, Commack, New York. Canada: M. Guttman, Markham Professional Centre, Markham, Ontario; E. Pourcher, Quebec Memory & Motor Skills Disorders Clinic, Québec City; M. Panisset, Hôtel-Dieu de Montreal, Montréal, Quebec; A. Goodridge, Health Science Centre, St John’s, Newfoundland; D. Grimes, The Ottawa Hospital–Civic Campus, Ottawa, Ontario; D. Hobson, Deer Lodge Centre, Winnipeg, Manitoba; W. Martin, Glenrose Rehabilitation Hospital, Edmonton, Alberta; R. Ranawaya, Department of Clinical Neurosciences Area 3 Neurology, Calgary, Alberta; D. Stewart, Neurocare Research Consulting Corporation, Kitchener, Ontario; J. Miyasaki, Toronto Western Hospital, Toronto, Ontario; A. Rajput, Royal University Hospital, Saskatoon, Saskatchewan; M. Jog, Canadian Foundation for Innovation, London, Ontario; and D. King, Dalhousie University, Halifax, Nova Scotia.

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Evans  AHKatzenschlager  RPaviour  D  et al.  Punding in Parkinson's disease: its relation to the dopamine dysregulation syndrome. Mov Disord 2004;19 (4) 397- 405
PubMed
Giovannoni  GO'Sullivan  JDTurner  KManson  AJLees  AJL Hedonistic homeostatic dysregulation in patients with Parkinson's disease on dopamine replacement therapies. J Neurol Neurosurg Psychiatry 2000;68 (4) 423- 428
PubMed
Ondo  WGLai  D Predictors of impulsivity and reward seeking behavior with dopamine agonists. Parkinsonism Relat Disord 2008;14 (1) 28- 32
PubMed
Singh  AKandimala  GDewey  RB  JrO'Suilleabhain  P Risk factors for pathological gambling and other compulsions among Parkinson's disease patients taking dopamine agonists. J Clin Neurosci 2007;14 (12) 1178- 1181
PubMed
Koran  LMFaber  RJAboujaoude  ELarge  MDSerpe  RT Estimated prevalence of compulsive buying behavior in the United States. Am J Psychiatry 2006;163 (10) 1806- 1812
PubMed
Striegel-Moore  RHFranko  DL Epidemiology of binge eating disorder. Int J Eat Disord 2003;34 ((suppl)) S19- S29
PubMed
Kuzma  JMBlack  DW Epidemiology, prevalence, and natural history of compulsive sexual behavior. Psychiatr Clin North Am 2008;31 (4) 603- 611
PubMed
Shaffer  HJHall  MNVander Bilt  J Estimating the prevalence of disordered gambling behavior in the United States and Canada: a research synthesis. Am J Public Health 1999;89 (9) 1369- 1376
PubMed
Voon  VThomsen  TMiyasaki  JM  et al.  Factors associated with dopaminergic drug-related pathological gambling in Parkinson disease. Arch Neurol 2007;64 (2) 212- 216
PubMed
Gurevich  EVJoyce  JN Distribution of dopamine D3 receptor expression neurons in the human forebrain: comparison with D2 receptor expressing neurons. Neuropsychopharmacology 1999;20 (1) 60- 80
PubMed
Holden  C ‘Behavioral’ addictions: do they exist? Science 2001;294 (5544) 980- 982
PubMed
Brewer  JAPotenza  MN The neurobiology and genetics of impulse control disorders: relationships to drug addictions. Biochem Pharmacol 2008;75 (1) 63- 75
PubMed
Gerlach  MDouble  KArzberger  TLeblhuber  FTatschner  TRiederer  P Dopamine receptor agonists in current clinical use: comparative dopamine receptor binding profiles defined in the human striatum. J Neural Transm 2003;110 (10) 1119- 1127
PubMed
Cunningham-Williams  RMCottler  LBCompton  WM  IIISpitznagel  EL Taking chances: problem gamblers and mental health disorders: results from the St. Louis Epidemiologic Catchment Area Study. Am J Public Health 1998;88 (7) 1093- 1096
PubMed
Grucza  RAPrzybeck  TRCloninger  CR Prevalence and correlates of binge eating disorder in a community sample. Compr Psychiatry 2007;48 (2) 124- 131
PubMed
Petry  NMStinson  FSGrant  BF Comorbidity of DSM-IV pathological gambling and other psychiatric disorders: results from the National Epidemiologic Survey on alcohol and related conditions. J Clin Psychiatry 2005;66 (5) 564- 574
PubMed
Slutske  WSEisen  STrue  WRLyons  MJGoldberg  JTsuang  M Common genetic vulnerability for pathological gambling and alcohol dependence in men. Arch Gen Psychiatry 2000;57 (7) 666- 673
PubMed
Comings  DEGonzalez  NWu  S  et al.  Studies of the 48 bp repeat polymorphism of the DRD4 gene in impulsive, compulsive, addictive behaviors: Tourette syndrome, ADHD, pathological gambling, and substance abuse. Am J Med Genet 1999;88 (4) 358- 368
PubMed
Lilenfeld  LRRRingham  RKalarchian  MAMarcus  MD A family history study of binge-eating disorder. Compr Psychiatry 2008;49 (3) 247- 254
PubMed
Crockford  DQuickfall  JCurrie  SFurtado  SSuchowersky  Oel-Guebaly  N Prevalence of problem and pathological gambling in Parkinson's disease. J Gambl Stud 2008;24 (4) 411- 422
PubMed
Giladi  NWeitzman  NSchreiber  SShabtai  HPeretz  C New onset heightened interest or drive for gambling, shopping, eating or sexual activity in patients with Parkinson's disease: the role of dopamine agonist treatment and age at motor symptoms onset. J Psychopharmacol 2007;21 (5) 501- 506
PubMed
Holman  AJ Impulse control disorder behaviors associated with pramipexole used to treat fibromyalgia. J Gambl Stud 2009;25 (3) 425- 431
PubMed10.1007/s10899-009-9123-2

Figures

Tables

Table Graphic Jump LocationTable 1. Demographic and Clinical Correlates of ICDs
Table Graphic Jump LocationTable 2. ICD Frequencies by Dopamine Agonist Treatment Status
Table Graphic Jump LocationTable 3. Multivariable Analyses of ICD Correlates in Entire Study Population

References

Voon  VFox  SH Medication-related impulse control and repetitive behaviors in Parkinson disease. Arch Neurol 2007;64 (8) 1089- 1096
PubMed
Weintraub  DSiderowf  ADPotenza  MN  et al.  Association of dopamine agonist use with impulse control disorders in Parkinson disease. Arch Neurol 2006;63 (7) 969- 973
PubMed
Voon  VHassan  KZurowski  M  et al.  Prospective prevalence of pathological gambling and medication association in Parkinson disease. Neurology 2006;66 (11) 1750- 1752
PubMed
Pontone  GWilliams  JRBassett  SSMarsh  L Clinical features associated with impulse control disorders in Parkinson disease. Neurology 2006;67 (7) 1258- 1261
PubMed
Avanzi  MBaratti  MCabrini  SUber  EBrighetti  GBonfà  F Prevalence of pathological gambling in patients with Parkinson's disease. Mov Disord 2006;21 (12) 2068- 2072
PubMed
Voon  VHassan  KZurowski  M  et al.  Prevalence of repetitive and reward-seeking behaviors in Parkinson disease. Neurology 2006;67 (7) 1254- 1257
PubMed
Molina  JASáinz-Artiga  MJFraile  A  et al.  Pathologic gambling in Parkinson's disease: a behavioral manifestation of pharmacologic treatment? Mov Disord 2000;15 (5) 869- 872
PubMed
Smeding  HMMGoudriaan  AEFoncke  EMJSchuurman  PRSpeelman  JDSchmand  B Pathological gambling after bilateral subthalamic nucleus stimulation in Parkinson disease. J Neurol Neurosurg Psychiatry 2007;78 (5) 517- 519
PubMed
Shaffer  HJLaBrie  RScanlan  KMCummings  TN Pathological gambling among adolescents: Massachusetts gambling screen (MAGS). J Gambl Stud 1994;10 (4) 339- 362
Christenson  GAFaber  RJdeZwaan  M  et al.  Compulsive buying: descriptive characteristics and psychiatric comorbidity. J Clin Psychiatry 1994;55 (1) 5- 11
PubMed
American Psychiatric Association, Diagnostic and Statistical Manual of Mental Disorders. Fourth Edition, Text Revision Washington, DC American Psychiatric Association2000;
Fahn  SElton  RLthe UPDRS Development Committee, Unified Parkinson's disease rating scale. Fahn  SMarsden  CDCalne  DGoldstein  MRecent Developments in Parkinson's Disease. Florham Park, NJ Macmillan Health Care Information1987;153- 163
Driver-Dunckley  ESamanta  JStacy  M Pathological gambling associated with dopamine agonist therapy in Parkinson's disease. Neurology 2003;61 (3) 422- 423
PubMed
Evans  AHKatzenschlager  RPaviour  D  et al.  Punding in Parkinson's disease: its relation to the dopamine dysregulation syndrome. Mov Disord 2004;19 (4) 397- 405
PubMed
Giovannoni  GO'Sullivan  JDTurner  KManson  AJLees  AJL Hedonistic homeostatic dysregulation in patients with Parkinson's disease on dopamine replacement therapies. J Neurol Neurosurg Psychiatry 2000;68 (4) 423- 428
PubMed
Ondo  WGLai  D Predictors of impulsivity and reward seeking behavior with dopamine agonists. Parkinsonism Relat Disord 2008;14 (1) 28- 32
PubMed
Singh  AKandimala  GDewey  RB  JrO'Suilleabhain  P Risk factors for pathological gambling and other compulsions among Parkinson's disease patients taking dopamine agonists. J Clin Neurosci 2007;14 (12) 1178- 1181
PubMed
Koran  LMFaber  RJAboujaoude  ELarge  MDSerpe  RT Estimated prevalence of compulsive buying behavior in the United States. Am J Psychiatry 2006;163 (10) 1806- 1812
PubMed
Striegel-Moore  RHFranko  DL Epidemiology of binge eating disorder. Int J Eat Disord 2003;34 ((suppl)) S19- S29
PubMed
Kuzma  JMBlack  DW Epidemiology, prevalence, and natural history of compulsive sexual behavior. Psychiatr Clin North Am 2008;31 (4) 603- 611
PubMed
Shaffer  HJHall  MNVander Bilt  J Estimating the prevalence of disordered gambling behavior in the United States and Canada: a research synthesis. Am J Public Health 1999;89 (9) 1369- 1376
PubMed
Voon  VThomsen  TMiyasaki  JM  et al.  Factors associated with dopaminergic drug-related pathological gambling in Parkinson disease. Arch Neurol 2007;64 (2) 212- 216
PubMed
Gurevich  EVJoyce  JN Distribution of dopamine D3 receptor expression neurons in the human forebrain: comparison with D2 receptor expressing neurons. Neuropsychopharmacology 1999;20 (1) 60- 80
PubMed
Holden  C ‘Behavioral’ addictions: do they exist? Science 2001;294 (5544) 980- 982
PubMed
Brewer  JAPotenza  MN The neurobiology and genetics of impulse control disorders: relationships to drug addictions. Biochem Pharmacol 2008;75 (1) 63- 75
PubMed
Gerlach  MDouble  KArzberger  TLeblhuber  FTatschner  TRiederer  P Dopamine receptor agonists in current clinical use: comparative dopamine receptor binding profiles defined in the human striatum. J Neural Transm 2003;110 (10) 1119- 1127
PubMed
Cunningham-Williams  RMCottler  LBCompton  WM  IIISpitznagel  EL Taking chances: problem gamblers and mental health disorders: results from the St. Louis Epidemiologic Catchment Area Study. Am J Public Health 1998;88 (7) 1093- 1096
PubMed
Grucza  RAPrzybeck  TRCloninger  CR Prevalence and correlates of binge eating disorder in a community sample. Compr Psychiatry 2007;48 (2) 124- 131
PubMed
Petry  NMStinson  FSGrant  BF Comorbidity of DSM-IV pathological gambling and other psychiatric disorders: results from the National Epidemiologic Survey on alcohol and related conditions. J Clin Psychiatry 2005;66 (5) 564- 574
PubMed
Slutske  WSEisen  STrue  WRLyons  MJGoldberg  JTsuang  M Common genetic vulnerability for pathological gambling and alcohol dependence in men. Arch Gen Psychiatry 2000;57 (7) 666- 673
PubMed
Comings  DEGonzalez  NWu  S  et al.  Studies of the 48 bp repeat polymorphism of the DRD4 gene in impulsive, compulsive, addictive behaviors: Tourette syndrome, ADHD, pathological gambling, and substance abuse. Am J Med Genet 1999;88 (4) 358- 368
PubMed
Lilenfeld  LRRRingham  RKalarchian  MAMarcus  MD A family history study of binge-eating disorder. Compr Psychiatry 2008;49 (3) 247- 254
PubMed
Crockford  DQuickfall  JCurrie  SFurtado  SSuchowersky  Oel-Guebaly  N Prevalence of problem and pathological gambling in Parkinson's disease. J Gambl Stud 2008;24 (4) 411- 422
PubMed
Giladi  NWeitzman  NSchreiber  SShabtai  HPeretz  C New onset heightened interest or drive for gambling, shopping, eating or sexual activity in patients with Parkinson's disease: the role of dopamine agonist treatment and age at motor symptoms onset. J Psychopharmacol 2007;21 (5) 501- 506
PubMed
Holman  AJ Impulse control disorder behaviors associated with pramipexole used to treat fibromyalgia. J Gambl Stud 2009;25 (3) 425- 431
PubMed10.1007/s10899-009-9123-2

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