MedPath

Vimpat® Added as Adjunctive Therapy to One Baseline Antiepileptic Drug

Completed
Conditions
Epilepsies, Partial
Registration Number
NCT01098162
Lead Sponsor
UCB Pharma GmbH
Brief Summary

The purpose of this study is to systematically and prospectively collect data from patients with partial-onset seizures in routine clinical practice setting receiving adjunctive Vimpat®. The observed population will be only patients with one baseline antiepileptic drug. Seizure control and tolerability data will be evaluated.

Detailed Description

Not available

Recruitment & Eligibility

Status
COMPLETED
Sex
All
Target Recruitment
576
Inclusion Criteria
  • The patient's treatment must be in accordance with the local marketing authorization (MA) for Vimpat®
  • The decision to prescribe Vimpat® has to be made by the physician before and independently of his/her decision to include the patient in the study
  • The Vimpat® treatment should have been started not longer than 2 weeks before study inclusion of the patient
  • The patient must have a diagnosis of Epilepsy with Partial-Onset Seizures
  • Based on the physician's clinical judgment, the patient's seizure activity is not controlled sufficiently on a current monotherapy and it is in the patient's best interest to be prescribed adjunctive Vimpat®
Exclusion Criteria

In accordance with the Summary of Product Characteristics (SmPC)

Study & Design

Study Type
OBSERVATIONAL
Study Design
Not specified
Primary Outcome Measures
NameTimeMethod
Clinical Global Impression of Change (CGI-C) at Month 6Month 6

For the assessment of the Clinical Global Impression of Change (CGI-C), the investigator provided his/her assessment of the subject's clinical status compared to Baseline. He/she was asked to check the category that best describes the subject's condition over the past 6 months compared to Baseline:

* Very much improved

* Much improved

* Minimally improved

* No change

* Minimally worse

* Much worse

* Very much worse

Secondary Outcome Measures
NameTimeMethod
Change in Number (Frequency) of Partial-onset Seizures Without Secondary Generalization From Baseline to Month 6From Baseline to Month 6

Baseline values for the seizure frequency (SF) during the 12 weeks time period prior to inclusion ('historical baseline'), and the post-baseline values of seizure frequency reported after 6 months were normalized to a 28 days interval.

Change in number of partial-onset seizures was derived as follows:

Change in SF per 28 days = (SF at 6 months per 28 days) - (SF at Baseline per 28 days).

A negative value in change from Baseline means that the value has decreased from Baseline to Month 6.

Partial-onset seizures can be classified into one of the following three groups:

* Simple partial seizures

* Complex partial seizures

* Partial seizures evolving to secondarily generalized seizures.

Change in Number (Frequency) of Seizures With Secondary Generalization From Baseline to Month 3From Baseline to Month 3

Baseline values for the seizure frequency (SF) during the 12 weeks time period prior to inclusion ('historical baseline'), and the post-baseline values of seizure frequency reported after 3 months were normalized to a 28 days interval.

Change in number of partial-onset seizures with secondary generalization was derived as follows:

Change in SF per 28 days = (SF at 3 months per 28 days) - (SF at Baseline per 28 days).

A negative value in change from Baseline means that the value has decreased from Baseline to Month 3.

Partial-onset seizures with secondary generalization can be classified into one of the following three groups:

* Simple partial seizures evolving to generalized seizures

* Complex partial seizures evolving to generalized seizures

* Simple partial seizures evolving to Complex partial seizures evolving to generalized seizures.

Incidence of Adverse Events During the StudyFrom Inclusion Visit (Day 0) up to Month 6

The number of subjects affected by any Treatment Emergent Adverse Event (TEAE) during the course of the study from Day 0 up to Month 6 is presented below.

Change in Number (Frequency) of Partial-onset Seizures Without Secondary Generalization From Baseline to Month 3From Baseline to Month 3

Baseline values for the seizure frequency (SF) during the 12 weeks time period prior to inclusion ('historical baseline'), and the post-baseline values of seizure frequency reported after 3 months were normalized to a 28 days interval.

Change in number of partial-onset seizures was derived as follows:

Change in SF per 28 days = (SF at 3 months per 28 days) - (SF at Baseline per 28 days).

A negative value in change from Baseline means that the value has decreased from Baseline to Month 3.

Partial-onset seizures can be classified into one of the following three groups:

* Simple partial seizures

* Complex partial seizures

* Partial seizures evolving to secondarily generalized seizures.

Change in Number (Frequency) of Seizures With Secondary Generalization From Baseline to Month 6From Baseline to Month 6

Baseline values for the seizure frequency (SF) during the 12 weeks time period prior to inclusion ('historical baseline'), and the post-baseline values of seizure frequency reported after 6 months were normalized to a 28 days interval.

Change in number of partial-onset seizures with secondary generalization was derived as follows:

Change in SF per 28 days = (SF at 6 months per 28 days) - (SF at Baseline per 28 days).

A negative value in change from Baseline means that the value has decreased from Baseline to Month 6.

Partial-onset seizures with secondary generalization can be classified into one of the following three groups:

* Simple partial seizures evolving to generalized seizures

* Complex partial seizures evolving to generalized seizures

* Simple partial seizures evolving to Complex partial seizures evolving to generalized seizures.

Trial Locations

Locations (113)

13

🇩🇪

Ulm, Germany

99

🇩🇪

Kleve, Germany

36

🇩🇪

Bielefeld, Germany

192

🇩🇪

Böblingen, Germany

21

🇩🇪

Dresden, Germany

175

🇩🇪

Brandenburg, Germany

14

🇩🇪

Stuttgart, Germany

75

🇩🇪

Berlin, Germany

55

🇩🇪

Aachen, Germany

7

🇩🇪

Eberswalde, Germany

102

🇩🇪

Eisenach, Germany

68

🇩🇪

Leipzig, Germany

57

🇩🇪

Potsdam, Germany

1

🇩🇪

Greifswald, Germany

168

🇩🇪

Schwedt, Germany

65

🇩🇪

Göttingen, Germany

134

🇩🇪

Halle (Saale), Germany

45

🇩🇪

Ravensburg, Germany

81

🇩🇪

Leipzig, Germany

148

🇩🇪

Lüdenscheid, Germany

151

🇩🇪

Mühlhausen, Germany

69

🇩🇪

Nürnberg, Germany

3

🇩🇪

Radeberg, Germany

49

🇩🇪

Berlin, Germany

167

🇩🇪

München, Germany

5

🇩🇪

Bonn, Germany

161

🇩🇪

Dortmund, Germany

194

🇩🇪

Aichach, Germany

78

🇩🇪

Aschaffenburg, Germany

20

🇩🇪

Schleswig, Germany

16

🇩🇪

Kiel, Germany

125

🇩🇪

Kaufbeuren, Germany

176

🇩🇪

Köln, Germany

4

🇩🇪

Leipzig, Germany

138

🇩🇪

Lohr am Main, Germany

131

🇩🇪

Ludwigsburg, Germany

87

🇩🇪

Oranienburg, Germany

113

🇩🇪

Leipzig, Germany

154

🇩🇪

Mannheim, Germany

123

🇩🇪

Neumarkt, Germany

15

🇩🇪

Herdecke, Germany

101

🇩🇪

München, Germany

2

🇩🇪

München, Germany

159

🇩🇪

Rathenow, Germany

62

🇩🇪

Neukirchen-Vluyn, Germany

33

🇩🇪

Mainz, Germany

43

🇩🇪

Neuburg, Germany

150

🇩🇪

Schwäb. Gmünd, Germany

140

🇩🇪

Senftenberg, Germany

54

🇩🇪

Unterhaching, Germany

107

🇩🇪

Berlin, Germany

10A

🇩🇪

Berlin, Germany

66

🇩🇪

Berlin, Germany

105

🇩🇪

Chemnitz, Germany

182

🇩🇪

Coppenbrügge, Germany

128

🇩🇪

Dresden, Germany

111

🇩🇪

Düren, Germany

38

🇩🇪

Düsseldorf, Germany

174

🇩🇪

Eisenach, Germany

56

🇩🇪

Ellwangen, Germany

50

🇩🇪

Erbach, Germany

179

🇩🇪

Erfurt, Germany

186

🇩🇪

Erfurt, Germany

6

🇩🇪

Erlangen, Germany

12

🇩🇪

Essen, Germany

137

🇩🇪

Fulda, Germany

103

🇩🇪

Gera, Germany

47

🇩🇪

Grevenbroich, Germany

158

🇩🇪

Göttingen, Germany

160

🇩🇪

Hamburg, Germany

40

🇩🇪

Immenstadt, Germany

93

🇩🇪

Hamm, Germany

147

🇩🇪

Heilbronn, Germany

122

🇩🇪

Herborn, Germany

71

🇩🇪

Hamburg, Germany

52

🇩🇪

Jena, Germany

61

🇩🇪

Jülich, Germany

44

🇩🇪

Karlstadt, Germany

133

🇩🇪

Kastellaun, Germany

37

🇩🇪

Krefeld, Germany

180

🇩🇪

Köln, Germany

46

🇩🇪

Lappersdorf, Germany

80

🇩🇪

Oelde, Germany

98

🇩🇪

Oldenburg, Germany

95

🇩🇪

Rostock, Germany

85

🇩🇪

Rüsselsheim, Germany

157

🇩🇪

Schlüchtern, Germany

166

🇩🇪

Schorndorf, Germany

181

🇩🇪

Schriesheim, Germany

17

🇩🇪

Tübingen, Germany

164

🇩🇪

Siegen, Germany

79

🇩🇪

Wismar, Germany

144

🇩🇪

Sondershausen, Germany

104

🇩🇪

Traunstein, Germany

171

🇩🇪

Wermsdorf, Germany

127

🇩🇪

Stralsund, Germany

170

🇩🇪

Stuttgart, Germany

48

🇩🇪

Ulm, Germany

143

🇩🇪

Westerstede, Germany

119

🇩🇪

Aalen, Germany

191

🇩🇪

Altenburg, Germany

136

🇩🇪

Alzenau, Germany

35

🇩🇪

Bad Berka, Germany

90

🇩🇪

Baesweiler, Germany

141

🇩🇪

Berlin, Germany

25

🇩🇪

Berlin, Germany

39

🇩🇪

Dresden, Germany

112

🇩🇪

Gelsenkirchen, Germany

88

🇩🇪

Göttingen, Germany

169

🇩🇪

Wolfratshausen, Germany

183

🇩🇪

Troisdorf, Germany

130

🇩🇪

Höchberg, Germany

27

🇩🇪

Freiburg, Germany

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