GOLI2015: Golimumab Effect in the Modulation of Gut Microbiota in Ulcerative Colitis
Study Details
Study Description
Brief Summary
This study aims to characterize the changes on intestinal microbiota pattern associated with the use of golimumab in order to determine if intestinal microbiota markers may correlate with golimumab therapeutic effect in patients naïve & non-naïve to anti-TNF treatment
| Condition or Disease | Intervention/Treatment | Phase |
|---|---|---|
Detailed Description
Golimumab effect in the modulation of gut microbiota in Ulcerative Colitis. Pilot Study.
- BACKGROUND Recently, a consistent body of evidence indicates that the gut microbiota ability to modulate and direct the host immune response is considered one of the pivotal factors that modulate the delicate balance between health and disease in digestive diseases. In the case of inflammatory bowel disease (IBD), the gut microbiota has a central role in maintaining the microbiological homeostasis of the patient. Recent studies describe the existence of different patterns of intestinal microbiota from patients with IBD and healthy individuals . The alteration of the microbiological pattern not associated with disease is known as dysbiosis and is directly related to the degree of inflammation of the intestinal mucosa, and, thus, the clinic status: a greater dysbiosis, greater clinical correlation with disease state, so that the gut microbiota is a direct marker of the state of colonic inflammation .
The state of dysbiosis is measured through different microbiological indices of the total population of bacteria in the colon. Changes in rates of these indices are the parameters that are measured to characterize the gut microbiota of the patients. In the case of ulcerative colitis (UC) studies have shown that intestinal microbiota is a central factor in maintaining the balance between deep remission and the presence of a flare-up. Despite advances, in-depth knowledge of how the gut microbiota interacts with the intestinal mucosa and alters the intestinal barrier and the molecular/genetic mechanism is still unknown. Some genes and associated cofactors have been identified but the exact mechanism of interaction has not yet been described. The data indicate that, presumably, the mechanism of regulation is a multifactorial process.
In this way, a deep understanding of gut microbiota and its interactions with the host and the colon will be of great interest, in order to shape the future of IBD treatment, especially of UC. Thus, IBD patients' intestinal microbiota could be either a therapeutic target itself (fecal transplantation) or be consider as an adjustable adjuvant with immunomodulators The group of anti-TNF drugs are the most recently incorporated in the therapeutic arsenal of UC, in some cases changing the natural curse of the disease. However, it is still unknown how these drugs modulate the intestinal microbiota and how they interfere with it, although, probably, they develop a role. Recent results from studies by our group, indicate that on entering clinical remission, gut microbiota is modified to patterns less related with dysbiosis. Given the increasing importance of the use of anti-TNF drugs, it is of great interest to discriminate between the patterns associated with dysbiosis and those related with healthy mucosa, and how they are modified as a result of the use of anti-TNF drugs. In this way, previous results of our group analyzing the changes of intestinal microbiota associated with Adalimumab anti-TNF drug treatment have shown that during the progression of the patient into remission, the mucosal dysbiosis pattern changes. On the other hand, our group has also observed that after drug treatment failure, the gut microbiota returns to a pattern closer to dysbiosis. For that reason, gut microbiota could be considered as an excellent indicator of the real drug effectiveness in the patient.
Regarding Golimumab, a recently introduced anti-TNF drug therapy in UC, it is still unknown how it is able to modulate the intestinal microbiota to remission-related patterns, since to date there are not available studies about the relationship between Golimumab and this phenomenon.
The use of prebiotics and probiotics has shown some effectiveness as adjuvants in the treatment of UC . For that reason, further characterization of the gut microbiota patterns is very important to develop new strategies for adjuvant ability to modulate it, especially in patients receiving anti-TNF drugs and do not achieve complete remission. Similarly to recent studies, we suggest that the modulation of gut microbiota could optimize the response outcomes in patients treated with Golimumab.
In conclusion, based on current trends in the literature, we suggest that modulation of the intestinal microbiota and the characterization of remission-related patterns, will have a huge impact on the management of patients with UC. Moreover, the modulation of gut microbiota together with the anti-TNF drug effectiveness could be the most promising field in the management of inflammatory bowel disease.
-
HYPOTHESIS AND OBJECTIVES 2.1 Hypothesis
-
Intestinal microbiota profile change according to UC activity.
-
The Intestinal microbiota profile correlated to clinical remission is represented by stable intestinal microbiota biodiversity.
-
Assess if Intestinal Microbiota is a useful tool to measure Golimumab effectiveness in patients naïve to anti-TNF treatment and patients recurrent to anti-TNF treatment.
2.2 Objectives
-
To correlate clinical remission under Golimumab treatment with normal intestinal microbiota profile biodiversity
-
To characterize the pattern of intestinal microbiota associated with the use of Golimumab and temporal dynamics of microbial change.
-
Assess the effect of golimumab on the degree of colic dysbiosis in the treatment of Ulcerative Colitis naive to Golimumab.
-
MATERIAL AND METHODS 3.1 Type of study/design Multicenter transversal pilot Study 3.2 Study population The proposed study will include 15 UC anti-TNF naïve patients from Hospital Universitari Dr. Josep Trueta. Investigators will consider remission when patients have an endoscopic Mayo score ≤1, and activity index score, Mayo= 0 points.
3.3 Interventions NOTE: "The assignment of a patient to a particular therapeutic strategy is not predetermined in advance by the study protocol, instead clinical practice. Plus, the decision to prescribe a particular drug is clearly unlinked from the decision to include the patient in the study. Patients will not undergo any intervention, whether diagnostic or monitoring, other than the usual clinical practice, and epidemiological methods shall be used for the analysis of the data collected"
3.3.1 Treatments GOLIMUMAB induction with 200mg at week 0, and 100mg at week 2. Under 80kg, the follow up treatment will be 50mg/month, and 100mg/month in patients over 80kg, as clinical practice.
3.4 Variables 3.4.1 Demographic variables
-
Age expressed in years (y)
-
Sex Male (M)/ Female (F)
-
Body Mass Index
-
Ethnic: Caucasian/ African/ Asiatic/ American
-
Tobacco: YES / NO / EX-Smoker
-
Age of UC diagnosis expressed in years (y)
-
Familiar Antecedents (YES/NO) which kind of disease?
-
Localization Left (L)/ Righ (R) / extended (E) 3.4.2 Clinical variables
-
Mayo clinic score (Clinical colitis activity index) (Schroeder KW et al. NEngl J Med 1987; 317: 1625-9). Score range: 0-9 points
-
CRP (C-reactive protein): blood C-reactive protein concentration (mg/L)
-
Faecal calprotectin: stool sample expressed in concentration of calprotectin in ug for g of feces (ug/g)
-
Standard Analysis:
Hemoglobin: blood hemoglobin concentration (g / dl) Platelets: blood platelets concentration (x103/ ul) Leucocytes: blood leucocytes concentration (x103/ ul) Albumin: blood albumin concentration (g / dl) Creatinine levels: blood creatinine concentration (mg/ dl) 3.4.3 Endoscopic variables • Mayo (Endoscopic score of Ulcerative Colitis) (Schroeder KW et al. 1987). Mayo Endoscopic Score is based only on Endoscopic Findings. Mayo Score range from 0 to 3.
o Note: Investigators will send the image to a centralized digital platform, where Mayo score will be assessed by 2 independent professionals in order to minimize inter-observer bias.
3.4.4 Microbiological variables
-
Operational Taxonomic Units (OTUs)
-
Abundance and bacterial load. 3.5 Methods The proposed study will include 15 UC patients over 18 years with informed consent signed, under treatment with anti-TNF according to clinical practice. All of them will have been screened for opportunistic infections. Patients will be anti-TNF naïve patients.
Stool samples will be collected before starting Anti-TNF treatment (A), and at weeks 4 (B), 9 (C), 13 (D), 26 (E), 39 (F), and 52 (G) to complete the study. The monitoring period will be one year. Investigators will collect demographic variables (age, sex, tobacco, age of diagnosis, localization,…), clinical data (partial Mayo clinical score, CRP, albumin, hemoglobin, creatinine, leucocytes, platelets…), and microbiological variables at A, B, C, D, E, F and G. Also, 7 calprotectin sampling (at weeks 4 (B), 9 (C), 13 (D), 26 (E), 39 (F), and 52 (G) as a clinical practice) and Mayo endoscopic index (at baseline and at the end of the monitoring period as a clinical practice). Follow-up visits will also take place within routine clinical practice. For better follow-up the evolution of the patient, investigators will perform additional tests included in routine clinical practice as a rectosigmoidoscopy at week 12 after starting Anti-TNF treatment.
Investigators will consider remission when patients have an endoscopic Mayo score ≤1, and activity index score, Mayo clinical score =0 points.
Moreover, depending on the evolution of the patient, additional tests will also be performed as routine clinical protocol during the monitoring period.
NOTE: Any test performed during the study and / or additional testing is routine clinical practice according to clinical judgment and criteria of the physician.
3.5.1 Sample processing
DNA Extraction:
Before microbiological analyses, genomic DNA of 16s RNA gene will be extracted using NucleoSpin® Soil Kit (Machery-Nagel GmbH & Co., Germany). DNA concentration will be determined with Qubit® BR (Invitrogen) Kit.
Bacterial 16S rRNA Gene Amplification by Pyrosequencing For pyrosequencing purposes, the 16S rRNA gene was partially amplified from extracted genomic DNA using the universal bacterial primers GC-357F 5'- CGCCCG CCGCGCCCCGCGCCCGGCCCGCCGCCCCCGCCC- CCT ACG GGA GGC AGC AG-3' (341Y357) and 907R 5'-CCG TCA ATT CCT TTG AGT TT-3' (907Y926). PCR was performed with a GeneAmp PCR System ® 2700 (AppliedBiosystems)). Then we purify the PCR product with kit Ampure (Agencourt AMPure, Beckman Coulter Inc), and quantify the PCR products with Qubit® BR (Invitrogen) Kit. The pyrosequencing will be performed with a 454 Life Genome Sciences Sequencer FLX.
Sequence Editing and Analysis High-quality consensus sequences will be obtained and manually refined with the Bioedit software package. Alignments were carried out with ClustalW24 software. Consensus sequences were compared with those in GenBank and the Ribosomal Database Project by using BLASTN 2.2.10. Sequences will be grouped by number of operational taxonomic units or phylotypes with the DOTUR program26 using the farthest neighbor method at a precision level of 0.01, i.e., 99% minimum similarity for any pair of sequences to belong to the same phylotype, on a distance matrix with the Jukes-Cantor correction calculated with the DNADIST program of the Phylip software package.
3.6 Statistical analysis Statistical analysis will be performed with the SPSSx version 11.0. Significance of distances between groups was checked using an analysis of variance. Pearson_s x2 test was used to compare the prevalence of genus and species.
Clinical and laboratory data will be correlated with the values of quantitative microbial indices using Receiver Operating Characteristic (ROC) curves.
Study Design
Arms and Interventions
| Arm | Intervention/Treatment |
|---|---|
| Ulcerative Colitis The proposed study will include 15 UC anti-TNF naïve patients . We will consider remission when patients have an endoscopic Mayo score ≤1, and activity index score, Mayo= 0 points. Stool samples will be collected before starting Anti-TNF treatment (M0), and then every 3 months (M1, M2, M3 and M4) to complete the study. GOLIMUMAB induction with 200mg at week 0, and 100mg at week 2. Under 70kg, the follow up treatment will be 50mg/month, and 100mg/month in patients over 70kg, as clinical practice. |
Drug: Golimumab
The treatment followed was an induction of 200 mg of Golimumab at week 0, and 100 mg at week 2. Under 70 Kg, the follow-up treatment dose would be 50 mg/month, and 100 mg/month in patients above 70 Kg asindicated in standard clinical practice.
|
Outcome Measures
Primary Outcome Measures
- Golimumab Induced Shifts in the Abundance of Bacterial Markers [Baseline (week 0); week 4; week 9; week 13; week 26; week 39; week 52]
Shifts of abundance of Eubacteria (EUB), A. municiphila (AKK), M. smithii (MSM), Bacteroidetes (BAC), Ruminococcus sp. (RUM), F. prausnitzii (FPRA) and E. coli (ECO) levels will be measured prior (week 0) and progressively all through golimumab therapy until week 54. Results will be expressed as 16S gene copies of microbes per gram of faeces.
Secondary Outcome Measures
- Golimumab Induced Shifts in Calprotectin Faecal Sample Levels [Baseline (week 0); week 4; week 9; week 13; week 26; week 39; week 52]
Shifts on calprotectin levels will be measured prior (week 0) and progressively all through golimumab therapy until week 52. Results will be expressed as microgram of calprotectin per gram of faeces
- Golimumab Induced Shifts in Clinical Response Based on Partial Mayo Score [Baseline (week 0) and week 52]
Change from baseline (week 0) in the Partial Mayo score at week 52 of Golimumab treatment. The clinical Mayo Score or partial Mayo Score (PMS) uses the three non-invasive components of the full Mayo Score (stool frequency, rectal bleeding and physician's global assessement), and thus excluding the endoscopic findings scoring. Maximum score values range from 0 to 9 [Schroeder et al 2005 NEJM; Rutgeerts et al 2005 NEJM]. Calculations are based on the sum of scores for the three parameters. Values ranging: <2, disease in clinical remission; 2-4, mild activity; 5-7, moderate activity; and >7 severe activity.
Eligibility Criteria
Criteria
Inclusion Criteria:
-
18 years
-
Signed the informed consent
-
Anti-TNF naïve
-
Screening for opportunistic infections
Exclusion Criteria:
-
Active tuberculosis or another chronic infections
-
Antibiotic treatment prior 1 month
-
Probiotics & Prebiotics
-
Gestation and lactation
-
Heart disfunction
-
Colectomy
Contacts and Locations
Locations
| Site | City | State | Country | Postal Code | |
|---|---|---|---|---|---|
| 1 | Hospital Doctor Josep Trueta | Girona | Catalonia | Spain | 17007 |
Sponsors and Collaborators
- Institut d'Investigació Biomèdica de Girona Dr. Josep Trueta
Investigators
- Principal Investigator: Xavier XA Aldeguer, Dr., Institut d'Investigació Biomèdica de Girona Dr. Josep Trueta
Study Documents (Full-Text)
More Information
Publications
None provided.- IISP 53713
Study Results
Participant Flow
| Recruitment Details | |
|---|---|
| Pre-assignment Detail |
| Arm/Group Title | Ulcerative Colitis |
|---|---|
| Arm/Group Description | A total of 15 patients were included in the study. Stool samples were collected before starting anti-TNFα treatment (A), 4 weeks (B), 2 months after (C), 3 months (D), 6 months (E), 9 months (F) and finally 1 year after starting treatment (G). The monitoring period was one year long. Patients were classified as responders (responders), responder after dose optimization of anti-TNF treatment (respond after dose optimization) and non-responders (non-responders). Two different statistical analyses were done: one considering the group of responders, responder after dose optimization and non-responders, and another statistical analysis considering a unique group of responder and responders after dose optimization versus non-responders. Due to the fact that there are only 2 non-responders and a minimum number of 3 individuals (n= 3) is required to perform statistics, these 2 samples have been doubled for analysis. |
| Period Title: Overall Study | |
| STARTED | 15 |
| COMPLETED | 15 |
| NOT COMPLETED | 0 |
Baseline Characteristics
| Arm/Group Title | Ulcerative Colitis |
|---|---|
| Arm/Group Description | The proposed study will include 15 UC anti-TNF naïve patients . We will consider remission when patients have an endoscopic Mayo score ≤1, and activity index score, Mayo= 0 points. Stool samples will be collected before starting Anti-TNF treatment (M0), and then every 3 months (M1, M2, M3 and M4) to complete the study. GOLIMUMAB induction with 200mg at week 0, and 100mg at week 2. Under 70kg, the follow up treatment will be 50mg/month, and 100mg/month in patients over 70kg, as clinical practice. Golimumab |
| Overall Participants | 15 |
| Overall faeces | 105 |
| Age (years) [Mean (Full Range) ] | |
| Mean (Full Range) [years] |
42
|
| Sex: Female, Male (Count of Participants) | |
| Female |
8
53.3%
|
| Male |
7
46.7%
|
| Race and Ethnicity Not Collected (Count of Participants) | |
| Abundance (16S gene copies per gram of faeces) [Mean (Standard Deviation) ] | |
| Total abundance of EUB 16S gene copies per gram of faeces |
44895329
(60712475)
|
| Total abundance of FPRA 16S gene copies per gram of faeces |
632588897
(973329718)
|
| Total abundance of ECO 16S gene copies per gram of faeces |
13920879614
(23430581289)
|
| Total abundance of PHG-I 16S gene copies per gram of faeces |
5595001683
(15764400311)
|
| Total abundance of PHG-II 16S gene copies per gram of faeces |
13444198425
(45637222044)
|
| Total abundance of AKK 16S gene copies per gram of faeces |
1137084734
(983517092)
|
| Total abundance of BAC 16S gene copies per gram of faeces |
72930687
(119110706)
|
| Total abundance of RUM 16S gene copies per gram of faeces |
266628585
(670089788)
|
| Total abundance of MSM 16S gene copies per gram of faeces |
1694557243
(2573008595)
|
| faecal calprotectin (microgram calprotectin per gram faeces) [Mean (Standard Deviation) ] | |
| Mean (Standard Deviation) [microgram calprotectin per gram faeces] |
959.52
(781.41)
|
Outcome Measures
| Title | Golimumab Induced Shifts in the Abundance of Bacterial Markers |
|---|---|
| Description | Shifts of abundance of Eubacteria (EUB), A. municiphila (AKK), M. smithii (MSM), Bacteroidetes (BAC), Ruminococcus sp. (RUM), F. prausnitzii (FPRA) and E. coli (ECO) levels will be measured prior (week 0) and progressively all through golimumab therapy until week 54. Results will be expressed as 16S gene copies of microbes per gram of faeces. |
| Time Frame | Baseline (week 0); week 4; week 9; week 13; week 26; week 39; week 52 |
Outcome Measure Data
| Analysis Population Description |
|---|
| [Not Specified] |
| Arm/Group Title | Ulcerative Colitis Baseline | Ulcerative Colitis Week 4 | Ulcerative Colitis Week 9 | Ulcerative Colitis Week 13 | Ulcerative Colitis Week 26 | Ulcerative Colitis Week 39 | Ulcerative Colitis Week 52 |
|---|---|---|---|---|---|---|---|
| Arm/Group Description | A total of 15 patients were included in the study. Stool samples were collected before starting anti-TNFα treatment (A). Patients were classified as responders (responders), responder after dose optimization of anti-TNF treatment (respond after dose optimization) and non-responders (non-responders). Two different statistical analyses were done: one considering the group of responders, responder after dose optimization and non-responders, and another statistical analysis considering a unique group of responder and responders after dose optimization versus non-responders. Due to the fact that there are only 2 non-responders and a minimum number of 3 individuals (n= 3) is required to perform statistics, these 2 samples have been doubled for analysis. | A total of 15 patients were included in the study. Stool samples were collected at week 4 after treatment (B). Patients were classified as responders (responders), responder after dose optimization of anti-TNF treatment (respond after dose optimization) and non-responders (non-responders). Two different statistical analyses were done: one considering the group of responders, responder after dose optimization and non-responders, and another statistical analysis considering a unique group of responder and responders after dose optimization versus non-responders. Due to the fact that there are only 2 non-responders and a minimum number of 3 individuals (n= 3) is required to perform statistics, these 2 samples have been doubled for analysis. | A total of 15 patients were included in the study. Stool samples were collected at week 9 after (C) starting treatment. Patients were classified as responders (responders), responder after dose optimization of anti-TNF treatment (respond after dose optimization) and non-responders (non-responders). Two different statistical analyses were done: one considering the group of responders, responder after dose optimization and non-responders, and another statistical analysis considering a unique group of responder and responders after dose optimization versus non-responders. Due to the fact that there are only 2 non-responders and a minimum number of 3 individuals (n= 3) is required to perform statistics, these 2 samples have been doubled for analysis. | A total of 15 patients were included in the study. Stool samples were collected at week 13 after starting treatment (D). Patients were classified as responders (responders), responder after dose optimization of anti-TNF treatment (respond after dose optimization) and non-responders (non-responders). Two different statistical analyses were done: one considering the group of responders, responder after dose optimization and non-responders, and another statistical analysis considering a unique group of responder and responders after dose optimization versus non-responders. Due to the fact that there are only 2 non-responders and a minimum number of 3 individuals (n= 3) is required to perform statistics, these 2 samples have been doubled for analysis. | A total of 15 patients were included in the study. Stool samples were collected at week 24 after starting treatment (E). Patients were classified as responders (responders), responder after dose optimization of anti-TNF treatment (respond after dose optimization) and non-responders (non-responders). Two different statistical analyses were done: one considering the group of responders, responder after dose optimization and non-responders, and another statistical analysis considering a unique group of responder and responders after dose optimization versus non-responders. Due to the fact that there are only 2 non-responders and a minimum number of 3 individuals (n= 3) is required to perform statistics, these 2 samples have been doubled for analysis. | A total of 15 patients were included in the study. Stool samples were collected at week 39 after starting treatment (F). Patients were classified as responders (responders), responder after dose optimization of anti-TNF treatment (respond after dose optimization) and non-responders (non-responders). Two different statistical analyses were done: one considering the group of responders, responder after dose optimization and non-responders, and another statistical analysis considering a unique group of responder and responders after dose optimization versus non-responders. Due to the fact that there are only 2 non-responders and a minimum number of 3 individuals (n= 3) is required to perform statistics, these 2 samples have been doubled for analysis. | A total of 15 patients were included in the study. Stool samples were collected at week 52 after starting treatment. Patients were classified as responders (responders), responder after dose optimization of anti-TNF treatment (respond after dose optimization) and non-responders (non-responders). Two different statistical analyses were done: one considering the group of responders, responder after dose optimization and non-responders, and another statistical analysis considering a unique group of responder and responders after dose optimization versus non-responders. Due to the fact that there are only 2 non-responders and a minimum number of 3 individuals (n= 3) is required to perform statistics, these 2 samples have been doubled for analysis. |
| Measure Participants | 15 | 15 | 15 | 15 | 15 | 15 | 15 |
| 16S EUB gene copies/gr |
14965109899
(20237491739)
|
132857054401767
(113260468624418)
|
12779328208
(9068076455)
|
12851286145
(9017866924)
|
12454690659
(12454690659854)
|
12503490379
(8532885467)
|
12813434576
(10526337966)
|
| 16S FPRA gene copies/gr |
175719138207
(270369366223)
|
170223467854756
(236215626215223)
|
155540451664
(189790530774)
|
156132981396
(89588898844)
|
147240545450
(178731186533)
|
147465572493
(178661245731)
|
147013558563
(220645931988)
|
| 16S ECO gene copies/gr |
3314495146263
(5578709830918)
|
3181151220276
(3126128990251)
|
2987333503143
(3353864671731)
|
2953273068761
(3369672897008)
|
2670971592149
(3245749806014)
|
2676569979573
(3242227933303)
|
2862128876536
(3694099594126)
|
| 16S PHG-1 gene copies/gr |
1554167134258
(4379000086392)
|
2287342976506
(5800677622879)
|
1443246127037
(4465319951431)
|
1454728431339
(4462926477230)
|
1486551880693
(4369653984051)
|
1484947845315
(4370115404158)
|
2264764764378
(5588585629983)
|
| 16S PHG-2 gene copiese/gr |
3734499562508
(12677006123368)
|
4224010739381
(15618887473109)
|
2856262666851
(11831601059514)
|
2850757893262
(11832638079600)
|
3374769646848
(12473113644843)
|
3377322959435
(12472534823110)
|
4956971378048
(16148476082404)
|
| 16S AKK gene copies/gr |
631713741289
(546398384696)
|
676730972613383
(619061596613631)
|
648849626045
(560073798388)
|
656752409224
(555980667881)
|
631530294495
(541410081002)
|
624464830535
(541709460521)
|
588975881273
(573284067068)
|
| 16S RUM gene copies/gr |
177752390157
(446726525618)
|
875769282253977
(107172042366984)
|
94665231220
(103802651252)
|
89460668888
(98352969991)
|
175237205610
(443046731406)
|
140434420342
(366893347216)
|
183217036465
(470624954343)
|
| 16S MSM gene copies/gr |
1412131035956
(2144173829971)
|
1448338957715
(103802651252363)
|
1154472147552
(2014237593970)
|
1324144197647
(2030070772991)
|
1419822238221
(2125371379113)
|
1378914738249
(2079724959914)
|
1354846963287
(2528371614749)
|
| 16S BAC gene copies/gr |
24310229086
(39703568898)
|
1154472147552
(2014237593970)
|
25492065263
(41712078985)
|
25406506889
(41440365839)
|
24041089844
(39392492447)
|
24145355533
(39357796954)
|
26282792708
(45453286920)
|
| Title | Golimumab Induced Shifts in Calprotectin Faecal Sample Levels |
|---|---|
| Description | Shifts on calprotectin levels will be measured prior (week 0) and progressively all through golimumab therapy until week 52. Results will be expressed as microgram of calprotectin per gram of faeces |
| Time Frame | Baseline (week 0); week 4; week 9; week 13; week 26; week 39; week 52 |
Outcome Measure Data
| Analysis Population Description |
|---|
| [Not Specified] |
| Arm/Group Title | Ulcerative Colitis Baseline | Ulcerative Colitis Week 4 | Ulcerative Colitis Week 9 | Ulcerative Colitis Week 13 | Ulcerative Colitis Week 26 | Ulcerative Colitis Week 39 | Ulcerative Colitis Week 52 |
|---|---|---|---|---|---|---|---|
| Arm/Group Description | A total of 9 patients were included in the study. Stool samples were collected before starting anti-TNFα treatment (A). Patients were classified as responders (responders), responder after dose optimization of anti-TNF treatment (respond after dose optimization) and non-responders (non-responders). Two different statistical analyses were done: one considering the group of responders, responder after dose optimization and non-responders, and another statistical analysis considering a unique group of responder and responders after dose optimization versus non-responders. Due to the fact that there are only 2 non-responders and a minimum number of 3 individuals (n= 3) is required to perform statistics, these 2 samples have been doubled for analysis. | A total of 9 patients were included in the study. Stool samples were collected at week 4 after starting treatment (B). Patients were classified as responders (responders), responder after dose optimization of anti-TNF treatment (respond after dose optimization) and non-responders (non-responders). Two different statistical analyses were done: one considering the group of responders, responder after dose optimization and non-responders, and another statistical analysis considering a unique group of responder and responders after dose optimization versus non-responders. Due to the fact that there are only 2 non-responders and a minimum number of 3 individuals (n= 3) is required to perform statistics, these 2 samples have been doubled for analysis. | A total of 9 patients were included in the study. Stool samples were collected at week 9 after starting treatment (C). Patients were classified as responders (responders), responder after dose optimization of anti-TNF treatment (respond after dose optimization) and non-responders (non-responders). Two different statistical analyses were done: one considering the group of responders, responder after dose optimization and non-responders, and another statistical analysis considering a unique group of responder and responders after dose optimization versus non-responders. Due to the fact that there are only 2 non-responders and a minimum number of 3 individuals (n= 3) is required to perform statistics, these 2 samples have been doubled for analysis. | A total of 9 patients were included in the study. Stool samples were collected at week 13 after starting treatment (D). Patients were classified as responders (responders), responder after dose optimization of anti-TNF treatment (respond after dose optimization) and non-responders (non-responders). Two different statistical analyses were done: one considering the group of responders, responder after dose optimization and non-responders, and another statistical analysis considering a unique group of responder and responders after dose optimization versus non-responders. Due to the fact that there are only 2 non-responders and a minimum number of 3 individuals (n= 3) is required to perform statistics, these 2 samples have been doubled for analysis. | A total of 9 patients were included in the study. Stool samples were collected at week 26 after starting treatment (E). Patients were classified as responders (responders), responder after dose optimization of anti-TNF treatment (respond after dose optimization) and non-responders (non-responders). Two different statistical analyses were done: one considering the group of responders, responder after dose optimization and non-responders, and another statistical analysis considering a unique group of responder and responders after dose optimization versus non-responders. Due to the fact that there are only 2 non-responders and a minimum number of 3 individuals (n= 3) is required to perform statistics, these 2 samples have been doubled for analysis. | A total of 9 patients were included in the study. Stool samples were collected at week 39 after starting treatment (F). Patients were classified as responders (responders), responder after dose optimization of anti-TNF treatment (respond after dose optimization) and non-responders (non-responders). Two different statistical analyses were done: one considering the group of responders, responder after dose optimization and non-responders, and another statistical analysis considering a unique group of responder and responders after dose optimization versus non-responders. Due to the fact that there are only 2 non-responders and a minimum number of 3 individuals (n= 3) is required to perform statistics, these 2 samples have been doubled for analysis. | A total of 9 patients were included in the study. Stool samples were collected at week 52 after starting treatment (G). Patients were classified as responders (responders), responder after dose optimization of anti-TNF treatment (respond after dose optimization) and non-responders (non-responders). Two different statistical analyses were done: one considering the group of responders, responder after dose optimization and non-responders, and another statistical analysis considering a unique group of responder and responders after dose optimization versus non-responders. Due to the fact that there are only 2 non-responders and a minimum number of 3 individuals (n= 3) is required to perform statistics, these 2 samples have been doubled for analysis. |
| Measure Participants | 9 | 9 | 9 | 9 | 9 | 9 | 9 |
| Mean (Standard Deviation) [mg/g] |
1379.78
(761.52)
|
626.79
(800.30)
|
1267.50
(811.18)
|
1036.68
(883.24)
|
994.39
(714.60)
|
545.64
(635.46)
|
478.50
(881.02)
|
| Title | Golimumab Induced Shifts in Clinical Response Based on Partial Mayo Score |
|---|---|
| Description | Change from baseline (week 0) in the Partial Mayo score at week 52 of Golimumab treatment. The clinical Mayo Score or partial Mayo Score (PMS) uses the three non-invasive components of the full Mayo Score (stool frequency, rectal bleeding and physician's global assessement), and thus excluding the endoscopic findings scoring. Maximum score values range from 0 to 9 [Schroeder et al 2005 NEJM; Rutgeerts et al 2005 NEJM]. Calculations are based on the sum of scores for the three parameters. Values ranging: <2, disease in clinical remission; 2-4, mild activity; 5-7, moderate activity; and >7 severe activity. |
| Time Frame | Baseline (week 0) and week 52 |
Outcome Measure Data
| Analysis Population Description |
|---|
| Baseline (week 0) and week 52 |
| Arm/Group Title | Partial Mayo Score Baseline | Partial Mayo Score at Week 52 |
|---|---|---|
| Arm/Group Description | A total of 15 patients were included in the study. Partial Mayo scores were collected from patients before starting Golimumab treatment (week 0) | A total of 15 patients were included in the study. Partial Mayo scores were collected from patients at week 52 (G) after starting Golimumab treatment. |
| Measure Participants | 15 | 15 |
| Patient 1 |
2
|
0
|
| Patient 2 |
9
|
5
|
| Patient 3 |
2
|
0
|
| Patient 4 |
0
|
0
|
| Patient 5 |
3
|
0
|
| Patient 6 |
6
|
0
|
| Patient 7 |
5
|
2
|
| Patient 8 |
7
|
0
|
| Patient 9 |
8
|
0
|
| Patient 10 |
2
|
1
|
| Patient 11 |
3
|
0
|
| Patient 12 |
2
|
5
|
| Patient 13 |
3
|
0
|
| Patient 14 |
3
|
1
|
| Patient 15 |
4
|
1
|
Adverse Events
| Time Frame | 1 year | |||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Adverse Event Reporting Description | not different to clinicaltrials.gov definitions | |||||||||||||
| Arm/Group Title | Ulcerative Colitis Baseline | Ulcerative Colitis Week 4 | Ulcerative Colitis Week 9 | Ulcerative Colitis Week 13 | Ulcerative Colitis Week 26 | Ulcerative Colitis Week 39 | Ulcerative Colitis Week 52 | |||||||
| Arm/Group Description | A total of 15 patients were included in the study. Stool samples were collected before starting anti-TNFα treatment (A). Patients were classified as responders (responders), responder after dose optimization of anti-TNF treatment (respond after dose optimization) and non-responders (non-responders). Two different statistical analyses were done: one considering the group of responders, responder after dose optimization and non-responders, and another statistical analysis considering a unique group of responder and responders after dose optimization versus non-responders. Due to the fact that there are only 2 non-responders and a minimum number of 3 individuals (n= 3) is required to perform statistics, these 2 samples have been doubled for analysis. | A total of 15 patients were included in the study. Stool samples were collected at week 4 after starting treatment (B). Patients were classified as responders (responders), responder after dose optimization of anti-TNF treatment (respond after dose optimization) and non-responders (non-responders). Two different statistical analyses were done: one considering the group of responders, responder after dose optimization and non-responders, and another statistical analysis considering a unique group of responder and responders after dose optimization versus non-responders. Due to the fact that there are only 2 non-responders and a minimum number of 3 individuals (n= 3) is required to perform statistics, these 2 samples have been doubled for analysis. | A total of 15 patients were included in the study. Stool samples were collected at week 8 after starting treatment (C). Patients were classified as responders (responders), responder after dose optimization of anti-TNF treatment (respond after dose optimization) and non-responders (non-responders). Two different statistical analyses were done: one considering the group of responders, responder after dose optimization and non-responders, and another statistical analysis considering a unique group of responder and responders after dose optimization versus non-responders. Due to the fact that there are only 2 non-responders and a minimum number of 3 individuals (n= 3) is required to perform statistics, these 2 samples have been doubled for analysis. | A total of 15 patients were included in the study. Stool samples were collected at week 13 after starting treatment (D). Patients were classified as responders (responders), responder after dose optimization of anti-TNF treatment (respond after dose optimization) and non-responders (non-responders). Two different statistical analyses were done: one considering the group of responders, responder after dose optimization and non-responders, and another statistical analysis considering a unique group of responder and responders after dose optimization versus non-responders. Due to the fact that there are only 2 non-responders and a minimum number of 3 individuals (n= 3) is required to perform statistics, these 2 samples have been doubled for analysis. | A total of 15 patients were included in the study. Stool samples were collected at week 26 after starting treatment (E). Patients were classified as responders (responders), responder after dose optimization of anti-TNF treatment (respond after dose optimization) and non-responders (non-responders). Two different statistical analyses were done: one considering the group of responders, responder after dose optimization and non-responders, and another statistical analysis considering a unique group of responder and responders after dose optimization versus non-responders. Due to the fact that there are only 2 non-responders and a minimum number of 3 individuals (n= 3) is required to perform statistics, these 2 samples have been doubled for analysis. | A total of 15 patients were included in the study. Stool samples were collected at week 39 after starting treatment (F). Patients were classified as responders (responders), responder after dose optimization of anti-TNF treatment (respond after dose optimization) and non-responders (non-responders). Two different statistical analyses were done: one considering the group of responders, responder after dose optimization and non-responders, and another statistical analysis considering a unique group of responder and responders after dose optimization versus non-responders. Due to the fact that there are only 2 non-responders and a minimum number of 3 individuals (n= 3) is required to perform statistics, these 2 samples have been doubled for analysis. | A total of 15 patients were included in the study. Stool samples were collected at week 52 after starting treatment (G). Patients were classified as responders (responders), responder after dose optimization of anti-TNF treatment (respond after dose optimization) and non-responders (non-responders). Two different statistical analyses were done: one considering the group of responders, responder after dose optimization and non-responders, and another statistical analysis considering a unique group of responder and responders after dose optimization versus non-responders. Due to the fact that there are only 2 non-responders and a minimum number of 3 individuals (n= 3) is required to perform statistics, these 2 samples have been doubled for analysis. | |||||||
All Cause Mortality |
||||||||||||||
| Ulcerative Colitis Baseline | Ulcerative Colitis Week 4 | Ulcerative Colitis Week 9 | Ulcerative Colitis Week 13 | Ulcerative Colitis Week 26 | Ulcerative Colitis Week 39 | Ulcerative Colitis Week 52 | ||||||||
| Affected / at Risk (%) | # Events | Affected / at Risk (%) | # Events | Affected / at Risk (%) | # Events | Affected / at Risk (%) | # Events | Affected / at Risk (%) | # Events | Affected / at Risk (%) | # Events | Affected / at Risk (%) | # Events | |
| Total | 0/15 (0%) | 0/15 (0%) | 0/15 (0%) | 0/15 (0%) | 0/15 (0%) | 0/15 (0%) | 0/15 (0%) | |||||||
Serious Adverse Events |
||||||||||||||
| Ulcerative Colitis Baseline | Ulcerative Colitis Week 4 | Ulcerative Colitis Week 9 | Ulcerative Colitis Week 13 | Ulcerative Colitis Week 26 | Ulcerative Colitis Week 39 | Ulcerative Colitis Week 52 | ||||||||
| Affected / at Risk (%) | # Events | Affected / at Risk (%) | # Events | Affected / at Risk (%) | # Events | Affected / at Risk (%) | # Events | Affected / at Risk (%) | # Events | Affected / at Risk (%) | # Events | Affected / at Risk (%) | # Events | |
| Total | 0/15 (0%) | 0/15 (0%) | 0/15 (0%) | 0/15 (0%) | 0/15 (0%) | 0/15 (0%) | 0/15 (0%) | |||||||
Other (Not Including Serious) Adverse Events |
||||||||||||||
| Ulcerative Colitis Baseline | Ulcerative Colitis Week 4 | Ulcerative Colitis Week 9 | Ulcerative Colitis Week 13 | Ulcerative Colitis Week 26 | Ulcerative Colitis Week 39 | Ulcerative Colitis Week 52 | ||||||||
| Affected / at Risk (%) | # Events | Affected / at Risk (%) | # Events | Affected / at Risk (%) | # Events | Affected / at Risk (%) | # Events | Affected / at Risk (%) | # Events | Affected / at Risk (%) | # Events | Affected / at Risk (%) | # Events | |
| Total | 0/15 (0%) | 0/15 (0%) | 0/15 (0%) | 0/15 (0%) | 0/15 (0%) | 0/15 (0%) | 0/15 (0%) | |||||||
Limitations/Caveats
More Information
Certain Agreements
Principal Investigators are NOT employed by the organization sponsoring the study.
There is NOT an agreement between Principal Investigators and the Sponsor (or its agents) that restricts the PI's rights to discuss or publish trial results after the trial is completed.
Results Point of Contact
| Name/Title | MD PhD X Aldeguer |
|---|---|
| Organization | Institut d'Investigació Biomèdica de Girona - Hosp Univ Dr Josep Trueta |
| Phone | 34972940200 ext 2401 |
| xaldeguer.girona.ics@gencat.cat; abahi@idibgi.org |
- IISP 53713