DCVAS: American College of Rheumatology/European League Against Rheumatism (ACR/EULAR) Diagnostic and Classification Criteria for Primary Systemic Vasculitis

Sponsor

University of Oxford (Other)

Overall Status

Unknown status

CT.gov ID

NCT01066208

Collaborator

American College of Rheumatology (Other), The European League Against Rheumatism (EULAR) (Other), The Vasculitis foundation (Other)

3,588

Enrollment

120

Locations

Duration (Months)

29.9

Patients Per Site

0.3

Patients Per Site Per Month

Study Details

Study Description

Brief Summary

Vasculitis is group of diseases where inflammation of blood vessels is the common feature. Patients typically present with fever, fatigue, weakness and muscle and joint aches. These symptoms are very common among many different diseases, not just vasculitis. A clustering of other symptoms, physical examination findings, blood tests, radiology and biopsy help make the diagnosis. There are currently no criteria to help doctors make a diagnosis of vasculitis when a patient presents with these non specific symptoms and they are reliant on previous experience and disease definitions. One of the aims of this project is to develop diagnostic criteria for the primary systemic vasculitides (granulomatosis with polyangiitis (Wegener's), microscopic polyangiitis, Churg Strauss syndrome, polyarteritis nodosa, giant cell arteritis, Takayasu arteritis). We, the investigators, will do this by studying a large group of patients with vasculitis and comparing them to a large group of patients that present in a similar way, but do not have vasculitis. By comparing the 2 groups we will create a list of items to differentiate between vasculitis and 'vasculitis mimics'.

We also aim to update the current classification criteria. Classification criteria are used to group patients into different types of vasculitis, once a diagnosis of vasculitis has been made, and are useful for studying patients in clinical trials with similar or identical diseases. The current classification criteria (American college of Rheumatology 1990 criteria) were developed 20 years ago, before the availability of some important diagnostic tests (e.g. antineutrophil cytoplasmic antibodies [ANCA]), and are now not consistent with some of the current disease definitions. Therefore to progress future research in vasculitis, it is important that the classification criteria are updated. We will recruit 260 patients with each of the 6 types of vasculitis and compare them with 1300 controls (patients with the 5 other types of vasculitis), in order to determine the optimal combination of symptoms, signs and investigations that classify each person into the appropriate group.

Condition or Disease	Intervention/Treatment	Phase
Wegener's Granulomatosis Microscopic Polyangiitis Churg Strauss Syndrome Polyarteritis Nodosa Giant Cell Arteritis Takayasu Arteritis

Detailed Description

The systemic vasculitides are a group of uncommon but important diseases whose prognosis has improved dramatically with the use of immunosuppressive therapy. However, long-term morbidity from recurrent disease flares, low-grade grumbling disease and/or accumulating damage from previous disease activity or drug therapy now characterise the long-term outlook for patients with vasculitis. There remains major controversy, and incompatibility between the ANCA-associated vasculitides: granulomatosis with polyangiitis (Wegener's), microscopic polyangiitis, and Churg Strauss Syndrome, as well as polyarteritis nodosa in the current classification criteria and disease definitions. Importantly, there are no diagnostic criteria for any of the primary systemic vasculitides.

We propose to improve existing classification criteria for the primary systemic vasculitides. As a starting point will include the following diseases: granulomatosis with polyangiitis (Wegener's) (GPA), microscopic polyangiitis (MPA), Churg Strauss syndrome (CSS), polyarteritis nodosa (PAN), giant cell arteritis (GCA) and Takayasu arteritis (TAK).

We propose to develop and validate classification and diagnostic criteria for primary systemic vasculitis using the guidelines suggested by the Classification and Response Criteria Subcommittee of the American College of Rheumatology Committee on Quality Measures. For all patients, a detailed medical history, physical examination, laboratory tests (including ANCA), radiology (including angiography), biopsy results, treatment, Birmingham Vasculitis Activity Score (BVAS)version 3, Vasculitis Damage Index (VDI), will be collected. The exact list of items to be recorded will be determined by the expert panel at the start of the study.

Classification criteria

We will study a minimum of 100 patients (new and existing patients) prospectively within each currently defined disease category (GPA, CSS, MPA, PAN, GCA, TAK) for the development of the classification criteria. We anticipate the need to recruit 130 patients to account for misdiagnosis and dropout to achieve the target of 100 with the confirmed reference diagnosis. This will include patients that have vasculitis which are assumed to be related to ANCA but do not fulfil the current definitions of any of the diseases, and patients with large vessel vasculitis which do not fulfil current definition for GCA or TAK. Therefore new categories of disease may be created as part of this process and some of the current disease categories may be changed to include or exclude certain patients.

The other diseases will be the controls. The same minimum number of patients will be used to validate the criteria. The 1st 100 patients with a formal reference diagnosis that are recruited for each disease will be used for development of the classification criteria; the next 100 consecutive patients recruited with a confirmed reference diagnosis for each disease will be used to validate the criteria. Again we anticipate the need to recruit 130 patients to account for misdiagnosis and dropout to achieve the 100 target. The majority of cases included will be the same as that used for the development of the diagnostic criteria.

In the absence of an established gold standard, we propose to develop a reference standard. Clinical vignettes using clustering of clinical features and investigations will be constructed from actual cases by the steering group. An expert panel will then be asked to classify each vignette. Hypothetical changes will then be made to components of each clinical vignette and the expert panel will be asked to re classify the case. This process will be repeated multiple times in an attempt to determine what key clinical feature influence the expert panel to change the diagnosis. Using this data driven process, a construct of important clinical features for each disease will be determined by the expert panel. Using this new construct, patients will be classified by the expert panel. This will form the reference standard against which the new criteria will be tested.

Diagnostic Criteria

We propose to develop and validate diagnostic criteria for primary systemic vasculitis. Based on current disease categories we will include GPA, MPA, CSS, PAN, GCA and TAK (but this may change depending on whether new categories are created or existing categories merged as part of the classification criteria component). For the development of diagnostic criteria, we will study a minimum of 100 patients (will require approx 130 patients to allow for dropout and misdiagnosis) for each disease category. Assuming 6 disease categories, the majority of these 780 patients will have already been identified from the classification criteria component of the study and will be re used for the development and validation of diagnostic criteria. However, for the diagnostic criteria to be clinically relevant we will only include patients that are seen at the time of 1st presentation, therefore not all the 780 patients recruited for the classification criteria section of the study will be suitable, and we will need to recruit additional new patients for each of the types of vasculitis being studied.

We will use a minimum of 400 context specific controls (patients that don't have vasculitis) for AAV and PAN that will cover the spectrum of different disease presentations and severity. In addition, we will recruit a minimum of 100 context specific controls for GCA and a similar number for TAK. Different control populations are needed for AAV, GCA and TAK as they have significantly different clinical presentations. In a similar manner to cases, we will recruit 30% more patients than the minimum required to account for misdiagnosis and drop out. The same minimum number of cases and controls will be needed to validate the criteria. The first half of the patients recruited would be used to develop the criteria, and the 2nd half to validate the criteria. We will allow inclusion of patients from previously studied prospective cohorts that meet all the appropriate inclusion / exclusion criteria and have had all the appropriate clinical information and mandatory investigation (to be defined later) recorded at time of their first presentation. This is to facilitate the recruitment of sufficient patients with PAN, CSS and TAK which are rare conditions.

Statistical analysis

We will follow the ACR recommended statistical methods for creating the classification criteria. Patients will have been classified into the different types of vasculitis according to the proposed EULAR/ACR schema by the expert panel or as a vasculitis mimic. The outcomes of interest are binary variables indicating whether or not a patient has been classified as having a particular type of vasculitis, such as GPA, MPA, etc. For each outcome, multivariable logistic regression modeling will be used to identify predictors of outcome based on the list of potential predictor variables described earlier. We will also explore the use of Classification And Regression Tree (CART) analysis. This is a tree-building technique ideally suited to the generation of clinical decision rules. Unlike conventional regression methods, patients are partitioned ("split") into different groups based on an exhaustive search of all possible predictor variables. The advantage of CART analysis over conventional methods is that it is non-parametric, so no assumptions are made about the underlying distribution of predictor variables. CART can handle many hundreds of possible predictor variables and can uncover complex interactions between predictors which may be difficult or impossible to uncover using traditional multivariate techniques that can suffer from model over fitting. In addition, clinicians generally do not think in terms of probability but rather in terms of categories, such as low versus high risk. Clinical decision rules generated using CART analysis are more likely to make clinical sense, and hence more likely to be followed in clinical practice.

Once the best items are identified, the expert panel will decide on the best short list of items to be included in each criteria and also choose the most appropriate decision tree. This will provide the best content validity.

The statistical methods to be used for diagnostic criteria will be very similar to that used for the classification criteria. The binary outcome for analysis is whether the person is a case or control (without vasculitis). We repeat the analyses for each of each type of vasculitis e.g. WG versus controls, then CSS versus controls etc

Study Design

Study Type:

Observational

Anticipated Enrollment :

3588 participants

Observational Model:

Case-Control

Time Perspective:

Prospective

Official Title:

ACR/EULAR Endorsed Study to Develop New Diagnostic and Classification Criteria for Primary Systemic Vasculitis

Study Start Date :

Jan 1, 2011

Anticipated Primary Completion Date :

Dec 1, 2017

Anticipated Study Completion Date :

Dec 1, 2018

Arms and Interventions

Arm	Intervention/Treatment
WG classification Patients with Wegener's granulomatosis. 1st half of these patients will be assigned to the development cohort and the second half to the validation cohort. Classification criteria.
MPA classification Patients with microscopic polyangiitis. 1st half of these patients will be assigned to the development cohort and the second half to the validation cohort. Classification criteria.
CSS classification Patients with Churg Strauss syndrome. 1st half of these patients will be assigned to the development cohort and the second half to the validation cohort. Classification criteria.
PAN classification Patients with polyarteritis nodosa. 1st half of these patients will be assigned to the development cohort and the second half to the validation cohort. Classification criteria.
Control Classification For each of the diseases being evaluated (WG, MPA, CSS, PAN, GCA, TAK), patients with the other 5 diseases will be the control group. Within these groups, 1st half of these patients will be assigned to the development cohort and the second half to the validation cohort. Classification criteria.
WG diagnostic Patients with a new presentation of Wegener's granulomatosis. 1st half of these patients will be assigned to the development cohort and the second half to the validation cohort. Diagnostic criteria.
MPA diagnostic Patients with a new presentation of microscopic polyangiitis. 1st half of these patients will be assigned to the development cohort and the second half to the validation cohort. Diagnostic criteria.
CSS diagnostic Patients with a new presentation of Churg Strauss syndrome. 1st half of these patients will be assigned to the development cohort and the second half to the validation cohort. Diagnostic criteria.
PAN diagnostic Patients with a new presentation of polyarteritis nodosa. 1st half of these patients will be assigned to the development cohort and the second half to the validation cohort. Diagnostic criteria.
Control diagnostic Patients without vasculitis, but presenting with similar features to the 6 different types of vasculitis being studied. 1st half of these patients will be assigned to the development cohort and the second half to the validation cohort. Diagnostic criteria.
GCA classification Patients with giant cell arteritis. 1st half of these patients will be assigned to the development cohort and the second half to the validation cohort. Classification criteria.
TAK classification Patients with Takayasu arteritis. 1st half of these patients will be assigned to the development cohort and the second half to the validation cohort. Classification criteria.
GCA diagnostic Patients with a new diagnosis of giant cell arteritis. 1st half of these patients will be assigned to the development cohort and the second half to the validation cohort. Diagnostic criteria.
TAK diagnostic Patients with a new diagnosis of Takayasu arteritis. 1st half of these patients will be assigned to the development cohort and the second half to the validation cohort. Diagnostic criteria.

Outcome Measures

Primary Outcome Measures

Develop new diagnostic and classification criteria for ANCA associated vasculitis and polyarteritis nodosa [3 years]

Eligibility Criteria

Criteria

Ages Eligible for Study:

18 Years and Older

Sexes Eligible for Study:

All

Accepts Healthy Volunteers:

Inclusion Criteria for Classification criteria:

Adult patients aged >18 years. There is no upper age limit.
Ability to give informed consent. If the patient is unable to give informed consent as a result of death or physical incapacity, then informed assent from next of kin.
Presumed diagnosis of a primary systemic vasculitis.

Exclusion criteria for classification criteria:

Patients < 18 years of age.
Inability to provide informed consent.
Hepatitis B or C
Co-morbidities that explain the clinical symptoms and signs on which the diagnosis of vasculitis is made. E.g. infection, tumour, other inflammatory condition, etc.

Inclusion criteria for diagnostic criteria:

Adult patients aged >18 years. There is no upper age limit.
Ability to give informed consent. If the patient is unable to give informed consent as a result of death or physical incapacity, then informed assent from next of kin.
Suspected diagnosis of a primary systemic vasculitis

Inclusion criteria for controls group for diagnostic criteria:

Adult patients aged >18 years. There is no upper age limit.
Ability to give informed consent. If the patient is unable to give informed consent as a result of death or physical incapacity, then informed assent from next of kin.
Patients presenting to secondary care with one of the following clinical presentations: I.Multi-system disease. Presentation of disease with at least 2 organs involved. II.Pulmonary-renal syndrome. Defined as haemoptysis / pulmonary haemorrhage with acute renal impairment. III.Acute renal failure IV.Acute respiratory distress. V.Chronic upper airways symptoms and signs. VI.Inflammatory polyarthritis. VII.Fever of unknown origin. VIII.Acute or chronic abdominal pain IX.Hypertension. X.Referred to secondary care with suspicion of vasculitis but confirmed not to have vasculitis. XII.New onset headache. XIII.Jaw or tongue pain. XIV.Sudden visual loss. XV.Limb claudication. XVI.Aortic aneurysm >5cm.

Exclusion Criteria for diagnostic criteria:

Patients under the age of 18
Patient or next of kin unable or unwilling to provide informed consent or assent.

Contacts and Locations

Locations

	Site	City	State	Country	Postal Code
1	University of Alabama at Birmingham	Birmingham	Alabama	United States	35233
2	Cedars-Sinai Medical Center, LA	Los Angeles	California	United States	90048
3	University of California, San Francisco	San Francisco	California	United States	94143-0500
4	University of Maryland	Baltimore	Maryland	United States	21201
5	Vasculitis Center, Boston University School of Medicine	Boston	Massachusetts	United States	02118
6	University of Michigan, Internal Medicine	Ann Arbor	Michigan	United States	48109
7	Mayo Clinic	Rochester	Minnesota	United States	55905
8	Dartmouth-Hitchcock Medical Centre, Lebanon, NH	Lebanon	New Hampshire	United States	03756
9	New York University Langone Medical Centre	New York	New York	United States	10016
10	University of North Carolina	Chapel Hill	North Carolina	United States	27599-7525
11	Cleveland Clinic	Cleveland	Ohio	United States	44195
12	University of Pennsylvania	Philadelphia	Pennsylvania	United States	19104
13	University of Pittsburgh	Pittsburgh	Pennsylvania	United States	15261
14	University Medical Center	Salt Lake City	Utah	United States	84132-0002
15	Hospital Interzonal San Juan Bautista	San Fernando del Valle de Catamarca	Catamarca	Argentina
16	Ramos Mejia Hospital, University of Buenos Aires	Buenos Aires		Argentina	C1221ADC
17	ANU Medical Centre	Canberra	Australian Capital Territory	Australia
18	Royal Brisbane and Women's Hospital	Herston	Queensland	Australia	4029
19	Medical University Innsbruck	Innsbruck		Austria
20	University Hospitals Leuven	Leuven		Belgium
21	University of Manitoba	Winnipeg	Manitoba	Canada	R3A 1M4
22	St Joseph's Healthcare	Hamilton	Ontario	Canada
23	University of Ottawa	Ottawa	Ontario	Canada	K1N 6N5
24	Mount Sinai Hospital, Toronto	Toronto	Ontario	Canada	ON M5T 2S8
25	McGill University	Montreal	Quebec	Canada	H3A 0G4
26	Sherbrooke University Hospital Centre	Sherbrooke	Quebec	Canada	J1H 5N4
27	University of Calgary	Calgary		Canada
28	St Joseph's Healthcare London, Ontario	Ontario		Canada
29	Peking Union Medical College Hospital, Beijing	Beijing		China	100032
30	General University Hospital, Prague	Prague		Czech Republic	128 08
31	General University Hospital	Prague		Czech Republic
32	Rigshospitalet	Copenhagen		Denmark
33	Assiut University, Assiut University Hospitals	Assiut		Egypt	71516
34	Cairo University, Kasr El Ainy Hospital	Cairo		Egypt
35	Helsinki University Central Hospital	Helsinki		Finland
36	Cochin Hospital, Université Paris-descartes	Paris		France	75679
37	Universitätsklinikum Jena	Jena		Germany	07743 Jena
38	University of Schleswig-Holstein	Luebeck		Germany
39	Universitätsklinikum Münster	Münster		Germany	48149
40	Kreiskliniken Esslingen	Plochingen		Germany	73207
41	University Hospital Tübingen	Tübingen		Germany	D-72076
42	University of Debrecen Medical and Health Science Center	Debrecen		Hungary	4032
43	Chatrapathi Shahuji Maharaj Medical Center, Lucknow (IProcess)	Lucknow	Uttar Pradesh	India	226003
44	Postgraduate Institute of Medical Education and Research, Chandigarh	Chandigarh		India	Pin- 160 012
45	Nizam's Institute of Medical Sciences, Hyderabad	Hyderabad		India	500082
46	Medanta, Delhi	New Delhi		India	110024
47	Christian Medical College & Hospital, Vellore	Vellore		India	632 004
48	Cork University Hospital	Cork		Ireland
49	St. Vincent's University Hospital, Dublin	Dublin 4		Ireland
50	University of Parma	Parma		Italy
51	Santa Maria Nuova Hospital, Reggio Emilia	Reggio Emilia		Italy	42123
52	Arcispedale Santa Maria Nuova	Reggio Emilia		Italy
53	Kameda Medical Centre, Kamogawa	Kamogawa City	Chiba prefecture	Japan	296-8602
54	Tsukuba University Hospital	Tsukuba	Ibaraki Prefecture	Japan	305-8576
55	Miyazaki University Hospital	Miyazaki City	Miyazaki Prefecture	Japan	889-1692
56	Saitama Medical University	Kawagoe	Saitama Prefecture	Japan	350-8550
57	Kyorin University Hospital	Mitaka	Tokyo Prefecture	Japan	181-8611
58	Chiba University	Chiba		Japan	260-8670
59	Kagawa University Hospital	Kagawa		Japan	761-0793
60	St. Marianna University Hospital	Kanagawa		Japan	216-8511
61	Kanazawa University Hospital	Kanazawa		Japan	920-8641
62	Okayama University Hospital	Okayama		Japan	700-8558
63	Kitano Hospital	Osaka		Japan
64	Juntendo University Koshigaya Hospital	Saitama		Japan	343-0032
65	Jichi Medical University Hospital	Tochigi-ken		Japan	3311-1 Yakushiji
66	University Tokyo Hospital	Tokyo		Japan	113-8655
67	Seoul National University Hospital	Seoul		Korea, Republic of	110-744
68	Instituto Nacional de Enfermedades Respiratorias	Mexico City		Mexico	14000
69	Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran	Mexico City		Mexico
70	VU University Medical Center	Amsterdam		Netherlands	6Z 165
71	University Medical Center Groningen	Groningen		Netherlands	30.001
72	University of Otago, Christchurch	Christchurch	Canterbury	New Zealand	8011
73	Auckland District Health Board	Auckland		New Zealand
74	Waitemata District Health Board, North Shore Hospital	Auckland		New Zealand
75	Waikato District Health Board	Hamilton		New Zealand	3240
76	Hospital of Southern Norway	Kristiansand		Norway	Post box 416, 4605
77	The University Hospital of Northern Norway, Tromsø	Tromsø		Norway	9038
78	University of Jagiellonian	Kraków		Poland	31-007
79	Hospital Garcia de Orta, Almada	Almada		Portugal
80	Santa Maria Hospital, Lisbon	Lisbon		Portugal	1649-035
81	Hospital Santo Antonio, Porto	Porto		Portugal	4099 - 001
82	First Moscow State Medical University	Moscow		Russian Federation	119991
83	University Medical Centre Ljubljana	Ljubljana		Slovenia	1000
84	Clinic Barcelona Hospital Universitari	Barcelona	Catalonia	Spain
85	University of Colombo	Columbo 8		Sri Lanka
86	Lund University	Lund		Sweden	SE-221 85
87	Karolinska Institute, Stockholm	Stockholm		Sweden	141 86
88	Linköping University	Stockholm		Sweden	581 83
89	Umeå University	Umeå		Sweden	901 85
90	Uppsala University Hospital	Uppsala		Sweden	751 85
91	University Hospital Basel	Basel		Switzerland	4031
92	Immunologie-Zentrum Zurich	Zurich		Switzerland
93	Hacettepe University	Ankara		Turkey
94	Istanbul University, Cerrahpasa Medical School	Istanbul		Turkey	34098
95	Marmara University Medical School	Istanbul		Turkey	34668
96	Fatih University Medical Faculty	Istanbul		Turkey	34844
97	Haydarpasa Education and Research Hospital	Istanbul		Turkey
98	Istanbul University, Istanbul Medical School	Istanbul		Turkey
99	North Cumbria University Hospitals, The Cumberland Infirmary	Carlisle	Cumbria	United Kingdom	CA2 7HY
100	Basildon and Thurrock University Hospitals NHS Foundation Trust	Basildon	Essex	United Kingdom	SS16 5NL
101	Queen's Hospital	Romford	Essex	United Kingdom	RM7 0AG
102	Southend University Hospital NHS Trust	Westcliff-on-Sea	Essex	United Kingdom	SS0 0RY
103	NHS Fife, Whyteman's Brae Hospital, Windygates	Kirkcaldy	Fife	United Kingdom	KY8 5PR
104	Aberdeen Royal Infirmary	Aberdeen	Scotland	United Kingdom	AB25 2ZN
105	NHS Greater Glasgow & Clyde, Gartnavel Hospital	Glasgow	Scotland	United Kingdom	G12 8TA
106	Ipswich Hospital NHS Trust	Ipswich	Suffolk	United Kingdom
107	Epsom and St Helier University Hospitals NHS Trust	Carshalton	Surrey	United Kingdom	SM5 1AA
108	University of Birmingham	Birmingham		United Kingdom
109	Addenbrooke's Hospital	Cambridge		United Kingdom
110	Dudley Group of Hospitals, NHS FT	Dudley		United Kingdom	DY1 2HQ
111	Imperial College Healthcare NHS Trust, Hammersmith Hospital	London		United Kingdom	W12 0HS
112	University of Manchester, Manchester Royal Infirmary	Manchester		United Kingdom	M13 9WL
113	Norfolk and Norwich University Hospital	Norwich		United Kingdom	NR4 7UY
114	Nottingham University Hospitals NHS Trust (QMC)	Nottingham		United Kingdom	NG7 2UH
115	Nuffield Orthopaedic Centre	Oxford		United Kingdom	OX3 7LD
116	Oxford University Hospitals NHS Trust (The Churchill Hospital)	Oxford		United Kingdom	OX3 7LE
117	Royal Berkshire NHS Trust	Reading		United Kingdom	RG1 5AN
118	Heatherwood & Wexham Park Hospitals NHS Foundation Trust	Slough		United Kingdom	SL2 4HL
119	Southampton University Hospitals NHS Trust	Southampton		United Kingdom	SO16 6YD
120	York Hospital NHS Foundation Trust	York		United Kingdom	YO31 8HE

Sponsors and Collaborators

University of Oxford
American College of Rheumatology
The European League Against Rheumatism (EULAR)
The Vasculitis foundation

Investigators

Principal Investigator: Raashid A Luqmani, DM, FRCP(E), University of Oxford, United Kingdom
Principal Investigator: Peter Merkel, MD, MPH, University of Pennsylvania
Principal Investigator: Richard Watts, DM, FRCP, University of East Anglia