Giant Cell Arteritis Clinical Trial
Official title:
ACR/EULAR Endorsed Study to Develop New Diagnostic and Classification Criteria for Primary Systemic Vasculitis
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.
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
;
Observational Model: Case Control, Time Perspective: Prospective
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