Identification of connective tissue disease autoantibodies and a novel autoantibody anti-annexin A11 in patients with "idiopathic" interstitial lung disease.

BACKGROUND: Autoantibodies are a hallmark feature of Connective Tissue Diseases (CTD). Their presence in patients with idiopathic interstitial lung disease (ILD) may suggest covert CTD. We aimed to determine the prevalence of CTD autoantibodies in patients diagnosed with idiopathic ILD. METHODS: 499 patient sera were analysed: 251 idiopathic pulmonary fibrosis (IPF), 206 idiopathic non-specific interstitial pneumonia (iNSIP) and 42 cryptogenic organising pneumonia (COP). Autoantibody status was determined by immunoprecipitation. RESULTS: 2.4% of IPF sera had a CTD-autoantibody compared to 10.2% of iNSIP and 7.3% of COP. 45% of autoantibodies were anti-synthetases. A novel autoantibody targeting an unknown 56 kDa protein was found in seven IPF patients (2.8%) and two NSIP (1%) patients. This was characterised as anti-annexin A11. CONCLUSION: Specific guidance on autoantibody testing and interpretation in patients with ILD could improve diagnostic accuracy. Further work is required to determine the clinical significance of anti-annexin A11.

Effectiveness of sequential lines of biologic and targeted small-molecule drugs in psoriatic arthritis: a systematic review.

OBJECTIVE: To assess current evidence for effectiveness of sequential lines of biologic and targeted small-molecule disease-modifying anti-rheumatic drugs (b/tsDMARDs) when used beyond first-line for psoriatic arthritis (PsA). METHODS: A systematic search of the literature (Medline, Embase, bibliographic searches) was undertaken (October and December 2022) to find studies meeting the criteria of assessing effectiveness of b/tsDMARDs beyond first-line in adults with PsA (PROSPERO CRD42022365298). Risk of bias assessment was undertaken (ROBINS-I/Cochrane RoB2). RESULTS: Of 2666 abstracts identified and following a full text review of 177 psoriatic disease studies, 12 manuscripts and two abstracts were eligible. Of the 12 manuscripts, 11 were observational and one was a sub-analysis of a RCT (n = 16 081: average age 49.5 years, female 53.3%). Two abstracts (n = 7186) were included. All studies comparing first- and second-line (three studies) found a reduced response in second-line. On average, DAPSA remission (most reported outcome, eight studies) was achieved in 26%, 19% and 10% first-, second- and third-line TNFi, and 22%, 13% and 11% first-, second- and third-line other bDMARDs, respectively. Responses varied to third-line bDMARDs; four studies found comparable second- and third-line responses, five studies found diminishing responses in sequential lines. CONCLUSION: Predominantly observational studies, inherently at high risk of bias, indicate bDMARDs can be effective to third-line in PsA, but that response is reduced after first line. There is very limited data for more advanced lines of b/tsDMARD. Prospective studies are required to better understand clinical response to advanced lines of treatment in PsA.

The comparative performance of three screening questionnaires for psoriatic arthritis in a primary care surveillance study.

OBJECTIVES: The objective of this study was to compare the performance of three PsA screening questionnaires in a primary care psoriasis surveillance study. METHODS: Participants with psoriasis, and not known to have PsA, were identified from general practice databases and invited to attend a secondary care centre for a clinical assessment. The three patient-completed screening questionnaires (PEST, CONTEST and CONTESTjt) were administered, along with other patient-reported measures, and a clinical examination of skin and joints was performed. Participants who demonstrated signs of inflammatory arthritis suggestive of PsA were referred, via their GP, for a further assessment in a secondary care rheumatology clinic. RESULTS: A total of 791 participants attended the screening visit, and 165 participants were judged to have signs and symptoms of inflammatory arthritis, of which 150 were referred for assessment. Of these, 126 were seen and 48 were diagnosed with PsA. The results for each questionnaire were as follows: PEST: sensitivity 0.625 (95% CI 0.482, 0.749), specificity 0.757 (0.724, 0.787); CONTEST: sensitivity 0.604 (0.461, 0.731), specificity 0.768 (0.736, 0.798); and CONTESTjt: sensitivity 0.542 (0.401, 0.676), specificity 0.834 (0.805, 0.859). CONTESTjt demonstrated marginally superior specificity to PEST, though the area under the ROC curve was similar for all three instruments. CONCLUSION: Minimal differences between the three screening questionnaires were found in this study, and no preferred questionnaire is indicated by these results. The choice of which instrument to choose will depend on other factors, such as simplicity and low patient burden.

International Guideline for Idiopathic Inflammatory Myopathy-Associated Cancer Screening: an International Myositis Assessment and Clinical Studies Group (IMACS) initiative.

Adult-onset idiopathic inflammatory myopathy (IIM) is associated with an increased cancer risk within the 3 years preceding and following IIM onset. Evidence- and consensus-based recommendations for IIM-associated cancer screening can potentially improve outcomes. This International Guideline for IIM-Associated Cancer Screening provides recommendations addressing IIM-associated cancer risk stratification, cancer screening modalities and screening frequency. The international Expert Group formed a total of 18 recommendations via a modified Delphi approach using a series of online surveys. First, the recommendations enable an individual patient's IIM-associated cancer risk to be stratified into standard, moderate or high risk according to the IIM subtype, autoantibody status and clinical features. Second, the recommendations outline a 'basic' screening panel (including chest radiography and preliminary laboratory tests) and an 'enhanced' screening panel (including CT and tumour markers). Third, the recommendations advise on the timing and frequency of screening via basic and enhanced panels, according to risk status. The recommendations also advise consideration of upper or lower gastrointestinal endoscopy, nasoendoscopy and 18F-FDG PET-CT scanning in specific patient populations. These recommendations are aimed at facilitating earlier IIM-associated cancer detection, especially in those who are at a high risk, thus potentially improving outcomes, including survival.

Comparison of clinical features between patients with anti-synthetase syndrome and dermatomyositis: Results from the MYONET registry.

OBJECTIVES: To compare clinical characteristics, including the frequency of cutaneous, extramuscular manifestations, and malignancy, between adults with anti-synthetase syndrome (ASyS) and dermatomyositis (DM). METHODS: Using data regarding adults from the MYONET registry, a cohort of DM patients with anti-Mi2/-TIF1É£/-NXP2/-SAE/-MDA5 autoantibodies, and a cohort of ASyS patients with anti-tRNA synthetase autoantibodies (anti-Jo1/-PL7/-PL12/-OJ/-EJ/-Zo/-KS) were identified. Patients with DM sine dermatitis or with discordant dual autoantibody specificities were excluded. Sub-cohorts of patients with ASyS with or without skin involvement were defined based on presence of DM-type rashes (heliotrope rash, Gottron's papules/sign, violaceous rash, shawl sign, V sign, erythroderma, and/or periorbital rash). RESULTS: In total 1,054 patients were included (DM, n = 405; ASyS, n = 649). In ASyS cohort, 31% (n = 203) had DM-type skin involvement (ASyS-DMskin). A higher frequency of extramuscular manifestations, including Mechanic's hands, Raynaud's phenomenon, arthritis, interstitial lung disease, and cardiac involvement differentiated ASyS-DMskin from DM (all p< 0.001), whereas higher frequency of any of four DM-type rashes: heliotrope rash (n = 248, 61% vs n = 90, 44%), violaceous rash (n = 166, 41% vs n = 57, 9%), V sign (n = 124, 31% vs n = 28, 4%), and shawl sign (n = 133, 33% vs n = 18, 3%) differentiated DM from ASyS-DMskin (all p< 0.005). Cancer-associated myositis (CAM) was more frequent in DM (n = 67, 17%) compared with ASyS (n = 21, 3%) and ASyS-DMskin (n = 7, 3%) cohorts (both p< 0.001). CONCLUSION: DM-type rashes are frequent in patients with ASyS; however, distinct clinical manifestations differentiate these patients from classical DM. Skin involvement in ASyS does not necessitate increased malignancy surveillance. These findings will inform future ASyS classification criteria and patient management.

Comparative Genetic Analysis of Psoriatic Arthritis and Psoriasis for the Discovery of Genetic Risk Factors and Risk Prediction Modeling.

OBJECTIVES: Psoriatic arthritis (PsA) has a strong genetic component, and the identification of genetic risk factors could help identify the ~30% of psoriasis patients at high risk of developing PsA. Our objectives were to identify genetic risk factors and pathways that differentiate PsA from cutaneous-only psoriasis (PsC) and to evaluate the performance of PsA risk prediction models. METHODS: Genome-wide meta-analyses were conducted separately for 5,065 patients with PsA and 21,286 healthy controls and separately for 4,340 patients with PsA and 6,431 patients with PsC. The heritability of PsA was calculated as a single-nucleotide polymorphism (SNP)-based heritability estimate (h2 SNP ) and biologic pathways that differentiate PsA from PsC were identified using Priority Index software. The generalizability of previously published PsA risk prediction pipelines was explored, and a risk prediction model was developed with external validation. RESULTS: We identified a novel genome-wide significant susceptibility locus for the development of PsA on chromosome 22q11 (rs5754467; P = 1.61 × 10-9 ), and key pathways that differentiate PsA from PsC, including NF-κB signaling (adjusted P = 1.4 × 10-45 ) and Wnt signaling (adjusted P = 9.5 × 10-58 ). The heritability of PsA in this cohort was found to be moderate (h2 SNP = 0.63), which was similar to the heritability of PsC (h2 SNP = 0.61). We observed modest performance of published classification pipelines (maximum area under the curve 0.61), with similar performance of a risk model derived using the current data. CONCLUSION: Key biologic pathways associated with the development of PsA were identified, but the investigation of risk classification revealed modest utility in the available data sets, possibly because many of the PsC patients included in the present study were receiving treatments that are also effective in PsA. Future predictive models of PsA should be tested in PsC patients recruited from primary care.

Defining anti-synthetase syndrome: a systematic literature review.

OBJECTIVES: Anti-synthetase syndrome (ASSD) is a heterogeneous autoimmune disease characterised by multi-system involvement with a wide variety of manifestations. Validated classification criteria are necessary to improve recognition and prevent misclassification, especially given the lack of reliable and standardised autoantibody testing. We systematically reviewed the literature to analyse proposed ASSD criteria, characteristics, and diagnostic performance. METHODS: We searched PubMed and Embase databases (01/01/1984 to 06/11/2018) and the ACR and EULAR meeting abstracts (2017-2018). Sensitivities, specificities, positive, negative likelihood ratios and risk of bias were calculated for ASSD criteria and key variables reported in the literature. We performed meta-analysis when appropriate. RESULTS: We retrieved 4,358 studies. We found 85 proposed ASSD criteria from a total of 82 studies. All but one study included anti-synthetase autoantibody (ARS) positivity in the ASSD criteria. Most studies required only one ASSD feature plus anti-ARS to define ASSD (n=64, 78%), whereas 16 studies required more than one ASSD variable plus anti-ARS. The only criteria not including anti-ARS positivity required 5 ASSD clinical features. We found limited data and wide variability in the diagnostic performance of each variable and definition proposed in the literature. Given these limitations we only meta-analysed the performance of individual muscle biopsy and clinical variables in diagnosing ASSD, which performed poorly. CONCLUSIONS: The current ASSD criteria include a variety of serological, clinical, and histological features with wide variability amongst proposed definitions and the performance of these definitions has not been tested. This systematic literature review suggests the need for additional data and consensus-driven classification criteria for ASSD.

A Commercial Anti-TIF1γ ELISA Is Superior to Line and Dot Blot and Should Be Considered as Part of Routine Myositis-Specific Antibody Testing.

Objectives: Anti-TIF1γ is an important autoantibody in the diagnosis of cancer-associated dermatomyositis and the most common autoantibody in juvenile onset dermatomyositis. Its reliable detection is important to instigate further investigations into underlying malignancy in adults. We previously showed that commercial assays using line and dot blots do not reliably detect anti-TIF1γ. We aimed to test a new commercial ELISA and compare with previously obtained protein immunoprecipitation. Methods: Radio-labelled immunoprecipitation had previously been used to determine the autoantibody status of patients with immune-mediated inflammatory myopathies and several healthy controls. ELISA was undertaken on healthy control and anti-TIF1γ sera and compared to previous immunoprecipitation data. Results: A total of 110 serum samples were analysed: 42 myositis patients with anti- TIF1γ and 68 autoantibody negative healthy control sera. Anti-TIF1γ was detected by ELISA in 41 out of 42 of the anti-TIF1γ-positive samples by immunoprecipitation, and in none of the healthy controls, giving a sensitivity of 97.6% and specificity of 100%. The false negative rate was 2%. Conclusion: ELISA is an affordable and time-efficient method which is accurate in detecting anti-TIF1γ.

Using Bayesian networks to identify musculoskeletal symptoms influencing the risk of developing psoriatic arthritis in people with psoriasis.

OBJECTIVES: The aim of this study was to explore the use of Bayesian networks (BNs) to understand the relationships between musculoskeletal symptoms and the development of PsA in people with psoriasis. METHODS: Incident cases of psoriasis were identified for 1998 to 2015 from the UK Clinical Research Practice Datalink. Musculoskeletal symptoms (identified by Medcodes) were concatenated into primary groups, each made up of several subgroups. Baseline demographics for gender, age, BMI, psoriasis severity, alcohol use and smoking status were also extracted. Several BN structures were composed using a combination of expert knowledge and data-oriented modelling based on: (i) primary musculoskeletal symptom groups; (ii) musculoskeletal symptom subgroups and (iii) demographic variables. Predictive ability of the networks using the area under the receiver operating characteristic curve was calculated. RESULTS: Over one million musculoskeletal symptoms were extracted for the 90 189 incident cases of psoriasis identified, of which 1409 developed PsA. The BN analysis yielded direct relationships between gender, BMI, arthralgia, finger pain, fatigue, hand pain, hip pain, knee pain, swelling, back pain, myalgia and PsA. The best BN, achieved by using the more site-specific musculoskeletal symptom subgroups, was 76% accurate in predicting the development of PsA in a test set and had an area under the receiver operating characteristic curve of 0.73 (95% CI: 0.70, 0.75). CONCLUSION: The presented BN model may be a useful method to identify clusters of symptoms that predict the development of PsA with reasonable accuracy. Using a BN approach, we have shown that there are several symptoms which are predecessors of PsA, including fatigue, specific types of pain and swelling.

Application of information theoretic feature selection and machine learning methods for the development of genetic risk prediction models.

In view of the growth of clinical risk prediction models using genetic data, there is an increasing need for studies that use appropriate methods to select the optimum number of features from a large number of genetic variants with a high degree of redundancy between features due to linkage disequilibrium (LD). Filter feature selection methods based on information theoretic criteria, are well suited to this challenge and will identify a subset of the original variables that should result in more accurate prediction. However, data collected from cohort studies are often high-dimensional genetic data with potential confounders presenting challenges to feature selection and risk prediction machine learning models. Patients with psoriasis are at high risk of developing a chronic arthritis known as psoriatic arthritis (PsA). The prevalence of PsA in this patient group can be up to 30% and the identification of high risk patients represents an important clinical research which would allow early intervention and a reduction of disability. This also provides us with an ideal scenario for the development of clinical risk prediction models and an opportunity to explore the application of information theoretic criteria methods. In this study, we developed the feature selection and psoriatic arthritis (PsA) risk prediction models that were applied to a cross-sectional genetic dataset of 1462 PsA cases and 1132 cutaneous-only psoriasis (PsC) cases using 2-digit HLA alleles imputed using the SNP2HLA algorithm. We also developed stratification method to mitigate the impact of potential confounder features and illustrate that confounding features impact the feature selection. The mitigated dataset was used in training of seven supervised algorithms. 80% of data was randomly used for training of seven supervised machine learning methods using stratified nested cross validation and 20% was selected randomly as a holdout set for internal validation. The risk prediction models were then further validated in UK Biobank dataset containing data on 1187 participants and a set of features overlapping with the training dataset.Performance of these methods has been evaluated using the area under the curve (AUC), accuracy, precision, recall, F1 score and decision curve analysis(net benefit). The best model is selected based on three criteria: the 'lowest number of feature subset' with the 'maximal average AUC over the nested cross validation' and good generalisability to the UK Biobank dataset. In the original dataset, with over 100 different bootstraps and seven feature selection (FS) methods, HLA_C_*06 was selected as the most informative genetic variant. When the dataset is mitigated the single most important genetic features based on rank was identified as HLA_B_*27 by the seven different feature selection methods, consistent with previous analyses of this data using regression based methods. However, the predictive accuracy of these single features in post mitigation was found to be moderate (AUC= 0.54 (internal cross validation), AUC=0.53 (internal hold out set), AUC=0.55(external data set)). Sequentially adding additional HLA features based on rank improved the performance of the Random Forest classification model where 20 2-digit features selected by Interaction Capping (ICAP) demonstrated (AUC= 0.61 (internal cross validation), AUC=0.57 (internal hold out set), AUC=0.58 (external dataset)). The stratification method for mitigation of confounding features and filter information theoretic feature selection can be applied to a high dimensional dataset with the potential confounders.

Composite Measures for Clinical Trials in Psoriatic Arthritis: Testing Pain and Fatigue Modifications in a UK Multicenter Study.

OBJECTIVE: To test the addition of pain and fatigue to the Composite Psoriatic Arthritis Disease Activity (CPDAI) and the Group for Research and Assessment of Psoriasis and PsA (GRAPPA) Composite Exercise (GRACE) composite measures of psoriatic arthritis (PsA). METHODS: Clinical and patient-reported outcome measures were assessed in patients with PsA at 3 consecutive follow-up visits over 6 months in a UK multicenter observational study. A pain visual analog scale and Functional Assessment of Chronic Illness Therapy Fatigue scale were added as modifications to the CPDAI and GRACE composite measures. Original and modified versions were tested against the PsA Disease Activity Score (PASDAS) and the Disease Activity Index for PsA (DAPSA). Discrimination between disease states and responsiveness were tested with t-scores, standardized response means (SRMs), and effect sizes. Data were presented to members at the 2020 annual meeting who then voted on the GRAPPA-recommended composite and treatment targets for clinical trials. RESULTS: One hundred forty-one patients were recruited with a mean PsA disease duration of 6.1 years (range 0-41 yrs). The SRMs for the GRACE and modified GRACE (mGRACE) were 0.67 and 0.64, respectively, and 0.54 and 0.46, respectively, for the CPDAI and modified CPDAI (mCPDAI). The t-scores for the GRACE and mGRACE were unchanged at 7.8 for both, and 6.8 and 7.0 for the CPDAI and mCPDAI, respectively. The PASDAS demonstrated the best responsiveness (SRM 0.84) and discrimination (t-scores 8.3). Most members (82%) agreed the composites should not be modified and 77% voted for the PASDAS as the GRAPPA-recommended composite for clinical trials, with 90% minimal disease activity (MDA) as the target. CONCLUSION: Modifying the CPDAI and GRACE with the addition of pain and fatigue does not enhance responsiveness nor the measures' ability to detect disease status in terms of requiring treatment escalation. GRAPPA members voted for the PASDAS as the composite measure in clinical trials and MDA as the target.

Composite Measures for Routine Clinical Practice in Psoriatic Arthritis: Testing of Shortened Versions in a UK Multicenter Study.

OBJECTIVE: To test shortened versions of the psoriatic arthritis (PsA) composite measures for use in routine clinical practice. METHODS: Clinical and patient-reported outcome measures (PROMs) were assessed in patients with PsA at 3 consecutive follow-up visits in a UK multicenter observational study. Shortened versions of the Composite Psoriatic Arthritis Disease Activity Index (CPDAI) and Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA) Composite Exercise (GRACE) measures were developed using PROMs and tested against the Disease Activity Score in 28 joints (DAS28), composite Disease Activity in Psoriatic Arthritis, and Routine Assessment of Patient Index Data (RAPID3). Discrimination between disease states and responsiveness were tested with the t-score, standardized response mean (SRM), and effect size (ES). Data were presented to members at the GRAPPA 2020 annual meeting and members voted on the recommended composite routine practice. RESULTS: The SRM for the GRACE, 3 visual analog scale (VAS), and 4VAS were 0.67, 0.77, and 0.63, respectively, and for CPDAI and shortened CPDAI (sCPDAI) were 0.54 and 0.55, respectively. Shortened versions of the GRACE increased the t-score from 7.8 to 8.7 (3VAS) and 9.0 (4VAS), but reduced the t-score in the CPDAI/sCPDAI from 6.8 and 6.1. The 3VAS and 4VAS had superior performance characteristics to the sCPDAI, DAS28, Disease Activity in Psoriatic Arthritis, and RAPID3 in all tests. Of the members, 60% agreed that the VAS scales contained enough information to assess disease and response to treatment, 53% recommended the 4VAS for use in routine care, and 26% the 3VAS, while leaving 21% undecided. Conclusion. Shortening the GRACE to VAS scores alone enhances the ability to detect status and responsiveness and has the best performance characteristics of the tested composite measures. GRAPPA members recommend further testing of the 3VAS and 4VAS in observational and trial datasets.

Composite Measures for Clinical Trials in Psoriatic Arthritis: Testing Pain and Fatigue Modifications in a UK Multicenter Study.

OBJECTIVE: To test the addition of pain and fatigue to the Composite Psoriatic Arthritis Disease Activity (CPDAI) and the Group for Research and Assessment of Psoriasis and PsA (GRAPPA) Composite Exercise (GRACE) composite measures of psoriatic arthritis (PsA). METHODS: Clinical and patient-reported outcome measures were assessed in patients with PsA at 3 consecutive follow-up visits over 6 months in a UK multicenter observational study. A pain visual analog scale and Functional Assessment of Chronic Illness Therapy Fatigue scale were added as modifications to the CPDAI and GRACE composite measures. Original and modified versions were tested against the PsA Disease Activity Score (PASDAS) and the Disease Activity Index for PsA (DAPSA). Discrimination between disease states and responsiveness were tested with t-scores, standardized response means (SRMs), and effect sizes. Data were presented to members at the 2020 annual meeting who then voted on the GRAPPArecommended composite and treatment targets for clinical trials. RESULTS: One hundred forty-one patients were recruited with a mean PsA disease duration of 6.1 years (range 0-41 yrs). The SRMs for the GRACE and modified GRACE (mGRACE) were 0.67 and 0.64, respectively, and 0.54 and 0.46, respectively, for the CPDAI and modified CPDAI (mCPDAI). The t-scores for the GRACE and mGRACE were unchanged at 7.8 for both, and 6.8 and 7.0 for the CPDAI and mCPDAI, respectively. The PASDAS demonstrated the best responsiveness (SRM 0.84) and discrimination (t-scores 8.3). Most members (82%) agreed the composites should not be modified and 77% voted for the PASDAS as the GRAPPA-recommended composite for clinical trials, with 90% minimal disease activity (MDA) as the target. CONCLUSION: Modifying the CPDAI and GRACE with the addition of pain and fatigue does not enhance responsiveness nor the measures' ability to detect disease status in terms of requiring treatment escalation. GRAPPA members voted for the PASDAS as the composite measure in clinical trials and MDA as the target.

Composite Measures for Routine Clinical Practice in Psoriatic Arthritis: Testing of Shortened Versions in a UK Multicenter Study.

OBJECTIVE: To test shortened versions of the psoriatic arthritis (PsA) composite measures for use in routine clinical practice. METHODS: Clinical and patient-reported outcome measures (PROMs) were assessed in patients with PsA at 3 consecutive follow-up visits in a UK multicenter observational study. Shortened versions of the Composite Psoriatic Arthritis Disease Activity Index (CPDAI) and Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA) Composite Exercise (GRACE) measures were developed using PROMs and tested against the Disease Activity Score in 28 joints (DAS28), composite Disease Activity in Psoriatic Arthritis, and Routine Assessment of Patient Index Data (RAPID3). Discrimination between disease states and responsiveness were tested with the t-score, standardized response mean (SRM), and effect size (ES). Data were presented to members at the GRAPPA 2020 annual meeting and members voted on the recommended composite routine practice. RESULTS: The SRM for the GRACE, 3 visual analog scale (VAS), and 4VAS were 0.67, 0.77, and 0.63, respectively, and for CPDAI and shortened CPDAI (sCPDAI) were 0.54 and 0.55, respectively. Shortened versions of the GRACE increased the t-score from 7.8 to 8.7 (3VAS) and 9.0 (4VAS), but reduced the t-score in the CPDAI/sCPDAI from 6.8 and 6.1. The 3VAS and 4VAS had superior performance characteristics to the sCPDAI, DAS28, Disease Activity in Psoriatic Arthritis, and RAPID3 in all tests. Of the members, 60% agreed that the VAS scales contained enough information to assess disease and response to treatment, 53% recommended the 4VAS for use in routine care, and 26% the 3VAS, while leaving 21% undecided. CONCLUSION: Shortening the GRACE to VAS scores alone enhances the ability to detect status and responsiveness and has the best performance characteristics of the tested composite measures. GRAPPA members recommend further testing of the 3VAS and 4VAS in observational and trial datasets.

A systematic review and meta-analysis to inform cancer screening guidelines in idiopathic inflammatory myopathies.

OBJECTIVES: To identify clinical factors associated with cancer risk in the idiopathic inflammatory myopathies (IIMs) and to systematically review the existing evidence related to cancer screening. METHODS: A systematic literature search was carried out on Medline, Embase and Scopus. Cancer risk within the IIM population (i.e. not compared with the general population) was expressed as risk ratios (RR) for binary variables and weighted mean differences (WMD) for continuous variables. Evidence relating to cancer screening practices in the IIMs were synthesized via narrative review. RESULTS: Sixty-nine studies were included in the meta-analysis. DM subtype (RR 2.21), older age (WMD 11.19), male sex (RR 1.53), dysphagia (RR 2.09), cutaneous ulceration (RR 2.73) and anti-transcriptional intermediary factor-1 gamma positivity (RR 4.66) were identified as being associated with significantly increased risk of cancer. PM (RR 0.49) and clinically amyopathic DM (RR 0.44) subtypes, Raynaud's phenomenon (RR 0.61), interstitial lung disease (RR 0.49), very high serum creatine kinase (WMD -1189.96) or lactate dehydrogenase (WMD -336.52) levels, and anti-Jo1 (RR 0.45) or anti-EJ (RR 0.17) positivity were identified as being associated with significantly reduced risk of cancer. Nine studies relating to IIM-specific cancer screening were included. CT scanning of the thorax, abdomen and pelvis appeared to be effective in identifying underlying asymptomatic cancers. CONCLUSION: Cancer risk factors should be evaluated in patients with IIM for risk stratification. Screening evidence is limited but CT scanning could be useful. Prospective studies and consensus guidelines are needed to establish cancer screening strategies in IIM patients.