Background Interstitial Lung Disease (ILD) and Pulmonary Arterial Hypertension (PAH) are the major sources of morbidity and mortality amongst patients with Scleroderma. Specific autoantibodies, anti-Scl70 and anti-centromere (ACA), are associated with ILD and PAH respectively. Screening for ILD and PAH using annual pulmonary function testing (PFT), High Resolution Computed Tomography (HRCT) and Echocardiography respectively, is recommended by the BTS ILD Guidelines, 2008. However, the predictive value of autoantibodies and clinical screening for ILD and PAH, remains unclear in regional centres managing patients with Scleroderma. We hypothesised that an objective scoring system would elucidate lung phenotypes amongst the cohort and confirm original radiology reports for these patients, whilst patients autoantibody profiles would serve a clinical purpose in management. We retrospectively compared identification of ILD by a specialist ILD radiologist, against the use of predictive autoantibody profiling, for the detection of ILD.

Methods 99 patients with Scleroderma, managed in Nottingham, were identified from clinic lists (n = 68) or the pathology database, for positive anti-Scl70 and ACA results (n = 31). Autoantibody profiles (n = 77), including Extractable Nuclear Antigens (ENA) and Myositis Immunoblot, were accessed using the Nottingham University Hospitals Trust pathology database. Existing and accessible HRCT scans (n = 69), were evaluated, by a radiologist with a special interest in connective tissue disease-ILD. The Scleroderma Lung Study scoring system was employed, evaluating ground glass opacity, fibrosis, bronchiectasis and honeycombing in three anatomical zones. A binary logistic regression model evaluated the role of autoantibodies in ILD diagnosis.

Results On re-evaluation of HRCT (n = 69), eight scans had no evidence of ILD. 49 scans had evidence of ILD (NSIP = 41; UIP = 5; non-specific pattern of ILD = 3). Following comparison with the initial reporting radiologists’ reports, twelve patients, with no previous diagnosis of ILD, were identified with the NSIP phenotype. The autoantibody model, using positive ACA and anti-Scl70 status, correctly classified 64.5% of cases overall (n = 62; p = 0.05).

Conclusions The role of objective HRCT evaluation, by a specialist radiologist, is superior in the detection of ILD, even in the ubiquitous NSIP phenotype, when compared to general radiology review and predictive autoantibody profiling of the same patients.