BackgroundThe idiopathic inflammatory myopathies (IIM) are autoimmune connective tissue diseases affecting skeletal muscle, skin and other organ systems. IIM-related interstitial lung disease (IIM-ILD) is the most common extra-muscular manifestation, being the leading cause of morbidity and mortality. Several studies have suggested that ILD pattern based on chest high-resolution computed tomography (HRCT) can be related to disease course and treatment response, but the results vary considerably. Moreover, the clinical impact of the quantitative ILD (QILD) score, a validated computer-aided scoring system in assessing ILD severity from HRCT, and its longitudinal changes have not yet been evaluated in IIM-ILD.ObjectivesThis study aims to investigate ILD patterns and QILD scores in patients with IIM-ILD, to identify their clinical impact, and to delineate longitudinal changes of QILD measurement.MethodsA total of 80 patients with IIM (polymyositis 22, and dermatomyositis 58) who underwent at least 2 times of serial HRCT scans were included. Visual ILD patterns were assessed by multiple thoracic radiologists. Quantitative analysis of HRCT was presented as total extent of QILD scores (%) in whole lung and most severe zone. Individual time-estimated ΔQILD score between first 2 visits was derived using a linear approximation of yearly change, where the duration of median (IQR) was 1.0 (0.4-1.6) years in the first 2 HRCT scans.ResultsThe median (IQR) age of the patients was 52.0 (43.5-58.5) years and 60 (75.0%) were women. Baseline median score of whole lung-QILD and most severe zone-QILD were 28.1% (19.1-43.8) and 68.0% (45.5-81.8), respectively, and QILD score showed significant correlations with pulmonary function tests (r=-0.349, p=0.002 for % predicted forced vital capacity; and r=-0.381, p=0.001 for % predicted diffusing capacity for carbon monoxide). The individual time-estimated yearly ΔQILD score between first 2 visits presented that approximately half of the patients showed improvement or stability in QILD scores; however, when patients were sorted by visual assessment in ILD subtype on HRCT, approximately two-thirds of the patients with usual interstitial pneumonia (UIP) pattern were aggravated in QILD scores and less than half of subjects with nonspecific interstitial pneumonia and organizing pneumonia were aggravated (Figure 1, 80% for UIP vs. 44.4% for non-UIP, p=0.013). There was no immunosuppressive drugs related to meaningful improvement in QILD scores during first 2 visits. Notably, we observed significant aggravation of QILD scores in tacrolimus users (n=7, median time-estimated whole lung-yarly ΔQILD 20.3 (2.7-38.4)) compared with tacrolimus non-users (n=73, median time estimated whole lung-yearly ΔQILD -1.2 (-8.3-6.5)). Among 80 patients, 6 (7.5%) were died due to various lung complications. Higher baseline QILD scores were noted in deaths (median whole lung-QILD 45.4 (32.9-56.5)) than in survivors (median whole lung-QILD 26.9 (19.0-42.4)), albeit not significant (p=0.084). Poor survival rate was observed in patients with high grade of ground glass opacity by visual assessment in right upper lobe (log-rank test, p=0.042). Among subgroup of patients with 3 serial HRCT scans (n=41), dynamic changes of four distinct patterns (improving, worsening, convex, and concave) were observed.Figure 1.Cleveland dot plot of individual time-estimated yearly ΔQILD during fist 2 visits.ConclusionThe changes in QILD score in IIM-ILD are dynamic and present different by visual assessment. QILD score has the potential for evaluation of the severity changes, prognosis and medication response in patients with IIM-ILD.References[1]Tashkin DP, et al. Ann Rheum Dis 2016;75(2):374-81.7 truncated values in the graph A. NSIP: nonspecific interstitial pneumonia; OP: organizing pneumonia; UIP: usual interstitial pneumonia.Disclosure of InterestsNone declared
BackgroundTumor necrosis factor inhibitors (TNFi) have become a mainstay of management for axial spondyloarthritis (axSpA). However, it remains unclear whether patients with axSpA should continue the standard-dose TNFi after achieving stable disease activity. Although complete discontinuation of TNFi is followed by early relapse in most cases, several studies documented that reduced doses of TNFi in patients with prolonged low disease activity showed similar effects on disease control and drug survival compared to standard dose of TNFi. One of the main problem in the dose-tapering strategies for TNFi is a selection of the appropriate patient. However, there has been a lack of robust evidence regarding clinical factors predicting the flare after tapering of TNFi in patients with axSpA.ObjectivesThis study aims to develop and validate the prediction model to select the patients in whom tapering of TNFi does not lead to flare.MethodsWe used the data from Korean College of Rheumatology Biologics registry, which included a total of 1,730 patients receiving biologic DMARD from 2017 to 2019 in South Korea. In this study, a total of 526 patients who were initially treated with the standard-dose TNFi and tapered the dose after at least 1 year of the treatment were analyzed. Dose quotient (DQ, 0-1) was applied to quantified TNFi used during interval. The main outcome was an occurrence of flare defined as ASDAS-CRP score of ≥2.1 after 1 year of tapering TNFi. To develop the prediction model, clinical factors having relevant association (p < 0.1) with the outcome were first selected as candidate predictors. Logistic regression using a stepwise approach through backward elimination was used for the final model.ResultsPatients’ mean (SD) age was 37.5 (11.9) years, 418 (79.5%) were men, and 474 (90.1%) were HLA-B27 positive. Mean disease duration was 5.0 (6.1) years and 433 (82.3%) were TNF naïve. The mean BASFI and ASDAS-CRP at baseline were 3.4 (2.6) and 3.7 (1.0), respectively. Approximately two-thirds of the patients (65.8%) were initiated TNFi tapering at the first 1 or 2 years from baseline. At the time of TNFi tapering, the mean DQ was 0.67 (0.15) and 381 (72.4%) were prescribed concurrently with NSAIDs, and the mean BASFI and ASDAS-CRP were 1.3 (1.8) and 1.6 (0.9), respectively. During 12 months of follow up starting from the TNFi tapering, 127 (24.1%) experienced the flare. The multivariable analysis revealed that HLA-B27 positivity (OR 0.337; 95% CI 0.161-0.705; p=0.004), inflammatory back pain (OR 2.920; 95% CI 1.283-6.648; p=0.011), ASDAS-CRP at tapering (OR 2.798; 95% CI 2.030-3.856; p<0.001), and BASFI at tapering (OR 1.214; 95% CI 1.051-1.402; p=0.008) were significantly associated with flare. Based on the results of the logistic regression analysis, the predicted probability was calculated by the following formula: P=1/[1+ exp{-(1.088 x HLA-B27 negativity + 1.072 x inflammatory back pain + 1.567 x psoriasis + 0.623 x family history of axSpA + 1.092 x diabetes mellitus + 0.435 x DQ at TNFi tapering + 1.029 x ASDAS-CRP at TNFi tapering + 0.194 x BASFI at TNFi tapering)}]. The best cut-off value of the model to define the flare was 0.2416 (95% CI 0.176, 0.301) with sensitivity 74.0% and with specificity 81.0%. AUC was 0.828 (95% CI 0.786-0.869) indicating a good predication (Figure 1). The internal validation with bootstrapping showed minimal overfitting (estimated AUC 0.794) and good calibration between observed and predicted values (calibration slope 1.110, 95% CI 0.903, 1.317; intercept 0.026, 95% CI -0.091, 0.039).Figure 1.Apparent performance of developed model for prediction of flare after 12 months of tumor necrosis factor inhibitors tapering.ConclusionWe developed the prediction model for the flare after 12 months of TNFi tapering in patients with axSpA. It might be applicable in real world setting, although external validation will be required in the future investigation.References[1]Zavada J, et al. Ann Rheum Dis. 2016;75(1):96-102.AcknowledgementsWe greatly thank to the the Clinical Research Committee of the Korean College of Rheumatology and all participating hospitals.Disclosure of InterestsNone declared
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.