[Interstitial lung disease associated with connective tissue disease]

Retrospective comparative study of the efficacy of JAK inhibitor (tofacitinib) in the treatment of systemic sclerosis-associated interstitial lung disease

The oral Janus kinases inhibitor (JAKi) has improved the management of skin manifestations in systemic sclerosis (SSc), and our study aimed to explore the efficacy of non-selective JAKi tofacitinib in ameliorating interstitial lung disease (ILD) in the patients with SSc. The hospitalization data of the SSc-ILD patients from April 2019 to April 2021 were collected, and the changes of pulmonary function and the radiological findings in pulmonary high-resolution CT (HRCT) from the 9 patients who received tofacitinib for at least 6 months and a matched group of 35 SSc-ILD patients treated with conventional immunosuppressants or glucocorticoids, were compared and analyzed. There were no significant differences in demographic data and clinical characteristics between the tofacitinib-treated group (tofa-group) and the matched group. However, in the tofa-group, the changes in serum lactate dehydrogenase (LDH) concentration and serum interleukin-6 levels were significantly lower than those in the matched group. Moreover, the tofa-group showed amelioration in decreased diffusing capacity of the lung for carbon monoxide (DLCO) (62.05 ± 9.47 vs. 66.61 ± 12.39, p = 0.046), reductions in ground-glass attenuation involvement (1.00 ± 0.86 vs. 0.33 ± 0.50, p = 0.024) and irregular pleural thickening (1.33 ± 0.50 vs. 0.67 ± 0.51, p = 0.004) in pulmonary HRCTs, alleviated modified Rodnan skin score (mRSS) of skin sclerosis (9.22 ± 3.81 vs. 7.11 ± 3.92, p = 0.048), and reduced HRCT scores of pulmonary fibrosis (15.00 ± 3.87 vs. 12.66 ± 4.92, p = 0.009). Logistic regression analysis showed that the involvement of ground-glass attenuation (OR 11.43) and the add-on therapy of tofacitinib (OR 9.98) were the relevant factors in the amelioration of HRCT. Our results indicate that the use of JAKi (tofacitinib) may be relevant to significant improvement of the sclerosis and early radiological abnormalities in SSc-ILD patients. Further studies are needed to confirm these findings and to explore its efficacy more precisely. Key Points • The currently available therapies for SSc-ILD have limited therapeutic benefits. • The add-on therapy of the oral JAK inhibitor is available in the real world. • The tofacitinib was promising in the improvement of the sclerosis and early radiological abnormalities in SSc-ILD patients.

Exploring the Value of Features of Lung Texture in Distinguishing Between Usual and Nonspecific Interstitial Pneumonia

RATIONALE AND OBJECTIVES

This article aims to explore the potential use of lung texture assessed in CT images in distinguishing between the usual interstitial pneumonia and the nonspecific interstitial pneumonia.

MATERIALS AND METHODS

A retrospective analysis of 96 cases of interstitial pneumonia was performed. Among these cases, there were 40 cases of usual interstitial pneumonia (UIP) and 56 cases of the nonspecific interstitial pneumonia (NSIP) . All of the patients underwent computed tomography (CT) scans. A lung intelligence kit (LK) was utilized to perform lung segmentation and texture feature extraction. The significant variables were determined by variance analysis, least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression. Finally, a multivariate logistic regression model was established to distinguish between the two types of interstitial pneumonia. Receiver operating characteristic (ROC) curves, area under the curve (AUC) values, sensitivity, and specificity were used to evaluate the performance of the established model.

RESULTS

A total of 100 texture features were extracted from the whole lung that was segmented by LK, and 8 features remained after feature reduction. The AUC, sensitivity, and specificity of the multivariate logistic regression model in the training group and the test group were 0.952 and 0.838, 0.821 and 0.667, and 0.949 and 0.824, respectively.

CONCLUSION

It is possible to distinguish between UIP and NSIP using lung texture features obtained from CT images.