Predicting Treatment Outcomes And Responder Subsets In Scleroderma-Related Interstitial Lung Disease

Abstract

Objectives-To identify baseline characteristics of patients with Scleroderma-Related Interstitial Lung Disease (SSc-ILD) which predict the most favorable response to a 12-month treatment with oral cyclophosphamide (CYC).Methods-Regression analyses were retrospectively applied to the Scleroderma Lung Study data in order to identify baseline characteristics that correlated with the absolute change in %-predicted Forced Vital Capacity (FVC) and the placebo-adjusted change in %-predicted FVC over time (the CYC treatment effect).Results-Completion of the CYC arm of the Scleroderma Lung Study was associated with a placebo-adjusted improvement in %-predicted FVC of 2.11% at 12 months which increased to 4.16% when patients were followed for another 6 months (p=0.014). Multivariate regression analyses identified the maximal severity of reticular infiltrates on baseline high-resolution computerized tomography (HRCT), the modified Rodnan Skin Score (mRSS), and Mahler's Baseline Dyspnea Index (BDI) as independent correlates of treatment response. When patients were stratified based on whether 50% or more of any lung zone was involved by reticular infiltrates on HRCT and/or the presence of a mRSS of at least 23, a subgroup emerged with an average CYC treatment effect of 4.73% at 12 months and 9.81% at 18 months (p<0.001). Conversely, there was no treatment effect (−0.58%) in patients with less severe HRCT findings and a lower mRSS.

High Resolution Computed Tomography Scoring Systems for Evaluating Interstitial Lung Disease in Systemic Sclerosis Patients

“…The pulmonary fibrosis score progressed in a greater proportion of patients on placebo compared to those receiving cyclophosphamide, but there was no difference in ground-glass or honeycombing [39]. Severity of fibrosis, but not ground glass, at baseline correlated with better response to treatment with cyclophosphamide [40]. The results of this study, again, put into doubt the interpretation that ground glass changes represent those pathologic abnormalities which perhaps lead to fibrosis and which may be reversible.…”

Immunosuppression for interstitial lung disease in systemic sclerosis

“…At present, little is known about predictors of treatment response in SSc-ILD. Factors that have been described to be associated to treatment response are: early phase of disease [34,35]; baseline FVC [70]; maximal severity of reticular infiltrates on HRCT at baseline; and mRss at baseline [71]. Nevertheless, in different studies, factors associated with better response were not always univocal.…”

“…The observation that patients with low FVC did not respond to immunosuppression could be explained by the fact that FVC reflects disease damage rather than disease activity [70]. On the contrary, another study observed a better response to CYC in patients with more severe reticular infiltrates on HRCT [71]. Therefore, in the absence of certain factors that may tell us which patient will respond better to treatment, immunosuppression should be started as soon as possible.…”

Predicting improvement in diffuse scleroderma: lessons learnt

“…14 15 In the former, the vast majority did not worsen or improve their lung function in either treatment arm, despite including relatively early patients with interstitial lung disease (ILD), but patients with more fibrosis on lung imaging and higher baseline mRSS (23 or more) were more likely to have benefit from cyclophosphamide treatment (as these patients were more apt to worsen on placebo). 14 In the latter trial, although all patients had to have a baseline digital ulcer, two-thirds had a recurrent ulcer over the 24-week long study, 15 whereas in an earlier trial of previous digital ulcers over the previous year, but not currently, 60% has a subsequent ulcer over the study period, so enriching the population leads to slightly more events. 16 In conclusion, enriching a population of early dcSSc that may change over 1 year of follow-up depends on how you predict the population will shift on the variable of interest such as the mRSS.…”