Systemic sclerosis (SSc) is a chronic autoimmune disease characterized by immune dysregulation, vasculopathy, and inflammation resulting in excessive fibrosis of the skin and internal organs [1,2]. Interstitial lung disease (ILD) is one of the most common manifestations of SSc, affecting approximately 40–60% of patients within this population. SSc-associated ILD (SSc-ILD) is the leading cause of hospitalization, morbidity, and mortality in patients with SSc, accounting for approximately 35% of SSc-related deaths [3–6]. The 2013 American College of Rheumatology/European Legion Against Rheumatism (ACR/EULAR) classification criteria defines SSc-ILD as, ‘pulmonary fibrosis seen on high-resolution computed tomography (HRCT) or chest radiograph, pronounced in the basilar portions of the lungs, or occurrence of “Velcro” crackles on auscultation, not because of another cause such as congestive heart failure’ . Major risk factors for the development of SSc-ILD identified from observational studies include diffuse cutaneous SSc, African American race, older age at disease onset, shorter disease duration, presence of anti-Scl-70 antibodies, and the absence of anticentromere antibodies [8–10].
As of this writing, there are no FDA-approved treatments for SSc-ILD. Current management approaches follow either a strategy of close monitoring of symptoms and pulmonary function tests (PFTs), or a regimen of immunosuppression with close follow-up of symptoms and PFTs. First-line therapy for treatment of SSc-ILD is mycophenolate mofetil (MMF), which was shown to have similar efficacy to and less toxicity than cyclophosphamide in Scleroderma Lung Study (SLS) II . In the recently published SENSCIS trial, patients with SSc-ILD who were taking nintedanib had a lower annual rate of forced vital capacity (FVC) decline than those taking placebo (difference, 41 ml per year; 95% confidence interval [CI], 2.9–79.0; P-value = 0.04) . Notably, 48% of patients in the trial were taking MMF concomitantly with nintedanib or placebo. At this time, it remains unknown where nintedanib will fit into the treatment algorithm of SSc-ILD. It may become the first FDA-approved medication for the treatment of SSc-ILD. Research into newer therapies, such as pirfenidone , is ongoing, yet morbidity and mortality from SSc-ILD remain high. Therefore, it is critical that we investigate methods to screen, classify, and risk stratify patients with SSc-ILD, so we can detect disease early and identify those at high risk of progression. Research into early detection and treatment of SSc-ILD may eventually enable prevention of progressive disease. In the present review, we aim to summarize fundamental preexisting literature and provide insight into recent advances in the classification, diagnosis, and early detection of SSc-ILD.
CLASSIFICATION OF SYSTEMIC SCLEROSIS-ASSOCIATED INTERSTITIAL LUNG DISEASE
There are several ways to classify SSc-ILD: by histopathology, radiographic pattern, radiographic extent of disease, and likelihood of progression (Fig. 1). Histopathologically, SSc-ILD is characterized by early pulmonary infiltration of inflammatory cells into the lung parenchyma with resultant fibrosis and can be classified into specific patterns of disease including nonspecific interstitial pneumonia (NSIP), usual interstitial pneumonia (UIP), organizing pneumonia, and lymphoid interstitial pneumonia [14,15]. The most common radiographic pattern on HRCT scan of the chest is NSIP, present in approximately 65% of cases and characterized by ground glass opacities in a primarily peripheral distribution with subpleural and basilar predominance. This contrasts with the UIP pattern, present in approximately 25% of cases, characterized by disrupted lung architecture, dense areas of patchy fibrosis, and honeycombing in a primarily subpleural distribution . Lung biopsy is usually not required to confirm the diagnosis of SSc-ILD unless other diagnoses such as malignancy or infection are suspected, as patterns can be determined through HRCT alone with a high degree of reliability .
Although these radiographic and histopathologic classifications are useful, and there is a trend for shorter survival in patients with a UIP pattern compared to those with an NSIP pattern , the prognosis of patients with SSc-ILD is quite variable and is more closely linked to both disease extent at baseline and progressive functional decline [14,16,17]. Given this variability, it is important not only to characterize SSc-ILD by histopathologic or radiographic pattern, but also to quantify disease extent and classify patients according to their individual risk of progression. In an era of increasingly personalized medicine, further advances in composite clinical screening algorithms and better characterization of predictive markers for progressive disease promise improvements in our overall management of SSc-ILD.
In 2008, Goh et al. developed a classification system to stage the extent of ILD in SSc. Using a combination of HRCT and PFTs, they classified patients into limited and extensive disease categories. Extensive disease was defined as more than 20% lung involvement on HRCT, or 10–30% ILD involvement on HRCT and FVC less than 70% predicted. Limited disease was defined as or less 10% ILD involvement on HRCT, or 10–30% lung involvement on HRCT and an FVC at least 70% predicted . This staging system has been validated as a predictor of mortality, and SSc-ILD patients with extensive disease have an approximately three-fold increased risk of clinical decline (defined as need for supplemental oxygen or lung transplantation) and death compared to those with limited disease [18–20].
Patients with SSc-ILD can also be stratified by their likelihood of progression. There is marked variability in the clinical course of disease: some patients have a slowly progressive decline in, or even stability of, FVC, whereas others experience a rapidly progressive course, leading to lung transplantation or death, despite treatment . Group-based trajectory modeling based on retrospective review of longitudinal FVC values from 254 patients with SSc has identified seven distinct FVC trajectories: very low baseline FVC with slow decline (5.5% of patients), very low baseline FVC with improvement (13.8% of patients), low baseline FVC with fast decline (9.5% of patients), low baseline FVC that remained stable (19.7% of patients), low-normal baseline FVC with improvement (31.1% of patients), normal baseline FVC with improvement (16.1% of patients), and normal baseline FVC that remained stable (4.3% of patients) . Similarly, the findings of Goh et al. have since been extrapolated to show that dynamic changes in imaging studies and PFTs hold prognostic value and can be utilized to help predict risk of progressive disease [21,23,24]. One-year declines in FVC and diffusion capacity for carbon monoxide (DLCO), for example, have been shown to predict survival in patients with extensive disease, with a decrease in FVC by more than 10% and/or a decrease in DLCO by more than 15% during 1 year associating with poorer prognosis [21,24]. These parameters have since been incorporated into the outcome measures in rheumatology (OMERACT) definition of progression of connective tissue disease-associated ILD (. More recently, Volkmann et al.[26▪▪] developed a mortality prediction model through post hoc Cox regression analyses of patients from SLS I and II. They showed that significant declines in FVC (≥10%) and DLCO (≥15%) over 24 months were the most robust predictors of long-term survival, even when adjusting for treatment arm and baseline disease severity [26▪▪]. Additional risk factors for worse prognosis of SSc-ILD included elevated baseline plasma C-reactive protein (CRP) levels, gastroesophageal reflex disease, pulmonary arterial hypertension, older age, African American race, and male sex [26▪▪,27,28].
Akin to approaches reported in the idiopathic pulmonary fibrosis (IPF) literature [29–31], several prediction models have been developed to risk stratify patients with SSc-ILD using clinical variables available at the time of a patient's initial office visit [32▪,33▪]. The SpO2 and Arthritis (SPAR) model is one such tool, designed to predict ILD progression, that was developed using two independent prospective cohorts of patients who met 2013 ACR/EULAR Classification Criteria for SSc and had mild ILD (<20% lung involvement) assessed by HRCT at baseline [32▪]. ILD progression was defined as a relative decrease in FVC by at least 15% or a decline in FVC by at least 10% combined with a decrease in DLCO by at least 15% at 1-year follow-up. In their multivariate analyses, declines in SpO2 after 6-min walk test and arthritis (defined as one or more tender and swollen joints as judged by a treating physician) were identified as independent predictors of ILD progression in both cohorts, with an optimal SpO2 cut-off value of 94% by ROC analysis [32▪]. The smoking history, age, and DLCO (SADL) model is another validated risk prediction model for all-cause mortality in SSc-ILD developed using two independent prospective cohorts of patients meeting 2013 ACR/EULAR Criteria for ILD. The SADL model uses a patient's smoking history, age, and DLCO to classify him or her into a low-risk, moderate-risk, or high mortality risk group at 3 years from ILD diagnosis [33▪]. Although further validation is required, such models are easily used and can potentially guide clinicians in their management decisions.
Although classification of SSc-ILD by radiographic pattern continues to hold important treatment and survival implications, we believe a personalized medicine approach that accounts for an individual's radiographic pattern and extent, FVC trajectory, autoantibody status, disease subtype, and demographic variables, is critical to determining the likelihood of progression and informing treatment decisions.
SCREENING AND DIAGNOSIS OF SYSTEMIC SCLEROSIS
Diagnosing SSc-ILD at an early stage can be challenging, as it may develop insidiously and patients may have asymptomatic, ‘subclinical’ ILD. The most common early clinical manifestations of SSc-ILD include exertional dyspnea and nonproductive cough, both of which are nonspecific . Given that patients may be asymptomatic or have nonspecific symptoms, and that ILD is both highly prevalent and the leading cause of death in SSc, universal screening of patients with SSc for ILD is critical. According to reports summarizing the proceedings from the ACR and Association of Physicians of Great Britain and Ireland Connective Tissue Disease (CTD)-ILD Summit, the development of a screening system with the dual objective of identifying early-stage disease and identifying those at greatest risk for progression and functional decline is a major unmet need within the field . The two most widely applied methodologies for ILD screening are PFTs and HRCT.
PFTs are a valuable noninvasive method to assess severity of ILD and monitor disease course. Although PFTs are widely utilized to screen patients with SSc for ILD, they lack sensitivity and have a high false-negative rate for the detection of ILD . In a single-center prospective cohort study, Suliman et al. showed that among 64 patients with ILD on HRCT, approximately 62.5% had a normal FVC, defined as at least 80% predicted. The sensitivity of an FVC less than 80% predicted for detection of SSc-ILD was only 38%; this increased only to 72% when the following parameters were combined: FVC less than 80% predicted or ΔFVC at least 10% or total lung capacity less than 80% predicted or DLCO less than 70% predicted and forced expiratory volume in 1s/FVC greater than 0.7. Showalter et al. performed a similar study of 265 patients meeting 2013 ACR/EULAR Classification Criteria for SSc to identify the sensitivity, specificity, and negative predictive value of PFTs for the presence of SSc-ILD on HRCT, and to determine optimal FVC and DLCO thresholds for the presence of SSc-ILD on HRCT. An FVC less than 80% predicted (sensitivity 69%, specificity 73%) and DLCO less than 62% predicted (sensitivity 60%, specificity 70%) were identified as the optimal thresholds to define ILD; however, all FVC and DLCO threshold combinations had a negative predictive value of less than 0.7. Collectively, these data suggest a high risk of missing SSc-ILD if relying solely on PFTs. Moreover, ILD is a radiographic (and/or histopathologic) diagnosis, thus imaging studies are required for diagnosis.
HRCT of the chest is the gold standard for detection of ILD and enables assessment of the radiographic pattern and extent of disease [35,38]. Launay et al. showed the utility of baseline HRCT, as 34 of 40 (85%) patients with SSc with normal HRCT at baseline still had normal HRCT at a mean follow-up of 5 years. Thus, these baseline HRCTs had both diagnostic and prognostic value. Routine use of screening HRCT in SSc may identify asymptomatic individuals with subclinical ILD at high risk for developing clinically significant ILD, just as the presence of subclinical ILD on baseline cardiac computed tomography (CT) scans predicts development of clinically significant ILD in community-dwelling adults . High attenuation areas (HAA), defined as the percentage of imaged lung with CT attenuation values between −600 and −250 Hounsfield units, are a novel CT-based quantitative biomarker of subclinical ILD that have strong construct validity as a biomarker of subclinical lung inflammation and extracellular matrix remodeling, processes that precede ILD, in community-dwelling adults [40,41]. In community-dwelling adults enrolled in the Multi-Ethnic Study of Atherosclerosis, greater HAA is associated with reduced FVC, reduced exercise capacity, elevated serum levels of matrix metalloproteinase-7 (MMP-7) and interleukin-6 (IL-6), the development of interstitial lung abnormalities (ILA, a qualitative visually-identified subclinical ILD phenotype on CT) on CT at 10-year follow-up, and an increased risk of developing clinically evident ILD and ILD-specific mortality at 12-year follow-up . Thus, research is needed into whether quantification of HAA on screening HRCTs in patients with SSc can identify individuals at high risk of developing clinically evident ILD and ILD-specific mortality. Ultimately, identification of subclinical ILD on screening HRCTs in patients with SSc may permit a ‘window of opportunity’ for intervention.
However, there remains substantial practice variation in rheumatologists’ use of HRCT to screen for ILD in their patients with SSc. In a survey of 676 ACR member rheumatologists in New York, New Jersey, Pennsylvania, and Connecticut, and 356 SSc experts worldwide, only 51% of the general rheumatologist respondents and 66% of the SSc expert respondents reported routinely performing screening HRCTs in their patients with SSc [42▪▪]. Moreover, there was significant global practice variation among SSc experts in their HRCT ordering practices: screening HRCT was ordered by 100% (7 of 7) of SSc experts in Latin America, 80% (4 of 5) in Asia, 79% (45 of 57) in Europe, 60% (28 of 47) in the United States, 33% (2 of 6) in Canada, and 0% (0 of 5) in Australia [42▪▪]. Further, there was little agreement regarding indications for HRCT among rheumatologists who do not routinely order screening HRCTs in their patients with SSc. In our practice, we routinely order HRCTs to screen for ILD in all newly diagnosed patients with SSc.
Given that PFTs lack sensitivity for detection of SSc-ILD, that HRCT is the gold standard for diagnosis of ILD, and that there is significant variation in both general rheumatologists’ and SSc expert rheumatologists’ use of HRCTs to screen for ILD in SSc, there is an urgent need to develop screening guidelines for the detection of ILD in SSc.
NOVEL METHODS FOR SCREENING AND CLASSIFICATION
Novel imaging techniques
Given the lack of any clear screening guidelines and gaps in our ability to prognosticate patients adequately, research into novel imaging is an intense area of focus. Over the past 15 years, lung ultrasound (LUS) has emerged as an attractive noninvasive, radiation-free technique with high sensitivity and specificity for the diagnosis of ILD [43,22,45]. Assessment for pleural irregularities and increased number of B-lines, discrete vertical hyperechoic reverberations arising from pleural lines, serves as the basis for LUS assessment for ILD. An increased number of B-lines is associated with thickening of the lung parenchyma and is suggestive of ILD . Previous studies identified a greater number of B-lines in patients with ILD than in those without ILD on HRCT, with a concordance rate of 83% [46,47]. A recent meta-analysis of 11 studies analyzing LUS for diagnosis of CTD-ILD yielded a pooled sensitivity and specificity of 85.9 and 83.9%, respectively . Current limitations of LUS for ILD screening in SSc include lack of standardization (e.g. number of lung zones or intercostal spaces to examine, and which probe to use), operator skill dependence, possible confounding because of skin fibrosis, and the total length of time required for the procedure .
Several promising exploratory methods of ILD detection are being investigated. Lung ultrasound surface wave elastography (LUSWE) is a new ultrasound application that measures the elasticity of superficial lung tissue. Zhang et al. found significant increases in the speed of ultrasound wave propagation through the more fibrotic lung surfaces of patients with SSc-ILD compared to healthy controls, which could be useful for screening patients with SSc for ILD, although it remains unclear how this technology fares in detecting changes of ILD other than fibrosis (e.g. ground glass opacifications) . Research into additional novel approaches such as magnetic resonance imaging (MRI) and molecular imaging are ongoing and show the ability to detect SSc-ILD with high accuracy without the use of ionizing radiation [49–51]. In 2018, for example, Gargani et al. evaluated the utility of lung MRI in 32 patients with SSc who underwent concurrent cardiac MRI with dedicated lung scanning (with T1 and STIR imaging) and chest HRCT. Mean T1/STIR times and HRCT semiquantitative scoring were calculated for each patient. The authors showed that mean STIR was moderately correlated with HRCT scores (r = 0.52; P < 0.01). Similarly, in a proof of concept study, Schniering et al. successfully targeted integrin αvβ3 (alpha-v-beta-3) and somatostatin receptor 2 (SSTR2), two proteins upregulated in ILD lungs, to illustrate the role of nuclear imaging to visualize ILD in animal models and patients with known ILD. Their study shows the potential for screening to occur on a molecular level through the precise targeting of proteins associated with fibrotic lung parenchyma.
In recent years, much research has gone into investigating the clinical utility of biomarkers for the diagnosis of ILD and assessment of disease severity and progression [52–53]. Although the precise utility of biomarkers remains investigational and no single serologic marker has been fully validated, numerous potential biomarkers identified in the IPF literature have been subsequently investigated in SSc-ILD [e.g. MMP-7, surfactant protein-D (SP-D), Krebs von den Lungen-6 (KL-6), and C-C motif chemokine ligand 18 (CCL18)] [53–56]. In addition, novel potential biomarkers continue to be explored, such as antibodies against chemokine receptors CXCR3 and CXCR4, two G-protein-coupled receptors implicated in the pathogenesis of pulmonary fibrosis via mediation of cell migration . Significantly higher levels of CXCR3 and CXCR4 antibodies were found in patients with SSc-ILD compared to controls, and levels of these antibodies were shown to correlate inversely with FVC and DLCO in patients with SSc. Somewhat paradoxically, however, patients with SSc-ILD with more progressive disease tended to have lower CXCR3 and CXCR4 antibody titers compared to those with more stable disease .
Although many of these biomarkers hold promise, there have been conflicting results regarding their sensitivity, specificity, and predictive power [56,58▪▪]. In a combined cohort study of 427 Norwegian and French patients meeting 2013 ACR/EULAR Classification Criteria for SSc, four promising ILD biomarkers [SP-D, KL-6, CCL18, and soluble OX40 ligand (OX40L)] were analyzed for their ability to diagnose and predict progression of SSc-ILD [58▪▪]. Serum levels of KL-6 were significantly inversely correlated with FVC (r = −0.317; P < 0.001) and DLCO (r = −0.335; P < 0.001) and positively correlated with the extent of fibrosis on HRCT (r = 0.551; P < 0.001). Similarly, KL-6 [odds ratio (OR) = 2.41; 95% CI, 1.43–4.07] and SP-D (OR = 3.15; 95% CI, 1.81–5.48; P < 0.001) were significantly associated with the presence of lung fibrosis in multivariable analysis adjusting for age and SSc disease duration, defined as the time between first non-Raynaud's symptom and blood sample collection [58▪▪]. These findings corroborate previous studies of KL-6 in SSc-ILD, but are inconsistent with previous smaller analyses of SP-D [59–62]. In a longitudinal analysis, CCL18 was an independent predictor of more than 10% decrement in FVC over a mean follow-up period of 3.2 years (hazard ratio = 2.90; 95% CI, 1.25–6.73; P = 0.014) and the development of de-novo extensive disease per Goh criteria (hazard ratio = 3.71; 95% CI, 1.02–13.52; P = 0.048) [58▪▪]. These results support previous smaller studies that showed elevated CCL18 levels were predictive of significant declines in FVC [63–66]. In sum, these findings suggest potential roles for SP-D as a diagnostic biomarker of SSc-ILD, KL-6 as a biomarker of lung fibrosis severity, and CCL18 as a biomarker of progressive SSc-ILD [58▪▪]. Despite the potential for their use in the diagnosis, classification, and risk stratification of SSc-ILD, however, further validation and standardization is ultimately required before such biomarkers should be utilized in clinical practice.
ILD is a common manifestation of SSc and the leading cause of mortality in this patient population. Although radiographic and histopathologic classifications help to define general disease patterns, stark variations in clinical course limits the utility of assessing SSc-ILD on the basis of pattern alone. Recent work suggests a paradigm shift has occurred, with patients classified primarily according to their probability of severe, progressive disease through identification of risk factors, measurement of disease extent on HRCT, longitudinal declines in FVC, and mortality prediction models. Although no clinical practice guidelines for ILD screening in SSc exist, we recommend screening with HRCT and PFT in all patients with SSc. Biomarkers, lung ultrasound, and novel imaging modalities serve as promising adjunctive or alternative means of screening and diagnosis. Further validation is required before they should be used in clinical practice.
Financial support and sponsorship
E.J.B. is supported by NIH/NIAMS K23AR075112.
Conflicts of interest
There are no conflicts of interest.
REFERENCES AND RECOMMENDED READING
Papers of particular interest, published within the annual period of review, have been highlighted as:
- ▪ of special interest
- ▪▪ of outstanding interest
1. Denton CP, Khanna D. Systemic sclerosis
. Lancet 2017; 390:1685–1699.
2. Varga J, Trojanowska M, Kuwana M. Pathogenesis of systemic sclerosis
: recent insights of molecular and cellular mechanisms and therapeutic opportunities. J Scleroderma Relat Disord 2017; 2:137–152.
3. Tyndall AJ, Bannert B, Vonk M, et al. Causes and risk factors for death in systemic sclerosis
: a study from the EULAR Scleroderma Trials and Research (EUSTAR) database. Ann Rheum Dis 2010; 69:1809–1815.
4. Elhai M, Meune C, Boubaya M, et al. Mapping and predicting mortality from systemic sclerosis
. Ann Rheum Dis 2017; 76:1897–1905.
5. Li X, Qian Y-Q, Liu N, et al. Survival rate, causes of death, and risk factors in systemic sclerosis
: a large cohort study. Clin Rheumatol 2018; 37:3051–3056.
6. Steen VD, Medsger TA. Changes in causes of death in systemic sclerosis
, 1972-2002. Ann Rheum Dis 2007; 66:940–944.
7. van den Hoogen F, Khanna D, Fransen J, et al. 2013 classification
criteria for systemic sclerosis
: an American college of rheumatology/European league against rheumatism collaborative initiative. Ann Rheum Dis 2013; 72:1747–1755.
8. Nihtyanova SI, Schreiber BE, Ong VH, et al. Prediction of pulmonary complications and long-term survival in systemic sclerosis
: pulmonary complications and survival in SSc. Arthritis Rheumatol 2014; 66:1625–1635.
9. Jaeger VK, Wirz EG, Allanore Y, et al. Incidences and risk factors of organ manifestations in the early course of systemic sclerosis
: a longitudinal EUSTAR Study. Assassi S, editor. PLoS ONE 2016; 11:e0163894.
10. Steen V, Domsic RT, Lucas M, et al. A clinical and serologic comparison of African American and Caucasian patients with systemic sclerosis
. Arthritis Rheum 2012; 64:2986–2994.
11. Tashkin DP, Roth MD, Clements PJ, et al. Mycophenolate mofetil versus oral cyclophosphamide in scleroderma-related interstitial lung disease
(SLS II): a randomised controlled, double-blind, parallel group trial. Lancet Respir Med 2016; 4:708–719.
12. Distler O, Highland KB, Gahlemann M, et al. Nintedanib for systemic sclerosis
–associated interstitial lung disease
. N Engl J Med 2019; NEJMoa1903076.
13. Roth M. Scleroderma Lung Study III – Combining Pirfenidone With Mycophenolate (SLSIII). 2019. Retrieved from https://clinicaltrials.gov/ct2/
(Identification No. NCT03221257)
14. Fischer A, Swigris JJ, Groshong SD, et al. Clinically significant interstitial lung disease
in limited scleroderma. Chest 2008; 134:601–605.
15. Goldin JG, Lynch DA, Strollo DC, et al. High-resolution CT scan findings in patients with symptomatic scleroderma-related interstitial lung disease
. Chest 2008; 134:358–367.
16. Bouros D, Wells AU, Nicholson AG, et al. Histopathologic subsets of fibrosing alveolitis in patients with systemic sclerosis
and their relationship to outcome. Am J Respir Crit Care Med 2002; 165:1581–1586.
17. Dobrota R, Mihai C, Distler O. Personalized medicine in systemic sclerosis
: facts and promises. Curr Rheumatol Rep 2014; 16:425.
18. Goh NSL, Desai SR, Veeraraghavan S, et al. Interstitial lung disease
in systemic sclerosis
: a simple staging system. Am J Respir Crit Care Med 2008; 177:1248–1254.
19. Moore OA, Goh N, Corte T, et al. Extent of disease on high-resolution computed tomography
lung is a predictor of decline and mortality in systemic sclerosis
-related interstitial lung disease
. Rheumatology 2013; 52:155–160.
20. Hax V, Bredemeier M, Didonet Moro AL, et al. Clinical algorithms for the diagnosis and prognosis of interstitial lung disease
in systemic sclerosis
. Semin Arthritis Rheum 2017; 47:228–234.
21. Moore OA, Proudman SM, Goh N, et al. Quantifying change in pulmonary function as a prognostic marker in systemic sclerosis
-related interstitial lung disease
. Clin Exp Rheumatol 2015; 33 (4 Suppl 91):S111–116.
22. Man A, Davidyock T, Ferguson LT, et al. Changes in forced vital capacity over time in systemic sclerosis
: application of group-based trajectory modelling. Rheumatology 2015; 54:1464–1471.
23. Goh NS, Hoyles RK, Denton CP, et al. Short-term pulmonary function trends are predictive of mortality in interstitial lung disease
associated with systemic sclerosis
: pulmonary function trends in SSc-associated ILD. Arthritis Rheumatol 2017; 69:1670–1678.
24. Hoffmann-Vold A-M, Aaløkken TM, Lund MB, et al. Predictive value of serial high-resolution computed tomography
analyses and concurrent lung function tests in systemic sclerosis
: serial lung analyses in SSc. Arthritis Rheumatol 2015; 67:2205–2212.
25. Khanna D, Mittoo S, Aggarwal R, et al. Connective tissue disease-associated interstitial lung diseases (CTD-ILD)---report from OMERACT CTD-ILD Working Group. J Rheumatol 2015; 42:2168–2171.
26▪▪. Volkmann ER, Tashkin DP, Sim M, et al. Short-term progression of interstitial lung disease
in systemic sclerosis
predicts long-term survival in two independent clinical trial cohorts. Ann Rheum Dis 2019; 78:122–130.
This post hoc analysis of SLS I and II demonstrates that longitudinal, short-term declines in FVC and DLCO over 2 years are a better predictor of mortality than baseline FVC and DLCO.
27. Liu X, Mayes MD, Pedroza C, et al. Does C-reactive protein predict the long-term progression of interstitial lung disease
and survival in patients with early systemic sclerosis
? Arthritis Care Res (Hoboken) 2013; 65:1375–1380.
28. Winstone TA, Assayag D, Wilcox PG, et al. Predictors of mortality and progression in scleroderma-associated interstitial lung disease
. Chest 2014; 146:422–436.
29. Lee SH, Park JS, Kim SY, et al. Comparison of CPI and GAP models in patients with idiopathic pulmonary fibrosis: a nationwide cohort study. Sci Rep 2018; 8:4784.
30. Ley B, Ryerson CJ, Vittinghoff E, et al. A multidimensional index and staging system for idiopathic pulmonary fibrosis. Ann Intern Med 2012; 156:684.
31. Wells AU, Desai SR, Rubens MB, et al. Idiopathic pulmonary fibrosis: a composite physiologic index derived from disease extent observed by computed tomography. Am J Respir Crit Care Med 2003; 167:962–969.
32▪. Wu W, Jordan S, Becker MO, et al. Prediction of progression of interstitial lung disease
in patients with systemic sclerosis
: the SPAR model. Ann Rheum Dis 2018; 77:1326–1332.
A prospective cohort study of patients with SSc with mild ILD by Goh criteria is utilized to create a risk prediction model (‘SPAR’).
33▪. Morisset J, Vittinghoff E, Elicker BM, et al. Mortality risk prediction in scleroderma-related interstitial lung disease
: the SADL model. Chest 2017; 152:999–1007.
A prospective cohort study of patients with SSc with mild ILD by Goh criteria is utilized to create a risk prediction model (‘SADL’).
34. Chowaniec M, Skoczyńska M, Sokolik R, et al. Interstitial lung disease
in systemic sclerosis
: challenges in early diagnosis and management. Reumatologia 2018; 56:249–254.
35. Fischer A, Strek ME, Cottin V, et al. Proceedings of the American College of Rheumatology/Association of Physicians of Great Britain and Ireland Connective Tissue Disease-Associated Interstitial Lung Disease
Summit: a multidisciplinary approach to address challenges and opportunities. Arthritis Rheumatol 2019; 71:182–195.
36. Suliman YA, Dobrota R, Huscher D, et al. Brief Report: Pulmonary function tests: high rate of false-negative results in the early detection and screening
of scleroderma-related interstitial lung disease
: pulmonary function tests to screen for SSc-related ILD. Arthritis Rheumatol 2015; 67:3256–3261.
37. Showalter K, Hoffmann A, Rouleau G, et al. Performance of forced vital capacity and lung diffusion cutpoints for associated radiographic interstitial lung disease
in systemic sclerosis
. J Rheumatol 2018; 45:1572–1576.
38. Raghu G, Collard HR, Egan JJ, et al. An official ATS/ERS/JRS/ALAT statement: idiopathic pulmonary fibrosis: evidence-based guidelines for diagnosis and management. Am J Respir Crit Care Med 2011; 183:788–824.
39. Launay D, Remy-Jardin M, Michon-Pasturel U, et al. High resolution computed tomography in fibrosing alveolitis associated with systemic sclerosis
. J Rheumatol 2006; 33:1789–1801.
40. Podolanczuk AJ, Oelsner EC, Barr RG, et al. High-attenuation areas on chest computed tomography and clinical respiratory outcomes in community-dwelling adults. Am J Respir Crit Care Med 2017; 196:1434–1442.
41. Podolanczuk AJ, Oelsner EC, Barr RG, et al. High attenuation areas on chest computed tomography in community-dwelling adults: the MESA study. Eur Respir J 2016; 48:1442–1452.
42▪▪. Bernstein EJ, Khanna D, Lederer DJ. Screening high-resolution computed tomography
of the chest to detect interstitial lung disease
in systemic sclerosis
: a global survey of rheumatologists. Arthritis Rheumatol 2018; 70:971–972.
A global survey of SSc experts and general rheumatologists that showed significant variation in both HRCT ordering practices and indications to initiate HRCT screening for ILD in patients with SSc.
43. Ferro F, Delle Sedie A. The use of ultrasound for assessing interstitial lung involvement in connective tissue diseases. Clin Exp Rheumatol 2018; 36 (Suppl 114(5)):165–170.
44. Xie HQ, Zhang WW, Sun DS, et al. A simplified lung ultrasound for the diagnosis of interstitial lung disease
in connective tissue disease: a meta-analysis. Arthritis Res Therapy 2019; 21:93.
45. Hassan RI, Lubertino LI, Barth MA, et al. Lung ultrasound as a screening
method for interstitial lung disease
in patients with systemic sclerosis
. J Clin Rheumatol 2018; 1: doi: 10.1097/RHU.0000000000000860. [Epub ahead of print].
46. Milanese G, Mannil M, Martini K, et al. Lung ultrasound for the screening
of interstitial lung disease
in very early systemic sclerosis
. Ann Rheum Dis 2013; 72:390–395.
47. Gigante A, Rossi Fanelli F, Lucci S, et al. Lung ultrasound in systemic sclerosis
: correlation with high-resolution computed tomography
, pulmonary function tests and clinical variables of disease. Intern Emerg Med 2016; 11:213–217.
48. Zhang X, Zhou B, Osborn T, et al. Lung ultrasound surface wave elastography for assessing interstitial lung disease
. IEEE Trans Biomed Eng 2019; 66:1346–1352.
49. Montesi SB, Caravan P. Novel imaging approaches in systemic sclerosis
-associated interstitial lung disease
. Curr Rheumatol Rep 2019; 21:25.
50. Gargani L, Bruni C, De Marchi D, et al. FRI0439 The promising role of lung MRI in detecting systemic sclerosis
(SSc)-related interstitial lung disease
(ILD). Ann Rheum Dis 2018; 77 (Suppl 2):749–750.
51. Schniering J, Benešová M, Brunner M, et al. Visualisation of interstitial lung disease
by molecular imaging of integrin αvβ3 and somatostatin receptor 2. Ann Rheum Dis 2019; 78:218–227.
52. Matsushita T, Takehara K. An update on biomarker discovery and use in systemic sclerosis
. Expert Rev Mol Diagn 2017; 17:823–833.
53. Dellaripa PF. Interstitial lung disease
in the connective tissue diseases; a paradigm shift in diagnosis and treatment. Clin Immunol 2018; 186:71–73.
54. Wu M, Baron M, Pedroza C, et al. CCL2 in the circulation predicts long-term progression of interstitial lung disease
in patients with early systemic sclerosis
: data from two independent cohorts: CCL2 predicts SSc-related ILD progression. Arthritis Rheumatol 2017; 69:1871–1878.
55. Hoffmann-Vold A-M, Weigt SS, Palchevskiy V, et al. Augmented concentrations of CX3CL1 are associated with interstitial lung disease
in systemic sclerosis
. Kuwana M, editor. PLOS ONE 2018; 13:e0206545.
56. Salazar GA, Kuwana M, Wu M, et al. KL-6 But Not CCL-18 is a predictor of early progression in systemic sclerosis
-related interstitial lung disease
. J Rheumatol 2018; 45:1153–1158.
57. Weigold F, Günther J, Pfeiffenberger M, et al. Antibodies against chemokine receptors CXCR3 and CXCR4 predict progressive deterioration of lung function in patients with systemic sclerosis
. Arthritis Res Therapy 2018; 20:52.
58▪▪. Elhai M, Hoffmann-Vold AM, Avouac J, et al. Performance of candidate serum biomarkers for systemic sclerosis
–associated interstitial lung disease
. Arthritis Rheumatol 2019; 71:972–982.
This is the largest study to date analysing potential lung biomarkers in SSc with prospective standardized assessments of HRCT and PFTs.
59. Yanaba K, Hasegawa M, Takehara K, Sato S. Comparative study of serum surfactant protein-D and KL-6 concentrations in patients with systemic sclerosis
as markers for monitoring the activity of pulmonary fibrosis. J Rheumatol 2004; 31:1112–1120.
60. Hant FN, Ludwicka-Bradley A, Wang H-J, et al. Surfactant protein D and KL-6 as serum biomarkers of interstitial lung disease
in patients with scleroderma. J Rheumatol 2009; 36:773–780.
61. Benyamine A, Heim X, Resseguier N, et al. Elevated serum Krebs von den Lungen-6 in systemic sclerosis
: a marker of lung fibrosis and severity of the disease. Rheumatol Int 2018; 38:813–819.
62. Lee JS, Lee EY, Ha Y-J, et al. Serum KL-6 levels reflect the severity of interstitial lung disease
associated with connective tissue disease. Arthritis Res Therapy 2019; 21:58.
63. Tiev KP, Hua-Huy T, Kettaneh A, et al. Serum CC chemokine ligand-18 predicts lung disease worsening in systemic sclerosis
. Eur Respir J 2011; 38:1355–1360.
64. Schupp J, Becker M, Gunther J, et al. Serum CCL18 is predictive for lung disease progression and mortality in systemic sclerosis
. Eur Respir J 2014; 43:1530–1532.
65. Hoffmann-Vold A-M, Tennøe AH, et al. High level of chemokine CCL18 is associated with pulmonary function deterioration, lung fibrosis progression, and reduced survival in systemic sclerosis
. Chest 2016; 150:299–306.
66. Cao X, Hu S, Xu D, Li M, et al. Serum levels of Krebs von den Lungen-6 as a promising marker for predicting occurrence and deterioration of systemic sclerosis
-associated interstitial lung disease
from a Chinese cohort. Int J Rheum Dis 2019; 22:108–115.