Aetiology, Risk Factors, and Biomarkers in Systemic Sclerosis with Interstitial Lung Disease

Systemic sclerosis (SSc) is a complex, multi-organ, autoimmune disease. Lung fibrosis occurs in ~80% of patients with SSc; 25-30% develop progressive interstitial lung disease (ILD). The pathogenesis of fibrosis in SSc associated ILD (SSc-ILD) involves cellular injury, activation/differentiation of mesenchymal cells and morphological/biological changes in epithelial/endothelial cells. Risk factors for progressive SSc-ILD include older age, male sex, lung involvement on baseline high-resolution computed tomography, reduced diffusing capacity for carbon monoxide and reduced forced vital capacity. SSc-ILD is characterized by genetic risk architecture distinct from that associated with idiopathic pulmonary fibrosis (IPF). Presence of anti-Scl-70 antibodies and absence of anti-centromere antibodies indicate increased likelihood of progressive ILD. Elevated levels of serum Krebs von den Lungen-6 (KL6) and CRP are associated with SSc-ILD severity, although whether KL6 independently predicts SSc-ILD progression remains controversial. A promising prognostic indicator is serum chemokine (C-C motif) ligand 18. SSc-ILD shares similarities with IPF, although clear differences exist. Histologically, a non-specific interstitial pneumonia pattern is commonly observed in SSc-ILD, whereas IPF is defined by usual interstitial pneumonia. The course of SSc-ILD is variable, ranging from minor, stable disease to a progressive course, while all IPF patients experience progression of disease. Although appropriately treated SSc-ILD patients have better chances of stabilization and survival, a relentlessly progressive course, akin to IPF, is seen in a minority. Better understanding of cellular and molecular pathogenesis, genetic risk and distinctive features of SSc-ILD, and identification of robust prognostic biomarkers are needed for optimal disease management. This article is open access and distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives License 4.0 (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Relationship between FEV1 change and patient-reported outcomes in randomised trials of inhaled bronchodilators for stable COPD: a systematic review.

BACKGROUND: Interactions between spirometry and patient-reported outcomes in COPD are not well understood. This systematic review and study-level analysis investigated the relationship between changes in FEV1 and changes in health status with bronchodilator therapy. METHODS: Six databases (to October 2009) were searched to identify studies with long-acting bronchodilator therapy reporting FEV1 and health status, dyspnoea or exacerbations. Mean and standard deviations of treatment effects were extracted for each arm of each study. Relationships between changes in trough FEV1 and outcomes were assessed using correlations and random-effects regression modelling. The primary outcome was St George's Respiratory Questionnaire (SGRQ) total score. RESULTS: Thirty-six studies (≥ 3 months) were included. Twenty-two studies (23,654 patients) with 49 treatment arms each contributing one data point provided SGRQ data. Change in trough FEV1 and change in SGRQ total score were negatively correlated (r = -0.46, p < 0.001); greater increases in FEV1 were associated with greater reductions (improvements) in SGRQ. The correlation strengthened with increasing study duration from 3 to 12 months. Regression modelling indicated that 100 mL increase in FEV1 (change at which patients are more likely to report improvement) was associated with a statistically significant reduction in SGRQ of 2.5 (95% CI 1.9, 3.1), while a clinically relevant SGRQ change (4.0) was associated with 160.6 (95% CI 129.0, 211.6) mL increase in FEV1. The association between change in FEV1 and other patient-reported outcomes was generally weak. CONCLUSIONS: Our analyses indicate, at a study level, that improvement in mean trough FEV1 is associated with proportional improvements in health status

Ongoing clinical trials and treatment options for patients with systemic sclerosis-associated interstitial lung disease

SSc is a rare CTD that affects multiple organ systems, resulting in substantial morbidity and mortality. Evidence of interstitial lung disease (ILD) is seen in ∼80% of patients with SSc. Currently there is no approved disease-modifying treatment for ILD and few effective treatment options are available. CYC is included in treatment guidelines, but it has limited efficacy and is associated with toxicity. MMF is becoming the most commonly used medication in clinical practice in North America and the UK, but its use is not universal. Newer agents targeting the pathogenic mechanisms underlying SSc-ILD, including fibrotic and inflammatory pathways, lymphocytes, cell-cell and cell-extracellular membrane interactions, hold promise for better treatment outcomes, including improved lung function, patient-related outcomes and quality of life. Here we review ongoing trials of established and novel agents that are currently recruiting patients with SSc-ILD

Comparison of the variability of the annual rates of change in FEV 1 determined from serial measurements of the pre- versus post-bronchodilator FEV 1 over 5 years in mild to moderate COPD: Results of the lung health study

This is the final published version, available from BMC via the DOI in this record.Background: The impact of interventions on the progressive course of COPD is currently assessed by the slope of the annual decline in FEV 1 determined from serial measurements of the post-, in preference to the pre-, bronchodilator FEV 1. We therefore compared the yearly slope and the variability of the slope of the pre- versus the post-bronchodilator FEV 1 in men and women with mild to moderate COPD who participated in the 5-year Lung Health Study (LHS).Methods: Data were analyzed from 4484 of the 5887 LHS participants who had measurements of pre- and post-bronchodilator FEV 1 at baseline (screening visit 2) and all five annual visits. The annual rate of decline in FEV 1 (±SE) measured pre- and post-bronchodilator from the first to the fifth annual visit was estimated separately using a random coefficient model adjusted for relevant covariates. Analyses were performed separately within each of the three randomized intervention groups. In addition, individual rates of decline in pre- and post-bronchodilator FEV 1 were also determined for each participant. Furthermore, sample sizes were estimated for determining the significance of differences in slopes of decline between different interventions using pre- versus post-bronchodilator measurements.Results: Within each intervention group, mean adjusted and unadjusted slope estimates were slightly higher for the pre- than the post-bronchodilator FEV 1 (range of differences 2.6-5.2 ml/yr) and the standard errors around these estimates were only minimally higher for the pre- versus the post-bronchodilator FEV 1 (range 0.05-0.11 ml/yr). Conversely, the standard deviations of the mean FEV 1 determined at each annual visit were consistently slightly higher (range of differences 0.011 to 0.035 L) for the post- compared to the pre-bronchodilator FEV 1. Within each group, the proportion of individual participants with a statistically significant slope was similar (varying by only 1.4 to 2.7%) comparing the estimates from the pre- versus the post-bronchodilator FEV 1. However, sample size estimates were slightly higher when the pre- compared to the post-bronchodilator value was used to determine the significance of specified differences in slopes between interventions.Conclusion: Serial measurements of the pre-bronchodilator FEV 1 are generally sufficient for comparing the impact of different interventions on the annual rate of change in FEV 1. © 2012 Tashkin et al.; licensee BioMed Central Ltd

Identifying and characterizing COPD patients in US managed care. A retrospective, cross-sectional analysis of administrative claims data

<p>Abstract</p> <p>Background</p> <p>Chronic obstructive pulmonary disease (COPD) is the fourth leading cause of death among US adults and is projected to be the third by 2020. In anticipation of the increasing burden imposed on healthcare systems and payers by patients with COPD, a means of identifying COPD patients who incur higher healthcare utilization and costs is needed.</p> <p>Methods</p> <p>This retrospective, cross-sectional analysis of US managed care administrative claims data describes a practical way to identify COPD patients. We analyze 7.79 million members for potential inclusion in the COPD cohort, who were continuously eligible during a 1-year study period. A younger commercial population (7.7 million) is compared with an older Medicare population (0.115 million). We outline a novel approach to stratifying COPD patients using "complexity" of illness, based on occurrence of claims for given comorbid conditions. Additionally, a unique algorithm was developed to identify and stratify COPD exacerbations using claims data.</p> <p>Results</p> <p>A total of 42,565 commercial (median age 56 years; 51.4% female) and 8507 Medicare patients (median 75 years; 53.1% female) were identified as having COPD. Important differences were observed in comorbidities between the younger commercial versus the older Medicare population. Stratifying by complexity, 45.0%, 33.6%, and 21.4% of commercial patients and 36.6%, 35.8%, and 27.6% of older patients were low, moderate, and high, respectively. A higher proportion of patients with high complexity disease experienced multiple (≥2) exacerbations (61.7% commercial; 49.0% Medicare) than patients with moderate- (56.9%; 41.6%), or low-complexity disease (33.4%; 20.5%). Utilization of healthcare services also increased with an increase in complexity.</p> <p>Conclusion</p> <p>In patients with COPD identified from Medicare or commercial claims data, there is a relationship between complexity as determined by pulmonary and non-pulmonary comorbid conditions and the prevalence of exacerbations and utilization of healthcare services. Identification of COPD patients at highest risk of exacerbations using complexity stratification may facilitate improved disease management by targeting those most in need of treatment.</p