Acute exacerbation of idiopathic pulmonary fibrosis: usual interstitial pneumonitis vs. possible usual interstitial pneumonitis pattern

Smoking status and clinical outcome in idiopathic pulmonary fibrosis: a nationwide study

BACKGROUND

Smoking status has been linked to the development of idiopathic pulmonary fibrosis (IPF). However, the effect of smoking on the prognosis of patients with IPF is unclear. We aimed to investigate the association between smoking status and all-cause mortality or hospitalisation by using national health claims data.

METHODS

IPF cases were defined as people who visited medical institutions between January 2002 and December 2018 with IPF and rare incurable disease exempted calculation codes from the National Health Insurance Database. Total 10,182 patients with available data on smoking status were included in this study. Ever-smoking status was assigned to individuals with a history of smoking ≥ 6 pack-years. The multivariable Cox proportional hazard model was used to evaluate the association between smoking status and prognosis.

RESULTS

In the entire cohort, the mean age was 69.4 years, 73.9% were males, and 45.2% were ever smokers (current smokers: 14.2%; former smokers: 31.0%). Current smokers (hazard ratio [HR]: 0.709; 95% confidence interval [CI]: 0.643-0.782) and former smokers (HR: 0.926; 95% CI: 0.862-0.996) were independently associated with all-cause mortality compared with non-smokers. Current smokers (HR: 0.884; 95% CI: 0.827-0.945) and former smokers (HR: 0.909; 95% CI: 0.862-0.959) were also associated with a reduced risk of all-cause hospitalisation compared with non-smokers. A non-linear association between smoking amount and prognosis was found in a spline HR curve and showed increasing risk below 6 pack-years.

CONCLUSION

Ever-smoking status may be associated with favourable clinical outcomes in patients with IPF.

Elevated Expression of Growth Differentiation Factor-15 Is Associated With Acute Exacerbation of Idiopathic Pulmonary Fibrosis

Backgrounds

Growth differentiation factor 15 (GDF-15) is a highly divergent member of the TGF-β superfamily and has been implicated in various biological functions. However, the expression of GDF-15 in patients with acute exacerbation of idiopathic pulmonary fibrosis (AE-IPF) is unclear.

Method

The study included 47 AE-IPF patients, 61 stable IPF (S-IPF) subjects, and 31 healthy controls (HCs). Serum GDF-15 levels and their expression in the lung were measured. The correlation between serum GDF-15 and other clinical parameters and the risk factors for AE occurrence and the survival of IPF patients were analyzed.

Results

Serum GDF-15 levels were significantly elevated in AE-IPF patients (1279.22 ± 540.02 pg/ml) as compared with HCs (891.30 ± 479.90 pg/ml) or S-IPF subjects (107.82 ± 14.21 pg/ml) (both p < 0.001). The protein and mRNA expressions of GDF-15 in the lung of AE-IPF patients were significantly increased as compared with S-IPF cases (p = 0.007 and p = 0.026, respectively). The serum GDF-15 level was correlated with the clinical variables of inflammation, metabolism, and disease severity in IPF subjects (all p < 0.05). The GDF-15 serum concentration was significantly higher in decedents than in survivors (p = 0.005). A serum GDF-15 level above 989.3 pg/ml was a risk factor for AE occurrence (p = 0.04), and the level above 1,075.76 pg/ml was an independent predictor for survival in IPF cases (p = 0.007).

Conclusions

The GDF-15 level was significantly elevated in subjects with AE-IPF. GDF-15 could be a promising biomarker for AE occurrence and survival in IPF patients.

Clinical efficacy of Chinese herbs for supplementing qi and activating blood circulation combined with N-acetylcysteine in the treatment of idiopathic pulmonary fibrosis: A systematic review and network meta-analysis

BACKGROUND

Chinese herbs for supplementing qi and activating blood circulation (CH) combined with N-acetylcysteine (NAC) is widely used for idiopathic pulmonary fibrosis (IPF) in China, but there is a lack of literature to evaluate its efficacy and clinical value.

PURPOSE

This study compared CH + NAC with other treatments by network meta-analysis to clarify its clinical value.

METHODS

Cochrane Library, PubMed, Embase, Web of Science, China National Knowledge Infrastructure, WanFang Data, VIP Database, and China Biology Medicine were searched. Outcomes included lung function (DLCO (%), VC (%), FVC (%), FVC (L)), 6-min walking distance (6MWD), score of St George's respiratory questionnaire (SGRQ), blood gas analysis (PaO2, PaCO2). The data were analyzed by Review Manager 5.4, Stata 12.0 and ADDIS 1.16.5.

RESULTS

23 studies including 1390 patients (702 in intervention group and 688 in control group) were collected to compare 8 outcome indicators among different treatments involving CH, CH+NAC, CH+PFD, NAC, PFD and PFD+NAC on IPF. Network meta-analysis showed that CH was better than NAC in terms of DLCO (%) (MD = 5.14, 95%CI: 1.01 to 8.68) and 6MWD (MD = 49.17, 95%CI: 25.97 to 71.36) as well as PFD + NAC was better than NAC in terms of FVC (L) (MD = -0.56, 95%CI: -0.83 to -0.31). In rankings results, CH + NAC is the best in terms of FVC (%), SGRQ, PaO2 and PaCO2; CH is the best in terms of DLCO (%), VC (%) and 6MWD; CH + PFD is the best in terms of FVC (L).

CONCLUSION

CH related treatments may have advantages in the treatment of IPF and CH + NAC may have clinical application value. However, limited by the quality and quantity of researches included, more rational and scientific randomized controlled trials containing large sample sizes need to be conducted to further verify our conclusions.

The Extent of Honeycombing on Computed Tomography Cannot Predict the Treatment Outcome of Patients with Acute Exacerbations of Interstitial Lung Disease

Background

The purpose of this retrospective study was to clarify whether the presence of honeycombing on computed tomography (CT) can affect the prognosis of patients with acute exacerbations (AEs) of interstitial lung diseases (ILDs).

Methods

Clinical parameters including age, sex, Charlson Comorbidity Index Score (CCIS), blood biomarkers, and 3-month mortality were retrospectively compared between the CT honeycombing present and absent groups at the diagnosis of AEs of ILDs.

Results

Ninety-five patients who were on corticosteroid pulse therapy were assessed. Though log-rank tests showed that Kaplan–Meier survival curves of the high and low ground-glass opacity (GGO) score groups differed significantly in 3-month mortality in patients with AEs of idiopathic ILDs (P = 0.007) and overall patients (P = 0.045), there was no significant difference between the CT honeycombing present and absent groups in patients with AEs of idiopathic ILDs (P = 0.472) and AEs of secondary ILDs (P = 0.905), as well as of overall patients (P = 0.600). In addition, whereas CCIS (OR, 1.436; 95% CI, 1.156–1.842; P < 0.001) was a significant predictor of 3-month mortality in the CT honeycombing absent group, serum LDH (OR, 1.005; 95% CI, 1.002–1.007; P = 0.001) was a significant predictor in the CT honeycombing present group.

Conclusions

The clinical features of patients with or without honeycombing may differ due to the difference in prognostic factors, but these groups were found to have similar prognoses 3 months after AE onset, and clinicopathological examinations according to these groups are essential.

Mechanism of Fei-Xian Formula in the Treatment of Pulmonary Fibrosis on the Basis of Network Pharmacology Analysis Combined with Molecular Docking Validation

Objective

This study aimed to clarify the mechanism of Fei-Xian formula (FXF) in the treatment of pulmonary fibrosis based on network pharmacology analysis combined with molecular docking validation.

Methods

Firstly, ingredients in FXF with pharmacological activities, together with specific targets, were identified based on the BATMA-TCM and TCMSP databases. Then, targets associated with pulmonary fibrosis, which included pathogenic targets as well as those known therapeutic targets, were screened against the CTD, TTD, GeneCards, and DisGeNet databases. Later, Cytoscape was employed to construct a candidate component-target network of FXF for treating pulmonary fibrosis. In addition, for nodes within the as-constructed network, topological parameters were calculated using CytoHubba plug-in, and the degree value (twice as high as the median degree value for all the nodes) was adopted to select core components as well as core targets of FXF for treating pulmonary fibrosis, which were subsequently utilized for constructing the core network. Furthermore, molecular docking study was carried out on those core active ingredients together with the core targets using AutoDock Vina for verifying results of network pharmacology analysis. At last, OmicShare was employed for enrichment analysis of the core targets.

Results

Altogether 12 active ingredients along with 13 core targets were identified from our constructed core component-target network of FXF for the treatment of pulmonary fibrosis. As revealed by enrichment analysis, the 13 core targets mostly concentrated in regulating biological functions, like response to external stimulus (from oxidative stress, radiation, UV, chemical substances, and virus infection), apoptosis, cell cycle, aging, immune process, and protein metabolism. In addition, several pathways, like IL-17, AGE-RAGE, TNF, HIF-1, PI3K-AKT, NOD-like receptor, T/B cell receptor, and virus infection-related pathways, exerted vital parts in FXF in the treatment of pulmonary fibrosis.

Conclusions

FXF can treat pulmonary fibrosis through a “multicomponent, multitarget, and multipathway” mean. Findings in this work lay foundation for further exploration of the FXF mechanism in the treatment of pulmonary fibrosis.

Establishment of a Clinical Nomogram Model to Predict the Progression of COVID-19 to Severe Disease

BACKGROUND

Coronavirus disease 2019 (COVID-19) is a worldwide public health pandemic with a high mortality rate, among severe cases. The disease is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. It is important to ensure early detection of the virus to curb disease progression to severe COVID-19. This study aims to establish a clinical-nomogram model to predict the progression to severe COVID-19 in a timely and efficient manner.

METHODS

This retrospective study included 202 patients with COVID-19 who were admitted to the Fifth Affiliated Hospital of Sun Yat-sen University and Shiyan Taihe Hospital from January 17 to April 30, 2020. The patients were randomly assigned to the training dataset (n = 163, with 43 progressing to severe COVID-19) or the validation dataset (n = 39, with 10 progressing to severe COVID-19) at a ratio of 8:2. The optimal subset algorithm was applied to filter for the clinical factors most relevant to the disease progression. Based on these factors, the logistic regression model was fit to distinguish severe (including severe and critical cases) from non-severe (including mild and moderate cases) COVID-19. Sensitivity, specificity, and area under the curve (AUC) were calculated using the R software package to evaluate prediction performance. A clinical nomogram was established and performance assessed using the discrimination curve.

RESULTS

Risk factors, including demographic data, symptoms, laboratory and image findings, were recorded for the 202 patients. Eight of the 53 variables that were entered into the selection process were selected via the best subset algorithm to establish the predictive model; they included gender, age, BMI, CRP, D-dimer, TP, ALB, and involved-lobe. AUC, sensitivity, and specificity were 0.91, 0.84 and 0.86 for the training dataset, and 0.87, 0.66, and 0.80 for the validation dataset.

CONCLUSION

We established an efficient and reliable clinical nomogram model which showed that gender, age, and initial indexes including BMI, CRP, D-dimer, involved-lobe, TP, and ALB could predict the risk of progression to severe COVID-19.

Radix Astragali and Radix Angelicae Sinensis in the Treatment of Idiopathic Pulmonary Fibrosis: A Systematic Review and Meta-analysis

Introduction

There are many clinical studies in the treatment of idiopathic pulmonary fibrosis (IPF) with herbal medicine including Astragalus mongholicus Bunge, Radix Astragali (RA) and Angelica sinensis (Oliv.) Diels, Radix Angelicae Sinensis (RAS). These have obtained good curative effect. There is no systematic evaluation on the clinical efficacy of RA and RAS in patients with IPF. The aim of this systematic review and meta-analysis was to critically evaluate the current evidence of efficacy and safety of RA and RAS in IPF.

Methods

We searched the primary database for randomized controlled trial (RCT) of RA and RAS treating IPF. We assessed the quality of included studies using the Jadad rating scale and referred to the Cochrane Reviewer's Handbook for guidelines to assess the risk of bias. We extracted the main outcomes of included RCTs and a meta-analysis was conducted using the Cochrane Collaboration's RevMan5.3 software.

Results

Seventeen eligible RCTs were identified and made a systematic review and meta-analysis. Risk of bias and quality of included RCTs were carried out. The results of meta-analysis showed that total effective rate and traditional Chinese medicine syndrome effective rate were statistically significantly higher in the experimental group than the control group, main pulmonary function index, six minute walking distance and Borg scale questionnaire score were statistically significantly better in the experimental group than the control group and incidence of adverse reactions was statistically significantly lower in the experimental group than the control group.

Conclusion

RA and RAS are effective and safe in the treatment of IPF, which is beneficial to pulmonary function and exercise tolerance of these patients.