CYFRA 21-1 Predicts Progression in Idiopathic Pulmonary Fibrosis: A Prospective Longitudinal Analysis of the PROFILE Cohort

Tumor-associated antigens are associated with primary Sjögren's syndrome-related interstitial lung disease and disease activity

OBJECTIVES

Tumor-associated antigens (TAAs) have been shown to be associated with a variety of connective tissue diseases. However, the role of TAAs in primary Sjögren's syndrome (pSS) patients is still unclear. This study aims to explore the correlation between TAA levels and systemic clinical manifestations and disease activity in pSS patients.

METHODS

Data were retrospectively collected from 108 patients with pSS (pSS group) and 100 healthy subjects (HCs group). Comparison of clinical characteristics and serological parameters between the TAA-positive group and the TAA-negative group. The independent risk factors of TAAs positivity were analyzed by univariate and multivariate regression, and the receiver operating characteristic curve was used to analyze the diagnostic performance of TAAs for pSS-associated interstitial lung disease (pSS-ILD).

RESULTS

Compared with the control group, the positivity rates of CEA, CA125, CA15-3, and CYFRA21-1 were higher, and the levels of serum CA125, CA15-3, and CYFRA21-1were higher in the pSS group. The incidence of ILD, pleural effusion, pericardial effusion, and ESSDAI ≥5 in the TAA-positive group was higher than in the TAA-positive group. Multivariate logistic regression analysis showed that the incidence of ILD was identified as an independent risk factor for TAA positivity. The AUC of CEA, CYFRA21-1, and NSE in the diagnosis of pSS-ILD were 0.690, 0.840, and 0.872, respectively, and the combined diagnosis could reach 0.952.

CONCLUSION

Certain TAA-positive rates and serum levels were increased in pSS patients. The TAA-positive group is correlated with the ESSDAI scores. ILD was an independent risk factor for TAA positivity, and CYFRA21-1 and NSE had the best diagnostic value in patients with pSS-ILD.

A deeper evaluation of cytokeratin fragment 21-1 as a lung cancer tumor marker and comparison of different assays

Studies show CYFRA 21-1 fragments of cytokeratin 19 (CK19) to be promising biomarkers for non-small cell lung cancer (NSCLC). Although previous literature identifies specific CYFRA 21-1 antibody binding epitopes, the exact molecular weight of the CK19 fragment being detected by current assays is not well-documented. Serum samples from 58 patients (lung cancer (N = 36), control (N = 22)) were used to measure CYFRA 21-1 across four different quantification assays: enzyme-linked immunosorbent assay (ELISA), chemiluminescent assay (ChLIA), electrochemiluminescence immunoassay (ECLIA), and compensated interferometric reader (CIR). In the cancer group, correlation between ECLIA and ELISA was high (R(Pearson) = 0.948, r(Spearman) = 0.868) while correlation between ECLIA vs ChLIA and ECLIA vs CIR was low (R= 0.005, r = -0.0593), (R = 0.0275, r = 0.167), respectively. In the control group, correlation between ECLIA and ELISA was high (R = 0.861, r = 0.927) while correlation between ECLIA vs ChLIA and ECLIA vs CIR was low (R = 0.0079, r = -0.0593), (R = 0.0244, r = -0.102), respectively. Compared to ECLIA, concordance coefficients (p c ) were poor (p c < 0.90) across all assays except for cancers group in ELISA (p c = 0.913). ECLIA was the only assay to report control ranges above 1 ng/mL CYFRA 21-1 (ECLIA, 1.14-21.59 ng/mL; ELISA, 0.79-24.26 ng/mL; ChLIA, 0.062-0.691 ng/mL; 0.08-7.68 ng/mL). Differing sizes of the protein being measured by each assay may have a role in the discrepancies observed. Given the different CYFRA 21-1 concentration estimates among assays, further characterization of the fragment and its release during epithelial malignancies, such as NSCLC, is imperative to developing effective biomarker assays.

Clinical analysis of patients with idiopathic pulmonary fibrosis concurrent with surgery resectable lung cancer: a retrospective cohort study from perspective of ILD physicians

BACKGROUND

Surgery resection would improve idiopathic pulmonary fibrosis (IPF) patients with early-stage lung cancer (LC). However, most associated studies were published from surgeons. Interstitial lung disease (ILD) physicians involved in perioperative management would be helpful for improving patients with idiopathic pulmonary fibrosis combined with lung cancer (IPF-LC). To enhance the understanding of the clinical characteristics presented by patients with IPF-LC who have undergone surgical resection, and to explore the factors linked to unfavorable prognosis, our ILD physicians conducted this study.

METHODS

We retrospectively examined clinical records of IPF-LC patients at Peking Union Medical College Hospital from January 2014 to December 2023.Data related to clinical manifestations and treatment methods were collected. Patients underwent routine follow-up through clinical assessments and telephone consultations. The demographic, clinical, and laboratory features of 12 surviving patients and 8 deceased patients were comparatively analysed.

RESULTS

There were 30 males and 2 females, aged from 49 years to 82 years. Twenty-eight patients had a history of smoking. Twenty-five patients had at least one comorbidity and emphysema was the most common. IPF was diagnosed before LC in 8 patients but none of them were prescribed with anti-fibrotic medications. Twenty-four patients were simultaneously diagnosed with LC and IPF, and 7 of them were prescribed anti-fibrotic medications. After surgery, 27 patients were pathologically diagnosed with non-small cell lung cancer and 26 patients were classified as stage I or II lung cancer. During follow-up, 8 patients died, 12 patients lost follow-up and 12 patients survived. Among the 8 deceased patients, 5 patients died from acute exacerbation of IPF, one died from cancer progression and 2 died from surgical complications. The serum Cyfra211 level was higher and the lung cancer stage was more advanced in the non-survival group than in the survival group.

CONCLUSION

Most of our IPF-LC patients were elderly males with a history of smoking and had at least one comorbidity. Most of them were diagnosed with IPF and LC simultaneously. However, only one fifth were prescribed with pirfenidone or nintedanib. Acute exacerbation of IPF was the main cause of death. Similar to the LC patients, higher serum Cyfra211 levels and more advanced lung cancer stages were associated with a poor prognosis for our enrolled IPF-LC patients.

CLINICAL TRIAL NUMBER

Not applicable.

Machine learning potential predictor of idiopathic pulmonary fibrosis

Introduction

Idiopathic pulmonary fibrosis (IPF) is a severe chronic respiratory disease characterized by treatment challenges and poor prognosis. Identifying relevant biomarkers for effective early-stage risk prediction is therefore of critical importance.

Methods

In this study, we obtained gene expression profiles and corresponding clinical data of IPF patients from the GEO database. GO enrichment and KEGG pathway analyses were performed using R software. To construct an IPF risk prediction model, we employed LASSO-Cox regression analysis and the SVM-RFE algorithm. PODNL1 and PIGA were identified as potential biomarkers associated with IPF onset, and their predictive accuracy was confirmed using ROC curve analysis in the test set. Furthermore, GSEA revealed enrichment in multiple pathways, while immune function analysis demonstrated a significant correlation between IPF onset and immune cell infiltration. Finally, the roles of PODNL1 and PIGA as biomarkers were validated through in vivo and in vitro experiments using qRT-PCR, Western blotting, and immunohistochemistry.

Results

These findings suggest that PODNL1 and PIGA may serve as critical biomarkers for IPF onset and contribute to its pathogenesis.

Discussion

This study highlights their potential for early biomarker discovery and risk prediction in IPF, offering insights into disease mechanisms and diagnostic strategies.

A narrative review on lung injury: mechanisms, biomarkers, and monitoring

Lung injury is closely associated with the heterogeneity, severity, mortality, and prognosis of various respiratory diseases. Effective monitoring of lung injury is crucial for the optimal management and improved outcomes of patients with lung diseases. This review describes acute and chronic respiratory diseases characterized by significant lung injury and current clinical tools for assessing lung health. Furthermore, we summarized the mechanisms of lung cell death observed in these diseases and highlighted recently identified biomarkers in the plasma indicative of injury to specific cell types and scaffold structure in the lung. Last, we propose an artificial intelligence-driven lung injury monitoring model to assess disease severity, and predict mortality and prognosis, aiming to achieve precision and personalized medicine.

Emerging electrochemical biosensors for lung cancer-associated protein biomarker and miRNA detection

Lung cancer remains a major driver of global morbidity and mortality, and diagnosing lung tumors early in their development is vital to maximizing treatment efficacy and patient survival. Several biomarkers, including CYFRA 21-1, NSE, ProGRP, CEA, and miRNA, have been identified as reliable indicators for early lung cancer detection and monitoring treatment progress. However, the minute changes in the levels of these biomarkers during the early stages of disease necessitate advanced detection platforms. In this space, electrochemical biosensors have currently emerged as robust tools for early lung cancer screening and diagnosis owing to their low costs, rapid responses, and superior sensitivity and selectivity. This review provides an up-to-date overview of the application of electrochemiluminescence, photoelectrochemical, and other electrochemical analytical strategies for detecting lung cancer-associated protein biomarkers, and miRNA. This review compares these techniques to provide a concise overview of the principles underlying these electrochemical analytical methods, the preparation of their components, and the performance of the resulting biosensors. Lastly, a discussion of the challenges and opportunities associated with electrochemical biosensors detection of lung cancer-associated biomarkers are provided.

Sustained amphiregulin expression in intermediate alveolar stem cells drives progressive fibrosis

Idiopathic pulmonary fibrosis (IPF) is a progressive and fatal fibrotic disease. Recent studies have highlighted the persistence of an intermediate state of alveolar stem cells in IPF lungs. In this study, we discovered a close correlation between the distribution pattern of intermediate alveolar stem cells and the progression of fibrotic changes. We showed that amphiregulin (AREG) expression is significantly elevated in intermediate alveolar stem cells of mouse fibrotic lungs and IPF patients. High levels of serum AREG correlate significantly with profound deteriorations in lung function in IPF patients. We demonstrated that AREG in alveolar stem cells is both required and sufficient for activating EGFR in fibroblasts, thereby driving lung fibrosis. Moreover, pharmacological inhibition of AREG using a neutralizing antibody effectively blocked the initiation and progression of lung fibrosis in mice. Our study underscores the therapeutic potential of anti-AREG antibodies in attenuating IPF progression, offering a promising strategy for treating fibrotic diseases.

Cluster analysis of blood biomarkers to identify molecular patterns in pulmonary fibrosis: assessment of a multicentre, prospective, observational cohort with independent validation

BACKGROUND

Pulmonary fibrosis results from alveolar injury, leading to extracellular matrix remodelling and impaired lung function. This study aimed to classify patients with pulmonary fibrosis according to blood biomarkers to differentiate distinct disease patterns, known as endotypes.

METHODS

In this cluster analysis, we first classified patients from the PROFILE study, a multicentre, prospective, observational cohort of individuals with incident idiopathic pulmonary fibrosis or non-specific interstitial pneumonia in the UK (Nottingham University Hospitals, Nottingham; and Royal Brompton Hospital, London). 13 blood biomarkers representing extracellular matrix remodelling, epithelial stress, and thrombosis were measured by ELISA in the PROFILE study. We classified patients by unsupervised consensus clustering. To evaluate generalisability, a machine learning classifier trained on biomarker signatures derived from consensus clustering was applied to a replication dataset from the Australian Idiopathic Pulmonary Fibrosis Registry (AIPFR). Biomarker associations with mortality and change in percentage of predicted forced vital capacity (FVC%) were assessed, adjusting for age, gender, baseline FVC%, and antifibrotic treatment and steroid treatment before and after baseline. Mortality risk associated with the clusters in the PROFILE cohort was evaluated with Cox proportional hazards models, and mixed-effects models were used to analyse how clustering was associated with longitudinal FVC% in the PROFILE and AIPFR cohorts.

FINDINGS

455 of 580 participants from the PROFILE study (348 [76%] men and 107 [24%] women; mean age 72·4 years [SD 8·3]) were included in the analysis. Within this group, three clusters were identified based on blood biomarkers. A basement membrane collagen (BM) cluster (n=248 [55%]) showed high concentrations of PRO-C4, PRO-C28, C3M, and C6M, whereas an epithelial injury (EI) cluster (n=109 [24%]) showed high concentrations of MMP-7, SP-D, CYFRA211, CA19-9, and CA-125. The third cluster (crosslinked fibrin [XF] cluster; n=98 [22%]) had high concentrations of X-FIB. In the replication dataset (117 of 833 patients from AIPFR; 87 [74%] men and 30 [26%] women; mean age 72·9 years [SD 7·9]), we identified the same three clusters (BM cluster, n=93 [79%]; EI cluster, n=8 [7%]; XF cluster, n=16 [14%]). These clusters showed similarities with clusters in the PROFILE dataset regarding blood biomarkers and phenotypic signatures. In the PROFILE dataset, the EI and XF clusters were associated with increased mortality risk compared with the BM cluster (EI vs BM: adjusted hazard ratio [HR] 1·88 [95% CI 1·42-2·49], p<0·0001; XF vs BM: adjusted HR 1·53 [1·13-2·06], p=0·0058). The EI cluster showed the greatest annual FVC% decline, followed by the BM and XF clusters. A similar FVC% decline pattern was observed in these clusters in the AIPFR replication dataset.

INTERPRETATION

Blood biomarker clustering in pulmonary fibrosis identified three distinct blood biomarker signatures associated with lung function and prognosis, suggesting unique pulmonary fibrosis biomarker patterns. These findings support the presence of pulmonary fibrosis endotypes with the potential to guide targeted therapy development.

FUNDING

None.

Molecular Endotypes of Idiopathic Pulmonary Fibrosis: A Latent Class Analysis of Two Multicenter Observational Cohorts

Rationale: Idiopathic pulmonary fibrosis (IPF) causes irreversible fibrosis of the lung parenchyma. Although antifibrotic therapy can slow IPF progression, treatment response is variable. There exists a critical need to develop a precision medicine approach to IPF. Objectives: To identify and validate biologically driven molecular endotypes of IPF. Methods: Latent class analysis (LCA) was independently performed in prospectively recruited discovery (n = 875) and validation (n = 347) cohorts. Twenty-five plasma biomarkers associated with fibrogenesis served as class-defining variables. The association between molecular endotype and 4-year transplant-free survival was tested using multivariable Cox regression adjusted for baseline confounders. Endotype-dependent differential treatment response to future antifibrotic exposure was then assessed in a pooled cohort of patients naive to antifibrotic therapy at the time of biomarker measurement (n = 555). Measurements and Main Results: LCA independently identified two latent classes in both cohorts (P < 0.0001). WFDC2 (WAP four-disulfide core domain protein 2) was the most important determinant of class membership across cohorts. Membership in class 2 was characterized by higher biomarker concentrations and a higher risk of death or transplant (discovery, hazard ratio [HR], 2.02; 95% confidence interval [CI], 1.64-2.48; P < 0.001; validation, HR, 1.95; 95% CI, 1.34-2.82; P < 0.001). In pooled analysis, significant heterogeneity in treatment effect was observed between endotypes (P = 0.030 for interaction), with a favorable antifibrotic response in class 2 (HR, 0.64; 95% CI, 0.45-0.93; P = 0.018) but not in class 1 (HR, 1.19; 95% CI, 0.77-1.84; P = 0.422). Conclusions: In this multicohort study, we identified two novel molecular endotypes of IPF with divergent clinical outcomes and responses to antifibrotic therapy. Pending further validation, these endotypes could enable a precision medicine approach for future IPF clinical trials.

A multidimensional classifier to support lung transplant referral in patients with pulmonary fibrosis

BACKGROUND

Lung transplantation remains the sole curative option for patients with idiopathic pulmonary fibrosis (IPF), but donor organs remain scarce, and many eligible patients die before transplant. Tools to optimize the timing of transplant referrals are urgently needed.

METHODS

Least absolute shrinkage and selection operator was applied to clinical and proteomic data generated as part of a prospective cohort study of interstitial lung disease (ILD) to derive clinical, proteomic, and multidimensional logit models of near-term death or lung transplant within 18 months of blood draw. Model-fitted values were dichotomized at the point of maximal sensitivity and specificity, and decision curve analysis was used to select the best-performing classifier. We then applied this classifier to independent IPF and non-IPF ILD cohorts to determine test performance characteristics. Cohorts were restricted to patients aged ≤72 years with body mass index 18 to 32 to increase the likelihood of transplant eligibility.

RESULTS

IPF derivation, IPF validation, and non-IPF ILD validation cohorts consisted of 314, 105, and 295 patients, respectively. A multidimensional model comprising 2 clinical variables and 20 proteins outperformed stand-alone clinical and proteomic models. Following dichotomization, the multidimensional classifier predicted near-term outcome with 70% sensitivity and 92% specificity in the IPF validation cohort and 70% sensitivity and 80% specificity in the non-IPF ILD validation cohort.

CONCLUSIONS

A multidimensional classifier of near-term outcomes accurately discriminated this end-point with good test performance across independent IPF and non-IPF ILD cohorts. These findings support refinement and prospective validation of this classifier in transplant-eligible individuals.

Metabolic dysfunction associated steatotic liver disease in patients with plaque psoriasis: a case-control study and serological comparison

Background

The relationship between plaque psoriasis and both MASLD and lean MASLD has not been sufficiently explored in the current literature.

Method

This retrospective and observational study was carried out from January 2021 to January 2023 at The First Affiliated Hospital of Zhejiang Chinese Medical University. Patients diagnosed with plaque psoriasis and a control group consisting of individuals undergoing routine physical examinations were enrolled. The incidence of MASLD and lean MASLD among these groups was compared. Additionally, patients with plaque psoriasis were divided into those with MASLD, those with lean MASLD, and a control group with only psoriasis for a serological comparative analysis.

Results

The incidence of MASLD in the observation group and the control group was 43.67% (69/158) and 22.15% (35/158), respectively (p < 0.01). Furthermore, the incidence of lean MASLD within the observation group and the control group was 10.76% (17/158) and 4.43% (7/158), respectively (p < 0.01). After controlling for potential confounding variables, plaque psoriasis was identified as an independent risk factor for MASLD with an odds ratio of 1.88 (95% cl: 1.10-3.21). In terms of serological comparison, compared to the simple psoriasis group, we observed a significant elevation in the tumor marker CYFRA21-1 levels in both groups compared to the control group with simple psoriasis (p < 0.01). Moreover, the MASLD group exhibited elevated levels of inflammatory markers and psoriasis score, whereas these effects were mitigated in the lean MASLD group.

Conclusion

The prevalence of MASLD and lean MASLD is higher among patients with psoriasis. Those suffering from psoriasis along with MASLD show increased psoriasis scores and inflammatory markers compared to those without metabolic disorders. MASLD likely worsens psoriasis conditions, indicating the necessity of targeted health education for affected individuals to reduce the risk of MASLD, this education should include guidelines on exercise and diet. In serological assessments, elevated levels of cytokeratin 19 fragment (CYFRA21-1) were noted in both MASLD and lean MASLD groups, implying a potential synergistic role between psoriasis and MASLD.

Proteomic Biomarkers of Survival in Idiopathic Pulmonary Fibrosis

Rationale: Idiopathic pulmonary fibrosis (IPF) causes progressive lung scarring and high mortality. Reliable and accurate prognostic biomarkers are urgently needed. Objectives: To identify and validate circulating protein biomarkers of IPF survival. Methods: High-throughput proteomic data were generated using prospectively collected plasma samples from patients with IPF from the Pulmonary Fibrosis Foundation Patient Registry (discovery cohort) and the Universities of California, Davis; Chicago; and Virginia (validation cohort). Proteins associated with three-year transplant-free survival (TFS) were identified using multivariable Cox proportional hazards regression. Those associated with TFS after adjustment for false discovery in the discovery cohort were advanced for testing in the validation cohort, with proteins maintaining TFS association with consistent effect direction considered validated. After combining cohorts, functional analyses were performed, and machine learning was used to derive a proteomic signature of TFS. Measurements and Main Results: Of 2,921 proteins tested in the discovery cohort (n = 871), 231 were associated with differential TFS. Of these, 140 maintained TFS association with consistent effect direction in the validation cohort (n = 355). After cohorts were combined, the validated proteins with the strongest TFS association were latent-transforming growth factor β-binding protein 2 (hazard ratio [HR], 2.43; 95% confidence interval [CI] = 2.09-2.82), collagen α-1(XXIV) chain (HR, 2.21; 95% CI = 1.86-2.39), and keratin 19 (HR, 1.60; 95% CI = 1.47-1.74). In decision curve analysis, a proteomic signature of TFS outperformed a similarly derived clinical prediction model. Conclusions: In the largest proteomic investigation of IPF outcomes performed to date, we identified and validated 140 protein biomarkers of TFS. These results shed important light on potential drivers of IPF progression.

Meaningful Endpoints for Idiopathic Pulmonary Fibrosis (IPF) Clinical Trials: Emphasis on 'Feels, Functions, Survives'. Report of a Collaborative Discussion in a Symposium with Direct Engagement from Representatives of Patients, Investigators, the National Institutes of Health, a Patient Advocacy Organization, and a Regulatory Agency

Background: Idiopathic pulmonary fibrosis (IPF) carries significant mortality and unpredictable progression, with limited therapeutic options. Designing trials with patient-meaningful endpoints, enhancing the reliability and interpretability of results, and streamlining the regulatory approval process are of critical importance to advancing clinical care in IPF. Methods: A landmark in-person symposium in June 2023 assembled 43 participants from the US and internationally, including patients with IPF, investigators, and regulatory representatives, to discuss the immediate future of IPF clinical trial endpoints. Patient advocates were central to discussions, which evaluated endpoints according to regulatory standards and the FDA's 'feels, functions, survives' criteria. Results: Three themes emerged: 1) consensus on endpoints mirroring the lived experiences of patients with IPF; 2) consideration of replacing forced vital capacity (FVC) as the primary endpoint, potentially by composite endpoints that include 'feels, functions, survives' measures or FVC as components; 3) support for simplified, user-friendly patient-reported outcomes (PROs) as either components of primary composite endpoints or key secondary endpoints, supplemented by functional tests as secondary endpoints and novel biomarkers as supportive measures (FDA Guidance for Industry (Multiple Endpoints in Clinical Trials) available at: https://www.fda.gov/media/162416/download). Conclusions: This report, detailing the proceedings of this pivotal symposium, suggests a potential turning point in designing future IPF clinical trials more attuned to outcomes meaningful to patients, and documents the collective agreement across multidisciplinary stakeholders on the importance of anchoring IPF trial endpoints on real patient experiences-namely, how they feel, function, and survive. There is considerable optimism that clinical care in IPF will progress through trials focused on patient-centric insights, ultimately guiding transformative treatment strategies to enhance patients' quality of life and survival.

Circulating biomarker analyses in a longitudinal cohort of patients with IPF

Idiopathic pulmonary fibrosis (IPF) is an incurable interstitial lung disease characterized by fibrosis. Two FDA-approved drugs, pirfenidone and nintedanib, only modestly prolong survival. In this study, we asked whether levels of select circulating biomarkers in patients with IPF demonstrated changes in response to treatment over time and whether treatment with pirfenidone and nintedanib led to differential biomarker expression. Serial plasma samples from 48 patients with IPF on usual treatment and six healthy volunteers were analyzed to identify differentially expressed blood protein. Hypothesis-driven potential biomarker selection was based on recent literature, internal preclinical data, and the PROLIFIC Consortium (Schafer P. 6th Annual IPF Summit. Boston, MA, 2022) proposed biomarkers of pulmonary fibrosis. We compared our findings to public databases to provide insights into relevant signaling pathways in IPF. Of the 26 proteins measured, we found that 11 (SP-D, TIMP1, MMP7, CYFRA21-1, YKL40, CA125, sICAM, IP-10, MDC, CXCL13) were significantly elevated in patients with IPF compared with healthy volunteers but their levels did not significantly change over time. In the IPF samples, seven proteins were elevated in the treatment group compared with the no-treatment group. However, protein profiles were not distinguishable between patients on pirfenidone versus nintedanib. We demonstrated that most proteins differentially detected in our samples were predicted to be secreted from the lung epithelial or interstitial compartments. However, a significant minority of the proteins are not known to be transcriptionally expressed by lung cells, suggesting an ongoing systemic response. Understanding the contributions of the systemic response in IPF may be important as new therapeutics are developed.NEW & NOTEWORTHY In this study, we confirmed protein expression differences in only a subset of predicted biomarkers from IPF and control subjects. Most differentially expressed proteins were predicted to be secreted from lung cells. However, a significant minority of the proteins are not known to be transcriptionally expressed by lung cells, suggesting an ongoing systemic response. The contributions of the systemic response in IPF may be important as new therapeutics are developed.

Antifibrotic Drugs against Idiopathic Pulmonary Fibrosis and Pulmonary Fibrosis Induced by COVID-19: Therapeutic Approaches and Potential Diagnostic Biomarkers

The COVID-19 pandemic has had a significant impact on the health and economy of the global population. Even after recovery from the disease, post-COVID-19 symptoms, such as pulmonary fibrosis, continue to be a concern. This narrative review aims to address pulmonary fibrosis (PF) from various perspectives, including the fibrotic mechanisms involved in idiopathic and COVID-19-induced pulmonary fibrosis. On the other hand, we also discuss the current therapeutic drugs in use, as well as those undergoing clinical or preclinical evaluation. Additionally, this article will address various biomarkers with usefulness for PF prediction, diagnosis, treatment, prognosis, and severity assessment in order to provide better treatment strategies for patients with this disease.

Predictive biomarkers of disease progression in idiopathic pulmonary fibrosis

Idiopathic pulmonary fibrosis (IPF) is a chronic interstitial disease that cannot be cured, and treatment options for IPF are very limited. Early diagnosis, close monitoring of disease progression, and timely treatment are therefore the best options for patients due to the irreversibility of IPF. Effective markers help doctors judge the development and prognosis of disease. Recent research on traditional biomarkers (KL-6, SP-D, MMP-7, TIMPs, CCL18) has provided novel ideas for predicting disease progression and prognosis. Some emerging biomarkers (HE4, GDF15, PRDX4, inflammatory cells, G-CSF) also provide more possibilities for disease prediction. In addition to markers in serum and bronchoalveolar lavage fluid (BALF), some improvements related to the GAP model and chest HRCT also show good predictive ability for disease prognosis.

Prognostic value of serum oncomarkers for patients hospitalized with acute exacerbation of interstitial lung disease

BACKGROUND

Different types of inflammatory processes and fibrosis have been implicated in the pathogenesis of interstitial lung disease (ILD), a heterogeneous, diffuse, parenchymal lung disease. Acute exacerbation (AE) of ILD is characterized by significant respiratory deterioration and is associated with high mortality rates. Several serum oncomarkers have been used to determine the prognosis of ILD; however, the prognostic value of serum oncomarker levels in patients with AE-ILD remains unclear.

OBJECTIVE

To evaluate the prognostic value of serum oncomarker levels in patients with AE-ILD and its main subtypes.

DESIGN

Retrospective study.

METHODS

The serum levels of 8 oncomarkers in 281 patients hospitalized with AE-ILD at our institution between 2017 and 2022 were retrospectively reviewed. The baseline characteristics and serum oncomarker levels were compared between the survival and non-survival groups of AE-ILD and its main subtypes. Multivariate logistic regression analysis was performed to identify independent prognosis-related markers, and the best prognostic predictor was analyzed using receiver operating characteristic curve (ROC) analysis.

RESULT

Idiopathic pulmonary fibrosis (IPF; n = 65), idiopathic nonspecific interstitial pneumonia (iNSIP; n = 26), and connective tissue disease-associated interstitial lung disease (CTD-ILD; n = 161) were the three main subtypes of ILD. The in-hospital mortality rate among patients with AE-ILD was 21%. The serum oncomarker levels of most patients with AE-ILD and its main subtypes in the non-survival group were higher than those in the survival group. Multivariate analysis revealed that ferritin and cytokeratin 19 fragments (CYFRA21-1) were independent prognostic risk factors for patients hospitalized with AE-ILD or AE-CTD-ILD. CYFRA21-1 was identified as an independent prognostic risk factor for patients hospitalized with AE-IPF or AE-iNSIP.

CONCLUSION

CYFRA21-1 may be a viable biomarker for predicting the prognosis of patients with AE-ILD, regardless of the underlying subtype of ILD. Ferritin has a prognostic value in patients with AE-ILD or AE-CTD-ILD.

Combination of BAL and Computed Tomography Differentiates Progressive and Non-progressive Fibrotic Lung Diseases

Rationale: Identifying patients with pulmonary fibrosis (PF) at risk of progression can guide management. Objectives: To explore the utility of combining baseline BAL and computed tomography (CT) in differentiating progressive and nonprogressive PF. Methods: The derivation cohort consisted of incident cases of PF for which BAL was performed as part of a diagnostic workup. A validation cohort was prospectively recruited with identical inclusion criteria. Baseline thoracic CT scans were scored for the extent of fibrosis and usual interstitial pneumonia (UIP) pattern. The BAL lymphocyte proportion was recorded. Annualized FVC decrease of >10% or death within 1 year was used to define disease progression. Multivariable logistic regression identified the determinants of the outcome. The optimum binary thresholds (maximal Wilcoxon rank statistic) at which the extent of fibrosis on CT and the BAL lymphocyte proportion could distinguish disease progression were identified. Measurements and Main Results: BAL lymphocyte proportion, UIP pattern, and fibrosis extent were significantly and independently associated with disease progression in the derivation cohort (n = 240). Binary thresholds for increased BAL lymphocyte proportion and extensive fibrosis were identified as 25% and 20%, respectively. An increased BAL lymphocyte proportion was rare in patients with a UIP pattern (8 of 135; 5.9%) or with extensive fibrosis (7 of 144; 4.9%). In the validation cohort (n = 290), an increased BAL lymphocyte proportion was associated with a significantly lower probability of disease progression in patients with nonextensive fibrosis or a non-UIP pattern. Conclusions: BAL lymphocytosis is rare in patients with extensive fibrosis or a UIP pattern on CT. In patients without a UIP pattern or with limited fibrosis, a BAL lymphocyte proportion of ⩾25% was associated with a lower likelihood of progression.

Disease progression in patients with usual interstitial pneumonia and probable UIP patterns on computed tomography with various underlying etiologies: a retrospective cohort study

Background

Usual interstitial pneumonia (UIP) is a pattern of interstitial pneumonia that is caused by different etiologies. This study aimed to investigate the transplant-free survival (TFS) and the decline in forced vital capacity (FVC) of the patients with UIP and probable UIP patterns on CT caused by various underlying conditions.

Methods

A retrospective cohort study was conducted, enrolling patients with interstitial lung disease exhibiting a CT pattern consistent with UIP or probable UIP. Clinical and prognostic data of patients categorized by the etiology were compared.

Results

A total of 591 patients were included and classified into the following groups: idiopathic pulmonary fibrosis (IPF) (n = 320), connective tissue disease (CTD)-UIP (n = 229), asbestosis-UIP (n = 28), and hypersensitivity pneumonitis (HP)-UIP (n = 14). Advanced age, elevated levels of serum cytokeratin fraction 21-1 and percentage of neutrophils in bronchoalveolar lavage were observed in all groups. IPF patients showed a more rapid decline in FVC (133.9 mL/year) compared to CTD-UIP (24.5 mL/year, p = 0.001) and asbestosis-UIP (61.0 mL/year, p = 0.008) respectively. Sub-analysis of CTD-UIP revealed that patients with rheumatoid arthritis (RA)-UIP (88.1 mL/year) or antineutrophil cytoplasmic antibody-associated vasculitis (AAV)-UIP (72.9 mL/year) experienced a faster deterioration in FVC compared to those with primary Sjögren's syndrome (pSS)-UIP (25.9 mL/year, p < 0.05). Kaplan-Meier curves showed that IPF had the poorest TFS (median 55.9 months), followed by HP-UIP (57.5 months), CTD-UIP (66.7 months), and asbestosis-UIP (TFS not reached). RA-UIP or AAV-UIP did not exhibit any prognostic advantages compared to IPF, while asbestosis-UIP and pSS-UIP showed better survival rates.

Conclusion

Patients with UIP caused by different underlying conditions share certain common features, but the trajectories of disease progression and survival outcomes differ.

Variability of serum CYFRA 21 - 1 and its susceptibility to clinical characteristics in individuals without cancer: a 4-year retrospective analysis

BACKGROUND

CYFRA 21 - 1 is a useful marker for diagnosing and monitoring lung cancer. However, its stability remains unclear. Moreover, while its applicability to screening is now being investigated, CYFRA 21 - 1 levels in individuals without cancer, who are targets for cancer screening, have not yet been the focus of research. Therefore, the present study investigated variability in and the factors increasing serum CYFRA 21 - 1 levels.

METHODS

This retrospective study recruited 951 individuals undergoing annual medical examinations for six years. We used data obtained in the first four years. Variability in serum CYFRA 21 - 1 levels over a period of four years were investigated. CYFRA 21 - 1 was categorized as normal (≤ 3.5 ng/ml) or elevated (> 3.5 ng/ml). The rate of an elevated level in one visit and the transition from an elevated to normal level between visits were visualized. A multiple logistic regression model was used to study the relationships between the frequency of elevated CYFRA 21 - 1 levels and clinical characteristics, such as age, sex, body mass index, weight changes, and the smoking status.

RESULTS

Approximately 5% of subjects had elevated CYFRA 21 - 1 levels once in five tests over four years, while 15% had elevated CYFRA 21 - 1 levels once or more. Among subjects with elevated CYFRA 21 - 1 levels in one blood test, between 63 and 72% had normal levels in the next test. The median CYFRA 21 - 1 level in subjects with elevations in one blood test significantly decreased in the next test at all four time points. The frequency of elevated CYFRA 21 - 1 levels was associated with an older age [odds ratio (OR) = 6.99, 95% confidence interval (CI) = 3.01-16.2], current heavy smoking (OR = 3.46, 95% CI = 1.52-7.9), and weight loss (OR = 1.86, 95% CI = 1.07-3.24).

CONCLUSIONS

Variability in and the factors increasing serum CYFRA 21 - 1 levels beyond the cut-off value need to be considered when interpretating CYFRA 21 - 1 test results. The future application of CYFRA 21 - 1 to lung cancer screening may require more than a single measurement.

Contemporary Concise Review 2022: Interstitial lung disease

Novel genetic associations for idiopathic pulmonary fibrosis (IPF) risk have been identified. Common genetic variants associated with IPF are also associated with chronic hypersensitivity pneumonitis. The characterization of underlying mechanisms, such as pathways involved in myofibroblast differentiation, may reveal targets for future treatments. Newly identified circulating biomarkers are associated with disease progression and mortality. Deep learning and machine learning may increase accuracy in the interpretation of CT scans. Novel treatments have shown benefit in phase 2 clinical trials. Hospitalization with COVID-19 is associated with residual lung abnormalities in a substantial number of patients. Inequalities exist in delivering and accessing interstitial lung disease specialist care.