Biomarkers as a Prognostic Factor in COPD Exacerbation: A Cohort Study

Factors associated with risk of death in hospitalized patients for exacerbation of chronic obstructive pulmonary disease: an updated scoping review

INTRODUCTION

The Exacerbation of Chronic Obstructive Pulmonary Disease (ECOPD), especially if leading to hospitalization, increases the risk of death. Our scoping review aims to identify updated mortality risk factors for both short- and long-term periods.

AREAS COVERED

A comprehensive search, covering the period from January 2013 to February 2024, was performed to identify eligible studies that consider factors associated with death in hospitalized ECOPD. We considered short-term mortality, up to one year (including in-hospital mortality, IHM) and long-term mortality over one year, without time limits. We excluded studies concerning the intensive care area.

EXPERT OPINION

We considered 38 studies, 32 and 8 reporting data about short- and long-term mortality, respectively. Two studies consider both periods. Several factors, some already known, others newly identified, have been evaluated and discussed. Some of these were related to the characteristics and severity of COPD (age, body mass index, lung impairment), and some considered the response to ECOPD. In this last context, we focused on the increasing role of biomarkers in predicting the mortality of patients, particularly IHM. Our factors associated with a worse prognosis may be helpful in clinical practice to identify patients at risk and, subsequently, determine a personalized approach.

Comprehensive Nomograms Using Routine Biomarkers Beyond Eosinophil Levels: Enhancing Predictability of Corticosteroid Treatment Outcomes in AECOPD

Purpose

Patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD) exhibit heterogeneous responses to corticosteroid treatment. We aimed to determine whether combining eosinophil levels with other routine clinical indicators can enhance the predictability of corticosteroid treatment outcomes and to come up with a scoring system.

Patients and Methods

Consecutive patients admitted with AECOPD receiving corticosteroid treatment between July 2013 and March 2022 at Beijing Chao-Yang Hospital were retrospectively analyzed. Data on patients' demographics, smoking status, hospitalization for AECOPD in the previous year, comorbidities, blood laboratory tests, in-hospital treatment and clinical outcomes were collected. Least absolute shrinkage and selection operator (LASSO) regression and backward logistic regression were used for predictor selection, and predictive nomograms were developed. The discrimination and calibration of the nomograms were assessed using the area under the receiver operating curve (AUC) and calibration plots. Internal validation was performed using the 500-bootstrap method, and clinical utility was evaluated using decision curve analysis (DCA).

Results

Among the 3254 patients included, 804 (24.7%) had treatment failure. A nomogram of eosinophils, platelets, C-reactive protein (CRP), low density lipoprotein cholesterol, prognostic nutritional index (PNI), hospitalization for AECOPD in the previous year, ischemic heart diseases and chronic hepatic disease was developed to predict treatment failure for patients with a smoking history. For patients without a smoking history, a nomogram of CRP, PNI, ischemic heart diseases and chronic hepatic disease was developed. Although the AUCs of these two nomograms were only 0.644 and 0.647 respectively, they were significantly superior to predictions based solely on blood eosinophil levels.

Conclusion

We developed easy-to-use comprehensive nomograms utilizing readily available clinical biomarkers related to inflammation, nutrition and immunity, offering modestly enhanced predictive value for treatment outcomes in corticosteroid-treated patients with AECOPD. Further investigations into novel biomarkers and additional patient data are imperative to optimize the predictive performance.

Prognostic Value of Serum Cholinesterase Levels for In-Hospital Mortality among Patients with Acute Exacerbation of Chronic Obstructive Pulmonary Disease

Cholinesterase (ChE) is associated with the pathogenesis of chronic obstructive pulmonary disease (COPD), including chronic airway inflammation and oxidation/antioxidant imbalance. However, the relationship between serum ChE levels and survival outcomes of patients hospitalized with acute exacerbations of COPD (AECOPD) is unknown. In this retrospective single-center study, we investigated the ability of the serum ChE level to predict in-hospital death in patients hospitalized with AECOPD. The clinicopathological data, including serum ChE levels as well as clinical and biochemical indicators were extracted for 477 patients from the hospital records and analyzed. Our results demonstrated that AECOPD patients with lower serum ChE levels were associated with increased mortality, frequent hospitalization due to acute exacerbations (AE) in the past year, and longer hospital stay. The optimal cutoff value for the serum ChE level was 4323 U/L. The area under the ROC curve (AUC) values for predicting in-hospital mortality based on the serum ChE level was 0.79 (95% confidence interval (CI), 0.72-0.85). Multivariate logistic regression analysis demonstrated that serum ChE level ≤ 4323 U/L (odds ratio (OR) 9.09, 95% CI 3.43-28.3, p < 0.001), age-adjusted Charlson comorbidity index (aCCI), and the number of hospitalizations due to AE in the past year were independent risk factors for predicting the in-hospital mortality of AECOPD patients. In conclusion, our study demonstrated that low serum ChE levels were associated with significantly higher in-hospital mortality rates of patients hospitalized with AECOPD. Therefore, serum ChE level is a promising prognostic predictor of hospitalized AECOPD patients.

Clinical significance of the neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio in acute exacerbations of COPD: present and future

Acute exacerbations of chronic obstructive pulmonary disease (AECOPD) are a leading cause of hospitalisation and death in COPD patients. In addition to the identification of better strategies to prevent AECOPD, there is an intense focus on discovering novel markers of disease severity that enhance risk stratification on hospital admission for the targeted institution of aggressiveversussupportive treatments. In the quest for such biomarkers, an increasing body of evidence suggests that specific indexes derived from routine complete blood counts,i.e.the neutrophil-to-lymphocyte ratio (NLR) and the platelet-to-lymphocyte ratio (PLR), can significantly predict adverse outcomes in AECOPD. This narrative review discusses the current evidence regarding the association between the NLR and the PLR on admission and several clinical end-points (need for invasive ventilation, noninvasive mechanical ventilation failure, admission to an intensive care unit, pulmonary hypertension, length of hospitalisation, and mortality) in AECOPD. Future research directions and potential clinical applications of these haematological indexes in this patient group are also discussed.

A Comprehensive Systematic Review and Meta-Analysis of the Association between the Neutrophil-to-Lymphocyte Ratio and Adverse Outcomes in Patients with Acute Exacerbation of Chronic Obstructive Pulmonary Disease

The neutrophil-to-lymphocyte ratio (NLR) predicts adverse outcomes in stable chronic obstructive pulmonary disease (COPD); however, its prognostic role in acute exacerbations (AECOPD) is less clear. We conducted a systematic review and meta-analysis of the association between the NLR on admission and adverse outcomes (mortality, need for mechanical ventilation, transfer to the intensive care unit, length of stay, pulmonary hypertension, or their combination) in AECOPD by searching PubMed, Web of Science, and Scopus from inception to April 2022. Risk of bias and certainty of evidence were assessed using the Joanna Briggs Institute Critical Appraisal Checklist and the Grades of Recommendation, Assessment, Development, and Evaluation, respectively. In 15 studies (n = 10,038 patients), the NLR was significantly associated with the risk of adverse outcomes (odds ratio = 1.054, 95% CI 1.016 to 1.093, p = 0.005; low certainty of evidence; standard mean difference = 0.82, 95% CI 0.57 to 1.06, p < 0.001; high certainty of evidence). Pooled sensitivity, specificity, and area under the curve were 0.71 (95% CI 0.64 to 0.77), 0.73 (95% CI 0.65 to 0.80), and 0.78 (95% CI 0.74 to 0.81), respectively. In our study, the NLR on admission was significantly associated with adverse outcomes in AECOPD patients, suggesting the potential utility of this biomarker for early risk stratification and management in this group.

Risk Factors for Length of Hospital Stay in Acute Exacerbation Chronic Obstructive Pulmonary Disease: A Multicenter Cross-Sectional Study

Background/Purpose

Patients and Methods

Results

Conclusion

Chronic obstructive pulmonary disease risk assessment tools: is one better than the others?

PURPOSE OF REVIEW

Risk assessment tools are essential in COPD care to help clinicians identify patients at higher risk of accelerated lung function decline, respiratory exacerbations, hospitalizations, and death.

RECENT FINDINGS

Conventional methods of assessing risk have focused on spirometry, patient-reported symptoms, functional status, and a combination of these tools in composite indices. More recently, qualitatively and quantitatively assessed chest imaging findings, such as emphysema, large and small airways disease, and pulmonary vascular abnormalities have been associated with poor long-term outcomes in COPD patients. Although several blood and sputum biomarkers have been investigated for risk assessment in COPD, most still warrant further validation. Finally, novel remote digital monitoring technologies may be valuable to predict exacerbations but their large-scale performance, ease of implementation, and cost effectiveness remain to be determined.

SUMMARY

Given the complex heterogeneity of COPD, any single metric is unlikely to fully capture the risk of poor long-term outcomes. Therefore, clinicians should review all available clinical data, including spirometry, symptom severity, functional status, chest imaging, and bloodwork, to guide personalized preventive care of COPD patients. The potential of machine learning tools and remote monitoring technologies to refine COPD risk assessment is promising but remains largely untapped pending further investigation.

Association of baseline parameters with year 0 and year 1 acute exacerbations in male patients with chronic obstructive pulmonary disease

Objectives

Acute exacerbations (AEs) of chronic obstructive pulmonary disease (COPD) can affect health status, hospitalization and readmission rates, and disease progression. This study aimed to identify independent markers associated with COPD AEs.

Methods

This study included male patients with COPD and collected data regarding their AEs and baseline clinical parameters.

Results

We included 149 male patients. Among them, 58 were included in the year 0 high-AE group and 91 in the low-AE group. Multivariate analysis revealed that the high-AE group had higher white blood cell count, lower serum albumin level, and post-bronchodilator (BD) forced expiratory volume in one second (FEV₁) (%) with a combined receiver operating characteristic curve (ROC) of 0.721 (p < 0.001). Additionally, 34 patients were included in the year 1 high-AE group and 70 in the low-AE group (p < 0.001). Multivariate analysis revealed that the high-AE group had higher platelet count, positive asthma history, and lower pre-BD FEV₁ (%) with a combined ROC of 0.782 (p < 0.001).

Conclusion

In male patients with COPD, baseline white blood cell count, albumin level, and post-BD FEV₁ (%) were correlated with year 0 AE; on the other hand, baseline platelet count, positive asthma history, and pre-BD FEV₁ (%) were associated with year 1 AE.