Multicomponent indices to predict survival in COPD: the COCOMICS study

Prognostic models and factors identifying end-of-life in non-cancer chronic diseases: a systematic review

BACKGROUND

Precise prognostic information, if available, is very helpful for guiding treatment decisions and resource allocation in patients with non-cancer non-communicable chronic diseases (NCDs). This study aimed to systematically review the existing evidence, examining prognostic models and factors for identifying end-of-life non-cancer NCD patients.

METHODS

Electronic databases, including Medline, Embase, CINAHL, Cochrane Library, PsychINFO and other sources, were searched from the inception of these databases up until June 2023. Studies published in English with findings mentioning prognostic models or factors related to identifying end-of-life in non-cancer NCD patients were included. The quality of studies was assessed using the Quality in Prognosis Studies tool.

RESULTS

The analysis included data from 41 studies, with 16 focusing on chronic obstructive pulmonary diseases (COPD), 10 on dementia, 6 on heart failure and 9 on mixed NCDs. Traditional statistical modelling was predominantly used for the identified prognostic models. Common predictors in COPD models included dyspnoea, forced expiratory volume in 1 s, functional status, exacerbation history and body mass index. Models for dementia and heart failure frequently included comorbidity, age, gender, blood tests and nutritional status. Similarly, mixed NCD models commonly included functional status, age, dyspnoea, the presence of skin pressure ulcers, oral intake and level of consciousness. The identified prognostic models exhibited varying predictive accuracy, with the majority demonstrating weak to moderate discriminatory performance (area under the curve: 0.5-0.8). Additionally, most of these models lacked independent external validation, and only a few underwent internal validation.

CONCLUSION

Our review summarised the most relevant predictors for identifying end-of-life in non-cancer NCDs. However, the predictive accuracy of identified models was generally inconsistent and low, and lacked external validation. Although efforts to improve these prognostic models should continue, clinicians should recognise the possibility that disease heterogeneity may limit the utility of these models for individual prognostication; they may be more useful for population level health planning.

Characteristics and phenotypes of a COPD cohort from referral hospital clinics in Uganda

INTRODUCTION

Chronic obstructive pulmonary disease (COPD) is a heterogeneous condition with varied clinical and pathophysiological characteristics. Although there is increasing evidence that COPD in low-income and middle-income countries may have different clinical characteristics from that in high-income countries, little is known about COPD phenotypes in these settings. We describe the clinical characteristics and risk factor profile of a COPD population in Uganda.

METHODS

We cross sectionally analysed the baseline clinical characteristics of 323 patients with COPD aged 30 years and above who were attending 2 national referral outpatient facilities in Kampala, Uganda between July 2019 and March 2021. Logistic regression was used to determine factors associated with spirometric disease severity.

RESULTS

The median age was 62 years; 51.1% females; 93.5% scored COPD Assessment Test >10; 63.8% modified medical research council (mMRC) >2; 71.8% had wheezing; 16.7% HIV positive; 20.4% had a history of pulmonary tuberculosis (TB); 50% with blood eosinophilic count >3%, 51.7% had 3 or more exacerbations in the past year. Greater severity by Global initiative for Chronic Obstructive Lung Disease (GOLD) stage was inversely related to age (aOR=0.95, 95% CI 0.92 to 0.97), and obesity compared with underweight (aOR=0.25, 95% CI 0.07 to 0.82). Regarding clinical factors, more severe airflow obstruction was associated with SPO2 <93% (aOR=3.79, 95% CI 2.05 to 7.00), mMRC ≥2 (aOR=2.21, 95% CI 1.08 to 4.53), and a history of severe exacerbations (aOR=2.64, 95% CI 1.32 to 5.26).

CONCLUSION

Patients with COPD in this population had specific characteristics and risk factor profiles including HIV and TB meriting tailored preventative approaches. Further studies are needed to better understand the pathophysiological mechanisms at play and the therapeutic implications of these findings.

The Relationship between Exertional Desaturation and Pulmonary Function, Exercise Capacity, or Medical Costs in Chronic Obstructive Pulmonary Disease Patients

Background and Objectives: Exertional desaturation (ED) is common and is associated with poorer clinical outcomes in chronic obstructive pulmonary disease (COPD). The age, dyspnea, airflow obstruction (ADO) and body mass index, airflow obstruction, dyspnea, and exercise (BODE) indexes are used to predict the prognosis of COPD patients. This study aimed to investigate the relationship between these indexes, pulmonary function, medical costs, and ED in COPD patients. Materials and Methods: Data were collected from the electronic database of the Kaohsiung Chang Gung Memorial Hospital. This retrospective study included 396 patients categorized as either ED (n = 231) or non-ED (n = 165). Variables (including age, smoking history, body mass index (BMI), pulmonary function test, maximum inspiratory pressure (MIP) and maximum expiratory pressure (MEP), six minutes walking test distance (6MWD), SpO₂, COPD Assessment Test (CAT) score, ADO index, BODE index, Charlson comorbidity index (CCI), and medical costs) were compared between the two groups, and their correlations were assessed. ED was defined as SpO₂ less than 90% or SpO₂ decrease of more than 4% compared to baseline levels during 6MWT. Results: A significant statistical difference was found regarding a lower score of the ADO index and the BODE index (both p < 0.001), better pulmonary function (forced expiratory volume in the first second (FEV1), p < 0.001; FEV1/ forced vital capacity (FVC), p < 0.001; diffusion capacity of the lung for carbon monoxide (DLCO), p < 0.001), and higher minimal oxygen saturation (p < 0.001) in non-ED COPD patients. No difference was found in the distance of the 6MWT (p = 0.825) and respiratory muscle strength (MIP; MEP, p = 0.86; 0.751). However, the adjusted multivariate logistic regression analysis showed that only SpO₂ (minimal) had a significant difference between of the ED and non-ED group (p < 0.001). There was either no difference in the medical expenses between ED and non-ED COPD patients. Conclusions: SpO₂ (minimal) during the 6MWT is the independent factor for ED. ED is related to BODE and ADO indices, but is not related to medical expense.

External Validation and User Experiences of the ProPal-COPD Tool to Identify the Palliative Phase in COPD

Background

Difficulty predicting prognosis is a major barrier to timely palliative care provision for patients with COPD. The ProPal-COPD tool, combining six clinical indicators and the Surprise Question (SQ), aims to predict 1-year mortality as a proxy for palliative care needs. It appeared to be a promising tool for healthcare providers to identify patients with COPD who could benefit from palliative care.

Objective

To externally validate the ProPal-COPD tool and to assess user experiences.

Methods

Patients admitted with an acute exacerbation COPD were recruited across 10 hospitals. Demographics, clinical characteristics and survival status were collected. Sensitivity, specificity, positive and negative predictive values of the tool using two cut-off values were calculated. Also, predictive properties of the SQ were calculated. In monitoring meetings and interviews, healthcare providers shared their experiences with the tool. Transcripts were deductively coded using six user experience domains: Acceptability, Satisfaction, Credibility, Usability, User-reported adherence and Perceived impact.

Results

A total of 523 patients with COPD were included between May 2019 and August 2020, of whom 100 (19.1%) died within 12 months. The ProPal-COPD tool had an AUC of 0.68 and a low sensitivity (55%) and moderate specificity (74%) for predicting 1-year all-cause mortality. Using a lower cut-off value, sensitivity was higher (74%), but specificity lower (46%). Sensitivity and specificity of the SQ were 56% and 73%, respectively (AUC 0.65). However, healthcare providers generally appreciated using the tool because it increased awareness of the palliative phase and provided a shared understanding of prognosis, although they considered its outcome not always correct.

Conclusion

The accuracy of the ProPal-COPD tool to predict 1-year mortality is limited, although screening patients with its indicators increases healthcare providers' awareness of palliative care needs and encourages them to timely initiate appropriate care.

Validation of Clinical COPD Phenotypes for Prognosis of Long-Term Mortality in Swedish and Dutch Cohorts

Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease with variable mortality risk. The aim of our investigation was to validate a simple clinical algorithm for long-term mortality previously proposed by Burgel et al. in 2017. Subjects with COPD from two cohorts, the Swedish PRAXIS study (n = 784, mean age (standard deviation (SD)) 64.0 years (7.5), 42% males) and the Rotterdam Study (n = 735, mean age (SD) 72 years (9.2), 57% males), were included. Five clinical clusters were derived from baseline data on age, body mass index, dyspnoea grade, pulmonary function and comorbidity (cardiovascular disease/diabetes). Cox models were used to study associations with 9-year mortality. The distribution of clinical clusters (1-5) was 29%/45%/8%/6%/12% in the PRAXIS study and 23%/26%/36%/0%/15% in the Rotterdam Study. The cumulative proportion of deaths at the 9-year follow-up was highest in clusters 1 (65%) and 4 (72%), and lowest in cluster 5 (10%) in the PRAXIS study. In the Rotterdam Study, cluster 1 (44%) had the highest cumulative mortality and cluster 5 (5%) the lowest. Compared with cluster 5, the meta-analysed age- and sex-adjusted hazard ratio (95% confidence interval) for cluster 1 was 6.37 (3.94-10.32) and those for clusters 2 and 3 were 2.61 (1.58-4.32) and 3.06 (1.82-5.13), respectively. Burgel's clinical clusters can be used to predict long-term mortality risk. Clusters 1 and 4 are associated with the poorest prognosis, cluster 5 with the best prognosis and clusters 2 and 3 with intermediate prognosis in two independent cohorts from Sweden and the Netherlands.

Clustering-based COPD subtypes have distinct longitudinal outcomes and multi-omics biomarkers

Introduction

Chronic obstructive pulmonary disease (COPD) can progress across several domains, complicating the identification of the determinants of disease progression. In our previous work, we applied k-means clustering to spirometric and chest radiological measures to identify four COPD-related subtypes: ‘relatively resistant smokers (RRS)’, ‘mild upper lobe-predominant emphysema (ULE)’, ‘airway-predominant disease (AD)’ and ‘severe emphysema (SE)’. In the current study, we examined the associations of these subtypes to longitudinal COPD-related health measures as well as blood transcriptomic and plasma proteomic biomarkers.

Methods

We included 8266 non-Hispanic white and African-American smokers from the COPDGene study. We used linear regression to investigate cluster associations to 5-year prospective changes in spirometric and radiological measures and to gene expression and protein levels. We used Cox-proportional hazard test to test for cluster associations to prospective exacerbations, comorbidities and mortality.

Results

The RRS, ULE, AD and SE clusters represented 39%, 15%, 26% and 20% of the studied cohort at baseline, respectively. The SE cluster had the greatest 5-year FEV₁ (forced expiratory volume in 1 s) and emphysema progression, and the highest risks of exacerbations, cardiovascular disease and mortality. The AD cluster had the highest diabetes risk. After adjustments, only the SE cluster had an elevated respiratory mortality risk, while the ULE, AD and SE clusters had elevated all-cause mortality risks. These clusters also demonstrated differential protein and gene expression biomarker associations, mostly related to inflammatory and immune processes.

Conclusion

COPD k-means subtypes demonstrate varying rates of disease progression, prospective comorbidities, mortality and associations to transcriptomic and proteomic biomarkers. These findings emphasise the clinical and biological relevance of these subtypes, which call for more study for translation into clinical practice.

Trail registration number

NCT00608764.

Development and validation of a multivariable mortality risk prediction model for COPD in primary care

Risk stratification of chronic obstructive pulmonary disease (COPD) patients is important to enable targeted management. Existing disease severity classification systems, such as GOLD staging, do not take co-morbidities into account despite their high prevalence in COPD patients. We sought to develop and validate a prognostic model to predict 10-year mortality in patients with diagnosed COPD. We constructed a longitudinal cohort of 37,485 COPD patients (149,196 person-years) from a UK-wide primary care database. The risk factors included in the model pertained to demographic and behavioural characteristics, co-morbidities, and COPD severity. The outcome of interest was all-cause mortality. We fitted an extended Cox-regression model to estimate hazard ratios (HR) with 95% confidence intervals (CI), used machine learning-based data modelling approaches including k-fold cross-validation to validate the prognostic model, and assessed model fitting and discrimination. The inter-quartile ranges of the three metrics on the validation set suggested good performance: 0.90–1.06 for model fit, 0.80–0.83 for Harrel’s c-index, and 0.40–0.46 for Royston and Saurebrei’s \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$R_D^2$$\end{document}RD2 with a strong overlap of these metrics on the training dataset. According to the validated prognostic model, the two most important risk factors of mortality were heart failure (HR 1.92; 95% CI 1.87–1.96) and current smoking (HR 1.68; 95% CI 1.66–1.71). We have developed and validated a national, population-based prognostic model to predict 10-year mortality of patients diagnosed with COPD. This model could be used to detect high-risk patients and modify risk factors such as optimising heart failure management and offering effective smoking cessation interventions.

Predictors of mortality in chronic obstructive pulmonary disease: a systematic review and meta-analysis

Background

Better insight in patients’ prognosis can help physicians to timely initiate advance care planning (ACP) discussions with patients with chronic obstructive pulmonary disease (COPD). We aimed to identify predictors of mortality.

Methods

We systematically searched databases Embase, PubMed, MEDLINE, Web of Science, and Cochrane Central in April 2020. Papers reporting on predictors or prognostic models for mortality at 3 months and up to 24 months were assessed on risk-of-bias. We performed a meta-analysis with a fixed or random-effects model, and evaluated the discriminative ability of multivariable prognostic models.

Results

We included 42 studies (49–418,251 patients); 18 studies were included in the meta-analysis. Significant predictors of mortality within 3–24 months in the random-effects model were: previous hospitalization for acute exacerbation (hazard ratio [HR] 1.97; 95% confidence interval [CI] 1.32–2.95), hospital readmission within 30 days (HR 5.01; 95% CI 2.16–11.63), cardiovascular comorbidity (HR 1.89; 95% CI 1.25–2.87), age (HR 1.48; 95% CI 1.38–1.59), male sex (HR 1.68; 95% CI 1.38–1.59), and long-term oxygen therapy (HR 1.74; 95% CI 1.10–2.73). Nineteen previously developed multicomponent prognostic models, as examined in 11 studies, mostly had moderate discriminate ability.

Conclusion

Identified predictors of mortality may aid physicians in selecting COPD patients who may benefit from ACP. However, better discriminative ability of prognostic models or development of a new prognostic model is needed for further large-scale implementation.

Registration: PROSPERO (CRD42016038494), https://www.crd.york.ac.uk/prospero/.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12890-022-01911-5.

Frailty Among Older Individuals with and without COPD: A Cohort Study of Prevalence and Association with Adverse Outcomes

Rationale

Frailty prevalence estimates among individuals with COPD have varied widely, and few studies have investigated relationships between frailty and adverse outcomes in a COPD population.

Objective(s)

Describe frailty prevalence among individuals with and without COPD and examine associations between frailty and mortality and other adverse outcomes in the next two years.

Methods

This was an observational cohort study using Health and Retirement Study data (2006–2018) of community living individuals ages 50–64 and ≥65 with and without COPD (non-COPD). Frailty (Fried phenotype [5 items], and a modified Frailty Index-Comprehensive Geriatric Assessment [Enhanced FI-CGA] [37 items], and debility (modified BODE Index [4 items]) were assessed. Two-year post-assessment outcomes (mortality, ≥1 inpatient stay, home health and skilled nursing facility (SNF) use) were reviewed in a population matched 3:1 (non-COPD: COPD) on age, sex, race, and year using univariate and multivariate logistic regression (adjusted for morbidities). Area-under-the-curve (AUC) was used to evaluate regressions.

Results

The study included 18,979 survey observations for age 50–64, and 24,162 age ≥65; 7.8% and 12.0% respectively reporting a diagnosis of COPD. Fried phenotype frailty prevalence for age ≥65 was 23.1% (COPD) and 9.4% (non-COPD), and for the Enhanced FI-CGA, 45.9% (COPD) and 22.4% (non-COPD). Two-year mortality for COPD was more than double non-COPD for age 50–64 (95% CI: 3.8–5.9% vs 0.7–1.3%) and age ≥65 (95% CI: 11.9–14.3% vs 5.6–6.6%). Inpatient utilization, home health care use, or at least temporary SNF placement were also more frequent for COPD. Measures were predictive of adverse outcomes. In adjusted models, the Fried phenotype and modified BODE score performed similarly, and both performed better than the Enhanced FI-CGA index. AUC values were higher for morality regressions.

Conclusion

Frailty prevalence among individuals with COPD in this national survey is substantially greater than without COPD, even at pre-retirement (50–64 years). These measures identify patients with increased risk of poor outcomes.

Development and validation of a prediction index for recent mortality in advanced COPD patients

The primary barrier to initiating palliative care for advanced COPD patients is the unpredictable course of the disease. We enroll 752 COPD patients into the study and validate the prediction tools for 1-year mortality using the current guidelines for palliative care. We also develop a composite prediction index for 1-year mortality and validate it in another cohort of 342 patients. Using the current prognostic models for recent mortality in palliative care, the best area under the curve (AUC) for predicting mortality is 0.68. Using the Modified Medical Research Council dyspnea score and oxygen saturation to define the combined dyspnea and oxygenation (DO) index, we find that the AUC of the DO index is 0.84 for predicting mortality in the validated cohort. Predictions of 1-year mortality based on the current palliative care guideline for COPD patients are poor. The DO index exhibits better predictive ability than other models in the study.

Value of Cardiopulmonary Exercise Testing in the Prognosis Assessment of Chronic Obstructive Pulmonary Disease Patients: A Retrospective, Multicentre Cohort Study

INTRODUCTION

Chronic obstructive pulmonary disease (COPD) is one of the most common chronic diseases associated with high mortality. Previous studies suggested a prognostic role for peak oxygen uptake (VO2peak) assessed during cardiopulmonary exercise testing (CPET) in patients with COPD. However, most of these studies had small sample sizes or short follow-up periods, and despite their relevance, CPET parameters are not included in the Global Initiative for Chronic Obstructive Lung Disease (GOLD) tool for assessment of severity.

OBJECTIVES

We therefore aimed to assess the prognostic value of CPET parameters in a large cohort of outpatients with COPD.

METHODS

In this retrospective, multicentre cohort study, medical records of patients with COPD who underwent CPET during 2004-2017 were reviewed and demographics, smoking habits, GOLD grade and category, exacerbation frequency, dyspnoea score, lung function measurements, and CPET parameters were documented. Relationships with survival were evaluated using Kaplan-Meier analysis, Cox regression, and receiver operating characteristic (ROC) curves.

RESULTS

Of a total of 347 patients, 312 patients were included. Five-year and 10-year survival probability was 75% and 57%, respectively. VO2peak significantly predicted survival (hazard ratio: 0.886 [95% confidence interval: 0.830; 0.946]). The optimal VO2peak threshold for discrimination of 5-year survival was 14.6 mL/kg/min (area under ROC curve: 0.713). Five-year survival in patients with VO2peak <14.6 mL/kg/min versus ≥ 14.6 mL/kg/min was 60% versus 86% in GOLD categories A/B and 64% versus 90% in GOLD categories C/D.

CONCLUSIONS

We confirm that VO2peak is a highly significant predictor of survival in COPD patients and recommend the incorporation of VO2peak into the assessment of COPD severity.

Multidimensional indices in the assessment of chronic obstructive pulmonary disease

Chronic obstructive pulmonary disease (COPD), a very common disease, is the third leading cause of death worldwide. Due to the significant heterogeneity of clinical phenotypes of COPD there is no single method suitable for predicting patients' health status and outcomes, and therefore multidimensional indices, assessing different components of the disease, were developed and are recommended for clinical practice by international guidelines. Several indices have been widely accepted: BODE and its modifications, ADO, DOSE, CODEX, COTE. They differ in their composition and aim, while they are more accurate and better validated in specific settings and populations. We review the characteristics, strengths and limitations of these indices, and we discuss their role in routine management of patients with COPD, as well as in specific clinical scenarios, such as resuscitation and ceiling of care, or decisions to offer more invasive treatments. This analysis may help clinicians to use those indexes in a more practical and appropriate way.

Radiomics approach for survival prediction in chronic obstructive pulmonary disease

OBJECTIVES

To apply radiomics analysis for overall survival prediction in chronic obstructive pulmonary disease (COPD), and evaluate the performance of the radiomics signature (RS).

METHODS

This study included 344 patients from the Korean Obstructive Lung Disease (KOLD) cohort. External validation was performed on a cohort of 112 patients. In total, 525 chest CT-based radiomics features were semi-automatically extracted. The five most useful features for survival prediction were selected by least absolute shrinkage and selection operation (LASSO) Cox regression analysis and used to generate a RS. The ability of the RS for classifying COPD patients into high or low mortality risk groups was evaluated with the Kaplan-Meier survival analysis and Cox proportional hazards regression analysis.

RESULTS

The five features remaining after the LASSO analysis were %LAA_-950, AWT_Pi10_6^th, AWT_Pi10_heterogeneity, %WA_heterogeneity, and VA_18mm. The RS demonstrated a C-index of 0.774 in the discovery group and 0.805 in the validation group. Patients with a RS greater than 1.053 were classified into the high-risk group and demonstrated worse overall survival than those in the low-risk group in both the discovery (log-rank test, < 0.001; hazard ratio [HR], 5.265) and validation groups (log-rank test, < 0.001; HR, 5.223). For both groups, RS was significantly associated with overall survival after adjustments for patient age and body mass index.

CONCLUSIONS

A radiomics approach for survival prediction and risk stratification in COPD patients is feasible, and the constructed radiomics model demonstrated acceptable performance. The RS derived from chest CT data of COPD patients was able to effectively identify those at increased risk of mortality.

KEY POINTS

• A total of 525 chest CT-based radiomics features were extracted and the five radiomics features of %LAA_-950, AWT_Pi10_6^th, AWT_Pi10_heterogeneity, %WA_heterogeneity, and VA_18mm were selected to generate a radiomics model. • A radiomics model for predicting survival of COPD patients demonstrated reliable performance with a C-index of 0.774 in the discovery group and 0.805 in the validation group. • Radiomics approach was able to effectively identify COPD patients with an increased risk of mortality, and patients assigned to the high-risk group demonstrated worse overall survival in both the discovery and validation groups.

Markers of disease activity in COPD: an 8-year mortality study in the ECLIPSE cohort

Rationale

There are no validated measures of disease activity in COPD. Since “active” disease is expected to have worse outcomes (e.g. mortality), we explored potential markers of disease activity in patients enrolled in the ECLIPSE cohort in relation to 8-year all-cause mortality.

Methods

We investigated 1) how changes in relevant clinical variables over time (1 or 3 years) relate to 8-year mortality; 2) whether these variables inter-relate; and 3) if any clinical, imaging and/or biological marker measured cross-sectionally at baseline relates to any activity component.

Results

Results showed that 1) after 1 year, hospitalisation for COPD, exacerbation frequency, worsening of body mass index, airflow obstruction, dyspnoea and exercise (BODE) index or health status (St George's Respiratory Questionnaire (SGRQ)) and persistence of systemic inflammation were significantly associated with 8-year mortality; 2) at 3 years, the same markers, plus forced expiratory volume in 1 s (FEV₁) decline and to a lesser degree computed tomography (CT) emphysema, showed association, thus qualifying as markers of disease activity; 3) changes in FEV₁, inflammatory cytokines and CT emphysema were not inter-related, while the multidimensional indices (BODE and SGRQ) showed modest correlations; and 4) changes in these markers could not be predicted by any baseline cross-sectional measure.

Conclusions

In COPD, 1- and 3-year changes in exacerbation frequency, systemic inflammation, BODE and SGRQ scores and FEV₁ decline are independent markers of disease activity associated with 8-year all-cause mortality. These disease activity markers are generally independent and not predictable from baseline measurements.

In patients with COPD, 1- and 3-year changes in exacerbation frequency, systemic inflammation, BODE and SGRQ scores, and FEV₁ decline, are independent markers of disease activity associated with 8-year all-cause mortalityhttps://bit.ly/2CyifcN

Development and validation of a prognostic index (BODEXS90) for mortality in stable chronic obstructive pulmonary disease

INTRODUCTION

Several multidimensional indices have been proposed to predict mortality in chronic obstructive pulmonary disease (COPD). The BODEX index is simple and easy to use for this purpose in all clinical settings. Only a few prognostic indices have integrated oxygenation variables, with measurement methods that are not practical for real life clinical practice in all settings.

OBJECTIVES

To develop and externally validate a new prognostic index (BODEXS90) that combines the variables included in BODEX index with rest peripheral oxygen saturation measured with finger oximetry (SpO₂) to predict all-cause mortality in stable COPD.

METHOD

Observational, non-intervention, multicenter historic cohort study. The BODEXS90 index was developed in a derivation cohort and externally validated in a validation cohort. Calibration of the index was carried out using Hosmer-Lemeshow test. The discrimination capacity of BODEXS90 and BODEX were compared by means of receiver-operating characteristics curves. Modelling of the index was carried out by crude and adjusted Cox regression analysis.

RESULTS

The derivation and validation cohorts included 787 and 1179 subjects, respectively. SpO₂ predicted all cause-mortality independently of BODEX index. Discrimination capacity of BODEXS90 to predict the outcome was significantly higher than that of BODEX, particularly for more severely affected patients, both in the derivation and in the validation cohorts.

CONCLUSIONS

The new index is potentially useful for designing clinical decision-making algorithms in stable COPD.

Mortality prediction in chronic obstructive pulmonary disease comparing the GOLD 2015 and GOLD 2019 staging: a pooled analysis of individual patient data

In 2019, The Global Initiative for Chronic Obstructive Lung Disease (GOLD) modified the grading system for patients with COPD, creating 16 subgroups (1A–4D). As part of the COPD Cohorts Collaborative International Assessment (3CIA) initiative, we aim to compare the mortality prediction of the 2015 and 2019 COPD GOLD staging systems.

We studied 17 139 COPD patients from the 3CIA study, selecting those with complete data. Patients were classified by the 2015 and 2019 GOLD ABCD systems, and we compared the predictive ability for 5-year mortality of both classifications.

In total, 17 139 patients with COPD were enrolled in 22 cohorts from 11 countries between 2003 and 2017; 8823 of them had complete data and were analysed. Mean±sd age was 63.9±9.8 years and 62.9% were male. GOLD 2019 classified the patients in milder degrees of COPD. For both classifications, group D had higher mortality. 5-year mortality did not differ between groups B and C in GOLD 2015; in GOLD 2019, mortality was greater for group B than C. Patients classified as group A and B had better sensitivity and positive predictive value with the GOLD 2019 classification than GOLD 2015. GOLD 2015 had better sensitivity for group C and D than GOLD 2019. The area under the curve values for 5-year mortality were only 0.67 (95% CI 0.66–0.68) for GOLD 2015 and 0.65 (95% CI 0.63–0.66) for GOLD 2019.

The new GOLD 2019 classification does not predict mortality better than the previous GOLD 2015 system.

GOLD 2019 staging system created 16 subgroups. GOLD 2015 and GOLD 2019 are not strong predictors of mortality, and do not have sufficient discriminatory power to be used as a tool for risk classification of mortality in patients with COPD.https://bit.ly/3idBuaN

Machine Learning and Prediction of All-Cause Mortality in COPD

BACKGROUND

COPD is a leading cause of mortality.

RESEARCH QUESTION

We hypothesized that applying machine learning to clinical and quantitative CT imaging features would improve mortality prediction in COPD.

STUDY DESIGN AND METHODS

We selected 30 clinical, spirometric, and imaging features as inputs for a random survival forest. We used top features in a Cox regression to create a machine learning mortality prediction (MLMP) in COPD model and also assessed the performance of other statistical and machine learning models. We trained the models in subjects with moderate to severe COPD from a subset of subjects in Genetic Epidemiology of COPD (COPDGene) and tested prediction performance in the remainder of individuals with moderate to severe COPD in COPDGene and Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE). We compared our model with the BMI, airflow obstruction, dyspnea, exercise capacity (BODE) index; BODE modifications; and the age, dyspnea, and airflow obstruction index.

RESULTS

We included 2,632 participants from COPDGene and 1,268 participants from ECLIPSE. The top predictors of mortality were 6-min walk distance, FEV1 % predicted, and age. The top imaging predictor was pulmonary artery-to-aorta ratio. The MLMP-COPD model resulted in a C index ≥ 0.7 in both COPDGene and ECLIPSE (6.4- and 7.2-year median follow-ups, respectively), significantly better than all tested mortality indexes (P < .05). The MLMP-COPD model had fewer predictors but similar performance to that of other models. The group with the highest BODE scores (7-10) had 64% mortality, whereas the highest mortality group defined by the MLMP-COPD model had 77% mortality (P = .012).

INTERPRETATION

An MLMP-COPD model outperformed four existing models for predicting all-cause mortality across two COPD cohorts. Performance of machine learning was similar to that of traditional statistical methods. The model is available online at: https://cdnm.shinyapps.io/cgmortalityapp/.

Early Predictors of Mortality in Patients with COPD, in Relation to Respiratory and Non-Respiratory Causes of Death - A National Register Study

Background

Both single factors and composite measures have been suggested to predict mortality in patients with chronic obstructive pulmonary disease (COPD) and there is a need to analyze the relative importance of each variable.

Objective

To explore the predictors of mortality for patients with COPD in relation to respiratory, cardiac, and malignant causes, as well as all causes of death.

Methods

After merging the Swedish Respiratory Tract Register (SRTR) and the Swedish Cause of Death Register, patients with respiratory, cardiac, and other causes of death were identified. Demographic and clinical variables from the deceased patients’ first registration with the SRTR were compared. Three univariable and multivariable Cox proportional hazards regression analyses were conducted for different causes of death, with time from first registration to either death or a fixed end date as dependent variable, and variables regarding demographics, respiration, and comorbidities as independent variables.

Results

In the multivariable Cox models, mortality for patients with all causes of death was predicted by older age 1.79 (CI 1.41, 2.27), lower percentage of predicted forced expiratory volume in 1 second (FEV₁ %) 0.99 (CI 0.98, 0.99), lower saturation 0.92 (CI 0.86, 0.97), worse dyspnea 1.48 (CI 1.26, 1.74) (p<0.002 to p<0.001), less exercise 0.91 (CI 0.85, 0.98), and heart disease 1.53 (CI 1.06, 2.19) (both p<0.05). Mortality for patients with respiratory causes was predicted by higher age 1.67 (CI 1.05, 2.65) (p<0.05), lower FEV_1% 0.98 (CI 0.97, 0.99), worse dyspnea 2.05 (CI 1.45, 2.90), and a higher number of exacerbations 1.27 (CI 1.11, 1.45) (p<0.001 in all comparisons). For patients with cardiac causes of death, mortality was predicted by lower FEV_1% 0.99 (CI 0.98, 0.99) (p=0.001) and lower saturation 0.82 (CI 0.76, 0.89) (p<0.001), older age 1.46 (CI 1.02, 2.09) (p<0.05), and presence of heart disease at first registration 2.06 (CI 1.13, 3.73) (p<0.05).

Conclusion

Obstruction predicted mortality in all models and dyspnea in two models and needs to be addressed. Comorbidity with heart disease could further worsen the COPD patient’s prognosis and should be treated by a multidisciplinary team of professional specialists.

A new maximal bicycle test using a prediction algorithm developed from four large COPD studies

Background: Maximum exercise workload (W_MAX) is today assessed as the first part of Cardiopulmonary Exercise testing. The W_MAX test exposes patients with COPD, often having cardiovascular comorbidity, to risks. Our research project was initiated with the final aim to eliminate the W_MAX test and replace this test with a predicted value of W_MAX, based on a prediction algorithm of W_MAX derived from multicentre studies.

Methods: Baseline data (W_MAX, demography, lung function parameters) from 850 COPD patients from four multicentre studies were collected and standardized. A prediction algorithm was prepared using Random Forest modelling. Predicted values of W_MAX were used in a new W_MAX test, which used a linear increase in order to reach the predicted W_MAX within 8 min. The new W_MAX test was compared with the standard stepwise W_MAX test in a pilot study including 15 patients with mild/moderate COPD.

Results: The best prediction algorithm of W_MAX included age, sex, height, weight, and six lung function parameters. FEV₁ and DLCO were the most important predictors. The new W_MAX test had a better correlation (R² = 0.84) between predicted and measured W_MAX than the standard W_MAX test (R² = 0.66), with slopes of 0.50 and 0.46, respectively. The results from the new W_MAX test and the standard W_MAX test correlated well.

Conclusion: A prediction algorithm based on data from four large multicentre studies was used in a new W_MAX test. The prediction algorithm provided reliable values of predicted W_MAX. In comparison with the standard W_MAX test, the new W_MAX test provided similar overall results.

Primary care risk stratification in COPD using routinely collected data: a secondary data analysis

Most clinical contacts with chronic obstructive pulmonary disease (COPD) patients take place in primary care, presenting opportunity for proactive clinical management. Electronic health records could be used to risk stratify diagnosed patients in this setting, but may be limited by poor data quality or completeness. We developed a risk stratification database algorithm using the DOSE index (Dyspnoea, Obstruction, Smoking and Exacerbation) with routinely collected primary care data, aiming to calculate up to three repeated risk scores per patient over five years, each separated by at least one year. Among 10,393 patients with diagnosed COPD, sufficient primary care data were present to calculate at least one risk score for 77.4%, and the maximum of three risk scores for 50.6%. Linked secondary care data revealed primary care under-recording of hospital exacerbations, which translated to a slight, non-significant cohort average risk score reduction, and an understated risk group allocation for less than 1% of patients. Algorithmic calculation of the DOSE index is possible using primary care data, and appears robust to the absence of linked secondary care data, if unavailable. The DOSE index appears a simple and practical means of incorporating risk stratification into the routine primary care of COPD patients, but further research is needed to evaluate its clinical utility in this setting. Although secondary analysis of routinely collected primary care data could benefit clinicians, patients and the health system, standardised data collection and improved data quality and completeness are also needed.

Prognostic models for outcome prediction in patients with chronic obstructive pulmonary disease: systematic review and critical appraisal

OBJECTIVE

To map and assess prognostic models for outcome prediction in patients with chronic obstructive pulmonary disease (COPD).

DESIGN

Systematic review.

DATA SOURCES

PubMed until November 2018 and hand searched references from eligible articles.

ELIGIBILITY CRITERIA FOR STUDY SELECTION

Studies developing, validating, or updating a prediction model in COPD patients and focusing on any potential clinical outcome.

RESULTS

The systematic search yielded 228 eligible articles, describing the development of 408 prognostic models, the external validation of 38 models, and the validation of 20 prognostic models derived for diseases other than COPD. The 408 prognostic models were developed in three clinical settings: outpatients (n=239; 59%), patients admitted to hospital (n=155; 38%), and patients attending the emergency department (n=14; 3%). Among the 408 prognostic models, the most prevalent endpoints were mortality (n=209; 51%), risk for acute exacerbation of COPD (n=42; 10%), and risk for readmission after the index hospital admission (n=36; 9%). Overall, the most commonly used predictors were age (n=166; 41%), forced expiratory volume in one second (n=85; 21%), sex (n=74; 18%), body mass index (n=66; 16%), and smoking (n=65; 16%). Of the 408 prognostic models, 100 (25%) were internally validated and 91 (23%) examined the calibration of the developed model. For 286 (70%) models a model presentation was not available, and only 56 (14%) models were presented through the full equation. Model discrimination using the C statistic was available for 311 (76%) models. 38 models were externally validated, but in only 12 of these was the validation performed by a fully independent team. Only seven prognostic models with an overall low risk of bias according to PROBAST were identified. These models were ADO, B-AE-D, B-AE-D-C, extended ADO, updated ADO, updated BODE, and a model developed by Bertens et al. A meta-analysis of C statistics was performed for 12 prognostic models, and the summary estimates ranged from 0.611 to 0.769.

CONCLUSIONS

This study constitutes a detailed mapping and assessment of the prognostic models for outcome prediction in COPD patients. The findings indicate several methodological pitfalls in their development and a low rate of external validation. Future research should focus on the improvement of existing models through update and external validation, as well as the assessment of the safety, clinical effectiveness, and cost effectiveness of the application of these prognostic models in clinical practice through impact studies.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42017069247.

Consensus for managing patients with chronic obstructive pulmonary disease according to the CODEX index

The comorbidity, obstruction, dyspnoea, exacerbations (CODEX) index is the first multicomponent scale designed to predict the risk of readmissions and mortality at 1 year for patients hospitalised for chronic obstructive pulmonary disease (COPD). The index includes the comorbidities (C) (measured by the Charlson index), the degree of obstruction (O) (assessed by the forced expiratory volume in 1 second percentage), dyspnoea (D) (stratified according to the modified Medical Research Council scale) and exacerbations (EX) in the previous year. Our objective was to prepare recommendations based on the index's various components for personalised therapeutic management. To this end, we performed a literature search based on guidelines, consensuses and systematic reviews, as a basis for preparing recommendations on basic concepts, comorbidities, dyspnoea, pulmonary obstruction, exacerbations and follow-up. The recommendations were then subjected to an external assessment process by a multidisciplinary group of 62 experts. In total, 108 recommendations were created, 96 of which achieved consensus, including the recommendation that COPD be considered a high-risk cardiovascular disease, as well as several specific recommendations on managing the various comorbidities. A consensus was reached on the recommended treatments in the guidelines for the various levels of obstruction, dyspnoea and exacerbations, adapted to the CODEX scores. Advice is also offered for patient follow-up after hospital discharge, which includes aspects on assessment, treatment and care coordination.

External Validation and Recalculation of the CODEX Index in COPD Patients. A 3CIAplus Cohort Study

The CODEX index was developed and validated in patients hospitalized for COPD exacerbation to predict the risk of death and readmission within one year after discharge. Our study aimed to validate the CODEX index in a large external population of COPD patients with variable durations of follow-up. Additionally, we aimed to recalculate the thresholds of the CODEX index using the cutoffs of variables previously suggested in the 3CIA study (mCODEX). Individual data on 2,755 patients included in the COPD Cohorts Collaborative International Assessment Plus (3CIA+) were explored. A further two cohorts (ESMI AND EGARPOC-2) were added. To validate the CODEX index, the relationship between mortality and the CODEX index was assessed using cumulative/dynamic ROC curves at different follow-up periods, ranging from 3 months up to 10 years. Calibration was performed using univariate and multivariate Cox proportional hazard models and Hosmer-Lemeshow test. A total of 3,321 (87.8% males) patients were included with a mean ± SD age of 66.9 ± 10.5 years, and a median follow-up of 1,064 days (IQR 25-75% 426-1643), totaling 11,190 person-years. The CODEX index was statistically associated with mortality in the short- (≤3 months), medium- (≤1 year) and long-term (10 years), with an area under the curve of 0.72, 0.70 and 0.76, respectively. The mCODEX index performed better in the medium-term (<1 year) than the original CODEX, and similarly in the long-term. In conclusion, CODEX and mCODEX index are good predictors of mortality in patients with COPD, regardless of disease severity or duration of follow-up.

What is early COPD and why is it important?

There is increasing interest in the origins of chronic obstructive pulmonary disease (COPD), as it is envisaged that preventive efforts and treatment can modify its clinical course. The concept of early COPD is not new, but it has recently regained interest, given new population data, recent cellular and molecular advances and insights from clinical trials. To date, many knowledge gaps in the nature of early COPD still exist, mainly because COPD has always been considered a disease of the elderly, and little attention has been paid to the pathological changes occurring in the lungs of individuals at risk before they develop clinically evident COPD. Future studies should focus on identifying early pathological manifestations of COPD in order to prevent its progression in susceptible individuals. In this review, we aim to summarise what is known on early COPD, from the epidemiological, cellular and clinical perspectives.

"A palliative end-stage COPD patient does not exist": a qualitative study of barriers to and facilitators for early integration of palliative home care for end-stage COPD

Early integration of palliative home care (PHC) might positively affect people with chronic obstructive pulmonary disease (COPD). However, PHC as a holistic approach is not well integrated in clinical practice at the end-stage COPD. General practitioners (GPs) and community nurses (CNs) are highly involved in primary and home care and could provide valuable perspectives about barriers to and facilitators for early integrated PHC in end-stage COPD. Three focus groups were organised with GPs (n = 28) and four with CNs (n = 28), transcribed verbatim and comparatively analysed. Barriers were related to the unpredictability of COPD, a lack of disease insight and resistance towards care of the patient, lack of cooperation and experience with PHC for professional caregivers, lack of education about early integrated PHC, insufficient continuity of care from hospital to home, and lack of communication about PHC between professional caregivers and with end-stage COPD patients. Facilitators were the use of trigger moments for early integrating PHC, such as after a hospital admission or when an end-stage COPD patient becomes oxygen-dependent or housebound, positive attitudes towards PHC in informal caregivers, more focus on early integration of PHC in professional caregivers' education, implementing advance care planning in healthcare and PHC systems, and enhancing communication about care and PHC. The results provide insights for clinical practice and the development of key components for successful practice in a phase 0-2 Early Integration of PHC for end-stage COPD (EPIC) trial, such as improving care integration, patients' disease insight and training PHC nurses in care for end-stage COPD.

Current Approaches for Phenotyping as a Target for Precision Medicine in COPD Management

The study of airway diseases continues to present several challenges for modern medicine. The different disease presentations with variables and overlapping features may result in a real challenge for the clinician. In this context, the concept of precision medicine has started to emerge in order to give answers to some of these challenges from a diagnostic and therapeutic point of view. The main reasons to target for precision medicine in chronic obstructive pulmonary disease (COPD) include that there is variability in the clinical presentation, there is no correlation between the different clinical variables at the patient level, there are a number of relevant clinical variables associated with outcomes, we do have specific therapies for specific patient types, and that there is variability in the clinical response to different therapies. To bring precision medicine into clinical practice several approaches have been used, including the use of independent variables to identify subjects, the use of multidimensional indexes, the so-called clinical phenotypes, and the approximation by the so-called treatable traits. All these approaches have their strengths and weaknesses which are reviewed in the present document. Although there is no universally accepted proposal, the available initiatives provide us with a framework on which to start working and move toward precision medicine in COPD, with the ultimate goal of bringing the best possible medicine to each patient in particular.

Large-scale external validation and comparison of prognostic models: an application to chronic obstructive pulmonary disease

BACKGROUND

External validations and comparisons of prognostic models or scores are a prerequisite for their use in routine clinical care but are lacking in most medical fields including chronic obstructive pulmonary disease (COPD). Our aim was to externally validate and concurrently compare prognostic scores for 3-year all-cause mortality in mostly multimorbid patients with COPD.

METHODS

We relied on 24 cohort studies of the COPD Cohorts Collaborative International Assessment consortium, corresponding to primary, secondary, and tertiary care in Europe, the Americas, and Japan. These studies include globally 15,762 patients with COPD (1871 deaths and 42,203 person years of follow-up). We used network meta-analysis adapted to multiple score comparison (MSC), following a frequentist two-stage approach; thus, we were able to compare all scores in a single analytical framework accounting for correlations among scores within cohorts. We assessed transitivity, heterogeneity, and inconsistency and provided a performance ranking of the prognostic scores.

RESULTS

Depending on data availability, between two and nine prognostic scores could be calculated for each cohort. The BODE score (body mass index, airflow obstruction, dyspnea, and exercise capacity) had a median area under the curve (AUC) of 0.679 [1st quartile-3rd quartile = 0.655-0.733] across cohorts. The ADO score (age, dyspnea, and airflow obstruction) showed the best performance for predicting mortality (difference AUCADO - AUCBODE = 0.015 [95% confidence interval (CI) = -0.002 to 0.032]; p = 0.08) followed by the updated BODE (AUCBODE updated - AUCBODE = 0.008 [95% CI = -0.005 to +0.022]; p = 0.23). The assumption of transitivity was not violated. Heterogeneity across direct comparisons was small, and we did not identify any local or global inconsistency.

CONCLUSIONS

Our analyses showed best discriminatory performance for the ADO and updated BODE scores in patients with COPD. A limitation to be addressed in future studies is the extension of MSC network meta-analysis to measures of calibration. MSC network meta-analysis can be applied to prognostic scores in any medical field to identify the best scores, possibly paving the way for stratified medicine, public health, and research.

Multiple Score Comparison: a network meta-analysis approach to comparison and external validation of prognostic scores

BACKGROUND

Prediction models and prognostic scores have been increasingly popular in both clinical practice and clinical research settings, for example to aid in risk-based decision making or control for confounding. In many medical fields, a large number of prognostic scores are available, but practitioners may find it difficult to choose between them due to lack of external validation as well as lack of comparisons between them.

METHODS

Borrowing methodology from network meta-analysis, we describe an approach to Multiple Score Comparison meta-analysis (MSC) which permits concurrent external validation and comparisons of prognostic scores using individual patient data (IPD) arising from a large-scale international collaboration. We describe the challenges in adapting network meta-analysis to the MSC setting, for instance the need to explicitly include correlations between the scores on a cohort level, and how to deal with many multi-score studies. We propose first using IPD to make cohort-level aggregate discrimination or calibration scores, comparing all to a common comparator. Then, standard network meta-analysis techniques can be applied, taking care to consider correlation structures in cohorts with multiple scores. Transitivity, consistency and heterogeneity are also examined.

RESULTS

We provide a clinical application, comparing prognostic scores for 3-year mortality in patients with chronic obstructive pulmonary disease using data from a large-scale collaborative initiative. We focus on the discriminative properties of the prognostic scores. Our results show clear differences in performance, with ADO and eBODE showing higher discrimination with respect to mortality than other considered scores. The assumptions of transitivity and local and global consistency were not violated. Heterogeneity was small.

CONCLUSIONS

We applied a network meta-analytic methodology to externally validate and concurrently compare the prognostic properties of clinical scores. Our large-scale external validation indicates that the scores with the best discriminative properties to predict 3 year mortality in patients with COPD are ADO and eBODE.

Smooth time-dependent receiver operating characteristic curve estimators

The receiver operating characteristic curve is a popular graphical method often used to study the diagnostic capacity of continuous (bio)markers. When the considered outcome is a time-dependent variable, two main extensions have been proposed: the cumulative/dynamic receiver operating characteristic curve and the incident/dynamic receiver operating characteristic curve. In both cases, the main problem for developing appropriate estimators is the estimation of the joint distribution of the variables time-to-event and marker. As usual, different approximations lead to different estimators. In this article, the authors explore the use of a bivariate kernel density estimator which accounts for censored observations in the sample and produces smooth estimators of the time-dependent receiver operating characteristic curves. The performance of the resulting cumulative/dynamic and incident/dynamic receiver operating characteristic curves is studied by means of Monte Carlo simulations. Additionally, the influence of the choice of the required smoothing parameters is explored. Finally, two real-applications are considered. An R package is also provided as a complement to this article.

Classification of Airflow Limitation Based on z-Score Underestimates Mortality in Patients with Chronic Obstructive Pulmonary Disease

RATIONALE

Global Lung Function Initiative recommends reporting lung function measures as z-score, and a classification of airflow limitation (AL) based on this parameter has recently been proposed.

OBJECTIVES

To evaluate the prognostic capacity of the AL classifications based on z-score or percentage predicted of FEV₁ in patients with chronic obstructive pulmonary disease (COPD).

METHODS

A cohort of 2,614 patients with COPD recruited outside the hospital setting was examined after a mean (± SD) of 57 ± 13 months of follow-up, totaling 10,322 person-years. All-cause mortality was analyzed, evaluating the predictive capacity of several AL staging systems.

MEASUREMENTS AND MAIN RESULTS

Based on Global Initiative for Chronic Obstructive Lung Disease guidelines, 461 patients (17.6%) had mild, 1,452 (55.5%) moderate, 590 (22.6%) severe, and 111 (4.2%) very severe AL. According to z-score classification, 66.3% of patients remained with the same severity, whereas 23.7% worsened and 10.0% improved. Unlike other staging systems, patients with severe AL according to z-score had higher mortality than those with very severe AL (increase of risk by 5.2 and 3.9 times compared with mild AL, respectively). The predictive capacity for 5-year survival was slightly higher for FEV₁ expressed as percentage of predicted than as z-score (area under the curve: 0.714-0.760 vs. 0.649-0.708, respectively). A severity-dependent relationship between AL grades by z-score and mortality was only detected in patients younger than age 60 years.

CONCLUSIONS

In patients with COPD, the AL classification based on z-score predicts worse mortality than those based on percentage of predicted. It is possible that the z-score underestimates AL severity in patients older than 60 years of age with severe functional impairment.

Prognostic variables and scores identifying the end of life in COPD: a systematic review

INTRODUCTION

COPD is a major cause of mortality, and the unpredictable trajectory of the disease can bring challenges to end-of-life care. We aimed to investigate known prognostic variables and scores that predict prognosis in COPD in a systematic literature review, specifically including variables that contribute to risk assessment of patients for death within 12 months.

METHODS

We conducted a systematic review on prognostic variables, multivariate score or models for COPD. Ovid MEDLINE, EMBASE, the Cochrane database, Cochrane CENTRAL, DARE and CINAHL were searched up to May 1, 2016.

RESULTS

A total of 5,276 abstracts were screened, leading to 516 full-text reviews, and 10 met the inclusion criteria. No multivariable indices were developed with the specific aim of predicting all-cause mortality in stable COPD within 12 months. Only nine indices were identified from four studies, which had been validated for this time period. Tools developed using expert knowledge were also identified, including the Gold Standards Framework Prognostic Indicator Guidance, the RADboud Indicators of Palliative Care Needs, the Supportive and Palliative Care Indicators Tool and the Necesidades Paliativas program tool.

CONCLUSION

A number of variables contributing to the prediction of all-cause mortality in COPD were identified. However, there are very few studies that are designed to assess, or report, the prediction of mortality at or less than 12 months. The quality of evidence remains low, such that no single variable or multivariable score can currently be recommended.

Development of the ProPal-COPD tool to identify patients with COPD for proactive palliative care

Background

Our objective was to develop a tool to identify patients with COPD for proactive palliative care. Since palliative care needs increase during the disease course of COPD, the prediction of mortality within 1 year, measured during hospitalizations for acute exacerbation COPD (AECOPD), was used as a proxy for the need of proactive palliative care.

Patients and methods

Patients were recruited from three general hospitals in the Netherlands in 2014. Data of 11 potential predictors, a priori selected based on literature, were collected during hospitalization for AECOPD. After 1 year, the medical files were explored for the date of death. An optimal prediction model was assessed by Lasso logistic regression, with 20-fold cross-validation for optimal shrinkage. Missing data were handled using complete case analysis.

Results

Of 174 patients, 155 patients were included; of those 30 (19.4%) died within 1 year. The optimal prediction model was internally validated and had good discriminating power (AUC =0.82, 95% CI 0.81–0.82). This model relied on the following seven predictors: the surprise question, Medical Research Council dyspnea questionnaire (MRC dyspnea), Clinical COPD Questionnaire (CCQ), FEV₁% of predicted value, body mass index, previous hospitalizations for AECOPD and specific comorbidities. To ensure minimal miss out of patients in need of proactive palliative care, we proposed a cutoff in the model that prioritized sensitivity over specificity (0.90 over 0.73, respectively). Our model (ProPal-COPD tool) was a stronger predictor of mortality within 1 year than the CODEX (comorbidity, age, obstruction, dyspnea, and previous severe exacerbations) index.

Conclusion

The ProPal-COPD tool is a promising multivariable prediction tool to identify patients with COPD for proactive palliative care.

[Chronic obstructive pulmonary disease in real life. LEONPOC study]

OBJECTIVE

The purpose of this study was to evaluate different characteristics of COPD patients according to phenotypes and GOLD guidelines.according to GesEPOC phenotypes and GOLD 2011 ABCD guidelines and pharmacological treatment agreement.

DESIGN

Cross-sectional survey.

LOCATION

COPD patients aged 40-85 from León were randomly selected from Primary Care database, MEDORA.

PARTICIPANTS

5222 eligible COPD patients were collected from MEDORA database. We calculated a sample size of 734 patients and finally studied 577 of them.

MAIN MEASUREMENTS

Patientś clinical, functional and health related quality of life information were collected. Spirometry and postbroncodilator test were performed.

RESULTS

A total of 577 patients were included in this study. 28.7% of them did not have a spirometry recorded in their files. 123 patients had a normal or non-obstructive spirometry pattern, so they were excluded from a COPD diagnostic. With regard to treatments, there was an overprescribing of inhaled steroids in patients from GOLD A and B groups, and also in patients with the called exacerbator phenotype (GesEPOC).

CONCLUSION

Although there have been several published guidelines, management of COPD patients in real life should be improved.

COPD in HIV-Infected Patients: CD4 Cell Count Highly Correlated

Background

COPD is a frequent and significant cause of respiratory morbidity in HIV-infected patients despite the control of HIV. We aimed to analyze the factors correlated with COPD in this population to evaluate the existence of specific indicators of vulnerability in this population.

Methods and Findings

623 HIV-infected outpatients were enrolled during one year. This population was characterised by a dedicated questionnaire and electronic patient records. COPD screening was performed according to recommended spirometric criteria. The prevalence of COPD was 9.0%. Age and smoking were independently correlated with COPD (OR, 1.61 per 10 years increase, P = 0.007; OR, 1.28 per 10 pack-year increase, P = 0.003, respectively). Body mass index (BMI) and CD4 cell-count were independently and negatively correlated with COPD (OR, 0.78, P < 0.001; 0R, 0.77 per 100 cell/mm³ increase, P < 0.001, respectively). Among COPD patients, 77% did not know their diagnosis. Five COPD-patients never smoked and 44.2% did not have any respiratory symptoms and so were not eligible to perform a spirometry according to the guidelines.

Conclusions

In addition to known risk factors, immune defect through CD4 cell count was independently and strongly correlated with COPD. COPD is largely underdiagnosed and thus unmanaged. However, early management and urgent smoking cessation are essential to improve prognosis. Clinicians’ awareness on the particular vulnerability for COPD in HIV-infected patients is crucial. Moreover, indications to perform conventional spirometry to diagnose COPD may include more parameters than tobacco-smoking and respiratory complaints with a particular concern toward patients with a profound CD4 cell count defect.

Comparison of World Health Organization and Asia-Pacific body mass index classifications in COPD patients

INTRODUCTION

A low body mass index (BMI) is associated with increased mortality and low health-related quality of life in patients with COPD. The Asia-Pacific classification of BMI has a lower cutoff for overweight and obese categories compared to the World Health Organization (WHO) classification. The present study assessed patients with COPD among different BMI categories according to two BMI classification systems: WHO and Asia-Pacific.

PATIENTS AND METHODS

Patients with COPD aged 40 years or older from the Korean COPD Subtype Study cohort were selected for evaluation. We enrolled 1,462 patients. Medical history including age, sex, St George's Respiratory Questionnaire (SGRQ-C), the modified Medical Research Council (mMRC) dyspnea scale, and post-bronchodilator forced expiratory volume in 1 second (FEV₁) were evaluated. Patients were categorized into different BMI groups according to the two BMI classification systems.

RESULT

FEV₁ and the diffusing capacity of the lung for carbon monoxide (DLCO) percentage revealed an inverse "U"-shaped pattern as the BMI groups changed from underweight to obese when WHO cutoffs were applied. When Asia-Pacific cutoffs were applied, FEV₁ and DLCO (%) exhibited a linearly ascending relationship as the BMI increased, and the percentage of patients in the overweight and obese groups linearly decreased with increasing severity of the Global Initiative for Chronic Obstructive Lung Disease criteria. From the underweight to the overweight groups, SGRQ-C and mMRC had a decreasing relationship in both the WHO and Asia-Pacific classifications. The prevalence of comorbidities in the different BMI groups showed similar trends in both BMI classifications systems.

CONCLUSION

The present study demonstrated that patients with COPD who have a high BMI have better pulmonary function and health-related quality of life and reduced dyspnea symptoms. Furthermore, the Asia-Pacific BMI classification more appropriately reflects the correlation of obesity and disease manifestation in Asian COPD patients than the WHO classification.

Classification of patients with chronic obstructive pulmonary disease according to the Latin American Thoracic Association (ALAT) staging systems and the global initiative for chronic obstructive pulmonary disease (GOLD)

INTRODUCTION

Several classification systems use different criteria when assessing COPD stages. The objective of this study was to compare the prevalence and distribution of COPD stagesusing Global initiative for chronic Obstructive Lung Disease (GOLD) recommendationsand Latin American Thoracic Association (ALAT) guidelinesin a primary-care population.

METHODS

Subjects attending routine primary care visits, ≥40 years of age, current or former smokers or exposed to biomass, completed a questionnaire and performed spirometry. COPD was defined as post-bronchodilator FEV₁/FVC<0.70 and categorised according to GOLD-2013 criteria and ALAT-2014 guideline. The BODEx index was used to assess the prognostic value of the stratification systems.

RESULTS

A total of 1743 subjects completed the interview, 1540 performed acceptable spirometry. COPD prevalence according GOLD-2013 was 20.1% and had a U-shaped stage distribution (group A: 9.3%, B: 4.3%, C: 2.0%, D: 4.6%). According to ALAT, prevalence was 19.7% with a bell-shaped stage distribution (mild: 2.9%, moderate: 9%, severe: 5.4%, very-severe: 2.7%). Approximately 73% of patients were stratified as moderate (45.4%) or severe (27.3%) by ALAT guidelines, whereas using GOLD-2013 criteria the majority of subjects (approximately 69%) were in group A (46.3%) or group B (22.7%). BODE index score increased as COPD worsened according to ALAT stratification. This is not observed with GOLD2013 criteria (similar values for B and C groups).

CONCLUSIONS

Disease stages differ under ALAT and GOLD-2013 criteria. ALAT identified a greater proportion of COPD subjects in the moderate and severe categories compared with GOLD-2013, where the majority were categorised in group A. Future evaluation of the ALAT classification should address its predictive ability in terms of hospitalizations and mortality.

Application of a parametric model in the mortality risk analysis of ICU patients with severe COPD

OBJECTIVE

To evaluate the mortality risk factors of patients with severe chronic obstructive pulmonary disease (COPD) in the intensive care unit (ICU) by utilizing parametric model of survival analysis, and to estimate patients' prognoses based on the risk and survival functions in the model.

METHODS

The clinical data and outcomes of COPD patients admitted to a respiratory intensive care unit (RICU) at Beijing Chao-Yang Hospital from January 2009 to June 2014 were prospectively collected. Based on the clinical outcomes, these patients were divided into a survival group and a death group. A univariate analysis was conducted to identify statistically significant variables. According to the distribution characteristics of these data, residual plots were prepared for an exponential model, a Weibull model and a Gamma model. The Gamma model was determined to be the best fitted for these data and was used as the analytical tool. Therefore, the variables with differences obtained from the univariate analysis were put into the Gamma model to determine the patients' mortality risk factors. The risk and survival functions were also generated according to the model formula.

RESULTS

A total of 160 patients (111 survival, 49 death) were enrolled. The univariate analysis showed that, compared with the survival group, patients in the death group had higher Charlson Comorbidity Index score (CCI), higher body temperature, higher white blood cell counts, higher proportions of neutrophils, higher serum creatinine levels and higher pH levels; lower resting carbon dioxide pressure (PCO₂ ); and more cases complicated with invasive pulmonary aspergillosis (IPA). A further analysis with the Gamma model revealed that concurrent or non-concurrent IPA, white blood cell count, pH level and PCO₂ were associated with the patients' mortality risk and that the predicted value (PV) of the patients' mortality risk = 2.8655 + 0.4070 × IPA + 0.0048 × WBC + 0.0049 × pH - 0.0097 × PCO₂ . Moreover, the survival function formula was obtained according to the Gamma model: S(x) = 1 - I (0.7507 x, -3.3773), where I is an incomplete gamma function.

CONCLUSION

Formula generated from parametric model may help to predict the prognosis of patients with severe COPD in ICU, and this method need to be evaluated in further studies. According to our formula, IPA is an important risk factor of mortality for patients with severe COPD in the ICU.

Prognostic assessment in COPD without lung function: the B-AE-D indices

Several composite markers have been proposed for risk assessment in chronic obstructive pulmonary disease (COPD). However, choice of parameters and score complexity restrict clinical applicability. Our aim was to provide and validate a simplified COPD risk index independent of lung function.The PROMISE study (n=530) was used to develop a novel prognostic index. Index performance was assessed regarding 2-year COPD-related mortality and all-cause mortality. External validity was tested in stable and exacerbated COPD patients in the ProCOLD, COCOMICS and COMIC cohorts (total n=2988).Using a mixed clinical and statistical approach, body mass index (B), severe acute exacerbations of COPD frequency (AE), modified Medical Research Council dyspnoea severity (D) and copeptin (C) were identified as the most suitable simplified marker combination. 0, 1 or 2 points were assigned to each parameter and totalled to B-AE-D or B-AE-D-C. It was observed that B-AE-D and B-AE-D-C were at least as good as BODE (body mass index, airflow obstruction, dyspnoea, exercise capacity), ADO (age, dyspnoea, airflow obstruction) and DOSE (dyspnoea, obstruction, smoking, exacerbation) indices for predicting 2-year all-cause mortality (c-statistic: 0.74, 0.77, 0.69, 0.72 and 0.63, respectively; Hosmer-Lemeshow test all p>0.05). Both indices were COPD specific (c-statistic for predicting COPD-related 2-year mortality: 0.87 and 0.89, respectively). External validation of B-AE-D was performed in COCOMICS and COMIC (c-statistic for 1-year all-cause mortality: 0.68 and 0.74; c-statistic for 2-year all-cause mortality: 0.65 and 0.67; Hosmer-Lemeshow test all p>0.05).The B-AE-D index, plus copeptin if available, allows a simple and accurate assessment of COPD-related risk.

Multi-component assessment of chronic obstructive pulmonary disease: an evaluation of the ADO and DOSE indices and the global obstructive lung disease categories in international primary care data sets

Suitable tools for assessing the severity of chronic obstructive pulmonary disease (COPD) include multi-component indices and the global initiative for chronic obstructive lung disease (GOLD) categories. The aim of this study was to evaluate the dyspnoea, obstruction, smoking, exacerbation (DOSE) and the age, dyspnoea, obstruction (ADO) indices and GOLD categories as measures of current health status and future outcomes in COPD patients. This was an observational cohort study comprising 5,114 primary care COPD patients across three databases from UK, Sweden and Holland. The associations of DOSE and ADO indices with (i) health status using the Clinical COPD Questionnaire (CCQ) and St George's Respiratory Questionnaire (SGRQ) and COPD Assessment test (CAT) and with (ii) current and future exacerbations, admissions and mortality were assessed in GOLD categories and DOSE and ADO indices. DOSE and ADO indices were significant predictors of future exacerbations: incident rate ratio was 1.52 (95% confidence intervals 1.46-1.57) for DOSE, 1.16 (1.12-1.20) for ADO index and 1.50 (1.33-1.68) and 1.23 (1.10-1.39), respectively, for hospitalisations. Negative binomial regression showed that the DOSE index was a better predictor of future admissions than were its component items. The hazard ratios for mortality were generally higher for ADO index groups than for DOSE index groups. The GOLD categories produced widely differing assessments for future exacerbation risk or for hospitalisation depending on the methods used to calculate them. None of the assessment systems were excellent at predicting future risk in COPD; the DOSE index appears better than the ADO index for predicting many outcomes, but not mortality. The GOLD categories predict future risk inconsistently. The DOSE index and the GOLD categories using exacerbation frequency may be used to identify those at high risk for exacerbations and admissions.

COPD control: Can a consensus be found?

There are currently no reliable instruments for assessing the onset and progression of chronic obstructive pulmonary disease (COPD) or predicting its prognosis. Currently, a comprehensive assessment of COPD including several objective and subjective parameters is recommended. However, the lack of biomarkers precludes a correct assessment of COPD severity, which consequently hampers adequate therapeutic approaches and COPD control. In the absence of a definition of "well-controlled disease", a consensus regarding COPD control will be difficult to reach. However, COPD patient assessment should be multidimensional, and anchored in five points: control of symptoms, decline of pulmonary function, levels of physical activity, exacerbations, and Quality of Life. Several non-pharmacological and pharmacological measures are currently available to achieve disease control. Smoking cessation, vaccination, exercise training programs and pulmonary rehabilitation are recognized as important non-pharmacological measures but bronchodilators are the pivotal therapy in the control of COPD. This paper discusses several objective and subjective parameters that may bridge the gap between disease assessment and disease control. The authors conclude that, at present, it is not possible to reach a consensus regarding COPD control, essentially due to the lack of objective instruments to measure it. Some recommendations are set forth, but true COPD control awaits further objective assessments.

Palliative care outcome measures in COPD patients: a conceptual review

In chronic obstructive pulmonary disease (COPD), palliative care is appropriate in very advanced stages based on recognition of its need when conventional therapy is no longer able to control symptoms, disease morbidity, or to improve/maintain an acceptable quality of life. Palliative care aims to improve quality of life, or, if applied specifically at the end-of-life, to ensure comfortable care. In COPD palliative care effectiveness of interventions should be quantified with outcome measures able to better capture the holistic nature of approaches and not only the specific features of disease. These should include: physical outcomes, psychological outcomes, social outcomes, spiritual outcomes. Such measures are discussed in this review along with arguments supporting their use.

An official American Thoracic Society/European Respiratory Society statement: research questions in COPD

Chronic obstructive pulmonary disease (COPD) is a leading cause of morbidity, mortality and resource use worldwide. The goal of this official American Thoracic Society (ATS)/European Respiratory Society (ERS) Research Statement is to describe evidence related to diagnosis, assessment, and management; identify gaps in knowledge; and make recommendations for future research. It is not intended to provide clinical practice recommendations on COPD diagnosis and management.

Clinicians, researchers and patient advocates with expertise in COPD were invited to participate. A literature search of Medline was performed, and studies deemed relevant were selected. The search was not a systematic review of the evidence. Existing evidence was appraised and summarised, and then salient knowledge gaps were identified.

Recommendations for research that addresses important gaps in the evidence in all areas of COPD were formulated via discussion and consensus.

Great strides have been made in the diagnosis, assessment and management of COPD, as well as understanding its pathogenesis. Despite this, many important questions remain unanswered. This ATS/ERS research statement highlights the types of research that leading clinicians, researchers and patient advocates believe will have the greatest impact on patient-centred outcomes.

ATS/ERS statement highlighting research areas that will have the greatest impact on patient-centred outcomes in COPDhttp://ow.ly/LXW2J