ICE COLD ERIC--International collaborative effort on chronic obstructive lung disease: exacerbation risk index cohorts--study protocol for an international COPD cohort study

Causal Mediation Analysis with Multiple Time-varying Mediators

In longitudinal studies with time-varying exposures and mediators, the mediational g-formula is an important method for the assessment of direct and indirect effects. However, current methodologies based on the mediational g-formula can deal with only one mediator. This limitation makes these methodologies inapplicable to many scenarios. Hence, we develop a novel methodology by extending the mediational g-formula to cover cases with multiple time-varying mediators. We formulate two variants of our approach that are each suited to a distinct set of assumptions and effect definitions and present nonparametric identification results of each variant. We further show how complex causal mechanisms (whose complexity derives from the presence of multiple time-varying mediators) can be untangled. We implemented a parametric method, along with a user-friendly algorithm, in R software. We illustrate our method by investigating the complex causal mechanism underlying the progression of chronic obstructive pulmonary disease. We found that the effects of lung function impairment mediated by dyspnea symptoms accounted for 14.6% of the total effect and that mediated by physical activity accounted for 11.9%. Our analyses thus illustrate the power of this approach, providing evidence for the mediating role of dyspnea and physical activity on the causal pathway from lung function impairment to health status. See video abstract at, http://links.lww.com/EDE/B988 .

On the Conventional Definition of Path-specific Effects: Fully Mediated Interaction With Multiple Ordered Mediators

Path-specific effects are a critical measure for assessing mediation in the presence of multiple mediators. However, the conventional definition of path-specific effects has generated controversy because it often causes misinterpretation of the results of multiple mediator analysis. For in-depth analysis of this issue, we propose the concept of decomposing fully mediated interaction from the average causal effect. We show that misclassification of fully mediated interaction is the main cause of misinterpretation of path-specific effects. We propose two strategies for specifying fully mediated interaction: isolating and reclassifying fully mediated interaction. The choice of strategy depends on the objective. Isolating fully mediated interaction is the superior strategy when the main objective is elucidating the mediation mechanism, whereas reclassifying it is superior when the main objective is precisely interpreting the mediation analysis results. To compare performance, this study used the two proposed strategies and the conventional decomposition strategy to analyze the mediating roles of dyspnea and anxiety in the effect of impaired lung function on poor health status in a population of patients with chronic obstructive pulmonary disease. The estimation result showed that the conventional decomposition strategy underestimates the importance of dyspnea as a mechanism of this disease. Specifically, the strategy of reclassifying fully mediated interaction revealed that 50% of the average causal effect is attributable to mediating effects, particularly the mediating effect of dyspnea.

Latent growth modeling of IRT versus CTT measured longitudinal latent variables

Latent growth models are often used to measure individual trajectories representing change over time. The characteristics of the individual trajectories depend on the variability in the longitudinal outcomes. In many medical and epidemiological studies, the individual health outcomes cannot be observed directly and are indirectly observed through indicators (i.e. items of a questionnaire). An item response theory or a classical test theory measurement model is required, but the choice can influence the latent growth estimates. In this study, under various conditions, this influence is directly assessed by estimating latent growth parameters on a common scale for item response theory and classical test theory using a novel plausible value method in combination with Markov chain Monte Carlo. The latent outcomes are considered missing data and plausible values are generated from the corresponding posterior distribution, separately for item response theory and classical test theory. These plausible values are linearly transformed to a common scale. A Markov chain Monte Carlo method was developed to simultaneously estimate the latent growth and measurement model parameters using this plausible value technique. It is shown that estimated individual trajectories using item response theory, compared to classical test theory to measure outcomes, provide a more detailed description of individual change over time, since item response patterns (item response theory) are more informative about the health measurements than sum scores (classical test theory).

The dyspnoea-inactivity vicious circle in COPD: development and external validation of a conceptual model

The vicious circle of dyspnoea-inactivity has been proposed, but never validated empirically, to explain the clinical course of chronic obstructive pulmonary disease (COPD). We aimed to develop and validate externally a comprehensive vicious circle model.We utilised two methods. 1) Identification and validation of all published vicious circle models by a systematic literature search and fitting structural equation models to longitudinal data from the Spanish PAC-COPD (Phenotype and Course of COPD) cohort (n=210, mean age 68 years, mean forced expiratory volume in 1 s (FEV1) 54% predicted), testing both the hypothesised relationships between variables in the model ("paths") and model fit. 2) Development of a new model and external validation using longitudinal data from the Swiss and Dutch ICE COLD ERIC (International Collaborative Effort on Chronic Obstructive Lung Disease: Exacerbation Risk Index Cohorts) cohort (n=226, mean age 66 years, mean FEV1 57% predicted).We identified nine vicious circle models for which structural equation models confirmed most hypothesised paths but showed inappropriate fit. In the new model, airflow limitation, hyperinflation, dyspnoea, physical activity, exercise capacity and COPD exacerbations remained related to other variables and model fit was appropriate. Fitting it to ICE COLD ERIC, all paths were replicated and model fit was appropriate.Previously published vicious circle models do not fully explain the vicious circle concept. We developed and externally validated a new comprehensive model that gives a more relevant role to exercise capacity and COPD exacerbations.

Effects of the "Living well with COPD" intervention in primary care: a comparative study

The pivotal objective of chronic obstructive pulmonary disease (COPD) self-management programmes is behaviour change to avoid moderate and severe exacerbations and improve health related quality of life.In a prospectively planned, controlled study, COPD patients who participated in the "Living well with COPD" (LWWCOPD) self-management intervention were compared with usual care patients from the primary care COPD Cohort ICE COLD ERIC, who did not receive self-management intervention (NCT00706602) The primary outcome was behaviour change and disease-specific health related quality of life after 1 year. Secondary end-points included exacerbation rates. We calculated mixed linear, zero-inflated negative binomial and logistic regression models and used propensity scores to counteract confounding.467 patients, 71 from the LWWCOPD and 396 from the usual care cohort, were included. The differences between intervention and control were 0.54 (95% CI 0.13-0.94) on the Chronic Respiratory Questionnaire domain "mastery", 0.55 (95% CI 0.11-0.99) on "fatigue", 0.54 (0.14-0.93) on "emotional function" and 0.64 (95% CI 0.14-1.14) on "dyspnoea". The intervention considerably reduced the risk of moderate and severe exacerbations (incidence rate ratio 0.36, 95% CI 0.25-0.52).Self-management coaching in primary care improves health-related quality of life and lowers exacerbation rates and health care use.

Do COPD subtypes really exist? COPD heterogeneity and clustering in 10 independent cohorts

BACKGROUND

COPD is a heterogeneous disease, but there is little consensus on specific definitions for COPD subtypes. Unsupervised clustering offers the promise of 'unbiased' data-driven assessment of COPD heterogeneity. Multiple groups have identified COPD subtypes using cluster analysis, but there has been no systematic assessment of the reproducibility of these subtypes.

OBJECTIVE

We performed clustering analyses across 10 cohorts in North America and Europe in order to assess the reproducibility of (1) correlation patterns of key COPD-related clinical characteristics and (2) clustering results.

METHODS

We studied 17 146 individuals with COPD using identical methods and common COPD-related characteristics across cohorts (FEV₁, FEV₁/FVC, FVC, body mass index, Modified Medical Research Council score, asthma and cardiovascular comorbid disease). Correlation patterns between these clinical characteristics were assessed by principal components analysis (PCA). Cluster analysis was performed using k-medoids and hierarchical clustering, and concordance of clustering solutions was quantified with normalised mutual information (NMI), a metric that ranges from 0 to 1 with higher values indicating greater concordance.

RESULTS

The reproducibility of COPD clustering subtypes across studies was modest (median NMI range 0.17-0.43). For methods that excluded individuals that did not clearly belong to any cluster, agreement was better but still suboptimal (median NMI range 0.32-0.60). Continuous representations of COPD clinical characteristics derived from PCA were much more consistent across studies.

CONCLUSIONS

Identical clustering analyses across multiple COPD cohorts showed modest reproducibility. COPD heterogeneity is better characterised by continuous disease traits coexisting in varying degrees within the same individual, rather than by mutually exclusive COPD subtypes.

Prediction of long-term clinical outcomes using simple functional exercise performance tests in patients with COPD: a 5-year prospective cohort study

The 1-min sit-to-stand (1-min STS) test and handgrip strength test have been proposed as simple tests of functional exercise performance in chronic obstructive pulmonary disease (COPD) patients. We assessed the long-term (5-year) predictive performance of the 1-min sit-to-stand and handgrip strength tests for mortality, health-related quality of life (HRQoL) and exacerbations in COPD patients. In 409 primary care patients, we found the 1-min STS test to be strongly associated with long-term morality (hazard ratio per 3 more repetitions: 0.81, 95% CI 0.65 to 0.86) and moderately associated with long-term HRQoL. Neither test was associated with exacerbations. Our results suggest that the 1-min STS test may be useful for assessing the health status and long-term prognosis of COPD patients. This study was registered at http://www.clinicaltrials.gov/ (NCT00706602, 25 June 2008).

Physical activity and risk of comorbidities in patients with chronic obstructive pulmonary disease: a cohort study

Multi-morbidity is common in patients with chronic obstructive pulmonary disease and low levels of physical activity are hypothesized to be an important risk factor. The current study aimed to assess the longitudinal association between physical activity and risk of seven categories of comorbidity in chronic obstructive pulmonary disease patients. The study included 409 patients from primary care practice in the Netherlands and Switzerland. We assessed physical activity using the Longitudinal Ageing Study Amsterdam Physical Activity Questionnaire at baseline and followed patients for up to 5 years. During follow-up, patients reported their comorbidities (cardiovascular, neurological, endocrine, musculoskeletal, malignant, and infectious diseases) and completed the Hospital Anxiety and Depression Scale questionnaire for mental health assessment. We implemented multinomial logistic regression (an approximation to discrete time survival model using death as a competing risk) for our analysis. Study results did not suggest a statistically significant association of baseline physical activity with the development of seven categories of comorbidity. However, when we focused on depression and anxiety symptoms, we found that higher levels of physical activity at baseline were associated with a lower risk for depression (adjusted hazard ratio, 0.85; 0.75–0.95; p = 0.005) and anxiety (adjusted hazard ratio, 0.89; 0.79–1.00; p = 0.045). In chronic obstructive pulmonary disease patients, those with high physical activity are less likely to develop depression or anxiety symptoms over time. Increasing physical activity in chronic obstructive pulmonary disease patients may be an approach for testing to lower the burden from incident depression and anxiety.

Patients with chronic lung disease who stay physically active could reduce their chances of depression and anxiety. Milo Puhan at the University of Zurich, Switzerland, and co-workers assessed the association between physical activity and the risk of developing various co-existing diseases in 409 patients with chronic obstructive pulmonary disease (COPD). Co-morbidities such as cardiovascular diseases, diabetes and depression are prevalent in patients with COPD, but the reasons why are not clear. Puhan’s team assessed patients’ activity levels using an existing questionnaire, and administered another questionnaire to assess mental health. They followed the cohort for 5 years. Results indicated weak associations between physical activity levels and most physical illnesses, but there were significant links between higher levels of physical activity and a reduced risk of depression and anxiety. The results could inform novel COPD treatment programs.

The Inaccuracy of Patient Recall for COPD Exacerbation Rate Estimation and Its Implications: Results from Central Adjudication

BACKGROUND

COPD exacerbation incidence rates are often ascertained retrospectively through patient recall and self-reports. We compared exacerbation ascertainment through patient self-reports and single-physician chart review to central adjudication by a committee and explored determinants and consequences of misclassification.

METHODS

Self-reported exacerbations (event-based definition) in 409 primary care patients with COPD participating in the International Collaborative Effort on Chronic Obstructive Lung Disease: Exacerbation Risk Index Cohorts (ICE COLD ERIC) cohort were ascertained every 6 months over 3 years. Exacerbations were adjudicated by single experienced physicians and an adjudication committee who had information from patient charts. We assessed the accuracy (sensitivities and specificities) of self-reports and single-physician chart review against a central adjudication committee (AC) (reference standard). We used multinomial logistic regression and bootstrap stability analyses to explore determinants of misclassifications.

RESULTS

The AC identified 648 exacerbations, corresponding to an incidence rate of 0.60 ± 0.83 exacerbations/patient-year and a cumulative incidence proportion of 58.9%. Patients self-reported 841 exacerbations (incidence rate, 0.75 ± 1.01; incidence proportion, 59.7%). The sensitivity and specificity of self-reports were 84% and 76%, respectively, those of single-physician chart review were between 89% and 96% and 87% and 99%, respectively. The multinomial regression model and bootstrap selection showed that having experienced more exacerbations was the only factor consistently associated with underreporting and overreporting of exacerbations (underreporters: relative risk ratio [RRR], 2.16; 95% CI, 1.76-2.65 and overreporters: RRR, 1.67; 95% CI, 1.39-2.00).

CONCLUSIONS

Patient 6-month recall of exacerbation events are inaccurate. This may lead to inaccurate estimates of incidence measures and underestimation of treatment effects. The use of multiple data sources combined with event adjudication could substantially reduce sample size requirements and possibly cost of studies.

CLINICAL TRIAL REGISTRATION

www.ClinicalTrials.gov, NCT00706602.

Determinants of Physical Activity in Patients with Chronic Obstructive Pulmonary Disease: A 5-Year Prospective Follow-Up Study

BACKGROUND

Although many studies examined determinants of physical activity in patients with chronic obstructive pulmonary disease (COPD), most were cross-sectional and focused on single determinants only.

OBJECTIVES

The aim of this study was to determine how COPD patients' physical activity changes over time and to identify the determinants of physical activity using multivariable and longitudinal methods.

METHODS

In a prospective cohort study, 409 primary care patients with COPD in the Netherlands and Switzerland were followed for up to 5 years. Physical activity was assessed at baseline and every 6 months using the Longitudinal Aging Study Amsterdam Physical Activity Questionnaire (LAPAQ) adapted to a 0- to 23-point scale. We studied the associations between determinants at baseline and patients' long-term physical activity levels using linear mixed models.

RESULTS

Unadjusted analysis showed an overall gradual decline in physical activity (0.22 points of the LAPAQ scale every 6 months, 95% CI: 0.17-0.28; p < 0.001). In multivariable analyses, baseline determinants that were independently associated (p ≤ 0.05) with lower long-term physical activity levels included (starting from coefficients with the smallest p value) lower exercise capacity, older age, working, more smoking pack-years, more fatigued, male sex, lower educational levels, previously not in fitness programs, more depressed, lower lung function, lower overall health status, and more prescription drug use.

CONCLUSIONS

We found that physical activity of COPD patients may decline more than reported in the healthy elderly. Longitudinal analysis identified independent determinants of physical activity, which allows the identification of patients having low physical activity levels and who may benefit from physical activity interventions.

Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): explanation and elaboration

The TRIPOD (Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis) Statement includes a 22-item checklist, which aims to improve the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. This explanation and elaboration document describes the rationale; clarifies the meaning of each item; and discusses why transparent reporting is important, with a view to assessing risk of bias and clinical usefulness of the prediction model. Each checklist item of the TRIPOD Statement is explained in detail and accompanied by published examples of good reporting. The document also provides a valuable reference of issues to consider when designing, conducting, and analyzing prediction model studies. To aid the editorial process and help peer reviewers and, ultimately, readers and systematic reviewers of prediction model studies, it is recommended that authors include a completed checklist in their submission. The TRIPOD checklist can also be downloaded from www.tripod-statement.org.

Validation of prediction models based on lasso regression with multiply imputed data

Background

In prognostic studies, the lasso technique is attractive since it improves the quality of predictions by shrinking regression coefficients, compared to predictions based on a model fitted via unpenalized maximum likelihood. Since some coefficients are set to zero, parsimony is achieved as well. It is unclear whether the performance of a model fitted using the lasso still shows some optimism. Bootstrap methods have been advocated to quantify optimism and generalize model performance to new subjects. It is unclear how resampling should be performed in the presence of multiply imputed data.

Method

The data were based on a cohort of Chronic Obstructive Pulmonary Disease patients. We constructed models to predict Chronic Respiratory Questionnaire dyspnea 6 months ahead. Optimism of the lasso model was investigated by comparing 4 approaches of handling multiply imputed data in the bootstrap procedure, using the study data and simulated data sets. In the first 3 approaches, data sets that had been completed via multiple imputation (MI) were resampled, while the fourth approach resampled the incomplete data set and then performed MI.

Results

The discriminative model performance of the lasso was optimistic. There was suboptimal calibration due to over-shrinkage. The estimate of optimism was sensitive to the choice of handling imputed data in the bootstrap resampling procedure. Resampling the completed data sets underestimates optimism, especially if, within a bootstrap step, selected individuals differ over the imputed data sets. Incorporating the MI procedure in the validation yields estimates of optimism that are closer to the true value, albeit slightly too larger.

Conclusion

Performance of prognostic models constructed using the lasso technique can be optimistic as well. Results of the internal validation are sensitive to how bootstrap resampling is performed.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2288-14-116) contains supplementary material, which is available to authorized users.

Prediction of COPD-specific health-related quality of life in primary care COPD patients: a prospective cohort study

Background:

Health-related quality of life (HRQL) is an important patient-reported outcome for chronic obstructive pulmonary disease (COPD).

Aim:

We developed models predicting chronic respiratory questionnaire (CRQ) dyspnoea, fatigue, emotional function, mastery and overall HRQL at 6 and 24 months using predictors easily available in primary care.

Methods:

We used the “least absolute shrinkage and selection operator” (lasso) method to build the models and assessed their predictive performance. Results were displayed using nomograms.

Results:

For each domain-specific CRQ outcome, the corresponding score at baseline was the best predictor. Depending on the domain, these predictions could be improved by adding one to six other predictors, such as the other domain-specific CRQ scores, health status and depression score. To predict overall HRQL, fatigue and dyspnoea scores were the best predictors. Predicted and observed values were on average the same, indicating good calibration. Explained variance ranged from 0.23 to 0.58, indicating good discrimination.

Conclusions:

To predict COPD-specific HRQL in primary care COPD patients, previous HRQL was the best predictor in our models. Asking patients explicitly about dyspnoea, fatigue, depression and how they cope with COPD provides additional important information about future HRQL whereas FEV₁ or other commonly used predictors add little to the prediction of HRQL.

The ADO index as a predictor of two-year mortality in general practice-based chronic obstructive pulmonary disease cohorts

BACKGROUND

Existing prediction models for mortality in chronic obstructive pulmonary disease (COPD) patients have not yet been validated in primary care, which is where the majority of patients receive care.

OBJECTIVES

Our aim was to validate the ADO (age, dyspnoea, airflow obstruction) index as a predictor of 2-year mortality in 2 general practice-based COPD cohorts.

METHODS

Six hundred and forty-six patients with COPD with GOLD (Global Initiative for Chronic Obstructive Lung Disease) stages I-IV were enrolled by their general practitioners and followed for 2 years. The ADO regression equation was used to predict a 2-year risk of all-cause mortality in each patient and this risk was compared with the observed 2-year mortality. Discrimination and calibration were assessed as well as the strength of association between the 15-point ADO score and the observed 2-year all-cause mortality.

RESULTS

Fifty-two (8.1%) patients died during the 2-year follow-up period. Discrimination with the ADO index was excellent with an area under the curve of 0.78 [95% confidence interval (CI) 0.71-0.84]. Overall, the predicted and observed risks matched well and visual inspection revealed no important differences between them across 10 risk classes (p = 0.68). The odds ratio for death per point increase according to the ADO index was 1.50 (95% CI 1.31-1.71).

CONCLUSIONS

The ADO index showed excellent prediction properties in an out-of-population validation carried out in COPD patients from primary care settings.

Five comorbidities reflected the health status in patients with chronic obstructive pulmonary disease: the newly developed COMCOLD index

OBJECTIVE

This study aimed to identify those comorbidities with greatest impact on patient-reported health status in patients with chronic obstructive pulmonary disease (COPD) and to develop a comorbidity index that reflects their combined impact.

STUDY DESIGN AND SETTING

We included 408 Swiss and Dutch primary care patients with COPD from the International Collaborative Effort on Chronic Obstructive Lung Disease: Exacerbation Risk Index Cohorts (ICE COLD ERIC) in this cross-sectional analysis. Primary outcome was the Feeling Thermometer, a patient-reported health status instrument. We assessed the impact of comorbidities at five cohort assessment times using multiple linear regression adjusted for FEV1, retaining comorbidities with associations P ≤ 0.1. We developed an index that reflects strength of association of comorbidities with health status.

RESULTS

Depression (prevalence: 13.0%; regression coefficient: -9.00; 95% CI: -13.52, -4.48), anxiety (prevalence: 11.8%; regression coefficient: -5.53; 95% CI -10.25, -0.81), peripheral artery disease (prevalence: 6.4%; regression coefficient: -5.02; 95% CI-10.64, 0.60), cerebrovascular disease (prevalence: 8.8%; regression coefficient: -4.57; 95% CI -9.43, 0.29), and symptomatic heart disease (prevalence: 20.3%; regression coefficient: -3.81; 95% CI -7.23, -0.39) were most strongly associated with the Feeling Thermometer. These five comorbidities, weighted, compose the COMorbidities in Chronic Obstructive Lung Disease (COMCOLD) index.

CONCLUSION

The COMCOLD index reflects the combined impact of five important comorbidities from patients' perspective and complements existing comorbidity indices that predict death. It may help clinicians focus on comorbidities affecting patients' health status the most.

All that glitters isn't gold: a survey on acknowledgment of limitations in biomedical studies

BACKGROUND

Acknowledgment of all serious limitations to research evidence is important for patient care and scientific progress. Formal research on how biomedical authors acknowledge limitations is scarce.

OBJECTIVES

To assess the extent to which limitations are acknowledged in biomedical publications explicitly, and implicitly by investigating the use of phrases that express uncertainty, so-called hedges; to assess the association between industry support and the extent of hedging.

DESIGN

We analyzed reporting of limitations and use of hedges in 300 biomedical publications published in 30 high and medium -ranked journals in 2007. Hedges were assessed using linguistic software that assigned weights between 1 and 5 to each expression of uncertainty.

RESULTS

Twenty-seven percent of publications (81/300) did not mention any limitations, while 73% acknowledged a median of 3 (range 1-8) limitations. Five percent mentioned a limitation in the abstract. After controlling for confounders, publications on industry-supported studies used significantly fewer hedges than publications not so supported (p = 0.028).

LIMITATIONS

Detection and classification of limitations was--to some extent--subjective. The weighting scheme used by the hedging detection software has subjective elements.

CONCLUSIONS

Reporting of limitations in biomedical publications is probably very incomplete. Transparent reporting of limitations may protect clinicians and guideline committees against overly confident beliefs and decisions and support scientific progress through better design, conduct or analysis of new studies.

Simple functional performance tests and mortality in COPD

Exercise tests are important to characterise chronic obstructive pulmonary disease patients and predict their prognosis, but are often not available outside of rehabilitation or research settings. Our aim was to assess the predictive performance of the sit-to-stand and handgrip strength tests.

The prospective cohort study in Dutch and Swiss primary care settings included a broad spectrum of patients (n=409) with Global Initiative for Chronic Obstructive Lung Disease stages II to IV. To assess the association of the tests with outcomes, we used Cox proportional hazards (mortality), negative binomial (centrally adjudicated exacerbations) and mixed linear regression models (longitudinal health-related quality of life) while adjusting for age, sex and severity of disease.

The sit-to-stand test was strongly (adjusted hazard ratio per five more repetitions of 0.58, 95% CI 0.40–0.85; p=0.004) and the handgrip strength test moderately strongly (0.84, 95% CI 0.72–1.00; p=0.04) associated with mortality. Both tests were also significantly associated with health-related quality of life but not with exacerbations. The sit-to-stand test alone was a stronger predictor of 2-year mortality (area under curve 0.78) than body mass index (0.52), forced expiratory volume in 1 s (0.61), dyspnoea (0.63) and handgrip strength (0.62).

The sit-to-stand test may close an important gap in the evaluation of exercise capacity and prognosis of chronic obstructive pulmonary disease patients across practice settings.

The 1-min sit-to-stand test predicts mortality in COPD patients and can easily be implemented across practice settingshttp://ow.ly/mxrPx

Multidimensional prognostic indices for use in COPD patient care. A systematic review

Background

A growing number of prognostic indices for chronic obstructive pulmonary disease (COPD) is developed for clinical use. Our aim is to identify, summarize and compare all published prognostic COPD indices, and to discuss their performance, usefulness and implementation in daily practice.

Methods

We performed a systematic literature search in both Pubmed and Embase up to September 2010. Selection criteria included primary publications of indices developed for stable COPD patients, that predict future outcome by a multidimensional scoring system, developed for and validated with COPD patients only. Two reviewers independently assessed the index quality using a structured screening form for systematically scoring prognostic studies.

Results

Of 7,028 articles screened, 13 studies comprising 15 indices were included. Only 1 index had been explored for its application in daily practice. We observed 21 different predictors and 7 prognostic outcomes, the latter reflecting mortality, hospitalization and exacerbation. Consistent strong predictors were FEV₁ percentage predicted, age and dyspnoea. The quality of the studies underlying the indices varied between fairly poor and good. Statistical methods to assess the predictive abilities of the indices were heterogenic. They generally revealed moderate to good discrimination, when measured. Limitations: We focused on prognostic indices for stable disease only and, inevitably, quality judgment was prone to subjectivity.

Conclusions

We identified 15 prognostic COPD indices. Although the prognostic performance of some of the indices has been validated, they all lack sufficient evidence for implementation. Whether or not the use of prognostic indices improves COPD disease management or patients' health is currently unknown; impact studies are required to establish this.

Characteristics of Dutch and Swiss primary care COPD patients - baseline data of the ICE COLD ERIC study

Introduction

International Collaborative Effort on Chronic Obstructive Lung Disease: Exacerbation Risk Index Cohorts (ICE COLD ERIC) is a prospective cohort study with chronic obstructive pulmonary disease (COPD) patients from Switzerland and The Netherlands designed to develop and validate practical COPD risk indices that predict the clinical course of COPD patients in primary care. This paper describes the characteristics of the cohorts at baseline.

Material and methods

Standardized assessments included lung function, patient history, self-administered questionnaires, exercise capacity, and a venous blood sample for analysis of biomarkers and genetics.

Results

A total of 260 Dutch and 151 Swiss patients were included. Median age was 66 years, 57% were male, 38% were current smokers, 55% were former smokers, and 76% had at least one and 40% had two or more comorbidities with cardiovascular disease being the most prevalent one. The use of any pulmonary and cardiovascular drugs was 84% and 66%, respectively. Although lung function results (median forced expiratory volume in 1 second [FEV₁] was 59% of predicted) were similar across the two cohorts, Swiss patients reported better COPD-specific health-related quality of life (Chronic Respiratory Questionnaire) and had higher exercise capacity.

Discussion

COPD patients in the ICE COLD ERIC study represent a wide range of disease severities and the prevalence of multimorbidity is high. The rich variation in these primary care cohorts offers good opportunities to learn more about the clinical course of COPD.