Multicomponent indices to predict survival in COPD: the COCOMICS study

Brief literature review

The course of COPD and the relationship between COPD, decline in lung function over time and exacerbations is a complex issue. It has been proposed that each COPD exacerbation reduces at least 10 mL of FEV₁ in individual COPD patients, accounting for a 1.2% to 1.4% relative decline from baseline FEV₁ and that, overall, probably ∼25% of the fall in lung function can be attributed to the effects of exacerbations [35]. Data from Vestbo et al. [36] quantified that each COPD exacerbation accounted for 2±0.5 mL in the annual rate of change in FEV₁. A recent meta-analysis of published data concluded that each exacerbation increases the risk of immediate death (case-fatality rate) by 16%, although there was a variability from 11.4% to 19.0% in the six studies included [37]. We believe that in addition to excluding all Spanish cohorts, the study of Hoogendoorn et al. [37] assesses only admitted COPD patients and it has a rather simplistic statistical analysis given that computes aggregated data, and therefore our current approach is improved in form and substance. We used a relatively new tool, pooled analysis, which collects individual patient-level data and analyses studies as a single, new study. This has advantages over classical meta-analyses as it avoids many of the methodological pitfalls related to classical meta-analytic techniques that rely exclusively on published data. It is of note that the CPI index was constructed by pooling individual data from 12 trials, involving a total of 8802 patients and amounting to >6000 patient-years of information [23], but the representativity of trial participants of real-life patients is debatable [38].

Clinical relevance

To what extent is each multicomponent index better than FEV₁ alone? First, C statistics do not have a direct application to the clinic. It is a mathematical summary measure that estimates the probability when comparing two given patients. The relevance of the conceptual discussion about the inclusion of age in COPD multicomponent indices versus other factors to determine individual clinical prognosis is exemplified in table 6. [39]. According to the ADO index, the older patient has a higher risk of death than the younger one (see table 2 for predicted mortality at different time-points). However, this has little to do with COPD and all to do with life itself. The addition of the 6MWD and BMI (both predictors of outcome) provide clinical dimensions that ADO does not have. These two clinical factors are also predictors of mortality independent of age. Patient 1 was referred for lung transplantation, whereas patient 2 was prescribed bronchodilators. Therefore, it is our understanding that age, as many other nonmodifiable factors, should have limited value in the clinical stratification of a specific disease process, such as COPD.

The 6MWD adds substantial value to any COPD prognostic assessment [40], yet we agree that performing the 6MWD could be cumbersome to some practising doctors and settings, particularly to family physicians that care mostly for mild COPD patients, or busy internal medicine wards. Nevertheless, the 6MWD alone is an important tool as predictor of mortality in patients with pulmonary fibrosis, pulmonary hypertension, and those with both heart and respiratory failure. We think that most or all patients under specialist care should have some type of exercise capacity assessed, and the 6-MWD is the simplest test. It is of interest that those indices that do not include exercise capacity, such as the BODEx index, also demonstrated good predictor ability and could be a good surrogate when the 6MWD is not available, which is a recent GOLD 2011 recommendation [1].

Strengths and limitations

The strengths of the COCOMICS study include, first, a large sample size of nearly 16 000 person-years, allowing for statistical power in most subanalyses; very few participants were lost to follow-up, as cohorts were built from clinical practices in elite, prestigious hospital centres managing these patients. Homogeneity is also a strength, as all COPD patients are Spanish, granted by law with guaranteed universal, free-of charge health coverage, and therefore giving robustness to the interpretation or assessment of health outcomes. Another strength is internal consistency, as all investigators follow the same COPD clinical guidelines for pharmacological and nonpharmacological treatments. As mentioned above, the analytical approach is not a meta-analysis of published results, but a pooled analysis of individual data collected for this project. Finally, by including cohorts of patients with different origins, and severity of disease, all indices have been tested in a diverse population.

One limitation of our study is that not all participants have data in all variables, and key variables such as exacerbations or cause of death were not collected either consistently or in all participants. Indeed, about two-thirds of our COPD patients died of comorbidities, mainly cardiovascular and lung cancer. To date, it seems that apart from the newly available COTE (COPD-specific comorbidity test) index [41], no index reflects the variable contribution of specific causes of death, which changes with lung function and the natural history of COPD [42]. All cohorts used protocols and collected data in a similar, but not identical, way, given the nature of “real life” usual care rather than the “research-only” origin of these cohorts. All our participants were Caucasian and extrapolation of results (table 2) should apply to those COPD patients cared for in systems with public health services. However, the use of different cohorts grouped to compare different staging systems or recommendations is considered useful if methodology is applied to all patient data [43]. Regrettably, history of past COPD exacerbations and/or prospective use of health resources (emergency department and hospitalisations) were not collected in all cohorts, and in the few who collected them consistently, it was considered that methods were too diverse to be pooled together. As has already been noted, numbers of female COPD patients were scant. It was not possible to make an analysis of treatments or of time-dependant variables to assess changes in medication, smoking habits and other factors. Even in the very long-term, our analyses assumed that the patients’ condition did not change from baseline, which in some variables may not be so (change in medication, becoming a frequent exacerbator or developing a new comorbidity). Although some COPD variables show stability and repeatability, these analyses had no regular monitoring and re-staging. Finally, we are analysing the COPD multicomponent indices available to us at the onset of the COCOMICS study. However, other indices have been newly proposed, such as the NIAF (physiological functioning, complaints, functional impairment and quality of life) study [44]. As recently proposed by Rossi and Zanardi [45], given the growing number of multidimensional indices for assessing COPD multiple phenotypes, we cannot expect a single variable or index to assess the heterogeneity of COPD, but multiple variables for different COPDs.

We conclude that no COPD multicomponent index predicts well short-term survival up to 6-months. It appears the index with the best prognostic value is ADO, but after age adjustment, all BODE modifications score better. The ADO and BODE indices are overall the most valid multicomponent indices to predict time to death in all COPD patients.