The paper does not fulfil the criteria of a systematic review (Cochrane) of a single topic, but includes several specialties with references. The paper thus contains elements of a perspective with models and hypotheses. We searched Medline (National Center for Biotechnology Information) with the search terms “asthma control and lung function”, “asthma risk”, “asthma monitoring”, “disease progression and COPD”, “fractal” in combination with “lung” and “respiratory system”, “long range
ReviewComplexity of chronic asthma and chronic obstructive pulmonary disease: implications for risk assessment, and disease progression and control
Introduction
Bronchial asthma and chronic obstructive pulmonary disease (COPD) are the two most common chronic respiratory diseases, affecting millions of children and adults. Nevertheless, many features of these diseases, including pathogenesis and progression are not fully understood. To treat patients with asthma or COPD correctly, markers of disease severity and control1 are needed that can be used to predict future exacerbations.2
However, in bronchial asthma the association between stimuli and exacerbations is poor3, 4, 5 and increasing evidence suggests that the classic paradigm of asthma, sequentially linking the trigger to the symptoms (figure 1), is incomplete in many situations. Indeed, the association between trigger and inflammation,6, 7 inflammation and bronchial hyper-reactivity,8, 9, 10, 11, 12 and airway obstruction and symptoms is not always strong. Asthma phenotypes are very heterogeneous—eg, inflammation can be predominantly eosinophilic, neutrophilic, or involve other pathways.13, 14, 15, 16, 17, 18, 19 Many inflammatory pathways that are part of the asthmatic cascade operate within a complex web of interactions, including various subsystems that are part of the host defence, immunity, and inflammation, and lung mechanics. Although COPD is different, the distinction between it and asthma is beginning to blur.20, 21 Additional interactions can occur between the organism and the environment, with several external heterogeneous triggers (eg, viral infections, allergens, and pollutants), showing high temporal variability.
Assessment of asthma severity and control based on one clinical marker, such as the averaged set of symptoms, has limitations because of the complexity of the disease. A multidimensional approach with more than one parameter or including statistical measures of parameters with time should provide a more comprehensive picture of the disease process. In this Review, we will explain the unpredictable nature of clinical events and exacerbations based on the complex and non-linear behaviour of the respiratory system fluctuating with time. Specifically, we will discuss how the network structure of the airway tree and the lung tissue contributes to unexpected sudden disease exacerbations in both asthma and emphysema. With fluctuation analysis of the history of physiological parameters, we show how prediction of exacerbations and hence treatment strategies might be improved.
Section snippets
Classic method of assessment of asthma control and severity
Asthma severity can be considered as the intrinsic intensity of the disease and is measured most easily and directly when a patient is not under long-term control treatment. Asthma control is the degree to which the manifestations of the disease (ie, symptoms, functional impairments, and risk of exacerbations) are minimised by treatment. Disease severity and control form the basis of asthma treatment according to the global strategy for asthma management and prevention guidelines,1, 22 and both
Unpredictability of disease progression
Clinicians are well aware of the difficulties in trying to predict the temporal fluctuations in disease progression or prognosis even with multidimensional approaches. The assessment of the risk of future asthma exacerbations, progressive reduction in lung function, or risk of adverse effects from medication remains elusive, and the time course of events is often unexpected. For example, small or even undetected triggers can lead to unexpected fatal asthma attacks,3 and even children with
Long-range correlation of lung function parameters
The extent of memory can be estimated from correlations within an output variable of the respiratory system. For instance, daily lung function tests or symptoms embody the features of the system's memory. Generally, the history of stimuli (or exposures) is not known, and can itself be a complex non-random process. However, when several inputs are coupled with immune reactions, inflammation, neurological control, and the mechanics of breathing, the response at the whole-organism level becomes
Quantification of the risk from PEF fluctuations
In addition to the long-range correlations, the risk of future exacerbations can be calculated from fluctuations in PEF. The conditional probability π that a patient will encounter a future obstructive episode (eg, with a predicted PEF less than 80%) is not only a function of today's PEF value but also depends on the long-range correlations of the time series of past PEF values.124 The risk π is therefore not a traditional risk factor based on population statistics (eg, smoking), and represents
Implications for the future
In complex diseases such as asthma or COPD, the description of disease severity, progression, and risk assessment is restricted with the unidimensional approach (figure 6). One possible way to address the complexity of the disease is with a multidimensional approach that includes a combination of several clinical and physiological parameters (figure 6). We have argued that observation of the long-term temporal fluctuations of clinical and physiological markers and the analysis of their
Search strategy and selection criteria
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