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      Models for estimating projections for the prevalence and disease burden of chronic obstructive pulmonary disease (COPD): systematic review protocol

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          Abstract

          Introduction Policymakers and governments must decide their healthcare priorities on the basis of the best healthcare intelligence available to them. Recent interest has increasingly focused on the global implications of an increasing and elderly population with long-term conditions. 1–3 The most recent figures from the Global Burden of Disease Study 2010 show that the third top global cause of death was chronic obstructive pulmonary disease (COPD), 4 rising from fourth place in 1990. 5 It is predominantly caused by cigarette smoking and leads to lung airflow limitation, cough, excessive sputum production, and breathlessness. People with COPD can suffer from substantial disability as the condition progresses. 6 A pressing challenge for governments is how best to project the future trend in the prevalence and burden of COPD in order to plan adequate health and social care for those affected by this condition within the scope of limited resources. Governments should ideally be planning for COPD on two levels: (1) they should consider how to manage resources to care and treat people who are already affected by COPD; and (2) how to prevent a greater increase in the burden from COPD by minimising the continuing smoking epidemic. In order to make such calculations, governments and other healthcare providers need to draw on epidemiological models. Merriam-Webster's dictionary defines a ‘model’ as ‘a system of postulates, data, and inferences presented as a mathematical description of an entity or state of affairs’. This is a useful starting point when considering the role of models in epidemiology. Most models are explanatory in nature and describe the relationships between different parameters. The focus of this study is on models which help to project future epidemiological trends and patterns in populations with COPD. Governments and policymakers have access to many models, but a review is required to appraise the published COPD models to aid selection between them. Various features of COPD present a particular challenge to mathematical and epidemiological modelling, including the many different definitions of a COPD diagnosis and its overlap with a diagnosis of asthma. Although COPD is most clearly attributable to cigarette smoking, there is debate over how best to classify non-smokers who develop COPD with the immunological and pathological features of COPD as a result of exposure to occupational dusts and gases or recurrent chest infections. In addition, there is uncertainty as to the correct classification of older non-smoking adults who have evidence of lung cell remodelling including squamous metaplasia following chronic inflammation due to long-term asthma. Such older adults have often lost the reversibility in their airways obstruction and demonstrate spirometry which is consistent with the thresholds for COPD. 7–9 According to the Global Initiative for Chronic Obstructive Lung Disease (GOLD), the diagnosis of COPD is characterised by an obstructive lung defect with forced expiratory volume in one second to forced vital capacity (FEV1/FVC) ratio <0.7. 10 Controversy regarding this threshold also complicates decisions of precisely which population to include in modelling. Lung function decreases with age, so a proportion of elderly people (age 75+) who have never smoked still fit these criteria for COPD. Some doctors reasonably argue that such elderly people really have normal lung function for their age and that medicalisation of the elderly should be avoided. 7 An alternative threshold of the lower limit of normal for FEV1/FVC has been proposed with a decreasing threshold according to age by percentile. The bottom 5% of FEV1/FVC measurements for whichever total population being measured would be considered abnormal in the older age group. 9 However, no up-to-date large standardised population database currently exists to validate such a measure. The nearest is the use of the European Coal and Steel Workers Population to provide percent predicted FEV1 values; however, this population was standardised over 20 years ago and is based on a working white European population without ethnic minorities. 11–13 Similarly, younger people (age 30–40 years) with larger FVC values and greater respiratory reserve may already have sustained COPD-type damage to their lungs before they reach the <0.7 ratio threshold, so at this end of the age range there is a risk of under-diagnosis of COPD. 13 The debate regarding the diagnosis of COPD is more than just a debate over spirometry thresholds. As many developing countries do not have access to spirometry or even to a reliable power supply, the usefulness of such diagnostic thresholds is limited. It has been proposed that COPD may also be diagnosed on history and clinical features. However, studies have shown that using clinical indicators of pulmonary function to diagnose COPD missed many participants who had low lung function and airways obstruction, especially in current smokers. 14 Therefore, in many countries the current situation has evolved where COPD is diagnosed from physician opinion without corroborating evidence from spirometry, resulting in a significant overlap between a diagnosis of COPD and a diagnosis of asthma. It seems likely that classifications in the future will evolve as the role of host susceptibility is increasingly understood in terms of genetic and epigenetic features. Several candidate genes related to COPD have been identified. 15 In addition, the science of epigenetics helps to explain how DNA transcription has been activated or suppressed by DNA methylation, acetylation, or other mechanisms in response to predominantly prenatal and early life environmental influences. 16 The result of such switching on or off of DNA transcription is to determine the host's response to noxious stimuli including cigarette smoke. Increased understanding of these factors is helping to unravel the mysteries of why some life-long smokers are virtually unaffected by their habit while others have severe COPD. Estimates as to the prevalence of COPD among smokers aged >45 years vary from 15% to 50% according to the criteria used for diagnosis. 17,18 Modelling COPD is also challenged by the key feature of exacerbations. An exacerbation may be triggered by increased bacterial or viral load in the lungs which induce an aggressive immune response and associated clinical features. 19–21 Associated with a greater frequency of exacerbations is higher morbidity, due to faster disease progression in terms of loss of lung function, and also mortality. 21 An additional challenge is the level of mathematical sophistication within each model. Ideally, a researcher with considerable statistical skill would be available to check the algorithms that drive each model and so provide a full appraisal of the quality of each model. In the absence of this ideal, it was decided to appraise the quality of reporting of each model as a proxy for the model's mathematical quality. Taking these challenges into account, it will be necessary to describe a degree of context with each model in order that it can be applied in an appropriate setting. This will help subsequent researchers to understand the necessary caveats to include when describing the results from each model. Objectives To identify all available models for estimating projections of COPD prevalence and burden, and to assess the quality of reporting of each model in its key publication. Methods A search strategy has been developed using search terms to cover the three concepts of ‘modelling’, ‘disease burden’, and ‘chronic obstructive pulmonary disease’ (see Appendix 1 for full details). Searches will be conducted in the following electronic databases: MEDLINE, EMBASE, CAB Abstracts, World Health Organization (WHO) Library and Information Services (WHOLIS — library catalogue of books and reports), WHO Regional Indexes (AIM (AFRO), LILACS (AMRO/PAHO), IMEMR (EMRO), IMSEAR (SEARO), WPRIM (WPRO)), and a modified search strategy will be used to identify reports from the WHO home website and Google. Searches will be for both published and unpublished modelling studies from 1980 (when modelling methods first began to be widely used) to 2013. Two authors will independently review the studies against the inclusion criteria and make a decision as to whether the study is suitable. Disagreements will be resolved by discussion and, if this is not possible, a third reviewer will arbitrate. Inclusion criteria Any modelling study which uses demographic and epidemiological data to project the prevalence and disease burden will be included. The included projected outcomes which are of interest are one or more of: incidence, prevalence and mortality, and disease burden. With regard to ‘disease burden’, the outcomes of interest can be considered from the individual's point of view, from the point of view of the healthcare system, and from the point of view of broader society. For the purposes of this review, the focus is on the perspective of the healthcare system. Other perspectives are valid; however, different instruments are used to measure them and the purpose of this study is to guide policymakers who will focus on the healthcare system perspective. Quality-adjusted life years (QALYs) and disability-adjusted life years (DALYs) are often used to measure and quantify the burden to the individual of the morbidity they are suffering. Treatments are assigned a cost per restored QALY, and this is an important measure used in cost-effectiveness studies. However, the scope of this study is more limited in order to avoid confusion of perspectives. Some of the studies included may discuss QALYs and DALYs, but they have not been chosen as primary disease burden outcomes for this review. Instead, we will concentrate on primary care visits, emergency department visits, hospital admissions, and COPD treatment costs. Exclusion criteria There will be no exclusions on the basis of language of the report. Studies which are population-based surveys of prevalence without modelling will be excluded as there has recently been a systematic review of such studies. 22 ‘Models’ will be excluded if they describe animals, cell lines, clinical series, or estimates of individual risk (such as individual prognostic models). Decision analytical models or decision support models will be excluded where they refer to clinical decision-making for individuals rather than populations. Models that compare one intervention with another intervention will also be excluded, as the aim is accurately to project the baseline outcomes so it is premature to take into account the effect of interventions. Also excluded will be regression models which start with a COPD population and ‘back-calculate’ the prevalence or burden using regression to quantify risk factors, as this follows a different logic from that of projection modelling. Participants The source population for the model may be from anywhere in the world. The model will pertain to adult populations aged >40 years as it is usually not appropriate to diagnose COPD in younger people. 10 COPD may be diagnosed by physician, spirometry, or by questionnaire. Other assumptions regarding the diagnosis of COPD will be evaluated in the context of the model. Data extraction The data will be extracted by one author and checked by a second. Data will be extracted using a pre-piloted data extraction form. The following identification details will be extracted for each model: author and email address, year, institution, and funding source. These data will be followed by: the purpose of the model, model title, model type, model setting, time period, and population (age, sex and country). Also extracted will be: inputs to the model, source of input data, details of processing of the model, outcomes for COPD (incidence, prevalence, mortality, GP visits, emergency department visits, hospitalisations, treatment costs), model output/results, details of the model's availability, any comparisons with other studies, social and economic policy implications of model outcomes, and future research recommendations. In this way, the data extraction form aims to encompass a comprehensive picture of the model. Quality appraisal framework Ideally, a quality appraisal of the actual modelling process would be undertaken. However, this requires significant statistical technical expertise. A pragmatic decision has therefore been made to quality appraise the reporting of the models rather than the actual modelling process for those that have full published reports. In order to do this, a quality of reporting framework has been designed following review of key guidelines as to good practice in modelling. 23–26 A scoring mechanism was devised in collaboration with Simon Capewell of Liverpool University 27 to weight the importance of the different elements required to produce a relevant high-quality model (see Appendix 2). Strategy for data synthesis The study will be the unit of analysis. Models will be described and classified. A detailed critical narrative synthesis of the highest scoring models will be undertaken. Where the models are not available, we will write to the model authors for further clarification. No subgroup analysis is planned.

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          Most cited references 14

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          A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010

          The Lancet, 380(9859), 2224-2260
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            New insights into the immunology of chronic obstructive pulmonary disease.

            Chronic obstructive pulmonary disease (COPD) is a heterogeneous syndrome associated with abnormal inflammatory immune responses of the lung to noxious particles and gases. Cigarette smoke activates innate immune cells such as epithelial cells and macrophages by triggering pattern recognition receptors, either directly or indirectly via the release of damage-associated molecular patterns from stressed or dying cells. Activated dendritic cells induce adaptive immune responses encompassing T helper (Th1 and Th17) CD4+ T cells, CD8+ cytotoxicity, and B-cell responses, which lead to the development of lymphoid follicles on chronic inflammation. Viral and bacterial infections not only cause acute exacerbations of COPD, but also amplify and perpetuate chronic inflammation in stable COPD via pathogen-associated molecular patterns. We discuss the role of autoimmunity (autoantibodies), remodelling, extracellular matrix-derived fragments, impaired innate lung defences, oxidative stress, hypoxia, and dysregulation of microRNAs in the persistence of the pulmonary inflammation despite smoking cessation. Copyright © 2011 Elsevier Ltd. All rights reserved.
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              Not 15 but 50% of smokers develop COPD?--Report from the Obstructive Lung Disease in Northern Sweden Studies.

              The prevalence of chronic obstructive pulmonary disease (COPD) according to guidelines of today seems considerably higher than has been reported also in recent literature. To estimate the prevalence of COPD as defined by British Thoracic Society (BTS) criteria and the recent global initiative for chronic obstructive lung disease (GOLD) criteria. Further aims were to assess the proportion of underdiagnosis and of symptoms in subjects with COPD, and to study risk factors for COPD. In 1996, 5892 of the Obstructive Lung Disease in Northern Sweden (OLIN) Study's first cohort could be traced to a third follow-up survey, and 5189 completed responses (88%) were received corresponding to 79% of the original cohort from December 1985. Of the responders, a random sample of 1500 subjects were invited to a structured interview and a lung function test, and 1237 of the invited completed a lung function test with acceptable quality. In ages >45 years, the prevalence of COPD according to the BTS guidelines was 8%, while it was 14% according to the GOLD criteria. The absolutely dominating risk factors were increasing age and smoking, and approximately a half of elderly smokers fulfilled the criteria for COPD according to both the BTS and the GOLD criteria. Family history of obstructive airway disease was also a risk factor, while gender was not. Of those fulfilling the BTS criteria for COPD, 94% were symptomatics, 69% had chronic productive cough, but only 31% had prior to the study been diagnosed as having either chronic bronchitis, emphysema, or COPD. The corresponding figures for COPD according GOLD were 88, 51, and 18%. In ages >45 years, the prevalence of COPD according to the BTS guidelines was 8%, and it was 14% according to the GOLD criteria. Fifty percent of elderly smokers had developed COPD. The large majority of subjects having COPD were symptomatic, while the proportion of those diagnosed as having COPD or similar diagnoses was small.
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                Author and article information

                Journal
                Prim Care Respir J
                Prim Care Respir J
                Primary Care Respiratory Journal: Journal of the General Practice Airways Group
                Nature Publishing Group
                1471-4418
                1475-1534
                June 2013
                30 May 2013
                : 22
                : 2
                : PS8-PS21
                Affiliations
                [1 ]Allergy and Respiratory Research Group, Centre for Population Health Sciences, The University of Edinburgh , Edinburgh, UK
                [2 ]Centre for Population Health Sciences, The University of Edinburgh , Edinburgh, UK
                Author notes
                [* ]Allergy and Respiratory Research Group, Centre for Population Health Sciences, The University of Edinburgh , Edinburgh EH8 9DX, UK. Tel: +44 (0)131 650 9242 E-mail: Susannah.mclean@ 123456ed.ac.uk

                SM drafted the article with oversight from CS SW and AS. AS and SM conceived the project as part of SM's PhD.

                Article
                pcrj201348
                10.4104/pcrj.2013.00048
                6442795
                23732639
                Copyright © 2013 Primary Care Respiratory Society UK
                Categories
                Protocol Summary

                modelling, epidemiology, copd

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