RESEARCH PROTOCOL PROPOSAL

Transcription

1 RESEARCH PROTOCOL PROPOSAL UNCOVERING AND NOTING LONG-TERM OUTCOMES IN COPD AND ASTHMA TO ENHANCE KNOWLEDGE - UNLOCK UNLOCK Study: The prevalence of comorbidities in COPD patients and their impact on the quality of life and COPD symptoms in primary care patients First Author: Björn Ställberg May 2014

2 Index Abstract 22 Background and rationale 22 Aims and objective 44 Methodology 55 Study design 55 Data variables to be included 55 Data analysis 66 Sample size calculation 66 Reporting and dissemination plan 77 Authorship and agreement 77 Ethics 77 Study governance 77 Chronogram 88 References 99 1

3 Title: The prevalence of comorbidities in COPD patients and their impact on the quality of life and COPD symptoms in primary care patients First author: Björn Ställberg Other contributing authors: Niels Chavannes, Ioanna Tsiligianni, Andrew Cave, Janwillem Kocks, Jaime Correia de Sousa (others may be involved) Abstract Introduction: Chronic obstructive pulmonary disease (COPD) is associated with comorbidities that increase in number and severity with age and are more prevalent among deprived social groups. Little is yet known about prevalence of comorbidities with COPD and its impact in quality of life in primary care populations. Increasing this knowledge is relevant for the development of better intervention strategies and for informing the reframing of clinical guidelines in primary care. Aim: To enhance knowledge in terms of prevalence of comorbidities in COPD patients and their impact on the quality of life and on COPD symptoms in primary care patients. Method: Retrospective cross sectional analysis of primary care data from different countries. Analysis will include descriptive statistics, null hypothesis tests such as Chi- Square, factorial analysis of variance and predictive binary logistic regression models. Results: Expected results will provide insight about prevalence of comorbidities with COPD and its impact in quality of life between gender, age groups and countries. Key terms: COPD, Quality of Life, Prevalence Comorbidities Background and rationale According to the World Health Organization chronic obstructive pulmonary disease (COPD) is a leading cause of morbidity and mortality associated with the diminishment of lung function that involves high social and economical costs. The prevalence of COPD has been reported to vary between 6% and 26,1% worldwide (1). COPD has also been associated with a high prevalence of one or more comorbid conditions, with an impact on quality of life and mortality (2-5). Chronic disorders have been associated with multimorbidity and with an increase of these with age. Also they are more prevalent among people living in socioeconomically deprived areas (6). 2

4 There is solid evidence that comorbidities have a negative impact in COPD patients (i.e. exacerbations, quality of life, mortality) (5). Nonetheless, COPD guidelines (GOLD) still consider comorbidities diagnosis and management from an individual disease point of view. Health services are largely structured for individual disease focus rather than multimorbidity (7). Although there is no evidence that comorbidities should be treated differently in COPD than according to usual disease guidelines the impact of comorbidities in the COPD patient still needs to be considered. Most studies that evaluated the spectrum and prevalence of comorbidities affecting COPD patients have been conducted in secondary care settings. For example, Divo et al established a relationship between comorbidities and the risk of death over a median of 51 months. The prevalence and mortality risk are expressed using an orbital bubble chart (fig. 1) and a quantitative risk stratification comorbidity tool (the COTE index). Figure 1. Comorbidome in Divo M, Cote C, de Torres JP, Casanova C, Marin JM, Pinto-Plata V, et al. Comorbidities and risk of mortality in patients with chronic obstructive pulmonary disease. American journal of respiratory and critical care medicine. 2012;186(2): p

5 The area of each circle relates to the prevalence of the disease it represents. The circle proximity to the centre of the graphic (mortality) expresses the strength of the association between the disease and risk of death. All diseases associated with a statistically significant increase in mortality are fully inside the dotted orbit. Results showed that anxiety, cancers and heart diseases are among the most significant comorbidity diseases to impact on COPD mortality risk in secondary care settings. It is known that diagnosis and management of COPD comorbidities is an important feature for the COPD patient exacerbations, quality of life and mortality, still there is a lack of knowledge about the prevalence and the impact of more than one comorbid conditions in primary care of COPD patients. The enhancement of the epidemiological knowledge about comorbidities in COPD and the better understanding of the impacts they have on quality of life are highly relevant to better inform clinical practices and health care services delivery. This study of comorbidities will render new insight for the development of preventive interventions, the reduction of burden of diseases and the adjustment of health care services to patients needs in primary care (6). Aims and objective This study aims to enhance knowledge in terms of prevalence of comorbidities in COPD patients and their impact on the quality of life and on COPD symptoms in primary care patients. This study will address the following research questions: 1. What is the prevalence of comorbidities in COPD patients in primary care? 2. What is the impact of one or more comorbidities on the quality of life and on COPD symptoms? 3. What is the impact of one or more comorbidities on the exacerbations in COPD? 4

6 Methodology Study design [V1][PMT2] Study design will be based on a retrospective cross sectional study with data from primary care in different countries. Study will be developed according to the STROBE Statement guidelines. Data variables to be included Members of IPCRG will be invited to participate in the study with cross sectional data from primary care settings. Data variables will include: Age and gender[v3] Lung function (i.e. FEV1(% of predicted) and FEV1/FVC-ratio), if available[v4] Exacerbations [V5] CCQ and/or CAT and MRC[V6] BMI, Smoking status[v7] Educational level[v8] Data of comorbidities: - Heart failure, Ischemic Heart Disease (or heart disease ) - Hypertension - Diabetes - Depression - Underweight - Asthma - If available: Osteoporosis, Anxiety, Sleep Apnea, Rheumatic Disease, Cancer, Rhinitis and Stroke[V9] The members that may contribute for the study are Björn Ställberg, Niels Chavannes, Ioanna Tsiligianni, Andrew Cave, Janwillem Kocks, Jaime Correia de Sousa, however others may be involved and will be invited to participate until the end of May. The identification of the participants in the datasets will be kept anonymous and the confidentiality will be assured in the collection and merging of the datasets procedures. 5

7 Data analysis Analysis will focus on descriptive statistics (e.g. frequencies, percentages, cross tabulations) with graphical display. Differences in number of morbidities between groups (e.g. gender, age groups) will be tested with factorial ANOVA models. The Chi- Square test will be used to analyse differences in prevalence of comorbidity and predictive associations between variables will be studied with binary logistic regression models and odds ratios and respective confidence intervals (e.g. 95%) will be reported. Statistical significance will be considered for p-values < 0.05 (i.e. error type I < 5%). The statistical significance in multivariate models will be adjusted depending on the number of variables tested (e.g. Bonferroni correction). The uncertainty of estimates, whenever possible will be quantified in terms of confidence interval (e.g.95%) and effect size values and statistical power (i.e. 1 - β (Prob.Error Type II)) will also be analysed, interpreted and reported. Analysis will be directed by the UNLOCK researcher (Pedro Teixeira) either by merging all datasets and performing them or by working closely with members that may not share data to assure consistency of the analytic process and consequent results reliability. Analyses will be performed using software IBM SPSS Statistics for Windows, Version Armonk, NY: IBM Corp. Sample size calculation The samples size calculation is not applicable here given that study will be developed with the comparison of data of different samples with different sizes that have already been collected. Nevertheless, the expected sample sizes will provide satisfactory statistical power for even very small effect sizes. For example, the values for a very small effect size such as a d (Cohen s effect size for means difference) of 0,15 will require a 1500 sample for a minimum 90% statistical power and still a small d of 0,35 will require only around 250 for identical statistical power as presented in figure 1. 6

8 t tests - Means: Dif erence between two independent means (two groups) Tail(s) = One, Allocation ratio N2/ N1 = 1, α err prob = 0,05 Total sample size Effect size d = 0,15 = 0,35 = 0,55 0 0,6 0,65 0,7 0,75 0,8 0,85 0,9 0,95 Power (1-β err prob) Figure 1. Sample size calculation for Cohen s d (0,15; 0,35; 0,55) given an = 0,05 and varying power (i.e.,60 < <,95) using G*Power software. Reporting and dissemination plan Reporting and dissemination will include the writing and submission of an article to a peer-review respiratory journal such as: Thorax, BMJ or PCRJ and presentation and discuss of results will take place in communications in international respiratory congress (e.g IPCRG, ERS). Reporting will be done according to the STROBE Statement checklist of items that should be included in reports of cross-sectional studies. Authorship and agreement The study will involve an agreement between IPCRG participating members in terms of authorship and the exclusive permission of the use of the datasets for this study. Ethics Ethical approvals required according to national regulations. Study governance The UNLOCK researcher (Pedro M Teixeira) will carry out data collection and analysis and will prepare the draft report of findings. Björn Ställberg will supervise the study. 7

9 Chronogram The study will be developed according to the following task and time schedule: Research task Apr May Jun Jul Aug Sep Oct Nov Dec Development of research protocol Invitation for participation in study Collecting and merging datasets Analysis of data Reporting and dissemination 8

10 References 1. Buist AS, McBurnie MA, Vollmer WM, Gillespie S, Burney P, Mannino DM, et al. International variation in the prevalence of COPD (the BOLD Study): a population-based prevalence study. Lancet. 2007;370(9589): Burgel PR, Escamilla R, Perez T, Carre P, Caillaud D, Chanez P, et al. Impact of comorbidities on COPD-specific health-related quality of life. Respiratory medicine. 2013;107(2): Sundh J, Stallberg B, Lisspers K, Montgomery SM, Janson C. Co-morbidity, body mass index and quality of life in COPD using the Clinical COPD Questionnaire. Copd. 2011;8(3): Divo M, Cote C, de Torres JP, Casanova C, Marin JM, Pinto-Plata V, et al. Comorbidities and risk of mortality in patients with chronic obstructive pulmonary disease. American journal of respiratory and critical care medicine. 2012;186(2): Cavailles A, Brinchault-Rabin G, Dixmier A, Goupil F, Gut-Gobert C, Marchand-Adam S, et al. Comorbidities of COPD. European respiratory review : an official journal of the European Respiratory Society. 2013;22(130): Guthrie B, Payne K, Alderson P, McMurdo ME, Mercer SW. Adapting clinical guidelines to take account of multimorbidity. BMJ (Clinical research ed). 2012;345:e Barnett K, Mercer SW, Norbury M, Watt G, Wyke S, Guthrie B. Epidemiology of multimorbidity and implications for health care, research, and medical education: a cross-sectional study. Lancet. 2012;380(9836):