External Validation Of The Updated ADO Score In COPD Patients From The Birmingham COPD Cohort

References

• Lozano R, Naghavi M, Foreman K, et al. Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: a systematic analysis for the global burden of disease study 2010. Lancet. 2012;380(9859):2095–2128. doi:10.1016/S0140-6736(12)61728-023245604
   PubMed Web of Science ®Google Scholar
• Decramer M, Janssens W, Miravitlles M. Chronic obstructive pulmonary disease. Lancet. 2012;379(9823):1341–1351. doi:10.1016/S0140-6736(11)60968-922314182
   PubMed Web of Science ®Google Scholar
• Moons KGM, Royston P, Vergouwe Y, Grobbee DE, Altman DG. Prognosis and prognostic research: what, why, and how? BMJ. 2009;338(7706):1317–1320. doi:10.1136/bmj.b375
   Web of Science ®Google Scholar
• Agusti A, Sobradillo P, Celli BR. Addressing the complexity of chronic obstructive pulmonary disease: from phenotypes and biomarkers to scale-free networks, systems biology, and P4 medicine. Am J Respir Crit Care Med. 2011;183(9):1129–1137. doi:10.1164/rccm.201009-1414PP21169466
   PubMed Web of Science ®Google Scholar
• Agusti A, Calverley PMA, Celli B, et al. Characterisation of COPD heterogeneity in the ECLIPSE cohort. Respir Res. 2010;11(122):1–14. doi:10.1186/1465-9921-11-120047687
   PubMed Web of Science ®Google Scholar
• Azarisman MS, Fauzi MA, Faizal MPA, Azami Z, Roslina AM, Roslan H. The SAFE (SGRQ score, air-flow limitation and exercise tolerance) Index: a new composite score for the stratification of severity in chronic obstructive pulmonary disease. Postgrad Med J. 2007;83(981):492–497. doi:10.1136/pgmj.2006.05239917621621
   PubMed Web of Science ®Google Scholar
• Jones RC, Donaldson GC, Chavannes NH, et al. Derivation and validation of a composite index of severity in chronic obstructive pulmonary disease: the DOSE index. Am J Respir Crit Care Med. 2009;180(12):1189–1195. doi:10.1164/rccm.200902-0271OC19797160
   PubMed Web of Science ®Google Scholar
• Divo M, Cote C, De Torres JP, et al. Comorbidities and risk of mortality in patients with chronic obstructive pulmonary disease. Am J Respir Crit Care Med. 2012;186(2):155–161. doi:10.1164/rccm.201201-0034OC22561964
   PubMed Web of Science ®Google Scholar
• Puhan MA, Garcia-Aymerich J, Frey M, et al. Expansion of the prognostic assessment of patients with chronic obstructive pulmonary disease: the updated BODE index and the ADO index. Lancet. 2009;374(9691):704–711. doi:10.1016/S0140-6736(09)61301-519716962
   PubMed Web of Science ®Google Scholar
• Celli B, Cote C, Marin JM, et al. The body-mass index, airflow obstruction, dyspnea, and exercise capacity index in chronic obstructive pulmonary disease. N Engl J Med. 2004;350(10):1005–1012. doi:10.1056/NEJMoa02132214999112
   PubMed Web of Science ®Google Scholar
• Cook NR. Statistical evaluation of prognostic versus diagnostic models: beyond the ROC curve. Clin Chem. 2008;54(1):17–23. doi:10.1373/clinchem.2007.096529
   Web of Science ®Google Scholar
• Haile SR, Guerra B, Soriano JB, Puhan MA. Multiple score comparison: a network meta-analysis approach to comparison and external validation of prognostic scores.BMC Med Res Methodol. 2017;17(1):172. doi:10.1186/s12874-017-0433-2.
   Google Scholar
• Puhan MA, Hansel NN, Sobradillo P, et al. Large-scale international validation of the ADO index in subjects with COPD : an individual subject data analysis of 10 cohorts. BMJ Open. 2012;2::e002152. doi:10.1136/bmjopen-2012-002152
   Web of Science ®Google Scholar
• Morales DR, Flynn R, Zhang J, Trucco E, Quint JK, Zutis K. External validation of ADO, DOSE, COTE and CODEX at predicting death in primary care patients with COPD using standard and machine learning approaches. Respir Med. 2018;138:150–155. doi:10.1016/j.rmed.2018.04.00329724388
   PubMed Web of Science ®Google Scholar
• Guerra B, Haile SR, Lamprecht B, et al. Large-scale external validation and comparison of prognostic models: an application to chronic obstructive pulmonary disease. BMC Med. 2018;16(1):1–13. doi:10.1186/s12916-018-1013-y
   Web of Science ®Google Scholar
• Abu Hussein N, Ter Riet G, Schoenenberger L, et al. The ADO index as a predictor of two-year mortality in general practice-based chronic obstructive pulmonary disease cohorts. Respiration. 2014;88(3):208–214. doi:10.1159/00036377025115178
   PubMed Web of Science ®Google Scholar
• James GD, Donaldson GC, Wedzicha JA, Nazareth I. Trends in management and outcomes of COPD patients in primary care, 2000–2009: a retrospective cohort study. NPJ Prim CARE Respir Med. 2014;24:14015. doi:10.1038/npjpcrm.2014.15
   Web of Science ®Google Scholar
• Moons KGM, Altman DG, Reitsma JB, et al. Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): explanation and elaboration. Ann Intern Med. 2015;162(1):W1–73.. doi:10.7326/M14-0698
   Web of Science ®Google Scholar
• Adab P, Fitzmaurice DA, Dickens AP, et al. Cohort profile: the Birmingham Chronic Obstructive Pulmonary Disease (COPD) cohort study. Int J Epidemiol. 2016;46(1):dyv350. doi:10.1093/ije/dyv350
   Web of Science ®Google Scholar
• Jordan RE, Adab P, Sitch A, et al. Targeted case finding for chronic obstructive pulmonary disease versus routine practice in primary care (TargetCOPD): a cluster-randomised controlled trial. Lancet Respir Med. 2017;4(9):720–730. doi:10.1016/S2213-2600(16)30149-7
   Web of Science ®Google Scholar
• Bestall JC, Paul EA, Garrod R, Garnham R, Jones PW, Wedzicha JA. Usefulness of the Medical Research Council (MRC) dyspnoea scale as a measure of disability in patients with chronic obstructive pulmonary disease. Thorax. 1999;54(7):581–586. doi:10.1136/thx.54.7.58110377201
   PubMed Web of Science ®Google Scholar
• Quanjer PH, Stanojevic S, Cole TJ, et al. Multi-ethnic reference values for spirometry for the 3–95-yr age range: the global lung function 2012 equations. Eur Respir J. 2012;40(6):1324–1343. doi:10.1183/09031936.0008031222743675
   PubMed Web of Science ®Google Scholar
• NHS. NHS Digital- Quality and Outcomes Framework.
   Google Scholar
• White IR, Royston P, Wood AM. Multiple imputation using chained equations : issues and guidance for practice. Stat Med. 2011;30(4):377–399. doi:10.1002/sim.406721225900
   PubMed Web of Science ®Google Scholar
• Altman DG, Bland JM. Statistics Notes: diagnostic tests 3: receiver operating characteristic plots. BMJ. 1994;309:188. doi:10.1136/bmj.309.6948.188
   Google Scholar
• Steyerberg EW, Vickers AJ, Cook NR, et al. Assessing the performance of prediction models : a framework for some traditional and novel measures. Epidemiology. 2010;21(1):128–138. doi:10.1097/EDE.0b013e3181c30fb2.
   Web of Science ®Google Scholar
• Marshall A, Altman DG, Holder RL, Royston P. Combining estimates of interest in prognostic modelling studies after multiple imputation: current practice and guidelines. BMC Med Res Methodol. 2009;9:57. doi:10.1186/1471-2288-9-57
   Web of Science ®Google Scholar
• Wretenberg P, Arborelius UP. Power and work produced in different leg muscle groups when rising from a chair. Eur J Appl Physiol Occup Physiol. 1994. doi:10.1007/BF0843738
   Web of Science ®Google Scholar
• Smith LJE, Moore E, Ali I, Smeeth L, Stone P, Quint JK. Prognostic variables and scores identifying the end of life in COPD: A systematic review. Int J COPD. 2017;12:2239–2256. doi:10.2147/COPD.S137868
   Google Scholar
• Copas JB. Regression, Prediction and Shrinkage. J R Stat Soc Ser B. 1983. doi:10.2307/2345402
   Google Scholar
• Il HY, Kim CH, Kang HR, et al. Comparison of the prevalence of chronic obstructive pulmonary disease diagnosed by lower limit of normal and fixed ratio criteria. J Korean Med Sci. 2009;24(4): 621–626. doi:10.3346/jkms.2009.24.4.621
   Web of Science ®Google Scholar
• Güder G, Brenner S, Angermann CE, et al. GOLD or lower limit of normal definition? A comparison with expert-based diagnosis of chronic obstructive pulmonary disease in a prospective cohort-study. Respir Res. 2012;13(1):13. doi:10.1186/1465-9921-13-1322309369
   PubMed Web of Science ®Google Scholar
• Bhatt SP, Balte PP, Schwartz JE, et al. Discriminative accuracy of FEV1:FVC thresholds for COPD-related hospitalization and mortality. JAMA. 2019;321(24):2438–2438. doi:10.1001/jama.2019.723331237643
   PubMed Web of Science ®Google Scholar
• Haroon S, Adab P, Riley RD, Fitzmaurice D, Jordan RE. Predicting risk of undiagnosed COPD: development and validation of the TargetCOPD score. Eur Respir J. 2017;49(6):1602191. doi:10.1183/13993003.02191-201628642308
   PubMed Web of Science ®Google Scholar
• Office for National Statistics. Impact of registration delays on mortality statistics. Natl Arch. 2011;2011:94–95.
   Google Scholar