References
- Centers for Disease Control, National Center for Health Statistics. 2015. FastStats asthma. [accessed 2021 Mar 15]. https://www.cdc.gov/nchs/fastats/asthma.htm.
- Centers for Disease Control. September 2014. Uncontrolled asthma among persons with current asthma. [accessed 2021 Mar 15]. https://www.cdc.gov/asthma/asthma_stats/uncontrolled_asthma.pdf.
- Barnes PJ, Jonsson B, Klim JB. The costs of asthma. Eur Respir J. 1996;9(4):636–642. doi:https://doi.org/10.1183/09031936.96.09040636.
- Asher I, Pearce N. Global burden of asthma among children. Int J Tuberc Lung Dis. 2014;18(11):1269–1278. doi:https://doi.org/10.5588/ijtld.14.0170.
- Wenzel S E, Schwartz L B, Langmack E L, Halliday J L, Trudeau J B, Gibbs R L, Chu H W. Evidence that severe asthma can be divided pathologically into two inflammatory subtypes with distinct physiologic and clinical characteristics. Am J Respir Crit Care Med. 1999;160(3):1001–1008. doi:https://doi.org/10.1164/ajrccm.160.3.9812110.
- Payne D, Bush A. Phenotype-specific treatment of difficult asthma in children. Paediatr Respir Rev. 2004;5(2):116–123. doi:https://doi.org/10.1016/j.prrv.2004.01.006.
- Education, National Asthma, and Prevention Program. Expert panel report 3 (EPR-3): guidelines for the diagnosis and management of asthma-summary report 2007. J Allergy Clin Immunol. 2007;120(5 Suppl):S94–S138.
- Haldar P, Pavord ID, Shaw DE, Berry MA, Thomas M, Brightling CE, Wardlaw AJ, Green RH. Cluster analysis and clinical asthma phenotypes. Am J Respir Crit Care Med. 2008;178(3):218–224. PMC3992366 doi:https://doi.org/10.1164/rccm.200711-1754OC.
- Moore WC, Meyers DA, Wenzel SE, Teague WG, Li H, Li X, D’Agostino R, Castro M, Curran-Everett D, Fitzpatrick AM, et al. Identification of asthma phenotypes using cluster analysis in the severe asthma research program. Am J Respir Crit Care Med. 2010;181(4):315–323. PMC2822971 doi:https://doi.org/10.1164/rccm.200906-0896OC.
- Schatz M, Hsu J-WY, Zeiger RS, Chen W, Dorenbaum A, Chipps BE, Haselkorn T. Phenotypes determined by cluster analysis in severe or difficult-to-treat asthma. J Allergy Clin Immunol. 2014;133(6):1549–1556. doi:https://doi.org/10.1016/j.jaci.2013.10.006.
- Just J, Gouvis-Echraghi R, Couderc R, Guillemot-Lambert N, Saint-Pierre P. Novel severe wheezy young children phenotypes: boys atopic multiple-trigger and girls nonatopic uncontrolled wheeze. J Allergy Clin Immunol. 2012;130(1):103–110. e108. doi:https://doi.org/10.1016/j.jaci.2012.02.041.
- Fitzpatrick AM, Teague WG, Meyers DA, Peters SP, Li X, Li H, Wenzel SE, Aujla S, Castro M, Bacharier LB, et al. Heterogeneity of severe asthma in childhood: confirmation by cluster analysis of children in the National Institutes of Health/National Heart, Lung, and Blood Institute Severe Asthma Research Program. J Allergy Clin Immunol. 2011;127(2):382–389. e381-313. PMC3060668 doi:https://doi.org/10.1016/j.jaci.2010.11.015.
- Ross MK, Yoon J, van der Schaar A, van der Schaar M. Discovering pediatric asthma phenotypes on the basis of response to controller medication using machine learning. Ann Am Thoracic Soc. 2018;15(1):49–58. PMC5822415 doi:https://doi.org/10.1513/AnnalsATS.201702-101OC.
- Prosperi MC, Sahiner UM, Belgrave D, Sackesen C, Buchan IE, Simpson A, Yavuz TS, Kalayci O, Custovic A. Challenges in identifying asthma subgroups using unsupervised statistical learning techniques. Am J Respir Crit Care Med. 2013;188(11):1303–1312. doi:https://doi.org/10.1164/rccm.201304-0694OC.
- Deliu M, Sperrin M, Belgrave D, Custovic A. Identification of asthma subtypes using clustering methodologies. Pulm Ther. 2016;2(1):19–41. doi:https://doi.org/10.1007/s41030-016-0017-z.
- Peters JM, Avol E, Navidi W, London SJ, Gauderman WJ, Lurmann F, Linn WS, Margolis H, Rappaport E, Gong H, et al. A study of twelve Southern California communities with differing levels and types of air pollution. I. Prevalence of respiratory morbidity. Am J Respir Crit Care Med. 1999;159(3):760–767. doi:https://doi.org/10.1164/ajrccm.159.3.9804143.
- Moher D, Liberati A, Tetzlaff J, Altman DG, Group P. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. J Clin Epidemiol. 2009;62(10):1006–1012. doi:https://doi.org/10.1016/j.jclinepi.2009.06.005.
- rpart: Recursive Partitioning and Regression Trees [computer program]. 2015.
- Fingleton J, Travers J, Williams M, Charles T, Bowles D, Strik R, Shirtcliffe P, Weatherall M, Beasley R, Braithwaite I, et al. Treatment responsiveness of phenotypes of symptomatic airways obstruction in adults. J Allergy Clin Immunol. 2015;136(3):601–609. doi:https://doi.org/10.1016/j.jaci.2015.01.013.
- Vogel MA, Wong AK. PFS clustering method. IEEE Trans Pattern Anal Mach Intell. 1979;(3):237–245. doi:https://doi.org/10.1109/tpami.1979.4766919.
- Tibshirani R, Walther G, Hastie T. Estimating the number of clusters in a data set via the gap statistic. J R Stat Soc: Ser B (Statistical Methodology). 2001;63(2):411–423. doi:https://doi.org/10.1111/1467-9868.00293.
- McConnell R, Berhane K, Yao L, Jerrett M, Lurmann F, Gilliland F, Künzli N, Gauderman J, Avol E, Thomas D, et al. Traffic, susceptibility, and childhood asthma. Environ Health Perspect. 2006;114(5):766–772. PMC1459934 doi:https://doi.org/10.1289/ehp.8594.
- Gauderman WJ, Urman R, Avol E, Berhane K, McConnell R, Rappaport E, Chang R, Lurmann F, Gilliland F. Association of improved air quality with lung development in children. N Engl J Med. 2015;372(10):905–913. doi:https://doi.org/10.1056/NEJMoa1414123.
- Knudson RJ, Lebowitz MD, Holberg CJ, Burrows B. Changes in the normal maximal expiratory flow-volume curve with growth and aging. Am Rev Respir Dis. 1983;127(6):725–734.
- Linn WS, Rappaport EB, Berhane KT, Bastain TM, Salam MT, Gilliland FD. Extended exhaled nitric oxide analysis in field surveys of schoolchildren: a pilot test. Pediatr Pulmonol. 2009;44(10):1033–1042. doi:https://doi.org/10.1002/ppul.21101.
- Linn WS, Rappaport EB, Eckel SP, Berhane KT, Zhang Y, Salam MT, Bastain TM, Gilliland FD. Multiple-flow exhaled nitric oxide, allergy, and asthma in a population of older children. Pediatr Pulmonol. 2013;48(9):885–896. doi:https://doi.org/10.1002/ppul.22708.
- Mahut B, Peyrard S, Delclaux C. Exhaled nitric oxide and clinical phenotypes of childhood asthma. Respir Res. 2011;12(1):65. PMC3126727 doi:https://doi.org/10.1186/1465-9921-12-65.
- Hinks TSC, Brown T, Lau LCK, Rupani H, Barber C, Elliott S, Ward JA, Ono J, Ohta S, Izuhara K, et al. Multidimensional endotyping in patients with severe asthma reveals inflammatory heterogeneity in matrix metalloproteinases and chitinase 3-like protein 1. J Allergy Clin Immunol. 2016;138(1):61–61. 75. PMC doi:https://doi.org/10.1016/j.jaci.2015.11.020.
- Musk AW, Knuiman M, Hunter M, Hui J, Palmer LJ, Beilby J, Divitini M, Mulrennan S, James A. Patterns of airway disease and the clinical diagnosis of asthma in the Busselton population. Eur Respir J. 2011;38(5):1053–1059. doi:https://doi.org/10.1183/09031936.00102110.
- Spycher BD, Silverman M, Brooke AM, Minder CE, Kuehni CE. Distinguishing phenotypes of childhood wheeze and cough using latent class analysis. Eur Respir J. 2008;31(5):974–981. doi:https://doi.org/10.1183/09031936.00153507.
- Agache I, Ciobanu C. Risk factors and asthma phenotypes in children and adults with seasonal allergic rhinitis. Phys Sportsmed. 2010;38(4):81–86. doi:https://doi.org/10.3810/psm.2010.12.1829.
- Benton AS, Wang Z, Lerner J, Foerster M, Teach SJ, Freishtat RJ. Overcoming heterogeneity in pediatric asthma: tobacco smoke and asthma characteristics within phenotypic clusters in an African American cohort. J Asthma. 2010;47(7):728–734. PMC3325290 doi:https://doi.org/10.3109/02770903.2010.491142.
- Just J, Gouvis-Echraghi R, Rouve S, Wanin S, Moreau D, Annesi-Maesano I. Two novel, severe asthma phenotypes identified during childhood using a clustering approach. Eur Respir J. 2012;40(1):55–60. doi:https://doi.org/10.1183/09031936.00123411.
- Just J, Saint-Pierre P, Gouvis-Echraghi R, Boutin B, Panayotopoulos V, Chebahi N, Ousidhoum-Zidi A, Khau CA. Wheeze phenotypes in young children have different courses during the preschool period. Ann Allergy Asthma Immunol. 2013;111(4):256–261. e251. doi:https://doi.org/10.1016/j.anai.2013.07.002.
- Lavoie-Charland É, Bérubé J-C, Laviolette M, Boulet L-P, Bossé Y. Multivariate asthma phenotypes in adults: the Quebec City case-control asthma cohort. Open J Respir Dis. 2013;3(4):133–142. doi:https://doi.org/10.4236/ojrd.2013.34021.
- Spycher BD, Silverman M, Pescatore AM, Beardsmore CS, Kuehni CE. Comparison of phenotypes of childhood wheeze and cough in 2 independent cohorts. J Allergy Clin Immunol. 2013;132(5):1058–1067. doi:https://doi.org/10.1016/j.jaci.2013.08.002.
- Lemiere C, NGuyen S, Sava F, D’Alpaos V, Huaux F, Vandenplas O. Occupational asthma phenotypes identified by increased fractional exhaled nitric oxide after exposure to causal agents. J Allergy Clin Immunol. 2014;134(5):1063–1067. doi:https://doi.org/10.1016/j.jaci.2014.08.017.
- Moore WC, Hastie AT, Li X, Li H, Busse WW, Jarjour NN, Wenzel SE, Peters SP, Meyers DA, Bleecker ER, et al. Sputum neutrophil counts are associated with more severe asthma phenotypes using cluster analysis. J Allergy Clin Immunol. 2014;133(6):1557–1563. doi:https://doi.org/10.1016/j.jaci.2013.10.011.
- Sakagami T, Hasegawa T, Koya T, Furukawa T, Kawakami H, Kimura Y, Hoshino Y, Sakamoto H, Shima K, Kagamu H, et al. Cluster analysis identifies characteristic phenotypes of asthma with accelerated lung function decline. J Asthma. 2014;51(2):113–118. doi:https://doi.org/10.3109/02770903.2013.852201.
- Siroux V, Gonzalez JR, Bouzigon E, Curjuric I, Boudier A, Imboden M, Anto JM, Gut I, Jarvis D, Lathrop M, et al. Genetic heterogeneity of asthma phenotypes identified by a clustering approach. Eur Respir J. 2014;43(2):439–452. doi:https://doi.org/10.1183/09031936.00032713.
- Wu W, Bleecker E, Moore W, Busse WW, Castro M, Chung KF, Calhoun WJ, Erzurum S, Gaston B, Israel E, et al. Unsupervised phenotyping of severe asthma research program participants using expanded lung data. J Allergy Clin Immunol. 2014;133(5):1280–1288. PMC4038417 doi:https://doi.org/10.1016/j.jaci.2013.11.042.
- Loureiro CC, Sa-Couto P, Todo-Bom A, Bousquet J. Cluster analysis in phenotyping a Portuguese population. Rev Port Pneumol. 2015;21(6):299–306.
- Mastalerz L, Celejewska-Wojcik N, Wojcik K, Gielicz A, Ćmiel A, Ignacak M, Oleś K, Szczeklik A, Sanak M, et al. Induced sputum supernatant bioactive lipid mediators can identify subtypes of asthma. Clin Exp Allergy. 2015;45(12):1779–1789. doi:https://doi.org/10.1111/cea.12654.
- Park HW, Song WJ, Kim SH, Park HK, Kim SH, Kwon YE, Kwon HS, Kim TB, Chang, YS, Cho YS, et al. Classification and implementation of asthma phenotypes in elderly patients. Ann Allergy Asthma Immunol. 2015;114(1):18–22. doi:https://doi.org/10.1016/j.anai.2014.09.020.
- Serrano-Pariente J, Rodrigo G, Fiz JA, Crespo A, Plaza V, High Risk Asthma Research Group. Identification and characterization of near-fatal asthma phenotypes by cluster analysis. Allergy. 2015;70(9):1139–1147. doi:https://doi.org/10.1111/all.12654.
- Sbihi H, Koehoorn M, Tamburic L, Brauer M. Asthma trajectories in a population-based birth cohort. Impacts of air pollution and greenness. Am J Respir Crit Care Med. 2017;195(5):607–613. doi:https://doi.org/10.1164/rccm.201601-0164OC.
- Sutherland ER, Goleva E, King TS, Lehman E, Stevens AD, Jackson LP, Stream AR, Fahy JV. Cluster analysis of obesity and asthma phenotypes. PLoS One. 2012;7(5):e36631. doi:https://doi.org/10.1371/journal.pone.0036631.
- Wu ST, Sohn S, Ravikumar KE, Wagholikar K, Jonnalagadda SR, Liu H, Juhn YJ. Automated chart review for asthma cohort identification using natural language processing: an exploratory study. Ann Allergy Asthma Immunol. 2013;111(5):364–369. PMC3839107 doi:https://doi.org/10.1016/j.anai.2013.07.022.
- Jo KW, Ra SW, Chae EJ, Seo JB, Kim NK, Lee JH, Kim EK, Lee YK, Kim TH, Huh JW, et al. Three phenotypes of obstructive lung disease in the elderly. Int J Tuberculosis Lung Dis. 2010;14(11):1481–1488.
- Williams-DeVane CR, Reif DM, Cohen Hubal E, Bushel PR, Hudgens EE, Gallagher JE, Edwards SW. Decision tree-based method for integrating gene expression, demographic, and clinical data to determine disease endotypes. BMC Syst Biol. 2013;7(1):119. PMC4228284 doi:https://doi.org/10.1186/1752-0509-7-119.
- Meyer N, Dallinga JW, Nuss SJ, Moonen EJ, van Berkel JJ, Akdis C, van Schooten FJ, Menz, G. Defining adult asthma endotypes by clinical features and patterns of volatile organic compounds in exhaled air. Respir Res. 2014;15:136. doi:https://doi.org/10.1186/s12931-014-0136-8.
- Konstantellou E, Papaioannou AI, Loukides S, Patentalakis G, Papaporfyriou A, Hillas G, Papiris S, Koulouris N, Bakakos P, Kostikas K. Persistent airflow obstruction in patients with asthma: Characteristics of a distinct clinical phenotype. Respir Med. 2015;109(11):1404–1409. doi:https://doi.org/10.1016/j.rmed.2015.09.009.
- Garcia-Aymerich J, Benet M, Saeys Y, Pinart M, Basagana X, Smit HA, Siroux V, Just J, Momas I, Rancière F, et al. Phenotyping asthma, rhinitis and eczema in MeDALL population-based birth cohorts: an allergic comorbidity cluster. Allergy. 2015;70(8):973–984. doi:https://doi.org/10.1111/all.12640.
- Ortega H, Prazma C, Suruki RY, Li H, Anderson WH. Association of CHI3L1 in African-Americans with prior history of asthma exacerbations and stress. J Asthma. 2013;50(1):7–13. doi:https://doi.org/10.3109/02770903.2012.733991.
- Boudier A, Curjuric I, Basagana X, Hazgui H, Anto JM, Bousquet J, Bridevaux PO, Dupuis-Lozeron E, Garcia-Aymerich J, Heinrich J, et al. Ten-year follow-up of cluster-based asthma phenotypes in adults. A pooled analysis of three cohorts. Am J Respir Crit Care Med. 2013;188(5):550–560. doi:https://doi.org/10.1164/rccm.201301-0156OC.
- Ranciere F, Nikasinovic L, Bousquet J, Momas I. Onset and persistence of respiratory/allergic symptoms in preschoolers: new insights from the PARIS birth cohort. Allergy. 2013;68(9):1158–1167. doi:https://doi.org/10.1111/all.12208.
- Weinmayr G, Keller F, Kleiner A, Du Prel JB, Garcia‐Marcos L, Batllés‐Garrido J, Garcia‐Hernandez G, Suarez‐Varela MM, Strachan DP, Nagel G. Asthma phenotypes identified by latent class analysis in the ISAAC phase II Spain study. Clin Exp Allergy. 2013;43(2):223–232. doi:https://doi.org/10.1111/cea.12035.
- Siroux V, Basagana X, Boudier A, Pin I, Garcia-Aymerich J, Vesin A, Slama R, Jarvis D, Anto JM, Kauffmann F, et al. Identifying adult asthma phenotypes using a clustering approach. Eur Respir J. 2011;38(2):310–317. doi:https://doi.org/10.1183/09031936.00120810.
- Kim TB, Jang AS, Kwon HS, Park, JS, Chang YS, Cho SH, Choi BW, Park JW, Nam DH, Yoon HJ, et al. Identification of asthma clusters in two independent Korean adult asthma cohorts. Eur Respir J. 2013;41(6):1308–1314. doi:https://doi.org/10.1183/09031936.00100811.
- Rootmensen G, van Keimpema A, Zwinderman A, Sterk P. Clinical phenotypes of obstructive airway diseases in an outpatient population. J Asthma. 2016;53(10):1026–1032. doi:https://doi.org/10.3109/02770903.2016.1174258.
- Yamada H, Masuko H, Yatagai Y, Sakamoto T, Kaneko Y, Iijima H, Naito T, Noguchi E, Konno S, Nishimura M, et al. Role of lung function genes in the development of asthma. PLoS One. 2016;11(1):e0145832. PMC4709100 doi:https://doi.org/10.1371/journal.pone.0145832.
- Zaihra T, Walsh CJ, Ahmed S, Fugère C, Hamid QA, Olivenstein R, Martin JG, Benedetti A. Phenotyping of difficult asthma using longitudinal physiological and biomarker measurements reveals significant differences in stability between clusters. BMC Pulm Med. 2016;16(1):74. PMC4862112 doi:https://doi.org/10.1186/s12890-016-0232-2.
- Weatherall M, Travers J, Shirtcliffe PM, Marsh SE, Williams MV, Nowitz MR, Aldington S, Beasley R. Distinct clinical phenotypes of airways disease defined by cluster analysis. Eur Respir J. 2009;34(4):812–818. doi:https://doi.org/10.1183/09031936.00174408.
- Couto M, Stang J, Horta L, Stensrud T, Severo M, Mowinckel P, Silva D, Delgado L, Moreira A, Carlsen KH. Two distinct phenotypes of asthma in elite athletes identified by latent class analysis. J Asthma. 2015;52(9):897–904. doi:https://doi.org/10.3109/02770903.2015.1067321.
- Wu W, Bang S, Bleecker ER, Castro M, Denlinger L, Erzurum SC, Fahy JV, Fitzpatrick AM, Gaston BM, Hastie AT, et al. Multiview cluster analysis identifies variable corticosteroid response phenotypes in severe asthma. Am J Respir Crit Care Med. 2019;199(11):1358–1367. PMC6543720 doi:https://doi.org/10.1164/rccm.201808-1543OC.
- Kaneko Y, Masuko H, Sakamoto T, Iijima H, Naito T, Yatagai Y, Yamada H, Konno S, Nishimura M, Noguchi E, et al. Asthma phenotypes in Japanese adults - their associations with the CCL5 and ADRB2 genotypes. Allergol Int. 2013;62(1):113–121. doi:https://doi.org/10.2332/allergolint.12-OA-0467.
- Amelink M, de Nijs SB, de Groot JC, van Tilburg PM, van Spiegel PI, Krouwels FH, Lutter R, Zwinderman AH, Weersink EJ, ten Brinke A, et al. Three phenotypes of adult-onset asthma. Allergy. 2013;68(5):674–680. doi:https://doi.org/10.1111/all.12136.
- Howrylak JA, Fuhlbrigge AL, Strunk RC, Zeiger RS, Weiss ST, Raby BA. Classification of childhood asthma phenotypes and long-term clinical responses to inhaled anti-inflammatory medications. J Allergy Clin Immunol. 2014;133(5):1289–1300. 1300 e1281-1212. PMC4047642 doi:https://doi.org/10.1016/j.jaci.2014.02.006.
- Ortega H, Li H, Suruki R, Albers F, Gordon D, Yancey S. Cluster analysis and characterization of response to mepolizumab. A step closer to personalized medicine for patients with severe asthma. Ann Am Thorac Soc. 2014;11(7):1011–1017. doi:https://doi.org/10.1513/AnnalsATS.201312-454OC.
- Newby C, Heaney LG, Menzies-Gow A, Niven RM, Mansur A, Bucknall C, Chaudhuri R, Thompson J, Burton P, Brightling C, et al. Statistical cluster analysis of the British Thoracic Society Severe refractory Asthma Registry: clinical outcomes and phenotype stability. PLoS One. 2014;9(7):e102987. PMC4109965 doi:https://doi.org/10.1371/journal.pone.0102987.
- Loza MJ, Adcock I, Auffray C, Chung KF, Djukanovic R, Sterk PJ, Susulic VS, Barnathan, ES, Baribaud F, Silkoff PE. Longitudinally stable, clinically defined clusters of patients with asthma independently identified in the ADEPT and U-BIOPRED asthma studies. Ann Am Thorac Soc. 2016;13 (Suppl 1):S102–S103.
- Zoratti EM, Krouse RZ, Babineau DC, Pongracic JA, O’Connor GT, Wood RA, Khurana Hershey GK, Kercsmar CM, Gruchalla RS, Kattan M, et al. Asthma phenotypes in inner-city children. J Allergy Clin Immunol. 2016;138(4):1016–1029. PMC5104222 doi:https://doi.org/10.1016/j.jaci.2016.06.061.
- Baptist AP, Hao W, Karamched KR, Kaur B, Carpenter L, Song PXK. Distinct Asthma Phenotypes Among Older Adults with Asthma. J Allergy Clin Immunol Pract. 2018;6(1):244–249 e242. PMC5897052 doi:https://doi.org/10.1016/j.jaip.2017.06.010.
- Ilmarinen P, Tuomisto LE, Niemela O, Tommola M, Haanpää J, Kankaanranta H. Cluster analysis on longitudinal data of patients with adult-onset asthma. J Allergy Clin Immunol Pract. 2017;5(4):967–978 e963. doi:https://doi.org/10.1016/j.jaip.2017.01.027.
- Sendin-Hernandez MP, Avila-Zarza C, Sanz C, García-Sánchez A, Marcos-Vadillo E, Muñoz-Bellido FJ, Laffond E, Domingo C, Isidoro-García M, Dávila I. Cluster analysis identifies 3 phenotypes within allergic asthma. J Allergy Clin Immunol Pract. 2018;6(3):955–961 e951. doi:https://doi.org/10.1016/j.jaip.2017.10.006.
- Wang L, Liang R, Zhou T, Zheng J, Liang BM, Zhang HP, Luo FM, Gibson PG, Wang G. Identification and validation of asthma phenotypes in Chinese population using cluster analysis. Ann Allergy Asthma Immunol. 2017;119(4):324–332. doi:https://doi.org/10.1016/j.anai.2017.07.016.
- Panico L, Stuart B, Bartley M, Kelly Y. Asthma trajectories in early childhood: identifying modifiable factors. PLoS One. 2014;9(11):e111922. PMC4224405 doi:https://doi.org/10.1371/journal.pone.0111922.
- Pite H, Gaspar A, Morais-Almeida M. Preschool-age wheezing phenotypes and asthma persistence in adolescents. Allergy Asthma Proc. 2016;37(3):231–241. doi:https://doi.org/10.2500/aap.2016.37.3955.
- Schoos A-MM, Chawes BL, Rasmussen MA, Bloch J, Bønnelykke K, Bisgaard H. Atopic endotype in childhood. J Allergy Clin Immunol. 2016;137(3):844–851. doi:https://doi.org/10.1016/j.jaci.2015.10.004.
- Westman M, Kull I, Lind T, Melen E, Stjärne P, Toskala E, Wickman M, Bergström A. The link between parental allergy and offspring allergic and nonallergic rhinitis. Allergy. 2013;68(12):1571–1578. doi:https://doi.org/10.1111/all.12267.
- Sonnenschein-van der Voort AMM, Arends LR, de Jongste JC, Annesi-Maesano I, Arshad SH, Barros H, Basterrechea M, Bisgaard H, Chatzi L, Corpeleijn E, et al. Preterm birth, infant weight gain, and childhood asthma risk: a meta-analysis of 147,000 European children. J Allergy Clin Immunol. 2014;133(5):1317–1329. PMC4024198 doi:https://doi.org/10.1016/j.jaci.2013.12.1082.
- Harrell FE, Jr, Dupont MC, The Hmisc Package. R Package, version. 2018:3.5-1.
- Nielsen F. Hierarchical clustering. In: Mackie I, ed. Introduction to HPC with MPI for data science. Switzerland: Springer International Publishing; 2016. p. 195–211.
- Jin X, Han J. K-medoids clustering. Boston, MA: Springer US; 2010.
- Vermunt JK, Magidson J. Latent class cluster analysis. Appl Latent Class Anal. 2002;11(89–106):60.
- Loza MJ, Djukanovic R, Chung KF, Horowitz D, Ma K, Branigan P, Barnathan ES, Susulic VS, Silkoff PE, Sterk PJ, et al. Validated and longitudinally stable asthma phenotypes based on cluster analysis of the ADEPT study. Respir Res. 2016;17(1):165. doi:https://doi.org/10.1186/s12931-016-0482-9.
- Jain AK. Data clustering: 50 years beyond k-means. Paper presented at: Joint European Conference on Machine Learning and Knowledge Discovery in Databases; 2008.
- Berhane K, Chang C-C, McConnell R, Gauderman WJ, Avol E, Rapapport E, Urman R, Lurmann F, Gilliland F. Association of changes in air quality with bronchitic symptoms in children in California, 1993-2012. JAMA. 2016;315(14):1491–1501. doi:https://doi.org/10.1001/jama.2016.3444.
- Centers for Disease Control. 2009. A SAS program for the CDC growth charts. [accessed 2021 Mar 15]. http://www.cdc.gov/nccdphp/dnpao/growthcharts/resources/sas.htm.
- He H, Butz A, Keet CA, Minkovitz CS, Hong X, Caruso DM, Pearson C, Cohen RT, Wills-Karp M, Zuckerman BS, et al. Preterm birth with childhood asthma: the role of degree of prematurity and asthma definitions. Am J Respir Crit Care Med. 2015;192(4):520–523. PMC4595670 doi:https://doi.org/10.1164/rccm.201503-0522LE.
- Collins GS, Reitsma JB, Altman DG, Moons KG. Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement. Br J Surg. 2015;102(3):148–158. doi:https://doi.org/10.1002/bjs.9736.
- Altman E, Avrachenkov K, Ramanath S. Multiscale fairness and its application to resource allocation in wireless networks. Comput Commun. 2012;35(7):820–828. doi:https://doi.org/10.1016/j.comcom.2012.01.013.
- Collins FS, Tabak LA. Policy: NIH plans to enhance reproducibility. Nature. 2014;505(7485):612–613. PMC4058759 doi:https://doi.org/10.1038/505612a.
- Howard R, Rattray M, Prosperi M, Custovic A. Distinguishing asthma phenotypes using machine learning approaches. Curr Allergy Asthma Rep. 2015;15(7):38. doi:https://doi.org/10.1007/s11882-015-0542-0.
- Jain AK. Data clustering: 50 years beyond K-means. Pattern Recog Lett. 2010;31(8):651–666. doi:https://doi.org/10.1016/j.patrec.2009.09.011.
- Petsky HL, Cates CJ, Kew KM, Chang AB. Tailoring asthma treatment on eosinophilic markers (exhaled nitric oxide or sputum eosinophils): a systematic review and meta-analysis. Thorax. 2018;73(12):1110–1119. doi:https://doi.org/10.1136/thoraxjnl-2018-211540.
- Expert Panel Working Group of the National Heart L, Blood Institute a, coordinated National Asthma E, et al. 2020 Focused updates to the asthma management guidelines: a report from the National Asthma Education and Prevention Program Coordinating Committee Expert Panel Working Group. J Allergy Clin Immunol. 2020;146(6):1217–1270.