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Strength of association between comorbidities and asthma: a meta-analysis

Paola Rogliani, Rossella Laitano, Josuel Ora, Richard Beasley, Luigino Calzetta
European Respiratory Review 2023 32: 220202; DOI: 10.1183/16000617.0202-2022
Paola Rogliani
1Unit of Respiratory Medicine, Department of Experimental Medicine, University of Rome “Tor Vergata”, Rome, Italy
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  • For correspondence: paola.rogliani@uniroma2.it
Rossella Laitano
1Unit of Respiratory Medicine, Department of Experimental Medicine, University of Rome “Tor Vergata”, Rome, Italy
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Josuel Ora
1Unit of Respiratory Medicine, Department of Experimental Medicine, University of Rome “Tor Vergata”, Rome, Italy
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Richard Beasley
2Medical Research Institute of New Zealand, Wellington, New Zealand
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Luigino Calzetta
3Department of Medicine and Surgery, Respiratory Disease and Lung Function Unit, University of Parma, Parma, Italy
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  • FIGURE 1
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    FIGURE 1

    PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 flow diagram for the identification of the studies included in the pairwise meta-analysis.

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    FIGURE 2

    Analysis of the strength of association of specific a) psychiatric and neuronal disorders, b) respiratory disorders, c) allergic disorders and d) cardiovascular disorders with asthma.

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    FIGURE 3

    Analysis of the strength of association of specific a) metabolic disorders, b) gastrointestinal disorders, c) musculoskeletal disorders and d) other disorders with asthma. GORD: gastro-oesophageal reflux disease.

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    FIGURE 4

    Analysis of the strength of association of specific a) psychiatric and neurological disorders, b) respiratory and allergic disorders, c) cardiovascular disorders, d) metabolic disorders and e) other disorders with severe asthma.

Tables

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  • TABLE 1

    Main characteristics of the observational studies included in the pairwise meta-analysis. When necessary, age, sex and smoking habit were reported as weighted arithmetic mean between asthma and nonasthma populations

    First author, year [ref.]CountryStudy characteristicsDuration of observation (years)Subjects analysedAsthmatic subjectsGroups of comparisonSubjects’ characteristicsAge (years)Male (%)Diagnosis of asthmaCurrent smokers (%)NOS quality assessmentJBI checklist tool+
    SelectionComparabilityOutcome#/exposure¶Total
    Chalitsios, 2021 [49]UKPopulation-based, retrospective, longitudinal, cohort study13658 749138 123 (21.0)Asthma versus nonasthma controlSubjects selected from the UK Clinical Practice Research Database51.841.0Read codes for asthma20.4********8
    Landré, 2020 [50]FranceRetrospective, cohort study2612 345372 (3.0)Asthma versus nonasthma controlSubjects selected from the French GAZEL cohort of community-dwelling adults69.874.0Diagnosis defined by questionnaire7.0*** §ƒ3
    Carter, 2019 [54]UKRetrospective, cohort study≈12362 54460 424 (16.7)Asthma versus nonasthma controlSubjects admitted to NHS hospitals in the UK48.626.5Diagnostic ICD-10 and OPCS-4 disease codesNA*** §*** ƒ6
    Kim, 2019 [55]KoreaPopulation-based, retrospective, longitudinal, cohort study≈11226 118113 059 (50.0)Asthma versus nonasthma controlSubjects randomly selected from the Korean National Health Insurance Service Database≥20.037.3Asthma or status asthmaticus diagnostic ICD-10 codes: J45 or J46 of a physician diagnosisNA*** §*** ƒ6
    Kim, 2019 [40]USPopulation-based, retrospective, cross-sectional survey≈4643 88544 420 (6.9)Asthma versus nonasthma controlRepresentative sample of civilian, non-institutionalised subjects of USA selected from the National Health Interview Survey≥18.048.0Diagnosis defined by questionnaire16.0High bias
    Bourdin, 2019 [63]FrancePopulation-based, retrospective, case–control study32760690 (25.0)Severe asthma versus nonasthma controlSubjects randomly selected from a French representative claims database61.034.3Diagnosis based on GINA recommendations (severe asthma patients received ≥1 dispensing for OMA and/or ≥10 dispensings of a medium or high dose of ICS+LABA)NA*******7
    Toppila-Salmi, 2019 [64]FinlandPopulation-based, retrospective, case–control study128901118 (38.7)Asthma (includes severe asthma) versus nonasthma controlSubjects randomly selected from the Finnish Drug Reimbursement Register53.037.0Drug reimbursement decision of diagnosed asthma granted by prior physician's certificate, which includes background information, clinical examination results, lung function test results and findings and conclusions after asthma treatment test for 6 monthsNA******6
    Varsano, 2017 [39]IsraelPopulation-based, retrospective, cross-sectional study139 99119 991 (50.0)Nonsevere and severe asthma versus nonasthma controlSubjects selected from an Israeli population present in a national electronic healthcare insurance provider database42.223.8Asthma diagnostic ICD-9 CM code of a physician's diagnosis of bronchial asthma20.0Low bias
    Weatherburn, 2017 [38]UKPopulation-based, retrospective, cross-sectional studyNA1 424 37884 505 (5.9)Asthma versus nonasthma controlRepresentative sample of the Scottish population selected from the UK NHS database of primary care practice≥18.049.1Primary-care physician's diagnosis24.5Moderate bias
    Bozek, 2016 [37]PolandPopulation-based, retrospective, cross-sectional study120991023 (48.7)Asthma versus nonasthma controlRepresentative population of all regions of Poland randomly selected from patient databases67.946.4Diagnosis based on clinical criteria according to GINA recommendations and a positive reversibility test after salbutamol according to the ATS/ERS criteria6.9Moderate bias
    Peng, 2015 [56]TaiwanNationwide, retrospective, population-based, cohort study≈363 85512 771 (20.0)Asthma versus nonasthma controlSubjects randomly selected from the National Health Insurance Research Database of Taiwan53.745.8Asthma diagnostic ICD-9 CM code: 493NA*** §*** ƒ6
    Van den Bemt, 2016 [57]The NetherlandsDynamic historical, longitudinal, cohort study≈202385795 (33.3)Asthma versus nonasthma controlSubjects selected from the Continuous Morbidity Registration Nijmegen database33.341.1Physician's diagnosisNA********8
    Yao, 2016 [58]ChinaPopulation-based, retrospective, longitudinal, cohort study684 47428 158 (33.3)Asthma versus nonasthma controlSubjects randomly selected from the National Health Insurance Research Database of Taiwan54.546.3Asthma diagnostic ICD-9 CM code: 493; subjects who had ≥1 hospitalisation or ≥3 visits for outpatient medical services for asthmaNA*** §*** ƒ6
    Cheng, 2015 [59]TaiwanNationwide, retrospective, longitudinal, cohort study1152 27510 455 (20.0)Asthma versus nonasthma controlSubjects randomly selected from the National Health Insurance Research Database of Taiwan59.841.3Asthma diagnostic ICD-9 CM code: 493; diagnosis by pulmonologist or rheumatologist on clinical judgement or pulmonary function testNA*** §*** ƒ6
    Alcázar Navarrete, 2015 [36]SpainCross-sectional studyNA5740 (70.2)Asthma versus nonasthma controlOutpatients in an ambulatory setting60.831.6Previous physician diagnosis of bronchial asthma7.0Moderate bias
    Chung, 2014 [60]TaiwanNationwide, retrospective, population-based, cohort study6156 51331 356 (20.0)Asthma versus nonasthma controlSubjects randomly selected from the National Health Insurance Research Database of Taiwan38.949.0Asthma diagnostic ICD-9 code: 493 from ambulatory case visits or admission recordsNA*** §*** ƒ6
    Chung, 2014 [61]TaiwanNationwide, retrospective, population-based, cohort study1172 58714 518 (20.0)Asthma versus nonasthma controlSubjects randomly selected from the National Health Insurance Research Database of Taiwan52.145.7Asthma diagnostic ICD-9 CM code: 493NA*** §*** ƒ6
    Steppuhn, 2014 [48]GermanyPopulation-based, retrospective, cross-sectional survey243 1892242 (5.2)Asthma versus nonasthma controlAdults randomly selected for the national telephone health interview survey in Germany49.048.6Self-reported physician's diagnosis29.8Low bias
    Huang, 2014 [65]TaiwanNationwide, prospective, population–based, case–control study (comorbidities were assessed retrospectively)3140 34435 086 (25.0)Asthma versus nonasthma controlSubjects randomly selected from the National Health Insurance Research Database of Taiwan47.744.1Diagnosis by board-certified internist, clinical immunologist, pulmonologist or other medical expertsNA********8
    Chen, 2014 [62]TaiwanNationwide, retrospective, longitudinal, population-based, cohort study1155 15011 030 (20.0)Asthma versus nonasthma controlSubjects randomly selected from the National Health Insurance Research Database of Taiwan60.941.7Asthma diagnostic ICD-9 CM code: 493NA*** §*** ƒ6
    Sundbom, 2013 [47]SwedenPopulation-based, retrospective, cross-sectional survey125 6101830 (7.1)Asthma versus nonasthma controlSubjects randomly selected for the 2008 GA2LEN survey43.749.0Diagnosis defined by questionnaire13.8Moderate bias
    Marcon, 2013 [66]ItalyPopulation-based, retrospective, multi-case–control study≈3662360 (54.4)Mild asthma versus nonasthma controlSubjects randomly selected from the general population belonging to the Italian Study on Asthma in Young Adults cohort and to the Italian branch of the European Community Respiratory Health Survey cohort43.849.0Diagnosis defined by questionnaire and lung function tests22.4*****5
    Lu, 2013 [46]SingaporePopulation-based, retrospective, cross-sectional survey12809106 (3.8)Asthma versus nonasthma controlAdults randomly selected from the Singapore National Mental Health Survey20.0–59.038.2Self-report of a doctor's diagnosisNALow bias
    Traister, 2013 [51]USARetrospective, cohort study≈616059 (36.9)Asthma versus nonasthma controlOutpatients selected by random computer-generated sequence44.633.7Asthma diagnostic ICD-9 CM code: 493 and spirometry tests35.1*** §ƒ3
    Patel, 2013 [45]USAPopulation-based, retrospective, cross-sectional survey822 1722873 (13.0)Asthma versus nonasthma controlRepresentative sample of civilian, non-institutionalised subjects of USA selected from the National Health and Nutrition Examination Survey46.748.1Self-report of a physician's diagnosisNAModerate bias
    Iribarren, 2012 [52]USAProspective, cohort study (comorbidities were assessed retrospectively)13407 190203 595 (50.0)Asthma versus nonasthma controlAdults selected from the Kaiser Permanente Northern California healthcare plan44.634.0Medical records of hospitalisation with primary discharge code ICD-9 CM 493.00−493.99 or ≥1 secondary code for asthma with a principal ICD-9 code for acute asthma-related respiratory conditions, or outpatient or ED visits for asthma17.4*** §*** ƒ6
    Luyster, 2012 [44]USA and UKRetrospective, cross-sectional studyNA282222 (78.7)Nonsevere asthma and severe asthma versus nonasthma controlParticipants selected from the retrospective multicentre Severe Asthma Research Program cohort study31.547.4Evaluation and classification according to the ATS definition of refractory asthma; diagnosis of severe asthma required continuous oral corticosteroid use or high-dose ICS use and ≥2 of the 7 minor criteria [67]0.0Moderate bias
    Cazzola, 2011 [6]ItalyPopulation-based retrospective, cross-sectional study1909 63855 500 (6.1)Asthma versus nonasthma controlSubjects selected from the Health Search Database of the Italian College of General Practitioners>14.047.3Asthma diagnostic ICD-9 CM code: 493NALow bias
    Hakola, 2011 [53]FinlandProspective, cohort study (comorbidities were assessed retrospectively)1–464 9512196 (3.4)Persistent asthma versus nonasthma controlFinnish public sector employees selected from national registers44.120.0Physician's diagnosis confirmation by the Social Insurance Institution of Finland18.3*** §* ƒ5
    Ng, 2007 [43]SingaporePopulation-based, retrospective, cross-sectional survey1109261 (5.6)Asthma versus nonasthma controlOlder adults selected from the National Mental Health Survey of Elderly of Singapore≥60.0NASelf-report of a doctor's diagnosisNALow bias
    Adams, 2006 [42]AustraliaPopulation-based, retrospective, cross-sectional household telephone interview survey17443834 (11.2)Asthma versus nonasthma controlAdults selected from the Collaborative Health and Well-being Survey≥18.050.9Self-report of a doctor's diagnosisNAHigh bias
    Goodwin, 2003 [41]USARetrospective, cross-sectional study≈2998176 (17.6)Asthma versus nonasthma controlPrimary care patients18.0–70.025.1Asthma diagnostic ICD-9 CM code: 493 of a primary-care physician's diagnosisNAModerate bias
    Goodwin, 2003 [35]GermanyPopulation-based, retrospective, cross-sectional, core survey14181236 (5.6)Nonsevere and severe asthma versus nonasthma controlRepresentative community sample of adults41.141.0Questionnaire and physician's diagnosisNAModerate bias

    Data are presented as n or n (%), unless otherwise stated. NOS: Newcastle–Ottawa Scale; JBI: Joanna Briggs Institute; NHS: National Health Service; ICD: International Statistical Classification of Diseases and Related Health Problems; OPCS: Office of Population Censuses and Surveys Classification of Interventions and Procedures; NA: not available; GINA: Global Initiative for Asthma; OMA: omalizumab; ICS: inhaled corticosteroids; LABA: long-acting β2-adrenoceptor agonists; CM: Clinical Modification; ATS: American Thoracic Society; ERS: European Respiratory Society; ED: emergency department. #: cohort studies could not be assigned a star for the outcome item “adequacy of follow-up of cohorts”, as outcomes of interest were all assessed retrospectively and there was no mention of losses; ¶: case–control studies could not be assigned a star for the exposure item “non-response rate”, as outcomes of interest were all assessed retrospectively; +: each of the eight items of the JBI tool was rated as “yes” (1 point) and “no” or “not applicable” (0 points). The score for each cross-sectional study was calculated on the proportion of “yes” responses for the possible maximum score and rated as high, moderate or low risk of bias according to the achieved score expressed as percentage (high bias: ≤49.0%; moderate bias: 50.0–69.0%; low bias ≥70.0%); §: no star could be assigned for the selection item “demonstration that outcome of interest was not present at start of study”, as outcomes of interest were already present at baseline; ƒ: no star could be assigned for the outcome item “was follow-up long enough for outcomes to occur”, as outcomes of interest were already present at baseline.

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    Strength of association between comorbidities and asthma: a meta-analysis
    Paola Rogliani, Rossella Laitano, Josuel Ora, Richard Beasley, Luigino Calzetta
    European Respiratory Review Mar 2023, 32 (167) 220202; DOI: 10.1183/16000617.0202-2022

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    Strength of association between comorbidities and asthma: a meta-analysis
    Paola Rogliani, Rossella Laitano, Josuel Ora, Richard Beasley, Luigino Calzetta
    European Respiratory Review Mar 2023, 32 (167) 220202; DOI: 10.1183/16000617.0202-2022
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