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A scoping review finds a growing trend in studies validating multimorbidity patterns and identifies five broad types of validation methods
Journal of Clinical Epidemiology, Volume: 165, Start page: 111214
Swansea University Authors: Rowena Bailey, Jim Rafferty , Ashley Akbari , Jane Lyons, Alan Watkins , Ronan Lyons
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DOI (Published version): 10.1016/j.jclinepi.2023.11.004
Abstract
Objectives: Multimorbidity, the presence of two or more long-term conditions, is a growing public health concern. Many studies use analytical methods to discover multimorbidity patterns from data. We aimed to review approaches used in published literature to validate these patterns.Study design and...
Published in: | Journal of Clinical Epidemiology |
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ISSN: | 0895-4356 |
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Elsevier BV
2024
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URI: | https://cronfa.swan.ac.uk/Record/cronfa65170 |
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Many studies use analytical methods to discover multimorbidity patterns from data. We aimed to review approaches used in published literature to validate these patterns.Study design and setting: We systematically searched PubMed and Web of Science for studies published between July 2017 and July 2023 that used analytical methods to discover multimorbidity patterns.Results: Out of 31,617 studies returned by the searches, 172 were included. Of these, 111 studies (64%) conducted validation, the number of studies with validation increased from 53.13% (17 out of 32 studies) to 71.25% (57 out of 80 studies) in 2017-2019 to 2022-2023, respectively. Five types of validation were identified: assessing the association of multimorbidity patterns with clinical outcomes (n = 79), stability across subsamples (n = 26), clinical plausibility (n = 22), stability across methods (n = 7) and exploring common determinants (n = 2). Some studies used multiple types of validation.Conclusion: The number of studies conducting a validation of multimorbidity patterns is clearly increasing. The most popular validation approach is assessing the association of multimorbidity patterns with clinical outcomes. Methodological guidance on the validation of multimorbidity patterns is needed.</abstract><type>Journal Article</type><journal>Journal of Clinical Epidemiology</journal><volume>165</volume><journalNumber/><paginationStart>111214</paginationStart><paginationEnd/><publisher>Elsevier BV</publisher><placeOfPublication/><isbnPrint/><isbnElectronic/><issnPrint>0895-4356</issnPrint><issnElectronic/><keywords>Analytical method; Cluster analysis; Latent class analysis; Multimorbidity; Scoping review; Validation.</keywords><publishedDay>1</publishedDay><publishedMonth>1</publishedMonth><publishedYear>2024</publishedYear><publishedDate>2024-01-01</publishedDate><doi>10.1016/j.jclinepi.2023.11.004</doi><url>http://dx.doi.org/10.1016/j.jclinepi.2023.11.004</url><notes/><college>COLLEGE NANME</college><department>Medical School</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>MEDS</DepartmentCode><institution>Swansea University</institution><apcterm>Another institution paid the OA fee</apcterm><funders/><projectreference/><lastEdited>2024-03-25T14:38:08.4814744</lastEdited><Created>2023-12-01T09:36:21.8255233</Created><path><level id="1">Faculty of Medicine, Health and Life Sciences</level><level id="2">Swansea University Medical School - Health Data Science</level></path><authors><author><firstname>Thamer Ba</firstname><surname>Dhafari</surname><orcid>0000-0002-8653-7874</orcid><order>1</order></author><author><firstname>Alexander</firstname><surname>Pate</surname><orcid>0000-0002-0849-3458</orcid><order>2</order></author><author><firstname>Narges</firstname><surname>Azadbakht</surname><order>3</order></author><author><firstname>Rowena</firstname><surname>Bailey</surname><order>4</order></author><author><firstname>Jim</firstname><surname>Rafferty</surname><orcid>0000-0002-1667-7265</orcid><order>5</order></author><author><firstname>Farideh</firstname><surname>Jalali-najafabadi</surname><order>6</order></author><author><firstname>Glen P.</firstname><surname>Martin</surname><order>7</order></author><author><firstname>Abdelaali</firstname><surname>Hassaine</surname><orcid>0000-0002-3270-1165</orcid><order>8</order></author><author><firstname>Ashley</firstname><surname>Akbari</surname><orcid>0000-0003-0814-0801</orcid><order>9</order></author><author><firstname>Jane</firstname><surname>Lyons</surname><orcid/><order>10</order></author><author><firstname>Alan</firstname><surname>Watkins</surname><orcid>0000-0003-3804-1943</orcid><order>11</order></author><author><firstname>Ronan</firstname><surname>Lyons</surname><orcid>0000-0001-5225-000X</orcid><order>12</order></author><author><firstname>Niels</firstname><surname>Peek</surname><orcid>0000-0002-6393-9969</orcid><order>13</order></author></authors><documents><document><filename>65170__29624__d2fee00347324911b49f6aa7758671e5.pdf</filename><originalFilename>65170.pdf</originalFilename><uploaded>2024-03-05T08:56:22.0590070</uploaded><type>Output</type><contentLength>822721</contentLength><contentType>application/pdf</contentType><version>Version of Record</version><cronfaStatus>true</cronfaStatus><documentNotes>This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/
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2024-03-25T14:38:08.4814744 v2 65170 2023-12-01 A scoping review finds a growing trend in studies validating multimorbidity patterns and identifies five broad types of validation methods 455e2c1e6193448f6269b9e72acaf865 Rowena Bailey Rowena Bailey true false 52effe759a718bd36eb12cdd10fe1a09 0000-0002-1667-7265 Jim Rafferty Jim Rafferty true false aa1b025ec0243f708bb5eb0a93d6fb52 0000-0003-0814-0801 Ashley Akbari Ashley Akbari true false 1b74fa5125a88451c52c45bcf20e0b47 Jane Lyons Jane Lyons true false 81fc05c9333d9df41b041157437bcc2f 0000-0003-3804-1943 Alan Watkins Alan Watkins true false 83efcf2a9dfcf8b55586999d3d152ac6 0000-0001-5225-000X Ronan Lyons Ronan Lyons true false 2023-12-01 MEDS Objectives: Multimorbidity, the presence of two or more long-term conditions, is a growing public health concern. Many studies use analytical methods to discover multimorbidity patterns from data. We aimed to review approaches used in published literature to validate these patterns.Study design and setting: We systematically searched PubMed and Web of Science for studies published between July 2017 and July 2023 that used analytical methods to discover multimorbidity patterns.Results: Out of 31,617 studies returned by the searches, 172 were included. Of these, 111 studies (64%) conducted validation, the number of studies with validation increased from 53.13% (17 out of 32 studies) to 71.25% (57 out of 80 studies) in 2017-2019 to 2022-2023, respectively. Five types of validation were identified: assessing the association of multimorbidity patterns with clinical outcomes (n = 79), stability across subsamples (n = 26), clinical plausibility (n = 22), stability across methods (n = 7) and exploring common determinants (n = 2). Some studies used multiple types of validation.Conclusion: The number of studies conducting a validation of multimorbidity patterns is clearly increasing. The most popular validation approach is assessing the association of multimorbidity patterns with clinical outcomes. Methodological guidance on the validation of multimorbidity patterns is needed. Journal Article Journal of Clinical Epidemiology 165 111214 Elsevier BV 0895-4356 Analytical method; Cluster analysis; Latent class analysis; Multimorbidity; Scoping review; Validation. 1 1 2024 2024-01-01 10.1016/j.jclinepi.2023.11.004 http://dx.doi.org/10.1016/j.jclinepi.2023.11.004 COLLEGE NANME Medical School COLLEGE CODE MEDS Swansea University Another institution paid the OA fee 2024-03-25T14:38:08.4814744 2023-12-01T09:36:21.8255233 Faculty of Medicine, Health and Life Sciences Swansea University Medical School - Health Data Science Thamer Ba Dhafari 0000-0002-8653-7874 1 Alexander Pate 0000-0002-0849-3458 2 Narges Azadbakht 3 Rowena Bailey 4 Jim Rafferty 0000-0002-1667-7265 5 Farideh Jalali-najafabadi 6 Glen P. Martin 7 Abdelaali Hassaine 0000-0002-3270-1165 8 Ashley Akbari 0000-0003-0814-0801 9 Jane Lyons 10 Alan Watkins 0000-0003-3804-1943 11 Ronan Lyons 0000-0001-5225-000X 12 Niels Peek 0000-0002-6393-9969 13 65170__29624__d2fee00347324911b49f6aa7758671e5.pdf 65170.pdf 2024-03-05T08:56:22.0590070 Output 822721 application/pdf Version of Record true This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/ 4.0/). false eng https://creativecommons.org/licenses/by/4.0/ |
title |
A scoping review finds a growing trend in studies validating multimorbidity patterns and identifies five broad types of validation methods |
spellingShingle |
A scoping review finds a growing trend in studies validating multimorbidity patterns and identifies five broad types of validation methods Rowena Bailey Jim Rafferty Ashley Akbari Jane Lyons Alan Watkins Ronan Lyons |
title_short |
A scoping review finds a growing trend in studies validating multimorbidity patterns and identifies five broad types of validation methods |
title_full |
A scoping review finds a growing trend in studies validating multimorbidity patterns and identifies five broad types of validation methods |
title_fullStr |
A scoping review finds a growing trend in studies validating multimorbidity patterns and identifies five broad types of validation methods |
title_full_unstemmed |
A scoping review finds a growing trend in studies validating multimorbidity patterns and identifies five broad types of validation methods |
title_sort |
A scoping review finds a growing trend in studies validating multimorbidity patterns and identifies five broad types of validation methods |
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455e2c1e6193448f6269b9e72acaf865 52effe759a718bd36eb12cdd10fe1a09 aa1b025ec0243f708bb5eb0a93d6fb52 1b74fa5125a88451c52c45bcf20e0b47 81fc05c9333d9df41b041157437bcc2f 83efcf2a9dfcf8b55586999d3d152ac6 |
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455e2c1e6193448f6269b9e72acaf865_***_Rowena Bailey 52effe759a718bd36eb12cdd10fe1a09_***_Jim Rafferty aa1b025ec0243f708bb5eb0a93d6fb52_***_Ashley Akbari 1b74fa5125a88451c52c45bcf20e0b47_***_Jane Lyons 81fc05c9333d9df41b041157437bcc2f_***_Alan Watkins 83efcf2a9dfcf8b55586999d3d152ac6_***_Ronan Lyons |
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Rowena Bailey Jim Rafferty Ashley Akbari Jane Lyons Alan Watkins Ronan Lyons |
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Thamer Ba Dhafari Alexander Pate Narges Azadbakht Rowena Bailey Jim Rafferty Farideh Jalali-najafabadi Glen P. Martin Abdelaali Hassaine Ashley Akbari Jane Lyons Alan Watkins Ronan Lyons Niels Peek |
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Journal of Clinical Epidemiology |
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165 |
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111214 |
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10.1016/j.jclinepi.2023.11.004 |
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Elsevier BV |
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http://dx.doi.org/10.1016/j.jclinepi.2023.11.004 |
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description |
Objectives: Multimorbidity, the presence of two or more long-term conditions, is a growing public health concern. Many studies use analytical methods to discover multimorbidity patterns from data. We aimed to review approaches used in published literature to validate these patterns.Study design and setting: We systematically searched PubMed and Web of Science for studies published between July 2017 and July 2023 that used analytical methods to discover multimorbidity patterns.Results: Out of 31,617 studies returned by the searches, 172 were included. Of these, 111 studies (64%) conducted validation, the number of studies with validation increased from 53.13% (17 out of 32 studies) to 71.25% (57 out of 80 studies) in 2017-2019 to 2022-2023, respectively. Five types of validation were identified: assessing the association of multimorbidity patterns with clinical outcomes (n = 79), stability across subsamples (n = 26), clinical plausibility (n = 22), stability across methods (n = 7) and exploring common determinants (n = 2). Some studies used multiple types of validation.Conclusion: The number of studies conducting a validation of multimorbidity patterns is clearly increasing. The most popular validation approach is assessing the association of multimorbidity patterns with clinical outcomes. Methodological guidance on the validation of multimorbidity patterns is needed. |
published_date |
2024-01-01T14:29:39Z |
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11.048042 |