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Title:Handling of missing component information for common composite score outcomes used in axial spondyloarthritis research when complete-case analysis is unbiased
Authors:ID Polysopoulos, Christos (Author)
ID Georgiadis, Stylianos (Author)
ID Midtbøll Ørnbjerg, Lykke (Author)
ID Scherer, Almut (Author)
ID Di Giuseppe, Daniela (Author)
ID Lund Hetland, Merete (Author)
ID Nissen, Michael John (Author)
ID Jones, Gareth T. (Author)
ID Glintborg, Bente (Author)
ID Gitte Loft, Anne (Author)
ID Perdan-Pirkmajer, Katja (Author)
ID Rotar, Žiga (Author), et al.
Files:.pdf PDF - Presentation file, download (1,65 MB)
MD5: 7F9F2E28AD62152DC033804F26B104FC
 
URL URL - Source URL, visit https://bmcmedresmethodol.biomedcentral.com/articles/10.1186/s12874-025-02515-3
 
Language:English
Typology:1.01 - Original Scientific Article
Organization:Logo UKC LJ - Ljubljana University Medical Centre
Abstract:Background: Observational data on composite scores often comes with missing component information. When a complete-case (CC) analysis of composite scores is unbiased, preferable approaches of dealing with missing component information should also be unbiased and provide a more precise estimate. We assessed the performance of several methods compared to CC analysis in estimating the means of common composite scores used in axial spondyloarthritis research. Methods: Individual mean imputation (IMI), the modified formula method (MF), overall mean imputation (OMI), and multiple imputation of missing component values (MI) were assessed either analytically or by means of simulations from available data collected across Europe. Their performance in estimating the means of the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), the Bath Ankylosing Spondylitis Functional Index (BASFI), and the Ankylosing Spondylitis Disease Activity Score based on C-reactive protein (ASDAS-CRP) in cases where component information was set missing completely at random was compared to the CC approach based on bias, variance, and coverage. Results: Like the MF method, IMI uses a modified formula for observations with missing components resulting in modified composite scores. In the case of an unbiased CC approach, these two methods yielded representative samples of the distribution arising from a mixture of the original and modified composite scores, which, however, could not be considered the same as the distribution of the original score. The IMI and MF method are, thus, intrinsically biased. OMI provided an unbiased mean but displayed a complex dependence structure among observations that, if not accounted for, resulted in severe coverage issues. MI improved precision compared to CC and gave unbiased means and proper coverage as long as the extent of missingness was not too large. Conclusions: MI of missing component values was the only method found successful in retaining CC's unbiasedness and in providing increased precision for estimating the means of BASDAI, BASFI, and ASDAS-CRP. However, since MI is susceptible to incorrect implementation and its performance may become questionable with increasing missingness, we consider the implementation of an error-free CC approach a valid and valuable option.
Keywords:axial spondyloarthritis, complete-case analysis, composite score, missing components, multiple imputation, aksialni spondiloartritis, analiza celotnega primera, sestavljena ocena, manjkajoče komponente, večkratna imputacija
Publication status:Published
Publication version:Version of Record
Year of publishing:2025
Number of pages:str. 1-16
Numbering:Vol. 25, no. 1, [article no.] 55
PID:20.500.12556/DiRROS-27871 New window
UDC:616-002
ISSN on article:1471-2288
DOI:10.1186/s12874-025-02515-3 New window
COBISS.SI-ID:229878275 New window
Note:Nasl. z nasl. zaslona; Opis vira z dne 21. 3. 2025;
Publication date in DiRROS:26.02.2026
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Downloads:56
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Record is a part of a journal

Title:BMC medical research methodology
Shortened title:BMC Med Res Methodol
Publisher:BioMed Central
ISSN:1471-2288
COBISS.SI-ID:2441236 New window

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Link:http://creativecommons.org/licenses/by-nc-nd/4.0/
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