Combining endpoint and change data did not affect the summary standardised mean difference in pairwise and network meta-analyses: An empirical study in depression

Edoardo G. Ostinelli*, Orestis Efthimiou, Yan Luo, Clara Miguel, Eirini Karyotaki, Pim Cuijpers, Toshi A. Furukawa, Georgia Salanti, Andrea Cipriani

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

When studies use different scales to measure continuous outcomes, standardised mean differences (SMD) are required to meta-analyse the data. However, outcomes are often reported as endpoint or change from baseline scores. Combining corresponding SMDs can be problematic and available guidance advises against this practice. We aimed to examine the impact of combining the two types of SMD in meta-analyses of depression severity. We used individual participant data on pharmacological interventions (89 studies, 27,409 participants) and internet-delivered cognitive behavioural therapy (iCBT; 61 studies, 13,687 participants) for depression to compare endpoint and change from baseline SMDs at the study level. Next, we performed pairwise (PWMA) and network meta-analyses (NMA) using endpoint SMDs, change from baseline SMDs, or a mixture of the two. Study-specific SMDs calculated from endpoint and change from baseline data were largely similar, although for iCBT interventions 25% of the studies at 3 months were associated with important differences between study-specific SMDs (median 0.01, IQR −0.10, 0.13) especially in smaller trials with baseline imbalances. However, when pooled, the differences between endpoint and change SMDs were negligible. Pooling only the more favourable of the two SMDs did not materially affect meta-analyses, resulting in differences of pooled SMDs up to 0.05 and 0.13 in the pharmacological and iCBT datasets, respectively. Our findings have implications for meta-analyses in depression, where we showed that the choice between endpoint and change scores for estimating SMDs had immaterial impact on summary meta-analytic estimates. Future studies should replicate and extend our analyses to fields other than depression.

Original languageEnglish
Pages (from-to)758-768
Number of pages11
JournalResearch Synthesis Methods
Volume15
Issue number5
Early online date9 May 2024
DOIs
Publication statusPublished - Sept 2024

Bibliographical note

Publisher Copyright:
© 2024 The Authors. Research Synthesis Methods published by John Wiley & Sons Ltd.

Funding

Edoardo G. Ostinelli and Andrea Cipriani were supported by the National Institute for Health and Care Research (NIHR) (grant RP-2017-08-ST2-006), by the National Institute for Health Research (NIHR) Applied Research Collaboration Oxford and Thames Valley (ARC OxTV) at Oxford Health NHS Foundation Trust, by the National Institute for Health and Care Research Oxford Health Clinical Research Facility, and by the NIHR Oxford Health Biomedical Research Centre (grant BRC-1215-20005). Edoardo G. Ostinelli was supported by the Brasenose College Senior Hulme scholarship. Orestis Efthimiou was supported by project grant number 180083 from the Swiss National Science Foundation (SNSF). Georgia Salanti was supported by the Swiss National Science Foundation (grant/award number 179158). The views expressed are those of the authors and not necessarily those of the UK National Health Service, the NIHR, or the Department of Health and Social Care. Edoardo G. Ostinelli and Andrea Cipriani were supported by the National Institute for Health and Care Research (NIHR) (grant RP\u20102017\u201008\u2010ST2\u2010006), by the National Institute for Health Research (NIHR) Applied Research Collaboration Oxford and Thames Valley (ARC OxTV) at Oxford Health NHS Foundation Trust, by the National Institute for Health and Care Research Oxford Health Clinical Research Facility, and by the NIHR Oxford Health Biomedical Research Centre (grant BRC\u20101215\u201020005). Edoardo G. Ostinelli was supported by the Brasenose College Senior Hulme scholarship. Orestis Efthimiou was supported by project grant number 180083 from the Swiss National Science Foundation (SNSF). Georgia Salanti was supported by the Swiss National Science Foundation (grant/award number 179158). The views expressed are those of the authors and not necessarily those of the UK National Health Service, the NIHR, or the Department of Health and Social Care.

FundersFunder number
Australian Research Council
National Institute for Health and Care Research Oxford Health Clinical Research Facility
Applied Research Collaboration Oxford
National Health Service
Thames Valley
Brasenose College Senior Hulme
National Institute for Health and Care ResearchRP‐2017‐08‐ST2‐006
NIHR Oxford Biomedical Research CentreBRC‐1215‐20005
Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung180083, 179158

    Keywords

    • change
    • continuous outcome
    • depression
    • follow-up
    • meta-analysis
    • standardised mean difference

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