How robust are findings of pairwise and network meta-analysis in the presence of missing participant outcome data?
© 2021. The Author(s)..
BACKGROUND: To investigate the prevalence of robust conclusions in systematic reviews addressing missing (participant) outcome data via a novel framework of sensitivity analyses and examine the agreement with the current sensitivity analysis standards.
METHODS: We performed an empirical study on systematic reviews with two or more interventions. Pairwise meta-analyses (PMA) and network meta-analyses (NMA) were identified from empirical studies on the reporting and handling of missing outcome data in systematic reviews. PMAs with at least three studies and NMAs with at least three interventions on one primary outcome were considered eligible. We applied Bayesian methods to obtain the summary effect estimates whilst modelling missing outcome data under the missing-at-random assumption and different assumptions about the missingness mechanism in the compared interventions. The odds ratio in the logarithmic scale was considered for the binary outcomes and the standardised mean difference for the continuous outcomes. We calculated the proportion of primary analyses with robust and frail conclusions, quantified by our proposed metric, the robustness index (RI), and current sensitivity analysis standards. Cohen's kappa statistic was used to measure the agreement between the conclusions derived by the RI and the current sensitivity analysis standards.
RESULTS: One hundred eight PMAs and 34 NMAs were considered. When studies with a substantial number of missing outcome data dominated the analyses, the number of frail conclusions increased. The RI indicated that 59% of the analyses failed to demonstrate robustness compared to 39% when the current sensitivity analysis standards were employed. Comparing the RI with the current sensitivity analysis standards revealed that two in five analyses yielded contradictory conclusions concerning the robustness of the primary analysis results.
CONCLUSIONS: Compared with the current sensitivity analysis standards, the RI offers an explicit definition of similar results and does not unduly rely on statistical significance. Hence, it may safeguard against possible spurious conclusions regarding the robustness of the primary analysis results.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2021 |
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| Erschienen: |
2021 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:19 |
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| Enthalten in: |
BMC medicine - 19(2021), 1 vom: 21. Dez., Seite 323 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Spineli, Loukia M [VerfasserIn] |
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| Links: |
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| Themen: |
Bayesian analysis |
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| Anmerkungen: |
Date Completed 24.01.2022 Date Revised 24.01.2022 published: Electronic Citation Status MEDLINE |
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| doi: |
10.1186/s12916-021-02195-y |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM334663113 |
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| 245 | 1 | 0 | |a How robust are findings of pairwise and network meta-analysis in the presence of missing participant outcome data? |
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| 500 | |a Date Revised 24.01.2022 | ||
| 500 | |a published: Electronic | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a © 2021. The Author(s). | ||
| 520 | |a BACKGROUND: To investigate the prevalence of robust conclusions in systematic reviews addressing missing (participant) outcome data via a novel framework of sensitivity analyses and examine the agreement with the current sensitivity analysis standards | ||
| 520 | |a METHODS: We performed an empirical study on systematic reviews with two or more interventions. Pairwise meta-analyses (PMA) and network meta-analyses (NMA) were identified from empirical studies on the reporting and handling of missing outcome data in systematic reviews. PMAs with at least three studies and NMAs with at least three interventions on one primary outcome were considered eligible. We applied Bayesian methods to obtain the summary effect estimates whilst modelling missing outcome data under the missing-at-random assumption and different assumptions about the missingness mechanism in the compared interventions. The odds ratio in the logarithmic scale was considered for the binary outcomes and the standardised mean difference for the continuous outcomes. We calculated the proportion of primary analyses with robust and frail conclusions, quantified by our proposed metric, the robustness index (RI), and current sensitivity analysis standards. Cohen's kappa statistic was used to measure the agreement between the conclusions derived by the RI and the current sensitivity analysis standards | ||
| 520 | |a RESULTS: One hundred eight PMAs and 34 NMAs were considered. When studies with a substantial number of missing outcome data dominated the analyses, the number of frail conclusions increased. The RI indicated that 59% of the analyses failed to demonstrate robustness compared to 39% when the current sensitivity analysis standards were employed. Comparing the RI with the current sensitivity analysis standards revealed that two in five analyses yielded contradictory conclusions concerning the robustness of the primary analysis results | ||
| 520 | |a CONCLUSIONS: Compared with the current sensitivity analysis standards, the RI offers an explicit definition of similar results and does not unduly rely on statistical significance. Hence, it may safeguard against possible spurious conclusions regarding the robustness of the primary analysis results | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Meta-Analysis | |
| 650 | 4 | |a Research Support, Non-U.S. Gov't | |
| 650 | 4 | |a Bayesian analysis | |
| 650 | 4 | |a Missing outcome data | |
| 650 | 4 | |a Pattern-mixture model | |
| 650 | 4 | |a Robust conclusions | |
| 650 | 4 | |a Sensitivity analysis | |
| 650 | 4 | |a Systematic reviews | |
| 700 | 1 | |a Kalyvas, Chrysostomos |e verfasserin |4 aut | |
| 700 | 1 | |a Papadimitropoulou, Katerina |e verfasserin |4 aut | |
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