Article type
Year
Abstract
Background: The results of subgroup analyses may have a significant impact on clinical and public health decision-making. How often cancer individual participant data meta-analyses (IPDMAs) prespecify subgroup analyses, conduct planned subgroup analyses, and use daft (across-trial interaction alone), deluded (within-trial and across-trial interactions combined), or deft (within-trial interaction alone) approach to assess the treatment-subgroup interactions remain unclear.
Objectives: This study aimed to explore the pre-specification and conduct of subgroup analyses in cancer IPDMAs.
Methods: We searched PubMed, Embase.com, Cochrane Library, and Web of Science to identify IPDMAs of randomized controlled trials evaluating intervention effects for cancer. We evaluated how often cancer IPDMAs prespecify subgroup analyses and statistical approaches for examining treatment-subgroup interactions and handling continuous subgroup variables.
Results: We included 89 IPDMAs, of which 41 (46.1%) reported a statistically significant treatment-subgroup interaction (p-value < 0.05) in at least one subgroup analysis. Forty-seven (52.8%) IPDMAs prespecified methods for conducting subgroup analyses and the remaining 42 (47.2%) did not prespecify subgroup analyses. Of the 47 IPDMAs prespecified subgroup analyses, 19 performed the planned subgroup analyses, 21 added subgroup analyses, 7 reduced subgroup analyses. Eighty IPDMAs examined treatment-subgroup interactions, but 72 IPDMAs did not provide enough information to determine whether an appropriate approach that avoided aggregation bias was used. Eighty-five IPDMAs that used continuous variables in subgroup analyses categorized continuous variables and only one IPDMA examined non-linear relationships.
Conclusions: Many cancer IPDMAs did not prespecify subgroup analyses, nor did they fully perform planned subgroup analyses. Lack of details for the test of treatment-subgroup interactions and examination of non-linear interactions was suboptimal.
Patient, public, and/or healthcare consumer involvement: NA.
Objectives: This study aimed to explore the pre-specification and conduct of subgroup analyses in cancer IPDMAs.
Methods: We searched PubMed, Embase.com, Cochrane Library, and Web of Science to identify IPDMAs of randomized controlled trials evaluating intervention effects for cancer. We evaluated how often cancer IPDMAs prespecify subgroup analyses and statistical approaches for examining treatment-subgroup interactions and handling continuous subgroup variables.
Results: We included 89 IPDMAs, of which 41 (46.1%) reported a statistically significant treatment-subgroup interaction (p-value < 0.05) in at least one subgroup analysis. Forty-seven (52.8%) IPDMAs prespecified methods for conducting subgroup analyses and the remaining 42 (47.2%) did not prespecify subgroup analyses. Of the 47 IPDMAs prespecified subgroup analyses, 19 performed the planned subgroup analyses, 21 added subgroup analyses, 7 reduced subgroup analyses. Eighty IPDMAs examined treatment-subgroup interactions, but 72 IPDMAs did not provide enough information to determine whether an appropriate approach that avoided aggregation bias was used. Eighty-five IPDMAs that used continuous variables in subgroup analyses categorized continuous variables and only one IPDMA examined non-linear relationships.
Conclusions: Many cancer IPDMAs did not prespecify subgroup analyses, nor did they fully perform planned subgroup analyses. Lack of details for the test of treatment-subgroup interactions and examination of non-linear interactions was suboptimal.
Patient, public, and/or healthcare consumer involvement: NA.