Secondary analysis of data on comorbidity/multimorbidity: a call for papers.

Despite the high proportion and growing number of people with comorbidity/multimorbidity, clinical trials often exclude this group, leading to a limited evidence base to guide policy and practice for these individuals [1–5]. This evidence gap can potentially be addressed by secondary analysis of studies that were not originally designed to specifically examine comorbidity/ multimorbidity, but have collected information from participants on co-occurring conditions. For example, secondary data analysis from randomized controlled trials may shed light on whether there is a differential impact of interventions on people with comorbidity/ multimorbidity. Furthermore, data regarding comorbidity/ multimorbidity can often be obtained from registration networks or administrative data sets. These types of data sets can address a range of epidemiological research questions, such as