Table 4.

Provisional Recommendations for Developing Evidence for People with Multimorbidity

1. Definition and Measurement of Comorbities and Multimorbidity Status

Identify, define, measure and routinely report the within-study prevalence of important and common comorbid conditions. As a general rule, this should also involve measuring and reporting summary metrics of multimorbidity.

Explicitly pre-specify the specific motivation for studying multimorbidity so that the most appropriate multimorbidity concept is measured.

Select a multimorbidity measurement instrument that best measures the most relevant aspect of multimorbidity for the research question of interest.

Based on specific motivation for studying multimorbidity, non-disease conditions should be considered.

Multimorbidity measurements should ideally be easily and reliably obtained in real world clinical practice.

Multimorbidity should be measured in ways that allow comparability of results across studies.

2. Multimorbidity-Related Effects on Study Design, Implementation and Analysis

Internal validity

Fully ascertain exposure to treatments (including onset, intensity and duration) and important multimorbidities with minimal bias and error.

Employ sound statistical methods, as well as external validation studies, to address treatment selection bias affecting internal validity.

Ascertain exposure to concomitant treatments and harms related to any treatments.

Design study procedures to avoid mis-diagnosis of outcomes in people with multimorbidity.

Pre-specify all likely treatment effect modifiers related to multimorbidity and implement study designs and procedures to deal with these.

Consider how multimorbidity will affect overall study power (especially outcome event rates) and whether study power should be calculated in light of important multimorbidities.

Design study to minimize losses to follow-up, especially in people with multimorbidity.

External validity

Study entry criteria should not explicitly or implicitly exclude people with important multimorbidity from trials unless necessary.

Design study procedures to recruit and retain people with important multimorbidity into trials.

Consider person-level and provider or environmental modifiers of treatment effect during study design and implementation, focusing on methods that will maximize applicability.

Monitor adherence to treatment rigorously to avoid misclassification according to multimorbidity status.

Consider distribution of competing risks in target populations and how it should be represented in study samples.

3. Heterogeneity of Treatment Effect

Identify and prioritize multimorbidity-related questions, obtaining expert clinical input where necessary.

Analyses should examine treatment effect modification across groups defined by important clusters of characteristics (e.g. by risk or by comorbidity burden), rather than only one-variable-at-a-time subgroup analysis.

Consider powering to support multimorbidity-related subgroup effects.

Consider stratification of randomization by important multimorbidity-related subgroups.

Consider multimorbidity-specific trials when indicated.

Collect relevant multimorbidity-related outcome data, particularly related to adverse events.

Define subgroups of interest for confirmatory, descriptive or exploratory analyses.

Subgroups for confirmatory analyses should be very few; fully pre-specified; explicitly justified; based on strong a priori pathophysiologic or empirical evidence of heterogeneity of treatment effects; adjusted for multiplicity if appropriate; and, always reported and labeled.