Can Methods Developed for Interpreting Group-level Patient-reported Outcome Data be Applied to Individual Patient Management?

Abstract

Background: 

Patient-reported outcome (PRO) data may be used at 2 levels: to evaluate impacts of disease and treatment aggregated across individuals (group-level) and to screen/monitor individual patients to inform their management (individual-level). For PRO data to be useful at either level, we need to understand their clinical relevance.

Purpose: 

To provide clarity on whether and how methods historically developed to interpret group-based PRO research results might be applied in clinical settings to enable PRO data from individual patients to inform their clinical management and decision-making.

Methods: 

We first differentiate PRO-based decision-making required at group versus individual levels. We then summarize established group-based approaches to interpretation (anchor-based and distribution based), and more recent methods that draw on item calibrations and qualitative research methods. We then assess the applicability of these methods to individual patient data and individual-level decision-making.

Findings: 

Group-based methods provide a range of thresholds that are useful in clinical care: some provide screening thresholds for patients who need additional clinical assessment and/or intervention, some provide thresholds for classifying an individual’s level of severity of symptoms or problems with function, and others provide thresholds for meaningful change when monitoring symptoms and functioning over time during or after interventions. Availability of established cut-points for screening and symptom severity, and normative/reference values, may play into choice of PRO measures for use in clinical care. Translatability of thresholds for meaningful change is more problematic because of the greater reliability needed at the individual-level versus group-level, but group-based methods may provide lower bound estimates. Caution is needed to set thresholds above bounds of measurement error to avoid “false-positive changes” triggering unwarranted alerts and action in clinic.

Conclusions: 

While there are some challenges in applying available methods for interpreting group-based PRO results to individual patient data and clinical care—including myriad contextual factors that may influence an individual patient’s management and decision-making—they provide a useful starting point, and should be used pragmatically.