Methodological approach for determining the Minimal Important Difference and Minimal Important Change scores for the European Organisation for Research and Treatment of Cancer Head and Neck Cancer Module (EORTC QLQ-HN43) exemplified by the Swallowing scale

Purpose

The aim of this study was to explore what methods should be used to determine the minimal important difference (MID) and minimal important change (MIC) in scores for the European Organisation for Research and Treatment of Cancer Head and Neck Cancer Module, the EORTC QLQ-HN43.

Methods

In an international multi-centre study, patients with head and neck cancer completed the EORTC QLQ-HN43 before the onset of treatment (t1), three months after baseline (t2), and six months after baseline (t3). The methods explored for determining the MID were: (1) group comparisons based on performance status; (2) 0.5 and 0.3 standard deviation and standard error of the mean. The methods examined for the MIC were patients' subjective change ratings and receiver-operating characteristics (ROC) curves, predictive modelling, standard deviation, and standard error of the mean. The EORTC QLQ-HN43 Swallowing scale was used to investigate these methods.

Results

From 28 hospitals in 18 countries, 503 patients participated. Correlations with the performance status were |r|< 0.4 in 17 out of 19 scales; hence, performance status was regarded as an unsuitable anchor. The ROC approach yielded an implausible MIC and was also discarded. The remaining approaches worked well and delivered MID values ranging from 10 to 14; the MIC for deterioration ranged from 8 to 16 and the MIC for improvement from − 3 to − 14.

Conclusions

For determining MIDs of the remaining scales of the EORTC QLQ-HN43, we will omit comparisons of groups based on the Karnofsky Performance Score. Other external anchors are needed instead. Distribution-based methods worked well and will be applied as a starting strategy for analyses. For the calculation of MICs, subjective change ratings, predictive modelling, and standard-deviation based approaches are suitable methods whereas ROC analyses seem to be inappropriate.

Supplementary Information

The online version of this article (10.1007/s11136-021-02939-6) contains supplementary material, which is available to authorized users.

Graphical displays of patient-reported outcomes (PRO) for use in clinical practice: What makes a pro picture worth a thousand words?

Patient-reported outcomes (PROs) report patients' assessments of the impact of a health condition and its treatment, and can promote patient-centered care.

OBJECTIVES

To address the effectiveness of graphic display of PRO data in clinical practice by reviewing existing literature, and current recommendations, regarding graphic presentations of PROs.

METHODS

We performed an integrated literature review to identify themes and emerging principles guiding effective graphic display of PRO data. The findings were placed in the context of the literature informing graphical presentation of other clinical data.

RESULTS

Although a large body of literature informs graphical presentation of clinical data, only nine empirical studies addressed presentation of PROs. Four major themes emerged: many patients and most clinicians can accurately interpret some PRO graphs; interpretation accuracy, personal preference, and perceived level of understanding are sometimes discordant; patient age and education may predict PRO graph comprehension; patients tend to prefer simpler graphs than do clinicians.

CONCLUSIONS

Little empirical research specifically addresses graphic representation of PRO data. A single format may not work optimally for both clinicians and patients.

PRACTICE IMPLICATIONS

Patients and clinicians may or may not comprehend PRO data when graphically presented. Further research to determine best practices for presenting PROs optimally is needed.