Prospective evaluation of patient reported swallow function with the Functional Assessment of Cancer Therapy (FACT), MD Anderson Dysphagia Inventory (MDADI) and the Sydney Swallow Questionnaire (SSQ) in head and neck cancer patients.

OBJECTIVES

The Functional Assessment of Cancer Therapy (FACT) instrument is comprised of a group of related and overlapping quality of life (QoL) questionnaires including a core general form, head and neck cancer (HNC)-specific items, and an expert-selected index (FACT-HNSI). Understanding how these relate to more HNC-specific instruments such as the MD Anderson Dysphagia Inventory (MDADI) and Sydney Swallow Questionnaire (SSQ) is vital for guiding their use in clinical trials.

MATERIALS AND

METHODS

HNC patients concurrently completed MDADI, SSQ, and FACT questionnaires at radiation oncology clinic visits (2015-2016). Spearman correlation coefficients were calculated between each FACT instrument and MDADI or SSQ. Unsupervised k-means cluster analyses were performed to identify clusters of similar QoL responses. Principal component analysis (PCA) identified the degree of variability explained by each instrument.

RESULTS

We identified 631 instances (363 patients) where the questionnaires were completed concurrently. Correlations between the various FACT measures and SSQ or MDADI were all significant (p < 0.001), but FACT HNC-specific subscale and FACT-HNSI showed the strongest correlation with MDADI and SSQ. Clustering identified 3 distinct groups of responses when combining instruments either pairwise or three-way. PCA revealed that MDADI and FACT HNC-specific subscale provide similar and likely redundant information.

CONCLUSION

FACT HNC-subscale and FACT-HNSI may be preferable over other FACT measures for use in clinical trials where patient-reported swallow function is evaluated. MDADI and FACT provide similar insights into HNC patient QoL while SSQ provides additional, complementary information which could serve to better stratify patients into groups with high, medium, and low QoL outcomes.