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Initial psychometric evaluation of the Adult Symptom Severity and Impacts Scale (PKU-SSIS) using interim data from the OPAL study

Biochemical/Metabolic and Therapeutics
  • Primary Categories:
    • Metabolic Genetics
  • Secondary Categories:
    • Metabolic Genetics
Introduction:
Phenylketonuria (PKU) is a genetic disorder characterized by the inability to metabolize phenylalanine (Phe), leading to neurological deficits if untreated. Traditional approaches to assessing PKU symptom burden may not fully capture the broad impacts on patients’ lives, with either generic tools being used or condition-specific tools that lack emphasis on the cognitive and psychological impact. To address this, the PKU-SSIS was developed, a patient-reported outcome measure to assess the severity and impacts of PKU symptoms across multiple domains. Content validity of the PKU-SSIS has been established, but there remains a need to quantitatively assess the psychometric properties. This study uses an interim data cut of OPAL, a Phase 4 multicenter observational study evaluating the real-world outcomes of pegvaliase in people with PKU, to assess the initial psychometric performance of the adult PKU-SSIS.

Methods:
The psychometric properties of the PKU-SSIS were evaluated using data from OPAL (December 2022). The 22-item PKU-SSIS was administered at baseline, Week 24, Week 48, and Week 96.

Item completion and compliance rates over time were assessed, evaluating participant engagement and data consistency. Baseline item distribution was analyzed by response category. Internal consistency was evaluated by examining Pearson’s-R correlations between items across all timepoints.

Convergent validity was assessed by correlating PKU-SSIS responses with established outcome measures capturing logically related health concepts, such as the PKU-Quality of Life (PKU-QoL) for PKU-specific symptoms and impacts, the Quality of Life Enjoyment and Satisfaction Questionnaire-Short Form (QLES-Q-SF), the EQ-5D for overall health status, and patient global impression scales (PGI-S/C) for symptom severity and change. Correlations determined how well PKU-SSIS scores aligned with related measures assessing similar symptom burdens and impacts.

Results:
The sample size at baseline consisted of 45 participants. Completion rates were consistently high across all time points, where 98% of participants had a PKU-SSIS total score at baseline and 100% at follow-up, indicating strong participant engagement and reliable data collection. Item distribution at baseline revealed a wide range of responses, with total scores ranging from 6.82 to 72.72 on the 0-100 scale, reflecting variability in symptom severity and impacts reported. This range suggests that the PKU-SSIS can distinguish varying symptom burden across individuals.

Item-level correlations within the PKU-SSIS supported internal consistency, with the majority (85%) of inter-item correlations being moderate (r>0.2), and a substantial proportion (38%) considered high (r>0.5). This suggests that items measure coherent aspects of symptom severity and impact, supporting the reliability of the scale.

Convergent validity was supported through moderate to strong correlations between the PKU-SSIS total score and related outcome measures.  The PKU-SSIS showed strong positive correlations with the PKU-QoL General Health subscale (r = 0.42, p < 0.001) and negative correlation with the QLES-Q-SF total score (r = -0.60, p < 0.001), indicating that the PKU-SSIS effectively captures key aspects of patient quality of life related to PKU symptoms. The PGI-S (r = -0.41, p < 0.001) and PGI-C (r = -0.40, p = 0.001) also showed significant negative correlations, further supporting the validity of the PKU-SSIS in capturing the impact of PKU symptoms on patient-reported outcomes. All correlations were in the expected direction, with higher symptom burden associated with lower quality of life and functioning.

Conclusion:
These findings provide initial evidence that the adult PKU-SSIS is a valid and reliable tool for assessing the symptom severity and impact of PKU on patients' lives. A psychometric evaluation with a larger sample size is recommended to further establish the psychometric properties of the PKU-SSIS, such as establishing a meaningful change threshold. The initial psychometric performance reinforces the potential of the PKU-SSIS as a valuable tool for measuring the effectiveness of treatments in PKU.

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