1069. Psychometric Properties of the Symptoms of Infection with Coronavirus-19: A Patient-Reported Outcome Measure for COVID-19 Signs and Symptoms
Authors: Chan Eric K H , Stoddard Jeffrey , Sadoff Jerald , Liu Yan , van Dromme Ilse , Katz Eva G , Liu Yi-hsuan , McQuarrie Kelly 
Published: December 2022

Abstract

Background
The Symptoms of Infection with Coronavirus-19 (SIC), a patient reported outcome (PRO) measure, was developed to assess COVID-19 signs and symptoms. Qualitative and cross-sectional studies demonstrated its content validity and preliminary psychometric properties. This study provides additional evidence on the reliability, responsiveness, known-group validity, and meaningful change thresholds of the SIC using methods aligned with regulatory guidance and best practices.

Methods
Data were from ENSEMBLE-2, a multicenter, randomized, double-blind, placebo-controlled phase 3 trial to assess the efficacy and safety of Ad26.COV2.S for the prevention of SARS-CoV-2 infections in adults (aged 18+). The SIC was used in the trial to evaluate COVID-19 signs and symptoms and the Patient Global Impression of Severity (PGIS) was used as an anchor for validation. Intra-class correlations (ICCs) and Cronbach’s alphas were computed to evaluate the test-retest reliability and internal consistency, and analyses of variance (ANOVAs) were performed to assess the known-group validity of the SIC. Responsiveness was evaluated using PGIS as an anchor variable and a 1- or 2-point improvement in PGIS was used to estimate the meaningful change thresholds of the SIC.

Results
183 participants with polymerase chain reaction (PCR) confirmed moderate to severe/critical COVID-19 were included (mean ± SD age: 51.5 ± 14.8 y; female: 44%; White 65%). ICCs showed strong test-retest reliabilities for most SIC domains (.60 and above). The internal consistency reliability of the SIC had a Cronbach’s alpha &gt; .70 for all but one domain (Neurological). Statistically significant differences (p values &lt; 0.05) for the different PGIS severity levels were found for all but one domain (Sensory), supporting known-group validity. All domains showed responsiveness based on changes (improvement and worsening) in PGIS, supporting the ability of the SIC to detect changes in COVID-19 signs and symptoms. Based on mean changes in the PGIS, estimated meaningful change thresholds for SIC domains ranged from -.36 to -2.11.

Conclusion
These results, based on data from ENSEMBLE-2, build upon prior cross-sectional analyses and provide additional supportive psychometric evidence on the SIC. Support: Janssen Vaccines & Prevention B.V.

Disclosures
Eric K. H. Chan, PhD, Janssen Global Services, LLC: Employee|Janssen Pharmaceuticals: Stocks/Bonds Jeffrey Stoddard, MD, Janssen Pharmaceuticals: Employee|Janssen Pharmaceuticals: Stocks/Bonds Jerald Sadoff, MD, Janssen Vaccines & Prevention BV: Employee Yan Liu, PhD, Janssen Pharmaceuticals: Employee|Janssen Pharmaceuticals: Stocks/Bonds Ilse van Dromme, PhD, Janssen Pharmaceuticals: Employee|Janssen Pharmaceuticals: Stocks/Bonds Eva G. Katz, PhD, MPH, RD, Janssen Pharmaceuticals: Employee|Janssen Pharmaceuticals: Stocks/Bonds Yi-hsuan Liu, PhD, MS, RD, Janssen Pharmaceuticals: Employee|Janssen Pharmaceuticals: Stocks/Bonds Kelly McQuarrie, BSN, Janssen Pharmaceuticals: Employee|Janssen Pharmaceuticals: Stocks/Bonds.