Eugenie Ng1, Thomas Law2, Eric C-H Tang1, Fiona N-Y Ho1, Michael C-F Tong1, Kathy Y-S Lee1. 1. Department of Otorhinolaryngology, Head and Neck Surgery, The Chinese University of Hong Kong & The Institute of Human Communicative Research, Shatin, Hong Kong, China; Department of Otorhinolaryngology, Head and Neck Surgery, Prince of Wales Hospital, Shatin, Hong Kong, China. 2. Department of Otorhinolaryngology, Head and Neck Surgery, The Chinese University of Hong Kong & The Institute of Human Communicative Research, Shatin, Hong Kong, China; Department of Otorhinolaryngology, Head and Neck Surgery, Prince of Wales Hospital, Shatin, Hong Kong, China. Electronic address: thomaslaw@ent.cuhk.edu.hk.
Abstract
BACKGROUND: Voice Handicap Index (VHI) has been used extensively in research and clinical settings. It has been suggested to be used as a diagnostic tool in the literature. However, little is known if it could be applied as a diagnostic tool to the Cantonese-speaking population. The study aims to establish cutoff points and the diagnostic accuracy for VHI-30 and VHI-10 to discriminate between Cantonese-speaking dysphonic and nondysphonic individuals. METHODS: Data from 256 adults from Hong Kong were extracted from a database at a local institution. There were a total of 91 nondysphonic individuals and 165 dysphonic individuals. Receiver operating characteristics curve analysis was conducted to establish cutoff points for VHI-30 and VHI-10. Diagnostic accuracy statistics such as sensitivity, specificity, positive, and negative predicted values (PPV and NPV) and likelihood ratios (LRs) were also reported. RESULTS: The dysphonic group scored higher than the nondysphonic group on the mean scores of both versions of VHI. Receiver operating characteristics curve analysis revealed a moderate to strong area under curve of 0.89 in both VHI-30 and VHI-10. A cutoff point of 18.5 point was yielded for VHI-30 (Sensitivity = 86.1%, Specificity = 81.3%, PPV = 89.3%, NPV = 76.3%, LR+ = 4.60, LR- = 0.17) and a cutoff point of 7.5 point was yielded for VHI-10 (Sensitivity = 80.6%, Specificity = 87.9%, PPV = 92.4%, NPV = 71.4%, LR+ = 6.66, LR- = 0.22). CONCLUSIONS: Both the Chinese VHI-30 and VHI-10 for Cantonese speakers showed promising diagnostic accuracy. VHI can be used as adjunct to clinical diagnosis and treatment outcome measures for voice disorders in the Cantonese-speaking population.
BACKGROUND: Voice Handicap Index (VHI) has been used extensively in research and clinical settings. It has been suggested to be used as a diagnostic tool in the literature. However, little is known if it could be applied as a diagnostic tool to the Cantonese-speaking population. The study aims to establish cutoff points and the diagnostic accuracy for VHI-30 and VHI-10 to discriminate between Cantonese-speaking dysphonic and nondysphonic individuals. METHODS: Data from 256 adults from Hong Kong were extracted from a database at a local institution. There were a total of 91 nondysphonic individuals and 165 dysphonic individuals. Receiver operating characteristics curve analysis was conducted to establish cutoff points for VHI-30 and VHI-10. Diagnostic accuracy statistics such as sensitivity, specificity, positive, and negative predicted values (PPV and NPV) and likelihood ratios (LRs) were also reported. RESULTS: The dysphonic group scored higher than the nondysphonic group on the mean scores of both versions of VHI. Receiver operating characteristics curve analysis revealed a moderate to strong area under curve of 0.89 in both VHI-30 and VHI-10. A cutoff point of 18.5 point was yielded for VHI-30 (Sensitivity = 86.1%, Specificity = 81.3%, PPV = 89.3%, NPV = 76.3%, LR+ = 4.60, LR- = 0.17) and a cutoff point of 7.5 point was yielded for VHI-10 (Sensitivity = 80.6%, Specificity = 87.9%, PPV = 92.4%, NPV = 71.4%, LR+ = 6.66, LR- = 0.22). CONCLUSIONS: Both the Chinese VHI-30 and VHI-10 for Cantonese speakers showed promising diagnostic accuracy. VHI can be used as adjunct to clinical diagnosis and treatment outcome measures for voice disorders in the Cantonese-speaking population.
Authors: Beata Miaśkiewicz; Elżbieta Gos; Małgorzata Dębińska; Aleksandra Panasiewicz-Wosik; Dorota Kapustka; Katarzyna Nikiel; Elżbieta Włodarczyk; Anna Domeracka-Kołodziej; Paulina Krasnodębska; Agata Szkiełkowska Journal: Int J Environ Res Public Health Date: 2022-08-29 Impact factor: 4.614