title: Validation of the Cepstral Spectral Index of Dysphonia (CSID) as a Screening Tool for Voice Disorders: Development of Clinical Cutoff Scores.
abstract: OBJECTIVE
  The purposes of this study were to (1) evaluate the performance of the Cepstral Spectral Index of Dysphonia (CSID--a multivariate estimate of dysphonia severity) as a potential screening tool for voice disorder identification and (2) identify potential clinical cutoff scores to classify voice-disordered cases versus controls.
  
  
  METHODS
  Subjects were 332 men and women (116 men, 216 women) comprised of subjects who presented to a physician with a voice-related complaint and a group of non-voice-related control subjects. Voice-disordered cases versus controls were initially defined via three reference standards: (1) auditory-perceptual judgment (dysphonia +/-); (2) Voice Handicap Index (VHI) score (VHI +/-); and (3) laryngoscopic description (laryngoscopic +/-). Speech samples were analyzed using the Analysis of Dysphonia in Speech and Voice program. Cepstral and spectral measures were combined into a CSID multivariate formula which estimated dysphonia severity for Rainbow Passage samples (i.e., the CSIDR). The ability of the CSIDR to accurately classify cases versus controls in relation to each reference standard was evaluated via a combination of logistic regression and receiver operating characteristic (ROC) analyses.
  
  
  RESULTS
  The ability of the CSIDR to discriminate between cases and controls was represented by the "area under the ROC curve" (AUC). ROC classification of dysphonia-positive cases versus controls resulted in a strong AUC = 0.85. A CSIDR cutoff of ≈24 achieved the best balance between sensitivity and specificity, whereas a more liberal cutoff score of ≈19 resulted in higher sensitivity while maintaining respectable specificity which may be preferred for screening purposes. Weaker but adequate AUCs = 0.75 and 0.73 were observed for the classification of VHI-positive and laryngoscopic-positive cases versus controls, respectively. Logistic regression analyses indicated that subject age may be a significant covariate in the discrimination of dysphonia-positive and VHI-positive cases versus controls.
  
  
  CONCLUSIONS
  The CSIDR can provide a strong level of accuracy for the classification of voice-disordered cases versus controls, particularly when auditory-perceptual judgment is used as the reference standard. Although users often focus on a cutoff score that achieves a balance between sensitivity and specificity, more liberal cutoffs for screening purposes versus conservative cutoffs when cost or risk of further evaluation is deemed to be high should also be considered.
authors.affiliation: Department of Audiology and Speech Pathology, Bloomsburg University of Pennsylvania, Bloomsburg, Pennsylvania. Electronic address: sawan@bloomu.edu.
authors.forename: Shaheen N
authors.initials: SN
authors.lastname: Awan
authors.affiliation: Department of Communication Sciences and Disorders, The University of Utah, Salt Lake City, Utah.
authors.forename: Nelson
authors.initials: N
authors.lastname: Roy
authors.affiliation: Department of Mathematics and Computer Science, Bloomsburg University of Pennsylvania, Bloomsburg, Pennsylvania.
authors.forename: Dong
authors.initials: D
authors.lastname: Zhang
authors.affiliation: Division of Otolaryngology-Head and Neck Surgery, Duke Voice Care Center, Duke University Medical Center, Durham, North Carolina.
authors.forename: Seth M
authors.initials: SM
authors.lastname: Cohen
mesh_terms: D000162:Acoustics; D000328:Adult; D000368:Aged; D000465:Algorithms; D019540:Area Under Curve; D016022:Case-Control Studies; D016009:Chi-Square Distribution; D004185:Disability Evaluation; D055154:Dysphonia / Q000175:diagnosis* / Q000503:physiopathology; D005260:Female; D006801:Humans; D007600:Judgment; D007828:Laryngoscopy; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D011237:Predictive Value of Tests; D012372:ROC Curve; D015203:Reproducibility of Results; D012720:Severity of Illness Index; D012815:Signal Processing, Computer-Assisted; D013018:Sound Spectrography; D013061:Speech Acoustics; D013067:Speech Perception; D013068:Speech Production Measurement; D011795:Surveys and Questionnaires; D014833:Voice Quality
keywords: Cepstral analysis; Cepstrum; Sensitivity; Specificity; Voice disorders; Voice screening