Advertisement

Validation of the Cepstral Spectral Index of Dysphonia (CSID) as a Screening Tool for Voice Disorders: Development of Clinical Cutoff Scores

Published:September 07, 2015DOI:https://doi.org/10.1016/j.jvoice.2015.04.009

      Summary

      Objectives

      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.

      Methodology

      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 (ie, 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.

      Key Words

      To read this article in full you will need to make a payment

      Purchase one-time access:

      Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online access
      One-time access price info
      • For academic or personal research use, select 'Academic and Personal'
      • For corporate R&D use, select 'Corporate R&D Professionals'

      Subscribe:

      Subscribe to Journal of Voice
      Already a print subscriber? Claim online access
      Already an online subscriber? Sign in
      Institutional Access: Sign in to ScienceDirect

      References

        • Roy N.
        • Merrill R.M.
        • Thibeault S.
        • Gray S.D.
        • Smith E.M.
        Voice disorders in teachers and the general population: effects on work performance, attendance, and future career choices.
        J Speech Lang Hear Res. 2004; 47: 542-551
        • Roy N.
        • Merrill R.M.
        • Thibeault S.
        • Parsa R.A.
        • Gray S.D.
        • Smith E.M.
        Prevalence of voice disorders in teachers and the general population.
        J Speech Lang Hear Res. 2004; 47: 281-293
        • Verdolini K.
        • Ramig L.O.
        Review: occupational risks for voice problems.
        Logoped Phoniatr Vocol. 2001; 26: 37-46
        • Bossuyt P.M.
        The STARD statement for reporting studies of diagnostic accuracy: explanation and elaboration.
        Clin Chem. 2003; 49: 7-18
        • Sackett D.L.
        • Rosenberg W.M.
        • Gray J.A.
        • Haynes R.B.
        • Richardson W.S.
        Evidence based medicine: what it is and what it isn't.
        BMJ. 1996; 312: 71-72
        • Roy N.
        • Barkmeier-Kraemer J.
        • Eadie T.
        • Sivasankar M.P.
        • Mehta D.
        • Paul D.
        • Hillman R.
        Evidence-based clinical voice assessment: a systematic review.
        Am J Speech Lang Pathol. 2013; 22: 212-226
        • Schwartz S.R.
        • Cohen S.M.
        • Dailey S.H.
        • et al.
        Clinical practice guideline: hoarseness (dysphonia).
        Otolaryngol Head Neck Surg. 2009; 141: S1-S31
        • Jacobson B.
        • Johnson A.
        • Grywalski C.
        • et al.
        The voice handicap index (VHI): development and validation.
        Am J Speech Lang Pathol. 1997; 6: 66-70
        • Ma E.P.
        • Yiu E.M.
        Voice activity and participation profile: assessing the impact of voice disorders on daily activities.
        J Speech Lang Hear Res. 2001; 44: 511-524
        • Rosen C.A.
        • Lee A.S.
        • Osborne J.
        • Zullo T.
        • Murry T.
        Development and validation of the voice handicap index-10.
        Laryngoscope. 2004; 114: 1549-1556
        • Hogikyan N.D.
        • Sethuraman G.
        Validation of an instrument to measure voice-related quality of life (V-RQOL).
        J Voice. 1999; 13: 557-569
        • Deary I.J.
        • Wilson J.A.
        • Carding P.N.
        • MacKenzie K.
        VoiSS: a patient-derived Voice Symptom Scale.
        J Psychosom Res. 2003; 54: 483-489
        • Kupfer R.A.
        • Hogikyan E.M.
        • Hogikyan N.D.
        Establishment of a normative database for the Voice-Related Quality of Life (V-RQOL) measure.
        J Voice. 2014; 28: 449-451
        • G Nichols B.
        • Varadarajan V.
        • Bock J.M.
        • Blumin J.H.
        Dysphonia in nursing home and assisted living residents: prevalence and association with frailty.
        J Voice. 2015; 29: 79-82
        • Fisher B.A.
        • Dolan K.
        • Hastings L.
        • McClinton C.
        • Taylor P.C.
        Prevalence of subjective voice impairment in rheumatoid arthritis.
        Clin Rheumatol. 2008; 27: 1441-1443
        • Speyer R.
        • Speyer I.
        • Heijnen M.A.
        Prevalence and relative risk of dysphonia in rheumatoid arthritis.
        J Voice. 2008; 22: 232-237
        • Sanz L.
        • Sistiaga J.A.
        • Lara A.J.
        • Cuende E.
        • García-Alcántara F.
        • Rivera T.
        The prevalence of dysphonia, its association with immunomediated diseases and correlation with biochemical markers.
        J Voice. 2012; 26: 148-153
        • Liu Z.W.
        • Masterson L.M.
        • Srouji I.A.
        • Musonda P.
        • Scott D.G.
        Voice symptoms in patients with autoimmune disease: a cross-sectional epidemiological study.
        Otolaryngol Head Neck Surg. 2012; 147: 1108-1113
        • Eskenazi L.
        • Childers D.G.
        • Hicks D.M.
        Acoustic correlates of vocal quality.
        J Speech Hear Res. 1990; 33: 298-306
        • Fex S.
        Perceptual evaluation.
        J Voice. 1992; 6: 155-158
        • Awan S.
        The Voice Diagnostic Protocol: A Practical Guide to the Diagnosis of Voice Disorders.
        Pro-Ed Inc, Austin, TX2001
        • Awan S.
        • Roy N.
        Toward the development of an objective index of dysphonia severity: a four-factor acoustic model.
        Clin Linguist Phon. 2006; 20: 35-49
        • Maryn Y.
        • Roy N.
        • De Bodt M.
        • Van Cauwenberge P.
        • Corthals P.
        Acoustic measurement of overall voice quality: a meta-analysis.
        J Acoust Soc Am. 2009; 126: 2619-2634
        • Awan S.
        • Roy N.
        • Jetté M.
        • Meltzner G.
        • Hillman R.
        Quantifying dysphonia severity using a spectral/cepstral-based acoustic index: comparisons with auditory-perceptual judgements from the CAPE-V.
        Clin Linguist Phon. 2010; 24: 742-758
        • Awan S.
        • Roy N.
        Acoustic prediction of voice type in women with functional dysphonia.
        J Voice. 2005; 19: 268-282
        • Awan S.
        • Roy N.
        • Dromey C.
        Estimating dysphonia severity in continuous speech: application of a multi-parameter spectral/cepstral model.
        Clin Linguist Phon. 2009; 23: 825-841
        • Peterson E.A.
        • Roy N.
        • Awan S.N.
        • Merrill R.M.
        • Banks R.
        • Tanner K.
        Toward validation of the cepstral spectral index of dysphonia (CSID) as an objective treatment outcomes measure.
        J Voice. 2013; 27: 401-410
        • Awan S.
        • Solomon N.
        • Helou L.
        • Stojadinovic A.
        Spectral-cepstral estimation of dysphonia severity: external validation.
        Ann Otol Rhinol Laryngol. 2013; 122: 40-48
        • Hillenbrand J.
        • Houde R.
        Acoustic correlates of breathy vocal quality: dysphonic voices and continuous speech.
        J Speech Hear Res. 1996; 39: 311-321
        • Heman-Ackah Y.
        • Michael D.
        • Goding G.
        The relationship between cepstral peak prominence and selected parameters of dysphonia.
        J Voice. 2002; 16: 20-27
        • Maryn Y.
        • Corthals P.
        • Van Cauwenberge P.
        • Roy N.
        • De Bodt M.
        Toward improved ecological validity in the acoustic measurement of overall voice quality: combining continuous speech and sustained vowels.
        J Voice. 2010; 24: 540-555
        • Behrman A.
        • Rutledge J.
        • Hembree A.
        • Sheridan S.
        Vocal hygiene education, voice production therapy, and the role of patient adherence: a treatment effectiveness study in women with phonotrauma.
        J Speech Lang Hear Res. 2008; 51: 350-366
        • Fairbanks G.
        Voice and Articulation Drillbook.
        2nd ed. Harper & Row, New York1960
        • Kempster G.B.
        • Gerratt B.R.
        • Verdolini Abbott K.
        • Barkmeier-Kraemer J.
        • Hillman R.E.
        Consensus auditory-perceptual evaluation of voice: development of a standardized clinical protocol.
        Am J Speech Lang Pathol. 2009; 18: 124-132
        • Field A.
        Discovering Statistics Using SPSS.
        3rd ed. Sage Publications Ltd, London2009
        • Portney L.
        • Watkins M.
        Foundations of Clinical Research, Applications to Practice.
        2nd ed. Prentice-Hall, Upper Saddle River2000
        • Glaser A.N.
        High-Yield Biostatistics, Epidemiology, and Public Health.
        4th ed. Lippincott Williams & Wilkins, Baltimore2014: 168
        • Metz C.E.
        Basic principles of ROC analysis.
        Semin Nucl Med. 1978; 8: 283-298
        • El Khouli R.H.
        • Macura K.J.
        • Barker P.B.
        • Habba M.R.
        • Jacobs M.A.
        • Bluemke D.A.
        Relationship of temporal resolution to diagnostic performance for dynamic contrast enhanced MRI of the breast.
        J Magn Reson Imaging. 2009; 30: 999-1004
        • Kraemer H.
        • Morgan G.
        • Leech N.
        • Gliner J.
        • Vaske J.
        • Harmon R.
        Measures of clinical significance.
        J Am Acad Child Adolesc Psychiatry. 2003; 42: 1524-1529
        • Dollaghan C.
        Appraising diagnostic evidence.
        in: Dollaghan C. The Handbook for Evidence-Based Practice in Communication Disorders. Brookes, Baltimore, MD2007
        • Attia J.
        Moving beyond sensitivity and specificity: using likelihood ratios to help interpret diagnostic tests.
        Aust Prescr. 2003; 26: 111-113
        • Youden W.
        Index for rating diagnostic tests.
        Cancer. 1950; 3: 32-35
        • Bewick V.
        • Cheek L.
        • Ball J.
        Statistics review 13: receiver operating characteristic curves.
        Crit Care. 2004; 8: 508-512
        • Fluss R.
        • Faraggi D.
        • Reiser B.
        Estimation of the Youden Index and its associated cutoff point.
        Biom J. 2005; 47: 458-472
        • DeLong E.
        • DeLong D.
        • Clarke-Pearson D.
        Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach.
        Biometrics. 1988; 44: 837-845
        • Burns R.
        • Burns R.
        Business Research Methods and Statistics Using SPSS.
        Sage Publications Ltd, London, U.K.2008
        • Hanley J.
        • McNeil B.
        A method of comparing the areas under receiver operating characteristic curves derived from the same cases.
        Radiology. 1983; 148: 839-843
        • Pepe M.
        The Statistical Evaluation of Medical Tests for Classification and Prediction.
        Oxford University Press, Oxford, UK2003
        • Gillespie A.I.
        • Dastolfo C.
        • Magid N.
        • Gartner-Schmidt J.
        Acoustic analysis of four common voice diagnoses: moving toward disorder-specific assessment.
        J Voice. 2014; 28: 582-588
        • Lowell S.Y.
        • Colton R.H.
        • Kelley R.T.
        • Mizia S.A.
        Predictive value and discriminant capacity of cepstral- and spectral-based measures during continuous speech.
        J Voice. 2013; 27: 393-400
        • Roy N.
        • Mazin A.
        • Awan S.N.
        Automated acoustic analysis of task dependency in adductor spasmodic dysphonia versus muscle tension dysphonia.
        Laryngoscope. 2014; 124: 718-724
        • Awan S.
        • Helou L.
        • Stojadinovic A.
        • Solomon N.
        Tracking voice change after thyroidectomy: application of spectral/cepstral analyses.
        Clin Linguist Phon. 2011; 25: 302-320
        • Awan S.N.
        • Roy N.
        • Cohen S.M.
        Exploring the relationship between spectral and cepstral measures of voice and the Voice Handicap Index (VHI).
        J Voice. 2014; 28: 430-439
        • Kreiman J.
        • Gerratt B.
        • Kempster G.
        • Erman A.
        • Berke G.
        Perceptual evaluation of voice quality: review, tutorial, and a framework for future research.
        J Speech Hear Res. 1993; 36: 21-40
        • Kreiman J.
        • Gerratt B.R.
        • Ito M.
        When and why listeners disagree in voice quality assessment tasks.
        J Acoust Soc Am. 2007; 122: 2354-2364
        • Rosenthal A.L.
        • Lowell S.Y.
        • Colton R.H.
        Aerodynamic and acoustic features of vocal effort.
        J Voice. 2014; 28: 144-153
      1. Awan S, Chan D, Hillman J, Kramer S. A Multi-Dimensional Examination of Strained Voice Quality. Paper Presented at the American Speech-Language-Hearing Association Convention. 2014. Orlando, FL.

        • Tanner K.
        • Roy N.
        • Ash A.
        • Buder E.H.
        Spectral moments of the long-term average spectrum: sensitive indices of voice change after therapy?.
        J Voice. 2005; 19: 211-222
        • Baken R.J.
        The aged voice: a new hypothesis.
        J Voice. 2005; 19: 317-325
        • Orlikoff R.
        The relationship of age and cardiovascular health to certain acoustic characteristics of male voices.
        J Speech Lang Hear Res. 1990; 33: 450
        • Wuyts F.L.
        • De Bodt M.S.
        • Molenberghs G.
        • et al.
        The dysphonia severity index: an objective measure of vocal quality based on a multiparameter approach.
        J Speech Lang Hear Res. 2000; 43: 796-809
        • Zraick R.
        • Birdwell K.
        • Smith-Olinde L.
        The effect of speaking sample duration on determination of habitual pitch.
        J Voice. 2005; 19: 197-201
        • Niebudek-Bogusz E.
        • Kuzańska A.
        • Woznicka E.
        • Sliwinska-Kowalska M.
        Assessment of the voice handicap index as a screening tool in dysphonic patients.
        Folia Phoniatr Logop. 2011; 63: 269-272
        • Cantarella G.
        • Iofrida E.
        • Boria P.
        • et al.
        Ambulatory phonation monitoring in a sample of 92 call center operators.
        J Voice. 2014; 28: 393.e1-393.e6
        • Speyer R.
        • Wieneke G.H.
        • Dejonckere P.H.
        Self-assessment of voice therapy for chronic dysphonia.
        Clin Otolaryngol Allied Sci. 2004; 29: 66-74
        • Van Gogh C.D.
        • Mahieu H.F.
        • Kuik D.J.
        • Rinkel R.N.
        • Langendijk J.A.
        • Verdonck-de Leeuw I.M.
        Voice in early glottic cancer compared to benign voice pathology.
        Eur Arch Otorhinolaryngol. 2007; 264: 1033-1038
        • Hamdan A.L.
        • Farhat S.
        • Saadeh R.
        • El-Dahouk I.
        • Sibai A.
        • Yamout B.
        Voice-related quality of life in patients with multiple sclerosis.
        Autoimmune Dis. 2012; 2012: 143813
        • Solomon N.P.
        • Helou L.B.
        • Henry L.R.
        • Howard R.S.
        • Coppit G.
        • Shaha A.R.
        • Stojadinovic A.
        Utility of the voice handicap index as an indicator of postthyroidectomy voice dysfunction.
        J Voice. 2013; 27: 348-354
        • Moradi N.
        • Pourshahbaz A.
        • Soltani M.
        • Javadipour S.
        Cutoff point at voice handicap index used to screen voice disorders among persian speakers.
        J Voice. 2013; 27: 130.e1-130.e5
        • Ohlsson A.-C.
        • Dotevall H.
        Voice handicap index in Swedish.
        Logoped Phoniatr Vocol. 2009; 34: 60-66