Advertisement

Individualized five-year risk assessment for oral premalignant lesion progression to cancer

Published:November 22, 2016DOI:https://doi.org/10.1016/j.oooo.2016.11.004

      Objective

      The standard of care for premalignant lesion risk assessment is dysplasia grading by histopathology. With significant overlap between dysplasia grades and high inter- and intraobserver variations, histopathology dysplasia grading alone is not a useful prognostic tool. Our aim is to investigate whether a method for quantitatively assessing S100A7, a prognostic biomarker, using image analysis can better predict clinical outcome in cases with oral dysplasia.

      Study Design

      Using the Visiopharm image analysis system, we analyzed a cohort of 150 oral biopsy samples to build and test Straticyte, a model for individualized assessment of the 5-year risk of progression of oral precancerous lesions to invasive squamous cell carcinomas.

      Results

      Straticyte classified lesions more accurately than histopathological dysplasia grading for risk to progression to cancer over the following 5 years. The sensitivity of low-risk versus intermediate- and high-risk Straticyte groups was 95% compared to 75% for mild versus moderate and severe dysplasia. Furthermore, the negative predictive value for low-risk versus intermediate- and high-risk Straticyte groups was 78% compared to 59% for mild versus moderate and severe dysplasia.

      Conclusion

      By quantitatively assessing S100A7, Straticyte better defines the risk for developing oral squamous cell carcinoma than histopathological dysplasia grading alone.
      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'

      References

        • Siegel R.L.
        • Miller K.D.
        • Jemal A.
        Cancer statistics, 2016.
        CA Cancer J Clin. 2016; 66: 7-30
        • Ferlay J.
        • Soerjomataram I.
        • Dikshit R.
        • et al.
        Cancer incidence and mortality worldwide: sources, methods and major patterns in GLOBOCAN 2012.
        Int J Cancer. 2015; 136: E359-386
        • Hawkins R.J.
        • Wang E.E.L.
        • Leake J.L.
        Preventitive health care, 1999 update: prevention of oral cancer mortality. The Canadian Task Force on Preventitive Health Care.
        J Can Dent Assoc. 1999; 65: 617
        • Lingen M.W.
        • Kalmar J.R.
        • Karrison T.
        • Speight P.M.
        Critical evaluation of diagnostic aids for the detection of oral cancer.
        Oral Oncol. 2008; 44: 10-22
        • Jacobson J.J.
        • Epstein J.B.
        • Eichmiller F.C.
        • et al.
        The cost burden of oral, oral pharyngeal, and salivary gland cancers in three groups: commercial insurance, Medicare, and Medicaid.
        Head Neck Oncol. 2012; 4: 15
        • Ogbureke K.U.E.
        Overview of oral cancer. Oral Cancer.
        Int Tech, 2012 (Available at:) (Accessed March 1, 2016)
        • Avon S.L.
        • Klieb H.B.
        Oral soft-tissue biopsy: an overview.
        J Can Dent Assoc. 2012; 78: c75
        • Poh C.F.
        • Ng S.
        • Berean K.W.
        • Williams P.M.
        • Rosin M.P.
        • Zhang L.
        Biopsy and histopathologic diagnosis of oral premalignant and malignant lesions.
        J Can Dent Assoc. 2008; 74: 283-288
        • McCullough M.J.
        • Prasad G.
        • Farah C.S.
        Oral mucosal malignancy and potentially malignant lesions: an update on the epidemiology, risk factors, diagnosis and management.
        Aust Dent J. 2010; 55: 61-65
        • Weir J.C.
        • Davenport W.D.
        • Skinner R.L.
        A diagnostics and epidemiologic survey of 15,783 oral lesions.
        J Am Dent Assoc. 1987; 115: 439-442
        • Hsue S.S.
        • Wang W.C.
        • Chen C.H.
        • Lin C.C.
        • Chen Y.K.
        • Lin L.M.
        Malignant transformation in 1458 patients with potentially malignant oral mucosal disorders: a follow-up study based in a Taiwanese hospital.
        J Oral Pathol Med. 2007; 36: 25-29
        • Mehanna H.M.
        • Rattay T.
        • Smith J.
        • McConkey C.C.
        Treatment and follow-up of oral dysplasia: a systematic review and meta-analysis.
        Head Neck. 2009; 31: 1600-1609
        • Dost F.
        • Le Cao K.
        • Ford P.J.
        • Ades C.
        • Farah C.S.
        Malignant transformation of oral epithelial dysplasia: a real-world evaluation of histopathologic grading.
        Oral Surg Oral Med Oral Pathol Oral Radiol. 2014; 117: 343-352
        • Fleskens S.
        • Slootweg P.
        Grading systems in head and neck dysplasia: their prognostic value, weaknesses and utility.
        Head Neck Oncol. 2009; 1: 11
        • Speight P.M.
        Update on oral epithelial dysplasia and progression to cancer.
        Head Neck Pathol. 2007; 1: 61-66
        • Warnakulasuriya S.
        • Reibel J.
        • Bouquot J.
        • Dabelsteen E.
        Oral epithelial dysplasia classification systems: predictive value, utility, weaknesses and scope for improvement.
        J Oral Pathol Med. 2008; 37: 127-133
        • Jullien J.A.
        • Zakrzewska J.M.
        • Downer M.C.
        • Speight P.M.
        Attendance and compliance at an oral cancer screening programme in a general medical practice.
        Eur J Cancer B Oral Oncol. 1995; 31 B: 202-206
        • Yusof Z.Y.
        • Netuveli G.
        • Ramli A.S.
        • Sheiham A.
        Is opportunistic oral cancer screening by dentists feasible? an analysis of the patterns of dental attendance of a nationally representative sample over 10 years.
        Oral Health Prev Dent. 2006; 4: 165-171
        • Amagasa T.
        • Yamashiro M.
        • Uzawa N.
        Oral premalignant lesions: from a clinical perspective.
        Int J Clin Oncol. 2011; 16: 5-14
        • Schaaij-Visser T.B.
        • Bremmer J.F.
        • Braakhuis B.J.
        • et al.
        Evaluation of cornulin, keratin 4, keratin 13 expression and grade of dysplasia for predicting malignant progression of oral leukoplakia.
        Oral Oncol. 2010; 46: 123-127
        • Warnakulasuriya S.
        • Ariyawardana A.
        Malignant transformation of oral leukoplakia: a systematic review of observational studies.
        J Oral Pathol Med. 2016; 45: 115-166
        • Warnakulasuriya S.
        • Kovacevic T.
        • Madden P.
        • et al.
        Factors predicting malignant transformation in oral potentially malignant disorders among patients accrued over a 10-year period in South East England.
        J Oral Pathol Med. 2011; 40: 677-683
        • Kaur J.
        • Matta A.
        • Kak I.
        • et al.
        S100A7 overexpression is a predictive marker for high risk of malignant transformation in oral dysplasia.
        Int J Cancer. 2014; 134: 1379-1388
        • Liu H.
        • Liu X.W.
        • Dong G.
        • et al.
        P16 Methylation as an early predictor for cancer development from oral epithelial dysplasia: a double-blind multicentre prospective study.
        EBioMedicine. 2015; 2: 432-437
        • Pattani K.M.
        • Zhang Z.
        • Demokan S.
        • et al.
        Endothelin receptor type B gene promoter hypermethylation in salivary rinses is independently associated with risk of oral cavity cancer and premalignancy.
        Cancer Prev Res (Phila). 2010; 3: 1093-1103
        • Sperandio M.
        • Brown A.L.
        • Lock C.
        • et al.
        Predictive value of dysplasia grading and DNA ploidy in malignant transformation of oral potentially malignant disorders.
        Cancer Prev Res (Phila). 2013; 6: 822-831
        • Xiao X.
        • Shi L.
        • Li H.
        • Song Y.
        • Liu W.
        • Zhou Z.
        DNA content status using brush biopsy with image cytometry correlated with staging of oral leukoplakia: a preliminary study.
        Oral Oncol. 2015; 51: 59-63
        • Zhang L.
        • Poh C.F.
        • Williams M.
        • et al.
        Loss of heterozygosity (LOH) profiles: validated risk predictors for progression to oral cancer.
        Cancer Prev Res (Phila). 2012; 5: 1081-1089
        • Ralhan R.
        • Desouza L.V.
        • Matta A.
        • et al.
        Discovery and verification of head-and-neck cancer biomarkers by differential protein expression analysis using iTRAQ labeling, multidimensional liquid chromatography, and tandem mass spectrometry.
        Mol Cell Proteomics. 2008; 7: 1162-1173
        • Tripathi S.C.
        • Matta A.
        • Kaur J.
        • et al.
        Nuclear S100 A7 is associated with poor prognosis in head and neck cancer.
        PLoS One. 2010; 5: e11939
        • Hanley J.A.
        • McNeil B.J.
        The meaning and use of the area under a receiver operating characteristic (ROC) curve.
        Radiology. 1982; 143: 29-36
        • Harrell Jr., F.E.
        Regression Modeling Strategies.
        1st ed. Springer-Verlag, New York, NY2001
        • Aalen O.
        Nonparametric inference for a family of counting processes.
        Ann Stat. 1978; 6: 701-726
        • Brewslow N.E.
        • Day N.E.
        Statistical Methods in Cancer Research. Vol. 2: The Design and Analysis of Cohort Studies.
        International Agency for Research on Cancer, Oxford University Press, New York1987
        • Nelson W.
        Theory and applications of hazard plotting for censored failure data.
        Technometrics. 1972; 14: 945-966
        • Rich J.T.
        • Neely J.G.
        • Paniello R.C.
        • Voelker C.C.
        • Nussenbaum B.
        • Wang E.W.
        A practical guide to understanding Kaplan-Meier curves.
        Otolaryngol Head Neck Surg. 2010; 143: 331-336
        • Tilakaratne W.M.
        • Sherriff M.
        • Morgan P.R.
        • Odell E.W.
        Grading oral epithelial dysplasia: analysis of individual features.
        J Oral Pathol Med. 2011; 40: 533-540
        • Lingen M.W.
        Screening for oral premalignancy and cancer: what platform and which biomarkers?.
        Cancer Prev Res (Phila). 2010; 3: 1056-1059
        • Lalkhen A.
        • McCluskey A.
        Clinical tests: sensitivity and specificity.
        Contin Educ Anaesth Crit Care Pain. 2008; 8: 221-223
        • Parikh R.
        • Mathai A.
        • Parikh S.
        Chandra Sekhar G, Thomas R. Understanding and using sensitivity, specificity and predictive values.
        Indian J Ophthalmol. 2008; 56: 45-50
        • Akobeng A.K.
        Understanding diagnostic tests 1: sensitivity, specificity and predictive values.
        Acta Paediatr. 2007; 96: 338-341
        • Eusebi P.
        Diagnostic accuracy measures.
        Cerebrovasc Dis. 2013; 36: 267-272
        • Raslich M.A.
        • Markert R.J.
        • Stutes S.A.
        Selecting and interpreting diagnostic tests.
        Biochem Med. 2007; 17: 151-161
        • Shariff J.A.
        • Zavras A.I.
        Malignant transformation rate in patients presenting oral epithelial dysplasia: systematic review and meta-analysis.
        J Oral Dis. 2015; 2015: 10
        • Tripepi G.
        • Jager K.J.
        • Dekker F.W.
        • Zoccali C.
        Statistical methods for the assessment of prognostic biomarkers (Part I): discrimination.
        Nephrol Dial Transplant. 2010; 25: 1399-1401