TY - JOUR
T1 - A cytomics-on-a-chip platform and diagnostic model stratifies risk for oral lichenoid conditions
AU - McRae, Michael P.
AU - Srinivasan Rajsri, Kritika
AU - Ross Kerr, A.
AU - Vigneswaran, Nadarajah
AU - Redding, Spencer W.
AU - Janal, Malvin
AU - Kang, Stella K.
AU - Palomo, Leena
AU - Christodoulides, Nicolaos J.
AU - Singh, Meena
AU - Johnston, Jeffery
AU - McDevitt, John T.
N1 - Publisher Copyright:
© 2024
PY - 2024/7
Y1 - 2024/7
N2 - Objective: A small fraction of oral lichenoid conditions (OLC) have potential for malignant transformation. Distinguishing OLCs from other oral potentially malignant disorders (OPMDs) can help prevent unnecessary concern or testing, but accurate identification by nonexpert clinicians is challenging due to overlapping clinical features. In this study, the authors developed a 'cytomics-on-a-chip' tool and integrated predictive model for aiding the identification of OLCs. Study Design: All study subjects underwent both scalpel biopsy for histopathology and brush cytology. A predictive model and OLC Index comprising clinical, demographic, and cytologic features was generated to discriminate between subjects with lichenoid (OLC+) (N = 94) and nonlichenoid (OLC−) (N = 237) histologic features in a population with OPMDs. Results: The OLC Index discriminated OLC+ and OLC− subjects with area under the curve (AUC) of 0.76. Diagnostic accuracy of the OLC Index was not significantly different from expert clinician impressions, with AUC of 0.81 (P = .0704). Percent agreement was comparable across all raters, with 83.4% between expert clinicians and histopathology, 78.3% between OLC Index and expert clinician, and 77.3% between OLC Index and histopathology. Conclusions: The cytomics-on-a-chip tool and integrated diagnostic model have the potential to facilitate both the triage and diagnosis of patients presenting with OPMDs and OLCs.
AB - Objective: A small fraction of oral lichenoid conditions (OLC) have potential for malignant transformation. Distinguishing OLCs from other oral potentially malignant disorders (OPMDs) can help prevent unnecessary concern or testing, but accurate identification by nonexpert clinicians is challenging due to overlapping clinical features. In this study, the authors developed a 'cytomics-on-a-chip' tool and integrated predictive model for aiding the identification of OLCs. Study Design: All study subjects underwent both scalpel biopsy for histopathology and brush cytology. A predictive model and OLC Index comprising clinical, demographic, and cytologic features was generated to discriminate between subjects with lichenoid (OLC+) (N = 94) and nonlichenoid (OLC−) (N = 237) histologic features in a population with OPMDs. Results: The OLC Index discriminated OLC+ and OLC− subjects with area under the curve (AUC) of 0.76. Diagnostic accuracy of the OLC Index was not significantly different from expert clinician impressions, with AUC of 0.81 (P = .0704). Percent agreement was comparable across all raters, with 83.4% between expert clinicians and histopathology, 78.3% between OLC Index and expert clinician, and 77.3% between OLC Index and histopathology. Conclusions: The cytomics-on-a-chip tool and integrated diagnostic model have the potential to facilitate both the triage and diagnosis of patients presenting with OPMDs and OLCs.
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U2 - 10.1016/j.oooo.2024.04.003
DO - 10.1016/j.oooo.2024.04.003
M3 - Article
C2 - 38755071
AN - SCOPUS:85193221054
SN - 2212-4403
VL - 138
SP - 88
EP - 98
JO - Oral Surgery, Oral Medicine, Oral Pathology and Oral Radiology
JF - Oral Surgery, Oral Medicine, Oral Pathology and Oral Radiology
IS - 1
ER -