METHODS: Clinico-pathological data from a previously treated cohort of 590 newly presenting PMD patients were reviewed and clinical outcomes categorized as disease free, persistent PMD or MT. Multiple logistic regression was used to predict the probability of MT in the cohort using age, gender, lesion type, site and incision biopsy histopathological diagnoses. Internal validation and calibration of the model was performed using the bootstrap method (n = 1000), and bias-corrected indices of model performance were computed.
RESULTS: Potentially malignant disorders were predominantly leukoplakias (79%), presenting most frequently at floor of mouth and lateral tongue sites (51%); 99 patients (17%) developed oral squamous cell carcinoma during the study period. The nomogram performed well when MT predictions were compared with patient outcome data, demonstrating good bias-corrected discrimination and calibration (Dxy = 0.58; C = 0.790), with a sensitivity of 87% and specificity 63%, and a positive predictive value of 32% and negative predictive value 96%.
CONCLUSION: The "Newcastle Nomogram" has been developed to predict the probability of MT in PMD, based on an internally validated statistical model. Based upon readily available and patient-specific clinico-pathological data, it provides clinicians with a pragmatic diagrammatic aid for clinical decision-making during diagnosis and management of PMD.