Use of Bayes rule and MIB-1 proliferation index to discriminate Spitz nevus from malignant melanoma.
Differentiating Spitz nevus from malignant melanoma is difficult and controversial. Despite helpful lists of differential diagnostic features, uncertainty about the diagnosis often provokes some to stain the tumor for MIB-1 antibody to Ki-67 and measure the proliferation index (PI) of the tumor. Of the many reports about MIB-1 PI in Spitz nevi and melanoma, none have consolidated the information to provide guidelines for the predictive probability that a lesion is a Spitz nevus, given that the MIB-1 PI falls into a certain interval. The present study used previously published data and exponential and gamma probability density functions to model statistical distributions of PI, respectively, in Spitz nevi and melanomas and Bayes rule to estimate the predictive probability that a lesion is a Spitz nevus, given an observed PI. Results indicate that PIs more than 10% favor a melanoma diagnosis and PIs less than 2%, Spitz nevus. PI values between 2% and 10% yield various predictive values for Spitz nevus, depending on the a priori probability that the lesion is a Spitz nevus. The algorithm tabulates guidelines for the predictive probabilities of Spitz nevus given an observed PI.
Laboratory Medicine, Veterans Affairs Medical Center, Durham, NC 27705, USA.
Robin T
RT
Vollmer
D001499:Bayes Theorem; D002455:Cell Division; D003937:Diagnosis, Differential; D006801:Humans; D019394:Ki-67 Antigen / Q000032:analysis*; D008545:Melanoma / Q000175:diagnosis / Q000473:pathology*; D008962:Models, Theoretical; D018332:Nevus, Epithelioid and Spindle Cell / Q000175:diagnosis / Q000473:pathology*; D011336:Probability
D019394:Ki-67 Antigen