Hmmm Bayesian methods using likelihood ratios to update age related odds of PD... where have I heard that approach before?? Nonetheless very important to formalise this approach and I think these criteria will be used widely...
Mov Disord. 2015 Oct;30(12):1600-11. doi: 10.1002/mds.26431.
Berg D, Postuma RB, Adler CH, Bloem BR, Chan P, Dubois B, Gasser T, Goetz CG, Halliday G, Joseph L, Lang AE, Liepelt-Scarfone I, Litvan I, Marek K, Obeso J, Oertel W, Olanow CW, Poewe W, Stern M, Deuschl G.
This article describes research criteria and probability methodology for the diagnosis of prodromal PD. Prodromal disease refers to the stage wherein early symptoms or signs of PD neurodegeneration are present, but classic clinical diagnosis based on fully evolved motor parkinsonism is not yet possible. Given the lack of clear neuroprotective/disease-modifying therapy for prodromal PD, these criteria were developed for research purposes only. The criteria are based upon the likelihood of prodromal disease being present with probable prodromal PD defined as ≥80% certainty. Certainty estimates rely upon calculation of an individual's risk of having prodromal PD, using a Bayesian naïve classifier. In this methodology, a previous probability of prodromal disease is delineated based upon age. Then, the probability of prodromal PD is calculated by adding diagnostic information, expressed as likelihood ratios. This diagnostic information combines estimates of background risk (from environmental risk factors and genetic findings) and results of diagnostic marker testing. In order to be included, diagnostic markers had to have prospective evidence documenting ability to predict clinical PD. They include motor and nonmotor clinical symptoms, clinical signs, and ancillary diagnostic tests. These criteria represent a first step in the formal delineation of early stages of PD and will require constant updating as more information becomes available. © 2015 International Parkinson and Movement Disorder Society.
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