Modeling the cumulative genetic risk for multiple sclerosis from genome-wide association data

Table 2 Estimated cumulative genetic risk using 12 validated multiple sclerosis genes^a

	Probability of being a MS case
	25% quartile	Median	75% quartile
Case (N = 2,062)	0.228	0.379	0.589
Control (N = 6,360)	0.072	0.134	0.268

Classification results in the discovery dataset were: classification sensitivity, 35.1%; classification specificity, 93.5%; classification accuracy rate, 63.8%; model fit analysis, P = 0.007 (Hosmer-Lemeshow goodness-of-fit test [30] was implemented to assess 'lack of fit' of the selected model; P > 0.05 indicates that there is no evidence of a lack of fit of the selected model). ^aHLA-DRB1, CD58, CLEC16a, EVI5, IL2Ra, IRF8, RGS1, CD226, TNFRSF1a, CD6, GPC5 and IL7R.

ISSN: 1756-994X