Table 5

Probit or ordered probit regression model for multivariate analysis

VariableMarginal effectP
CD38 30% or more, n = 102 Mutation −0.022 .008 
 Male 0.168 .017 
 Age at diagnosis 0.006 .026 
 GC 0.027 .531 
 GG 0.037 .666 
ZAP-70 20% or more, n = 59 Mutation −0.048 <.001 
 GC + GG 0.194 .010 
 Trisomy 12 0.230 .010 
Splenomegaly, n = 51 Deletion 11 0.420 .004 
 GG 0.531 .005 
 Male 0.140 .015 
 Trisomy 12 0.224 .022 
 Deletion 17 0.197 .065 
Richter syndrome, n = 30 GC 0.124 .007 
 GG 0.306 .040 
Lines of treatment, n = 67 Trisomy 12 0.078 .004 
 Deletion 11 0.148 .001 
 Deletion 17 0.112 .005 
 Mutation −0.007 .014 
VariableMarginal effectP
CD38 30% or more, n = 102 Mutation −0.022 .008 
 Male 0.168 .017 
 Age at diagnosis 0.006 .026 
 GC 0.027 .531 
 GG 0.037 .666 
ZAP-70 20% or more, n = 59 Mutation −0.048 <.001 
 GC + GG 0.194 .010 
 Trisomy 12 0.230 .010 
Splenomegaly, n = 51 Deletion 11 0.420 .004 
 GG 0.531 .005 
 Male 0.140 .015 
 Trisomy 12 0.224 .022 
 Deletion 17 0.197 .065 
Richter syndrome, n = 30 GC 0.124 .007 
 GG 0.306 .040 
Lines of treatment, n = 67 Trisomy 12 0.078 .004 
 Deletion 11 0.148 .001 
 Deletion 17 0.112 .005 
 Mutation −0.007 .014 

Marginal effect measures the variation in probability generated by a unit increase in the considered variable.

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