Table 4.

Univariate Analysis for OS and FFS in the Current Series (n: 152 Patients) and Logistic Regression Model for Failure Prediction in the Training Set of Patients (n: 103)

Protein	Reference category	Univariate analysis for FFS (Cox regression)				Multivariate analysis for failure protein, RNA-expression-based model and model integrating IPI; (logistic regression)
		P	RR	95% CI		Beta in PEB model	Beta in PEB + IPI model	Difference between models
				Lower	Higher
IPI	IPI (0–2)	0.000	3.257	2.121	5.001		3.260
cyclin E	<80%	0.000	3.293	1.839	5.894	3.035	2.477	0.184
CDK1	>80%	0.029	2.281	1.090	4.771	2.650	2.975	−0.123
SKP2	>80%	0.019	3.999	1.261	12.683	2.457	2.329	0.052
EBER	−	0.086	1.898	0.913	3.945	2.249	2.569	−0.142
MUM1	<80%	0.071	0.065	0.409	1.037	1.483	1.758	−0.185
CDK2	<50%	0.114	0.623	0.347	1.120	0.964	0.739	0.233
Bcl-6	>50%	0.040	1.747	1.027	2.972	0.937	0.655	0.301
Rb-P	>80%	0.117	1.648	0.882	3.078	0.646	1.037	−0.391
p21	−	0.001	3.042	1.601	5.780
cyclin B1	>50%	0.094	1.869	0.899	3.883
cyclin A	>50%	>0.2
MDM2	−	0.097	1.446	0.936	2.234
Rb	>80%	0.192	1.342	0.863	2.088
CD38	<80%	0.188	1.369	0.858	2.184
CD138	<80%	0.090	1.882	0.906	3.907
Oct_2*	+	0.015	4.270	1.325	13.757
BOB1*	+	0.003	8.836	2.074	37.657
EMA*	−	0.040	2.891	1.052	7.948
CD95	−	>0.2
Bax	−	0.037	3.428	1.080	10.879
Bcl-2	<50%	0.015	1.740	1.114	2.719

^*, <5 values in one category; −, no data available. 

PEB, protein-expression-based; RR, relative risk. 

Specific weight (beta) of each variable for predicting failure in the protein and RNA-expression-based model, compared with values for model integrating the IPI. Differences were calculated as (beta1-beta2)/beta1.