Radiomic assessment as a method for predicting tumor mutation burden (TMB) of bladder cancer patients: a feasibility study

Table 2 Multivariate Logistic regression using backward elimination strategy

Radiomic Features			Beta value	OR	95%CI OR	P value	AUC^a
log-sigma-1-0-mm-3D	glcm	Imc1	−1.24	0.29	0.10–0.82	0.019	0.637
log-sigma-2-5-mm-3D	glcm	MaximumProbability	1.14	3.13	1.34–7.33	0.009	0.638
wavelet-LHL	glcm	MCC	−1.02	0.36	0.16–0.82	0.015	0.690
wavelet-LHH	glszm	ZoneEntropy	1.56	4.74	1.70–13.20	0.003	0.661
wavelet-HLH	glszm	SizeZoneNonUniformityNormalized	1.23	3.43	1.45–8.13	0.005	0.696
wavelet-HHL	glcm	MCC	−0.80	0.45	0.18–1.12	0.086	0.644

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