. Author manuscript; available in PMC: 2021 Mar 5.

Published in final edited form as: J Urol. 2020 Sep 10;205(2):434–440. doi: 10.1097/JU.0000000000001355

Table 2.

Performance of models based on existing prediction tools with and without additional patient-reported or claims-based health measures

Models	Covariates	AIC^&	Pseudo R²^{^}	LR Test	DF	AUC^#
Cho model	Base model: Age, Race/Ethnicity, NCI Comorbidity	9188.72	0.09	304.68	8	0.749
Cho model	Base model + Overall Health + Smoking	9115.30	0.11	386.09^**	12	0.753
Daskivich model	Base Model: Age, Race/Ethnicity, Primary Treatment, PSA, Gleason Score, Cancer Stage, PCCI	9115.09	0.12	400.31	19	0.783
Daskivich model	Base Model + Overall Health + Smoking	9043.33	0.14	480.07^**	23	0.796
Hoffman model	Base Model: Age, Race/Ethnicity, Overall Health	9184.58	0.10	310.81	9	0.738
Hoffman model	Base Model + NCI Comorbidity + Frailty Indicator Count	9117.34	0.11	388.06^**	14	0.744

^{^}

Pseudo R² = 1 - e^-(LRT/n); higher value is better.

AUC, time-dependent AUC at year 10 after diagnosis.

^**

LR test with P-value <0.001 compared to original model.

AIC, smaller value is better.