Table 2.

Predictive models for risk stratification in upper-tract urothelial carcinoma

Author	Purpose	Variables included	Accuracy
Zamboni et al.[44]	Prediction of non-organ confined disease	Tumor grade, tumor architecture + tumor location	NOC-UTUC: 76.6%
Favaretto et al.[19]	Prediction of muscle-invasive and non-organ confined disease	Local invasion on imaging + ureteroscopy high grade	≥pT2 disease: 71% NOC-UTUC: 70%
Petros et al.[56]	Prediction of high-risk non-organ-confined upper-tract urothelial carcinoma	Tumor grade, tumor architecture, clinical stage +hemoglobin	NOC-UTUC: 82%
Rouprêt et al.[57]	Prediction of CSS after radical nephroureterectomy	Age, tumor stage, lymph node involvement, tumor architecture + lymphovascular invasion	CSS: 80%
Cha et al.[58]	Prediction of RFS and CSS after radical nephroureterectomy	Prediction of RFS: Tumor stage, lymph node involvement, tumor architecture, lymphovascular invasion + concomitant CIS Prediction of CSS: Tumor stage, lymph node involvement, tumor architecture + lymphovascular invasion	RFS: 76.8% CSS: 81.5%
Yates et al.[59]	Prediction of CSS after radical nephroureterectomy	Tumor stage, lymph node involvement tumor grade, age + tumor location	CSS: 78%
Seisen et al.[60]	Prediction of CSS after radical nephroureterectomy in patients with localized and/or locally advanced disease	Age, tumor stage, tumor grade, tumor location, tumor architecture + lymphovascular invasion	CSS: 81%
Krabbe et al.[61]	RFS in patients with High grade disease	Age, tumor stage, lymph node involvement + tumor architecture	RFS: 77% (external validation cohort)

RFS: Recurrence-free survival; CSS: cancer-specific survival; NOC-UTUC: non-organ confined upper tract urothelial carcinoma