Table 2 Basic characteristics of included studies for quantitative analysis (clinical nomograms)
Author (publication year) | Country | TRIPOD style | No | EPE rate | Whole-gland vs. side-specific | Nomogram name | Clinical variables |
|---|---|---|---|---|---|---|---|
Boyce 2013 [50] | Ireland | 4 | 603 | 0.30 | Whole-gland | ND | PSA, cT, biopsy GS |
DalMoro1 2018 [51] | Italy | 4 | 94 | 0.58 | Side-specific | Partin 1997 | PSA, cT, biopsy GS |
Egawa 1998 [52] | Japan | 1a | 81 | 0.43 | Whole-gland | ND | PSA, cT, biopsy GS, number of cancer cores, maximum cancer length in biopsy cores |
Majchrzak 2021 [58] | Poland | 4 | 61 | 0.31 | Side-specific | MSKCC | PSA, cT, biopsy GS, % positive cores, % Ca |
Patin 1997 [56] | USA | 1b | 4133 | 0.40 | Whole-gland | Partin 1997 | PSA, cT, biopsy GS |
Sighinolfi 2023 [57] | Italy | 4 | 141 | 0.47 | Side-specific | PRECE nomogram [63] | Age, PSA, cT, GS, % positive cores |
Song 2004 [54] | Korean | 4 | 317 | 0.40 | Whole-gland | Partin 1997 | PSA, cT, biopsy GS |
Thalgott 2018 [55] | Germany | 4 | 73 | 0.73 | Whole-gland | MSKCC, Partin 2013 | PSA, cT, bGS, % positive cores, % Ca |
Tsao 2014 [53] | China | 4 | 299 | 0.36 | Whole-gland | Partin 2007 | PSA, cT, biopsy GS sum |
Wang 2018 [59] | China | 4 | 541 | 0.54 | Whole-gland | Partin 2017 | PSA, cT, biopsy GS |
Xiang 2022 [62] | China | 4 | 105 | 0.42 | Whole-gland | MSKCC, Partin | PSA, cT, bGS, % positive cores, % Ca |
Xu 2021 [60] | China | 4 | 130 | 0.48 | Whole-gland | CAPRA 2005, MSKCC | age, PSA, cT, primary and secondary GS, positive cores ratio |
Zanelli 2019 [61] | Italy | 4 | 73 | 0.33 | Whole-gland | Partin 2013, MSKCC, CAPRA 2017 | age, PSA, cT, primary and secondary GS, positive cores ratio |