OBJECTIVE: To examine whether percentage of tumour volume (%TV) and percentage of high-grade tumour volume (%HGTV) help to better identify men at higher risk of early biochemical recurrence (BCR) after radical prostatectomy (RP) for non-metastatic high-risk prostate cancer, as early BCR after RP might be associated with higher risk of metastases and cancer-specific mortality. PATIENTS AND METHODS: We examined the data of 595 men treated with RP for non-metastatic high-risk prostate cancer between 1992 and 2011 at two European tertiary care centres. Kaplan-Meier analyses were used to graphically depict 2-year BCR-free survival. Multivariable Cox regression models addressed early BCR. We tested whether addition of %TV and %HGTV to a multivariable Cox regression model helps to increase a model's predictive accuracy (PA) for prediction of early BCR. RESULTS: In all, 32 men (10%) with specimen-confined prostate cancer (pT2-pT3a, negative surgical margin, pN0) and 67 men (24%) with non-specimen-confined prostate cancer had early BCR. After stratification according to %HGTV (%HGTV threshold: ≤33.33 vs >33.33%), the 2-year BCR-free survival rates were respectively 93 vs 60% (log-rank P < 0.001). In multivariable Cox regression models %HGTV emerged as an independent predictor of early BCR (P < 0.001), whereas %TV did not (P > 0.05). However, adding %HGTV (regardless of its coding) to other covariates in multivariable Cox regression analysis did not increase the model's PA in a meaningful fashion compared with the use of the detailed Gleason grading system (6 vs 7a vs 7b vs 8 vs 9-10). CONCLUSIONS: In a large cohort of patients with high-risk prostate cancer, %HGTV and %TV did not improve prediction of early BCR after RP substantially, although %HGTV was an independent predictor of early BCR. Therefore, sophisticated TV/HGTV measurements do not seem to have additional benefit for early BCR prediction relative to the use of Gleason grading. However, these results need to be confirmed in larger, prospective studies.
OBJECTIVE: To examine whether percentage of tumour volume (%TV) and percentage of high-grade tumour volume (%HGTV) help to better identify men at higher risk of early biochemical recurrence (BCR) after radical prostatectomy (RP) for non-metastatic high-risk prostate cancer, as early BCR after RP might be associated with higher risk of metastases and cancer-specific mortality. PATIENTS AND METHODS: We examined the data of 595 men treated with RP for non-metastatic high-risk prostate cancer between 1992 and 2011 at two European tertiary care centres. Kaplan-Meier analyses were used to graphically depict 2-year BCR-free survival. Multivariable Cox regression models addressed early BCR. We tested whether addition of %TV and %HGTV to a multivariable Cox regression model helps to increase a model's predictive accuracy (PA) for prediction of early BCR. RESULTS: In all, 32 men (10%) with specimen-confined prostate cancer (pT2-pT3a, negative surgical margin, pN0) and 67 men (24%) with non-specimen-confined prostate cancer had early BCR. After stratification according to %HGTV (%HGTV threshold: ≤33.33 vs >33.33%), the 2-year BCR-free survival rates were respectively 93 vs 60% (log-rank P < 0.001). In multivariable Cox regression models %HGTV emerged as an independent predictor of early BCR (P < 0.001), whereas %TV did not (P > 0.05). However, adding %HGTV (regardless of its coding) to other covariates in multivariable Cox regression analysis did not increase the model's PA in a meaningful fashion compared with the use of the detailed Gleason grading system (6 vs 7a vs 7b vs 8 vs 9-10). CONCLUSIONS: In a large cohort of patients with high-risk prostate cancer, %HGTV and %TV did not improve prediction of early BCR after RP substantially, although %HGTV was an independent predictor of early BCR. Therefore, sophisticated TV/HGTV measurements do not seem to have additional benefit for early BCR prediction relative to the use of Gleason grading. However, these results need to be confirmed in larger, prospective studies.
Authors: Se Young Choi; Byung Hoon Chi; Bumjin Lim; Yoon Soo Kyung; Dalsan You; In Gab Jeong; Cheryn Song; Jun Hyuk Hong; Hanjong Ahn; Choung-Soo Kim Journal: J Cancer Res Clin Oncol Date: 2020-01-08 Impact factor: 4.553
Authors: Ahva Shahabi; Raj Satkunasivam; Inderbir S Gill; Gary Lieskovsky; Sia Daneshmand; Jacek K Pinski; Mariana C Stern Journal: Can Urol Assoc J Date: 2016-01-14 Impact factor: 1.862
Authors: Fang-Ming Deng; Nicholas M Donin; Ruth Pe Benito; Jonathan Melamed; Julien Le Nobin; Ming Zhou; Sisi Ma; Jinhua Wang; Herbert Lepor Journal: Eur Urol Date: 2015-10-30 Impact factor: 20.096
Authors: Yujiro Ito; Kazuma Udo; Emily A Vertosick; Daniel D Sjoberg; Andrew J Vickers; Hikmat A Al-Ahmadie; Ying-Bei Chen; Anuradha Gopalan; S Joseph Sirintrapun; Satish K Tickoo; Peter T Scardino; James A Eastham; Victor E Reuter; Samson W Fine Journal: J Urol Date: 2019-03 Impact factor: 7.450