PURPOSE: Two models for stratification of prostate cancer aggressiveness predominate for the purposes of daily treatment decision making. This study investigates the relationships between these two clinically popular models. METHODS: Both risk stratification models use the same definition for low risk: Gleason score (GS) <or=6, pretreatment initial prostate specific antigen (iPSA) <or=10 ng/mL, and stage T1c-T2c. For the single factor high risk model (SF), intermediate risk (IR) is defined as the presence of GS 7 or PSA > 10-20 ng/mL, without the presence of any high-risk feature; high risk (HR) was defined as the presence of GS 8-10, iPSA >20, or palpation stage T3. For the double factor high risk (DF) model, IR and HR were defined as one and more than one of the following: GS >or=7, iPSA >10, or stage T3. Between April 1989 and October 2001, 1,597 patients were treated definitively with 3D conformal radiation therapy (3D-CRT) alone for prostate cancer at our institution. The main clinical endpoint was freedom from biochemical failure (FFBF). RESULTS: The 5-year actuarial FFBF rate for the low-risk group was 83%. The SF model resulted in FFBF rates of 76% and 47% for IR and HR patients respectively. The DF model resulted in FFBF rates of 70% and 52% for IR and HR patients, respectively. The FFBF rate for patients defined as IR and HR by both models was 76% and 40%, respectively. Those classified as IR by the DF model and then further subdivided into IR and HR by the SF model had a 76% and 52% 5-year FFBF rate (p = 0.0004). Those classified as HR by the DF model and then further subdivided into IR and HR by the SF model had a 71% and 40% 5-year FFBF (p = 0.0014). CONCLUSIONS: The SF model created prognostic groups with a greater internal consistency than the DF model. The SF was also better at identifying patients with high-risk prostate cancer who may benefit from a more aggressive approach.
PURPOSE: Two models for stratification of prostate cancer aggressiveness predominate for the purposes of daily treatment decision making. This study investigates the relationships between these two clinically popular models. METHODS: Both risk stratification models use the same definition for low risk: Gleason score (GS) <or=6, pretreatment initial prostate specific antigen (iPSA) <or=10 ng/mL, and stage T1c-T2c. For the single factor high risk model (SF), intermediate risk (IR) is defined as the presence of GS 7 or PSA > 10-20 ng/mL, without the presence of any high-risk feature; high risk (HR) was defined as the presence of GS 8-10, iPSA >20, or palpation stage T3. For the double factor high risk (DF) model, IR and HR were defined as one and more than one of the following: GS >or=7, iPSA >10, or stage T3. Between April 1989 and October 2001, 1,597 patients were treated definitively with 3D conformal radiation therapy (3D-CRT) alone for prostate cancer at our institution. The main clinical endpoint was freedom from biochemical failure (FFBF). RESULTS: The 5-year actuarial FFBF rate for the low-risk group was 83%. The SF model resulted in FFBF rates of 76% and 47% for IR and HR patients respectively. The DF model resulted in FFBF rates of 70% and 52% for IR and HR patients, respectively. The FFBF rate for patients defined as IR and HR by both models was 76% and 40%, respectively. Those classified as IR by the DF model and then further subdivided into IR and HR by the SF model had a 76% and 52% 5-year FFBF rate (p = 0.0004). Those classified as HR by the DF model and then further subdivided into IR and HR by the SF model had a 71% and 40% 5-year FFBF (p = 0.0014). CONCLUSIONS: The SF model created prognostic groups with a greater internal consistency than the DF model. The SF was also better at identifying patients with high-risk prostate cancer who may benefit from a more aggressive approach.
Authors: G Goldner; R Pötter; J J Battermann; M P Schmid; C Kirisits; S Sljivic; M van Vulpen Journal: Strahlenther Onkol Date: 2012-02-22 Impact factor: 3.621
Authors: Michael Souvatzoglou; Matthias Eiber; Axel Martinez-Moeller; Sebastian Fürst; Konstantin Holzapfel; Tobias Maurer; Sibylle Ziegler; Stephan Nekolla; Markus Schwaiger; Ambros J Beer Journal: Eur J Nucl Med Mol Imaging Date: 2013-05-24 Impact factor: 9.236
Authors: Tracy L Klayton; Karen Ruth; Eric M Horwitz; Robert G Uzzo; Alexander Kutikov; David Y T Chen; Mark Sobczak; Mark K Buyyounouski Journal: Radiother Oncol Date: 2011-08-31 Impact factor: 6.280