INTRODUCTION: The aim of the study was to identify the appropriate level of Charlson comorbidity index (CCI) in older patients (>70 years) with high-risk prostate cancer (PCa) to achieve survival benefit following radical prostatectomy (RP). METHODS: We retrospectively analyzed 1008 older patients (>70 years) who underwent RP with pelvic lymph node dissection for high-risk prostate cancer (preoperative prostate-specific antigen >20 ng/mL or clinical stage ≥T2c or Gleason ≥8) from 14 tertiary institutions between 1988 and 2014. The study population was further grouped into CCI < 2 and ≥2 for analysis. Survival rate for each group was estimated with Kaplan-Meier method and competitive risk Fine-Gray regression to estimate the best explanatory multivariable model. Area under the curve (AUC) and Akaike information criterion were used to identify ideal 'Cut off' for CCI. RESULTS: The clinical and cancer characteristics were similar between the two groups. Comparison of the survival analysis using the Kaplan-Meier curve between two groups for non-cancer death and survival estimations for 5 and 10 years shows significant worst outcomes for patients with CCI ≥ 2. In multivariate model to decide the appropriate CCI cut-off point, we found CCI 2 has better AUC and p value in log rank test. CONCLUSION: Older patients with fewer comorbidities harboring high-risk PCa appears to benefit from RP. Sicker patients are more likely to die due to non-prostate cancer-related causes and are less likely to benefit from RP.
INTRODUCTION: The aim of the study was to identify the appropriate level of Charlson comorbidity index (CCI) in older patients (>70 years) with high-risk prostate cancer (PCa) to achieve survival benefit following radical prostatectomy (RP). METHODS: We retrospectively analyzed 1008 older patients (>70 years) who underwent RP with pelvic lymph node dissection for high-risk prostate cancer (preoperative prostate-specific antigen >20 ng/mL or clinical stage ≥T2c or Gleason ≥8) from 14 tertiary institutions between 1988 and 2014. The study population was further grouped into CCI < 2 and ≥2 for analysis. Survival rate for each group was estimated with Kaplan-Meier method and competitive risk Fine-Gray regression to estimate the best explanatory multivariable model. Area under the curve (AUC) and Akaike information criterion were used to identify ideal 'Cut off' for CCI. RESULTS: The clinical and cancer characteristics were similar between the two groups. Comparison of the survival analysis using the Kaplan-Meier curve between two groups for non-cancer death and survival estimations for 5 and 10 years shows significant worst outcomes for patients with CCI ≥ 2. In multivariate model to decide the appropriate CCI cut-off point, we found CCI 2 has better AUC and p value in log rank test. CONCLUSION: Older patients with fewer comorbidities harboring high-risk PCa appears to benefit from RP. Sicker patients are more likely to die due to non-prostate cancer-related causes and are less likely to benefit from RP.
Authors: Axel Heidenreich; Joaquim Bellmunt; Michel Bolla; Steven Joniau; Malcolm Mason; Vsevolod Matveev; Nicolas Mottet; Hans-Peter Schmid; Theo van der Kwast; Thomas Wiegel; Filliberto Zattoni Journal: Eur Urol Date: 2010-10-28 Impact factor: 20.096
Authors: Scott E Eggener; Peter T Scardino; Patrick C Walsh; Misop Han; Alan W Partin; Bruce J Trock; Zhaoyong Feng; David P Wood; James A Eastham; Ofer Yossepowitch; Danny M Rabah; Michael W Kattan; Changhong Yu; Eric A Klein; Andrew J Stephenson Journal: J Urol Date: 2011-01-15 Impact factor: 7.450
Authors: Stephen A Boorjian; R Jeffrey Karnes; Rosalia Viterbo; Laureano J Rangel; Eric J Bergstralh; Eric M Horwitz; Michael L Blute; Mark K Buyyounouski Journal: Cancer Date: 2011-01-10 Impact factor: 6.860
Authors: Hendrik Isbarn; Manuela Wanner; Georg Salomon; Thomas Steuber; Thorsten Schlomm; Jens Köllermann; Guido Sauter; Alexander Haese; Hans Heinzer; Hartwig Huland; Markus Graefen Journal: BJU Int Date: 2009-12-11 Impact factor: 5.588
Authors: Stacy Loeb; Edward M Schaeffer; Bruce J Trock; Jonathan I Epstein; Elizabeth B Humphreys; Patrick C Walsh Journal: Urology Date: 2009-11-22 Impact factor: 2.649
Authors: Giorgio Calleris; Giancarlo Marra; Ettore Dalmasso; Marco Falcone; Robert Jeffrey Karnes; Alessandro Morlacco; Marco Oderda; Rafael Sanchez-Salas; Francesco Soria; Paolo Gontero Journal: World J Urol Date: 2019-04-06 Impact factor: 4.226