OBJECTIVES: To explore the association among patient factors (age, comorbidity), disease-specific factors (stage, Gleason score), and suboptimal initial treatment in a cohort of men with localized prostate cancer. METHODS: An age-stratified, geographically representative cohort of 276 patients with localized prostate cancer diagnosed in 1995 to 1996 was identified using the Ontario Cancer Registry. Data describing age, comorbidity, Gleason score, stage, and treatment received were abstracted by chart review. A previously developed Markov state-transition model was used to estimate the optimal treatment for each patient. A logistic regression model was developed to estimate the predictors of suboptimal treatment. The treatment received was compared with the predicted optimal treatment. Suboptimal treatment occurred when the difference between the optimal treatment and treatment received was clinically important (thresholds of 0.2 to 1.0 life year or quality-adjusted life year). RESULTS: Of 276 patients, 41 (14.9%) received suboptimal treatment. Age, Gleason score, and comorbidity were independent predictors of suboptimal treatment. Healthy men aged 70 years or older, with Gleason scores of 5 to 7 or 8 to 10 had the greatest proportion of suboptimal treatment (46.9% and 72.7%, respectively). The average quality-adjusted life expectancy lost for healthy men aged 70 to 79 years with Gleason scores of 5 to 7 and 8 to 10 was 0.62 year and 0.93 year per patient, respectively. CONCLUSIONS: Otherwise healthy men in their 70s and 80s with localized prostate cancer are often receiving watchful waiting and potentially losing valuable years of life. Many of these patients with at least moderate-grade disease may benefit from potentially curative therapy (radical prostatectomy or radiotherapy).
OBJECTIVES: To explore the association among patient factors (age, comorbidity), disease-specific factors (stage, Gleason score), and suboptimal initial treatment in a cohort of men with localized prostate cancer. METHODS: An age-stratified, geographically representative cohort of 276 patients with localized prostate cancer diagnosed in 1995 to 1996 was identified using the Ontario Cancer Registry. Data describing age, comorbidity, Gleason score, stage, and treatment received were abstracted by chart review. A previously developed Markov state-transition model was used to estimate the optimal treatment for each patient. A logistic regression model was developed to estimate the predictors of suboptimal treatment. The treatment received was compared with the predicted optimal treatment. Suboptimal treatment occurred when the difference between the optimal treatment and treatment received was clinically important (thresholds of 0.2 to 1.0 life year or quality-adjusted life year). RESULTS: Of 276 patients, 41 (14.9%) received suboptimal treatment. Age, Gleason score, and comorbidity were independent predictors of suboptimal treatment. Healthy men aged 70 years or older, with Gleason scores of 5 to 7 or 8 to 10 had the greatest proportion of suboptimal treatment (46.9% and 72.7%, respectively). The average quality-adjusted life expectancy lost for healthy men aged 70 to 79 years with Gleason scores of 5 to 7 and 8 to 10 was 0.62 year and 0.93 year per patient, respectively. CONCLUSIONS: Otherwise healthy men in their 70s and 80s with localized prostate cancer are often receiving watchful waiting and potentially losing valuable years of life. Many of these patients with at least moderate-grade disease may benefit from potentially curative therapy (radical prostatectomy or radiotherapy).
Authors: Leah Y Nakamura; Rafael N Nunez; Paul E Andrews; Robert G Ferrigni; Mitchell R Humphreys; Scott K Swanson; Christopher E Wolter; Erik P Castle Journal: J Robot Surg Date: 2011-02-05
Authors: Claudio Jeldres; Nazareno Suardi; Paul Perrotte; Umberto Capitanio; Jochen Walz; Georg C Hutterer; Fred Saad; Luc Valiquette; Markus Graefen; Hugues Widmer; Pierre I Karakiewicz Journal: Can Urol Assoc J Date: 2009-02 Impact factor: 1.862
Authors: Simon Yang; Shabbir M H Alibhai; Erin D Kennedy; Abraham El-Sedfy; Matthew Dixon; Natalie Coburn; Alex Kiss; Calvin H L Law Journal: HPB (Oxford) Date: 2014-06-24 Impact factor: 3.647