Artículos de revistas
Pretreatment tumor volume estimation based on total serum psa in patients with localized prostate cancer
Fecha
2008Registro en:
Clinics, v.63, n.6, p.759-762, 2008
1807-5932
10.1590/S1807-59322008000600009
Autor
KATO, Raphael Barroso
SROUGI, Victor
SALVADORI, Fernanda Aburesi
AYRES, Pedro Paulo Marino Rodrigues
LEITE, Katia Moreira
Srougi, Miguel
Institución
Resumen
OBJECTIVES: To establish a formula that estimates tumor volume in localized prostate cancer based on serum prostate specific antigen levels. One of the main prognostic variables in localized prostate cancer is tumor volume, which can be precisely defined only after prostate extirpation. The present study defines a simple method that allows for estimation of tumor volume before treatment, which can help to establish a better therapeutic strategy for each patient. METHODS: From 1997 to 2002, 735 patients with prostate cancer of stagesT1c-T2c without any previous treatment were submitted to radical prostatectomy. Surgical specimens were evaluated by the same pathologist and the total tumor volume (in cc) and the relative tumor volume (as the percent of the total prostate volume) were determined using the grid morphometric method. Pretreatment serum prostate specific antigen was correlated with tumor volume in each patient using a linear regression model. RESULTS: There were positive correlations between the serum levels of prostate specific antigen and the total tumor volume in cc (p<0.001) and the relative tumor volume as a percentage (p<0.001). For each ng/ml unit increment of serum prostate specific antigen, there was a 0.302 cc increase in total tumor volume and a 0.7% increase in relative tumor volume. Total and percent tumor volume could be calculated, respectively, using the formulas Volume (cc) = 3.476 + 0.302 x PSA (ng/ml) and Volume (%) = 11.331 + 0.704 x prostate specific antigen (ng/ml). CONCLUSIONS: Tumor volume in patients with prostate cancer can be determined before treatment based on the serum prostate specific antigen levels.