PSA density of the lesion: a mathematical formula that uses clinical and pathological data to predict biochemical recurrence in prostate cancer patients

• Autor(a) principal: JUNQUEIRA,PEDRO HENRIQUE REZENDE
• Data de Publicação: 2021
• Outros Autores: SANTOS,GABRIEL ARANTES DOS, XAVIER,MARCELO, ROMÃO,POLIANA, REIS,SABRINA, SROUGI,MIGUEL, NAHAS,WILLIAN CARLOS, PASSEROTTI,CARLO CARMARGO
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Revista do Colégio Brasileiro de Cirurgiões
• Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69912021000100229
• topic: Recurrence; Prognosis; Prostate-Specific Antigen; Prostatic Neoplasms

ABSTRACT A main challenge in the clinical management of prostate cancer is to identify which tumor is aggressive and needs invasive treatment. Thus, being able to predict which cancer will progress to biochemical recurrence is a great strategy to stratify prostate cancer patients. With that in mind, we created a mathematical formula that takes into account the patients clinical and pathological data resulting in a quantitative variable, called PSA density of the lesion, which has the potential to predict biochemical recurrence. To test if our variable is able to predict biochemical recurrence, we use a cohort of 219 prostate cancer patients, associating our new variable and classic parameters of prostate cancer with biochemical recurrence. Total PSA, lesion weight, volume and classic PSA density were positively associated with biochemical recurrence (p<0.05). ISUP score was also associated with biochemical recurrence in both biopsy and surgical specimen (p<0.001). The increase of PSA density of the lesion was significantly associated with the biochemical recurrence (p=0.03). Variables derived from the formula, PSA 15% and PSA 152, were also positive associated with the biochemical recurrence (p=0.01 and p=0.002 respectively). Logistic regression analysis shows that classic PSA density, PSA density of the lesion and total PSA, together, can explain up to 13% of cases of biochemical recurrence. PSA density of the lesion alone would have the ability to explain up to 7% of cases of biochemical recurrence. In conclusion, this new mathematical approach could be a useful tool to predict disease recurrence in prostate cancer.