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

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.

摘要 前列腺癌临床管理中的核心挑战之一，在于甄别具有侵袭性、需接受侵入性治疗的肿瘤。因此，能够预测癌症进展为生化复发的风险，是对前列腺癌患者进行分层管理的有效策略。基于此，我们构建了一款数学公式，可整合患者的临床与病理数据，生成一项定量变量——病灶PSA密度（PSA density of the lesion），其具备预测生化复发的潜力。为验证该变量能否预测生化复发，我们纳入219例前列腺癌患者的队列，将本研究提出的新变量与前列腺癌经典临床参数一同与生化复发进行关联分析。总PSA、病灶重量、体积以及经典PSA密度均与生化复发呈正相关（p<0.05）。ISUP评分（ISUP score）在活检标本与手术标本中均与生化复发存在关联（p<0.001）。病灶PSA密度的升高与生化复发存在显著关联（p=0.03）。由该公式衍生出的变量——PSA 15%与PSA 152，同样与生化复发呈正相关（分别为p=0.01与p=0.002）。Logistic回归分析显示，经典PSA密度、病灶PSA密度与总PSA三者联合，可解释高达13%的生化复发病例。单独使用病灶PSA密度，则可解释高达7%的生化复发病例。综上，这一新型数学方法可作为预测前列腺癌患者疾病复发的有效工具。