Roy Soumyajit, Sun Yilun, Wallis Cristopher J D, Morgan Scott C, Grimes Scott, Malone Julia, Kishan Amar U, Mukherjee Dibya, Spratt Daniel E, Saad Fred, Malone Shawn
Department of Radiation Oncology, Rush University Medical Center, Chicago, IL, USA.
Department of Population and Quantitative Health Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, USA.
Prostate Cancer Prostatic Dis. 2023 Mar;26(1):119-125. doi: 10.1038/s41391-022-00560-3. Epub 2022 Jul 5.
Metastatic castrate sensitive prostate cancer (mCSPC) is a heterogeneous disease state with variable prognosis. Although several life-prolonging systemic agents are available, there is no robust multivariable model to predict prognosis and improve risk stratification in mCSPC. The objective of this study was to build and validate a multivariable prognostic model to predict overall survival (OS) in mCSPC.
We used data from LATITUDE, a phase III randomized controlled trial in which men with de novo mCSPC were randomly allocated to either ADT plus abiraterone or ADT with placebo. Patients with non-missing data (n = 1,058) were randomly split in a 70:30 ratio to training (n = 743) and testing (n = 315) sets. Elastic net regression was used for variable selection. A multivariable Cox regression model for OS was then fitted using the selected variables. The predictive accuracy of the model was assessed on the testing set using the time-dependent area under curve (tAUC) with bootstrapped confidence intervals [CI] primarily for OS and secondarily for radiographic progression-free survival (rPFS).
The 11 prognostic variables in the final model were performance status, number of skeletal metastases, Gleason score, presence of liver metastasis, worst pain score, albumin, lactate dehydrogenase, prostate-specific antigen, hemoglobin, and treatment regimen. The tAUC for predicting OS at 2- and 3-years was 0.74 (95% CI, 0.67-0.80) and 0.72 (95% CI, 0.65-0.77), respectively. The tAUC for rPFS at 2- and 3-years was 0.72 (95% CI, 0.65-0.77) and 0.77 (95% CI, 0.70-0.82), respectively.
A prognostic model for men with de novo mCSPC was developed and validated in an independent testing set. Our model had high accuracy for predicting OS and rPFS. The model includes commonly used clinical and laboratory parameters and can guide risk stratification of these patients for participation in future trials.
转移性去势敏感性前列腺癌（mCSPC）是一种预后各异的异质性疾病状态。尽管有几种延长生命的全身治疗药物可供使用，但尚无强大的多变量模型来预测mCSPC的预后并改善风险分层。本研究的目的是构建并验证一个多变量预后模型，以预测mCSPC患者的总生存期（OS）。
我们使用了LATITUDE研究的数据，这是一项III期随机对照试验，其中初发mCSPC男性患者被随机分配至雄激素剥夺治疗（ADT）联合阿比特龙组或ADT联合安慰剂组。对数据无缺失的患者（n = 1,058）按70:30的比例随机分为训练集（n = 743）和测试集（n = 315）。采用弹性网回归进行变量选择。然后使用所选变量拟合OS的多变量Cox回归模型。在测试集上，主要针对OS并其次针对影像学无进展生存期（rPFS），使用带自助置信区间[CI]的时间依赖性曲线下面积（tAUC）评估模型的预测准确性。
最终模型中的11个预后变量为体能状态、骨转移数量、Gleason评分、肝转移情况、最严重疼痛评分、白蛋白、乳酸脱氢酶、前列腺特异性抗原、血红蛋白和治疗方案。预测2年和3年OS的tAUC分别为0.74（95%CI，0.67 - 0.80）和0.72（95%CI，0.65 - 0.77）。预测2年和3年rPFS的tAUC分别为0.72（95%CI，0.65 - 0.77）和0.77（95%CI，0.70 - 0.82）。
开发了一种针对初发mCSPC男性患者的预后模型，并在独立测试集中进行了验证。我们的模型在预测OS和rPFS方面具有较高的准确性。该模型包括常用的临床和实验室参数，可指导这些患者参与未来试验的风险分层。
