Development and Validation of a Nomogram for Predicting the Overall Survival of Prostate Cancer Patients

A Large Population-Based Cohort Study

Zheng Zhou; Jinxian Pu; Xuedong Wei; Yuhua Huang; Yuxin Lin; Liangliang Wang


Transl Androl Urol. 2022;11(9):1325-1335. 

In This Article

Abstract and Introduction


Background: Prostate cancer (PC) is the second most common malignant tumor, and its survival is of great concern. However, the assessment of survival risk in current studies is limited. This study is to develop and validate a nomogram for the prediction of survival in PC patients using data from the Surveillance, Epidemiology, and End Results (SEER) database.

Methods: A total of 153,796 PC patients were included in this cohort study. Patients were divided into a training set (n=107,657) and a testing set (n=46,139). The 3-, 5- and 10-year survival of the PC patients were regarded as the outcomes. Predictors based on the demographic and pathological data for survival were identified by multivariate Cox regression analysis to develop the predictive nomogram. Internal and subgroup validations were performed to assess the predictive performance of the nomogram. The C-index, time-dependent receiver operating characteristic (ROC) curves, and corresponding areas under the ROC curves (AUCs) were used to estimate the predictive performance of the nomogram.

Results: Age at diagnosis, race, marital status, tumor node metastasis (TNM) stage, prostate specific antigen (PSA) status, Gleason score, and pathological stage were identified as significantly associated with the survival of PC patients (P<0.05). The C-index of the nomogram indicated a moderate predictive ability [training set: C-index =0.782, 95% confidence interval (CI): 0.779–0.785; testing set: C-index =0.782, 95% CI: 0.777–0.787]. The AUCs of this nomogram for the 3-, 5-, and 10-year survival were 0.757 (95% CI: 0.756–0.758), 0.741 (95% CI: 0.740–0.742), and 0.716 (95% CI: 0.715–0.717), respectively. The results of subgroup validation showed that all the AUCs for the nomogram at 3, 5, and 10 years were more than 0.70, regardless of marital status and race.

Conclusions: We developed a nomogram with the moderate predictive ability for the long-term survival (3-, 5-, and 10-year survival) of patients with PC.


Prostate cancer (PC) is the second most common malignant tumor diagnosed among men and remains the fifth leading cause of cancer-related deaths worldwide.[1,2] An estimated 268,490 new cases and 34,500 cancer-related deaths are reported annually in the United States.[1] The 5-year survival rate declines to 31% for PC patients with metastatic disease.[3] Therefore, it is imperative to identify PC patients with poor prognoses, so as to implement management regimens to improve their quality of life.

Previous research have identified the factors associated with the prognosis of PC, including expression of the prostate specific antigen (PSA).[4,5] Younger age at diagnosis and being married have also been associated with improved prognosis and survival in PC patients.[6–10] To predict patient prognosis more accurately, several models incorporating multiple prognostic factors have been built. Hu et al. developed a prognostic prediction model based on 22 autophagy-related genes expressed in PC patients.[11] Han et al. conducted a prognostic nomogram for progression-free survival of 255 PC patients.[12] However, the clinical applicability of these models is limited by the need to collect clinical samples and predictive ability. Furthermore, the performance of these prediction models validated in different subgroups has not been investigated.

Herein, a nomogram was developed to predict the long-term survival (3, 5, and 10 years) in 152,796 individuals based on data from the Surveillance, Epidemiology, and End Results (SEER) database. Internal validation and subgroup validation based on marital status and race were performed to assess the predictive performance of the nomogram. We present the following article in accordance with the TRIPOD reporting checklist (available at