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. 2022 Sep;11(9):1325-1335.
doi: 10.21037/tau-22-498.

Development and validation of a nomogram for predicting the overall survival of prostate cancer patients: a large population-based cohort study

Zheng Zhou  1 , Jinxian Pu  1 , Xuedong Wei  1 , Yuhua Huang  1 , Yuxin Lin  1 , Liangliang Wang  1
Affiliations

Development and validation of a nomogram for predicting the overall survival of prostate cancer patients: a large population-based cohort study

Zheng Zhou et al. Transl Androl Urol. 2022 Sep.

Abstract

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.

Keywords: Prostate cancer; SEER database; nomogram; survival.

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Conflict of interest statement

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tau.amegroups.com/article/view/10.21037/tau-22-498/coif). The authors have no conflicts of interest to declare.

Figures

Figure 1
Figure 1
A flow chart of screening of prostate cancer patients. PC, prostate cancer; TNM, tumor node metastasis; PSA, prostate-specific antigen; SEER, Surveillance, Epidemiology, and End Results.
Figure 2
Figure 2
Predictors of the survival in PC patients. HR, hazard ratio; T, tumor; N, node; M, metastasis; PSA, prostate specific antigen; PC, prostate cancer.
Figure 3
Figure 3
A nomogram for predicting the survival of PC patients. *P<0.05; **P<0.001. T, tumor; N, node; M, metastasis; PSA, prostate specific antigen; Pr, probability; PC, prostate cancer.
Figure 4
Figure 4
Time-dependent ROC curves and the corresponding AUC for the 3-, 5-, and 10-year survival. (A) Training set and (B) testing set. ROC, receiver operating characteristic; AUC, area under the curve.
Figure 5
Figure 5
Time-dependent ROC curves and the corresponding AUC for the 3-, 5-, and 10-year survival of subgroups according to marital status. (A) Married and (B) unmarried. ROC, receiver operating characteristic; AUC, area under the curve.
Figure 6
Figure 6
Time-dependent ROC curves and corresponding AUC for the 3-, 5-, and 10-year survival of subgroups according to race. (A) Black, (B) White, and (C) other races. ROC, receiver operating characteristic; AUC, area under the curve.
Figure 7
Figure 7
An example using the nomogram for predicting the survival of PC patients. *P<0.05; **P<0.001. PSA, prostate specific antigen; T, tumor; N, node; M, metastasis; Pr, probability; PC, prostate cancer.
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