Development and validation of two nomograms for predicting overall survival and Cancer-specific survival in prostate cancer patients with bone metastases: a population-based study

Abstract

Background: Prostate cancer with bone metastasis has significant invasiveness and markedly poorer prognosis. The purpose of this study is to establish two nomograms for predicting the overall survival (OS) and cancer-specific survival (CSS) of prostate cancer patients with bone metastasis.

Methods: From January 2000 to December 2018, a total of 2683 prostate adenocarcinoma with bone metastasis patients were identified from the Surveillance, Epidemiology, and End Results Program (SEER) database. These patients were then divided into a training cohort and a validation cohort, with OS and CSS as the study endpoints. Correlation analyses were employed to assess the relationship between variables. Univariate and multivariate Cox analyses were utilized to ascertain the independent prognostic factors. Calibration curves and the area under the time-dependent receiver operating characteristic curve (time-dependent AUC) were employed to evaluate discrimination and calibration of the nomogram. DCA was applied to examine accuracy and clinical benefits. The clinical utility of the nomogram and the AJCC Stage System was compared using net reclassification improvement (NRI) and integrated discrimination improvement (IDI). Lastly, the risk stratifications of the nomogram and the AJCC Stage System were compared.

Results: There was no collinearity among the variables that were screened. The results of multivariate Cox regression analysis showed that seven variables (age, surgery, brain metastasis, liver metastasis, lung metastasis, Gleason score, marital status) and six variables (age, surgery, lung metastasis, liver metastasis, Gleason score, marital status) were identified to establish the nomogram for OS and CSS, respectively. The calibration curves, time-dependent AUC curves, and DCA revealed that both nomograms had pleasant predictive power. Furthermore, NRI and IDI confirmed that the nomogram outperformed the AJCC Stage System.

Conclusion: Both nomograms had satisfactory accuracy and were validated to assist clinicians in evaluating the prognosis of PABM patients.

Keywords: Bone metastases; Nomogram; Overall survival; Prostate cancer.

Fig. 1

Flow diagram illustrating recruitment of patients

Fig. 2

Cumulative incidence predictions of CSS in gastric cancer with liver metastasis. (A) Age (B) Race (C) Gleason Score (D) T Stage (E) N Stage (F) Radiotherapy (G) Chemotherapy (H) Surgery (I) brain (J) liver (K) lung (L) PSA (M) Marital Status

Fig. 3

The results of correlation analysis between all included variables. CT: chemotherapy; RT: radiotherapy

Fig. 4

Constructed nomograms for prognostic prediction of overall survival and cancer specific survival

Fig. 5

Calibration curves. A 3-year and 5-year likelihoods of OS and CSS in the training dataset. B 3-year and 5-year likelihoods of OS and CSS in the validation dataset

Fig. 6

Time-dependent AUC and receiver operating characteristic (ROC) curves of OS and CSS. A,B Time-dependent AUC of using the nomogram to OS and CSS probability within 5 years in the training cohort and validation cohort. The blue line represents AUC = 0.65. And the shading area between blue dotted curves represents 95% credible intervals. C,D ROC curves corresponding to 3-year and 5-year OS in the training and validation cohort, respectively. E,F ROC curves corresponding to 3-year and 5-year CSS in the training and validation cohort, respectively

Fig. 7

Decision curve analysis of the nomogram in the estimation of OS and CSS of patients with PABM. A Training cohort. B Validation cohort. The None line illustrates the net benefit when assuming no patients die; the All line represents the net benefit if all patients die

Fig. 8

Kaplan–Meier OS and CSS curves of PABM patients with different risks stratified by the nomogram. A,B PABM patients in the training and validation cohort at different stages are classified according to the AJCC staging system. C,D PABM patients in the training and validation cohort at different stages are classified according to the cox model nomogram. E,F PABM patients in the training and validation cohort at different stages are classified according to the competing risk model nomogram