Novel metastatic burden-stratified risk model in de novo metastatic hormone-sensitive prostate cancer

Japanese Urological Oncology Group

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)


The metastatic burden is a critical factor for decision-making in the treatment of metastatic hormone-sensitive prostate cancer (HSPC). This study aimed to develop and validate a novel risk model for survival in patients with de novo low- and high-burden metastatic HSPC. The retrospective observational study included men with de novo metastatic prostate cancer who were treated with primary androgen-deprivation therapy at 30 institutions across Japan between 2008 and 2017. We created a risk model for overall survival (OS) in the discovery cohort (n = 1449) stratified by the metastatic burden (low vs high) and validated its predictive ability in a separate cohort (n = 951). Based on multivariate analyses, lower hemoglobin levels, higher Gleason grades, and higher clinical T-stage were associated with poor OS in low-burden disease. Meanwhile, lower hemoglobin levels, higher Gleason grade group, liver metastasis, and higher extent of disease scores in bone were associated with poor OS in patients with high-burden disease. In the discovery and validation cohorts, the risk model using the aforementioned parameters exhibited excellent discriminatory ability for progression-free survival and OS. The predictive ability of this risk model was superior to that of previous risk models. Our novel metastatic burden-stratified risk model exhibited excellent predictive ability for OS, and it is expected to have several clinical uses, such as precise prognostic estimation.

Original languageEnglish
Pages (from-to)3616-3626
Number of pages11
JournalCancer science
Issue number9
Publication statusPublished - 2021 Sep


  • androgen-deprivation therapy
  • hormone-sensitive prostate cancer
  • metastatic burden
  • metastatic prostate cancer
  • risk model

ASJC Scopus subject areas

  • Oncology
  • Cancer Research


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