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BMC Med. 2018 Feb 28;16(1):31. doi: 10.1186/s12916-018-1019-5.

The Cambridge Prognostic Groups for improved prediction of disease mortality at diagnosis in primary non-metastatic prostate cancer: a validation study.

Author information

1
Academic Urology Group, Department of Surgery and Oncology, University of Cambridge, Box 279 (S4), Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK. vjg29@cam.ac.uk.
2
Addenbrookes Hospital, Department of Urology, Addenbrooke's Hospital, Cambridge, UK. vjg29@cam.ac.uk.
3
Department of Translational Medicine, Division of Urological Cancers, Lund University, Lund, Sweden.
4
Institute of Population Health, University of Manchester, Manchester, UK.
5
Department of Urology, Singapore General Hospital, Singapore, Singapore.
6
Department of Surgical and Perioperative Science, Urology and Andrology, Umeå University, Umeå, Sweden.
7
Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.

Abstract

BACKGROUND:

The purpose of this study is to validate a new five-tiered prognostic classification system to better discriminate cancer-specific mortality in men diagnosed with primary non-metastatic prostate cancer.

METHODS:

We applied a recently described five-strata model, the Cambridge Prognostic Groups (CPGs 1-5), in two international cohorts and tested prognostic performance against the current standard three-strata classification of low-, intermediate- or high-risk disease. Diagnostic clinico-pathological data for men obtained from the Prostate Cancer data Base Sweden (PCBaSe) and the Singapore Health Study were used. The main outcome measure was prostate cancer mortality (PCM) stratified by age group and treatment modality.

RESULTS:

The PCBaSe cohort included 72,337 men, of whom 7162 died of prostate cancer. The CPG model successfully classified men with different risks of PCM with competing risk regression confirming significant intergroup distinction (p < 0.0001). The CPGs were significantly better at stratified prediction of PCM compared to the current three-tiered system (concordance index (C-index) 0.81 vs. 0.77, p < 0.0001). This superiority was maintained for every age group division (p < 0.0001). Also in the ethnically different Singapore cohort of 2550 men with 142 prostate cancer deaths, the CPG model outperformed the three strata categories (C-index 0.79 vs. 0.76, p < 0.0001). The model also retained superior prognostic discrimination in the treatment sub-groups: radical prostatectomy (n = 20,586), C-index 0.77 vs. 074; radiotherapy (n = 11,872), C-index 0.73 vs. 0.69; and conservative management (n = 14,950), C-index 0.74 vs. 0.73. The CPG groups that sub-divided the old intermediate-risk (CPG2 vs. CPG3) and high-risk categories (CPG4 vs. CPG5) significantly discriminated PCM outcomes after radical therapy or conservative management (p < 0.0001).

CONCLUSIONS:

This validation study of nearly 75,000 men confirms that the CPG five-tiered prognostic model has superior discrimination compared to the three-tiered model in predicting prostate cancer death across different age and treatment groups. Crucially, it identifies distinct sub-groups of men within the old intermediate-risk and high-risk criteria who have very different prognostic outcomes. We therefore propose adoption of the CPG model as a simple-to-use but more accurate prognostic stratification tool to help guide management for men with newly diagnosed prostate cancer.

KEYWORDS:

All-cause mortality; Cambridge Prognostic Groups; Cancer-specific mortality; Competing risks; Improved treatment section; Non-metastatic disease; Prognostic prediction; Prostate cancer; Stratification; Treatment selection

PMID:
29490658
PMCID:
PMC5831573
DOI:
10.1186/s12916-018-1019-5
[Indexed for MEDLINE]
Free PMC Article

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