Evidence map›Paper›PMID 29490658›Full record

ArticleBMC medicine2018

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

V J Gnanapragasam, O Bratt, K Muir, L S Lee, H H Huang, P Stattin, A Lophatananon

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In one paragraph

Article in BMC medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
40citing papers in PubMed, 1 pooled it
4.0field-weighted citation impact, top 6% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

40 citing papers in PubMed, 1 synthesis or guideline pooled it, 72 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 5 institutions in 3 countries.

V J GnanapragasamAcademic Urology Group, Department of Surgery and Oncology, University of Cambridge, Box 279 (S4), Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK. vjg29@cam.ac.uk.
O BrattDepartment of Translational Medicine, Division of Urological Cancers, Lund University, Lund, Sweden.
K MuirInstitute of Population Health, University of Manchester, Manchester, UK.
L S LeeDepartment of Urology, Singapore General Hospital, Singapore, Singapore.
H H HuangDepartment of Urology, Singapore General Hospital, Singapore, Singapore.
P StattinDepartment of Surgical and Perioperative Science, Urology and Andrology, Umeå University, Umeå, Sweden.
A LophatananonInstitute of Population Health, University of Manchester, Manchester, UK.
Singapore General Hospital · SGUniversity of Manchester · GBLund University · SEUmeå University · SEUniversity of Cambridge · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe 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.

methodsWe 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.

resultsThe 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).

conclusionsThis 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.

Indexed as

Cohort StudiesHumansMaleMortalityPrognosisProstatic NeoplasmsSurvival RateAll-cause mortalityCambridge Prognostic GroupsCancer-specific mortalityCompeting risksImproved treatment sectionNon-metastatic diseasePrognostic predictionProstate cancerStratificationTreatment selection

Identifiers

PMID29490658
PMCPMC5831573
OpenAlexW2789622370

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.