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. 2021 Feb 11;11(2):e040531.
doi: 10.1136/bmjopen-2020-040531.

Diagnostic and prognostic factors in patients with prostate cancer: a systematic review protocol

Katharina Beyer  1 , Lisa Moris  2 , Michael Lardas  3 , Anna Haire  4 , Francesco Barletta  5 , Simone Scuderi  5 , Eleni Vradi  6 , Giorgio Gandaglia  5 , Muhammad Imran Omar  7 , Steven MacLennan  7 , Jihong Zong  8 , Bahman Farahmand  9 , Sara J Maclennan  7 , Zsuzsanna Devecseri  10 , Alex Asiimwe  6 , Laurence Collette  11 , Anders Bjartell  12 , James Ndow  13 , Alberto Briganti  5   14 , Mieke Van Hemelrijck  4 ; PIONEER Consortium
Collaborators, Affiliations

Diagnostic and prognostic factors in patients with prostate cancer: a systematic review protocol

Katharina Beyer et al. BMJ Open. .

Abstract

Introduction: As part of the PIONEER (Prostate Cancer Diagnosis and Treatment Enhancement Through the Power of Big Data in Europe) Consortium, we will explore which diagnostic and prognostic factors (DPFs) are currently being researched to previously defined clinical and patient-reported outcomes for prostate cancer (PCa).

Methods and analysis: This research project will follow the following four steps: (1) a broad systematic literature review of DPFs for all stages of PCa, covering evidence from 2014 onwards; (2) discussion of systematic review findings by a multidisciplinary expert panel; (3) risk of bias assessment and applicability with Prediction model Risk Of Bias Assessment Tool criteria, Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) and the Quality In Prognosis Studies tool (QUIPS) and (4) additional quantitative assessments if required.

Ethics and dissemination: We aim to develop an online tool to present the DPFs identified in this research and make them available across all stakeholders. There are no ethical implications.

Keywords: oncology; prostate disease; urological tumours.

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Conflict of interest statement

Competing interests: None declared.

Figures

Figure 1
Figure 1
Overview of four stage process. CDR, clinical decision rule; CHARMS PF, Critical Appraisal and Data Extraction for systematic reviews of prediction modelling; PIONEER, Prostate Cancer Diagnosis and Treatment Enhancement Through the Power of Big Data in Europe; PROBAST, Prediction model Risk Of Bias ASsessment Tool; QUADAS- 2, Quality Assessment of Diagnostic Accuracy Studies; QUIPS, Quality In Prognosis Studies tool; SR, systematic review.
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