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. 2023 Oct 6:13:1242639.
doi: 10.3389/fonc.2023.1242639. eCollection 2023.

Cohort profile: the Turin prostate cancer prognostication (TPCP) cohort

Nicolas Destefanis  1 , Valentina Fiano  1 , Lorenzo Milani  1 , Paolo Vasapolli  1 , Michelangelo Fiorentino  2 , Francesca Giunchi  3 , Luca Lianas  4 , Mauro Del Rio  4 , Francesca Frexia  4 , Luca Pireddu  4 , Luca Molinaro  5 , Paola Cassoni  5 , Mauro Giulio Papotti  6 , Paolo Gontero  7 , Giorgio Calleris  7 , Marco Oderda  7 , Umberto Ricardi  8 , Giuseppe Carlo Iorio  8 , Piero Fariselli  9 , Elena Isaevska  1 , Olof Akre  10 , Renata Zelic  11 , Andreas Pettersson  12 , Daniela Zugna  1 , Lorenzo Richiardi  1
Affiliations

Cohort profile: the Turin prostate cancer prognostication (TPCP) cohort

Nicolas Destefanis et al. Front Oncol. .

Abstract

Introduction: Prostate cancer (PCa) is the most frequent tumor among men in Europe and has both indolent and aggressive forms. There are several treatment options, the choice of which depends on multiple factors. To further improve current prognostication models, we established the Turin Prostate Cancer Prognostication (TPCP) cohort, an Italian retrospective biopsy cohort of patients with PCa and long-term follow-up. This work presents this new cohort with its main characteristics and the distributions of some of its core variables, along with its potential contributions to PCa research.

Methods: The TPCP cohort includes consecutive non-metastatic patients with first positive biopsy for PCa performed between 2008 and 2013 at the main hospital in Turin, Italy. The follow-up ended on December 31st 2021. The primary outcome is the occurrence of metastasis; death from PCa and overall mortality are the secondary outcomes. In addition to numerous clinical variables, the study's prognostic variables include histopathologic information assigned by a centralized uropathology review using a digital pathology software system specialized for the study of PCa, tumor DNA methylation in candidate genes, and features extracted from digitized slide images via Deep Neural Networks.

Results: The cohort includes 891 patients followed-up for a median time of 10 years. During this period, 97 patients had progression to metastatic disease and 301 died; of these, 56 died from PCa. In total, 65.3% of the cohort has a Gleason score less than or equal to 3 + 4, and 44.5% has a clinical stage cT1. Consistent with previous studies, age and clinical stage at diagnosis are important prognostic factors: the crude cumulative incidence of metastatic disease during the 14-years of follow-up increases from 9.1% among patients younger than 64 to 16.2% for patients in the age group of 75-84, and from 6.1% for cT1 stage to 27.9% in cT3 stage.

Discussion: This study stands to be an important resource for updating existing prognostic models for PCa on an Italian cohort. In addition, the integrated collection of multi-modal data will allow development and/or validation of new models including new histopathological, digital, and molecular markers, with the goal of better directing clinical decisions to manage patients with PCa.

Keywords: DNA methylation; digital pathology; prognosis; prognostic modelling; prostate cancer.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Overview of the TPCP cohort study design data sources.
Figure 2
Figure 2
TPCP flow diagram for patient inclusion. ASAP, Atypical Small Acinar Proliferation; HGPIN, High-Grade Prostatic Intraepithelial Neoplasia.
Figure 3
Figure 3
A simplified schematic representation of the analytical process based on the Digital Pathology Platform: from the scanning of the slides to the phases of annotation by the uropathologists and the laboratory post-review.
Figure 4
Figure 4
Cumulative incidence functions for the TPCP cohort (n = 891).
Figure 5
Figure 5
Non-parametric cumulative incidences of metastatic prostate cancer, by clinical stage (p < 0.001).
Figure 6
Figure 6
Non-parametric cumulative incidences of metastatic prostate cancer, by age (p = 0.045).
Figure 7
Figure 7
Non-parametric cumulative incidences of metastatic prostate cancer, by social deprivation index (p = 0.40).
See this image and copyright information in PMC

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