Literature DB >> 35933885

Incorporating progesterone receptor expression into the PREDICT breast prognostic model.

Isabelle Grootes1, Renske Keeman2, Fiona M Blows3, Roger L Milne4, Graham G Giles4, Anthony J Swerdlow5, Peter A Fasching6, Mustapha Abubakar7, Irene L Andrulis8, Hoda Anton-Culver9, Matthias W Beckmann10, Carl Blomqvist11, Stig E Bojesen12, Manjeet K Bolla13, Bernardo Bonanni14, Ignacio Briceno15, Barbara Burwinkel16, Nicola J Camp17, Jose E Castelao18, Ji-Yeob Choi19, Christine L Clarke20, Fergus J Couch21, Angela Cox22, Simon S Cross23, Kamila Czene24, Peter Devilee25, Thilo Dörk26, Alison M Dunning3, Miriam Dwek27, Douglas F Easton28, Diana M Eccles29, Mikael Eriksson24, Kristina Ernst30, D Gareth Evans31, Jonine D Figueroa32, Visnja Fink30, Giuseppe Floris33, Stephen Fox34, Marike Gabrielson24, Manuela Gago-Dominguez35, José A García-Sáenz36, Anna González-Neira37, Lothar Haeberle10, Christopher A Haiman38, Per Hall39, Ute Hamann40, Elaine F Harkness41, Mikael Hartman42, Alexander Hein10, Maartje J Hooning43, Ming-Feng Hou44, Sacha J Howell45, Hidemi Ito46, Anna Jakubowska47, Wolfgang Janni30, Esther M John48, Audrey Jung49, Daehee Kang50, Vessela N Kristensen51, Ava Kwong52, Diether Lambrechts53, Jingmei Li54, Jan Lubiński55, Mehdi Manoochehri40, Sara Margolin56, Keitaro Matsuo57, Nur Aishah Mohd Taib58, Anna Marie Mulligan59, Heli Nevanlinna60, William G Newman31, Kenneth Offit61, Ana Osorio62, Sue K Park63, Tjoung-Won Park-Simon26, Alpa V Patel64, Nadege Presneau27, Katri Pylkäs65, Brigitte Rack30, Paolo Radice66, Gad Rennert67, Atocha Romero68, Emmanouil Saloustros69, Elinor J Sawyer70, Andreas Schneeweiss71, Fabienne Schochter30, Minouk J Schoemaker72, Chen-Yang Shen73, Rana Shibli67, Peter Sinn74, William J Tapper29, Essa Tawfiq75, Soo Hwang Teo76, Lauren R Teras64, Diana Torres77, Celine M Vachon78, Carolien H M van Deurzen79, Camilla Wendt80, Justin A Williams17, Robert Winqvist65, Mark Elwood75, Marjanka K Schmidt81, Montserrat García-Closas7, Paul D P Pharoah28.   

Abstract

BACKGROUND: Predict Breast (www.predict.nhs.uk) is an online prognostication and treatment benefit tool for early invasive breast cancer. The aim of this study was to incorporate the prognostic effect of progesterone receptor (PR) status into a new version of PREDICT and to compare its performance to the current version (2.2).
METHOD: The prognostic effect of PR status was based on the analysis of data from 45,088 European patients with breast cancer from 49 studies in the Breast Cancer Association Consortium. Cox proportional hazard models were used to estimate the hazard ratio for PR status. Data from a New Zealand study of 11,365 patients with early invasive breast cancer were used for external validation. Model calibration and discrimination were used to test the model performance.
RESULTS: Having a PR-positive tumour was associated with a 23% and 28% lower risk of dying from breast cancer for women with oestrogen receptor (ER)-negative and ER-positive breast cancer, respectively. The area under the ROC curve increased with the addition of PR status from 0.807 to 0.809 for patients with ER-negative tumours (p = 0.023) and from 0.898 to 0.902 for patients with ER-positive tumours (p = 2.3 × 10-6) in the New Zealand cohort. Model calibration was modest with 940 observed deaths compared to 1151 predicted.
CONCLUSION: The inclusion of the prognostic effect of PR status to PREDICT Breast has led to an improvement of model performance and more accurate absolute treatment benefit predictions for individual patients. Further studies should determine whether the baseline hazard function requires recalibration.
Copyright © 2022 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Entities:  

Keywords:  PREDICT Breast; Progesterone receptor; Prognosis; breast cancer

Mesh:

Substances:

Year:  2022        PMID: 35933885     DOI: 10.1016/j.ejca.2022.06.011

Source DB:  PubMed          Journal:  Eur J Cancer        ISSN: 0959-8049            Impact factor:   10.002


  1 in total

1.  Development and validation of an extended Cox prognostic model for patients with ER/PR+ and HER2- breast cancer: a retrospective cohort study.

Authors:  Yiqun Xie; Xizhou Li; Ying Wu; Wenting Cui; Yang Liu
Journal:  World J Surg Oncol       Date:  2022-10-12       Impact factor: 3.253

  1 in total

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