Incorporating progesterone receptor expression into the PREDICT breast prognostic model
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Incorporating progesterone receptor expression into the PREDICT breast prognostic model. / ABCTB Investigators; kConFab Investigators.
I: European Journal of Cancer, Bind 173, 2022, s. 178-193.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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TY - JOUR
T1 - Incorporating progesterone receptor expression into the PREDICT breast prognostic model
AU - Grootes, Isabelle
AU - Keeman, Renske
AU - Blows, Fiona M.
AU - Milne, Roger L.
AU - Giles, Graham G.
AU - Swerdlow, Anthony J.
AU - Fasching, Peter A.
AU - Abubakar, Mustapha
AU - Andrulis, Irene L.
AU - Anton-Culver, Hoda
AU - Beckmann, Matthias W.
AU - Blomqvist, Carl
AU - Bojesen, Stig E.
AU - Bolla, Manjeet K.
AU - Bonanni, Bernardo
AU - Briceno, Ignacio
AU - Burwinkel, Barbara
AU - Camp, Nicola J.
AU - Castelao, Jose E.
AU - Choi, Ji-Yeob
AU - Clarke, Christine L.
AU - Couch, Fergus J.
AU - Cox, Angela
AU - Cross, Simon S.
AU - Czene, Kamila
AU - Devilee, Peter
AU - Dork, Thilo
AU - Dunning, Alison M.
AU - Dwek, Miriam
AU - Easton, Douglas F.
AU - Eccles, Diana M.
AU - Eriksson, Mikael
AU - Ernst, Kristina
AU - Evans, D. Gareth
AU - Figueroa, Jonine D.
AU - Fink, Visnja
AU - Floris, Giuseppe
AU - Fox, Stephen
AU - Gabrielson, Marike
AU - Gago-Dominguez, Manuela
AU - Garcia-Saenz, Jose A.
AU - Gonzalez-Neira, Anna
AU - Haeberle, Lothar
AU - Haiman, Christopher A.
AU - Hall, Per
AU - Hamann, Ute
AU - Harkness, Elaine F.
AU - Hartman, Mikael
AU - Hein, Alexander
AU - Hooning, Maartje J.
AU - ABCTB Investigators
AU - kConFab Investigators
PY - 2022
Y1 - 2022
N2 - 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 x 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 predic-tions for individual patients. Further studies should determine whether the baseline hazard function requires recalibration. (C) 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
AB - 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 x 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 predic-tions for individual patients. Further studies should determine whether the baseline hazard function requires recalibration. (C) 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
KW - Prognosis
KW - PREDICT Breast
KW - breast cancer
KW - Progesterone receptor
KW - ADJUVANT TAMOXIFEN
KW - ESTROGEN-RECEPTOR
KW - CANCER PATIENTS
KW - THERAPY
U2 - 10.1016/j.ejca.2022.06.011
DO - 10.1016/j.ejca.2022.06.011
M3 - Journal article
C2 - 35933885
VL - 173
SP - 178
EP - 193
JO - European Journal of Cancer, Supplement
JF - European Journal of Cancer, Supplement
SN - 0959-8049
ER -
ID: 327946675