Dynamic prediction in breast cancer: proving feasibility in clinical practice using the TEAM trial

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Standard

Dynamic prediction in breast cancer : proving feasibility in clinical practice using the TEAM trial. / Fontein, D B Y; Klinten Grand, M; Nortier, J W R; Seynaeve, C; Meershoek-Klein Kranenbarg, E; Dirix, L Y; van de Velde, C J H; Putter, H.

I: Annals of Oncology, Bind 26, Nr. 6, 06.2015, s. 1254-62.

Publikation: Bidrag til tidsskriftTidsskriftartikelfagfællebedømt

Harvard

Fontein, DBY, Klinten Grand, M, Nortier, JWR, Seynaeve, C, Meershoek-Klein Kranenbarg, E, Dirix, LY, van de Velde, CJH & Putter, H 2015, 'Dynamic prediction in breast cancer: proving feasibility in clinical practice using the TEAM trial', Annals of Oncology, bind 26, nr. 6, s. 1254-62. https://doi.org/10.1093/annonc/mdv146

APA

Fontein, D. B. Y., Klinten Grand, M., Nortier, J. W. R., Seynaeve, C., Meershoek-Klein Kranenbarg, E., Dirix, L. Y., van de Velde, C. J. H., & Putter, H. (2015). Dynamic prediction in breast cancer: proving feasibility in clinical practice using the TEAM trial. Annals of Oncology, 26(6), 1254-62. https://doi.org/10.1093/annonc/mdv146

Vancouver

Fontein DBY, Klinten Grand M, Nortier JWR, Seynaeve C, Meershoek-Klein Kranenbarg E, Dirix LY o.a. Dynamic prediction in breast cancer: proving feasibility in clinical practice using the TEAM trial. Annals of Oncology. 2015 jun.;26(6):1254-62. https://doi.org/10.1093/annonc/mdv146

Author

Fontein, D B Y ; Klinten Grand, M ; Nortier, J W R ; Seynaeve, C ; Meershoek-Klein Kranenbarg, E ; Dirix, L Y ; van de Velde, C J H ; Putter, H. / Dynamic prediction in breast cancer : proving feasibility in clinical practice using the TEAM trial. I: Annals of Oncology. 2015 ; Bind 26, Nr. 6. s. 1254-62.

Bibtex

@article{e943194865b549e9a3f9ac031366e9b1,
title = "Dynamic prediction in breast cancer: proving feasibility in clinical practice using the TEAM trial",
abstract = "BACKGROUND: Predictive models are an integral part of current clinical practice and help determine optimal treatment strategies for individual patients. A drawback is that covariates are assumed to have constant effects on overall survival (OS), when in fact, these effects may change during follow-up (FU). Furthermore, breast cancer (BC) patients may experience events that alter their prognosis from that time onwards. We investigated the 'dynamic' effects of different covariates on OS and developed a nomogram to calculate 5-year dynamic OS (DOS) probability at different prediction timepoints (tP) during FU.METHODS: Dutch and Belgian postmenopausal, endocrine-sensitive, early BC patients enrolled in the TEAM trial were included. We assessed time-varying effects of specific covariates and obtained 5-year DOS predictions using a proportional baselines landmark supermodel. Covariates included age, histological grade, hormone receptor and HER2 status, T- and N-stage, locoregional recurrence (LRR), distant recurrence, and treatment compliance. A nomogram was designed to calculate 5-year DOS based on individual characteristics.RESULTS: A total of 2602 patients were included (mean FU 6.2 years). N-stage, LRR, and HER2 status demonstrated time-varying effects on 5-year DOS. Hazard ratio (HR) functions for LRR, high-risk N-stage (N2/3), and HER2 positivity were HR = (8.427 × 0.583[Formula: see text], HR = (3.621 × 0.816[Formula: see text], and HR = (1.235 × 0.851[Formula: see text], respectively. Treatment discontinuation was associated with a higher mortality risk, but without a time-varying effect [HR 1.263 (0.867-1.841)]. All other covariates were time-constant.DISCUSSION: The current nomogram accounts for elapsed time since starting adjuvant endocrine treatment and optimizes prediction of individual 5-year DOS during FU for postmenopausal, endocrine-sensitive BC patients. The nomogram can facilitate in determining whether further therapy will benefit an individual patient, although validation in an independent dataset is still needed.",
keywords = "Adult, Aged, Aged, 80 and over, Antineoplastic Agents, Hormonal/adverse effects, Belgium, Biomarkers, Tumor/analysis, Breast Neoplasms/chemistry, Chemotherapy, Adjuvant, Decision Support Techniques, Feasibility Studies, Female, Humans, Mastectomy/adverse effects, Middle Aged, Neoplasm Recurrence, Local, Neoplasm Staging, Netherlands, Nomograms, Patient Selection, Predictive Value of Tests, Receptor, ErbB-2/analysis, Risk Assessment, Risk Factors, Survival Analysis, Time Factors, Treatment Outcome",
author = "Fontein, {D B Y} and {Klinten Grand}, M and Nortier, {J W R} and C Seynaeve and {Meershoek-Klein Kranenbarg}, E and Dirix, {L Y} and {van de Velde}, {C J H} and H Putter",
note = "{\textcopyright} The Author 2015. Published by Oxford University Press on behalf of the European Society for Medical Oncology. All rights reserved. For permissions, please email: journals.permissions@oup.com.",
year = "2015",
month = jun,
doi = "10.1093/annonc/mdv146",
language = "English",
volume = "26",
pages = "1254--62",
journal = "Annals of Oncology",
issn = "0923-7534",
publisher = "Oxford University Press",
number = "6",

}

RIS

TY - JOUR

T1 - Dynamic prediction in breast cancer

T2 - proving feasibility in clinical practice using the TEAM trial

AU - Fontein, D B Y

AU - Klinten Grand, M

AU - Nortier, J W R

AU - Seynaeve, C

AU - Meershoek-Klein Kranenbarg, E

AU - Dirix, L Y

AU - van de Velde, C J H

AU - Putter, H

N1 - © The Author 2015. Published by Oxford University Press on behalf of the European Society for Medical Oncology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

PY - 2015/6

Y1 - 2015/6

N2 - BACKGROUND: Predictive models are an integral part of current clinical practice and help determine optimal treatment strategies for individual patients. A drawback is that covariates are assumed to have constant effects on overall survival (OS), when in fact, these effects may change during follow-up (FU). Furthermore, breast cancer (BC) patients may experience events that alter their prognosis from that time onwards. We investigated the 'dynamic' effects of different covariates on OS and developed a nomogram to calculate 5-year dynamic OS (DOS) probability at different prediction timepoints (tP) during FU.METHODS: Dutch and Belgian postmenopausal, endocrine-sensitive, early BC patients enrolled in the TEAM trial were included. We assessed time-varying effects of specific covariates and obtained 5-year DOS predictions using a proportional baselines landmark supermodel. Covariates included age, histological grade, hormone receptor and HER2 status, T- and N-stage, locoregional recurrence (LRR), distant recurrence, and treatment compliance. A nomogram was designed to calculate 5-year DOS based on individual characteristics.RESULTS: A total of 2602 patients were included (mean FU 6.2 years). N-stage, LRR, and HER2 status demonstrated time-varying effects on 5-year DOS. Hazard ratio (HR) functions for LRR, high-risk N-stage (N2/3), and HER2 positivity were HR = (8.427 × 0.583[Formula: see text], HR = (3.621 × 0.816[Formula: see text], and HR = (1.235 × 0.851[Formula: see text], respectively. Treatment discontinuation was associated with a higher mortality risk, but without a time-varying effect [HR 1.263 (0.867-1.841)]. All other covariates were time-constant.DISCUSSION: The current nomogram accounts for elapsed time since starting adjuvant endocrine treatment and optimizes prediction of individual 5-year DOS during FU for postmenopausal, endocrine-sensitive BC patients. The nomogram can facilitate in determining whether further therapy will benefit an individual patient, although validation in an independent dataset is still needed.

AB - BACKGROUND: Predictive models are an integral part of current clinical practice and help determine optimal treatment strategies for individual patients. A drawback is that covariates are assumed to have constant effects on overall survival (OS), when in fact, these effects may change during follow-up (FU). Furthermore, breast cancer (BC) patients may experience events that alter their prognosis from that time onwards. We investigated the 'dynamic' effects of different covariates on OS and developed a nomogram to calculate 5-year dynamic OS (DOS) probability at different prediction timepoints (tP) during FU.METHODS: Dutch and Belgian postmenopausal, endocrine-sensitive, early BC patients enrolled in the TEAM trial were included. We assessed time-varying effects of specific covariates and obtained 5-year DOS predictions using a proportional baselines landmark supermodel. Covariates included age, histological grade, hormone receptor and HER2 status, T- and N-stage, locoregional recurrence (LRR), distant recurrence, and treatment compliance. A nomogram was designed to calculate 5-year DOS based on individual characteristics.RESULTS: A total of 2602 patients were included (mean FU 6.2 years). N-stage, LRR, and HER2 status demonstrated time-varying effects on 5-year DOS. Hazard ratio (HR) functions for LRR, high-risk N-stage (N2/3), and HER2 positivity were HR = (8.427 × 0.583[Formula: see text], HR = (3.621 × 0.816[Formula: see text], and HR = (1.235 × 0.851[Formula: see text], respectively. Treatment discontinuation was associated with a higher mortality risk, but without a time-varying effect [HR 1.263 (0.867-1.841)]. All other covariates were time-constant.DISCUSSION: The current nomogram accounts for elapsed time since starting adjuvant endocrine treatment and optimizes prediction of individual 5-year DOS during FU for postmenopausal, endocrine-sensitive BC patients. The nomogram can facilitate in determining whether further therapy will benefit an individual patient, although validation in an independent dataset is still needed.

KW - Adult

KW - Aged

KW - Aged, 80 and over

KW - Antineoplastic Agents, Hormonal/adverse effects

KW - Belgium

KW - Biomarkers, Tumor/analysis

KW - Breast Neoplasms/chemistry

KW - Chemotherapy, Adjuvant

KW - Decision Support Techniques

KW - Feasibility Studies

KW - Female

KW - Humans

KW - Mastectomy/adverse effects

KW - Middle Aged

KW - Neoplasm Recurrence, Local

KW - Neoplasm Staging

KW - Netherlands

KW - Nomograms

KW - Patient Selection

KW - Predictive Value of Tests

KW - Receptor, ErbB-2/analysis

KW - Risk Assessment

KW - Risk Factors

KW - Survival Analysis

KW - Time Factors

KW - Treatment Outcome

U2 - 10.1093/annonc/mdv146

DO - 10.1093/annonc/mdv146

M3 - Journal article

C2 - 25862439

VL - 26

SP - 1254

EP - 1262

JO - Annals of Oncology

JF - Annals of Oncology

SN - 0923-7534

IS - 6

ER -

ID: 197857557