Dynamic prediction in breast cancer: proving feasibility in clinical practice using the TEAM trial
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- Dynamic prediction in breast cancer
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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.
Original language | English |
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Journal | Annals of Oncology |
Volume | 26 |
Issue number | 6 |
Pages (from-to) | 1254-62 |
Number of pages | 9 |
ISSN | 0923-7534 |
DOIs | |
Publication status | Published - Jun 2015 |
- 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
Research areas
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