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ABSTRACT: Background
Data characterising long-term survivors (LTS) with human epidermal growth factor receptor 2 (HER2)-positive metastatic breast cancer (MBC) are limited. This analysis describes LTS using registHER observational study data.Methods
A latent class modelling (LCM) approach was used to identify distinct homogenous patient groups (or classes) based on progression-free survival (PFS), overall survival, and complete response. Demographics, clinicopathologic factors, first-line treatment patterns, and clinical outcomes were described for each class. Class-associated factors were evaluated using logistic regression analysis.Results
LCM identified two survivor groups labelled as LTS (n=244) and short-term survivors (STS; n=757). Baseline characteristics were similar between groups, although LTS were more likely to be white (83.6% vs 77.8%) with oestrogen receptor-positive (ER+) or progesterone receptor-positive (PgR+) disease (59.4% vs 50.9%). Median PFS in LTS was 37.2 (95% confidence interval (CI): 32.9-40.5) vs 7.3 months (95% CI: 6.8-8.0) in STS. Factors associated with long-term survival included ER+ or PgR+ disease, metastasis to node/local sites, first-line trastuzumab use, and first-line taxane use.Conclusions
Prognostic variables identified by LCM define a HER2-positive MBC patient profile and therapies that may be associated with more favourable long-term outcomes, enabling treatment selection appropriate to the patient's disease characteristics.
SUBMITTER: Yardley DA
PROVIDER: S-EPMC4037822 | biostudies-literature | 2014 May
REPOSITORIES: biostudies-literature
Yardley D A DA Tripathy D D Brufsky A M AM Rugo H S HS Kaufman P A PA Mayer M M Magidson J J Yoo B B Quah C C Ulcickas Yood M M
British journal of cancer 20140417 11
<h4>Background</h4>Data characterising long-term survivors (LTS) with human epidermal growth factor receptor 2 (HER2)-positive metastatic breast cancer (MBC) are limited. This analysis describes LTS using registHER observational study data.<h4>Methods</h4>A latent class modelling (LCM) approach was used to identify distinct homogenous patient groups (or classes) based on progression-free survival (PFS), overall survival, and complete response. Demographics, clinicopathologic factors, first-line ...[more]