Literature DB >> 23618694

Pitfalls in outcome prediction of breast cancer.

Emad A Rakha1.   

Abstract

Breast cancer represents a heterogeneous group of diseases with varied presentation, morphological and biological features, behaviour, and response to therapy. Management of breast cancer relies on availability of robust predictive and prognostic factors to support decision making. Identifying and validating the prognostic and predictive value of a given marker is based on studying its association with clinical outcome with or without consideration for therapy, respectively. In the field of cancer research, clinical outcome is determined by assessing certain time-dependent events: 'endpoints' such as tumour progression, recurrence and patient mortality. Guidelines for reporting tumour markers have been published and there is a perception that outcome determination in breast cancer is well documented. However, reviewing the literature has highlighted the varied use of definitions used in clinical outcome measures and there are pitfalls in outcome analysis. This may have contributed to the discrepancies in the literature and to the inconsistent conclusions seen in published studies assessing the same markers. Identification of these pitfalls is expected to improve prognostic and predictive marker assessment. Here issues related to outcome determination in breast cancer including definitions and pitfalls and some critical views are presented.

Entities:  

Keywords:  BREAST; BREAST CANCER; BREAST PATHOLOGY

Mesh:

Substances:

Year:  2013        PMID: 23618694     DOI: 10.1136/jclinpath-2012-201083

Source DB:  PubMed          Journal:  J Clin Pathol        ISSN: 0021-9746            Impact factor:   3.411


  21 in total

Review 1.  Molecular and cellular heterogeneity in breast cancer: challenges for personalized medicine.

Authors:  Ashley G Rivenbark; Siobhan M O'Connor; William B Coleman
Journal:  Am J Pathol       Date:  2013-08-27       Impact factor: 4.307

2.  Decreased expression of SOX17 is associated with tumor progression and poor prognosis in breast cancer.

Authors:  De-Yuan Fu; Hao-Sheng Tan; Jin-Li Wei; Chang-Ren Zhu; Ji-Xin Jiang; Yu-Xiang Zhu; Feng-Lin Cai; Mei-Hong Chong; Chuan-Li Ren
Journal:  Tumour Biol       Date:  2015-05-14

3.  IL6 Signaling in Peripheral Blood T Cells Predicts Clinical Outcome in Breast Cancer.

Authors:  Lei Wang; Andrea K Miyahira; Diana L Simons; Xuyang Lu; Andrew Y Chang; Carrie Wang; Maria A Suni; Vernon C Maino; Frederick M Dirbas; John Yim; James Waisman; Peter P Lee
Journal:  Cancer Res       Date:  2016-11-22       Impact factor: 12.701

4.  Erythropoietin-producing hepatocellular A6 overexpression is a novel biomarker of poor prognosis in patients with breast cancer.

Authors:  Danmei Zhou; Kehan Ren; Jigang Wang; Hong Ren; Wenlin Yang; Wenjuan Wang; Qiong Li; Xiuping Liu; Feng Tang
Journal:  Oncol Lett       Date:  2018-02-01       Impact factor: 2.967

5.  Serine-arginine protein kinase 1 is associated with breast cancer progression and poor patient survival.

Authors:  Xing-hua Li; Jun-wei Song; Jun-ling Liu; Shu Wu; Le-shi Wang; Li-yun Gong; Xi Lin
Journal:  Med Oncol       Date:  2014-06-25       Impact factor: 3.064

6.  Prognostic factors in metaplastic carcinoma of the breast: a multi-institutional study.

Authors:  E A Rakha; P H Tan; Z Varga; G M Tse; A M Shaaban; F Climent; C H M van Deurzen; D Purnell; D Dodwell; T Chan; I O Ellis
Journal:  Br J Cancer       Date:  2014-11-25       Impact factor: 7.640

7.  Phosphoprotein secretome of tumor cells as a source of candidates for breast cancer biomarkers in plasma.

Authors:  Anna M Zawadzka; Birgit Schilling; Michael P Cusack; Alexandria K Sahu; Penelope Drake; Susan J Fisher; Christopher C Benz; Bradford W Gibson
Journal:  Mol Cell Proteomics       Date:  2014-02-06       Impact factor: 5.911

8.  Early diagnostic value of survivin and its alternative splice variants in breast cancer.

Authors:  Salma Khan; Heather Ferguson Bennit; David Turay; Mia Perez; Saied Mirshahidi; Yuan Yuan; Nathan R Wall
Journal:  BMC Cancer       Date:  2014-03-12       Impact factor: 4.430

Review 9.  Computational prognostic indicators for breast cancer.

Authors:  Xinan Yang; Xindi Ai; John M Cunningham
Journal:  Cancer Manag Res       Date:  2014-07-12       Impact factor: 3.989

10.  Molecular breast cancer subtypes and therapies in a public hospital of northeastern Brazil.

Authors:  Ana Cláudia de Macêdo Andrade; Carlos Alberis Ferreira Júnior; Beatriz Dantas Guimarães; Ana Waleska Pessoa Barros; Gibran Sarmento de Almeida; Mathias Weller
Journal:  BMC Womens Health       Date:  2014-09-12       Impact factor: 2.809

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