Literature DB >> 10066089

Assessing the clinical impact of prognostic factors: when is "statistically significant" clinically useful?

D F Hayes1, B Trock, A L Harris.   

Abstract

Very few tumor markers have been recommended for routine clinical care of patients with breast cancer. A framework to determine the clinical utility of tumor markers is required. In a previous publication, a "Tumor Marker Utility Grading System" (TMUGS) was proposed. TMUGS included a semi-quantitative grading scale (0-3+) which can be used to assign a score to a given tumor marker for a given outcome. Only those markers that are felt to be sufficiently strong to influence a therapeutic decision that results in improved clinical outcome for the patient are recommended. The studies from which data are used to assign a TMUGS grade can be placed into one of five Levels of Evidence (LOE). An extension of TMUGS ("TMUGS-Plus") is now proposed in which the relative strength of a prognostic or predictive factor can be estimated and expressed in terms of a risk ratio (RR) for prognostic factors or benefit ratio (BR) for predictive factors. Three categories of prognostic factors and three categories of predictive factors are proposed (strong, moderate, and weak). It is recommended that only LOE type I studies (prospective, highly powered studies of the tumor marker, or meta-analysis of LOE II or III datasets), be used to estimate the RR or BR of a given factor. Finally, a matrix, based on assumptions of acceptable absolute benefits relative to risks, is proposed in which any given tumor marker can be assessed for its clinical utility. TMUGS-Plus should aid in the assessment of published data regarding clinical utility of tumor markers. Perhaps more important, clinical investigators can use TMUGS-Plus to design tumor marker studies that will fulfill criteria for clinical utility, resulting in more rapid acceptance of tumor markers for routine clinical use.

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Year:  1998        PMID: 10066089     DOI: 10.1023/a:1006197805041

Source DB:  PubMed          Journal:  Breast Cancer Res Treat        ISSN: 0167-6806            Impact factor:   4.872


  31 in total

Review 1.  Prognostic factors in breast cancer: current and new predictors of metastasis.

Authors:  D F Hayes; C Isaacs; V Stearns
Journal:  J Mammary Gland Biol Neoplasia       Date:  2001-10       Impact factor: 2.673

Review 2.  Biomarkers and surrogate end points--the challenge of statistical validation.

Authors:  Marc Buyse; Daniel J Sargent; Axel Grothey; Alastair Matheson; Aimery de Gramont
Journal:  Nat Rev Clin Oncol       Date:  2010-04-06       Impact factor: 66.675

3.  [Prognostic and predictive factors of invasive breast cancer: update 2009].

Authors:  T Decker; D Hungermann; W Böcker
Journal:  Pathologe       Date:  2009-02       Impact factor: 1.011

4.  Gene expression of the mismatch repair gene MSH2 in primary colorectal cancer.

Authors:  Lars Henrik Jensen; Hidekazu Kuramochi; Dorthe Gylling Crüger; Jan Lindebjerg; Steen Kolvraa; Peter Danenberg; Kathleen Danenberg; Anders Jakobsen
Journal:  Tumour Biol       Date:  2011-07-06

5.  E2F4 Program Is Predictive of Progression and Intravesical Immunotherapy Efficacy in Bladder Cancer.

Authors:  Chao Cheng; Frederick S Varn; Carmen J Marsit
Journal:  Mol Cancer Res       Date:  2015-06-01       Impact factor: 5.852

Review 6.  Translating metastasis-related biomarkers to the clinic--progress and pitfalls.

Authors:  François-Clément Bidard; Jean-Yves Pierga; Jean-Charles Soria; Jean Paul Thiery
Journal:  Nat Rev Clin Oncol       Date:  2013-02-05       Impact factor: 66.675

7.  Relative efficiency of precision medicine designs for clinical trials with predictive biomarkers.

Authors:  Weichung Joe Shih; Yong Lin
Journal:  Stat Med       Date:  2017-12-04       Impact factor: 2.373

8.  Prediction of outcome of patients with metastatic breast cancer: evaluation with prognostic factors and Nottingham prognostic index.

Authors:  Mu-Tai Liu; Wen-Tao Huang; Ai-Yih Wang; Chia-Chun Huang; Chao-Yuan Huang; Tung-Hao Chang; Chu-Pin Pi; Hao-Han Yang
Journal:  Support Care Cancer       Date:  2009-11-11       Impact factor: 3.603

9.  An algorithm to discover gene signatures with predictive potential.

Authors:  Robin M Hallett; Anna Dvorkin; Christine M Gabardo; John A Hassell
Journal:  J Exp Clin Cancer Res       Date:  2010-09-02

10.  EZH2 is a marker of aggressive breast cancer and promotes neoplastic transformation of breast epithelial cells.

Authors:  Celina G Kleer; Qi Cao; Sooryanarayana Varambally; Ronglai Shen; Ichiro Ota; Scott A Tomlins; Debashis Ghosh; Richard G A B Sewalt; Arie P Otte; Daniel F Hayes; Michael S Sabel; Donna Livant; Stephen J Weiss; Mark A Rubin; Arul M Chinnaiyan
Journal:  Proc Natl Acad Sci U S A       Date:  2003-09-19       Impact factor: 11.205

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