Literature DB >> 26932435

Statistical aspect of translational and correlative studies in clinical trials.

Herbert Pang1, Xiaofei Wang2.   

Abstract

In this article, we describe statistical issues related to the conduct of translational and correlative studies in cancer clinical trials. In the era of personalized medicine, proper biomarker discovery and validation is crucial for producing groundbreaking research. In order to carry out the framework outlined in this article, a team effort between oncologists and statisticians is the key for success.

Entities:  

Keywords:  Big data; bioinformatics; biomarkers; oncology; personalized medicine; translational science

Mesh：

Substances：

Year:  2016        PMID： 26932435      PMCID： PMC4780353          DOI： 10.3978/j.issn.2304-3865.2014.07.04

Source DB:  PubMed          Journal:  Chin Clin Oncol        ISSN： 2304-3865


  21 in total

1.  Reporting Recommendations for Tumor Marker Prognostic Studies (REMARK): explanation and elaboration.

Authors:  Douglas G Altman; Lisa M McShane; Willi Sauerbrei; Sheila E Taube
Journal:  PLoS Med       Date:  2012-05-29       Impact factor: 11.069

2.  Sample size planning for developing classifiers using high-dimensional DNA microarray data.

Authors:  Kevin K Dobbin; Richard M Simon
Journal:  Biostatistics       Date:  2006-04-13       Impact factor: 5.899

3.  The Brief Pain Inventory and its "pain at its worst in the last 24 hours" item: clinical trial endpoint considerations.

Authors:  Thomas M Atkinson; Tito R Mendoza; Laura Sit; Steven Passik; Howard I Scher; Charles Cleeland; Ethan Basch
Journal:  Pain Med       Date:  2010-01-15       Impact factor: 3.750

4.  Use of archived specimens in evaluation of prognostic and predictive biomarkers.

Authors:  Richard M Simon; Soonmyung Paik; Daniel F Hayes
Journal:  J Natl Cancer Inst       Date:  2009-10-08       Impact factor: 13.506

5.  Pathway analysis using random forests with bivariate node-split for survival outcomes.

Authors:  Herbert Pang; Debayan Datta; Hongyu Zhao
Journal:  Bioinformatics       Date:  2009-11-18       Impact factor: 6.937

6.  Pathway-based identification of SNPs predictive of survival.

Authors:  Herbert Pang; Michael Hauser; Stéphane Minvielle
Journal:  Eur J Hum Genet       Date:  2011-02-02       Impact factor: 4.246

7.  Evaluating the yield of medical tests.

Authors:  F E Harrell; R M Califf; D B Pryor; K L Lee; R A Rosati
Journal:  JAMA       Date:  1982-05-14       Impact factor: 56.272

8.  Prognostic and predictive blood-based biomarkers in patients with advanced pancreatic cancer: results from CALGB80303 (Alliance).

Authors:  Andrew B Nixon; Herbert Pang; Mark D Starr; Paula N Friedman; Monica M Bertagnolli; Hedy L Kindler; Richard M Goldberg; Alan P Venook; Herbert I Hurwitz
Journal:  Clin Cancer Res       Date:  2013-10-04       Impact factor: 12.531

9.  Sample size considerations of prediction-validation methods in high-dimensional data for survival outcomes.

Authors:  Herbert Pang; Sin-Ho Jung
Journal:  Genet Epidemiol       Date:  2013-03-07       Impact factor: 2.135

10.  PGC-1alpha-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes.

Authors:  Vamsi K Mootha; Cecilia M Lindgren; Karl-Fredrik Eriksson; Aravind Subramanian; Smita Sihag; Joseph Lehar; Pere Puigserver; Emma Carlsson; Martin Ridderstråle; Esa Laurila; Nicholas Houstis; Mark J Daly; Nick Patterson; Jill P Mesirov; Todd R Golub; Pablo Tamayo; Bruce Spiegelman; Eric S Lander; Joel N Hirschhorn; David Altshuler; Leif C Groop
Journal:  Nat Genet       Date:  2003-07       Impact factor: 38.330
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