Literature DB >> 19485842

Molecular biomarkers to individualise treatment: assessing the evidence.

Chee K Lee1, Sarah J Lord, Alan S Coates, R John Simes.   

Abstract

The absolute benefit of a treatment varies between individuals depending on their prognosis before treatment and whether their response to the treatment varies from the overall relative risk reduction measured in clinical trials. Based on these principles, biomarkers that can provide information about an individual's prognosis or predict his or her treatment response can be used to tailor treatment decisions to individual patients. Many novel molecular biomarkers are currently available. Although there is evidence to show that some of these can improve patient outcomes through improved biomarker-guided treatment strategies, others are yet to be adequately evaluated. Randomised controlled trials (RCTs) can distinguish whether a biomarker provides prognostic or predictive information and assess whether using a biomarker to guide treatment improves patient outcomes. Targeted RCTs can be used to demonstrate the efficacy of treatment in a restricted biomarker-defined population, and non-targeted RCTs can compare biomarker-guided versus conventional test-guided treatment strategies in broader populations.

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Year:  2009        PMID: 19485842

Source DB:  PubMed          Journal:  Med J Aust        ISSN: 0025-729X            Impact factor:   7.738


  10 in total

Review 1.  Preclinical strategies to define predictive biomarkers for therapeutically relevant cancer subtypes.

Authors:  Marina Pajic; Christopher J Scarlett; David K Chang; Robert L Sutherland; Andrew V Biankin
Journal:  Hum Genet       Date:  2011-04-23       Impact factor: 4.132

Review 2.  Patient-centric trials for therapeutic development in precision oncology.

Authors:  Andrew V Biankin; Steven Piantadosi; Simon J Hollingsworth
Journal:  Nature       Date:  2015-10-15       Impact factor: 49.962

Review 3.  Biomarker-Guided Non-Adaptive Trial Designs in Phase II and Phase III: A Methodological Review.

Authors:  Miranta Antoniou; Ruwanthi Kolamunnage-Dona; Andrea L Jorgensen
Journal:  J Pers Med       Date:  2017-01-25

Review 4.  Extrapolating evidence for molecularly targeted therapies from common to rare cancers: a scoping review of methodological guidance.

Authors:  Doah Cho; Saskia Cheyne; Sarah J Lord; John Simes; Chee Khoon Lee
Journal:  BMJ Open       Date:  2022-07-12       Impact factor: 3.006

5.  Glutathione S-transferase Pi expression predicts response to adjuvant chemotherapy for stage C colon cancer: a matched historical control study.

Authors:  Lucy Jankova; Graham Robertson; Charles Chan; King L Tan; Maija Kohonen-Corish; Caroline L-S Fung; Candice Clarke; Betty P C Lin; Mark Molloy; Pierre H Chapuis; Les Bokey; Owen F Dent; Stephen J Clarke
Journal:  BMC Cancer       Date:  2012-05-28       Impact factor: 4.430

Review 6.  Somatic variation and cancer: therapies lost in the mix.

Authors:  Andrew V Biankin; Thomas J Hudson
Journal:  Hum Genet       Date:  2011-06-05       Impact factor: 5.881

7.  Assessing personalized medicines in Australia: a national framework for reviewing codependent technologies.

Authors:  Tracy Merlin; Claude Farah; Camille Schubert; Andrew Mitchell; Janet E Hiller; Philip Ryan
Journal:  Med Decis Making       Date:  2012-08-15       Impact factor: 2.583

Review 8.  Biomarker-Guided Adaptive Trial Designs in Phase II and Phase III: A Methodological Review.

Authors:  Miranta Antoniou; Andrea L Jorgensen; Ruwanthi Kolamunnage-Dona
Journal:  PLoS One       Date:  2016-02-24       Impact factor: 3.240

9.  Fool's gold, lost treasures, and the randomized clinical trial.

Authors:  David J Stewart; Razelle Kurzrock
Journal:  BMC Cancer       Date:  2013-04-16       Impact factor: 4.430

10.  Randomized test-treatment studies with an outlook on adaptive designs.

Authors:  Werner Vach; Antonia Zapf; Amra Hot; Patrick M Bossuyt; Oke Gerke; Simone Wahl
Journal:  BMC Med Res Methodol       Date:  2021-06-01       Impact factor: 4.615

  10 in total

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