Biomarkers, subgroup evaluation, and clinical trial design

Discovery Medicine

Volumn 13, Issue 70, 2012, Pages 187-192

  Baker, Stuart G ^a   Kramer, Barnett S ^a   Sargent, Daniel J ^b   Bonetti, Marco ^c  

^a NATIONAL CANCER INSTITUTE   (United States)

^b MAYO CLINIC   (United States)

^c BOCCONI UNIVERSITY   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

BIOLOGICAL MARKER;

ARTICLE; CLINICAL TRIAL (TOPIC); GENE MUTATION; GENETIC ANALYSIS; GENETIC MARKER; HUMAN; K RAS MUTATION; MALIGNANT NEOPLASM; MATHEMATICAL MODEL; MELANOMA; ONCOGENE K RAS; OUTCOME ASSESSMENT; PHARMACOGENETIC TESTING; PHARMACOGENETICS; PHASE 3 CLINICAL TRIAL (TOPIC); PROGNOSTIC ASSESSMENT; RANDOMIZED CONTROLLED TRIAL (TOPIC); RESEARCH DIAGNOSTIC CRITERIA; STATISTICAL ANALYSIS; CASE CONTROL STUDY; COHORT ANALYSIS; EVALUATION; METABOLISM; REVIEW;

BIOLOGICAL MARKERS; CASE-CONTROL STUDIES; CLINICAL TRIALS AS TOPIC; COHORT STUDIES; EVALUATION STUDIES AS TOPIC; HUMANS;

EID: 84866791471     PISSN: 15396509     EISSN: 19447930     Source Type: Journal    
DOI: None     Document Type: Article

References (22)

1. Achan J, Talisuna AO, Erhart A, Yeka A, Tibenderana JK, Baliraine FN, Rosenthal PJ, Alessandro UD. Quinine, an old anti-malarial drug in a modern world: role in the treatment of malaria. Malaria J 10:144, 2011
2. Baker SG, Freedman LS. Potential impact of genetic testing on cancer prevention trials, using breast cancer as an example. J Natl Cancer Inst 87:1137-1144, 1995
3. Baker SG, Kramer BS. Statistics for weighing benefits and harms in a proposed genetic substudy of a randomized cancer prevention trial. Appl Stat 54(5):941-954, 2005
4. Bonetti M, Gelber RD. A graphical method to assess treatment-covariate interactions using the cox model on subsets of the data. Stat Med 19:2595-2609, 2000
5. Bonetti M, Gelber RD. Patterns of treatment effects in subsets of patients in clinical trials. Biostatistics 5:465-481, 2005
6. Cai T, Tian L, Wong PH, Wei LJ. Analysis of randomized comparative clinical trial data for personalized treatment selections. Biostatistics 12(2):270-282, 2011
7. Chapman PB, Hauschild A, Robert C, Larkin JMG,. Haanen J B AG, Ribas A, Hogg D, Day S, Ascierto PA, Testori A, Lorigan P, Dummer R, Sosman JA, Garbe C, Lee RJ, Nolop KB, Nelson B, Hou J, Flaherty KT, McArthur G A. Phase III randomized, open-label, multicenter trial (BRIM3) comparing BRAF inhibitor vemurafenib with dacarbazine (DTIC) in patients with V600EBRAF-mutated melanoma. J Clin Oncol 29(suppl), abstract #LBA4, 2011
8. Costigan T. Bonferroni inequalities and intervals In: Encyclopedia of Biostatistics. Armitage P, Colton T (eds.). Volume 1, pp. 421-425, John Wiley & Sons, Ltd., Chichester, UK, 1998
9. Dahabreh IJ, Terasawa T, Castaldi PJ, Trikalinos TA. Systematic review: anti-epidermal growth factor receptor treatment effect modification by KRAS mutations in advanced colorectal cancer. Ann Internal Med 154(1):37-49, 2011
10. Foster JC, Taylor JMG, Ruber SJ. Subgroup identification from randomized clinical trial data. Stat Med 30(24):2867-2880, 2011
11. Freidlin B, McShane LM, Korn EL. Randomized clinical trials with biomarkers: design issues J Natl Cancer Inst 102(3):152-160, 2010
12. Freidlin B, Simon R. Adaptive signature design: an adaptive clinical trial design for generating and prospectively testing a gene expression signature for sensitive patients. Clin Cancer Res 11(21):7872-7878, 2005
13. Hand DJ. Classifier technology and the illusion of progress. Statist Sci 21(1):1-14, 2006
14. Hopkins MM, Ibarreta D, Gaisser S, Enzing CM, Ryan J, Martin PA, Lewis G, Detmar S, van den Akker-van Marle ME, Hedgecoe, AM, Nightingale P, Dreiling M, Hartig KJ, Vullings W, Forde T. Putting pharmocogenetics into practice. Nat Biotechnol 24(4):403-410, 2006
15. Janes H, Pepe MS, Bossuyt PM, Barlow WE. Measuring the performance of markers for guiding treatment decisions. Ann Intern Med 154(4):253-259, 2011
16. Jiang W, Freidlin B, Simon R. Biomarker-adaptive threshold design: a procedure for evaluating treatment with possible biomarker-defined subset effect. J Natl Cancer Inst 99(13):1036-1043, 2007
17. King MC, Wieand S, Hale K, Lee M, Walsh T, Owens K, Tait J, Ford L, Dunn BK, Costantino J, Wickerham L, Wolmark N, Fisher B; National Surgical Adjuvant Breast and Bowel Project. Tamoxifen and breast cancer incidence among women with inherited mutations in BRCA1 and BRCA2: National Surgical Adjuvant Breast and Bowel Project (NSABP-P1) Breast Cancer Prevention Trial. JAMA 286(18):2251-2256, 2001
18. Parker TL, Strout MP. Chronic lymphocytic leukemia: prognostic factors and impact on treatment. Discov Med 11(4):115-123, 2011
19. RansohoffDF. Evaluating discovery-based research: when biologic reasoning cannot work. Gastroenterology 127:1028, 2004
20. Sargent DJ, Conley BA, Allegra C, Collete L. Clinical trial designs for predictive marker validation in cancer treatment trials. J Clin Oncol 23(9):2020-2227, 2005
21. Song X, Pepe MS. Evaluating markers for selecting a patient's treatment. Biometrics 60(4):874-883, 2004
22. Vickers AJ, Kattan MW, Sargent DJ. Method for evaluating prediction models that apply the results of randomized trials to individual patients. Trials 9:14, 2007