메뉴 건너뛰기




Volumn 10, Issue 1, 2014, Pages 99-121

An approach to evaluating and comparing biomarkers for patient treatment selection

Author keywords

Interaction; Predictive marker; Prescriptive marker; Randomized trial; Treatment selection marker

Indexed keywords

CYCLOPHOSPHAMIDE; DOXORUBICIN; TAMOXIFEN; TUMOR MARKER;

EID: 84902515144     PISSN: None     EISSN: 15574679     Source Type: Journal    
DOI: 10.1515/ijb-2012-0052     Document Type: Article
Times cited : (42)

References (47)
  • 1
    • 56949087846 scopus 로고    scopus 로고
    • Lost in translation: Problems and pitfalls in translating laboratory observations to clinical utility
    • Simon R. Lost in translation: problems and pitfalls in translating laboratory observations to clinical utility. Eur J Cancer 2008;44:2707-13.
    • (2008) Eur J Cancer , vol.44 , pp. 2707-2713
    • Simon, R.1
  • 3
    • 84868259237 scopus 로고    scopus 로고
    • Prognostic interaction between expression of p53 and estrogen receptor in patients with node-negative breast cancer: Results from IBCSG trials VIII and IX
    • Coates AA, Miller EK, O'Toole SA, Molloy TJ, Viale G, Goldhirsch A, et al. Prognostic interaction between expression of p53 and estrogen receptor in patients with node-negative breast cancer: results from IBCSG trials VIII and IX. Breast Cancer Res 2012;14:R143.
    • (2012) Breast Cancer Res , Issue.14
    • Coates, A.A.1    Miller, E.K.2    O'Toole, S.A.3    Molloy, T.J.4    Viale, G.5    Goldhirsch, A.6
  • 4
    • 84866703356 scopus 로고    scopus 로고
    • Low ERK phosphorylation in cancer-associated fibroblasts is associated with tamoxifen resistance in pre-menopausal breast cancer
    • Busch S, Ryden L, Stal O, Jirstrom K, Landberg G. Low ERK phosphorylation in cancer-associated fibroblasts is associated with tamoxifen resistance in pre-menopausal breast cancer. PLoS One 2012;7:e45669.
    • (2012) PLoS One , Issue.7
    • Busch, S.1    Ryden, L.2    Stal, O.3    Jirstrom, K.4    Landberg, G.5
  • 5
    • 84865558322 scopus 로고    scopus 로고
    • Temozolomide versus standard 6-week radiotherapy versus hypofractionated radiotherapy in patients older than 60 years with glioblastoma: The nordic randomised, phase 3 trial
    • N. C. B. T. S. G. NCBTSG
    • Malmstrom A, Gronberg BH, Marosi C, Stupp R, Frappaz D, Schultz H, et al., and N. C. B. T. S. G. (NCBTSG). Temozolomide versus standard 6-week radiotherapy versus hypofractionated radiotherapy in patients older than 60 years with glioblastoma: the nordic randomised, phase 3 trial. Lancet Oncol 2012;13:916-26.
    • (2012) Lancet Oncol , vol.13 , pp. 916-926
    • Malmstrom, A.1    Gronberg, B.H.2    Marosi, C.3    Stupp, R.4    Frappaz, D.5    Schultz, H.6
  • 6
    • 79951611991 scopus 로고    scopus 로고
    • Measuring the performance of markers for guiding treatment decisions
    • Janes H, Pepe MS, Bossuyt PM, Barlow WE. Measuring the performance of markers for guiding treatment decisions. Ann Intern Med 2011;154:253-9.
    • (2011) Ann Intern Med , vol.154 , pp. 253-259
    • Janes, H.1    Pepe, M.S.2    Bossuyt, P.M.3    Barlow, W.E.4
  • 7
    • 84866749582 scopus 로고    scopus 로고
    • Assessing treatment-selection markers using a potential outcomes framework
    • Huang Y, Gilbert PB, Janes H. Assessing treatment-selection markers using a potential outcomes framework. Biometrics 2012;68:687-96.
    • (2012) Biometrics , vol.68 , pp. 687-696
    • Huang, Y.1    Gilbert, P.B.2    Janes, H.3
  • 8
    • 20044377408 scopus 로고    scopus 로고
    • Patterns of treatment effects in subsets of patients in clinical trials
    • Bonetti M, Gelber RD. Patterns of treatment effects in subsets of patients in clinical trials. Biostatistics 2004;5:465-81.
    • (2004) Biostatistics , vol.5 , pp. 465-481
    • Bonetti, M.1    Gelber, R.D.2
  • 9
    • 4344621625 scopus 로고    scopus 로고
    • A new approach to modelling interactions between treatment and continuous covariates in clinical trials by using fractional polynomials
    • Royston P, Sauerbrei W. A new approach to modelling interactions between treatment and continuous covariates in clinical trials by using fractional polynomials. Stat Med 2004;23:2509-25.
    • (2004) Stat Med , vol.23 , pp. 2509-2525
    • Royston, P.1    Sauerbrei, W.2
  • 10
    • 79953133534 scopus 로고    scopus 로고
    • Analysis of randomized comparative clinical trial data for personalized treatment selections
    • Cai T, Tian L, Wong P, Wei L. Analysis of randomized comparative clinical trial data for personalized treatment selections. Biostatistics 2011;12:270-82.
    • (2011) Biostatistics , vol.12 , pp. 270-282
    • Cai, T.1    Tian, L.2    Wong, P.3    Wei, L.4
  • 13
    • 10944237674 scopus 로고    scopus 로고
    • Evaluating markers for selecting a patient's treatment
    • Song X, Pepe MS. Evaluating markers for selecting a patient's treatment. Biometrics 2004;60:874-83.
    • (2004) Biometrics , vol.60 , pp. 874-883
    • Song, X.1    Pepe, M.S.2
  • 14
    • 27344447884 scopus 로고    scopus 로고
    • Statistics for weighing benefits and harms in a proposed genetic substudy of a randomized cancer prevention trial
    • Baker S, Kramer B. Statistics for weighing benefits and harms in a proposed genetic substudy of a randomized cancer prevention trial. J Royal Stat Soc Ser C (Appl Stat) 2005;54:941-54.
    • (2005) J Royal Stat Soc Ser C (Appl Stat) , vol.54 , pp. 941-954
    • Baker, S.1    Kramer, B.2
  • 15
    • 34447646946 scopus 로고    scopus 로고
    • Method for evaluating prediction models that apply the results of randomized trials to individual patients
    • Vickers AJ, Kattan MW, Sargent D. Method for evaluating prediction models that apply the results of randomized trials to individual patients. Trials 2007;8:14.
    • (2007) Trials , vol.8 , pp. 14
    • Vickers, A.J.1    Kattan, M.W.2    Sargent, D.3
  • 16
    • 77953005977 scopus 로고    scopus 로고
    • A generalized estimator of the attributable benefit of an optimal treatment regime
    • Brinkley J, Tsiatis AA, Anstrom KJ. A generalized estimator of the attributable benefit of an optimal treatment regime. Biometrics 2010;66:512-22.
    • (2010) Biometrics , vol.66 , pp. 512-522
    • Brinkley, J.1    Tsiatis, A.A.2    Anstrom, K.J.3
  • 17
    • 84886467569 scopus 로고    scopus 로고
    • Variable selection for optimal treatment decision
    • Lu W, Zhang HH, Zeng D. Variable selection for optimal treatment decision. Stat Meth Med Res 2012;22(5):493-504.
    • (2012) Stat Meth Med Res , vol.22 , Issue.5 , pp. 493-504
    • Lu, W.1    Zhang, H.H.2    Zeng, D.3
  • 18
    • 80053563163 scopus 로고    scopus 로고
    • Subgroup identification from randomized clinical trial data
    • Foster JC, Taylor JM, Ruberg SJ. Subgroup identification from randomized clinical trial data. Stat Med 2011;30:2867-80.
    • (2011) Stat Med , vol.30 , pp. 2867-2880
    • Foster, J.C.1    Taylor, J.M.2    Ruberg, S.J.3
  • 19
    • 84862908630 scopus 로고    scopus 로고
    • Variable selection for qualitative interactions in personalized medicine while controlling the family-wise error rate
    • Gunter L, Zhu J, Murphy S. Variable selection for qualitative interactions in personalized medicine while controlling the family-wise error rate. J Biopharm Stat 2011;21:1063-78.
    • (2011) J Biopharm Stat , vol.21 , pp. 1063-1078
    • Gunter, L.1    Zhu, J.2    Murphy, S.3
  • 20
    • 84870707096 scopus 로고    scopus 로고
    • Performance guarantees for individualized treatment rules
    • Qian M, Murphy S. Performance guarantees for individualized treatment rules. Ann Stat 2011;39:1180-210.
    • (2011) Ann Stat , vol.39 , pp. 1180-1210
    • Qian, M.1    Murphy, S.2
  • 21
    • 84902529842 scopus 로고    scopus 로고
    • Evaluation of treatment policies via sparse functional linear regression
    • McKeague IW, Qian M. Evaluation of treatment policies via sparse functional linear regression. Stat Sin 2013.
    • Stat Sin 2013
    • McKeague, I.W.1    Qian, M.2
  • 22
    • 84871667403 scopus 로고    scopus 로고
    • A robust method for estimating optimal treatment regimes
    • Zhang B, Tsiatis AA, Laber EB, Davidian M. A robust method for estimating optimal treatment regimes. Biometrics 2012;68(4):1010-8.
    • (2012) Biometrics , vol.68 , Issue.4 , pp. 1010-1018
    • Zhang, B.1    Tsiatis, A.A.2    Laber, E.B.3    Davidian, M.4
  • 26
    • 19344364880 scopus 로고    scopus 로고
    • Effects of chemotherapy and hormonal therapy for early breast cancer on recurrence and 15-year survival: An overview of the randomized trials
    • Early Breast Cancer Trialists Collaborative Group
    • Early Breast Cancer Trialists Collaborative Group. Effects of chemotherapy and hormonal therapy for early breast cancer on recurrence and 15-year survival: an overview of the randomized trials. Lancet 2005;365:1687-717.
    • (2005) Lancet , vol.365 , pp. 1687-1717
  • 28
    • 73249140371 scopus 로고    scopus 로고
    • Prognostic and predictive value of the 21-gene recurrence score assay in postmenopausal women with node-positive, oestrogen-receptor-positive breast cancer on chemotherapy: A retrospective analysis of a randomized trial
    • Albain KS, Barlow WE, Shak S, Hortobagyi GN, Livingston RB, Yeh IT. Prognostic and predictive value of the 21-gene recurrence score assay in postmenopausal women with node-positive, oestrogen-receptor-positive breast cancer on chemotherapy: A retrospective analysis of a randomized trial. Lancet Oncol 2010;11:55-65.
    • (2010) Lancet Oncol , vol.11 , pp. 55-65
    • Albain, K.S.1    Barlow, W.E.2    Shak, S.3    Hortobagyi, G.N.4    Livingston, R.B.5    Yeh, I.T.6
  • 29
    • 19944422061 scopus 로고    scopus 로고
    • A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer
    • Paik S, Shak S, Tang G, Kim C, Baker J, Cronin M, et al. A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. New Engl J Med 2004;351:2817-26.
    • (2004) New Engl J Med , vol.351 , pp. 2817-2826
    • Paik, S.1    Shak, S.2    Tang, G.3    Kim, C.4    Baker, J.5    Cronin, M.6
  • 30
    • 33744814477 scopus 로고    scopus 로고
    • Gene expression and benefit of chemotherapy in women with node-negative, estrogen-receptor-positive breast cancer
    • Paik S, Tang G, Shak S, Chungyeul K, Baker J, Kim W, et al. Gene expression and benefit of chemotherapy in women with node-negative, estrogen-receptor-positive breast cancer. J Clin Oncol 2006;24:3726-34.
    • (2006) J Clin Oncol , vol.24 , pp. 3726-3734
    • Paik, S.1    Tang, G.2    Shak, S.3    Chungyeul, K.4    Baker, J.5    Kim, W.6
  • 31
    • 72149104757 scopus 로고    scopus 로고
    • Adjuvant chemotherapy and timing of tamoxifen in postmenopausal patients with endocrine-responsive, nodepositive breast cancer: A phase 3, open-label, randomized controlled trial
    • Breast Cancer Intergroup of North America
    • Albain KS, Barlow WE, Davdin PM, Farrar WB, Burton GV, Ketchel SJ, et al., and the Breast Cancer Intergroup of North America. Adjuvant chemotherapy and timing of tamoxifen in postmenopausal patients with endocrine-responsive, nodepositive breast cancer: A phase 3, open-label, randomized controlled trial. Lancet 2009;274:2055-63.
    • (2009) Lancet , vol.274 , pp. 2055-2063
    • Albain, K.S.1    Barlow, W.E.2    Davdin, P.M.3    Farrar, W.B.4    Burton, G.V.5    Ketchel, S.J.6
  • 32
    • 84893821653 scopus 로고    scopus 로고
    • A framework for evaluating markers used to select patient treatment
    • Janes H, Pepe MS, Huang Y. A framework for evaluating markers used to select patient treatment. Med Decis Making 2014;34(2):159-67.
    • (2014) Med Decis Making , vol.34 , Issue.2 , pp. 159-167
    • Janes, H.1    Pepe, M.S.2    Huang, Y.3
  • 33
    • 77956002848 scopus 로고    scopus 로고
    • Semiparametric methods for evaluating the covariate-specific predictiveness of continuous markers in matched case-control studies
    • Huang Y, Pepe M. Semiparametric methods for evaluating the covariate-specific predictiveness of continuous markers in matched case-control studies. J R Stat Soc Ser B 2010;59:437-56.
    • (2010) J R Stat Soc Ser B , vol.59 , pp. 437-456
    • Huang, Y.1    Pepe, M.2
  • 34
    • 77953166434 scopus 로고    scopus 로고
    • Assessing risk prediction models in case-control studies using semiparametric and nonparametric methods
    • Huang Y, Pepe MS. Assessing risk prediction models in case-control studies using semiparametric and nonparametric methods. Stat Med 2010;29:1391-410.
    • (2010) Stat Med , vol.29 , pp. 1391-1410
    • Huang, Y.1    Pepe, M.S.2
  • 35
    • 36749078166 scopus 로고    scopus 로고
    • Evaluating the predictiveness of a continuous marker
    • Huang Y, Sullivan Pepe M, Feng Z. Evaluating the predictiveness of a continuous marker. Biometrics 2007;63:1181-8.
    • (2007) Biometrics , vol.63 , pp. 1181-1188
    • Huang, Y.1    Pepe, M.S.2    Feng, Z.3
  • 36
    • 79251564078 scopus 로고    scopus 로고
    • One statistical test is sufficient for assessing new predictive markers
    • Vickers AJ, Cronin AM, Begg CB. One statistical test is sufficient for assessing new predictive markers. BMC Med Res Methodol 2011;11:13.
    • (2011) BMC Med Res Methodol , vol.11 , pp. 13
    • Vickers, A.J.1    Cronin, A.M.2    Begg, C.B.3
  • 37
    • 79960815320 scopus 로고    scopus 로고
    • Evaluating the incremental value of new biomarkers with integrated discrimination improvement
    • Kerr KF, McClelland RL, Brown ER, Lumley T. Evaluating the incremental value of new biomarkers with integrated discrimination improvement. Am J Epidemiol 2011;174:364-74.
    • (2011) Am J Epidemiol , vol.174 , pp. 364-374
    • Kerr, K.F.1    McClelland, R.L.2    Brown, E.R.3    Lumley, T.4
  • 39
    • 84876331767 scopus 로고    scopus 로고
    • Comparing ROC curves derived from regression models
    • Seshan VE, Gonen M, Begg CB. Comparing ROC curves derived from regression models. Stat Med 2013;32(9):1483-93.
    • (2013) Stat Med , vol.32 , Issue.9 , pp. 1483-1493
    • Seshan, V.E.1    Gonen, M.2    Begg, C.B.3
  • 40
    • 84866436976 scopus 로고    scopus 로고
    • Misuse of DeLONG test to compare AUCs for nested models
    • Demler OV, Pencina MJ, D'Agostino RB. Misuse of DeLONG test to compare AUCs for nested models. Stat Med 2012;31:2577-87.
    • (2012) Stat Med , vol.31 , pp. 2577-2587
    • Demler, O.V.1    Pencina, M.J.2    D'Agostino, R.B.3
  • 41
    • 84890117399 scopus 로고    scopus 로고
    • Net reclassification indices for evaluating risk prediction instruments: A critical review
    • Kerr KF, Wang Z, Janes H, McClelland RL, Psaty BM, Pepe MS. Net reclassification indices for evaluating risk prediction instruments: a critical review. Epidemiology 2014;25(1):114-121.
    • (2014) Epidemiology , vol.25 , Issue.1 , pp. 114-121
    • Kerr, K.F.1    Wang, Z.2    Janes, H.3    McClelland, R.L.4    Psaty, B.M.5    Pepe, M.S.6
  • 42
    • 0022072706 scopus 로고
    • Testing for qualitative interactions between treatment effects and patient subsets
    • Gail M, Simon R. Testing for qualitative interactions between treatment effects and patient subsets. Biometrics 1985;41:361-72.
    • (1985) Biometrics , vol.41 , pp. 361-372
    • Gail, M.1    Simon, R.2
  • 43
    • 0021078618 scopus 로고
    • Interaction between prognostic factors and treatment
    • Shuster J, van Eys J. Interaction between prognostic factors and treatment. Control Clin Trials 1983;4:209-14.
    • (1983) Control Clin Trials , vol.4 , pp. 209-214
    • Shuster, J.1    Van Eys, J.2
  • 44
    • 0020063002 scopus 로고
    • A review of goodness of fit statistics for use in the development of logistic regression models
    • Lemeshow S, Hosmer DJ. A review of goodness of fit statistics for use in the development of logistic regression models. Am J Epidemiol 1982;115:92-106.
    • (1982) Am J Epidemiol , vol.115 , pp. 92-106
    • Lemeshow, S.1    Hosmer, D.J.2
  • 45
    • 0018671320 scopus 로고
    • Logistic disease incidence models and case-control studies
    • Prentice RL, Pyke R. Logistic disease incidence models and case-control studies. Biometrika 1979;66:403-11.
    • (1979) Biometrika , vol.66 , pp. 403-411
    • Prentice, R.L.1    Pyke, R.2
  • 46
    • 70350457746 scopus 로고    scopus 로고
    • Measures to summarize and compare the predictive capacity of markers
    • Gu W, Pepe M. Measures to summarize and compare the predictive capacity of markers. Int J Biostat 2009;5:Article 27. Accessed at: http://dx.doi.org/10. 2202/1557-4679.1188
    • (2009) Int J Biostat , Issue.5 , pp. 27
    • Gu, W.1    Pepe, M.2
  • 47
    • 14944365889 scopus 로고    scopus 로고
    • False discovery rate-adjusted multiple confidence intervals for selected parameters
    • Benjamini Y, Yekuteili D. False discovery rate-adjusted multiple confidence intervals for selected parameters. J Am Stat Assoc 2005;100:71-81.
    • (2005) J Am Stat Assoc , vol.100 , pp. 71-81
    • Benjamini, Y.1    Yekuteili, D.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.