메뉴 건너뛰기




Volumn 34, Issue 14, 2015, Pages 2181-2195

Joint modeling of survival and longitudinal non-survival data: Current methods and issues. Report of the DIA Bayesian joint modeling working group

Author keywords

Applications; Random effects; Software; Time dependent

Indexed keywords

CANCER VACCINE; ANTI HUMAN IMMUNODEFICIENCY VIRUS AGENT; PHARMACOLOGICAL BIOMARKER;

EID: 84930151542     PISSN: 02776715     EISSN: 10970258     Source Type: Journal    
DOI: 10.1002/sim.6141     Document Type: Article
Times cited : (112)

References (75)
  • 1
    • 77954944281 scopus 로고    scopus 로고
    • Basic concepts and methods for joint models of longitudinal and survival data
    • Ibrahim JG, Chu H, Chen LM. Basic concepts and methods for joint models of longitudinal and survival data. Journal of Clinical Oncology 2010; 28:2796-2801.
    • (2010) Journal of Clinical Oncology , vol.28 , pp. 2796-2801
    • Ibrahim, J.G.1    Chu, H.2    Chen, L.M.3
  • 5
    • 84864682470 scopus 로고    scopus 로고
    • Joint modeling of longitudinal outcomes and survival using latent growth modeling approach in a mesothelioma trial
    • Wang P, Shen W, Boye ME. Joint modeling of longitudinal outcomes and survival using latent growth modeling approach in a mesothelioma trial. Health Services & Outcomes Research Methodologies 2012; 12:182-199.
    • (2012) Health Services & Outcomes Research Methodologies , vol.12 , pp. 182-199
    • Wang, P.1    Shen, W.2    Boye, M.E.3
  • 6
    • 84880909003 scopus 로고    scopus 로고
    • Toward patient-centered drug development in oncology
    • Basch E. Toward patient-centered drug development in oncology. New England Journal of Medicine 2013; 369:397-400.
    • (2013) New England Journal of Medicine , vol.369 , pp. 397-400
    • Basch, E.1
  • 7
    • 79960208982 scopus 로고    scopus 로고
    • Sample size and power determination in joint modeling of longitudinal and survival data
    • Chen LM, Ibrahim JG, Chu HT. Sample size and power determination in joint modeling of longitudinal and survival data. Statistics in Medicine 2011; 30:2295-2309.
    • (2011) Statistics in Medicine , vol.30 , pp. 2295-2309
    • Chen, L.M.1    Ibrahim, J.G.2    Chu, H.T.3
  • 8
    • 0037304940 scopus 로고    scopus 로고
    • The challenges and achievements involved in implementing quality of life research in cancer clinical trials
    • Bottomley A, Vanvoorden V, Flechtner H, Therasse P. The challenges and achievements involved in implementing quality of life research in cancer clinical trials. European Journal of Cancer 2003; 39:275-285.
    • (2003) European Journal of Cancer , vol.39 , pp. 275-285
    • Bottomley, A.1    Vanvoorden, V.2    Flechtner, H.3    Therasse, P.4
  • 9
    • 0032585268 scopus 로고    scopus 로고
    • Reporting on quality of life in randomised controlled trials: bibliographic study
    • Sanders C, Egger M, Donovan J, Tallon D, Frankel S. Reporting on quality of life in randomised controlled trials: bibliographic study. BMJ 1998; 317:1191-1194.
    • (1998) BMJ , vol.317 , pp. 1191-1194
    • Sanders, C.1    Egger, M.2    Donovan, J.3    Tallon, D.4    Frankel, S.5
  • 11
    • 34250370236 scopus 로고    scopus 로고
    • Guideline on the evaluation of anticancer medicinal products in man, EMEA
    • EMEA. Guideline on the evaluation of anticancer medicinal products in man, EMEA, 2013. Available from: http://www.ema.europa.eu/docs/en_GB/document_library/Scientific_guideline/2013/01/WC500137128.pdf.Accessed8-27-2013.
    • (2013)
  • 12
    • 33747813779 scopus 로고    scopus 로고
    • Guidance for industry: clinical trial endpoints for the approval of cancer drugs and biologics
    • Food and Drug Administration, Accessed8-27-2013.
    • Food and Drug Administration. Guidance for industry: clinical trial endpoints for the approval of cancer drugs and biologics, Food and Drug Administration, 2007. Available from: http://www.fda.gov/downloads/Drugs/GuidanceComplianceRegulatoryInformation/Guidances/ucm071590.pdf.Accessed8-27-2013.
    • (2007)
  • 13
    • 33746261692 scopus 로고    scopus 로고
    • Guidance for industry: patient-reported outcomes measures: use in medical product development to support labeling claims
    • Food and Drug Administration, Available from:. Accessed8-27-2013.
    • Food and Drug Administration. Guidance for industry: patient-reported outcomes measures: use in medical product development to support labeling claims, Food and Drug Administration, 2009. Available from: http://www.fda.gov/downloads/Drugs/Guidances/UCM193282.pdf. Accessed8-27-2013.
    • (2009)
  • 14
    • 84861149601 scopus 로고    scopus 로고
    • Beyond the FDA PRO guidance: steps toward integrating meaningful patient-reported outcomes into regulatory trials and US drug labels
    • Basch E. Beyond the FDA PRO guidance: steps toward integrating meaningful patient-reported outcomes into regulatory trials and US drug labels. Value in Health 2012; 15:401-403.
    • (2012) Value in Health , vol.15 , pp. 401-403
    • Basch, E.1
  • 15
    • 84874371892 scopus 로고    scopus 로고
    • Reporting of patient-reported outcomes in randomized trials: the CONSORT PRO extension
    • Calvert M. Reporting of patient-reported outcomes in randomized trials: the CONSORT PRO extension. Journal of the American Medical Association 2013; 309:814-822.
    • (2013) Journal of the American Medical Association , vol.309 , pp. 814-822
    • Calvert, M.1
  • 17
    • 0012027867 scopus 로고
    • Assessing cross-sectional correlation in panel data
    • Frees EW. Assessing cross-sectional correlation in panel data. Journal of Econometrics 1995; 69:393-414.
    • (1995) Journal of Econometrics , vol.69 , pp. 393-414
    • Frees, E.W.1
  • 18
    • 8644246036 scopus 로고    scopus 로고
    • Joint modeling of longitudinal and time-to-event data: an overview
    • Tsiatis AA, Davidian M. Joint modeling of longitudinal and time-to-event data: an overview. Statistica Sinica 2004; 14:809-834.
    • (2004) Statistica Sinica , vol.14 , pp. 809-834
    • Tsiatis, A.A.1    Davidian, M.2
  • 19
    • 70349235858 scopus 로고    scopus 로고
    • Latent-model robustness in joint models for a primary endpoint and a longitudinal process
    • Huang X, Stefanski LA, Davidson M. Latent-model robustness in joint models for a primary endpoint and a longitudinal process. Biometrics 2009; 65:719-727.
    • (2009) Biometrics , vol.65 , pp. 719-727
    • Huang, X.1    Stefanski, L.A.2    Davidson, M.3
  • 20
    • 40249113335 scopus 로고    scopus 로고
    • Shared parameter models under random effects misspecification
    • Rizopoulos D, Verbeke G, Molenberghs G. Shared parameter models under random effects misspecification. Biometrika 2008; 95:63-74.
    • (2008) Biometrika , vol.95 , pp. 63-74
    • Rizopoulos, D.1    Verbeke, G.2    Molenberghs, G.3
  • 21
    • 84870913219 scopus 로고    scopus 로고
    • Flexible parametric joint modelling of longitudinal and survival data
    • Crowther MJ, Abrams KR, Lambert PC. Flexible parametric joint modelling of longitudinal and survival data. Statistics in Medicine 2012; 31:4456-4471.
    • (2012) Statistics in Medicine , vol.31 , pp. 4456-4471
    • Crowther, M.J.1    Abrams, K.R.2    Lambert, P.C.3
  • 22
    • 84870389666 scopus 로고    scopus 로고
    • Joint models of longitudinal data and recurrent events with informative terminal event
    • Kim S, Zeng D, Chambless L, Li Y. Joint models of longitudinal data and recurrent events with informative terminal event. Statistics in Biosciences 2012; 4:d62-281.
    • (2012) Statistics in Biosciences , vol.4 , pp. d62-281
    • Kim, S.1    Zeng, D.2    Chambless, L.3    Li, Y.4
  • 23
    • 58149163015 scopus 로고    scopus 로고
    • Joint analysis of correlated repeated measures and recurrent event processes in the presence of death, with application to a study on acquired immune deficinecy syndrome
    • Liu L, Huang X. Joint analysis of correlated repeated measures and recurrent event processes in the presence of death, with application to a study on acquired immune deficinecy syndrome. Journal of the Royal Statistical Society Series C 2009; 58:65-81.
    • (2009) Journal of the Royal Statistical Society Series C , vol.58 , pp. 65-81
    • Liu, L.1    Huang, X.2
  • 24
    • 70349243621 scopus 로고    scopus 로고
    • Semiparametric transformation models with random effects for joint analysis of recurrent and terminal events
    • Zeng D, Lim DY. Semiparametric transformation models with random effects for joint analysis of recurrent and terminal events. Biometrics 2009; 65:746-752.
    • (2009) Biometrics , vol.65 , pp. 746-752
    • Zeng, D.1    Lim, D.Y.2
  • 25
    • 79955617684 scopus 로고    scopus 로고
    • Molife LRea. Phase 1 trials of molecularly targeted agents: should we pay more attention to late toxicities
    • Postel-Vinay S, Gomez-Roca C. Molife LRea. Phase 1 trials of molecularly targeted agents: should we pay more attention to late toxicities. Journal of Clinical Oncology 2011; 29:1728-1735.
    • (2011) Journal of Clinical Oncology , vol.29 , pp. 1728-1735
    • Postel-Vinay, S.1    Gomez-Roca, C.2
  • 26
    • 20744435134 scopus 로고    scopus 로고
    • A Bayesian approach to jointly modeling toxicity and biomarker expression in a phase I/II dose-finding trial
    • Bekele BN, Shen Y. A Bayesian approach to jointly modeling toxicity and biomarker expression in a phase I/II dose-finding trial. Biometrics 2005; 61:344-354.
    • (2005) Biometrics , vol.61 , pp. 344-354
    • Bekele, B.N.1    Shen, Y.2
  • 27
    • 78649367492 scopus 로고    scopus 로고
    • A novel Bayesian dose-escalation phase Ib design investigating safety of combination of RAD001 with chemotherapy plus trastuzumab in patients with HER2-overexpressing metastatic breast cancer with prior resistance to trastuzumab
    • Abstract
    • Di Scala L, Pylvanianen I, Molloy B, Manlius C, Vittori L, Sahmoud T, Lebwohl D, Zuber EP. A novel Bayesian dose-escalation phase Ib design investigating safety of combination of RAD001 with chemotherapy plus trastuzumab in patients with HER2-overexpressing metastatic breast cancer with prior resistance to trastuzumab. Journal of Clinical Oncology 2008; 26:S1130 (Abstract).
    • (2008) Journal of Clinical Oncology , vol.26 , pp. S1130
    • Di Scala, L.1    Pylvanianen, I.2    Molloy, B.3    Manlius, C.4    Vittori, L.5    Sahmoud, T.6    Lebwohl, D.7    Zuber, E.P.8
  • 28
    • 58249141626 scopus 로고    scopus 로고
    • A Bayesian population PK-PD model for ispinesib/docetaxel combination-induced myelosuppression
    • Kathman SJ, Williams DH, Hodge JP, Dar M. A Bayesian population PK-PD model for ispinesib/docetaxel combination-induced myelosuppression. Cancer Chemothearpy and Pharmacology 2009; 63:469-476.
    • (2009) Cancer Chemothearpy and Pharmacology , vol.63 , pp. 469-476
    • Kathman, S.J.1    Williams, D.H.2    Hodge, J.P.3    Dar, M.4
  • 29
    • 35548941748 scopus 로고    scopus 로고
    • Population pharmacokinetic and pharmacodynamic analysis for time courses of docetaxel-induced neutropenia in Japanese cancer patients
    • Ozawa K, Minami H, Sato H. Population pharmacokinetic and pharmacodynamic analysis for time courses of docetaxel-induced neutropenia in Japanese cancer patients. Cancer Science 2007; 98:1985-1992.
    • (2007) Cancer Science , vol.98 , pp. 1985-1992
    • Ozawa, K.1    Minami, H.2    Sato, H.3
  • 30
    • 84930184146 scopus 로고    scopus 로고
    • Computational tools for Bayesian PKPD modeling, Metrum Institute
    • Available from:[Accessed on 7 March 2014].
    • Gillespie WR. Computational tools for Bayesian PKPD modeling, Metrum Institute, 2010. Available from: http://legacy.samsi.info/201011/pkpd/gillespiePKPDSoftwareSAMSI2010.pdf [Accessed on 7 March 2014].
    • (2010)
    • Gillespie, W.R.1
  • 31
    • 84930184147 scopus 로고    scopus 로고
    • BUGS/WBDiff software: Bayesian inference for dynamical systems
    • MRC Biostatistics Unit, Cambridge University, Available from:[Accessed on 7 March 2014].
    • Lunn DJ. BUGS/WBDiff software: Bayesian inference for dynamical systems, MRC Biostatistics Unit, Cambridge University, 2011. Available from: http://sbml.org/images/2/2f/StatMeeting_Lunn.pdf [Accessed on 7 March 2014].
    • (2011)
    • Lunn, D.J.1
  • 32
    • 65649097629 scopus 로고    scopus 로고
    • GNU MCSim: Bayesian statistical inference for SBML-coded systems biology models
    • Bois FY. GNU MCSim: Bayesian statistical inference for SBML-coded systems biology models. Bioinformatics 2009; 25:1453-1454.
    • (2009) Bioinformatics , vol.25 , pp. 1453-1454
    • Bois, F.Y.1
  • 33
    • 84930182832 scopus 로고    scopus 로고
    • MCMC Bayesian analysis for population analysis of complex pK/pD models in NonMEM VII beta
    • Bauer RJ, Ludden T. MCMC Bayesian analysis for population analysis of complex pK/pD models in NonMEM VII beta. Clinical Pharmacology and Therapeutics 2009; 85:S30-S31.
    • (2009) Clinical Pharmacology and Therapeutics , vol.85 , pp. S30-S31
    • Bauer, R.J.1    Ludden, T.2
  • 34
    • 34247887681 scopus 로고    scopus 로고
    • A survey of population analysis methods and software for complex pharmacokinetic and pharmacodynamic models with examples
    • Bauer RJ, Guzy S, Ng C. A survey of population analysis methods and software for complex pharmacokinetic and pharmacodynamic models with examples. AAPS Journal 2007; 9:E60-E83.
    • (2007) AAPS Journal , vol.9 , pp. E60-E83
    • Bauer, R.J.1    Guzy, S.2    Ng, C.3
  • 36
    • 79955847737 scopus 로고    scopus 로고
    • A Bayesian semiparametric multivariate joint model for multiple longitudinal outcomes and a time-to-event
    • Rizopoulos D, Ghosh P. A Bayesian semiparametric multivariate joint model for multiple longitudinal outcomes and a time-to-event. Statistics in Medicine 2011; 30:1366-1380.
    • (2011) Statistics in Medicine , vol.30 , pp. 1366-1380
    • Rizopoulos, D.1    Ghosh, P.2
  • 38
    • 0000710136 scopus 로고    scopus 로고
    • Joint modelling of longitudinal measurements and event time data
    • Henderson R, Diggle P, Dobson A. Joint modelling of longitudinal measurements and event time data. Biostatistics 2000; 1:465-480.
    • (2000) Biostatistics , vol.1 , pp. 465-480
    • Henderson, R.1    Diggle, P.2    Dobson, A.3
  • 39
    • 0030893266 scopus 로고    scopus 로고
    • A joint model for survival and longitudinal data measured with error
    • Wulfsohn MS, Tsiatis AA. A joint model for survival and longitudinal data measured with error. Biometrics 1997; 53:330-339.
    • (1997) Biometrics , vol.53 , pp. 330-339
    • Wulfsohn, M.S.1    Tsiatis, A.A.2
  • 40
    • 33845482505 scopus 로고    scopus 로고
    • Joint modeling of survival and longitudinal data: likelihood approach revisited
    • Hsieh F, Tseng YK, Wang JL. Joint modeling of survival and longitudinal data: likelihood approach revisited. Biometrics 2006; 62:1037-1043.
    • (2006) Biometrics , vol.62 , pp. 1037-1043
    • Hsieh, F.1    Tseng, Y.K.2    Wang, J.L.3
  • 41
    • 80053576984 scopus 로고    scopus 로고
    • Bayesian inference on joint models of HIV dynamics for time-to-event and longitudinal data with skewness and covariate measurement errors
    • Huang YX, Dagne G, Wu L. Bayesian inference on joint models of HIV dynamics for time-to-event and longitudinal data with skewness and covariate measurement errors. Statistics in Medicine 2011; 30:2930-2946.
    • (2011) Statistics in Medicine , vol.30 , pp. 2930-2946
    • Huang, Y.X.1    Dagne, G.2    Wu, L.3
  • 42
    • 0037102914 scopus 로고    scopus 로고
    • Flexible parametric proportional-hazards and proportional-odds models for censored survival data, with application to prognostic modelling and estimation of teratment effects
    • Royston P, Parmar MKB. Flexible parametric proportional-hazards and proportional-odds models for censored survival data, with application to prognostic modelling and estimation of teratment effects. Statistics in Medicine 2002; 21:2175-2197.
    • (2002) Statistics in Medicine , vol.21 , pp. 2175-2197
    • Royston, P.1    Parmar, M.K.B.2
  • 44
    • 56049124129 scopus 로고    scopus 로고
    • Semiparametric modeling of longitudinal measurements and time-to-event data - a two-stage regression calibration approach
    • Ye W, Lin X, Taylor JMG. Semiparametric modeling of longitudinal measurements and time-to-event data - a two-stage regression calibration approach. Biometrics 2008; 64:1238-1246.
    • (2008) Biometrics , vol.64 , pp. 1238-1246
    • Ye, W.1    Lin, X.2    Taylor, J.M.G.3
  • 45
    • 77649100570 scopus 로고    scopus 로고
    • Pretreatment CD4 cell slope and progression to AIDS or death in HIV-infected patients initiating antiretroviral therapy - the CASCADE collaboration: a collaboration of 23 cohort studies
    • e1000239
    • Wolbers M, Babiker A, Sabin C, Young J, Dorrucci M, Chêne G, Mussini C, Porter K, Bucher HC. Pretreatment CD4 cell slope and progression to AIDS or death in HIV-infected patients initiating antiretroviral therapy - the CASCADE collaboration: a collaboration of 23 cohort studies. PLOS medicine 2010; 7(2)e1000239:1-13.
    • (2010) PLOS medicine , vol.7 , Issue.2 , pp. 1-13
    • Wolbers, M.1    Babiker, A.2    Sabin, C.3    Young, J.4    Dorrucci, M.5    Chêne, G.6    Mussini, C.7    Porter, K.8    Bucher, H.C.9
  • 46
    • 21844506206 scopus 로고
    • Modeling the relationship of survival to longitudinal data measured with error: applications to survival and CD4 counts in patients with AIDS
    • Tsiatis AA, DeGruttola V, Wulfsohn MS. Modeling the relationship of survival to longitudinal data measured with error: applications to survival and CD4 counts in patients with AIDS. Journal of the American Statistical Association 1995; 90:27-37.
    • (1995) Journal of the American Statistical Association , vol.90 , pp. 27-37
    • Tsiatis, A.A.1    DeGruttola, V.2    Wulfsohn, M.S.3
  • 47
    • 0029763749 scopus 로고    scopus 로고
    • Simultaneously modelling censored survival data and repeatedly measured covariates: a Gibbs sampling approach
    • Faucett CJ, Thomas DC. Simultaneously modelling censored survival data and repeatedly measured covariates: a Gibbs sampling approach. Statistics in Medicine 1996; 15:1663-1685.
    • (1996) Statistics in Medicine , vol.15 , pp. 1663-1685
    • Faucett, C.J.1    Thomas, D.C.2
  • 48
    • 3442883055 scopus 로고    scopus 로고
    • Bayesian methods for joint modeling of longitudinal and survival data with applications to cancer vaccine studies
    • Ibrahim JG, Chen MH, Sinha D. Bayesian methods for joint modeling of longitudinal and survival data with applications to cancer vaccine studies. Statistica Sinica 2004; 14:863-883.
    • (2004) Statistica Sinica , vol.14 , pp. 863-883
    • Ibrahim, J.G.1    Chen, M.H.2    Sinha, D.3
  • 49
    • 84930177531 scopus 로고    scopus 로고
    • Jointly modelling longitudinal and event time data with application to AIDS studies
    • unpublished ms).
    • Wang Y, Taylor JMG. 'Jointly modelling longitudinal and event time data with application to AIDS studies', 2000. (unpublished ms).
    • (2000)
    • Wang, Y.1    Taylor, J.M.G.2
  • 51
    • 80052418167 scopus 로고    scopus 로고
    • Joint modelling of longitudinal and time-to-event data with application to predicting abdominal aortic aneurysm growth and rupture
    • Sweeting MJ, Thompson SG. Joint modelling of longitudinal and time-to-event data with application to predicting abdominal aortic aneurysm growth and rupture. Biometrical Journal 2011; 53:750-763.
    • (2011) Biometrical Journal , vol.53 , pp. 750-763
    • Sweeting, M.J.1    Thompson, S.G.2
  • 52
    • 77955157844 scopus 로고    scopus 로고
    • JM: an R package for the joint modelling of longitudinal and time-to-event data
    • Rizopoulos D. JM: an R package for the joint modelling of longitudinal and time-to-event data. Journal of Statistical Software 2010; 35:1-33.
    • (2010) Journal of Statistical Software , vol.35 , pp. 1-33
    • Rizopoulos, D.1
  • 53
    • 84890426165 scopus 로고    scopus 로고
    • joineR - joint modelling of repeated measurements and time-to-event data
    • Available from:[Accessed on 7 March 2014].
    • Philipson P, Sousa I, Diggle PJ. joineR - joint modelling of repeated measurements and time-to-event data, 2013. Available from: http://cran.r-project.org/ [Accessed on 7 March 2014].
    • (2013)
    • Philipson, P.1    Sousa, I.2    Diggle, P.J.3
  • 54
    • 0006407254 scopus 로고    scopus 로고
    • WinBUGS - a Bayesian modelling framework: concepts, structure, and extensibility
    • Lunn DJ, Thomas A, Best N, Spiegelhalter DJ. WinBUGS - a Bayesian modelling framework: concepts, structure, and extensibility. Statistics and Computing 2000; 10:325-337.
    • (2000) Statistics and Computing , vol.10 , pp. 325-337
    • Lunn, D.J.1    Thomas, A.2    Best, N.3    Spiegelhalter, D.J.4
  • 55
    • 1342289473 scopus 로고    scopus 로고
    • Separate and joint modeling of longitudinal and event time data using standard computer packages
    • Guo X, Carlin BP. Separate and joint modeling of longitudinal and event time data using standard computer packages. American Statistician 2004; 58:16-24.
    • (2004) American Statistician , vol.58 , pp. 16-24
    • Guo, X.1    Carlin, B.P.2
  • 56
    • 84930184148 scopus 로고    scopus 로고
    • JMbayesL joint modeling of longitudinal and time-to-event data under a Bayesian approach
    • Available from:[Accessed on 7 March 2014].
    • Rizopoulos D. JMbayesL joint modeling of longitudinal and time-to-event data under a Bayesian approach, 2013. Available from: http://cran.r-project.org/web/packages/JMbayes/index.html [Accessed on 7 March 2014].
    • (2013)
    • Rizopoulos, D.1
  • 57
    • 84930184149 scopus 로고    scopus 로고
    • JMFit: a SAS macro for assessing model fit in joint models of longitudinal and survival data
    • Submitted for publication to Journal of Statistical Software).
    • Zhang D, Chen MH, Ibrahim JG, Boye ME, Shen W. JMFit: a SAS macro for assessing model fit in joint models of longitudinal and survival data, 2013. (Submitted for publication to Journal of Statistical Software).
    • (2013)
    • Zhang, D.1    Chen, M.H.2    Ibrahim, J.G.3    Boye, M.E.4    Shen, W.5
  • 60
    • 84950459427 scopus 로고
    • Hierarchical Bayes models for the progression of HIV infection using longitudinal CD4 T-cell numbers (Disc. p 626-632)
    • Lange N, Carlin BP, Gelfand AE. Hierarchical Bayes models for the progression of HIV infection using longitudinal CD4 T-cell numbers (Disc. p 626-632). Journal of the American Statistical Association 1992; 87:615-626.
    • (1992) Journal of the American Statistical Association , vol.87 , pp. 615-626
    • Lange, N.1    Carlin, B.P.2    Gelfand, A.E.3
  • 63
    • 0028627762 scopus 로고
    • Modeling progression of CD4-lymphocyte count and its relationship to survival time
    • DeGruttola V, Tu XM. Modeling progression of CD4-lymphocyte count and its relationship to survival time. Biometrics 1994; 50:1003-1014.
    • (1994) Biometrics , vol.50 , pp. 1003-1014
    • DeGruttola, V.1    Tu, X.M.2
  • 64
    • 0029954122 scopus 로고    scopus 로고
    • Models for empirical Bayes estimators of longitudinal CD4 counts
    • Lavalley MP, DeGruttola V. Models for empirical Bayes estimators of longitudinal CD4 counts. Statistics in Medicine 1996; 15:2289-2305.
    • (1996) Statistics in Medicine , vol.15 , pp. 2289-2305
    • Lavalley, M.P.1    DeGruttola, V.2
  • 68
    • 0041941609 scopus 로고    scopus 로고
    • Cytomegaloviris (CMV) and human immunodeficiency virus (HIV) burden, CMV end-organ disease, and survival in subjects with advanced HIV infection (AIDS clinical trials group protocol 360)
    • Erice A, Tierney C, Hirsch M, Caliendo AM, Weinberg A, Kendall MA, Polsky B. Cytomegaloviris (CMV) and human immunodeficiency virus (HIV) burden, CMV end-organ disease, and survival in subjects with advanced HIV infection (AIDS clinical trials group protocol 360). Clinical Infectious Diseases 2003; 37:567-578.
    • (2003) Clinical Infectious Diseases , vol.37 , pp. 567-578
    • Erice, A.1    Tierney, C.2    Hirsch, M.3    Caliendo, A.M.4    Weinberg, A.5    Kendall, M.A.6    Polsky, B.7
  • 70
    • 9344242918 scopus 로고    scopus 로고
    • Prophylaxis against disseminated mycobacterium avium complex with weekly azithromycin, daily rifabutin, or both
    • Havlir D, Dube M, Sattler F. Prophylaxis against disseminated mycobacterium avium complex with weekly azithromycin, daily rifabutin, or both. New England Journal of Medicine 1996; 335:392-398.
    • (1996) New England Journal of Medicine , vol.335 , pp. 392-398
    • Havlir, D.1    Dube, M.2    Sattler, F.3
  • 74
    • 0041833567 scopus 로고    scopus 로고
    • Bayesian methods for joint modeling of longitudinal and survival data with applications to cancer vaccine studies
    • Brown ER, Ibrahim JG. Bayesian methods for joint modeling of longitudinal and survival data with applications to cancer vaccine studies. Biometrics 2003; 59:686-693.
    • (2003) Biometrics , vol.59 , pp. 686-693
    • Brown, E.R.1    Ibrahim, J.G.2
  • 75
    • 78651422985 scopus 로고    scopus 로고
    • A general joint model for longitudinal measurements and competing risks survival data with heterogeneous random effects
    • Huang X, Li G, Elashoff RM, Pan J. A general joint model for longitudinal measurements and competing risks survival data with heterogeneous random effects. Lifetime Data Analysis 2011; 17:80-100.
    • (2011) Lifetime Data Analysis , vol.17 , pp. 80-100
    • Huang, X.1    Li, G.2    Elashoff, R.M.3    Pan, J.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.