Joint modeling of longitudinal outcomes and survival using latent growth modeling approach in a mesothelioma trial

Health Services and Outcomes Research Methodology

Volumn 12, Issue 2-3, 2012, Pages 182-199

  Wang, Ping ^a   Shen, Wei ^a   Boye, Mark Ernest ^a  

^a ELI LILLY AND COMPANY   (United States)

Author keywords

Cox proportional hazards model; Joint modeling; Latent trajectory; Oncology clinical trial; Patient reported outcomes; Random effects

Indexed keywords

CISPLATIN; PEMETREXED;

CANCER COMBINATION CHEMOTHERAPY; CANCER SURVIVAL; CONFERENCE PAPER; CONTROLLED STUDY; CORRELATION ANALYSIS; COVARIANCE; DATA ANALYSIS; HUMAN; JOINT MODELING; LATENT GROWTH MODELING; LONGITUDINAL STUDY; MAJOR CLINICAL STUDY; MATHEMATICAL COMPUTING; MESOTHELIOMA; MONOTHERAPY; MULTIPLE CYCLE TREATMENT; OUTCOME ASSESSMENT; PHASE 3 CLINICAL TRIAL; PRIORITY JOURNAL; PROPORTIONAL HAZARDS MODEL; RANDOMIZED CONTROLLED TRIAL; STATISTICAL MODEL; STATISTICAL PARAMETERS; TREATMENT RESPONSE;

EID: 84864682470     PISSN: 13873741     EISSN: 15729400     Source Type: Journal    
DOI: 10.1007/s10742-012-0092-z     Document Type: Conference Paper

References (29)

1. Asparouhov, T., Masyn, K., Muthén, B.: Continuous time survival in latent variable models. Proceedings of the Joint Statistical Meeting, ASA Biometrics Section, pp. 180-187 (2006
2. Bottomley, A., Coens, C., Efficace, F., Gaafar, R., Manegold, C., Burgers, S., Vincent, M., Legrand, C., van Meerbeeck, J.: EORTC-NCIC: Symptoms and patient-reported well-being: Do they predict survival in malignant pleural mesothelioma? A prognostic factor analysis of EORTC-NCIC 08983: Randomized phase III study of cisplatin with or without raltitrexed in patients with malignant pleural mesothelioma. J. Clin. Oncol. 25, 5770-5776 (2007
3. Brown, E.R., Ibrahim, J.G.: A Bayesian semiparametric joint hierarchical model for longitudinal and survival data. Biometrics 59, 221-228 (2003 (Pubitemid 36750335)
4. Chen, L.M., Ibrahim, J.G., Chu, H.: Sample size and power determination in joint modeling of longitudinal and survival data. Stat. Med. 30, 2295-2309 (2011
5. Cox, D.R.: Partial likelihood. Biometrika 62, 269-276 (1975
6. Faucett, C.J., Thomas, D.C.: Simultaneously modeling censored survival data and repeatedly measured covariates: A Gibbs sampling approach. Stat. Med. 15, 1663-1685 (1996 (Pubitemid 26261589)
7. Guo, X., Carlin, B.P.: Separate and joint modeling of longitudinal and event time data using standard computer packages. Am. Stat. 58, 16-24 (2004 (Pubitemid 38260325)
8. Hanson, T.E., Branscum, A.J., Johnson, W.O.: Predictive comparison of joint longitudinal-survival modeling: A case study illustrating competing approaches. Lifetime Data Anal. 17, 3-28 (2011
9. Hatfield, L.A., Boye, M.E., Carlin, B.P.: Joint modeling of multiple longitudinal patient-reported outcomes and survival. J. Biopharm. Stat. 21, 971-991 (2011
10. Henderson, R., Diggle, P., Dobson, A.: Joint modeling of longitudinal measurements and event time data. Biostatistics 1, 465-480 (2000 (Pubitemid 33213549)
11. Hollen, P., Gralla, R., Kris, M.: An overview of the lung cancer symptom scale. In: Assess Quality of Life in Patients with Lung Cancer: A Guide for Clinicians, pp. 57-63. NCM Publishers, New York (1995
12. Hollen, P., Gralla, R., Liepa, A., Symanowski, J., Rusthoven, J.: Measuring quality of life in patients with pleural mesothelioma using a modified version of the Lung Cancer Symptom Scale (LCSS): Psychometric properties of the LCSS-Meso. Support Care Cancer 14, 11-21 (2006 (Pubitemid 43119592)
13. Ibrahim, J.G., Chu, H., Chen, L.M.: Basic concepts and methods for joint models of longitudinal and survival data. J. Clin. Oncol. 28, 2796-2801 (2010
14. Muthén, B., Asparouhov, T., Boye, M., Hackshaw, M., Naegeli, A. Applications of continuous-time survival in latent variable models for the analysis of oncology randomized clinical trial data using Mplus. Technical Report (2009
15. Muthén, L.K., Muthén, B.O.: Mplus User's Guide, 6th edn. Muthén and Muthén, Los Angeles, CA (1998-2010
16. Prentice, R.L.: Covariate measurement errors and parameter estimation in a failure time regression model. Biometrika 69, 331-342 (1982
17. Raftery, A.E.: Bayesian model selection in social research. Sociol Methodol 25, 111-163 (1995
18. Rizopoulos, D.: JM: An R package for the joint modeling of longitudinal and time-to-event data. J. Stat. Softw. 35, 1-33 (2010
19. Schwarz, G.: Estimating the dimension of a model. Ann. Stat. 6, 461-464 (1978
20. Siddiqui, O., Hung, H.M., O'Neill, R.: MMRM vs. LOCF: A comprehensive comparison based on simulation study and 25 NDA datasets. J. Biopharm. Stat. 19, 227-246 (2009
21. Song, X., Davidian, M., Tsiatis, A.A.: A semiparametric likelihood approach to joint modeling of longitudinal and time-to-event data. Biometrics 58, 742-753 (2002 (Pubitemid 36133752)
22. Spiegelhalter, D.J., Best, N.G., Carlin, B.P., van der Linde, A.: Bayesian measures of model complexity and fit (with discussion and rejoinder). J. R. Stat. Soc., Ser. B. 64, 583-639 (2002
23. Tsiatis, A.A., Davidian, M.: Joint modeling of longitudinal and time-to-event data: An overview. Stat. Sinica 14, 809-834 (2004 (Pubitemid 39499214)
24. Tsiatis, A.A., De Gruttola, V., Wulfsohn, M.S.: Modeling the relationship of survival to longitudinal data measures with error. Applications to survival and CD4 counts in patients with AIDS. J. Am. Stat. Assoc. 90, 27-37 (1995
25. Vogelzang, N., Rusthoven, J., Symanowski, J., Denham, C., Kaukel, E., Ruffie, P., Gatzemeier, U., Boyer, M., Emri, S., Manegold, C., Niyikiza, C., Paoletti, P.: Phase III study of pemetrexed in combination with cisplatin versus cisplatin alone in patients with malignant pleural mesothelioma. J. Clin. Oncol. 21, 2636-2644 (2003 (Pubitemid 46606305)
26. Wang, Y., Taylor, J.M.G.: Jointly modeling longitudinal and event time data with application to acquired immunodeficiency syndrome. J. Am. Stat. Assoc. 96, 895-905 (2001
27. Wulfsohn, M.S., Tsiatis, A.A.: A joint model for survival and longitudinal data measured with error. Biometrics 53, 330-339 (1997 (Pubitemid 27131905)
28. Xu, J., Zeger, S.L.: Joint analysis of longitudinal data comprising repeated measures and times to events. Appl. Stat. 50, 375-387 (2001 (Pubitemid 33399970)
29. Yu, M., Law, N.J., Taylor, J.M.G., Sandler, H.M.: Joint longitudinal-survival-cure models and their application to prostate cancer. Stat. Sinica 14, 835-862 (2004) (Pubitemid 39499215)