Performance of Nonlinear Mixed Effects Models in the Presence of Informative Dropout

AAPS Journal

Volumn 17, Issue 1, 2015, Pages 245-255

  Björnsson, Marcus A ^a,b   Friberg, Lena E ^b   Simonsson, Ulrika S H ^b  

^a ASTRAZENECA R AND D   (Sweden)

^b UPPSALA UNIVERSITY   (Sweden)

Author keywords

bias; informative dropout; nonlinear mixed effects; NONMEM

Indexed keywords

ANALYTIC METHOD; ARTICLE; FOCE I METHOD; INFORMATION PROCESSING; LAPLACE METHOD; MEASUREMENT ACCURACY; NONLINEAR SYSTEM; PLACEBO EFFECT; PROCESS MODEL; STATISTICAL MODEL; STATISTICAL PARAMETERS; CLINICAL TRIAL (TOPIC); COMPUTER SIMULATION; HUMAN; PATIENT DROPOUTS; STATISTICAL ANALYSIS; STATISTICAL BIAS; STATISTICS AND NUMERICAL DATA;

BIAS (EPIDEMIOLOGY); CLINICAL TRIALS AS TOPIC; COMPUTER SIMULATION; DATA INTERPRETATION, STATISTICAL; HUMANS; MODELS, STATISTICAL; NONLINEAR DYNAMICS; PATIENT DROPOUTS;

EID: 84922106194     PISSN: None     EISSN: 15507416     Source Type: Journal    
DOI: 10.1208/s12248-014-9700-x     Document Type: Article

References (14)

1. Heyting A, Tolboom JT, Essers JG. Statistical handling of drop-outs in longitudinal clinical trials. Stat Med. 1992;11(16):2043–61.
2. Siddiqui O, Hung HM, O'Neill R. MMRM vs. LOCF: a comprehensive comparison based on simulation study and 25 NDA datasets. J Biopharm Stat. 2009;19(2):227–46.
3. Laird NM. Missing data in longitudinal studies. Stat Med. 1988;7(1–2):305–15.
4. Rubin DB. Inference and missing data. Biometrika. 1976;63:581–92.
5. Little RJA, Rubin DB. Statistical analysis with missing data. New York: Wiley; 1987.
6. Gastonguay MR, French JL, Heitjan DF, Rogers JA, Ahn JE, Ravva P. Missing data in model-based pharmacometric applications: points to consider. J Clin Pharmacol. 2010;50(9 Suppl):63S–74.
7. Hu C, Sale ME. A joint model for nonlinear longitudinal data with informative dropout. J Pharmacokinet Pharmcodyn. 2003;30(1):83–103.
8. Gomeni R, Lavergne A, Merlo-Pich E. Modelling placebo response in depression trials using a longitudinal model with informative dropout. Eur J Pharm Sci. 2009;36(1):4–10.
9. Hu C, Szapary PO, Yeilding N, Zhou H. Informative dropout modeling of longitudinal ordered categorical data and model validation: application to exposure-response modeling of physician's global assessment score for ustekinumab in patients with psoriasis. J Pharmacokinet Pharmacodyn. 2011;38(2):237–60.
10. Friberg LE, de Greef R, Kerbusch T, Karlsson MO. Modeling and simulation of the time course of asenapine exposure response and dropout patterns in acute schizophrenia. Clin Pharmacol Ther. 2009;86(1):84–91.
11. Bjornsson MA, Simonsson USH. Modelling of pain intensity and informative dropout in a dental pain model after naproxcinod, naproxen and placebo administration. Br J Clin Pharmacol. 2011;71(6):899–906.
12. Beal SLSL, Boeckmann AJ. NONMEM users guides. Ellicott City: ICON Development Solutions; 1989–2006.
13. Lindbom L, Pihlgren P, Jonsson EN. PsN-Toolkit—a collection of computer intensive statistical methods for non-linear mixed effect modeling using NONMEM. Comput Methods Programs Biomed. 2005;79(3):241–57.
14. Jonsson EN, Karlsson MO. Xpose—an S-PLUS based population pharmacokinetic/pharmacodynamic model building aid for NONMEM. Comput Methods Programs Biomed. 1999;58(1):51–64.