Optimal individualized dosing strategies: A pharmacologic approach to developing dynamic treatment regimens for continuous-valued treatments

Biometrical Journal

Volumn 58, Issue 3, 2016, Pages 502-517

  Rich, Benjamin ^a   Moodie, Erica E M ^a   Stephens, David A ^b  

^a MCGILL UNIVERSITY   (Canada)

^b MCGILL UNIVERSITY   (Canada)

Author keywords

Adaptive individualized dosing; Anticoagulation therapy; Continuous doses; Dynamic treatment regimens; G estimation

Indexed keywords

DRUG DOSAGE;

ADAPTIVE INDIVIDUALIZED DOSING; ANTICOAGULATION THERAPY; CONTINUOUS DOSE; DOSING STRATEGY; DRUG RESPONSE; DYNAMIC TREATMENT REGIMEN; DYNAMIC TREATMENTS; G-ESTIMATION; OPTIMAL TREATMENT; REALISTIC SIMULATION;

PHARMACOKINETICS;

ANTICOAGULANT AGENT; WARFARIN;

CLINICAL PROTOCOL; COMPUTER SIMULATION; DOSE CALCULATION; HUMAN; PERSONALIZED MEDICINE; PROCEDURES;

ANTICOAGULANTS; CLINICAL PROTOCOLS; COMPUTER SIMULATION; DRUG DOSAGE CALCULATIONS; HUMANS; PRECISION MEDICINE; WARFARIN;

EID: 84949035372     PISSN: 03233847     EISSN: 15214036     Source Type: Journal    
DOI: 10.1002/bimj.201400244     Document Type: Article

References (32)

1. Blesius, A., Chabaud, S., Cucherat, M., Mismetti, P., Boissel, J. P., and Nony, P. (2006). Compliance-guided therapy: a new insight into the potential role of clinical pharmacologists. Clinical Pharmacokinetics 45, 95-104.
2. Budnitz, D. S., Lovegrove, M. C., Shehab, N., and Richards, C. L. (2011). Emergency hospitalizations for adverse drug events in older Americans. The New England Journal of Medicine 365, 2002-2012.
3. Chakraborty, B. and Moodie, E. E. M. (2013). Statistical Methods for Dynamic Treatment Regimes: Reinforcement Learning, Causal Inference, and Personalized Medicine, Springer, New York, NY.
4. Cotton, C. A. and Heagerty, P. J. (2011). A data augmentation method for estimating the causal effect of adherence to treatment regimens targeting control of an intermediate measure. Statistics in Biosciences 3, 28-44.
5. Cromme, L., Völler, H., Gäbler, F., Salzwedel, A., and Taborski, U. (2010). Computer-aided dosage in oral anticoagulation therapy using phenprocoumon: Problems and approaches. Hämostaseologie 30, 183-189.
6. D'Argenio, D. Z. and Khakmahd, K. (1983). Adaptive control of theophylline therapy: importance of blood sampling times. Journal of Pharmacokinetics and Biopharmaceutics 11, 547-559.
7. Dawid, A. P. and Didelez, V. (2010). Identifying the consequences of dynamic treatment strategies: a decision-theoretic overview. Statistics Surveys 4, 184-231.
8. Dayneka, N. L., Garg, V., and Jusko, W. J. (1993). Comparison of four basic models of indirect pharmacodynamic responses. Journal of Pharmacokinetics and Biopharmaceutics 21, 457-478.
9. Funatogawa, I. and Funatogawa, T. (2012). Dose-response relationship from longitudinal data with response-dependent dose modification using likelihood methods. Thrombosis Research 54, 494-506.
10. Furie, B. (2013). Do pharmacogenetics have a role in the dosing of vitamin K antagonists? New England Journal of Medicine 369, 2345-2346.
11. Fusaro, V. A., Patil, P., Chi, C. l., Contant, C. F., and Tonellato, P. J. (2013). A systems approach to designing effective clinical trials using simulations. Circulation 127, 517-526.
12. Gabrielsson, J. and Weiner, D. (2007). Pharmacokinetic and Pharmacodynamic Data Analysis: Concepts and Applications (4th edn.). Swedish Pharmaceutical Press, Stockholm, SE.
13. Gibaldi, M. and Perrier, D. (1982). Pharmacokinetics. Marcel Dekker, New York, NY.
14. Henderson, R., Ansell, P., and Alshibani, D. (2010). Regret-regression for optimal dynamic treatment regimes. Biometrics 66, 1192-1201.
15. Hirsh, J., Dalen, J. E., Anderson, D. R., Poller, L., Bussey, H., Ansell, J., and Deykin, D. (2001). Oral anticoagulants: mechanism of action, clinical effectiveness, and optimal therapeutic range. Chest 119, 8S-21S.
16. Holford, N. H. G. (1986). Clinical pharmacokinetics and pharmacodynamics of warfarin: understanding the dose-effect relationship. Clinical Pharmacokinetics 11, 483-504.
17. Joffe, M. M., Yang, W. P., and Feldman, H. (2012). G-estimation and artificial censoring: Problems, challenges, and applications. Biometrics 68, 275-286.
18. Lei, H., Nahum-Shani, I., Lynch, K., Oslin, D., and Murphy, S. (2012). A "SMART" design for building individualized treatment sequences. Annual Review of Clinical Psychology 8, 21-48.
19. Michaud, V., Vanier, M. C., Brouillette, D., Roy, D., Verret, L., Noel, N., Taillon, I., O'Hara, G., Gossard, D., Champagne, M., Goodman, K., Renaud, Y., Brown, A., Phillips, M., Ajami, A. M., and Turgeon, J. (2008). Combination of phenotype assessments and CYP2C9-VKORC1 polymorphisms in the determination of warfarin dose requirements in heavily medicated patients. Clinical Pharmacology and Therapeutics 83, 740-748.
20. Moodie, E. E. M. (2009). A note on the variance of doubly-robust G-estimators. Biometrika 96, 998-1004.
21. Moodie, E. E. M. and Richardson, T. S. (2010). Estimating optimal dynamic regimes: correcting bias under the null. Scandinavian Journal of Statistics 37, 126-146.
22. Moodie, E. E. M., Richardson, T. S., and Stephens, D. A. (2007). Demystifying optimal dynamic treatment regimes. Biometrics 63, 447-455.
23. Murphy, S. A. (2003). Optimal dynamic treatment regimes. Journal of the Royal Statistical Society: Series B 65, 331-355.
24. Nielsen, P. B., Lundbye-Christensen, S., Rasmussen, L. H., and Larsen, T. B. (2014). Improvement of anticoagulant treatment using a dynamic decision support algorithm: a Danish cohort study. Thrombosis Research 133, 375-379.
25. Poller, L., Keown, M., Ibrahim, S., Lowe, G., Moia, M., Turpie, A., Roberts, C., van den Besselaar, A., van der Meer, F., Tripodi, A., Palareti, G., Shiach, C., Bryan, S., Samama, M., Burgess-Wilson, M., Heagerty, A., Maccallum, P., Wright, D., and Jespersen, J. (2008). An international multicenter randomized study of computer-assisted oral anticoagulant dosage vs. medical staff dosage. Journal of Thrombosis and Haemostasis 6, 935-943.
26. Poller, L., Keown, M., Ibrahim, S., Lowe, G., Moia, M., Turpie, A., Roberts, C., van den Besselaar, A., van der Meer, F., Tripodi, A., Palareti, G., Shiach, C., Bryan, S., Samama, M., Burgess-Wilson, M., Heagerty, A., Maccallum, P., Wright, D., Jespersen, J., and on Anticoagulation (EAA), T.E.A., (2009). A multicentre randomised assessment of the DAWN AC computer-assisted oral anticoagulant dosage program. Thrombosis and Haemostasis 101, 487-494.
27. Rich, B., Moodie, E. E. M., Stephens, D. A., and Platt, R. W. (2010). Model checking with residuals for g-estimation of optimal dynamic treatment regimes. The International Journal of Biostatistics 6, Article 12.
28. Robins, J. M. (2004). Optimal structural nested models for optimal sequential decisions, In D.Y. Lin and P.J. Heagerty (Eds.), Proceedings of the Second Seattle Symposium in Biostatistics: Analysis of Correlated Data, Springer, New York, NY.
29. Rosthøj, S., Fullwood, C., Henderson, R., and Stewart, S. (2006). Estimation of optimal dynamic anticoagulation regimes from observational data: a regret-based approach. Statistics in Medicine 25, 4197-4215.
30. Teml, A., Schaeffeler, E., Herrlinger, K. R., Klotz, U., and Schwab, M. (2007). Thiopurine treatment in inflammatory bowel disease. Clinical Pharmacokinetics 46, 187-208.
31. The International Warfarin Pharmacogenetics Consortium. (2009). Estimation of the warfarin dose with clinical and pharmacogenetic data. The New England Journal of Medicine 360, 753-764.
32. Wysowski, D. K., Nourjah, P., and Swartz, L. (2007). Bleeding complications with warfarin use: a prevalent adverse effect resulting in regulatory action. Archives of Internal Medicine 167, 1414-1419.