Managing clinical use of high-alert drugs: A supervised learning approach to pharmacokinetic data analysis

IEEE Transactions on Systems, Man, and Cybernetics Part A:Systems and Humans

Volumn 37, Issue 4, 2007, Pages 481-492

  Hu, Paul Jen Hwa ^a   Cheng, Tsang Hsiang ^b   Wei, Chih Ping ^c   Yu, Chun Hui ^d,e   Chan, Agnes L F ^f   Wang, Hue Yu ^f  

^a UNIVERSITY OF UTAH   (United States)

^b SOUTHERN TAIWAN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Taiwan)

^c NATIONAL TSING HUA UNIVERSITY   (Taiwan)

^d TIAN SHENG MEMORIAL HOSPITAL   (Taiwan)

^e TZU HUI INSTITUTE OF TECHNOLOGY   (Taiwan)

^f CHI MEI MEDICAL CENTER   (Taiwan)

Author keywords

Bagging; Decision support in health care; Management of clinical use of vancomycin; Model tree based regression; Pharmacokinetic data mining; Supervised learning; Support vector machine (SVM)

Indexed keywords

COMPUTER SIMULATION; DATA MINING; DECISION SUPPORT SYSTEMS; PATIENT MONITORING; PHARMACOKINETICS; REGRESSION ANALYSIS; SUPPORT VECTOR MACHINES;

MODEL-TREE-BASED REGRESSION TECHNIQUE; PATIENT MANAGEMENT;

SUPERVISED LEARNING;

EID: 34347391689     PISSN: 10834427     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSMCA.2007.897700     Document Type: Article

References (40)

1. E. Bauer and R. Kohavi, "An empirical comparison of voting classification algorithms: Bagging, boosting, and variants," Mach. Learn., vol. 36, no. 1/2, pp. 105-142, Jul./Aug. 1999.
2. L. Breiman, "Bagging predictors," Mach. Learn., vol. 24, no. 2, pp. 123-140, Aug. 1996.
3. R. Burbidge, M. Trotter, B. Buxton, and S. Holden, "Drug design by machine learning: Support vector machines for pharmaceutical data analysis," Comput. Chem., vol. 26, no. 1, pp. 5-14, Dec. 2001.
4. Center for Biologics Evaluation and Research, Food and Drug Administration, U.S. Department of Health and Human Services, Guidance for Industry: Pharmacokinetics in Patients With Impaired Renal Function - Study Design, Data Analysis, and Impact on Dosing and Labeling, May 1998. [Online]. Available: http://www.fda.gov/cber/ gdlns/renal.pdf
5. H. Chow, K. M. Tolle, D. J. Roe, C. Elsberry, and H. Chen, "Application of neural networks to population pharmacokinetic data analysis," J. Pharm. Sci., vol. 86, no. 7, pp. 840-845, Jul. 1997.
6. F. R. Ernst and A. J. Grizzle, "Drug-related morbidity and mortality: Updating the cost-of-illness model," J. Amer. Pharm. Assoc., vol. 41, no. 2, pp. 192-199, 2001.
7. Y. Freund, "Boosting a weak learning algorithm by majority," Inf. Comput., vol. 121, no. 2, pp. 256-285, Sep. 1996.
8. Y. Freund and R. E. Schapire, "Experiments with a new boosting algorithm," in Proc. 13th Nat. Conf. Mach. Learn., 1996, pp. 148-156.
9. R. Herman, "Current issues related to therapeutic drug monitoring: Vancomycin," World Drug Inf., vol. 14, no. 1, pp. 1-4, 6, 2003.
10. A.K. Hurst, M. A. Yoshinaga, G. H. Mitani, K. A. Foo, R. W. Jelliffe, and E. C. Harrison, "Application of a Bayesian method to monitor and adjust vancomycin dosage regimens," Antimicrob. Agents Chemother. vol. 34, no. 6, pp. 1165-1171, Jun. 1990.
11. R. W. Jelliffe, P. Maire, F. Sattler, P. Gomis, and B. Tahani, "Adaptive control of drug dosage regimens: Basic foundations, relevant issues, and clinical examples," Int. J. Bio-Med. Comput., vol. 36, no. 1/2, pp. 1-23, Jun. 1994.
12. R. W. Jelliffe, A. Schumitzky, M. Van Guilder, M. Liu, L. Hu, P. Maire, P. Gomis, X. Barbaut, and B. Tahani, "Individualizing drug dosage regimens: Roles of population pharmacokinetic and dynamic models, Bayesian fitting, and adaptive control," Ther. Drug Monit., vol. 15, no. 5, pp. 380-393, Oct. 1993.
13. J. A. Johnson and J. L. Bootman, "Drug-related morbidity and mortality: A cost-of-illness model," Arch. Inter. Med., vol. 155, no. 18, pp. 1949-1956, Oct. 1995.
14. K.D. Lake and C. D. Peterson, "Evaluation of a method for initiating vancomycin therapy: Experience in 205 patients," Pharmacotherapy, vol. 8, no. 5, pp. 284-286, 1988.
15. W. G. Leader, M. H. Chandler, and M. Castiglia, "Pharmacokinetic optimisation of vancomycin therapy," Clin. Pharmacokinet., vol. 28, no. 8, pp. 327-342, Apr. 1995.
16. J. Listgarten, S. Damaraju, B. Poulin, L. Cook, J. Dufour, A. Driga, J. Mackey, D. Wishart, R. Greiner, and B. Zanke, "Predictive models for breast cancer susceptibility from multiple single nucleotide polymorphisms," Clin. Cancer Res., vol. 10, no. 8, pp. 2725-2737, Apr. 2004.
17. G. R. Matzke, J. M. Kovarik, M. J. Rybak, and S. C. Boike, "Evaluation of the vancomycin-clearance: Creatinine-clearance relationship for predicting vancomycin dosage," Clin. Pharm., vol. 4, no. 3, pp. 311-315, May/Jun. 1985.
18. M. Michel and L. Gutmann, "Methicillin-resistance staphylococcus aureus and vancomycin-resistant enterococci: Therapeutic realities and possibilities," Lancet, vol. 349, no. 9069, pp. 1901-1906, 1997.
19. R. C. Moellering, D. J. Krogstad, and D. J. Greenblatt, "Vancomycin therapy in patients with impaired renal function: A nomogram for dosage," Annu. Intern. Med., vol. 94, no. 3, pp. 343-346, Mar. 1981.
20. D. J. Pauly, D. M. Musa, M. R. Lestico, M. J. Lindstrom, and C. M. Hetsko, "Risk of nephrotoxicity with combination vancomycinaminoglycoside antibiotic therapy," Pharmacotherapy, vol. 10, no. 6, pp. 378-382, 1990.
21. F. Pea, M. Bertolissi, A. D. Silvestre, D. Poz, F. Giordano, and M. Furlanut, "TDM coupled with Bayesian forecasting should be considered an invaluable tool for optimizing vancomycin daily exposure in unstable critically ill patients," Int. J. Antimicrob. Agents, vol. 20, no. 5, pp. 326-332, Nov. 2002.
22. C. A. Pedersen, P. J. Schneider, and D. J. Scheckelhoff, "ASHP national survey of pharmacy practice in hospital settings: Monitoring and patient education-2003," Amer. J. Health-Syst. Pharm., vol. 61, no. 5, pp. 457-471, Mar. 2004.
23. J. R. Quinlan, "Induction of decision trees," Mach. Learn., vol. 1, no. 1, pp. 81-106, 1986.
24. J.R. Quinlan, "Learning with continuous classes," in Proc. 5th Australian Joint Conf. Artif. Intell., 1992, pp. 343-348.
25. J. R. Quinlan, C4.5: Programs for Machine Learning. San Mateo, CA: Morgan Kaufmann, 1993.
26. J. R. Quinlan, "Bagging, boosting, and C4.5," in Proc. 13th Nat. Conf. Artif. Intell. (AAAD), Portland, OR, 1996, pp. 725-730.
27. S. Sabbatani, B. Cannella, C. Fulgaro, E. Pipitone, and R. Cesari, "Pharmaco-economic evaluation of antibiotic therapy in a ward for infections diseases," Le Infez. Med., vol. 8, no. 3, pp. 156-166, 2000.
28. R. E. Schapire, "The strength of weak learnability," Mach. Learn. vol. 5, no. 2, pp. 197-227, Jun. 1990.
29. H. P. Selker, J. L. Griffith, S. Patil, W. J. Long, and R. B. D'Agostino, "A comparison of performance of mathematical predictive methods for medical diagnosis: Identifying acute cardiac ischemia among emergency department patients," J. Investig. Med., vol. 43, no. 5, pp. 468-476, Oct. 1995.
30. J. Shifiey, J. D. Paine, G. Sarah, and J. D. Benator, "JCAHO initiative seeks to improve patient safety," Drug Benefit Trends, vol. 15, no. 1, pp. 23-24, 2003.
31. A. J. Smola and B. Schölkopf, "A tutorial on support vector regression," Stat. Comput., vol. 14, no. 3, pp. 199-222, 2004.
32. K. M. Tolle, H. Chen, and H. Chow, "Estimating drug/plasma concentration levels by applying neural networks to pharmacokinetic data sets," Decis. Support Syst., vol. 30, no. 2, pp. 139-152, Dec. 2000.
33. L. S. Tyler and N. A. Nickman, "Hospital pharmacy compliance with JCAHO standards and ASHP guidelines for reporting adverse drug reactions," Amer. J. Hosp. Pharm., vol. 49, no. 4, pp. 845-850, Apr. 1992.
34. V. Vapnik, The Nature of Statistical Learning Theory. New York: Springer-Verlag, 1995.
35. J. L. Vincent, D. J. Bihari, P. M. Suter, H. A. Bruining, J. White, M. H. Nicolas-Chanoin, M. Wolff, R. C. Spencer, and M. Hemmer, "The prevalence of nosocomial infection in intensive care units in europe: Results of the European Prevalence of Infection in Intensive Care (EPIC) study. EPIC International Advisory Committee," J. Amer. Med. Assoc. vol. 274, no. 8, pp. 639-644, Aug. 1995.
36. Y. Wang and I. H. Witten, "Induction of model trees for predicting continuous classes," in Proc. Eur. Conf. Mach. Learn., 1997, pp. 128-137.
37. M.E. Winter, Basic Clinical Pharmacokinetics, 4th ed. Baltimore, MD: Lippincott Williams Wilkins, 2004, p. 451.
38. Y. Xue, C. W. Yap, L. Z. Sun, Z. W. Cao, J. F. Wang, and Y. Z. Chen, "Prediction of P-glycoprotein substrates by a support vector machine approach," J. Chem. Inf. Comput. Sci., vol. 44, no. 4, pp. 1497-1505, Jul./Aug. 2004.
39. S. Yamamura, R. Takehira, K. Kawada, K. Nishizawa, S. Katayama, M. Hirano, and Y. Momose, "Application of artificial neural network modeling to identify severely ill patients whose aminoglycoside concentrations are likely to fall below therapeutic concentrations," J. Clin. Pharm. Ther., vol. 28, no. 5, pp. 425-432, Oct. 2003.
40. Z. H. Zhou, J. Wu, and W. Tang, "Ensembling neural networks: Many could be better than all," Artif Intell., vol. 137, no. 1/2, pp. 239-263, May 2002.