Drug Dosage Individualization Based on a Random-Effects Linear Model
Article Properties
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LanguageEnglish
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DOI (url)
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Publication Date2012/03/14
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Indian UGC (journal)
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Refrences24
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Citations17
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Francisco J. Diaz a Department of Biostatistics , University of Kansas Medical Center , Kansas City , Kansas , USA
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Myladis R. Cogollo b Department of Basic Sciences , Universidad EAFIT , Medellin , Colombia
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Edoardo Spina c Section of Pharmacology, Department of Clinical and Experimental Medicine and Pharmacology , University of Messina and IRCCS Centro Neurolesi “Bonino-Pulejo,” Policlinico Universitario di Messina , Messina , Italy
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Vincenza Santoro c Section of Pharmacology, Department of Clinical and Experimental Medicine and Pharmacology , University of Messina and IRCCS Centro Neurolesi “Bonino-Pulejo,” Policlinico Universitario di Messina , Messina , Italy
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Diego M. Rendon d Financial Analysis Unit. Secretaria de Hacienda , Medellin , Colombia
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Jose de Leon e Mental Health Research Center , Lexington , Kentucky , USA
Cite
Diaz, Francisco J., et al. “Drug Dosage Individualization Based on a Random-Effects Linear Model”. Journal of Biopharmaceutical Statistics, vol. 22, no. 3, 2012, pp. 463-84, https://doi.org/10.1080/10543406.2010.547264.
Diaz, F. J., Cogollo, M. R., Spina, E., Santoro, V., Rendon, D. M., & de Leon, J. (2012). Drug Dosage Individualization Based on a Random-Effects Linear Model. Journal of Biopharmaceutical Statistics, 22(3), 463-484. https://doi.org/10.1080/10543406.2010.547264
Diaz FJ, Cogollo MR, Spina E, Santoro V, Rendon DM, de Leon J. Drug Dosage Individualization Based on a Random-Effects Linear Model. Journal of Biopharmaceutical Statistics. 2012;22(3):463-84.
Journal Categories
Medicine
Public aspects of medicine
Toxicology
Poisons
Medicine
Therapeutics
Pharmacology
Science
Mathematics
Probabilities
Mathematical statistics
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Refrences
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
| The anti-phospholipid antibody syndrome (Hughes syndrome): therapeutic aspects | Best Practice & Research Clinical Rheumatology |
| 18 | 2000 |
| The anti-phospholipid antibody syndrome (Hughes syndrome): therapeutic aspects | 1999 | |||
| SAS/IML 9.2 User's Guide | 2008 | |||
| Linear Mixed Models for Longitudinal Data | 2000 | |||
| Population Pharmacokinetics | Clinical Pharmacokinetics |
| 98 | 1986 |
Citations
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
Dose-Related Reference Range as a Tool in Therapeutic Drug Monitoring | Therapeutic Drug Monitoring |
| 2022 | |
Measuring Individual Benefits of Medical Treatments Using Longitudinal Hospital Data with Non-Ignorable Missing Responses Caused by Patient Discharge: Application to the Study of Benefits of Pain Management Post Spinal Fusion | Revista Colombiana de Estadística | 2022 | ||
Using population crossover trials to improve the decision process regarding treatment individualization in N‐of‐1 trials | Statistics in Medicine |
| 2 | 2021 |
Linear Mixed Effect Models for Rehabilitation Research | American Journal of Physical Medicine & Rehabilitation |
| 2021 | |
| Individualized Multidirectional Variable Selection | Journal of the American Statistical Association |
| 17 | 2020 |
Citations Analysis
The category
Medicine: Medicine (General): Medical technology 10
is the most commonly referenced area in studies that cite this article. The first research to cite this article was titled Response to Diaz and de Leon “The Mathematics of Drug Dose Individualization Should be Built With Random Effects Linear Models” and was published in 2013. The most recent citation comes from a 2022 study titled Measuring Individual Benefits of Medical Treatments Using Longitudinal Hospital Data with Non-Ignorable Missing Responses Caused by Patient Discharge: Application to the Study of Benefits of Pain Management Post Spinal Fusion. This article reached its peak citation in 2020, with 4 citations. It has been cited in 11 different journals, 9% of which are open access. Among related journals, the Therapeutic Drug Monitoring cited this research the most, with 4 citations. The chart below illustrates the annual citation trends for this article.