Formulae for estimation of kidney function as an approach to calculating drug doses: A scoping review
DOI:
https://doi.org/10.46542/pe.2024.243.322328Keywords:
Drug safety, Estimation formula, Kidney functionAbstract
Background: The kidneys are the main organ for drug excretion, and it is critical to assess kidney function when designing dosage regimens for drugs that undergo renal elimination. Various formulae have been used to estimate kidney function and safely adjust doses.
Objective: This research reviewed studies that assessed patients' kidney function with various approaches to provide appropriate choices of kidney function estimation formulas based on patients' age and clinical conditions.
Method: The search involved browsing scientific articles in PubMed and ScienceDirect with the keywords (("assessment") AND ("GFR") AND ("formula")) OR ("renal function") AND ("human")) AND (“Creatinine”). The articles included were those available in full text and English. Thirty articles addressing the formulae for kidney function assessment were reviewed.
Result: The Schwartz formula is more appropriate for pediatric and adult patients, whereas the creatinine-based chronic kidney disease epidemiology (CKD-EPI) formula can be used in geriatrics, obese patients, and patients already known to have decreased kidney function. The cystatin C-based CKD-EPI formula is for patients with HIV and post-transplant patients.
Conclusion: This study identified that physiological conditions, especially patients’ age and pathology, should be considered in devising formulae to estimate kidney function to accurately calculate safe drug doses.
References
Alhelal, K., Almotairi, W., Alrajhi, Y., Alghunaim, A., Alfouzan, R., Vasudevan, D. S. & Mansour, M. (2020). Early post-transplant renal functions predict incidence of acute rejection in kidney transplantation. Journal of Pharmaceutical Research International, 32(34). https://doi.org/10.9734/JPRI/2020/v32i3430964
Beetham, K. S., Howden, E. J., Isbel, N. M. & Coombes, J. S. (2018). Agreement between cystatin-C and creatinine based eGFR estimates after a 12-month exercise intervention in patients with chronic kidney disease. BMC Nephrol, 19(1), 366 https://doi.org/10.1186/s12882-018-1146-4
Björk, J., Nyman, U., Larsson, A., Delanaye, P. & Pottel, H. (2021). Estimation of the glomerular filtration rate in children and young adults by means of the CKD-EPI equation with age-adjusted creatinine values. Kidney Int, 99(4), 940‒947 https://doi.org/10.1016/j.kint.2020.10.017
Browne, G. M., Eustace, J. A., Fitzgerald, A. P., Lutomski, J. E. & Perry, I. J. (2012). Prevalence of diminished kidney function in a representative sample of middle and older age adults in the Irish population. BMC Nephrology, 13(1), 144 https://doi.org/10.1186/1471-2369-13-144
Casal, M. A., Nolin, T. D. & Beumer, J. H. (2019). Estimation of kidney function in oncology: Implications for anticancer drug selection and dosing. Clin J Am Soc Nephrol, 14(4), 587‒595 https://doi.org/10.2215/cjn.11721018
Chrobak, L., Dębska-Ślizień, A., Jankowska, M., Sledziński, Z. & Rutkowski, B. (2014). Epidemiology of posttransplantation chronic kidney disease can be altered by choice of formula estimating glomerular filtration rate. Transplant Proc, 46(8), 2660‒2663 https://doi.org/10.1016/j.transproceed.2014.09.008
Cristelli, M. P., Cofán, F., Rico, N., Trullàs, J. C., Manzardo, C., Agüero, F., Bedini, J. L., Moreno, A., Oppenheimer, F., Miro, J. M., Dieckman, F., Cases, A., Poch, E., Martinez, E., Blanco, J. L., García, F., Mallolas, J., Gatell, J. M. & the, C. K. D. H. C. I. (2017). Estimation of renal function by CKD-EPI versus MDRD in a cohort of HIV-infected patients: A cross-sectional analysis. BMC Nephrology, 18(1), 58 https://doi.org/10.1186/s12882-017-0470-4
Ebert, N., Loesment, A., Martus, P., Jakob, O., Gaedeke, J., Kuhlmann, M., Bartel, J., Schuchardt, M., Toelle, M., Huang, T., van der Giet, M. & Schaeffner, E. (2015). Iohexol plasma clearance measurement in older adults with chronic kidney disease - Sampling time matters. Nephrology Dialysis Transplantation, 30. https://doi.org/10.1093/ndt/gfv116
Erstad, B. L. & Nix, D. E. (2021). Assessment of kidney function in patients with extreme obesity: A narrative review. Ann Pharmacother, 55(1), 80‒88 https://doi.org/10.1177/1060028020935580
Ferreira, J. P., Girerd, N., Pellicori, P., Duarte, K., Girerd, S., Pfeffer, M. A., McMurray, J. J., Pitt, B., Dickstein, K., Jacobs, L., Staessen, J. A., Butler, J., Latini, R., Masson, S., Mebazaa, A., Rocca, H. P., Delles, C., Heymans, S., Sattar, N., Jukema, J. W., Cleland, J. G., Zannad, F. & Rossignol, P. (2016). Renal function estimation and Cockroft-Gault formulas for predicting cardiovascular mortality in population-based, cardiovascular risk, heart failure and post-myocardial infarction cohorts: The Heart 'OMics' in AGEing (HOMAGE) and the high-risk myocardial infarction database initiatives. BMC Med, 14(1), 181 https://doi.org/10.1186/s12916-016-0731-2
Gao, A., Cachat, F., Faouzi, M., Bardy, D., Mosig, D., Meyrat, B. J., Girardin, E. & Chehade, H. (2013). Comparison of the glomerular filtration rate in children by the new revised Schwartz formula and a new generalised formula. Kidney Int, 83(3), 524‒530 https://doi.org/10.1038/ki.2012.388
Gowda, S., Desai, P. B., Kulkarni, S. S., Hull, V. V., Math, A. A. & Vernekar, S. N. (2010). Markers of renal function tests. N Am J Med Sci, 2(4), 170‒173.
Hirayama, A., Konta, T., Kamei, K., Suzuki, K., Ichikawa, K., Fujimoto, S., Iseki, K., Moriyama, T., Yamagata, K., Tsuruya, K., Kimura, K., Narita, I., Kondo, M., Asahi, K., Kurahashi, I., Ohashi, Y. & Watanabe, T. (2015). Blood pressure, proteinuria, and renal function decline: Associations in a large community-based population. Am J Hypertens, 28(9), 1150‒1156 https://doi.org/10.1093/ajh/hpv003
Inker, L. A., Schmid, C. H., Tighiouart, H., Eckfeldt, J. H., Feldman, H. I., Greene, T., Kusek, J. W., Manzi, J., Van Lente, F., Zhang, Y. L., Coresh, J. & Levey, A. S. (2012). Estimating glomerular filtration rate from serum creatinine and cystatin C. New England Journal of Medicine, 367(1), 20‒29 https://doi.org/10.1056/NEJMoa1114248
Januškevičiūtė, E., Vicka, V., Krauklytė, J., Vickienė, A., Ringaitienė, D., Šerpytis, M. & Šipylaitė, J. (2021). Acute kidney injury in cardiac Surgery patients: Role of glomerular filtration rate and fat-free mass. Acta Med Litu, 28(1), 112‒120 https://doi.org/10.15388/Amed.2021.28.1.22
Kim, B. Y., Choi, D. H., Jung, C. H., Mok, J. O. & Kim, C. H. (2021). Associations between obesity, weight change and decreased renal function in Korean type 2 diabetic patients: a longitudinal follow-up study. BMC Endocr Disord, 21(1), 188 https://doi.org/10.1186/s12902-021-00853-z
Kukla, A., Issa, N., Jackson, S., Spong, R., Foster, M. C., Matas, A. J., Mauer, M. S., Eckfeldt, J. H. & Ibrahim, H. N. (2014). Cystatin C enhances glomerular filtration rate estimating equations in kidney transplant recipients. Am J Nephrol, 39(1), 59‒65 https://doi.org/10.1159/000357594
Lemoine, S., Guebre-Egziabher, F., Sens, F., Nguyen-Tu, M. S., Juillard, L., Dubourg, L. & Hadj-Aissa, A. (2014). Accuracy of GFR estimation in obese patients. Clin J Am Soc Nephrol, 9(4), 720V727 https://doi.org/10.2215/cjn.03610413
Maioli, C., Mangano, M., Conte, F., Del Sole, A., Tagliabue, L., Alberici, F., Galassi, A. & Cozzolino, M. (2020). The ideal marker for measuring GFR: what are we looking for? Acta Biomed, 91(4), e2020132 https://doi.org/10.23750/abm.v91i4.9304
Matsushita, K., Tonelli, M., Lloyd, A., Levey, A. S., Coresh, J. & Hemmelgarn, B. R. (2012). Clinical risk implications of the CKD Epidemiology Collaboration (CKD-EPI) equation compared with the Modification of Diet in Renal Disease (MDRD) Study equation for estimated GFR. Am J Kidney Dis, 60(2), 241‒249 https://doi.org/10.1053/j.ajkd.2012.03.016
Mayne, T. J., Nordyke, R. J., Schold, J. D., Weir, M. R. & Mohan, S. (2021). Defining a minimal clinically meaningful difference in 12-month estimated glomerular filtration rate for clinical trials in deceased donor kidney transplantation. Clin Transplant, 35(7), e14326 https://doi.org/10.1111/ctr.14326
Motie, M., Evangelista, L. S., Lombardo, D., Hoi, J., Horwich, T. B., Hamilton, M. & Fonarow, G. C. (2017). Effect of weight loss on renal function in overweight and obese patients with heart failure. Diabetes Metab Syndr, 11(2), 95‒98 https://doi.org/10.1016/j.dsx.2016.06.026
Pieters, T. T., Beele, P., Van Zuilen, A. D., Verhaar, M. C., Huitema, A. D. R. & Rookmaaker, M. B. (2020). Early estimation of renal function after transplantation to enable appropriate dosing of critical drugs: Retrospective analysis of 103 patients in a single center. Clin Pharmacokinet, 59(10), 1303‒1311 https://doi.org/10.1007/s40262-020-00893-z
Polkinghorne, K. R., Wolfe, R., Jachno, K. M., Wetmore, J. B., Woods, R. L., McNeil, J. J., Nelson, M. R., Reid, C. M. & Murray, A. M. (2019). Prevalence of chronic kidney disease in the elderly using the ASPirin in Reducing Events in the Elderly study cohort. Nephrology (Carlton), 24(12), 1248‒1256 https://doi.org/10.1111/nep.13565
Rocco, M. V., Chapman, A., Chertow, G. M., Cohen, D., Chen, J., Cutler, J. A., Diamond, M. J., Freedman, B. I., Hawfield, A., Judd, E., Killeen, A. A., Kirchner, K., Lewis, C. E., Pajewski, N. M., Wall, B. M. & Yee, J. (2016). Chronic kidney disease classification in systolic blood pressure intervention trial: Comparison using modification of diet in renal disease and CKD-epidemiology collaboration definitions. Am J Nephrol, 44(2), 130‒140 https://doi.org/10.1159/000448722
Rothberg, A. E., McEwen, L. N. & Herman, W. H. (2020). Severe obesity and the impact of medical weight loss on estimated glomerular filtration rate. PLoS One, 15(2), e0228984 https://doi.org/10.1371/journal.pone.0228984
Sato, S., Fujiwara, H., Oishi, T., Shimada, M., Machida, S., Takei, Y., Itamochi, H., Suzuki, M. & Kigawa, J. (2012). Evaluation of a formula for individual dosage of nedaplatin based on renal function. Cancer Chemotherapy and Pharmacology, 69(3), 599‒603 https://doi.org/10.1007/s00280-011-1739-0
Selistre, L., Rabilloud, M., Cochat, P., de Souza, V., Iwaz, J., Lemoine, S., Beyerle, F., Poli-de-Figueiredo, C. E. & Dubourg, L. (2016). Comparison of the Schwartz and CKD-EPI equations for estimating glomerular filtration rate in children, adolescents, and adults: A retrospective cross-sectional study. PLoS Med, 13(3), e1001979 https://doi.org/10.1371/journal.pmed.1001979
Takeuchi, M., Imamura, C. K., Booka, E., Takeuchi, H., Mizukami, T., Kawakami, T., Funakoshi, T., Wakuda, K., Aoki, Y., Hamamoto, Y., Kitago, M., Kawakubo, H., Boku, N., Tanigawara, Y. & Kitagawa, Y. (2021). Prospective evaluation and refinement of an S-1 dosage formula based on renal function for clinical application. Cancer Sci, 112(2), 751‒759 https://doi.org/10.1111/cas.14758
Tøndel, C., Salvador, C. L., Hufthammer, K. O., Bolann, B., Brackman, D., Bjerre, A., Svarstad, E. & Brun, A. (2018). Iohexol plasma clearance in children: validation of multiple formulas and single-point sampling times. Pediatr Nephrol, 33(4), 683-696 https://doi.org/10.1007/s00467-017-3841-y
Wardhani, F., Chiuman, L., Ginting, C. & Ginting, S. (2020). Role of Cystatin-C as Serum Biomarkers in Predicting Glomerular Function-Associated with Copper-Induced Acute Kidney Injury. Majalah Kedokteran Bandung, 52, 16‒21 https://doi.org/10.15395/mkb.v52n1.1793
Weis, L., Metzger, M., Haymann, J. P., Thervet, E., Flamant, M., Vrtovsnik, F., Gauci, C., Houillier, P., Froissart, M., Letavernier, E., Stengel, B. & Boffa, J. J. (2013). Renal function can improve at any stage of chronic kidney disease. PLoS One, 8(12), e81835 https://doi.org/10.1371/journal.pone.0081835
Zhao, N., Zeng, Z., Liang, H., Wang, F., Yang, D., Xiao, J., Chen, M., Zhao, H., Zhang, F. & Gao, G. (2021). Estimation of renal function by three CKD-EPI equations in Chinese HIV/AIDS patients: A STROBE-compliant article. Medicine (Baltimore), 100(22), e26003 https://doi.org/10.1097/md.0000000000026003
