Organ Dysfunction: Treating Patients With CKD and Liver Disease

JULY 10, 2012
Jeannette Y. Wick, RPH, MBA, FASCP

Because the renally and hepatically impaired are often not included in clinical trials, drug regimens for these populations can be challenging.

Every human tissue has the potential to metabolize drugs. Safe medication use, however, is usually most dependent on the condition of patients’ kidneys and livers. Organ dysfunction may decrease drug or drug metabolite excretion in phase 1 or phase 2 drug metabolism reactions (See Table), leading to accumulation and potential toxicity.

When evaluating whether to prescribe a drug, the parent compound isn’t the sole concern; some hepatically-reduced drug metabolites are excreted renally. Kidney and liver failure are quite different, but have at least 3 things in common—they increase in incidence with age, one may lead to the other, and they often challenge prescribers when medication therapy is indicated.3

Drug Metabolism

The FDA has approved many drugs with little pharmacokinetic (PK)/pharmacodynamic (PD) information in these special patient populations. In organ dysfunction patients, a specific challenge is use of new—and potentially better or targeted— pharmacologic agents in organ dysfunction patients. Gathering organ dysfunction data has traditionally been a post-marketing function.4,5

When lacking actual data, prescribers may monitor serum drug concentrations to achieve therapeutic target ranges; this is called pharmacologically guided dosing. If pharmacologically guided dosing is impossible, some clinicians reckon empirically; they extend dosing intervals, decrease doses, or both to avoid excess drug exposure. Empiric dosing creates some conundrums. Reducing doses to prevent excessive toxicity may also create a risk of suboptimal treatment.4,5

Kidney Dysfunction

The kidneys’ role in normal physiology is excretory, biosynthetic, and metabolic. Approximately 1 in 8 American adults has chronic kidney disease (CKD), and about 2% of these patients are in terminal end-stage renal disease.6,7 Silent until its late stages, CKD is often undiagnosed until symptomatic kidney failure threatens.

Usually, early to moderate CKD patients are relatively stable, although renal function continually decreases. Drug PK can be affected by:
  • the kidney’s altered metabolic capacity,
  • altered renal excretion pursuant to altered renal blood flow, or
  • production of nephrotoxic compounds.

Renal dysfunction causes a cascade of pathological and physiological alterations in every organ system; one significant effect is reduced hepatic drug clearance. In CKD, gene expression decreases, and circulating uremic toxins modify CYP450 activity. CKD can also reduce phase 2 hepatic metabolic reactions,2,3 and may also suppress phase 2 enzymatic activities, like glucuronidation and acetylation.8,9

CKD can affect drug absorption, plasma protein binding, and drug distribution in organs other than the kidney or liver. Although the mechanism is unclear, we know that as the kidneys fail, key gastrointestinal (GI) and kidney enzymatic systems become inhibited and alter some drug metabolism.10-12 CKD can decrease gastrointestinal P-glycoprotein, thus reducing first-pass metabolism or drug excretion, and increasing drug bioavailability. CKD also reduces GI gene expression, down-regulating intestinal CYP450.1,2 As renal impairment progresses from mild to moderate or severe, these changes become more marked.1,2,13

Measuring Renal Failure

Several methods are used to estimate degree of renal function. Direct measurement uses insulin clearance or exogenous filtration markers, and is not usually available clinically. Glomerular filtration rate (GFR) is a surrogate marker of renal drug elimination. Formulas can estimate GFR in most patients. Serum creatinine (SCr) can be used to differentiate degree of renal function, and estimate dose reduction of some drugs; measuring SCr has some limitations based on the formula used to estimate it.14,15

Clinicians have tried more than 25 formulas to estimate renal function using SCr levels, but many are too convoluted for clinical use. The National Kidney Foundation of the United States recommends using the Cockcroft and Gault (C&G) formula or the Modification of Diet in Renal Disease (MDRD; developed in 1999).16-18 Both formulas use SCr, age, and gender to estimate renal clearance. The C&G formula is shorter, easier to use, and has been used longer (since 1976). The MDRD equation can be corrected to improve its accuracy in African American patients.19-21

To avoid estimation’s pitfalls, health care providers can measure creatinine clearance (CrCl) via 24-hour urine collection. CrCl factors in muscle mass variations, which affect creatinine generation, but it may overestimate GFR since the kidneys secrete creatinine in addition to filtering it. Urine collection, prompt processing, and analysis can also be cumbersome in the clinical setting.14,15

Accuracy—not estimation—is critical in drugs with low therapeutic indices. Clinicians should not use C&G to estimate doses if an incorrect dose could jeopardize a patient’s life or a more accurate test is available. The MDRD is more precise than C&G, although it has limitations.18 Many online versions of these formulas are available to “do the math” for clinicians.

Liver Disease

Hepatic disease can alter PK or PD. Hepatic impairment can cause drug accumulation or, less often, prevent active metabolite formation (recall that phase 1 reactions often produce an active metabolite). Patients with liver dysfunction are generally less stable than those with CRF. Typically, liver function continually declines, but may do so precipitously.
  • Hepatic dysfunction usually manifests in distinct clinical patterns: Hepatocellular disease – often associated with viral hepatitis or alcoholic liver disease; manifests as liver injury, inflammation, and necrosis.
  • Cholestatic disease – associated with gallstones, malignant obstruction, primary biliary cirrhosis, exposure to certain drugs; manifests as bile flow inhibition.
  • Mixed pattern disease mixes hepatocellular and cholestatic injury, and is often drug-induced.22
The symptom onset and prominence patterns can suggest a diagnosis, particularly if major risk factors (age, gender, and exposure or risk behavior history) are considered. Table 3 lists some of liver disease’s many etiologies. In the United States, drug-induced liver injury (DILI) is now the leading cause of acute liver failure, exceeding all other causes combined.22-24

Of note, liver disease can sometimes alter kidney function, leading to accumulation of drugs/metabolites even if they are not hepatically eliminated.25,26

Researchers have attempted to establish reliable laboratory measures of hepatic function. They’ve also considered ascites, encephalopathy, nutritional status, peripheral edema, and histological evidence of fibrosis. No single measurement or cluster of measurements sufficiently estimates hepatic impairment’s effect on a drug’s PK and/or PD in indieidual patients.23,27 This leads to reliance on clinical studies, observation, and hypothetical dose titration.

Many clinicians use the Child-Pugh Liver Dysfunction Classification to stage disease and suggest a prognosis. It incorporates a combination of 3 synthesis/ elimination markers (ie, prothrombin time, albumin level, bilirubin level) and 2 clinical features (ie, presence of ascites, encephalopathy) and can give a general picture of patient’s hepatic health, but it has some limitations.28,29

Even if an agent’s PK is unaltered in organ dysfunction, patients with liver or kidney disease may still experience increased sensitivity to specific drugs. For example:
  • low serum albumin may create a higher free fraction of the drug, increasing the agent’s toxicity
  • increased anemia secondary to renal dysfunction may reduce bone marrow reserve and cause a greater likelihood of toxicity.23,27

Managing a drug regimen for patients with impaired renal and hepatic function is challenging. Historically, these patients have been under represented in most drug development clinical trials, and this has made dosing difficult. Clinicians often consider organ dysfunction patients either too frail to tolerate drug therapy, or at high risk for adverse events or drug-related toxicity. This may or may not be the case.

The FDA is now encouraging pharmaceutical firms to test new drugs in patients with organ impairment when appropriate.4,5 Most importantly, prescribers and pharmacists need to recognize that multiorgan impairment is possible and likely as these conditions progress.

Table 2: Unreliable Conditions for Cockcroft–Gault and MDRD Equations

Cockcroft–Gault and MDRD Equations may be unreliable in patients who:
• Consume vegetarian or high-protein diets
• Take creatinine or amino acid supplements
• Are extremely large or small
• Are diagnosed with conditions affecting skeletal muscle, eg, cachexia, high muscle mass, sarcopenia, paraplegia, or amputees
• Are members of population in which the equations have not been validated, eg, children, small minority populations
• Are dialysis-dependent or have acute changes in kidney
Adapted from references 4, 16, 17, 19, and 30.

Table 3: Liver Disease Etiologies
Alcohol abuse
Autoimmune disease
Bile duct obstruction
Budd-Chiari syndrome
Cancers, tumors, and cysts
Drugs (partially listed below) and toxins:
Acetaminophen overdose
Anabolic steroids
Antidiabetic agents
Cancer chemotherapy
HMG-CoA reductase inhibitors (statins)
Isoniazid (INH)
Valproic acid
Hepatitis infection
Hereditary genetic aberrations (primary hemochromatosis, alpha-1-antitrypsin deficiency,
Wilson’s disease, congenital disorders of bilirubin metabolism, Gilbert syndrome)
Ischemic hepatitis
Pancreatic inflammation
Adapted from references 23-28.

Ms. Wick is a visiting professor at the University of Connecticut School of Pharmacy and a freelance clinical writer.

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4. U.S. Food and Drug Administration. Guidance for Industry Drug-Induced Liver Injury: Premarketing Clinical Evaluation. Available at…oryInformation/Guidances/UCM174090.pdf. Accessed March 23, 2012.

5. U.S. Food and Drug Administration. Guidance for Industry Pharmacokinetics in Patients with Impaired Renal Function — Study Design, Data Analysis, and Impact on Dosing and Labeling. Available at…/Drugs/GuidanceComplianceRegulatory. Accessed March 23, 2012.

6. National Kidney Foundation. K/DOQI Clinical Practice Guidelines for Chronic Kidney Disease: Evaluation, Classification, and Stratification. Available at Accessed March 23, 2012.

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8. Uchida N, Kurata N, Shimada K, et al. Changes of hepatic microsomal oxidative drug metabolizing enzymes in chronic renal failure (CRF) rats by partial nephrectomy. Jpn J Pharmacol. 1995;68:431-9.

9. Leblond F, Guévin C, Demers C, Pellerin I, Gascon-Barré M, Pichette V. Downregulation of hepatic cytochrome P450 in chronic renal failure. J Am Soc Nephrol. 2001;12:326-32.

10. Martin DE, Chapelsky MC, Ilson B, et al. Pharmacokinetics and protein binding of eprosartan in healthy volunteers and in patients with varying degrees of renal impairment. J Clin Pharmacol. 1998;38:129-37.

11. Kovacs SJ, Tenero DM, Martin DE, Ilson BE, Jorkasky DK. Pharmacokinetics and protein binding of eprosartan in hemodialysis-dependent patients with end-stage renal disease. Pharmacotherapy. 1999;19:612-9.

12. McTaggart F, Buckett L, Davidson R, et al. Preclinical and clinical pharmacology of Rosuvastatin, a new 3-hydroxy-3-methylglutaryl coenzyme A reductase inhibitor. Am J Cardiol. 2001;87:28B-32B.

13. Touchette MA, Slaughter RL. The effect of renal failure on hepatic drug clearance. DICP. 1991;25:1214-24.

14. Aronoff GR, Berns JS, Brier ME, et al. Drug prescribing in renal failure: Dosing guidelines for adults (ed 4). Philadelphia, PA, American College of Physicians-American Society of Internal Medicine, 1999.

15. Kasiske BL, Keane WF. Laboratory assessment of renal disease: Clearance, urinalysis, and renal biopsy. In: Brenner BM, Rector FC, eds. Brenner & Rector’s The Kidney. 6th ed. Philadelphia, PA: WB Saunders; 2000:1129-70.

16. Cockcroft DW, Gault MH. Prediction of creatinine clearance from serum creatinine. Nephron. 1976;16:31-41.

17. National Kidney Foundation. K/DOQI clinical practice guidelines for kidney disease: evaluation, classification, and stratification. Kidney Disease Outcome Quality Initiative. Am J Kidney Dis. 2002;39 (Suppl. 1):S1-S266.

18. Levey AS, Bosch JP, Lewis JB, et al. A more accurate method to estimate glomerular filtration rate from serum creatinine: A new prediction equation. Ann Intern Med. 1999;130:461-70.

19. Stevens L, Coresh J, Greene T, et al. Assessing kidney function — measured and estimated glomerular filtration rate. N Engl J Med. 2006;354:2473–83.

20. The Australasian Creatinine Consensus Working Group. Chronic kidney disease and automatic reporting of estimated glomerular filtration rate: A position statement. Med J Aust. 2005;183:138–41.

21. Levey AS, Bosch JP, Lewis JB, et al. A more accurate method to estimate glomerular filtration rate from serum creatinine: A new prediction equation. Ann Intern Med. 1999;130:461–70.

22. Egorin M. The effects of organ dysfunction on drug dosing. Clin Adv Hematol Oncol. 2006;4:116-8.

23. Lee WM, Seremba E. Etiologies of acute liver failure. Curr Opin Crit Care. 2008;14:198-201.

24. Lee WM. Etiologies of acute liver failure. Semin Liver Dis. 2008;28:142-52.

25. Egorin M. The effects of organ dysfunction on drug dosing. Clin Adv Hematol Oncol. 2006;4:116-8.

26. Mano MS, Cassidy J, Canney P. Liver metastases from breast cancer: Management of patients with significant liver dysfunction. Cancer Treat Rev. 2005;31:35-48.

27. Ghobrial IM, Wolf RC, Pereira DL, et al. Therapeutic options in patients with lymphoma and severe liver dysfunction. Mayo Clin Proc. 2004;79:169-175.

28. Kamath PS, Wiesner RH, Malinchoc M, et al. A model to predict survival in patients with end-stage liver disease. Hepatology. 2001;33:464-470.

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30. Pugh RNH, Murray-Lyon IM, Dawson JL, Pietroni MC, Williams R. Transection of the esophagus in bleeding oesophageal varices. Br J Surg. 1973;60:648-52.

31. Anonymous. The patient, the drug and the kidney. Drug Ther Bull. 2006;44:89–95.


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