Accurate assessment of GFR is crucial to guiding drug eligibility, dosing of systemic therapy, and minimizing the risks of both undertreatment and toxicity in patients with cancer. Up to 32% of patients with cancer have baseline CKD, and both malignancy and treatment may cause kidney injury and subsequent CKD. To date, there has been lack of guidance to standardize approaches to GFR estimation in the cancer population. In this two-part statement from the American Society of Onco-Nephrology, we present key messages for estimation of GFR in patients with cancer, including the choice of GFR estimating equation, use of race and body surface area adjustment, and anticancer drug dose-adjustment in the setting of CKD. These key messages are based on a systematic review of studies assessing GFR estimating equations using serum creatinine and cystatin C in patients with cancer, against a measured GFR comparator. The preponderance of current data involving validated GFR estimating equations involves the CKD Epidemiology Collaboration (CKD-EPI) equations, with 2508 patients in whom CKD-EPI using serum creatinine and cystatin C was assessed (eight studies) and 15,349 in whom CKD-EPI with serum creatinine was assessed (22 studies). The former may have improved performance metrics and be less susceptible to shortfalls of eGFR using serum creatinine alone. Since included studies were moderate quality or lower, the American Society of Onco-Nephrology Position Committee rated the certainty of evidence as low. Additional studies are needed to assess the accuracy of other validated eGFR equations in patients with cancer. Given the importance of accurate and timely eGFR assessment, we advocate for the use of validated GFR estimating equations incorporating both serum creatinine and cystatin C in patients with cancer. Measurement of GFR via exogenous filtration markers should be considered in patients with cancer for whom eGFR results in borderline eligibility for therapies or clinical trials.

Treating chronic hyponatremia by continuous renal replacement therapy (CRRT) is challenging because the gradient between a replacement fluid's [sodium] and a patient's serum sodium can be steep, risking too rapid of a correction rate with possible consequences. Besides CRRT, other gains and losses of sodium- and potassium-containing solutions, like intravenous fluid and urine output, affect the correction of serum sodium over time, known as osmotherapy. The way these fluids interact and contribute to the sodium/potassium/water balance can be parsed as a mixing problem. As Na/K/H2 O are added, mixed in the body, and drained via CRRT, the net balance of solutes must be related to the change in serum sodium, expressible as a differential equation. Its solution has many variables, one of which is the sodium correction rate, but all variables can be evaluated by a root-finding technique. The mixing paradigm is proved to replicate the established equations of osmotherapy, as in the special case of a steady volume. The flexibility to solve for any variable broadens our treatment options. If the pre-filter replacement fluid cannot be diluted, then we can compensate by calculating the CRRT blood flow rate needed. Or we can deduce the infusion rate of dextrose 5% water, post-filter, to appropriately slow the rise in serum sodium. In conclusion, the mixing model is a generalizable and practical tool to analyze patient scenarios of greater complexity than before, to help doctors customize a CRRT prescription to safely and effectively reach the serum sodium target.

Several major advances over the last years have increased our understanding of the pathogenesis of diabetic kidney disease (DKD), thanks in large part to the utility of experimental animal models. Pathologically, DKD is characterized by glomerular basement membrane thickening, mesangial matrix expansion, glomerulosclerosis, and tubulointerstitial fibrosis. These changes correlate clinically with the development of albuminuria and hypertension and a decline in glomerular filtration rate (GFR). While a unifying hypothesis for diabetic pathogenesis has been difficult to prove, various metabolic, hemodynamic, and inflammatory pathways have been shown to redundantly activate molecular and cellular pathways of injury. Hyperglycemia alters glucose metabolism in renal cells causing it to utilize alternative pathways and is associated with mitochondrial dysfunction. Meanwhile, nonenzymatic glycation, oxidative stress, and protein kinase C signaling contribute to further glucotoxicity. Further, the renin–angiotensin–aldosterone system (RAAS) has been demonstrated to be central to the early hemodynamic changes in the glomerulus including hyperfiltration and intraglomerular hypertension. This explains the protective role of agents that intercept the RAAS (angiotensin-converting enzyme inhibitors and angiotensin receptor blockers) and the new findings on the efficacy of novel mineralocorticoid receptor antagonists in preventing DKD progression. However, recently the success of the sodium–glucose cotransporter inhibitors in delaying kidney injury brought to light hypotheses on the role of tubuloglomerular feedback in the development of hyperfiltration. All the different pathways activated in the diabetic kidney converge to activate pathways for fibrosis, heralding the final stages of DKD. By further elucidating the pathophysiology of DKD, newer and more effective therapies will be on the horizon.

A hyponatremic patient with the syndrome of inappropriate antidiuresis (SIAD) gets normal saline (NS), and the plasma sodium decreases, paradoxically. To explain, desalination is often invoked: if urine is more concentrated than NS, the fluid’s salts are excreted while some water is reabsorbed, exacerbating hyponatremia. But comparing concentrations can be deceiving. They should be converted to quantities because mass balance is key to unlocking the paradox. The [sodium] equation can legitimately be used to track all of the sodium, potassium, and water entering and leaving the body. Each input or output “module” can be counterbalanced by a chosen iv fluid so that the plasma sodium stays stable. This equipoise is expressed in terms of the iv fluid’s infusion rate, an easy calculation called the ratio profile. Knowing the infusion rate that maintains steady state, we can prescribe the iv fluid at a faster rate in order to raise the plasma sodium. Rates less than the ratio profile may risk a paradox, which essentially is caused by an iv fluid underdosing. Selecting an iv fluid that is more concentrated than urine is not enough to prevent paradoxes; even 3% saline can be underdosed. Drinking water adds to the ratio profile and is underestimated in its ability to provoke a paradox. In conclusion, the quantitative approach demystifies the paradoxical worsening of hyponatremia in SIAD and offers a prescriptive guide to keep the paradox from happening. The ratio profile method is objective and quickly deployable on rounds, where it may change patient management for the better.

[Creatinine] was proved to change in the opposite direction of the kinetic GFR (GFR(K)), but does the [creatinine] also change in the opposite direction of the volume rate? If volume is administered and the [creatinine] actually goes up, then the two changes move in the same direction and their ratio is positive, paradoxically. The equation that describes [creatinine] as a function of time was differentiated with respect to the volume rate. This partial first derivative has a global maximum that can be positive under definable conditions. Knowing what makes the maximum positive informs when the derivative will be positive over some continuous domain of volume rate inputs. The first derivative versus volume rate curve has a maximum and a minimum point depending on the GFR(K). If GFR(K) is below a calculable value, then the curve's minimum vanishes, letting it descend to -infinity and not allowing the derivative to ever be positive. If GFR(K) lies between a lower and a higher calculable value, then the curve's maximum vanishes, letting the derivative diverge to +infinity, though the clinical scenario is unrealistic. If GFR(K) is above the higher calculable value, then the curve's absolute maximum can become positive by decreasing the creatinine generation rate or increasing the initial [creatinine]. The derivative is potentially positive under these clinically realizable circumstances. The combination of parameters above can align in septic patients (low creatinine generation rate) with kidney failure (high initial [creatinine]) who are put on continuous dialysis (high GFR(K)). If a first derivative is positive, removing more volume can improve the [creatinine] and, dismayingly, giving more volume can worsen the [creatinine]. This paradox is explained by a covert interplay between the ambient [creatinine] and GFR(K) that excretes creatinine faster than its volume of distribution declines.

Background:Worsening serum creatinine is common during treatment of acute decompensated heart failure (ADHF). A possible contributor to creatinine increase is diuresis-induced changes in volume of distribution (VD) of creatinine as total body water (TBW) contracts around a fixed mass of creatinine. Our objective was to better understand the filtration and nonfiltration factors driving change in creatinine during ADHF. Methods:Participants in the ROSE-AHF trial with baseline to 72-hour serum creatinine; net fluid output; and urinary KIM-1, NGAL, and NAG were included (n=270). Changes in VD were calculated by accounting for measured input and outputs from weight-based calculated TBW. Changes in observed creatinine (Crobserved) were compared with predicted changes in creatinine after accounting for alterations in VD and non-steady state conditions using a kinetic GFR equation (Cr72HR Kinetic). Results:When considering only change in VD, the median diuresis to elicit a ≥0.3 mg/dl rise in creatinine was -7526 ml (IQR, -5932 to -9149). After accounting for stable creatinine filtration during diuresis, a change in VD alone was insufficient to elicit a ≥0.3 mg/dl rise in creatinine. Larger estimated decreases in VD were paradoxically associated with improvement in Crobserved (r=-0.18, P=0.003). Overall, -3% of the change in eCr72HR Kinetic was attributable to the change in VD. A ≥0.3 mg/dl rise in eCr72HR Kinetic was not associated with worsening of KIM-1, NGAL, NAG, or postdischarge survival (P>0.05 for all). Conclusions:During ADHF therapy, increases in serum creatinine are driven predominantly by changes in filtration, with minimal contribution from change in VD.

Introduction: When the serum [creatinine] is changing, creatinine kinetics can still gauge the kidney function, and knowing the kinetic glomerular filtration rate (GFR) helps doctors take care of patients with renal failure. We wondered how the serum [creatinine] would respond if the kinetic GFR were tweaked. In every scenario, if the kinetic GFR decreased, the [creatinine] would increase, and vice versa. This opposing relationship was hypothesized to be universal. Methods: Serum [creatinine] and kinetic GFR, along with other parameters, are described by a differential equation. We differentiated [creatinine] with respect to kinetic GFR to test if the two variables would change oppositely of each other, throughout the gamut of all allowable clinical values. To remove the discontinuities in the derivative, limits were solved. Results: The derivative and its limits were comprehensively analyzed and proved to have a sign that is always negative, meaning that [creatinine] and kinetic GFR must indeed move in opposite directions. The derivative is bigger in absolute value at the higher end of the [creatinine] scale, where a small drop in the kinetic GFR can cause the [creatinine] to shoot upward, making acute kidney injury similar to chronic kidney disease in that regard. Conclusions: All else being equal, a change in the kinetic GFR obligates the [creatinine] to change in the opposite direction. This does not negate the fact that an increasing [creatinine] can be compatible with a rising kinetic GFR, due to differences in how the time variable is treated.

Diabetic nephropathy affects approximately 25-35% of patients with type 1 or type 2 diabetes mellitus. The disease progresses through various clinical stages, from hyper-filtration to microalbuminuria to macroalbuminuria to nephrotic proteinuria to progressive chronic kidney disease, which eventually leads to end-stage renal disease. These stages are generally associated with structural pathological changes affecting all compartments of the kidney: the glomerulus, the tubules, the vasculature, and the interstitium. With increased glycemia, various metabolites and by-products, including advanced glycation end-products and reactive oxygen species, are stimulated. These metabolic insults converge with the main driver of the hemodynamic insult, angiotensin II, to induce diabetic renal pathology at its different levels. Advances in genetics and molecular biology will continue to reveal more about the pathogenesis of diabetic nephropathy, but the multifactorial nature of the disease has defied attempts at a general theory that unifies all the known cellular and biochemical pathways.

The Adrogué-Madias (A-M) formula is correct as written, but technically, it only works when adding 1 L of an intravenous (IV) fluid. For all other volumes, the A-M algorithm gives an approximate answer, one that diverges further from the truth as the IV volume is increased. If 1 L of an IV fluid is calculated to change the serum sodium by some amount, then it was long assumed that giving a fraction of the liter would change the serum sodium by a proportional amount. We challenged that assumption and now prove that the A-M change in [sodium] ([Na]) is not scalable in a linear way. Rather, the Δ[Na] needs to be scaled in a way that accounts for the actual volume of IV fluid being given. This is accomplished by our improved version of the A-M formula in a mathematically rigorous way. Our equation accepts any IV fluid volume, eliminates the illogical infinities, and most importantly, incorporates the scaling step so that it cannot be forgotten. However, the nonlinear scaling makes it harder to obtain a desired Δ[Na]. Therefore, we reversed the equation so that clinicians can enter the desired Δ[Na], keeping the rate of sodium correction safe, and then get an answer in terms of the volume of IV fluid to infuse. The improved equation can also unify the A-M formula with the corollary A-M loss equation wherein 1 L of urine is lost. The method is to treat loss as a negative volume. Because the new equation is just as straightforward as the original formula, we believe that the improved form of A-M is ready for immediate use, alongside frequent [Na] monitoring.

Acute kidney injury (AKI) remains a common complication of cancer treatment and entails increased length of stay, cost, and mortality. The etiology of AKI may be direct injury from the underlying malignancy, drug toxicity, related to stem cell transplant, or from treatment complications. Advances in immunotherapy and targeted therapy have also highlighted the nephrotoxic potential of many of these drugs. Patients with liquid tumors (leukemia, lymphoma, myeloma) have the highest incidence of AKI, especially in the critical care setting. Although AKI does tend to improve in survivors, renal recovery is less likely with more severe grade of AKI. Baseline chronic kidney disease also confers an increased risk of AKI during cancer treatment. Although cancer itself is not a contraindication for starting renal replacement therapy (RRT), the benefits of RRT must be weighed against the overall prognosis of the patient and quality of life. A multidisciplinary discussion between the patient, nephrologist, oncologist, intensivist, and palliative care physician is often necessary to make an informed clinical decision.

Introduction and objective: Onconephrology is a new and evolving field that deals with kidney complications in patients with cancer as well as the management of cancer in patients with preexisting kidney disease. With increasing numbers of patients with cancer with kidney-related complications, the field has garnered increased attention. Thus, an annual Greater Toronto Area Onconephrology Interest Group symposium was held in May 2019. The objective of the meeting was to demonstrate the junctures between oncology and nephrology by highlighting recent data regarding (1) kidney impairment in solid organ malignancies, (2) management and treatment of kidney cancer, (3) kidney impairment in hematologic malignancies, (4) malignancy and kidney transplantation, and (5) hyponatremia in patients with cancer. Methods and sources of information: Through a structured presentation, the group explored key topics discussed at a Kidney Disease Improving Global Outcomes (KDIGO) Controversies Conference on Onconephrology. Expert opinions, clinical trial findings, and publication summaries were used to illustrate patient and treatment-related considerations in onconephrology. Key findings: Kidney complications in patients with cancer are a central theme in onconephrology. An estimated 12% to 25% of patients with solid organ malignancies have chronic kidney disease (CKD), although in certain cancers, the prevalence of CKD is higher. Kidney impairment is also a common complication of some hematologic malignancies. The incidence of renal failure in patients with multiple myeloma is estimated at 18% to 56% and light chain cast nephropathy is seen in approximately 30% of these patients. In addition, there appears to be a bidirectional relationship between kidney cancer and CKD, with some data sets suggesting the risk increases as kidney function declines. Cancer is also of concern in patients with preexisting kidney disease. Kidney transplant recipients have a greater risk of cancer and a higher risk of cancer-related mortality. Kidney complications have also been associated with novel cancer therapies, such as immune checkpoint inhibitors and chimeric antigen receptor (CAR) T-cell therapy. An estimated 2% to 4% of patients initiating an immune checkpoint inhibitor may develop nephrotoxicity, whereas up to 40% of patients on CAR T-cell therapy experience cytokine release syndrome (CRS). Tumor lysis syndrome and electrolyte abnormalities, such as hyponatremia, have also been reported with CAR T-cell therapy. While the incidence and prevalence of hyponatremia vary depending on the cancer type and serum sodium cutoff point, hyponatremia may be seen in up to 46% of patients hospitalized in cancer centers. Conclusions: Onconephrology is a developing field and the themes arising from this meeting indicate a need for greater collaboration between oncologists and nephrologists. Educational symposia and onconephrology fellowship programs may allow for improved cancer care for patients with kidney disease.

Rationale & Objective The approved therapeutic indication for immune checkpoint inhibitors (CPIs) are rapidly expanding including treatment in the adjuvant setting, the immune related toxicities associated with CPI can limit the efficacy of these agents. The literature on the nephrotoxicity of CPI is limited. Here, we present cases of biopsy proven acute tubulointerstitial nephritis (ATIN) and glomerulonephritis (GN) induced by CPIs and discuss potential mechanisms of these adverse effects. Study design, setting, & participants We retrospectively reviewed all cancer patients from 2008 to 2018 who were treated with a CPI and subsequently underwent a kidney biopsy at The University of Texas MD Anderson Cancer Center. Results We identified 16 cases diagnosed with advanced solid or hematologic malignancy; 12 patients were male, and the median age was 64 (range 38 to 77 years). The median time to developing acute kidney injury (AKI) from starting CPIs was 14 weeks (range 6–56 weeks). The average time from AKI diagnosis to obtaining renal biopsy was 16 days (range from 1 to 46 days). Fifteen cases occurred post anti-PD-1based therapy. ATIN was the most common pathologic finding on biopsy (14 of 16) and presented in almost all cases as either the major microscopic finding or as a mild form of interstitial inflammation in association with other glomerular pathologies (pauci-immune glomerulonephritis, membranous glomerulonephritis, C3 glomerulonephritis, immunoglobulin A (IgA) nephropathy, or amyloid A (AA) amyloidosis). CPIs were discontinued in 15 out of 16 cases. Steroids and further immunosuppression were used in most cases as indicated for treatment of ATIN and glomerulonephritis (14 of 16), with the majority achieving complete to partial renal recovery. Conclusions Our data demonstrate that CPI related AKI occurs relatively late after CPI therapy. Our biopsy data demonstrate that ATIN is the most common pathological finding; however it can frequently co-occur with other glomerular pathologies, which may require immune suppressive therapy beyond corticosteroids. In the lack of predictive blood or urine biomarker, we recommend obtaining kidney biopsy for CPI related AKI.

Hyponatremia is a common but challenging disorder to treat. The pathogenesis and the workup can be unexpectedly complicated, and the available therapies are manifold. Instead of trying to wrangle all of the aspects of hyponatremia into a comprehensive algorithm, we describe a general strategy that goes back to the first principles embodied in the model discovered by Edelman and colleagues back in 1958. The so-called Edelman equation underpins our modern understanding of [sodium] disorders, and it has engendered pretty much all of the [sodium] equations that are in clinical use. As the dysnatremias have a quantitative basis, a numerical approach seems prudent. We developed a predictive [sodium] equation that simultaneously considers all of the ongoing inputs and outputs of Na/K/H2O that would perturb the serum [Na] and also factors in the element of time that would determine the rate of [Na] correction. Our equation solves for the rate of intravenous fluid (or salt tablet) administration, because that information helps clinicians the most when prescribing therapy for inpatients. With the rate of [Na] correction built in, the equation also aims to safeguard against overcorrection. Since the equation is programmable into a clinical calculator, our renal fellows find it easy to use on their own. However, all of the [sodium] equations are fallible, because their data are no longer valid when the clinical parameters change, as they are likely to do. Nevertheless, we believe that the quantitative approach to hyponatremia has much to offer in terms of efficacy and safety.

BACKGROUND:In acute kidney injury (AKI), medication dosing based on Cockcroft-Gault creatinine clearance (CrCl) or Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) estimated glomerular filtration rates (eGFR) are not valid when serum creatinine (SCr) is not in steady state. The aim of this study was to determine the impact of a kinetic estimating equation that incorporates fluctuations in SCrs on drug dosing in critically ill patients.METHODS:We used data from participants enrolled in the NIH Acute Respiratory Distress Syndrome Network Fluid and Catheters Treatment Trial to simulate drug dosing category changes with the application of the kinetic estimating equation developed by Chen. We evaluated whether kinetic estimation of renal function would change medication dosing categories (≥60, 30-59, 15-29, and <15mL/min) compared with the use of CrCl or CKD-EPI eGFR.RESULTS:The use of kinetic CrCl and CKD-EPI eGFR resulted in a large enough change in estimated renal function to require medication dosing recategorization in 19.3% [95 CI 16.8%-21.9%] and 23.4% [95% CI 20.7%-26.1%] of participants, respectively. As expected, recategorization occurred more frequently in those with AKI. When we examined individual days for those with AKI, dosing discordance was observed in 8.5% of total days using the CG CrCl and 10.2% of total days using the CKD-EPI equation compared with the kinetic counterparts.CONCLUSION:In a critically ill population, use of kinetic estimates of renal function impacted medication dosing in a substantial proportion of AKI participants. Use of kinetic estimates in clinical practice should lower the incidence of medication toxicity as well as avoid subtherapeutic dosing during renal recovery.

Over the past decade, Onco-Nephrology has emerged as an important sub-field of not only nephrology and oncology but also hematology, urology, critical care medicine, clinical pharmacology, and palliative care medicine. This nexus reflects the unique connection that exists for kidney disease and cancer in all of clinical medicine. As noted, Onco-Nephrology combines the knowledge and skills of a number of specialty groups that span all areas of medicine. In this issue of the Journal of Onco-Nephrology, a series of papers addressing the various forms of kidney disease that develop in patients with cancer and its therapy is presented as part of the Onco-Nephrology Highlights section. These papers are based on the Onco-Nephrology Symposium that took place at MD Anderson Cancer Center in 2018. We hope you find these six papers educational and practical as you evaluate and treat patients with cancer and kidney disease in your clinical practice.