The Nephrologist's Management of Renal Cell Carcinoma After Kidney Surgery

Pharmacotherapy considerations in patients who develop acute kidney injury during anti-cancer therapy

INTRODUCTION

Acute kidney injury (AKI) frequently develops in patients receiving cancer therapy and requires a wide differential diagnosis due to possible role of unique cancer and drug-related factors, in addition to common pre- and post-renal causes. Rapid development of new molecular targeted anti-cancer drugs and immunotherapies has opened unprecedented possibilities of treatment at the price of an increased spectrum of renal side effects.

AREAS COVERED

The present review aims at providing a state-of-the-art picture of AKI in cancer patient (PubMed and Embase libraries were searched from inception to January 2024), with a focus on differential diagnosis and management of diverse clinical settings. Reports of parenchymal AKI due to glomerular, microvascular, tubular and interstitial damage have been constantly increasing. Complex electrolyte and acid-base disorders can coexist. The role of renal biopsy and possible therapeutic approaches are also discussed.

EXPERT OPINION

Onconephrology has become an important subspecialty of clinical nephrology, requiring constantly updated skills and a high degree of interdisciplinary integration to tackle diagnostic challenges and even therapeutic and ethical dilemmas. Integrated onconephrological guidelines and availability of biomarkers may provide new tools for management of this unique type of patients in the near future.

Genitourinary Cancer: Updates on Treatments and Their Impact on the Kidney

Genitourinary cancers are diverse in their presentation, prevalence, and mortality risk. Although there have been significant advancements in medical (eg, immune checkpoint inhibitors and tyrosine kinase inhibitors) and surgical treatments of genitourinary cancers, patients are still at risk for chronic kidney disease, hypertension, and electrolyte derangements in the short and long term. In addition, pre-existing kidney disease may increase the risk of developing some genitourinary cancers. This review focuses on the kidney-related effects of treatments for renal cell carcinoma and bladder and prostate cancers.

Impacts of Neighborhood Characteristics and Surgical Treatment Disparities on Overall Mortality in Stage I Renal Cell Carcinoma Patients

Racial/ethnic minority groups in the United States have high renal cell carcinoma (RCC) mortality rates. This study assessed surgical treatment disparities across racial/ethnic groups and impacts of neighborhood socioeconomic characteristics on surgical treatments and overall mortality. Stage I RCC patients diagnosed between 2004 and 2016 from National Cancer Database were included (n = 238,141). We assessed differences in associations between race/ethnicity and treatment patterns using logistic regression and between race/ethnicity and overall mortality using Cox regression with and without neighborhood characteristics in the regression models. When compared to non-Hispanic Whites (NHWs), American Indians/Alaska Natives and non-Hispanic Blacks (NHBs) were more likely not to receive surgical care and all racial/ethnic minority groups had significantly increased odds of undergoing radical rather than partial nephrectomy, even after adjusting for neighborhood characteristics. Including surgical treatment and neighborhood factors in the models slightly attenuated the association, but NHBs had a significantly increased risk of overall mortality. NHBs who underwent radical nephrectomy had an increased risk of mortality (HR 1.15, 95% CI: 1.08-1.23), but not for NHBs who underwent partial nephrectomy (HR 0.92, 95% CI: 0.84-1.02). Neighborhood factors were associated with surgical treatment patterns and overall mortality in both NHBs and NHWs. Neighborhood socioeconomic factors may only partly explain RCC disparities.

Prediction of the Values of CRP, eGFR, and Hemoglobin in the Follow-Up of Renal Cell Carcinoma Patients after (Cryo)Surgery Using Machine Learning Algorithms

Background

Artificial intelligence can support clinical decisions by predictive modeling. Using patient-specific characteristics, models may predict the course of clinical parameters, thus guiding monitoring approaches for the individual patient. Here, we present prediction models for inflammation and for the course of renal function and hemoglobin (Hb) in renal cell carcinoma patients after (cryo)surgery.

Methods

Using random forest machine learning in a longitudinal value-based healthcare data set (n = 86) of renal cell carcinoma patients, prediction models were established and optimized using random and grid searches. Data were split into a training and test set in a 70:30 ratio. Inflammation was predicted for a single timepoint, whereas for renal function estimated glomerular filtration rate (eGFR) and Hb time course prediction was performed.

Results

Whereas the last Hb and eGFR values before (cryo)surgery were the main basis for the course of Hb and renal function, age and several time frame features also contributed significantly. For eGFR, the type of (cryo)surgery was also a main predicting feature, and for Hb, tumor location, and body mass index were important predictors. With regard to prediction of inflammation no feature was markedly prominent. Inflammation prediction was based on a combination of patient characteristics, physiological parameters, and time frame features.

Conclusions

This study provided interesting insights into factors influencing complications and recovery in individual renal cell carcinoma patients. The established prediction models provide the basis for development of clinical decision support tools for selection and timing of laboratory analyses after (cryo)surgery, thus contributing to quality and efficiency of care.

Collaborative Review: Factors Influencing Treatment Decisions for Patients with a Localized Solid Renal Mass

CONTEXT

With the addition of active surveillance and thermal ablation (TA) to the urologist's established repertoire of partial (PN) and radical nephrectomy (RN) as first-line management options for localized renal cell carcinoma (RCC), appropriate treatment decision-making has become increasingly nuanced.

OBJECTIVE

To critically review the treatment options for localized, nonrecurrent RCC; to highlight the patient, renal function, tumor, and provider factors that influence treatment decisions; and to provide a framework to conceptualize that decision-making process.

EVIDENCE ACQUISITION

A collaborative critical review of the medical literature was conducted.

EVIDENCE SYNTHESIS

We identify three key decision points when managing localized RCC: (1) decision for surveillance versus treatment, (2) decision regarding treatment modality (TA, PN, or RN), and (3) decision on surgical approach (open vs minimally invasive). In evaluating factors that influence these treatment decisions, we elaborate on patient, renal function, tumor, and provider factors that either directly or indirectly impact each decision point. As current nomograms, based on preselected patient datasets, perform poorly in prospective settings, these tools should be used with caution. Patient decision aids are an underutilized tool in decision-making.

CONCLUSIONS

Localized RCC requires highly nuanced treatment decision-making, balancing patient- and tumor-specific clinical variables against indirect structural influences to provide optimal patient care.

PATIENT SUMMARY

With expanding treatment options for localized kidney cancer, treatment decision is highly nuanced and requires shared decision-making. Patient decision aids may be helpful in the treatment discussion.