Risk factors of immune checkpoint inhibitor-associated acute kidney injury: evidence from clinical studies and FDA pharmacovigilance database

Acute Kidney Injury Associated with Novel Anticancer Therapies: Immunotherapy

The landscape of cancer survival has been positively affected by the introduction and dissemination of immunotherapy with the wide usage of immune checkpoint inhibitors and chimeric antigen receptors cell therapies. The success of these novel therapies can, however, be limited to a certain extent by systemic inflammatory toxicities affecting, directly or indirectly, the kidney. In the case of immune checkpoint inhibitors, severe acute interstitial nephritis is the main adverse event and can lead to permanent discontinuation of the therapy. In turn, chimeric antigen receptor cell therapy can cause cytokine release syndrome and immune effector cell-associated hemophagocytic lympho-histiocytosis, with kidney damage through various mechanisms, and be life threatening. Prompt diagnosis and management of these entities is essential to preserve kidney function and ensure the best possible kidney and overall outcomes to patients with cancer.

Analysis of risk factors for immune checkpoint inhibitor-associated liver injury: a retrospective analysis based on clinical study and real-world data

BACKGROUND

Immune-mediated hepatotoxicity (IMH) induced by immune checkpoint inhibitors (ICIs) can lead to fatal outcomes. Exploring the risk factors associated with IMH is crucial for the early identification and management of immune-related adverse events (irAEs).

METHODS

Screening IMH-influencing factors by applying meta-analysis to clinical research data. Utilizing FAERS data, ICIs-related IMH prediction models were developed using two types of variables (full variables and optimal variables screened by univariate logistic regression) and nine machine learning algorithms (logistic regression, decision tree, random forest, gradient boosting decision tree, extreme gradient boosting, K-Nearest Neighbor, bootstrap aggregation, adaptive boosting, and extremely randomized trees). Comparing the nine machine learning algorithms and screening the optimal model while using SHAP (SHapley Additive exPlanations) analysis to interpret the results of the optimal machine learning model.

RESULTS

A total of 17 studies (10,135 patients) were included. The results showed that ICIs combination therapy (OR = 5.10, 95% CI: 1.68-15.48) and history of ICIs treatment (OR = 3.58, 95% CI: 2.08-6.14) were significantly associated with the risk of all-grade IMH. Patients aged 56-63 years (MD = - 5.09, 95% CI: - 9.52 to - 0.67) were significantly associated with the risk of ≥ grade 3 IMH. The liver adverse reaction prediction model included a total of 51,555 patients from the FAERS database, of which 4607 cases were liver adverse reactions. Univariate logistic regression analysis ultimately screened eight optimal variables, with females, report areas, cancer type, ICIs drug type, concomitant autoimmune disease, the concomitant use of anti-hypertension drugs, and the concomitant use of CTLA-4 inhibitors or targeted therapy drugs being significant influencing factors. The performance of the model after the variables were screened by univariate logistic regression was slightly worse than that of the model with full variables. Among the best-performing liver adverse reaction prediction models was GBDT (training set AUC = 0.82, test set AUC = 0.79). The top 3 key predictors in the GBDT model were report areas, disease type, and ICIs drug type.

CONCLUSION

In clinical studies, we found that age between 56 and 63 years, ICIs combination therapy, and history of ICIs treatment were significantly associated with an increased risk of IMH. In the FAERS database, we observed that females, report areas, cancer type, ICIs drug type, concomitant autoimmune disease, the concomitant use of anti-hypertension drugs, and the concomitant use of CTLA-4 inhibitors or targeted therapy drugs may be potential risk factors for ICIs-related hepatic irAEs. The predictive model for ICIs-related liver adverse reactions established in this study has good performance and potential clinical applications.

Adverse renal outcomes following targeted therapies in renal cell carcinoma: a systematic review and meta-analysis

Introduction: To clarify the prevalence of adverse renal outcomes following targeted therapies in renal cell carcinoma (RCC). Methods: A systematic search was performed in MEDLINE, EMBASE, and Cochrane Central Library. Studies that had reported adverse renal outcomes following targeted therapies in RCC were eligible. Outcomes included adverse renal outcomes defined as either renal dysfunction as evidenced by elevated serum creatinine levels or the diagnosis of acute kidney injury, or proteinuria as indicated by abnormal urine findings. The risk of bias was assessed according to Cochrane handbook guidelines. Publication bias was assessed using Funnel plot analysis and Egger Test. Results: The occurrences of the examined outcomes, along with their corresponding 95% confidence intervals (CIs), were combined using a random-effects model. In all, 23 studies including 10 RCTs and 13 observational cohort studies were included. The pooled incidence of renal dysfunction and proteinuria following targeted therapies in RCC were 17% (95% CI: 12%-22%; I2 = 88.5%, p < 0.01) and 29% (95% CI: 21%-38%; I2 = 93.2%, p < 0.01), respectively. The pooled incidence of both types of adverse events varied substantially across different regimens. Occurrence is more often in polytherapy compared to monotherapy. The majority of adverse events were rated as CTCAE grades 1 or 2 events. Four studies were assessed as having low risk of bias. Conclusion: Adverse renal outcomes reflected by renal dysfunction and proteinuria following targeted therapies in RCC are not uncommon and are more often observed in polytherapy compared to monotherapy. The majority of the adverse events were of mild severity. Systematic Review Registration: Identifier CRD42023441979.

Acute kidney injury in cancer patients receiving anti-vascular endothelial growth factor monoclonal antibody vs. immune checkpoint inhibitors: a retrospective real-world study

BACKGROUND

Anti-vascular endothelial growth factor monoclonal antibody (anti-VEGF) or immune checkpoint inhibitors (ICIs) combined with chemotherapy are commonly administered to cancer patients. Although cancer patients receiving anti-VEGF or ICIs have been reported to experience an increased risk of acute kidney injury (AKI), comparative studies on the AKI incidence have not been evaluated.

METHODS

Cancer patients receiving anti-VEGF or ICIs were retrospectively selected from the hospital information system of the First Affiliated Hospital of Wenzhou Medical University between Jan, 2020 and Dec, 2022 and were divided into two groups according to the treatment regimen: anti-VEGF group and ICIs group. The baseline characteristics were propensity-score matched. The primary outcome was sustained AKI. A comparison of cumulative incidence of sustained AKI was performed by Kaplan-Meier curves and log-rank test. Risks for outcomes were assessed using Cox proportional regression.

RESULTS

A total of 1581 cancer patients receiving anti-VEGF (n = 696) or ICIs (n = 885) were included in the primary analysis. The ICIs group had a higher cumulative incidence of sustained AKI within one year than the anti-VEGF group (26.8% vs. 17.8%, P < 0.001). Among 1392 propensity score matched patients, ICIs therapy (n = 696) was associated with an increased risk of sustained AKI events in the entire population (HR 2.0; 95%CI 1.3 to 2.5; P = 0.001) and especially in those with genitourinary cancer (HR 4.2; 95%CI 1.3 to 13.2; P = 0.015). Baseline serum albumin level (> 35 g/l) was an important risk factor for a lower incidence of sustained AKI in the anti-VEGF group (HR 0.5; 95%CI 0.3 to 0.9; P = 0.027) and the ICIs group (HR 0.3; 95%CI 0.2 to 0.5; P < 0.001).

CONCLUSIONS

Among cancer patients in this real-world study, treatment with ICIs increased incidence of sustained AKI in one year. Baseline serum albumin level was an important risk factor for sustained AKI. The risk factors for sustained AKI differed between the anti-VEGF group and the ICIs group.

TRIAL REGISTRATION

The study has been registered at ClinicalTrials.gov (NCT06119347) on 11/06/2023.

Development and validation of a nomogram for predicting the occurrence of renal dysfunction after treatment of immune checkpoint inhibitor: a retrospective case-control study

PURPOSE

The administration of immune checkpoint inhibitors (ICIs) may lead to renal adverse events, notably including renal dysfunction. To early predict the probability of renal dysfunction after ICIs therapy, a retrospective case-control study was conducted.

METHODS

Clinical information on ICIs-treated patients was collected. Multivariable logistic regression was applied to identify risk factors for renal dysfunction after ICIs treatment. Moreover, a nomogram model was developed and validated internally.

RESULTS

A total of 442 patients were included, among which 35 (7.9%) experienced renal dysfunction after ICIs treatment. Lower baseline estimated glomerular filtration rate (eGFR) (OR 0.941; 95% CI 0.917 to 0.966; p<0.001), concurrent exposure of platinum(OR 4.014; 95% CI 1.557 to 10.346; p=0.004), comorbidities of hypertension (OR 3.478; 95% CI 1.600 to 7.562; p=0.002) and infection (OR 5.402; 95% CI 1.544 to 18.904; p=0.008) were found to be independent associated with renal dysfunction after ICIs treatment. To develop a predictive nomogram for the occurrence of renal dysfunction after ICIs treatment, the included cases were divided into training and validation groups in a ratio of 7:3 randomly. The above four independent risk factors were included in the model. The area under the receiver operating characteristic curves of the predictiive model were 0.822 (0.723-0.922) and 0.815 (0.699-0.930) in the training and validation groups, respectively.

CONCLUSIONS

Lower baseline eGFR, platinum exposure, comorbidities of hypertension and infection were predictors of renal dysfunction in ICIs-treated patients with cancer. A nomogram was developed to predict the probability of renal dysfunction after ICIs treatment, which might be operable and valuable in clinical practice.

Nephrotoxicity in the Age of Immune Checkpoint Inhibitors: Mechanisms, Diagnosis, and Management

Immune checkpoint inhibitors (ICI) revolutionized cancer therapy by augmenting anti-tumor immunity via cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) and programmed death-1/programmed death-ligand 1 (PD-1/PD-L1). However, this breakthrough is accompanied by immune-related adverse effects (irAEs), including renal complications. ICI-related nephritis involves complex mechanisms like auto-reactive T cells, auto-antibodies, reactivation of drug-specific T cells, and cytokine-driven inflammation culminating in AKI. ICI-AKI typically manifests weeks to months into treatment, often with other irAEs. Timely detection relies on monitoring creatinine levels and urine characteristics. Biomarkers, like soluble interleukin-2 receptor (sIL-2R) and urine cytokine levels, provide non-invasive insights, while renal biopsy remains the gold standard for confirmation. Management of ICI-AKI requires a balance between discontinuing ICI therapy and prompt immunosuppressive intervention, typically with corticosteroids. Some cases permit ICI therapy resumption, but varying renal recovery rates highlight the importance of vigilant monitoring and effective therapy. Beyond its clinical implications, the potential of irAEs to predict positive treatment responses in certain cancers raises intriguing questions. Data on nephritis-treatment response links are limited, and ongoing research explores this complex interaction. In summary, ICI therapy's transformative impact on cancer treatment is counterbalanced by irAEs, including nephritis. Early recognition and management are vital, with ongoing research refining diagnostic and treatment strategies.