Incidence, risk factors and prognosis of acute kidney injury in patients treated with immune checkpoint inhibitors: a retrospective study

Ji, Ming-Su; Wu, Rilige; Feng, Zhe; Wang, Yuanda; Wang, Yong; Zhang, Li; Sun, Xiaofeng; Chen, Xiangmei; He, Kunlun; Cai, Guangyan

doi:10.1038/s41598-022-21912-y

Cited by 12 publications

(16 citation statements)

References 40 publications

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“…PPIs, which have been associated with the development of AKI in several observational studies [ 12 , 13 , 30 ], were also identified as a key feature in our prediction model. In addition, although not at the top of the list, diuretics, NSAIDs, and baseline renal function features were also identified as key risk factors by the model, as shown in the dependence plot [ 17 ] ( Fig 3c , S4 Fig in S1 File ). Although the dependence plot did not indicate a causal relationship, the prediction model regarded these key features as crucial for predicting AKI.…”

Section: Discussionmentioning

confidence: 99%

Interpretable machine learning-based individual analysis of acute kidney injury in immune checkpoint inhibitor therapy

Sakuragi,

Uchino,

Sato

et al. 2024

PLoS ONE

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Background Acute kidney injury (AKI) is a critical complication of immune checkpoint inhibitor therapy. Since the etiology of AKI in patients undergoing cancer therapy varies, clarifying underlying causes in individual cases is critical for optimal cancer treatment. Although it is essential to individually analyze immune checkpoint inhibitor-treated patients for underlying pathologies for each AKI episode, these analyses have not been realized. Herein, we aimed to individually clarify the underlying causes of AKI in immune checkpoint inhibitor-treated patients using a new clustering approach with Shapley Additive exPlanations (SHAP). Methods We developed a gradient-boosting decision tree-based machine learning model continuously predicting AKI within 7 days, using the medical records of 616 immune checkpoint inhibitor-treated patients. The temporal changes in individual predictive reasoning in AKI prediction models represented the key features contributing to each AKI prediction and clustered AKI patients based on the features with high predictive contribution quantified in time series by SHAP. We searched for common clinical backgrounds of AKI patients in each cluster, compared with annotation by three nephrologists. Results One hundred and twelve patients (18.2%) had at least one AKI episode. They were clustered per the key feature, and their SHAP value patterns, and the nephrologists assessed the clusters’ clinical relevance. Receiver operating characteristic analysis revealed that the area under the curve was 0.880. Patients with AKI were categorized into four clusters with significant prognostic differences (p = 0.010). The leading causes of AKI for each cluster, such as hypovolemia, drug-related, and cancer cachexia, were all clinically interpretable, which conventional approaches cannot obtain. Conclusion Our results suggest that the clustering method of individual predictive reasoning in machine learning models can be applied to infer clinically critical factors for developing each episode of AKI among patients with multiple AKI risk factors, such as immune checkpoint inhibitor-treated patients.

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Section: Discussionmentioning

confidence: 99%

Interpretable machine learning-based individual analysis of acute kidney injury in immune checkpoint inhibitor therapy

Sakuragi,

Uchino,

Sato

et al. 2024

PLoS ONE

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“…Acute kidney injury (AKI) is a common complication in cancer population with an incidence rate that varies from 7.5% to 25% depending on the type of malignancy, criteria used to define AKI, duration of the study, and patients’ comorbidities [1–5]. Patients receiving ICI therapy have a similar overall AKI incidence, ranging from 5 to 25%, based on real-world data from multiple retrospective studies [6–11]. Unfortunately, studies that have evaluated the incidence of AKI in patients receiving ICIs have used different criteria to define AKI.…”

Section: Incidence Of Aki In Patients Receiving Ici Therapymentioning

confidence: 99%

“…The acute interstitial nephritis (AIN) is the most common finding in the kidney biopsies of patients with ICI-associated AKI in about 80–90% [14, 15]. However, a spectrum of other glomerulopathies could also be seen, albeit less commonly, including pauci-immune vasculitis, C3 glomerulonephritis, thrombotic microangiopathy, and immune complex glomerulonephritis [6–12, 16, 17]. Although the median time for diagnosing ICI-associated AKI from the initiation of ICIs to clinical presentation is approximately 3–4 months, it has been reported to occur as early as a few days or as late as 18 months into therapy [14, 15, 18, 19].…”

Section: Incidence Of Aki In Patients Receiving Ici Therapymentioning

confidence: 99%

“…Based on KDIGO guideline, the extent of AKI severity in patients on ICIs includes stage 1 (sCr, 1.5-1.9 times baseline or ≥0.3 mg/dL above baseline) in 0-85% of the patients, stage 2 (sCr, 2-2.9 times baseline) in 8.6-43%, stage 3 (sCr, ≥3 times baseline, sCr ≥4 mg/dL, or initiation on renal replacement therapy) in 7-57%, and stage 3 requiring renal replacement therapy in 0-9%. The variability in these rates may be related, at least in part, to the inclusion of different types of AKI (ICI vs. non-ICI-associated AKI) and the definition of AKI (sustained vs. transient) in the data analysis across various studies [6][7][8][9][10][11][12][13][14][15]20].…”

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confidence: 99%

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Immune Checkpoint Inhibitor-Associated Nephrotoxicity

Danesh¹,

Mamlouk²

2023

Nephron

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Context: The clinical indications for immune checkpoint inhibitors (ICIs) are rapidly expanding. However, adverse events affecting multiple organs, including kidneys leading to ICI-associated acute kidney injury (AKI), remain a significant challenge with ICI therapy. Although AKI is considered a rare complication, it can be severe and result in treatment interruption or discontinuation of ICIs. Despite a generally favorable kidney prognosis, the possibility of re-challenging ICI therapy remains a subject of debate, particularly for patients who have exhausted other treatment options or experienced severe AKI. Subject of Review: In a recent review article, Sprangers et al. provide a comprehensive overview of the possible mechanisms and clinical manifestations of ICI-associated AKI [Nat Rev Nephrol. 2022;18(12):794–805]. The authors propose a practical strategy for diagnosing and managing suspected cases of ICI-associated AKI, which includes identifying a subset of eligible patients who may be re-exposed to ICIs following an episode of AKI. Second Opinion: The authors of the review article offer several recommendations on the diagnosis and treatment of ICI-associated nephrotoxicity. While we generally agree with the recommendations proposed by the authors, it is important to acknowledge that the available data primarily rely on small retrospective studies, as the authors have recognized. In addition, there are two key questions that need be carefully addressed in future studies: (1) the optimal dose and duration of corticosteroids and the use of alternative immunosuppressive agents in patients with ICI-associated nephrotoxicity and (2) a clear guideline for restarting ICI treatment in patients with AKI who have not fully recovered their kidney function.

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“…Through extensive clinical studies and meta-analyses, several key factors have emerged: Age and sex: Although there are limited data, there appeared to be no notable differences observed with regard to advancing age, male gender, white race, or other pre-existing comorbidities [ 4 , 16 ]. Drugs: Renal irAEs are potentially more prevalent in patients undergoing ICI therapy combined with PPIs, NSAIDs, or antibiotics [ 4 , 17 ]. Combining ICIs with these medications, particularly NSAIDs and PPIs, has been linked to AIN, potentially activating drug-specific T cells, and triggering immune reactions.…”

Section: Diagnosismentioning

confidence: 99%

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

Moturi,

Sharma,

Hashemi-Sadraei

2023

IJMS

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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.

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Incidence, risk factors and prognosis of acute kidney injury in patients treated with immune checkpoint inhibitors: a retrospective study

Cited by 12 publications

References 40 publications

Interpretable machine learning-based individual analysis of acute kidney injury in immune checkpoint inhibitor therapy

Interpretable machine learning-based individual analysis of acute kidney injury in immune checkpoint inhibitor therapy

Immune Checkpoint Inhibitor-Associated Nephrotoxicity

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

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