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Zhou P, Gao Y, Kong Z, Wang J, Si S, Han W, Li J, Lv Z, Wang R. Immune checkpoint inhibitors and acute kidney injury. Front Immunol 2024; 15:1353339. [PMID: 38464524 PMCID: PMC10920224 DOI: 10.3389/fimmu.2024.1353339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2023] [Accepted: 02/12/2024] [Indexed: 03/12/2024] Open
Abstract
As a new type of anti-tumor immunotherapy, immune checkpoint inhibitors (ICIs) have improved the prognosis of multiple malignancies. However, renal complications are becoming more frequent. Nephrotoxicity often manifests as acute kidney injury (AKI), and the most common histopathological type is acute tubulointerstitial nephritis (ATIN). Based on previous studies of the incidence and potential risk factors for nephrotoxicity, in this review, we describe the mechanism of AKI after ICIs treatment, summarize the incidence, risk factors, and outcomes of AKI, and discuss the diagnosis and management of immune checkpoint inhibitors-associated acute kidney injury (ICI-AKI). In addition, we review the current status of ICIs rechallenge and the therapeutic strategies of ICIs applied in kidney transplant recipients. Finally, we emphasize the importance of collaboration between nephrologists and oncologists to guide the treatment of ICIs and the management of renal complications.
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Affiliation(s)
- Ping Zhou
- Department of Nephrology, Shandong Provincial Hospital, Shandong University, Jinan, China
| | - Ying Gao
- Department of Nephrology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Zhijuan Kong
- Department of Nephrology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Junlin Wang
- Department of Nephrology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Shuxuan Si
- Department of Nephrology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Wei Han
- Department of Nephrology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Jie Li
- Department of Nephrology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Zhimei Lv
- Department of Nephrology, Shandong Provincial Hospital, Shandong University, Jinan, China
- Department of Nephrology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Rong Wang
- Department of Nephrology, Shandong Provincial Hospital, Shandong University, Jinan, China
- Department of Nephrology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
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Chen JJ, Lee TH, Kuo G, Yen CL, Lee CC, Chang CH, Tu KH, Chen YC, Fang JT, Hung CC, Yang CW, Chou WC, Chi CC, Tu YK, Yu Yang H. All-cause and immune checkpoint inhibitor-associated acute kidney injury in immune checkpoint inhibitor users: a meta-analysis of occurrence rate, risk factors and mortality. Clin Kidney J 2024; 17:sfad292. [PMID: 38186874 PMCID: PMC10768773 DOI: 10.1093/ckj/sfad292] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Indexed: 01/09/2024] Open
Abstract
Background Immune checkpoint inhibitors (ICIs) have been associated with acute kidney injury (AKI). However, the occurrence rate of ICI-related AKI has not been systematically examined. Additionally, exposure to proton pump inhibitors (PPIs) and non-steroidal anti-inflammatory drugs (NSAIDs) were considered as risk factors for AKI, but with inconclusive results in ICI-related AKI. Our aim was to analyse the occurrence rate of all-cause AKI and ICI-related AKI and the occurrence rates of severe AKI and dialysis-requiring AKI, and to determine whether exposure to PPIs and NSAIDs poses a risk for all-cause and ICI-related AKI. Methods This study population was adult ICI recipients. A systematic review was conducted by searching MEDLINE, Embase and PubMed through October 2023. We included prospective trials and observational studies that reported any of the following outcomes: the occurrence rate of all-cause or ICI-related AKI, the relationship between PPI or NSAID exposure and AKI development or the mortality rate in the AKI or non-AKI group. Proportional meta-analysis and pairwise meta-analysis were performed. The evidence certainty was assessed using the Grading of Recommendations Assessment, Development and Evaluation framework. Results A total of 120 studies comprising 46 417 patients were included. The occurrence rates of all-cause AKI were 7.4% (14.6% from retrospective studies and 1.2% from prospective clinical trials). The occurrence rate of ICI-related AKI was 3.2%. The use of PPIs was associated with an odds ratio (OR) of 1.77 [95% confidence interval (CI) 1.43-2.18] for all-cause AKI and an OR of 2.42 (95% CI 1.96-2.97) for ICI-related AKI. The use of NSAIDs was associated with an OR of 1.77 (95% CI 1.10-2.83) for all-cause AKI and an OR of 2.57 (95% CI 1.68-3.93) for ICI-related AKI. Conclusions Our analysis revealed that approximately 1 in 13 adult ICI recipients may experience all-cause AKI, while 1 in 33 adult ICI recipients may experience ICI-related AKI. Exposure to PPIs and NSAIDs was associated with an increased OR risk for AKI in the current meta-analysis.
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Affiliation(s)
- Jia-Jin Chen
- Kidney Research Center, Nephrology Department, Chang Gung Memorial Hospital in Linkou, Chang Gung University College of Medicine, Taoyuan, Taiwan
| | - Tao-Han Lee
- Nephrology Department, Chansn Hospital, Taoyuan City, Taiwan
| | - George Kuo
- Kidney Research Center, Nephrology Department, Chang Gung Memorial Hospital in Linkou, Chang Gung University College of Medicine, Taoyuan, Taiwan
| | - Chieh-Li Yen
- Kidney Research Center, Nephrology Department, Chang Gung Memorial Hospital in Linkou, Chang Gung University College of Medicine, Taoyuan, Taiwan
| | - Cheng-Chia Lee
- Kidney Research Center, Nephrology Department, Chang Gung Memorial Hospital in Linkou, Chang Gung University College of Medicine, Taoyuan, Taiwan
| | - Chih-Hsiang Chang
- Kidney Research Center, Nephrology Department, Chang Gung Memorial Hospital in Linkou, Chang Gung University College of Medicine, Taoyuan, Taiwan
| | - Kun-Hua Tu
- Kidney Research Center, Nephrology Department, Chang Gung Memorial Hospital in Linkou, Chang Gung University College of Medicine, Taoyuan, Taiwan
| | - Yung-Chang Chen
- Kidney Research Center, Nephrology Department, Chang Gung Memorial Hospital in Linkou, Chang Gung University College of Medicine, Taoyuan, Taiwan
| | - Ji-Tseng Fang
- Kidney Research Center, Nephrology Department, Chang Gung Memorial Hospital in Linkou, Chang Gung University College of Medicine, Taoyuan, Taiwan
| | - Cheng-Chieh Hung
- Kidney Research Center, Nephrology Department, Chang Gung Memorial Hospital in Linkou, Chang Gung University College of Medicine, Taoyuan, Taiwan
| | - Chih-Wei Yang
- Kidney Research Center, Nephrology Department, Chang Gung Memorial Hospital in Linkou, Chang Gung University College of Medicine, Taoyuan, Taiwan
| | - Wen-Chi Chou
- Department of Hematology and Oncology, Chang Gung Memorial Hospital in Linkou and College of Medicine, Chang Gung University, Taoyuan, Taiwan
| | - Ching-Chi Chi
- School of Medicine, College of Medicine, Chang Gung University; Department of Dermatology, Chang Gung Memorial Hospital, Linkou, Taoyuan, Taiwan
| | - Yu-Kang Tu
- Graduate Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan
| | - Huang- Yu Yang
- Kidney Research Center, Nephrology Department, Chang Gung Memorial Hospital in Linkou, Chang Gung University College of Medicine, Taoyuan, Taiwan
- Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
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Hu JX, Zhao CF, Wang SL, Tu XY, Huang WB, Chen JN, Xie Y, Chen CR. Acute pancreatitis: A review of diagnosis, severity prediction and prognosis assessment from imaging technology, scoring system and artificial intelligence. World J Gastroenterol 2023; 29:5268-5291. [PMID: 37899784 PMCID: PMC10600804 DOI: 10.3748/wjg.v29.i37.5268] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Revised: 07/31/2023] [Accepted: 09/14/2023] [Indexed: 09/25/2023] Open
Abstract
Acute pancreatitis (AP) is a potentially life-threatening inflammatory disease of the pancreas, with clinical management determined by the severity of the disease. Diagnosis, severity prediction, and prognosis assessment of AP typically involve the use of imaging technologies, such as computed tomography, magnetic resonance imaging, and ultrasound, and scoring systems, including Ranson, Acute Physiology and Chronic Health Evaluation II, and Bedside Index for Severity in AP scores. Computed tomography is considered the gold standard imaging modality for AP due to its high sensitivity and specificity, while magnetic resonance imaging and ultrasound can provide additional information on biliary obstruction and vascular complications. Scoring systems utilize clinical and laboratory parameters to classify AP patients into mild, moderate, or severe categories, guiding treatment decisions, such as intensive care unit admission, early enteral feeding, and antibiotic use. Despite the central role of imaging technologies and scoring systems in AP management, these methods have limitations in terms of accuracy, reproducibility, practicality and economics. Recent advancements of artificial intelligence (AI) provide new opportunities to enhance their performance by analyzing vast amounts of clinical and imaging data. AI algorithms can analyze large amounts of clinical and imaging data, identify scoring system patterns, and predict the clinical course of disease. AI-based models have shown promising results in predicting the severity and mortality of AP, but further validation and standardization are required before widespread clinical application. In addition, understanding the correlation between these three technologies will aid in developing new methods that can accurately, sensitively, and specifically be used in the diagnosis, severity prediction, and prognosis assessment of AP through complementary advantages.
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Affiliation(s)
- Jian-Xiong Hu
- Intensive Care Unit, The Affiliated Hospital of Putian University, Putian 351100, Fujian Province, China
| | - Cheng-Fei Zhao
- School of Pharmacy and Medical Technology, Putian University, Putian 351100, Fujian Province, China
- Key Laboratory of Pharmaceutical Analysis and Laboratory Medicine, Putian University, Putian 351100, Fujian Province, China
| | - Shu-Ling Wang
- Department of Critical Care Medicine, Fujian Medical University Union Hospital, Fuzhou 350001, Fujian Province, China
| | - Xiao-Yan Tu
- Department of Critical Care Medicine, Fujian Medical University Union Hospital, Fuzhou 350001, Fujian Province, China
| | - Wei-Bin Huang
- Department of Critical Care Medicine, Fujian Medical University Union Hospital, Fuzhou 350001, Fujian Province, China
| | - Jun-Nian Chen
- Department of Critical Care Medicine, Fujian Medical University Union Hospital, Fuzhou 350001, Fujian Province, China
| | - Ying Xie
- School of Mechanical, Electrical and Information Engineering, Putian University, Putian 351100, Fujian Province, China
| | - Cun-Rong Chen
- Department of Critical Care Medicine, Fujian Medical University Union Hospital, Fuzhou 350001, Fujian Province, China
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Hu J, Li Y, Zhang X, Wang Y, Zhang J, Yan J, Li J, Zhang Z, Yin H, Wei Q, Jiang Q, Wei S, Zhang Q. Ultrasensitive Silicon Nanowire Biosensor with Modulated Threshold Voltages and Ultra-Small Diameter for Early Kidney Failure Biomarker Cystatin C. BIOSENSORS 2023; 13:645. [PMID: 37367010 PMCID: PMC10296041 DOI: 10.3390/bios13060645] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Revised: 06/01/2023] [Accepted: 06/09/2023] [Indexed: 06/28/2023]
Abstract
Acute kidney injury (AKI) is a frequently occurring severe disease with high mortality. Cystatin C (Cys-C), as a biomarker of early kidney failure, can be used to detect and prevent acute renal injury. In this paper, a biosensor based on a silicon nanowire field-effect transistor (SiNW FET) was studied for the quantitative detection of Cys-C. Based on the spacer image transfer (SIT) processes and channel doping optimization for higher sensitivity, a wafer-scale, highly controllable SiNW FET was designed and fabricated with a 13.5 nm SiNW. In order to improve the specificity, Cys-C antibodies were modified on the oxide layer of the SiNW surface by oxygen plasma treatment and silanization. Furthermore, a polydimethylsiloxane (PDMS) microchannel was involved in improving the effectiveness and stability of detection. The experimental results show that the SiNW FET sensors realize the lower limit of detection (LOD) of 0.25 ag/mL and have a good linear correlation in the range of Cys-C concentration from 1 ag/mL to 10 pg/mL, exhibiting its great potential in the future real-time application.
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Affiliation(s)
- Jiawei Hu
- School of Information Science and Technology, North China University of Technology, Beijing 100144, China; (J.H.); (Y.L.); (X.Z.); (Y.W.); (J.Z.)
- Advanced Integrated Circuits R&D Center, Institute of Microelectronic of the Chinese Academy of Sciences, Beijing 100029, China; (J.L.); (Z.Z.)
| | - Yinglu Li
- School of Information Science and Technology, North China University of Technology, Beijing 100144, China; (J.H.); (Y.L.); (X.Z.); (Y.W.); (J.Z.)
- Advanced Integrated Circuits R&D Center, Institute of Microelectronic of the Chinese Academy of Sciences, Beijing 100029, China; (J.L.); (Z.Z.)
| | - Xufang Zhang
- School of Information Science and Technology, North China University of Technology, Beijing 100144, China; (J.H.); (Y.L.); (X.Z.); (Y.W.); (J.Z.)
| | - Yanrong Wang
- School of Information Science and Technology, North China University of Technology, Beijing 100144, China; (J.H.); (Y.L.); (X.Z.); (Y.W.); (J.Z.)
| | - Jing Zhang
- School of Information Science and Technology, North China University of Technology, Beijing 100144, China; (J.H.); (Y.L.); (X.Z.); (Y.W.); (J.Z.)
| | - Jiang Yan
- School of Information Science and Technology, North China University of Technology, Beijing 100144, China; (J.H.); (Y.L.); (X.Z.); (Y.W.); (J.Z.)
| | - Junjie Li
- Advanced Integrated Circuits R&D Center, Institute of Microelectronic of the Chinese Academy of Sciences, Beijing 100029, China; (J.L.); (Z.Z.)
| | - Zhaohao Zhang
- Advanced Integrated Circuits R&D Center, Institute of Microelectronic of the Chinese Academy of Sciences, Beijing 100029, China; (J.L.); (Z.Z.)
| | - Huaxiang Yin
- Advanced Integrated Circuits R&D Center, Institute of Microelectronic of the Chinese Academy of Sciences, Beijing 100029, China; (J.L.); (Z.Z.)
| | - Qianhui Wei
- State Key Laboratory of Advanced Materials for Smart Sensing, General Research Institute for Nonferrous Metals, Beijing 101402, China;
| | - Qifeng Jiang
- School of Information Science and Technology, North China University of Technology, Beijing 100144, China; (J.H.); (Y.L.); (X.Z.); (Y.W.); (J.Z.)
| | - Shuhua Wei
- School of Information Science and Technology, North China University of Technology, Beijing 100144, China; (J.H.); (Y.L.); (X.Z.); (Y.W.); (J.Z.)
| | - Qingzhu Zhang
- Advanced Integrated Circuits R&D Center, Institute of Microelectronic of the Chinese Academy of Sciences, Beijing 100029, China; (J.L.); (Z.Z.)
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Liu C, Wei W, Yang L, Li J, Yi C, Pu Y, Yin T, Na F, Zhang L, Fu P, Zhao Y. Incidence and risk factors of acute kidney injury in cancer patients treated with immune checkpoint inhibitors: a systematic review and meta-analysis. Front Immunol 2023; 14:1173952. [PMID: 37313406 PMCID: PMC10258324 DOI: 10.3389/fimmu.2023.1173952] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2023] [Accepted: 05/10/2023] [Indexed: 06/15/2023] Open
Abstract
Background The incidence and risk factors of acute kidney injury (AKI) in patients with malignancies receiving immune checkpoint inhibitors (ICIs) are being extensively reported with their widespread application. Objective This study aimed to quantify the incidence and identify risk factors of AKI in cancer patients treated with ICIs. Methods We searched the electronic databases of PubMed/Medline, Web of Science, Cochrane and Embase before 1 February 2023 on the incidence and risk factors of AKI in patients receiving ICIs and registered the protocol in PROSPERO (CRD42023391939). A random-effect meta-analysis was performed to quantify the pooled incidence estimate of AKI, identify risk factors with pooled odds ratios (ORs) and 95% confidence intervals (95% CIs) and investigate the median latency period of ICI-AKI in patients treated with ICIs. Assessment of study quality, meta-regression, and sensitivity and publication bias analyses were conducted. Results In total, 27 studies consisting of 24048 participants were included in this systematic review and meta-analysis. The overall pooled incidence of AKI secondary to ICIs was 5.7% (95% CI: 3.7%-8.2%). Significant risk factors were older age (OR: 1.01, 95% CI: 1.00-1.03), preexisting chronic kidney disease (CKD) (OR: 2.90, 95% CI: 1.65-5.11), ipilimumab (OR: 2.66, 95% CI: 1.42-4.98), combination of ICIs (OR: 2.45, 95% CI: 1.40-4.31), extrarenal immune-related adverse events (irAEs) (OR: 2.34, 95% CI: 1.53-3.59), and proton pump inhibitor (PPI) (OR: 2.23, 95% CI: 1.88-2.64), nonsteroidal anti-inflammatory drug (NSAID) (OR: 2.61, 95% CI: 1.90-3.57), fluindione (OR: 6.48, 95% CI: 2.72-15.46), diuretic (OR: 1.78, 95% CI: 1.32-2.40) and angiotensin-converting enzyme inhibitors (ACEIs) or angiotensin-receptor blockers (ARBs) (pooled OR: 1.76, 95% CI: 1.15-2.68) use. Median time from ICIs initiation to AKI was 108.07 days. Sensitivity and publication bias analyses indicated robust results for this study. Conclusion The occurrence of AKI following ICIs was not uncommon, with an incidence of 5.7% and a median time interval of 108.07 days after ICIs initiation. Older age, preexisting chronic kidney disease (CKD), ipilimumab, combined use of ICIs, extrarenal irAEs, and PPI, NSAID, fluindione, diuretics and ACEI/ARB use are risk factors for AKI in patients receiving ICIs. Systematic review registration https://www.crd.york.ac.uk/prospero/, identifier CRD42023391939.
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Affiliation(s)
- Caihong Liu
- Department of Nephrology, Kidney Research Institute, West China Hospital of Sichuan University, Chengdu, China
| | - Wei Wei
- Department of Nephrology, Kidney Research Institute, West China Hospital of Sichuan University, Chengdu, China
| | - Letian Yang
- Department of Nephrology, Kidney Research Institute, West China Hospital of Sichuan University, Chengdu, China
| | - Jian Li
- Department of Nephrology, Kidney Research Institute, West China Hospital of Sichuan University, Chengdu, China
| | - Cheng Yi
- Department of Thyroid and Parathyroid Surgery, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yajun Pu
- Department of Nephrology, Kidney Research Institute, West China Hospital of Sichuan University, Chengdu, China
| | - Ting Yin
- Department of Nephrology, Kidney Research Institute, West China Hospital of Sichuan University, Chengdu, China
| | - Feifei Na
- Department of Thoracic Oncology, Cancer Center, and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China
| | - Ling Zhang
- Department of Nephrology, Kidney Research Institute, West China Hospital of Sichuan University, Chengdu, China
| | - Ping Fu
- Department of Nephrology, Kidney Research Institute, West China Hospital of Sichuan University, Chengdu, China
| | - Yuliang Zhao
- Department of Nephrology, Kidney Research Institute, West China Hospital of Sichuan University, Chengdu, China
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Innovating human chemical hazard and risk assessment through an holistic approach. CURRENT OPINION IN TOXICOLOGY 2023. [DOI: 10.1016/j.cotox.2023.100386] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/12/2023]
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