Skip Navigation
Skip to contents

Cancer Res Treat : Cancer Research and Treatment

OPEN ACCESS

Articles

Page Path
HOME > Cancer Res Treat > Volume 53(2); 2021 > Article
Original Article
Immunotherapy
The Pattern of Time to Onset and Resolution of Immune-Related Adverse Events Caused by Immune Checkpoint Inhibitors in Cancer: A Pooled Analysis of 23 Clinical Trials and 8,436 Patients
Si-Qi Tang1, Ling-Long Tang1, Yan-Ping Mao1, Wen-Fei Li1, Lei Chen1, Yuan Zhang1, Ying Guo2, Qing Liu3, Ying Sun1, Cheng Xu1, Jun Ma1
Cancer Research and Treatment : Official Journal of Korean Cancer Association 2021;53(2):339-354.
DOI: https://doi.org/10.4143/crt.2020.790
Published online: November 6, 2020

1Department of Radiation Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, China

2Clinical Trials Center, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, China

3Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China

Correspondence: Jun Ma, Department of Radiation Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center of Cancer Medicine, 651 Dongfeng Road East, Guangzhou 510060, China,
Tel: 86-20-87343469 Fax: 86-20-87343295 E-mail: majun2@mail.sysu.edu.cn
Co-correspondence: Cheng Xu, Department of Radiation Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center of Cancer Medicine, 651 Dongfeng Road East, Guangzhou 510060, China,
Tel: 86-20-87343500 Fax: 86-20-87343500 E-mail: xucheng@sysucc.org.cn
* Si-Qi Tang, Ling-Long Tang, and Yan-Ping Mao contributed equally to this work.
• Received: August 8, 2020   • Accepted: November 5, 2020

Copyright © 2021 by the Korean Cancer Association

This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

  • 15,140 Views
  • 708 Download
  • 94 Web of Science
  • 100 Crossref
  • 102 Scopus
prev next
  • Purpose
    The occurrence pattern of immune-related adverse events (irAEs) induced by immune checkpoint inhibitor (ICI) in cancer treatment remains unclear.
  • Materials and Methods
    Phase II–III clinical trials that evaluated ICI-based treatments in cancer and were published between January 2007 and December 2019 were retrieved from public electronic databases. The pooled median time to onset (PMT-O), resolution (PMT-R), and immune-modulation resolution (PMT-IMR) of irAEs were generated using the metamedian package of R software.
  • Results
    Twenty-two eligible studies involving 23 clinical trials and 8,436 patients were included. The PMT-O of all-grade irAEs ranged from 2.2 to 14.8 weeks, with the longest in renal events. The PMT-O of grade ≥ 3 irAEs was significantly longer than that of all-grade irAEs induced by programmed cell death protein 1 (PD-1) and its ligand 1 (PD-L1) inhibitors (27.5 weeks vs. 8.4 weeks, p < 0.001) and treatment of nivolumab (NIV) plus ipilimumab (IPI) (7.9 weeks vs. 6.0 weeks, p < 0.001). The PMT-R of all-grade irAEs ranged from 0.1 to 54.3 weeks, with the shortest and longest in hypersensitivity/infusion reaction and endocrine events, respectively. The PMT-IMR of grade ≥ 3 irAEs was significantly shorter than that of all-grade irAEs caused by PD-1/PD-L1 blockade (6.9 weeks vs. 40.6 weeks, p=0.002) and NIV+IPI treatment (3.1 weeks vs. 5.9 weeks, p=0.031).
  • Conclusion
    This study revealed the general and specific occurrence pattern of ICI-induced irAEs in pan-cancers, which was deemed to aid the comprehensive understanding, timely detection, and effective management of ICI-induced irAEs.
Immune checkpoint inhibitors (ICIs) have opened a new era of cancer management through the leverage of the immune system’s potential and have become one of the mainstays of antitumor treatment [1]. The activation and proliferation of T cells are modulated by certain inhibitory surface signaling molecules, so-called checkpoints. Several different immune checkpoint molecules have been identified, in particular, cytotoxic T-lymphocyte antigen 4 (CTLA-4) and programmed cell death protein 1 (PD-1) and its ligand 1 (PD-L1). Selectively blocking the interaction of ligands with these checkpoints can lead to amplification of T cell–mediated immunity and disruption of tumor immune escape. Substantial clinical studies have demonstrated that antibodies against CTLA-4 and PD-1/PD-L1 can yield a significant survival improvement in several tumor types, including metastatic melanoma, non-small cell lung cancer, and renal cell carcinoma [25]. However, the routine application of these novel ICI drugs highlights the essence of knowledge and management of ICI-induced immune-related adverse events (irAEs).
In light of the fact that ICI delivers positive antitumor efficacy by interfering with immune system regulation, an activated immune response might attack normal body tissues and be responsible for the development of irAEs. The common irAEs include colitis, hepatitis, pneumonitis, nephritis, and endocrinopathies [6,7]. Although the majority of irAEs show moderate toxicity, there have been reports of ICI- induced deaths, mainly due to autoimmune colitis, myocarditis, and myasthenia gravis [2,811]. Most of mild-to-moderate irAEs can be well controlled by observation and supportive treatment without withholding ICI drugs, however, patients with severe irAEs still require enhanced and timely medical interventions, such as corticosteroids and immunosuppressive agents, in line with the guidelines of the National Comprehensive Cancer Network (NCCN) and European Society for Medical Oncology (ESMO) [12,13]. Our previous study revealed that the toxicity profile and incidence of irAEs varied among ICI drugs [14]. However, the pattern of the time to onset and resolution of ICI-induced irAEs remains undetermined and is worth further exploration. There are few studies concerning the pattern of irAE development in cancer. Martins et al. [15] proposed that the majority of grade ≥ 3 irAEs induced by anti–CTLA-4 antibodies occur within 8–12 weeks of commencing treatment. Skin rash usually had the earliest onset and irAEs tended to occur earlier in the course of nivolumab (NIV) plus ipilimumab (IPI) treatment than in that of IPI monotherapy [15]. Nonetheless, the results were summarized through a literature review rather than statistical calculations and the time to resolution was not investigated. Although Weber et al. [16] demonstrated a characteristic pattern of the occurrence of irAEs, these results were generated based on small sample size (n=325) and the pattern was applicable to only four organ-specific irAEs and specific treatment of IPI 10 mg/kg every 3 weeks, failing to provide a comprehensive view of ICI-induced irAEs in pan-cancers [16].
By using the data derived from robust clinical trials, we conducted a pooled analysis to investigate the pattern of the time to onset, resolution, and immune-modulation resolution of irAEs in cancer, intending to aid a better understanding, timely detection, and effective management of ICI-induced irAEs in routine practice.
A prospective protocol was created and uploaded to the PROSPERO online platform, with the registration number CRD42020167835.
1. Data sources and searches
We searched for relevant studies published between January 2007 and December 2019 through public electronic databases, including PubMed, Embase, Cochrane Library, and Web of Science. Two investigators (S.Q.T. and C.X.) determined the final search strategy (Supplementary Materials). After screening the titles or abstracts, full texts were assessed, and references of relevant publications were manually searched.
2. Study selection
We included phase II–III clinical trials that reported the median time to onset, resolution, or immune-modulation resolution of irAEs in cancer receiving ICI-based treatments (e.g., ICI alone or ICI plus conventional therapy). Conventional therapies (CT) included chemotherapy, radiotherapy, and so on. The definitions for outcomes above were listed in Supplementary Materials and were consistent among all included clinical trials. We excluded conference abstracts and presentations of ongoing clinical trials due to the insufficient information.
3. Data extraction and processing
We extracted the data from the main text and supplementary materials. Two reviewers (S.Q.T. and C.X.) independently recorded the data on a predesigned list (Supplementary Materials). Data from the updated study were used to supplement those from the previous report of the same trial. Common Terminology Criteria for Adverse Events were used to evaluate the adverse events and grade the severity of each irAE [17]. Grade ≥ 3 irAEs were considered severe events.
4. Quality assessment
Two reviewers (S.Q.T. and C.X.) used the tool recommended by the Cochrane Collaboration Handbook and the modified Jadad scale to evaluate the quality of the included clinical trials [18,19]. Discrepancies regarding study selection, data extraction, and quality assessment between two reviewers were resolved by discussion.
5. Data synthesis and statistical analysis
The timing data that represented different event subsets to the same organ-specific irAEs were pooled as the timing data of that category. For example, the time to onset of hyperthyroidism and hypothyroidism would be pooled as that of endocrine events. The data with censored values were excluded. We used the pooled median time (weighted median time) to onset (PMT-O), resolution (PMT-R), and immune-modulation resolution (PMT-IMR) and their 95% confidence interval as summary statistics. The outcomes were generated by using the metamedian package in R ver. 3.6.1 (http://www.r-project.org/) [20]. The primary outcomes were PMT-O and PMT-R of all-grade irAEs. The secondary outcomes were PMT-IMR of all-grade irAEs and the outcomes of grade ≥ 3 irAEs. All outcomes were assessed from two different perspectives: overview and detail, based on the time of development of all irAEs and that of organ-specific irAE, respectively.
Given that the different toxicity profiles among ICI agents, the PMT-O, PMT-R, and PMT-IMR were compared between PD-1/PD-L1 inhibitor, CTLA-4 inhibitor, and combination therapy (i.e. more than one kind of ICI agent). The former two treatments refer to applying one ICI agent with or without CT. Subgroup analyses were based on ICI drugs, ICI doses, and cancer types.
Data visualization methods were used to depict the pooled median time and 95% confidence interval via Microsoft Excel (Microsoft, Inc., Redmond, WA). We used the Z test to identify the differences among PMT-O, PMT-R, and PMT-IMR by SPSS ver. 24.0 (IBM Corp., Armonk, NY). All p-values were two-sided with significance defined as p < 0.05.
1. Literature search and characteristics
We included 22 studies involving 23 clinical trials and 8,436 patients in this study (S1 Table, S2 Fig.) [3,2141]. The baseline characteristics of each study were shown in Table 1. Thirteen clinical trials (56.5%) were phase III trials. One study reported the pooled results of a phase I and a phase II clinical trial with a large sample size of 1,738 patients; thus, the phase I trial was also included [32]. The cancer types included lung cancer (number of the involving trials=6), melanoma (n=7), urinary system cancer (n=4), and other (n=6). PD-1/PD-L1 blockade-based treatments included monotherapy of NIV (n=10), pembrolizumab (n=2), and avelumab (n=2). CTLA-4 blockade-based treatments included IPI monotherapy (n=5) and IPI+CT (n=3). Combination therapy included NIV+IPI (n=5). Subgroup analysis included two updated clinical trials without duplicate counting of their sample sizes [30]. According to modified Jadad scores, 20 studies were assessed as high quality, and two studies were assessed as relatively low quality (S3 Table) [3,23].
2. Pooled analysis of the time to onset
The PMT-O of all-grade irAEs ranged from 2.2 to 14.8 weeks. The four irAEs with the top shortest PMT-O were skin, hypersensitivity/infusion reaction, gastrointestinal, and neurologic events, while the longest PMT-O was observed in renal events (Fig. 1A, C, and E).
The PMT-O of grade ≥ 3 irAEs ranged from 4.6 to 12.2 weeks for CTLA-4 inhibitors and NIV+IPI treatment and ranged from 14.1 to 123.4 weeks for PD-1/PD-L1 inhibitors. Compared with all-grade irAEs, the PMT-O of grade ≥ 3 irAEs was significantly longer for PD-1/PD-L1 inhibitors (27.5 weeks vs. 8.4 weeks, p < 0.001) and NIV+IPI treatment (7.9 weeks vs. 6.0 weeks, p < 0.001) in overview; as for CTLA-4 inhibitors, that was significantly longer in gastrointestinal (7.0 weeks vs. 5.0 weeks, p=0.023), hepatic (9.9 weeks vs. 8.9 weeks, p=0.002), endocrine (10.6 weeks vs. 9.1 weeks, p=0.049), hypersensitivity/infusion reaction (7.4 weeks vs. 6.1 weeks, p=0.005), and neurologic events (11.1 weeks vs. 4.0 weeks, p=0.002) (Fig. 1).
3. Pooled analysis of the time to resolution
The PMT-R of all-grade irAEs ranged from 0.1 to 54.3 weeks. The five irAEs with the top shortest PMT-R were hypersensitivity/infusion reaction, gastrointestinal, pulmonary, hepatic, and renal events, which might be resolved within 10.5 weeks (Fig. 2A, E, and I). The PMT-R of grade ≥ 3 irAEs was within 7.9 weeks when excluding endocrine events (Fig. 2B, F, and J).
In overview, the PMT-R was comparable between grade ≥ 3 and all-grade irAEs. By organ, the PMT-R of grade ≥ 3 irAEs was significantly shorter than that of all-grade irAEs induced by NIV+IPI treatment in skin (3.1 weeks vs. 10.9 weeks, p=0.049), endocrine (11.6 weeks vs. 27.6 weeks, p < 0.001), pulmonary (1.5 weeks vs. 4.5 weeks, p=0.010), and renal events (2.4 weeks vs. 6.3 weeks, p=0.028) (Fig. 2A, B, E, F, I, J). When applying the immune-modulation drug, the time to resolution of grade ≥ 3 irAEs was significantly shorter than that of all-grade irAEs caused by PD-1/PD-L1 blockade (6.9 weeks vs. 40.6 weeks, p=0.002) and NIV+IPI treatment (3.1 weeks vs. 5.9 weeks, p=0.031) in the overview. As for CTLA-4 blockade, the PMT-IMR of grade ≥ 3 irAEs was significantly shorter than that of all-grade irAEs in skin (8.5 weeks vs. 14.4 weeks, p < 0.001), gastrointestinal (3.3 weeks vs. 4.4 weeks, p < 0.001), and hypersensitivity/infusion reaction (0.3 weeks vs. 2.1 weeks, p < 0.001) (Fig. 2C, D, G, H, K, and L).
When compared with PMT-R, the PMT-IMR of all-grade irAEs caused by PD-1/PD-L1 inhibitors was significantly longer (40.6 weeks vs. 10.1 weeks, p=0.010) in overview; as for CTLA-4 inhibitors, the PMT-IMR was significantly longer in skin (14.4 weeks vs. 9.3 weeks, p=0.004), gastrointestinal (4.4 weeks vs. 2.9 weeks, p < 0.001), and hypersensitivity/infusion reaction (2.1 weeks vs. 0.1 weeks, p < 0.001) (Fig. 2A, C, E, G, I, and K). Regardless of grading, hypersensitivity/infusion reaction and endocrine events were associated with the shortest and longest PMT-IMR, respectively, which were similar to the patterns of PMT-R.
4. Subgroup analysis based on ICI drugs
NIV monotherapy was associated with significantly longer PMT-O of all-grade irAEs than NIV+IPI (8.2 weeks vs. 6.0 weeks, p < 0.001) and IPI alone (8.2 weeks vs. 6.1 weeks, p=0.012). The PMT-R was comparable between NIV+IPI and the corresponding monotherapy (Fig. 3).
In terms of grade ≥ 3 irAEs, NIV monotherapy had the significantly longest PMT-O among these three treatments in overview (IPI vs. NIV+IPI vs. NIV: 7.4 weeks vs. 7.9 vs. 27.5 weeks; p < 0.05), especially in gastrointestinal (7.0 weeks vs. 7.4 weeks vs. 36.4 weeks, p < 0.001), endocrine (10.6 weeks vs. 12.2 weeks vs. 24.0 weeks, p < 0.05), pulmonary (6.2 weeks vs. 6.0 weeks vs. 27.5 weeks, p < 0.05), and renal events (10.0 weeks vs. 11.3 weeks vs. 123.4 weeks, p < 0.001) (S4 Table).
In overview, the PMT-O and PMT-R were comparable between IPI alone and IPI+CT. By organ, the PMT-O of hepa-tic (8.9 weeks vs. 5.9 weeks, p < 0.001) and neurologic events (13.1 weeks vs. 4.0 weeks, p < 0.001) and the PMT-R of skin (9.3 weeks vs. 4.3 weeks, p=0.037) and endocrine events (54.3 weeks vs. 10.4 weeks, p < 0.001) were significantly longer in IPI cohort than in IPI+CT cohort (S5 Fig.).
5. Subgroup analysis based on ICI dose
The PMT-O and PMT-R were similar between the two different doses of IPI, except for those of endocrine events and PMT-O of neurologic events. Compared with NIV 1 mg/kg every 3 weeks and IPI 3 mg/kg every 3 weeks, significantly longer PMT-O of skin (5.1 weeks vs. 2.1 weeks, p < 0.001), hepatic (9.0 weeks vs. 6.0 weeks, p < 0.001), pulmonary (15.4 weeks vs. 10.1 weeks, p < 0.001), and renal events (15.7 weeks vs. 13.9 weeks, p=0.002) were observed in the treatment of NIV 3 mg/kg every 3 weeks and IPI 1 mg/kg every 3 weeks; the PMT-R was comparable between two doses of combination therapy in all events except for the gastrointestinal irAE (Table 2).
6. Subgroup analysis based on cancer type
The PMT-O of all-grade irAEs was significantly shorter in lung cancer cohort than in melanoma cohort (4.7 weeks vs. 6.1 weeks, p=0.017), including renal (8.2 weeks vs. 13.9 weeks, p=0.048), hypersensitivity/infusion reaction (0.2 weeks vs. 3.3 weeks, p=0.004), and neurologic (4.0 weeks vs. 13.1 weeks, p < 0.001) events (Table 3). Under the treatment of NIV 3 mg/kg every 2 weeks, two groups showed significantly different PMT-O of hepatic (lung cancer vs. melanoma: 8.0 weeks vs. 14.1 weeks, p < 0.001), hypersensitivity/infusion reaction (0.2 weeks vs. 3.3 weeks, p < 0.001), endocrine (11.2 weeks vs. 8.2 weeks, p=0.007), and pulmonary events (27.9 weeks vs. 8.7 weeks, p=0.001). The PMT-R of organ-specific irAEs were comparable between the two cancer types, except for that of skin events (S6 Table).
Currently, ICI is considered to be a promising treatment option for patients with cancer. However, the adverse events associated with immunologic etiology cannot be ignored. Although substantial evidence has demonstrated the safety profile of ICIs, most studies have focused on the incidence and certain kinds of ICI drugs, and the typical timing of the development of irAEs remains unclear [4246]. In this study, we aim to clarify the pattern of time to onset and resolution of ICI-induced irAEs in pan-cancers; therefore, it can provide clues for early recognition and timely management of irAEs to clinicians.
The premise of the successful management of irAEs and the reduction of sequelae is mastering the general pattern. In the previous studies of patients with melanoma receiving ICI monotherapy, it was reported that skin-related irAE was the earliest event to appear (median, 2–6 weeks), followed by gastrointestinal events (6–7 weeks), while renal events were the last to appear (15 weeks). Moreover, endocrine irAEs was the last (28 weeks) event to be resolved [3,16]. The pattern reported in our study was consistent with the above findings. Apart from the commonly selected irAEs in previous studies, we also included hypersensitivity/infusion reaction and neurological events in the analysis, and the former was newly found to be the first to resolve.
Severe irAEs were prone to occur later and be resolved with immune-modulation agents earlier than mild-to-moderate irAEs. On the one hand, this result may be due to the dose-dependent effect of irAEs. In a phase II trial comparing three dose administration of IPI (0.3 mg/kg, 3.0 mg/kg, and 10 mg/kg) in patients with advanced melanoma, the incidence of irAEs was 26%, 56%, and 70% and occurrence of grade 3–4 irAEs was 0%, 7%, and 25% of patients, respectively [47]. Similarly, a dose-based network meta-analysis suggested that high-dose IPI had a greater incidence of 3–4 grade irAEs than low-dose IPI [14]. Besides, in a phase I trial assessing the safety of anti–PD-1 antibody in patients with multiple cancer, an increase in the frequency of grade 3–4 irAE (0%, 4%, and 8%) was observed with an increasing dose level (0.3 mg/kg, 3.0 mg/kg, and 10 mg/kg, respectively) [48]. ICI drugs reach a higher cumulative dose in the later treatment course, therefore inducing late-onset severe irAEs. On the other hand, positive clinical management might foster the earlier resolution of severe irAEs. According to the NCCN and ESMO clinical practice guidelines for the management of immunotherapy-related toxicities, the common management would be observation and supportive treatment when initially encountered with grade 1–2 irAEs [12,13]. However, enhanced medical interventions and close nursing care will be adopted on the condition of dealing with severe irAEs. Given that ICI is a novel therapy with high hopes in the current spotlight, clinicians are more likely to find severe irAEs and perform timely resolutions.
The endocrine-related irAEs featured delayed onset (8.0–12.0 weeks), the longest resolution duration, and the lowest resolution rate in all ICI regimens. This result corroborates those from a study investigating IPI, where it took 9 weeks before the onset of endocrine events [16]. The underlying reason for the long time to recover from endocrine-related irAE was that it might take time for patients to become adequately replaced with the exogenous hormone. Thus, closer follow-up is needed approximately 9 weeks after the start of treatment, and patients should be provided with appropriate education regarding this prolonged treatment, including guidelines for psychological construction, medication norms, regular follow-up time, and adjustment of drug dose.
The irAEs caused by NIV+IPI generally occurred earlier than those induced by NIV alone. In a review, irAEs tended to occur earlier in the course of treatment with IPI plus an anti–PD-1 antibody compared with IPI monotherapy or anti–PD-1/(PD-L1) antibodies [15]. Similarly, a study of 1,551 patients assessed by the European Medicines Agency demonstrated that most of the irAEs occurred earlier in the NIV+IPI cohort than in the monotherapy cohort, including skin, gastrointestinal, hepatic, endocrine and renal events [49].
Although irAEs generally occurred within 14.8 weeks after the first dose of ICI drugs, they could appear several months even years after the completion of treatment. In this study, we noticed that the maximum time to onset could reach three years after starting treatment in some cases. The wide range in time of onset was also described in recent publications. The cutaneous presentation occurred in patients up to 60 weeks after the first dose of anti–PD-1 treatment in stage IV melanoma [50]. Ocular adverse effects were experienced by some patients with metastatic melanoma 1 year after the last dose of IPI [51]. Although the half-life of ICI is ascertained, such as two weeks for IPI, it may still have a biological effect for a long time after the drug is cleared [13,52]. Thus, surveillance should be reinforced and a long-term multidisciplinary follow-up should be arranged.
Several limitations should be mentioned. First, irAEs were diagnosed by investigators, which might be influenced by clinical experience. Indeed, the incidence of irAEs reported by randomized controlled trials published after 2017 seemed greater than those before (76.9% vs. 58.5%). It may be because more attention has been paid to these adverse events and more clinical experience has been gained. Hence, the quantifiable criteria to clarify the definition of irAE are eagerly awaited. Second, standard deviations or quartile information of timing data were not extracted and analyzed because they were rarely reported. Nevertheless, to make a reliable estimation, the metamedian method used in this study was proved to be well-performed under this circumstance by collecting median values [20]. Third, the dataset of the group receiving anti–PD-1/PD-L1 treatment mainly originated from the trials on NIV. Thus, the applicability of corresponding results may be more specific to NIV monotherapy and the clinical trials involving ICI agents are recommended to report the time data on the development of irAEs in the future. Fourth, the subgroup analysis of cancer types involved a small number of trials, so the relevant results should be regarded with caution.
The irAEs induced by ICI agents appear to be an emerging challenge in clinical practice. This study revealed the occurrence pattern of irAEs, expanding the knowledge of the characteristics of this new issue. Our findings may serve as a useful tool to help clinicians detect irAEs timely and make therapeutic decisions properly.
Supplementary materials are available at Cancer Research and Treatment website (https://www.e-crt.org).

Author Contributions

Conceived and designed the analysis: Tang SQ, Tang LL, Mao YP, Xu C, Ma J.

Collected the data: Tang SQ, Tang LL, Mao YP, Li WF, Chen L, Zhang Y, Guo Y.

Contributed data or analysis tools: Tang SQ, Tang LL, Mao YP, Li WF, Chen L.

Performed the analysis: Tang SQ, Tang LL, Mao YP, Zhang Y, Guo Y, Liu Q.

Wrote the paper: Tang SQ, Tang LL, Mao YP.

Review: Sun Y, Xu C, Ma J.

Conflicts of Interest

Conflict of interest relevant to this article was not reported.

Acknowledgements
This study was supported by the National Natural Science Foundation of China (81930072), Key-Area Research and Development Program of Guangdong Province (2019B020230002), Natural Science Foundation of Guangdong Province (2017A030312003), Health & Medical Collaborative Innovation Project of Guangzhou City, China (201803040003), Innovation Team Development Plan of the Ministry of Education (No. IRT_17R110), and Overseas Expertise Introduction Project for Discipline Innovation (111 Project, B14035).
Fig. 1
The pattern of time to onset of all-grade (A, C, E) and grade ≥ 3 (B, D, F) irAEs. Circles and bars represent median values and 95% confidence intervals, respectively. Number and percent of an event indicate the incidence of the irAE. CTLA-4, cytotoxic T-lymphocyte antigen 4; IPI, ipilimumab; irAEs, immune-related adverse events; NIV, nivolumab; PD-1/PD-L1, programmed cell death protein 1 or its ligand 1. a)p < 0.05 between the comparison of time to onset of all-grade irAEs and grade ≥ 3 irAEs. A total of 3,977 and 1,261 patients were included in the analysis of all-grade and grade ≥ 3 irAEs, respectively, for PD-1/PD-L1 inhibitors; 2,958 and 1,294 patients for CTLA-4 inhibitors; 828 and 867 patients for NIV+IPI.
crt-2020-790f1.jpg
Fig. 2
The pattern of resolution (A, B, E, F, I, J) and immune-modulation resolution (C, D, G, H, K, L) of all-grade (A, E, I, C, G, K) and grade ≥ 3 (B, F, J, D, H, L) irAEs. Circles and bars represent median values and 95% confidence intervals, respectively. Number and percent of an event indicate the patients whose irAE resolved (A, B, E, F, I, J) and patients whose irAE resolved with usage of immune-modulation agents (C, D, G, H, K, L). CTLA-4, cytotoxic T-lymphocyte antigen 4; IM, immune-modulation; IPI, ipilimumab; irAEs, immune-related adverse events; NIV, nivolumab; PD-1/PD-L1, programmed cell death protein 1 or its ligand 1. a)p < 0.05 between the comparison of time to resolution of all-grade and grade ≥ 3 irAEs, b)p < 0.05 between the comparison of time to immune-modulation resolution of all-grade and grade ≥ 3 irAEs, c)p < 0.05 between the comparison of time to resolution and immune-modulation resolution of all-grade, d)p < 0.05 between the comparison of time to resolution and immune-modulation resolution of grade ≥ 3 irAEs. A total of 1,196 and 192 patients were included in the analysis of time to resolution and immune-modulation resolution of all-grade irAEs, respectively, for PD-1/PD-L1 inhibitors; 2,611 and 402 patients for CTLA-4 inhibitors; 1,572 and 247 patients for NIV+IPI. A total of 71 and 37 patients were included in the analysis of time to resolution and immune-modulation resolution of grade ≥ 3 irAEs, respectively, for PD-1/PD-L1 inhibitors; 348 and 194 patients for CTLA-4 inhibitors; 254 and 117 patients for NIV+IPI.
crt-2020-790f2.jpg
Fig. 3
Kinetics (A–C) and ranking (D) of the onset and resolution of all-grade irAEs caused by nivolumab (A), IPI (B), and nivolumab plus IPI (C). The beginning and end of each curve in Fig. 3A–C represent the median time to the onset of an irAE and the median time to resolution, respectively; the peak and tail of each curve show the proportion of patients who developed an irAE and the proportion of patients whose irAE had not been resolved, respectively. The number in parentheses of Fig. 3D represents the pooled median time (weeks). The ranking is arranged from the shortest to the longest pooled median time. Items with underlining share the same ranking. IPI, ipilimumab; irAEs, immune-related adverse events; NA, not applicable; NIV, nivolumab. a)p < 0.05 between the comparison of NIV and NIV+IPI, b)p < 0.05 between the comparison of NIV and IPI, c)p < 0.05 between the comparison of IPI and NIV+IPI. A total of 1,815 and 1,196 patients were included in the analysis of time to onset and resolution, respectively, for NIV; 2,092 and 2,123 patients for IPI; 828 and 1,572 patients for NIV+IPI.
crt-2020-790f3.jpg
Table 1
Baseline characteristics of the included studies
Author, year Study ID Region Cancer Phase Total No. Safety analysis No. Arm Treatment Median follow-up time (mo) CTCAE version
Weber (2013) [21] MDX010-20 MN Melanoma III 676 403 1 IPI 3 mg/kg Q3W plus gp100 21.0 3.0
131 2 IPI 3 mg/kg Q3W 27.8
136 3 Gp 100 17.2
Kwon (2014) [22] CA184-043 MN Prostate cancer III 799 399 1 IPI 10 mg/kg Q3W plus bone-directed radiotherapy 9.9 3.0
400 2 Placebo plus bone-directed radiotherapy 9.3
Brahmer (2015) [3] CheckMate 017 MN Lung cancer III 272 131 1 NIV 3 mg/kg Q2W Min 11.0 4.0
129 2 DOC 75 mg/m2 Q3W Min 11.0
Borghaei (2015) [23] CheckMate 057 MN Lung cancer III 582 287 1 NIV 3 mg/kg Q2W Min 13.2 4.0
268 2 DOC 75 mg/m2 Q3W Min 13.2
Reck (2016) [25] CA184-156 MN Lung cancer III 954 478 1 IPI 10 mg/kg Q3W, ETO, and DDP or CBP 10.5 3.0
476 2 ETO and DDP or CBP 10.2
Eggermont (2016) [24] EORTC 18071 MN Melanoma III 951 471 1 IPI 10 mg/kg Q3W 63.6 3.0
476 2 Placebo Q3W 64.8
Weber (2017) [27] CheckMate 238 MN Melanoma III 905 452 1 NIV 3 mg/kg Q2W 19.5 4.0
453 2 IPI 10 mg/kg Q3W 19.5
Ascierto (2017) [26] CA184-169 MN Melanoma III 727 364 1 IPI 10 mg/kg Q3W 14.5 3.0
362 2 IPI 3 mg/kg Q3W 11.2
Larkin (2017) [28] CheckMate 037 MN Melanoma II 405 268 1 NIV 3 mg/kg Q2W 24.0 4.0
102 2 ICC (DTIC 1,000 mg/m2 Q3W or CBP AUC=6 and PTX 175 mg/m2 Q3W) 24.0
Govindan (2017) [29] CA184-104 MN Lung cancer III 749 388 1 IPI 10 mg/kg Q3W, PTX and CBP 12.5 3.0
361 2 PTX and CBP 11.8
Horn (2017) [30] CheckMate 017 MN Lung cancer III 854 418 1 NIV 3 mg/kg Q2W Min 24.0 4.0
CheckMate 057 MN Lung cancer III 397 2 DOC 75 mg/m2 Q3W Min 24.0
Armand (2018) [31] CheckMate 205 MN Hodgkin lymphoma II 243 243 1 NIV 3 mg/kg Q2W 18.0 4.0
Kelly (2018) [32] JAVELIN Solid Tumor MN Solid tumors Ia) 1,650 1,650 1 AVE 10 mg/kg Q2W Min 3.0 4.0
JAVELIN Merkel 200 MN Merkel cell carcinoma II 88 88 1 AVE 10 mg/kg Q2W Min 9.0 4.0
Larkin (2019) [34] CheckMate 067 MN Melanoma III 945 313 1 NIV 1 mg/kg plus IPI 3 mg/kg Q3W, followed by NIV 3 mg/kg Q2W Min 60.0 4.0
313 2 NIV 3 mg/kg Q2W 36.9
311 3 IPI 3 mg/kg Q3W 19.9
Geoerger (2019) [35] Keynote 051 MN Advanced pediatric cancer I–II 154 154 1 PEM 2 mg/kg Q3W 8.6 4.0
Fradet (2019) [33] Keynote 045 MN Urothelial carcinoma III 542 270 1 PEM 200 mg Q3W 27.7 4.0
272 2 PTX 175 mg/m2 Q3W, DOC 75 mg/m2 Q3W, or VIN 320 mg/m2 Q3W 27.7
Tomita (2020) [41] CheckMate 214 Japan Renal cell carcinoma III 72 38 1 NIV 3 mg/kg plus IPI 1 mg/kg Q3W, followed by NIV 3 mg/kg Q2W 32.4 4.0
34 2 SUN 50 mg QD for 4 weeks Q6W 32.4
Lebbe (2019) [38] CheckMate 511 MN Melanoma IIIB/IV 358 180 1 NIV 3 mg/kg plus IPI 1 mg/kg Q3W, followed by NIV 480 mg Q4W 18.8 4.0
178 2 NIV 1 mg/kg plus IPI 3 mg/kg Q3W, followed by NIV 480 mg Q4W 18.6
Sharma (2020) [40] CheckMate 032 MN Urothelial carcinoma I/II 274 78 1 NIV 3 mg/kg Q2W Min 37.7 4.0
104 2 NIV 3 mg/kg plus IPI 1 mg/kg Q3W, followed by NIV 3 mg/kg Q2W Min 38.8
92 3 NIV 1 mg/kg plus IPI 3 mg/kg Q3W, followed by NIV 3 mg/kg Q2W Min 7.9
Morse (2019) [39] CheckMate 142 MN Colorectal cancer II 119 119 1 NIV 3 mg/kg plus IPI 1 mg/kg Q3W, followed by NIV 3 mg/kg Q2W 13.4 4.0
Carneiro (2019) [36] NA MN Adrenocortical carcinoma II 10 10 1 NIV 240 mg Q2W 4.5 4.0
Horinouchi (2019) [37] ONO 4538 05 Japan Lung cancer II 35 35 1 NIV 3 mg/kg Q2W 36.0 4.0
ONO 4538 06 Japan Lung cancer II 76 76 1 NIV 3 mg/kg Q2W 36.0 4.0

AUC, area under the curve; AVE, avelumab; CBP, carboplatin; CTCAE, Common Terminology Criteria for Adverse Events; DDP, cisplatin; DOC, docetaxel; DTIC, dacarbazine; ETO, etoposide; ICC, investigator’s choice chemotherapy; IPI, ipilimumab; MN, multinational; NA, not available; NIV, nivolumab; PEM, pembrolizumab; PTX, paclitaxel; Q2W, every 2 weeks; Q3W, every 3 weeks; Q6W, every 6 weeks; SUN, sunitinib; VIN, vinflunine.

a) The study of Kelly et al. [32] reported pooled results of phase I and phase II clinical trials with a large sample size (n=1,738); thus, the phase I trial was also included in the analysis.

Table 2
Time to onset and resolution of all-grade irAEs based on ICI doses
IPI-3 IPI-10 NIV-1+IPI-3 NIV-3+IPI-1
All categories
 No. of patients with irAE 606 (13.5) 1,565 (20.3) 921 (29.9) 402 (19.9)
  Time to onset (wk) 5.1 (3.6–7.1) 6.3 (4.1–8.9) 4.9 (2.4–6.1) 6.1 (5.2–9.0)
 No. of patients with irAE 495 (87.3) 1,252 (85.2) 663 (79.0) 607 (82.8)
  Time to resolution (wk) 3.6 (2.9–11.0) 4.4 (3.1–7.0) 5.1 (2.9–10.9) 5.0 (1.8–6.3)
Skin
 No. of patients with irAE 218 (32.4) 460 (35.7) 288 (58.7) 135 (40.1)
  Time to onset (wk) 3.6 (3.6–5.1) 2.6 (2.6–4.1) 2.1 (2.1–2.4)a) 5.1 (3.1–5.2)a)
 No. of patients with resolution 179 (82.1) 377 (82.0) 193 (67.2) 100 (70.9)
  Time to resolution (wk) 11 (5.1–11.0) 9.3 (3.1–9.3) 10.9 (10.9–24.1) 9.0 (9.0–13.1)
Gastrointestinal
 No. of patients with irAE 231 (34.3) 567 (44.0) 207 (42.2) 84 (24.9)
  Time to onset (wk) 7.1 (4.6–7.6) 6.3 (4.4–7.6) 4.9 (3.9–4.9) 6.1 (3.6–9.1)
 No. of patients with resolution 218 (94.8) 539 (95.1) 197 (95.6) 170 (96.6)
  Time to resolution (wk) 2.9 (2.9–3.6) 3.1 (2.1–4.0) 2.9 (2.9–3.0)a) 1.5 (1.5–2.7)a)
Hepatic
 No. of patients with irAE 32 (4.8) 223 (17.3) 163 (33.2) 58 (17.2)
  Time to onset (wk) 8.9 (6.1–9.0) 8.9 (8.1–8.9) 6.0 (6.0–6.1)a) 9.0 (7.0–10.0)a)
 No. of patients with resolution 30 (93.8) 205 (91.9) 148 (90.8) 117 (76.0)
  Time to resolution (wk) 4.1 (2.9–4.1) 4.4 (4.4–7.0) 5.1 (5.1–6.1) 5.0 (2.0–8.2)
Endocrine
 No. of patients with irAE 57 (8.5) 269 (20.9) 192 (39.1) 89 (26.4)
  Time to onset (wk) 9.1 (8.9–9.1)b) 10.2 (8.9–10.2)b) 8.0 (6.0–8.0) 6.1 (6.1–12.0)
 No. of patients with resolution 14 (70.0) 93 (53.8) 57 (53.3) -
  Time to resolution (wk) 3.4 (3.4–3.4)b) 54.3 (13.9–54.3)b) 27.6 (27.6–27.6) NA
Pulmonary
 No. of patients with irAE 6 (1.9) 11 (2.4) 25 (8.0) 22 (6.5)
  Time to onset (wk) 10.1 (10.1–10.1) 10.0 (10.0–10.0) 10.1 (10.1–10.1)a) 15.4 (10.5–16.6)a)
 No. of patients with resolution 5 (83.3) 11 (100) 29 (96.7) 114 (84.4)
  Time to resolution (wk) 6.3 (6.3–6.3) 3.7 (3.7–3.7) 7.0 (3.0–7.0) 4.5 (2.8–14.6)
Renal
 No. of patients with irAE 8 (2.6) 7 (1.5) 32 (6.5) 14 (4.2)
  Time to onset (wk) 10.0 (10.0–10.0) 9.7 (9.7–9.7) 13.9 (8.7–13.9)a) 15.7 (12.6–36.4)a)
 No. of patients with resolution 7 (87.5) 4 (57.1) 27 (84.4) 106 (83.5)
  Time to resolution (wk) 2.5 (2.5–2.5) 52.7 (52.7–52.7) 2.1 (1.3–2.1) 6.3 (1.6–6.9)
Hypersensitivity/Infusion reaction
 No. of patients with irAE 8 (2.6) 9 (2.0) 14 (4.5) -
  Time to onset (wk) 4.3 (4.3–4.3) 6.1 (6.1–6.1) 3.1 (3.1–3.1) NA
 No. of patients with resolution 8 (100) 9 (100) 12 (85.7) -
  Time to resolution (wk) 0.1 (0.1–0.1) 0.1 (0.1–0.1) 0.2 (0.2–0.2) NA
Neurologic
 No. of patients with irAE 1 (0.3) 19 (2.3) - -
  Time to onset (wk) 11.7 (11.7–11.7)b) 13.1 (10.4–13.1)b) NA NA
 No. of patients with resolution 1 (100) 14 (73.7) - -
  Time to resolution (wk) 0.7 (0.7–0.7) 8.0 (8.0–11.6) NA NA

Values are presented as number (%) or median (95% confidence interval). ICI, immune checkpoint inhibitor; IPI-1, ipilimumab 1 mg/kg Q3W; IPI-3, ipilimumab 3 mg/kg Q3W; IPI-10, ipilimumab 10 mg/kg Q3W; irAE, immune-related adverse event; NA, not available; NIV-1, nivolumab 1 mg/kg Q3W; NIV-3, nivolumab 3 mg/kg Q3W.

a) p < 0.05 between the comparison of NIV1+IPI3 and NIV3+IPI1,

b) p < 0.05 between the comparison of IPI3 and IPI10.

Table 3
Time to onset and resolution of all-grade immune-related adverse events based on cancer types
Lung cancer Melanoma
All categories
 No. of patients with irAE 800 (10.0) 4,359 (18.3)
  Time to onset (wk) 4.7 (4.7–5.7)a) 6.1 (5.7–7.6)a)
 No. of patients with irAE 502 (76.9) 3,222 (80.5)
  Time to resolution (wk) 4.0 (2.7–9.4) 4.4 (3.4–6.9)
Skin
 No. of patients with irAE 270 (19.4) 1,496 (40.8)
  Time to onset (wk) 4.7 (2.9–5.7) 4.0 (2.6–5.7)
 No. of patients with resolution 178 (76.7) 1,026 (72.6)
  Time to resolution (wk) 9.4 (4.3–10.1) 10.9 (5.1–22.1)
Gastrointestinal
 No. of patients with irAE 226 (16.2) 1,294 (35.3)
  Time to onset (wk) 4.5 (4.4–22.4) 6.3 (4.6–7.6)
 No. of patients with resolution 186 (86.5) 1,217 (94.3)
  Time to resolution (wk) 2.7 (2.3–2.9) 2.9 (2.4–3.1)
Hepatic
 No. of patients with irAE 74 (5.3) 542 (14.8)
  Time to onset (wk) 8.0 (2.0–9.0) 8.9 (6.1–9.0)
 No. of patients with resolution 56 (83.6) 491 (90.6)
  Time to resolution (wk) 3.3 (2.0–4.0)a) 5.1 (4.4–6.1)a)
Endocrine
 No. of patients with irAE 107 (7.7) 749 (20.4)
  Time to onset (wk) 11.2 (8.9–13.3) 8.9 (8.0–10.2)
 No. of patients with resolution 18 (52.9) 258 (53.6)
  Time to resolution (wk) 10.4 (10.4–10.4) 29.1 (13.9–54.3)
Pulmonary
 No. of patients with irAE 25 (4.7) 77 (3.1)
  Time to onset (wk) 27.9 (4.8–27.9)a) 10.1 (8.7–10.1)a)
 No. of patients with resolution 16 (84.2) 69 (89.6)
  Time to resolution (wk) 5.9 (5.9–5.9) 6.3 (3.0–7.0)
Renal
 No. of patients with irAE 17 (3.2) 70 (2.8)
  Time to onset (wk) 8.2 (8.2–17.8)a) 13.9 (9.7–15.7)a)
 No. of patients with resolution 6 (54.5) 54 (77.1)
  Time to resolution (wk) 10.5 (10.5–10.5)a) 2.3 (2.1–10.5)a)
Hypersensitivity/Infusion reaction
 No. of patients with irAE 16 (3.0) 66 (3.1)
  Time to onset (wk) 0.2 (0.2–1.8)a) 3.3 (2.2–6.1)a)
 No. of patients with resolution 10 (100) 59 (89.4)
  Time to resolution (wk) 0.1 (0.1–0.1) 0.1 (0.1–0.2)
Neurologic
 No. of patients with irAE 65 (7.5) 20 (1.7)
  Time to onset (wk) 4.0 (4.0–7.1)a) 13.1 (10.4–13.1)a)
 No. of patients with resolution 32 (49.2) 15 (75.0)
  Time to resolution (wk) 28.7 (28.7–28.9)a) 8.0 (0.7–11.6)a)

Values are presented as number (%) or median (95% confidence interval). irAE, immune-related adverse event.

a) p < 0.05 between the comparison of lung cancer and melanoma.

  • 1. Jain A, Zhang Q, Toh HC. Awakening immunity against cancer: a 2017 primer for clinicians. Chin J Cancer. 2017;36:67.ArticlePubMedPMC
  • 2. Hodi FS, O’Day SJ, McDermott DF, Weber RW, Sosman JA, Haanen JB, et al. Improved survival with ipilimumab in patients with metastatic melanoma. N Engl J Med. 2010;363:711–23. ArticlePubMedPMC
  • 3. Brahmer J, Reckamp KL, Baas P, Crino L, Eberhardt WE, Poddubskaya E, et al. Nivolumab versus docetaxel in advanced squamous-cell non-small-cell lung cancer. N Engl J Med. 2015;373:123–35. ArticlePubMedPMC
  • 4. McDermott DF, Drake CG, Sznol M, Choueiri TK, Powderly JD, Smith DC, et al. Survival, durable response, and long-term safety in patients with previously treated advanced renal cell carcinoma receiving nivolumab. J Clin Oncol. 2015;33:2013–20. ArticlePubMedPMC
  • 5. Lim SM, Kim SW, Cho BC, Kang JH, Ahn MJ, Kim DW, et al. Real-world experience of nivolumab in non-small cell lung cancer in Korea. Cancer Res Treat. 2020;52:1112–9. ArticlePubMedPMC
  • 6. Weber JS, Hodi FS, Wolchok JD, Topalian SL, Schadendorf D, Larkin J, et al. Safety profile of nivolumab monotherapy: a pooled analysis of patients with advanced melanoma. J Clin Oncol. 2017;35:785–92. ArticlePubMed
  • 7. Weber JS, Yang JC, Atkins MB, Disis ML. Toxicities of immunotherapy for the practitioner. J Clin Oncol. 2015;33:2092–9. ArticlePubMedPMC
  • 8. Johnson DB, Saranga-Perry V, Lavin PJ, Burnette WB, Clark SW, Uskavitch DR, et al. Myasthenia gravis induced by ipilimumab in patients with metastatic melanoma. J Clin Oncol. 2015;33:e122–4. ArticlePubMedPMC
  • 9. Liao B, Shroff S, Kamiya-Matsuoka C, Tummala S. Atypical neurological complications of ipilimumab therapy in patients with metastatic melanoma. Neuro Oncol. 2014;16:589–93. ArticlePubMedPMC
  • 10. Moslehi JJ, Salem JE, Sosman JA, Lebrun-Vignes B, Johnson DB. Increased reporting of fatal immune checkpoint inhibitor-associated myocarditis. Lancet. 2018;391:933.ArticlePMC
  • 11. Salem JE, Manouchehri A, Moey M, Lebrun-Vignes B, Bastarache L, Pariente A, et al. Cardiovascular toxicities associated with immune checkpoint inhibitors: an observational, retrospective, pharmacovigilance study. Lancet Oncol. 2018;19:1579–89. ArticlePubMedPMC
  • 12. National Comprehensive Cancer NetworkNCCN Clinical Practice Guidelines in Oncology, version 1 [Internet]. Plymouth Meeting, PA: National Comprehensive Cancer Network; 2020. [cited 2020 Aug 8]. Available from: https://www.nccn.org/professionals/physician_gls/default.aspx
  • 13. Haanen J, Carbonnel F, Robert C, Kerr KM, Peters S, Larkin J, et al. Management of toxicities from immunotherapy: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up. Ann Oncol. 2017;28:iv119–42. ArticlePubMed
  • 14. Xu C, Chen YP, Du XJ, Liu JQ, Huang CL, Chen L, et al. Com- parative safety of immune checkpoint inhibitors in cancer: systematic review and network meta-analysis. BMJ. 2018;363:k4226.ArticlePubMedPMC
  • 15. Martins F, Sofiya L, Sykiotis GP, Lamine F, Maillard M, Fraga M, et al. Adverse effects of immune-checkpoint inhibitors: epidemiology, management and surveillance. Nat Rev Clin Oncol. 2019;16:563–80. ArticlePubMed
  • 16. Weber JS, Kahler KC, Hauschild A. Management of immune-related adverse events and kinetics of response with ipilimumab. J Clin Oncol. 2012;30:2691–7. ArticlePubMed
  • 17. Common Terminology Criteria for Adverse Events version 50 [Internet]. Washington, DC: U.S. Department of Health and Human Services; 2017. [cited 2020 Nov 5]. Available from: https://www.eortc.be/services/doc/ctc/CTCAE_v5_Quick_Reference_5x7.pdf
  • 18. Cumpston M, Li T, Page MJ, Chandler J, Welch VA, Higgins JP, et al. Updated guidance for trusted systematic reviews: a new edition of the Cochrane Handbook for Systematic Reviews of Interventions. Cochrane Database Syst Rev. 2019;10:ED000142.ArticlePubMed
  • 19. Jadad AR, Moore RA, Carroll D, Jenkinson C, Reynolds DJ, Gavaghan DJ, et al. Assessing the quality of reports of randomized clinical trials: is blinding necessary? Control Clin Trials. 1996;17:1–12. ArticlePubMed
  • 20. McGrath S, Zhao X, Qin ZZ, Steele R, Benedetti A. One-sample aggregate data meta-analysis of medians. Stat Med. 2019;38:969–84. ArticlePubMed
  • 21. Weber JS, Dummer R, de Pril V, Lebbe C, Hodi FS; MDX010-20 Investigators. Patterns of onset and resolution of immune-related adverse events of special interest with ipilimumab: detailed safety analysis from a phase 3 trial in patients with advanced melanoma. Cancer. 2013;119:1675–82. ArticlePubMed
  • 22. Kwon ED, Drake CG, Scher HI, Fizazi K, Bossi A, van den Eertwegh AJ, et al. Ipilimumab versus placebo after radiotherapy in patients with metastatic castration-resistant prostate cancer that had progressed after docetaxel chemotherapy (CA184-043): a multicentre, randomised, double-blind, phase 3 trial. Lancet Oncol. 2014;15:700–12. ArticlePubMedPMC
  • 23. Borghaei H, Paz-Ares L, Horn L, Spigel DR, Steins M, Ready NE, et al. Nivolumab versus docetaxel in advanced nonsquamous non-small-cell lung cancer. N Engl J Med. 2015;373:1627–39. ArticlePubMedPMC
  • 24. Eggermont AM, Chiarion-Sileni V, Grob JJ, Dummer R, Wolchok JD, Schmidt H, et al. Prolonged survival in stage III melanoma with ipilimumab adjuvant therapy. N Engl J Med. 2016;375:1845–55. ArticlePubMedPMC
  • 25. Reck M, Luft A, Szczesna A, Havel L, Kim SW, Akerley W, et al. Phase III randomized trial of ipilimumab plus etoposide and platinum versus placebo plus etoposide and platinum in extensive-stage small-cell lung cancer. J Clin Oncol. 2016;34:3740–8. ArticlePubMed
  • 26. Ascierto PA, Del Vecchio M, Robert C, Mackiewicz A, Chiarion-Sileni V, Arance A, et al. Ipilimumab 10 mg/kg versus ipilimumab 3 mg/kg in patients with unresectable or metastatic melanoma: a randomised, double-blind, multicentre, phase 3 trial. Lancet Oncol. 2017;18:611–22. ArticlePubMed
  • 27. Weber J, Mandala M, Del Vecchio M, Gogas HJ, Arance AM, Cowey CL, et al. Adjuvant nivolumab versus ipilimumab in resected stage III or IV melanoma. N Engl J Med. 2017;377:1824–35. ArticlePubMed
  • 28. Larkin J, Minor D, D’Angelo S, Neyns B, Smylie M, Miller WH Jr, et al. Overall survival in patients with advanced melanoma who received nivolumab versus investigator’s choice chemotherapy in CheckMate 037: a randomized, controlled, open-label phase III trial. J Clin Oncol. 2018;36:383–90. ArticlePubMed
  • 29. Govindan R, Szczesna A, Ahn MJ, Schneider CP, Gonzalez Mella PF, Barlesi F, et al. Phase III trial of ipilimumab combined with paclitaxel and carboplatin in advanced squamous non-small-cell lung cancer. J Clin Oncol. 2017;35:3449–57. ArticlePubMed
  • 30. Horn L, Spigel DR, Vokes EE, Holgado E, Ready N, Steins M, et al. Nivolumab versus docetaxel in previously treated patients with advanced non-small-cell lung cancer: two-year outcomes from two randomized, open-label, phase III trials (CheckMate 017 and CheckMate 057). J Clin Oncol. 2017;35:3924–33. ArticlePubMedPMC
  • 31. Armand P, Engert A, Younes A, Fanale M, Santoro A, Zinzani PL, et al. Nivolumab for relapsed/refractory classic Hodgkin lymphoma after failure of autologous hematopoietic cell transplantation: extended follow-up of the multicohort single-arm phase II CheckMate 205 trial. J Clin Oncol. 2018;36:1428–39. ArticlePubMedPMC
  • 32. Kelly K, Infante JR, Taylor MH, Patel MR, Wong DJ, Iannotti N, et al. Safety profile of avelumab in patients with advanced solid tumors: a pooled analysis of data from the phase 1 JAVELIN solid tumor and phase 2 JAVELIN Merkel 200 clinical trials. Cancer. 2018;124:2010–7. ArticlePubMedPMC
  • 33. Fradet Y, Bellmunt J, Vaughn DJ, Lee JL, Fong L, Vogelzang NJ, et al. Randomized phase III KEYNOTE-045 trial of pembrolizumab versus paclitaxel, docetaxel, or vinflunine in recurrent advanced urothelial cancer: results of >2 years of follow-up. Ann Oncol. 2019;30:970–6. ArticlePubMedPMCPDF
  • 34. Larkin J, Chiarion-Sileni V, Gonzalez R, Grob JJ, Rutkowski P, Lao CD, et al. Five-year survival with combined nivolumab and ipilimumab in advanced melanoma. N Engl J Med. 2019;381:1535–46. ArticlePubMed
  • 35. Geoerger B, Kang HJ, Yalon-Oren M, Marshall LV, Vezina C, Pappo A, et al. Pembrolizumab in paediatric patients with advanced melanoma or a PD-L1-positive, advanced, relapsed, or refractory solid tumour or lymphoma (KEYNOTE-051): interim analysis of an open-label, single-arm, phase 1–2 trial. Lancet Oncol. 2020;21:121–33. ArticlePubMed
  • 36. Carneiro BA, Konda B, Costa RB, Costa RL, Sagar V, Gursel DB, et al. Nivolumab in metastatic adrenocortical carcinoma: results of a phase 2 trial. J Clin Endocrinol Metab. 2019;104:6193–200. ArticlePubMed
  • 37. Horinouchi H, Nishio M, Hida T, Nakagawa K, Sakai H, Nogami N, et al. Three-year follow-up results from phase II studies of nivolumab in Japanese patients with previously treated advanced non-small cell lung cancer: pooled analysis of ONO-4538-05 and ONO-4538-06 studies. Cancer Med. 2019;8:5183–93. ArticlePubMedPMC
  • 38. Lebbe C, Meyer N, Mortier L, Marquez-Rodas I, Robert C, Rutkowski P, et al. Evaluation of two dosing regimens for nivolumab in combination with ipilimumab in patients with advanced melanoma: results from the phase IIIb/IV CheckMate 511 trial. J Clin Oncol. 2019;37:867–75. ArticlePubMedPMC
  • 39. Morse MA, Overman MJ, Hartman L, Khoukaz T, Brutcher E, Lenz HJ, et al. Safety of nivolumab plus low-dose ipilimumab in previously treated microsatellite instability-high/mismatch repair-deficient metastatic colorectal cancer. Oncologist. 2019;24:1453–61. ArticlePubMedPMC
  • 40. Sharma P, Sohn J, Shin SJ, Oh DY, Keam B, Lee HJ, et al. Efficacy and tolerability of tremelimumab in locally advanced or metastatic urothelial carcinoma patients who have failed first-line platinum-based chemotherapy. Clin Cancer Res. 2020;26:61–70. ArticlePubMed
  • 41. Tomita Y, Kondo T, Kimura G, Inoue T, Wakumoto Y, Yao M, et al. Nivolumab plus ipilimumab versus sunitinib in previously untreated advanced renal-cell carcinoma: analysis of Japanese patients in CheckMate 214 with extended follow-up. Jpn J Clin Oncol. 2020;50:12–9. ArticlePubMed
  • 42. De Velasco G, Je Y, Bosse D, Awad MM, Ott PA, Moreira RB, et al. Comprehensive meta-analysis of key immune-related adverse events from CTLA-4 and PD-1/PD-L1 inhibitors in cancer patients. Cancer Immunol Res. 2017;5:312–8. ArticlePubMedPMC
  • 43. Minkis K, Garden BC, Wu S, Pulitzer MP, Lacouture ME. The risk of rash associated with ipilimumab in patients with cancer: a systematic review of the literature and meta-analysis. J Am Acad Dermatol. 2013;69:e121–8. ArticlePubMed
  • 44. Tarhini A. Immune-mediated adverse events associated with ipilimumab CTLA-4 blockade therapy: the underlying mechanisms and clinical management. Scientifica (Cairo). 2013;2013:857519Article
  • 45. Baxi S, Yang A, Gennarelli RL, Khan N, Wang Z, Boyce L, et al. Immune-related adverse events for anti-PD-1 and anti-PD-L1 drugs: systematic review and meta-analysis. BMJ. 2018;360:k793.ArticlePubMedPMC
  • 46. Almutairi AR, McBride A, Slack M, Erstad BL, Abraham I. Potential immune-related adverse events associated with monotherapy and combination therapy of ipilimumab, nivolumab, and pembrolizumab for advanced melanoma: a systematic review and meta-analysis. Front Oncol. 2020;10:91.ArticlePubMedPMC
  • 47. Wolchok JD, Neyns B, Linette G, Negrier S, Lutzky J, Thomas L, et al. Ipilimumab monotherapy in patients with pretreated advanced melanoma: a randomised, double-blind, multicentre, phase 2, dose-ranging study. Lancet Oncol. 2010;11:155–64. ArticlePubMed
  • 48. Topalian SL, Hodi FS, Brahmer JR, Gettinger SN, Smith DC, McDermott DF, et al. Safety, activity, and immune correlates of anti-PD-1 antibody in cancer. N Engl J Med. 2012;366:2443–54. ArticlePubMedPMC
  • 49. Hassel JC, Heinzerling L, Aberle J, Bahr O, Eigentler TK, Grimm MO, et al. Combined immune checkpoint blockade (anti-PD-1/anti-CTLA-4): evaluation and management of adverse drug reactions. Cancer Treat Rev. 2017;57:36–49. ArticlePubMed
  • 50. Goldinger SM, Stieger P, Meier B, Micaletto S, Contassot E, French LE, et al. Cytotoxic cutaneous adverse drug reactions during anti-PD-1 therapy. Clin Cancer Res. 2016;22:4023–9. ArticlePubMed
  • 51. Kahler KC, Hassel JC, Heinzerling L, Loquai C, Mossner R, Ugurel S, et al. Management of side effects of immune checkpoint blockade by anti-CTLA-4 and anti-PD-1 antibodies in metastatic melanoma. J Dtsch Dermatol Ges. 2016;14:662–81. Article
  • 52. Freeman-Keller M, Weber JS. Anti-programmed death receptor 1 immunotherapy in melanoma: rationale, evidence and clinical potential. Ther Adv Med Oncol. 2015;7:12–21. ArticlePubMedPMC

Figure & Data

REFERENCES

    Citations

    Citations to this article as recorded by  
    • Oral and cutaneous immune‐related adverse events in cancer patients: Prevalence and overall survival
      Osias Vieira de Oliveira Filho, Ivana Lameiras Gibbons, Yuri de Lima Medeiros, Thiago Bueno de Oliveira, Nathaniel Simon Treister, Fabio Abreu Alves
      Oral Diseases.2025; 31(1): 278.     CrossRef
    • Clinical Outcomes of Elective Early Discontinuation of Immunotherapy Based on Objective Response in Microsatellite Instability-High Metastatic Colorectal Cancer
      Annie Xiao, Xiaochen Li, Chongkai Wang, Marwan Fakih
      Clinical Colorectal Cancer.2025; 24(1): 32.     CrossRef
    • Association between immune checkpoint inhibitor and cytomegalovirus infection: A pharmacovigilance study based on the adverse event reporting system
      Naoto Okada, Tomoyuki Yanagi, Takaaki Sasaki, Miho Tamura, Masakazu Ozaki, Atsuyuki Saisyo, Takashi Kitahara
      International Journal of Cancer.2025; 156(2): 293.     CrossRef
    • A Case of Olmesartan-associated Gastritis Observed Over Time
      Mizuho Fujisawa, Tetsuya Yoshizaki, Satoshi Urakami, Risa Ashizaki, Eri Nishikawa, Hiroshi Tanabe, Shinya Hoki, Ryosuke Ishida, Hitomi Hori, Chise Ueda, Hirofumi Abe, Madoka Takao, Yoshinori Morita, Takashi Toyonaga, Yuzo Kodama
      Internal Medicine.2025;[Epub]     CrossRef
    • The use of peripheral blood biomarkers for predicting the risk of immune-related adverse events in immune checkpoint inhibitor therapy
      Louise E Duvall
      Annals of Clinical Biochemistry: International Journal of Laboratory Medicine.2025;[Epub]     CrossRef
    • Developing alert thresholds and self-management advice for people receiving immune checkpoint inhibitors: a Multinational Association for Supportive Care in Cancer modified Delphi survey
      Julia Lai-Kwon, Claudia Rutherford, Stephanie Best, Hope S. Rugo, Christina H. Ruhlmann, Michael Jefford
      Supportive Care in Cancer.2025;[Epub]     CrossRef
    • Very Early Health Technology Assessment for Potential Predictive Biomarkers in the Treatment of Advanced Non-Small Cell Lung Cancer
      Leila-Sophie Otten, Alessandra I. G. Buma, Berber Piet, Rob ter Heine, Michel M. van den Heuvel, Valesca P. Retèl
      PharmacoEconomics - Open.2025;[Epub]     CrossRef
    • Clinical and economic impact of the advanced practice nurse in lung cancer patients receiving immunotherapy-based treatments: A quantitative study
      Jorgina Serra-López, Clara Pujol-Besora, Sergio Martínez-Recio, Andrés Barba Joaquín, Mariona Riudavets Melià, Ivana Sullivan, Jordi Torralbas-Ortega, Gina Lladó-Jordan, Margarita Majem, Maria-Antonia Martínez-Momblan
      European Journal of Oncology Nursing.2025; 74: 102809.     CrossRef
    • Long-term immune related adverse events
      Leo Plaçais, Olivier Lambotte
      Current Opinion in Oncology.2025; 37(2): 142.     CrossRef
    • Characterization of Hospital Admissions During Immune Checkpoint Inhibitor Therapy: Insights From the ICOG Study
      Jonas Paul Wiegmann, Tabea Fröhlich, Nora Möhn, Laura Duzzi, Emily Narten, Johanna Aurich, Janin Thomas, Lea Grote‐Levi, Susann Mahjoub, Dominik Berliner, Thomas Wirth, Heiko Golpon, Benjamin‐Alexander Bollmann, Imke Von Wasilewski, Ralf Gutzmer, Florian
      Cancer Medicine.2025;[Epub]     CrossRef
    • Application of Immune Checkpoint Inhibitors in the Treatment of Renal Cell Carcinoma: Current Status, Challenges, and Future Directions
      Lingxiang Ran, Rui Zhao, Yu Li, Benfan Lin, Zhen Yang, Yuanyin Teng, Jingyi Li, Shi Wang, Hsu Yi Liang, Guangmo Hu
      AI Med.2025; 1(1): 1.     CrossRef
    • Immune-related adverse events with PD-1/PD-L1 inhibitors: insights from a real-world cohort of 2523 patients
      Ting Yan, Minghui Long, Chaoyi Liu, Jiwen Zhang, Xingyu Wei, Fei Li, Dehua Liao
      Frontiers in Pharmacology.2025;[Epub]     CrossRef
    • Challenges and opportunities in single-domain antibody-based tumor immunotherapy
      Xiaozhi Xi, Shasha Guo, Yuchao Gu, Xuekai Wang, Qiang Wang
      Biochimica et Biophysica Acta (BBA) - Reviews on Cancer.2025; 1880(2): 189284.     CrossRef
    • Predictors of severity and onset timing of immune-related adverse events in cancer patients receiving immune checkpoint inhibitors: a retrospective analysis
      Qimei Fang, Yan Qian, Zhaolu Xie, Hongqiong Zhao, Yang Zheng, Di Li
      Frontiers in Immunology.2025;[Epub]     CrossRef
    • Clinical Characteristics of Toxicities of Immune Checkpoint Inhibitors and Their Impact on Efficacy in Solid Cancers: An Analysis of Real-World Data in Moroccan Patients
      Badiaa Batlamous, Sihame Lkhoyaali, Loubna Omri, Magaly-Gwen-Farnely Nguema-Mipaka, Mohamed Khalis, Hanane Inrhaoun, Sarah Naciri, Ibrahim El Ghissassi, Hind Mrabti, Saber Boutayeb, Hassan Errihani
      JCO Global Oncology.2025;[Epub]     CrossRef
    • Late-onset bone granulomatous reaction of hand from immune checkpoint-inhibitors detected on FDG-PET/CT
      Miki Nishimori, Kouki Togami, Noriko Nitta, Kana Miyatake, Hitomi Iwasa, Kosuke Nakaji, Kenta Ogi, Takayasu Izumi, Tomohiro Matsumoto, Rika Yoshimatsu, Tomoaki Yamanishi, Kazufumi Takamatsu, Shudai Muramatsu, Mayuko Yamamoto, Takuji Yamagami
      Radiology Case Reports.2025; 20(5): 2338.     CrossRef
    • Immune checkpoint inhibitor–related adverse events: Real-world experience from a single veterans’ affairs medical center
      Samantha Benz, Katherine A Sherman, Constantin A Dasanu, Juliana Alvarez-Argote
      Journal of Oncology Pharmacy Practice.2024; 30(4): 697.     CrossRef
    • Assessment of Variables Related to the Risk of Severe Adverse Events in Cutaneous Melanoma Patients Treated with Immune Checkpoint Inhibitors
      Kremena Petrova Trichkova, Franziska Görtler, Line Bjørge, Cornelia Schuster
      Cancers.2024; 16(2): 250.     CrossRef
    • Management of liver and gastrointestinal toxicity induced by immune checkpoint inhibitors: Position statement of the AEEH–AEG–SEPD–SEOM–GETECCU
      Mar Riveiro-Barciela, Sabela Carballal, Álvaro Díaz-González, Míriam Mañosa, Javier Gallego-Plazas, Joaquín Cubiella, Paula Jiménez-Fonseca, María Varela, Luis Menchén, Bruno Sangro, Ana Fernández-Montes, Francisco Mesonero, Miguel Ángel Rodríguez-Gandía,
      Gastroenterología y Hepatología.2024; 47(4): 401.     CrossRef
    • Management of liver and gastrointestinal toxicity induced by immune checkpoint inhibitors: Position statement of the AEEH-AEG-SEPD-SEOM-GETECCU
      Mar Riveiro-Barciela, Sabela carballal, Álvaro Díaz-González, Miriam Mañosa, Javier Gallgo-Plazas, Joaquín Cubiella, Paula Jiménez-Fonseca, María Varela, Luis Menchén, Bruno Sangro, Ana Fernández-Montes, Francisco Mesonero, Miguel Ángel Rodríguez-Gandí
      Revista Española de Enfermedades Digestivas.2024;[Epub]     CrossRef
    • Discontinuation risk from adverse events: immunotherapy alone vs. combined with chemotherapy: a systematic review and network meta-analysis
      Sangwon Shin, Jimin Moon, Chiyoon Oum, Seulki Kim, Soo Ick Cho, Yoojoo Lim, Chan-Young Ock, Seunghwan Shin
      BMC Cancer.2024;[Epub]     CrossRef
    • A case of Stiff-person syndrome with muscle tonicity of the extremities and neck after use of Dulvalumab for lung adenocarcinoma
      Takashi Inoue, Kei Oiwa, Kazuhiro Horiuchi
      Rinsho Shinkeigaku.2024; 64(3): 176.     CrossRef
    • Clinical and translational attributes of immune-related adverse events
      Karijn P. M. Suijkerbuijk, Mick J. M. van Eijs, Femke van Wijk, Alexander M. M. Eggermont
      Nature Cancer.2024; 5(4): 557.     CrossRef
    • Immune checkpoint inhibitors and neurotoxicity: a focus on diagnosis and management for a multidisciplinary approach
      Desirèe Speranza, Mariacarmela Santarpia, Francesco Luppino, Fausto Omero, Enrica Maiorana, Mariacarmela Cavaleri, Elena Sapuppo, Vincenzo Cianci, Alessia Pugliese, Vito Racanelli, Giulia Maria Camerino, Carmelo Rodolico, Nicola Silvestris
      Expert Opinion on Drug Safety.2024; 23(11): 1405.     CrossRef
    • Immune-Related Colitis Is Associated with Fecal Microbial Dysbiosis and Can Be Mitigated by Fecal Microbiota Transplantation
      Arielle Elkrief, Nicholas R. Waters, Natalie Smith, Angel Dai, John Slingerland, Nathan Aleynick, Binita Febles, Pooja Gogia, Nicholas D. Socci, Melissa Lumish, Paul A. Giardina, Jamie E. Chaft, Juliana Eng, Robert J. Motzer, Robin B. Mendelsohn, Kate A.
      Cancer Immunology Research.2024; 12(3): 308.     CrossRef
    • Management of liver and gastrointestinal toxicity induced by immune checkpoint inhibitors: Position statement of the AEEH–AEG–SEPD–SEOM–GETECCU
      Mar Riveiro-Barciela, Sabela Carballal, Álvaro Díaz-González, Míriam Mañosa, Javier Gallego-Plazas, Joaquín Cubiella, Paula Jiménez-Fonseca, María Varela, Luis Menchén, Bruno Sangro, Ana Fernández-Montes, Francisco Mesonero, Miguel Ángel Rodríguez-Gandía,
      Gastroenterología y Hepatología (English Edition).2024; 47(4): 401.     CrossRef
    • Pathogenesis, Diagnosis and Treatment of Immune-Related Cardiotoxicity
      静宜 任
      Advances in Clinical Medicine.2024; 14(03): 284.     CrossRef
    • Extending the dosing intervals of nivolumab: model-based simulations in unselected cancer patients
      Alicja Puszkiel, Guillaume Bianconi, Blaise Pasquiers, David Balakirouchenane, Jennifer Arrondeau, Pascaline Boudou-Rouquette, Marie-Claire Bretagne, Joe-Elie Salem, Xavier Declèves, Michel Vidal, Nora Kramkimel, Sarah Guegan, Selim Aractingi, Olivier Hui
      British Journal of Cancer.2024; 130(11): 1866.     CrossRef
    • Endocrine-metabolic assessment checklist for cancer patients treated with immunotherapy: A proposal by the Italian Association of Medical Oncology (AIOM), Italian Association of Medical Diabetologists (AMD), Italian Society of Diabetology (SID), Italian S
      Maria Chiara Zatelli, Antongiulio Faggiano, Antonella Argentiero, Romano Danesi, Stella D'Oronzo, Stefano Fogli, Tindara Franchina, Francesco Giorgino, Nicola Marrano, Dario Giuffrida, Stefania Gori, Giampiero Marino, Rossella Mazzilli, Matteo Monami, Mon
      Cancer Treatment Reviews.2024; 126: 102734.     CrossRef
    • Guide for the Diagnosis of Immune Checkpoint Inhibitor-Induced Liver Injury
      Takanori Ito, Yasuto Takeuchi, Kazuyuki Mizuno, Michitaka Imai, Yoko Yoshimaru, Kazumichi Abe, Masanori Abe, Takanori Matsuura, Masataka Yokode, Masahiro Shiokawa, Yuzo Kodama, Mina Komuta, Kenichi Harada, Atsushi Tanaka
      Kanzo.2024; 65(6): 268.     CrossRef
    • Diagnostic guide for immune checkpoint inhibitor‐induced liver injury
      Takanori Ito, Yasuto Takeuchi, Kazuyuki Mizuno, Michitaka Imai, Yoko Yoshimaru, Kazumichi Abe, Masanori Abe, Takanori Matsuura, Masataka Yokode, Masahiro Shiokawa, Yuzo Kodama, Mina Komuta, Kenichi Harada, Atsushi Tanaka
      Hepatology Research.2024; 54(8): 719.     CrossRef
    • Tumor-Agnostic Therapy—The Final Step Forward in the Cure for Human Neoplasms?
      Mohamed Mahmoud El-Sayed, Julia Raffaella Bianco, YiJing Li, Zsolt Fabian
      Cells.2024; 13(12): 1071.     CrossRef
    • Mesenteric Panniculitis as a Side Effect of Nivolumab in a Patient with Larnyngeal Cancer
      O Karhan, Y Sezgin, S Ileri, S Tunc
      Nigerian Journal of Clinical Practice.2024; 27(6): 800.     CrossRef
    • Real‐world first‐line treatment with pembrolizumab for non‐small cell lung carcinoma with high PD‐L1 expression: Updated analysis
      Yasuyuki Ikezawa, Ryo Morita, Hidenori Mizugaki, Kazunari Tateishi, Keiki Yokoo, Toshiyuki Sumi, Hajime Kikuchi, Yasuo Kitamura, Atsushi Nakamura, Maki Kobayashi, Mari Aso, Nozomu Kimura, Fumiaki Yoshiike, Furuta Megumi, Hisashi Tanaka, Motoki Sekikawa, T
      Cancer Medicine.2024;[Epub]     CrossRef
    • Multi-organ immune-related adverse events from immune checkpoint inhibitors and their downstream implications: a retrospective multicohort study
      Guihong Wan, Wenxin Chen, Sara Khattab, Katie Roster, Nga Nguyen, Boshen Yan, Ahmad Rajeh, Jayhyun Seo, Hannah Rashdan, Leyre Zubiri, Matthew J Hadfield, Shadmehr Demehri, Kun-Hsing Yu, William Lotter, Alexander Gusev, Nicole R LeBoeuf, Kerry L Reynolds,
      The Lancet Oncology.2024; 25(8): 1053.     CrossRef
    • Selecting Immune Checkpoint Inhibitor Side Effects for Real-Time Monitoring in Routine Cancer Care: A Modified Delphi Study
      Julia Lai-Kwon, Michael Jefford, Stephanie Best, Iris Zhang, Claudia Rutherford
      JCO Oncology Practice.2024; 20(12): 1663.     CrossRef
    • Differences in checkpoint-inhibitor-induced hypophysitis: mono- versus combination therapy induced hypophysitis
      Stephanie van der Leij, Karijn P.M. Suijkerbuijk, Medard F.M. van den Broek, Gerlof D. Valk, Jan Willem Dankbaar, Hanneke M. van Santen
      Frontiers in Endocrinology.2024;[Epub]     CrossRef
    • Unravelling the Acute, Chronic and Steroid-Refractory Management of High-Grade Neurological Immune-Related Adverse Events: A Call to Action
      Antonio Malvaso, Pierpaolo Giglio, Luca Diamanti, Matteo Gastaldi, Elisa Vegezzi, Andrea Pace, Paola Bini, Enrico Marchioni
      Brain Sciences.2024; 14(8): 764.     CrossRef
    • Machine learning modeling of patient health signals informs long-term survival on immune checkpoint inhibitor therapy
      Gerald J. Sun, Gustavo Arango-Argoty, Gary J. Doherty, Damian E. Bikiel, Dejan Pavlovic, Allen C. Chen, Ross A. Stewart, Zhongwu Lai, Etai Jacob
      iScience.2024; 27(9): 110634.     CrossRef
    • Toxicity in the era of immune checkpoint inhibitor therapy
      Synat Keam, Naimah Turner, Fernanda G. Kugeratski, Rene Rico, Jocelynn Colunga-Minutti, Rayansh Poojary, Sayan Alekseev, Anisha B. Patel, Yuanteng Jeff Li, Ajay Sheshadri, Monica E. Loghin, Karin Woodman, Ashley E. Aaroe, Sarah Hamidi, Priyanka Chandrasek
      Frontiers in Immunology.2024;[Epub]     CrossRef
    • Onco-Primary Care of Patients Receiving Immune Checkpoint Inhibitors
      Christopher J. Hoimes, Suzanne McGettigan, Lee Schwartzberg
      The American Journal of Medicine.2024; 137(12): 1200.     CrossRef
    • Subjective symptoms are triggers for the detection of immune checkpoint inhibitor-induced interstitial lung disease and associate with disease severity: a single-center retrospective study
      Mari Yokoi, Atsushi Yonezawa, Daiki Hira, Tomohiro Handa, Kiminobu Tanizawa, Shunsaku Nakagawa, Masahiro Tsuda, Yasuaki Ikemi, Ryo Itotani, Hironori Yoshida, Motoo Nomura, Junichi Matsubara, Kosaku Murakami, Hiroaki Ozasa, Manabu Muto, Tomohiro Terada
      Journal of Pharmaceutical Health Care and Sciences.2024;[Epub]     CrossRef
    • Melittin-incorporated nanomedicines for enhanced cancer immunotherapy
      Xuefeng Duan, Haoyang Zou, Jiazhen Yang, Shixian Liu, Tianmin Xu, Jianxun Ding
      Journal of Controlled Release.2024; 375: 285.     CrossRef
    • Do corticosteroids affect immunotherapy efficacy in malignancy? – A systematic review
      Yoni Byron, Sonya Yegorova‐Lee, Martin Tio
      Cancer Medicine.2024;[Epub]     CrossRef
    • Immune Checkpoint Inhibitors in the Pre-Transplant Hepatocellular Carcinoma Setting: A Glimpse Beyond the Liver
      Luca Marzi, Andrea Mega, Chiara Turri, Stefano Gitto, Federica Ferro, Gilbert Spizzo
      International Journal of Molecular Sciences.2024; 25(21): 11676.     CrossRef
    • Assessing the Prognostic Value of Cytoplasmic and Stromal Caveolin-1 in Early Triple-Negative Breast Cancer Undergoing Neoadjuvant Chemotherapy
      Iris Teruel, Eva Castellà, Sabela Recalde, Gemma Viñas, Anna Petit, Macedonia Trigueros, Eva Martínez-Balibrea, Eudald Felip, Milana Bergamino, Adrià Bernat-Peguera, Beatriz Cirauqui, Vanesa Quiroga, Angelica Ferrando-Díez, Anna Pous, Assumpció López, Lai
      International Journal of Molecular Sciences.2024; 25(22): 12241.     CrossRef
    • Real world comparison of immune-related adverse events with nivolumab-relatlimab versus ipilimumab-nivolumab in patients with advanced cutaneous melanoma
      Brooke Kielkowski, Diana Mansour, Brooke Ebbert, Kelsea Seago, Sijin Wen, Hang Li, Christine Barrett
      Journal of Oncology Pharmacy Practice.2024;[Epub]     CrossRef
    • Association of Immune-Related Adverse Events With Efficacy in Consolidation Nivolumab Plus Ipilimumab or Nivolumab Alone After Chemoradiation in Patients With Unresectable Stage III Nonsmall Cell Lung Cancer: An Exploratory Analysis From the Big 10 Cancer
      Cynthia X. Wei, Sandra K. Althouse, Hirva Mamdani, Nasser H. Hanna, Greg A. Durm
      Clinical Lung Cancer.2024;[Epub]     CrossRef
    • Safety of sequential immune checkpoint inhibitors after prior immune therapy
      Muhammad Awidi, Brendan Connell, Delaney Johnson, Isabel Craven, Rojer Ranjit, Brigitte Gil, Natalie Dal’Bo, Lewena Maher, Seanna Reilly Daves, Stephanie McDonald, Krishna S. Gunturu
      Journal of Cancer Research and Clinical Oncology.2023; 149(6): 2375.     CrossRef
    • The role of immune checkpoint inhibitors in clinical practice: an analysis of the treatment patterns, survival and toxicity rates by sex
      Murielle N. Wahli, Stefanie Hayoz, Dennis Hoch, Christoph O. Ryser, Michèle Hoffmann, Amina Scherz, Birgit Schwacha-Eipper, Simon Häfliger, Julian Wampfler, Martin D. Berger, Urban Novak, Berna C. Özdemir
      Journal of Cancer Research and Clinical Oncology.2023; 149(7): 3847.     CrossRef
    • Association between skin immune-related adverse events (irAEs) and multisystem irAEs during PD-1/PD-L1 inhibitor monotherapy
      Atsushi Yamaguchi, Yoshitaka Saito, Katsuya Narumi, Ayako Furugen, Yoh Takekuma, Naofumi Shinagawa, Yasushi Shimizu, Hirotoshi Dosaka-Akita, Mitsuru Sugawara, Masaki Kobayashi
      Journal of Cancer Research and Clinical Oncology.2023; 149(4): 1659.     CrossRef
    • Immune checkpoint inhibitor-induced pure red cell aplasia: Case series and large‐scale pharmacovigilance analysis
      Qian Guo, Jian Gao, Hui Guo, Jun Xie, Jingmin Cheng
      International Immunopharmacology.2023; 114: 109490.     CrossRef
    • Prognostic Significance of the Severity of Immune-Related Adverse Events in Advanced Cancer Patients Treated with PD-1/PD-L1 Inhibitors: A Real-World Data Analysis
      Su Jeong Song, Yun-Kyoung Song, Mihwa Jang, Eunjeong Shin, Sung Yun Suh, Yoon Sook Cho, Ju-Yeun Lee, Jung Mi Oh
      Targeted Oncology.2023; 18(1): 147.     CrossRef
    • Immune checkpoint inhibitor-induced aplastic anaemia: Case series and large-scale pharmacovigilance analysis
      Qian Guo, Jin Ning Zhao, Ting Liu, Jian Gao, Hui Guo, Jing Min Cheng
      Frontiers in Pharmacology.2023;[Epub]     CrossRef
    • Association of Immune-Related Adverse Events With Efficacy of Atezolizumab in Patients With Non–Small Cell Lung Cancer
      Mark A. Socinski, Robert M. Jotte, Federico Cappuzzo, Makoto Nishio, Tony S. K. Mok, Martin Reck, Gene G. Finley, Monika D. Kaul, Wei Yu, Nindhana Paranthaman, Ilze Bāra, Howard J. West
      JAMA Oncology.2023; 9(4): 527.     CrossRef
    • Management of Non-Melanoma Skin Cancer: Radiologists Challenging and Risk Assessment
      Gaetano Maria Russo, Anna Russo, Fabrizio Urraro, Fabrizio Cioce, Luigi Gallo, Maria Paola Belfiore, Angelo Sangiovanni, Stefania Napolitano, Teresa Troiani, Pasquale Verolino, Antonello Sica, Gabriella Brancaccio, Giulia Briatico, Valerio Nardone, Alfons
      Diagnostics.2023; 13(4): 793.     CrossRef
    • Blood cell counts can predict adverse events of immune checkpoint inhibitors: A systematic review and meta-analysis
      Juyue Zhou, Zhonghai Du, Jie Fu, Xiuxiu Yi
      Frontiers in Immunology.2023;[Epub]     CrossRef
    • Gastritis as an immunotherapy-related toxicity in the treatment of endometrial cancer: A case report
      Nidhi Goel, Monica D. Levine, Laura M. Chambers, Christa I. Nagel
      Gynecologic Oncology Reports.2023; 47: 101174.     CrossRef
    • Society for Immunotherapy of Cancer (SITC) consensus definitions for immune checkpoint inhibitor-associated immune-related adverse events (irAEs) terminology
      Jarushka Naidoo, Catherine Murphy, Michael B Atkins, Julie R Brahmer, Stephane Champiat, David Feltquate, Lee M Krug, Javid Moslehi, M Catherine Pietanza, Joanne Riemer, Caroline Robert, Elad Sharon, Maria E Suarez-Almazor, Karthik Suresh, Michelle Turner
      Journal for ImmunoTherapy of Cancer.2023; 11(3): e006398.     CrossRef
    • Multidisciplinary recommendations for essential baseline functional and laboratory tests to facilitate early diagnosis and management of immune-related adverse events among cancer patients
      Berna C. Özdemir, Cristina Espinosa da Silva, Dimitri Arangalage, Pierre Monney, Sabina A. Guler, Uyen Huynh-Do, Guido Stirnimann, Lucia Possamai, Roman Trepp, Robert Hoepner, Anke Salmen, Camille L. Gerard, Petr Hruz, Lisa Christ, Sacha I. Rothschild
      Cancer Immunology, Immunotherapy.2023; 72(7): 1991.     CrossRef
    • Immune checkpoint inhibitor-induced cutaneous toxicities: a review of histopathologic and clinical features
      Julianna Martel, Hannah L. Hanania, Anisha B. Patel
      Human Pathology.2023; 140: 144.     CrossRef
    • Immune checkpoint inhibitors: maximizing benefit whilst minimizing toxicity
      Catherine C. Fahey, Thomas J. Gracie, Douglas B. Johnson
      Expert Review of Anticancer Therapy.2023; 23(7): 673.     CrossRef
    • Prevalence of immune-related adverse events and anti-tumor efficacy in advanced/metastatic urothelial carcinoma following immune-checkpoint inhibitor treatment
      Rafael Morales-Barrera, Guillermo Villacampa, Natalia Vidal, Mariona Figols, Julia Giner, Teresa Bonfill, Cristina Suárez, Nely Díaz, Joaquín Mateo, Macarena González, Montserrat Domenech, Javier Puente, Joan Carles
      Clinical and Translational Oncology.2023; 25(12): 3556.     CrossRef
    • The Feasibility, Acceptability, and Effectiveness of Electronic Patient-Reported Outcome Symptom Monitoring for Immune Checkpoint Inhibitor Toxicities: A Systematic Review
      Julia Lai-Kwon, Jordan E. Cohen, Karolina Lisy, Claudia Rutherford, Afaf Girgis, Ethan Basch, Michael Jefford
      JCO Clinical Cancer Informatics.2023;[Epub]     CrossRef
    • Elevated eosinophils proportion as predictor of immune‐related adverse events after ipilimumab and nivolumab treatment of advanced and metastatic renal cell carcinoma
      Yoshihiko Tasaki, Shuzo Hamamoto, Yosuke Sugiyama, Nami Tomiyama, Taku Naiki, Toshiki Etani, Kazumi Taguchi, Nayuka Matsuyama, Yasuhito Sue, Yoshihisa Mimura, Hiroki Kubota, Yusuke Noda, Maria Aoki, Yoshinobu Moritoki, Satoshi Nozaki, Satoshi Kurokawa, At
      International Journal of Urology.2023; 30(10): 866.     CrossRef
    • Antinuclear antibody (ANA) status predicts immune-related adverse events in liver cancer patients undergoing anti-PD-1 therapy
      Shu-Jung Hsu, Yen-Cheng Chao, Xia-Hui Lin, Hua-Hua Liu, Yang Zhang, Wei-Feng Hong, Mao-Pei Chen, Xin Xu, Lan Zhang, Zheng-Gang Ren, Shi-Suo Du, Rong-Xin Chen
      Clinical and Experimental Immunology.2023; 212(3): 239.     CrossRef
    • First-Line, Fixed-Duration Nivolumab Plus Ipilimumab Followed by Nivolumab in Clinically Diverse Patient Populations With Unresectable Stage III or IV Melanoma: CheckMate 401
      Reinhard Dummer, Pippa Corrie, Ralf Gutzmer, Tarek M. Meniawy, Michele Del Vecchio, Céleste Lebbé, Michele Guida, Caroline Dutriaux, Brigitte Dreno, Nicolas Meyer, Pier Francesco Ferrucci, Stéphane Dalle, Muhammad Adnan Khattak, Jean-Jacques Grob, Karen B
      Journal of Clinical Oncology.2023; 41(23): 3917.     CrossRef
    • Early-Stage Triple-Negative Breast Cancer Journey: Beginning, End, and Everything in Between
      Hyo Sook Han, Praveen Vikas, Ricardo L.B. Costa, Nusrat Jahan, Ammanuel Taye, Erica M. Stringer-Reasor
      American Society of Clinical Oncology Educational Book.2023;[Epub]     CrossRef
    • An updated review of gastrointestinal toxicity induced by PD-1 inhibitors: from mechanisms to management
      Yiyu Cheng, Fangmei Ling, Junrong Li, Yidong Chen, Mingyang Xu, Shuang Li, Liangru Zhu
      Frontiers in Immunology.2023;[Epub]     CrossRef
    • Postmarketing surveillance of nivolumab plus ipilimumab combination therapy in Japanese patients with unresectable malignant melanoma
      Naoya Yamazaki, Yoshio Kiyohara, Hisashi Uhara, Tetsuya Tsuchida, Ai Yoshida, Takako Yamada, Akira Komoto
      The Journal of Dermatology.2023; 50(9): 1108.     CrossRef
    • Real‐world evidence of incidence and outcomes of aplastic anaemia following administration of immune checkpoint inhibitors
      Srilatha Dasari, William Tse, Jiasheng Wang
      British Journal of Haematology.2023; 202(6): 1205.     CrossRef
    • Development of an eHealth-enhanced model of care for the monitoring and management of immune-related adverse events in patients treated with immune checkpoint inhibitors
      André Manuel da Silva Lopes, Sara Colomer-Lahiguera, Célia Darnac, Stellio Giacomini, Sébastien Bugeia, Garance Gutknecht, Gilliosa Spurrier-Bernard, Veronica Aedo-Lopez, Nuria Mederos, Sofiya Latifyan, Alfredo Addedo, Olivier Michielin, Manuela Eicher
      Supportive Care in Cancer.2023;[Epub]     CrossRef
    • CD4 T cells and toxicity from immune checkpoint blockade
      Noah Earland, Wubing Zhang, Abul Usmani, Aishwarya Nene, Antonella Bacchiocchi, David Y. Chen, Mario Sznol, Ruth Halaban, Aadel A. Chaudhuri, Aaron M. Newman
      Immunological Reviews.2023; 318(1): 96.     CrossRef
    • Anti‑PD1 therapy‑associated distal renal tubular acidosis: A case report
      Xuejia Qiu, Bingnan Ren, Lingzhi Fang, Zhanjun Dong
      Experimental and Therapeutic Medicine.2023;[Epub]     CrossRef
    • Recent advances in immune checkpoint inhibitors in the treatment of urothelial carcinoma: A review
      Minoru Kato, Junji Uchida
      International Journal of Urology.2023; 30(12): 1068.     CrossRef
    • Severe Immune-Related Enteritis after In Utero Exposure to Pembrolizumab
      Manuel A. Baarslag, Joosje H. Heimovaara, Jessica S.W. Borgers, Koen J. van Aerde, Hans J.P.M. Koenen, Ruben L. Smeets, Pauline L.M. Buitelaar, Dick Pluim, Shoko Vos, Stefanie S.V. Henriet, Jan Willem B. de Groot, Martine van Grotel, Hilde Rosing, Jos H.
      New England Journal of Medicine.2023; 389(19): 1790.     CrossRef
    • Incidence and Timing of Immune-Related Adverse Events in Immune-Checkpoint Inhibitor-Treated Patients: A Retrospective Observational Study
      Kou Masaki, Motoyasu Miyazaki, Hideki Kakimoto, Yuma Fukiage, Haruka Fukue, Akio Nakashima, Osamu Imakyure
      Journal of Clinical Medicine.2023; 12(24): 7564.     CrossRef
    • Immune checkpoint inhibitors and cancer immunotherapy by aptamers: an overview
      Priyatharcini Kejamurthy, K. T. Ramya Devi
      Medical Oncology.2023;[Epub]     CrossRef
    • Imaging of Cancer Immunotherapy: Response Assessment Methods, Atypical Response Patterns, and Immune-Related Adverse Events, From theAJRSpecial Series on Imaging of Inflammation
      Sara Sheikhbahaei, Charles V. Marcus, Mohammad S. Sadaghiani, Steven P. Rowe, Martin G. Pomper, Lilja B. Solnes
      American Journal of Roentgenology.2022; 218(6): 940.     CrossRef
    • Pharmacokinetic Simulation Analysis of Less Frequent Nivolumab and Pembrolizumab Dosing: Pharmacoeconomic Rationale for Dose Deescalation
      Cody J. Peer, Brian L. Heiss, Daniel A. Goldstein, Jennifer C. Goodell, William D. Figg, Mark J. Ratain
      The Journal of Clinical Pharmacology.2022; 62(4): 532.     CrossRef
    • T cell characteristics associated with toxicity to immune checkpoint blockade in patients with melanoma
      Alexander X. Lozano, Aadel A. Chaudhuri, Aishwarya Nene, Antonietta Bacchiocchi, Noah Earland, Matthew D. Vesely, Abul Usmani, Brandon E. Turner, Chloé B. Steen, Bogdan A. Luca, Ti Badri, Gunsagar S. Gulati, Milad R. Vahid, Farnaz Khameneh, Peter K. Harri
      Nature Medicine.2022; 28(2): 353.     CrossRef
    • Guarantee‐time bias in studies on the relationship between immune‐related adverse events and antitumor activity
      Ka Man Cheung, Therese Yue Man Tsui, James Chung Hang Chow
      Cancer.2022; 128(13): 2549.     CrossRef
    • CD21lo B Cells Could Be a Potential Predictor of Immune-Related Adverse Events in Renal Cell Carcinoma
      Kenichi Nishimura, Tatsuya Konishi, Toshiki Ochi, Ryuta Watanabe, Terutaka Noda, Tetsuya Fukumoto, Noriyoshi Miura, Yuki Miyauchi, Tadahiko Kikugawa, Katsuto Takenaka, Takashi Saika
      Journal of Personalized Medicine.2022; 12(6): 888.     CrossRef
    • A Phase I/IIa Randomized Trial Evaluating the Safety and Efficacy of SNK01 Plus Pembrolizumab in Patients with Stage IV Non-Small Cell Lung Cancer
      Eo Jin Kim, Yong-Hee Cho, Dong Ha Kim, Dae-Hyun Ko, Eun-Ju Do, Sang-Yeob Kim, Yong Man Kim, Jae Seob Jung, Yoonmi Kang, Wonjun Ji, Myeong Geun Choi, Jae Cheol Lee, Jin Kyung Rho, Chang-Min Choi
      Cancer Research and Treatment.2022; 54(4): 1005.     CrossRef
    • Predictive Biomarkers of Severe Immune-Related Adverse Events With Immune Checkpoint Inhibitors: Prevention, Underlying Causes, Intensity, and Consequences
      Ana Cardeña-Gutiérrez, Mónica López Barahona
      Frontiers in Medicine.2022;[Epub]     CrossRef
    • Human leucocyte antigen genotype association with the development of immune-related adverse events in patients with non-small cell lung cancer treated with single agent immunotherapy
      Afaf Abed, Ngie Law, Leslie Calapre, Johnny Lo, Vikas Bhat, Samantha Bowyer, Michael Millward, Elin S. Gray
      European Journal of Cancer.2022; 172: 98.     CrossRef
    • Development of Lymphopenia during Therapy with Immune Checkpoint Inhibitors Is Associated with Poor Outcome in Metastatic Cutaneous Melanoma
      Dirk Tomsitz, Max Schlaak, Sarah Zierold, Giulia Pesch, Thomas U. Schulz, Genoveva Müller, Christine Zecha, Lars E. French, Lucie Heinzerling
      Cancers.2022; 14(13): 3282.     CrossRef
    • Phase 1 Study of Chemoradiotherapy Combined with Nivolumab ± Ipilimumab for the Curative Treatment of Muscle-invasive Bladder Cancer
      Ben-Max de Ruiter, Jons W. van Hattum, Djoeri Lipman, Theo M. de Reijke, R. Jeroen A. van Moorselaar, Erik J. van Gennep, A.H. Maartje Piet, Mila Donker, Tom van der Hulle, Jens Voortman, Jorg R. Oddens, Maarten C.C.M. Hulshof, Adriaan D. Bins
      European Urology.2022; 82(5): 518.     CrossRef
    • Adverse Renal Effects of Anticancer Immunotherapy: A Review
      Maciej Borówka, Stanisław Łącki-Zynzeling, Michał Nicze, Sylwia Kozak, Jerzy Chudek
      Cancers.2022; 14(17): 4086.     CrossRef
    • Evolution of Radiological Treatment Response Assessments for Cancer Immunotherapy: From iRECIST to Radiomics and Artificial Intelligence
      Nari Kim, Eun Sung Lee, Sang Eun Won, Mihyun Yang, Amy Junghyun Lee, Youngbin Shin, Yousun Ko, Junhee Pyo, Hyo Jung Park, Kyung Won Kim
      Korean Journal of Radiology.2022; 23(11): 1089.     CrossRef
    • Use of PD-1 inhibitors in patients with end-stage renal disease: safety and clinical outcomes from real-world data
      Jiasheng Wang, Srilatha Dasari, Dina Elantably, Akram Alkrekshi, Yeseong David Kim
      Acta Oncologica.2022; 61(9): 1157.     CrossRef
    • Association of High Levels of Antidrug Antibodies Against Atezolizumab With Clinical Outcomes and T-Cell Responses in Patients With Hepatocellular Carcinoma
      Chan Kim, Hannah Yang, Ilhwan Kim, Beodeul Kang, Hyeyeong Kim, Hyunho Kim, Won Suk Lee, Sanghoon Jung, Ho Yeong Lim, Jaekyung Cheon, Hong Jae Chon
      JAMA Oncology.2022; 8(12): 1825.     CrossRef
    • Germline genetic variation and predicting immune checkpoint inhibitor induced toxicity
      Ik Shin Chin, Aman Khan, Anna Olsson-Brown, Sophie Papa, Gary Middleton, Claire Palles
      npj Genomic Medicine.2022;[Epub]     CrossRef
    • The incidence and risk factors for acute kidney injury in patients treated with immune checkpoint inhibitors
      Deniz Can Guven, Deniz Aral Ozbek, Taha Koray Sahin, Gozde Kavgaci, Melek Seren Aksun, Enes Erul, Hasan Cagri Yildirim, Elvin Chalabiyev, Cebrayil Cebroyilov, Tolga Yildirim, Omer Dizdar, Sercan Aksoy, Suayib Yalcin, Saadettin Kilickap, Mustafa Erman, Mus
      Anti-Cancer Drugs.2022;[Epub]     CrossRef
    • Vascular Normalization to Improve Treatment of COVID-19: Lessons from Treatment of Cancer
      Lance L. Munn, Triantafyllos Stylianopoulos, Natalie K. Jain, C. Corey Hardin, Melin J. Khandekar, Rakesh K. Jain
      Clinical Cancer Research.2021; 27(10): 2706.     CrossRef
    • Lenvatinib plus pembrolizumab in patients with advanced or recurrent uterine carcinosarcoma
      Jonathan T. Hunt, Laura M. Chambers, Meng Yao, Amy Joehlin-Price, Robert Debernardo, Peter G. Rose
      Gynecologic Oncology Reports.2021; 37: 100840.     CrossRef
    • Blocking antibody-mediated phosphatidylserine enhances cancer immunotherapy
      Jie Zhang, Zhujiang Dai, Cheng Yan, Daorong Wang, Dong Tang
      Journal of Cancer Research and Clinical Oncology.2021; 147(12): 3639.     CrossRef
    • Important Surgical and Clinical End Points in Neoadjuvant Immunotherapy Trials in Resectable NSCLC
      Jay M. Lee, Anthony W. Kim, Tomasz Marjanski, Pierre-Emmanuel Falcoz, Masahiro Tsuboi, Yi-Long Wu, Shawn W. Sun, Barbara J. Gitlitz
      JTO Clinical and Research Reports.2021; 2(10): 100221.     CrossRef
    • Management of Immune-Related Adverse Events in Patients Treated With Immune Checkpoint Inhibitor Therapy: ASCO Guideline Update
      Bryan J. Schneider, Jarushka Naidoo, Bianca D. Santomasso, Christina Lacchetti, Sherry Adkins, Milan Anadkat, Michael B. Atkins, Kelly J. Brassil, Jeffrey M. Caterino, Ian Chau, Marianne J. Davies, Marc S. Ernstoff, Leslie Fecher, Monalisa Ghosh, Ishmael
      Journal of Clinical Oncology.2021; 39(36): 4073.     CrossRef
    • Rheumatic Manifestations and Diseases From Immune Checkpoint Inhibitors in Cancer Immunotherapy
      Pan Shen, Xuan Deng, Zhishuo Hu, Zhe Chen, Yao Huang, Ke Wang, Kai Qin, Ying Huang, Xin Ba, Jiahui Yan, Liang Han, Shenghao Tu
      Frontiers in Medicine.2021;[Epub]     CrossRef

    • PubReader PubReader
    • ePub LinkePub Link
    • Cite
      CITE
      export Copy Download
      Close
      Download Citation
      Download a citation file in RIS format that can be imported by all major citation management software, including EndNote, ProCite, RefWorks, and Reference Manager.

      Format:
      • RIS — For EndNote, ProCite, RefWorks, and most other reference management software
      • BibTeX — For JabRef, BibDesk, and other BibTeX-specific software
      Include:
      • Citation for the content below
      The Pattern of Time to Onset and Resolution of Immune-Related Adverse Events Caused by Immune Checkpoint Inhibitors in Cancer: A Pooled Analysis of 23 Clinical Trials and 8,436 Patients
      Cancer Res Treat. 2021;53(2):339-354.   Published online November 6, 2020
      Close
    • XML DownloadXML Download
    The Pattern of Time to Onset and Resolution of Immune-Related Adverse Events Caused by Immune Checkpoint Inhibitors in Cancer: A Pooled Analysis of 23 Clinical Trials and 8,436 Patients
    Image Image Image
    Fig. 1 The pattern of time to onset of all-grade (A, C, E) and grade ≥ 3 (B, D, F) irAEs. Circles and bars represent median values and 95% confidence intervals, respectively. Number and percent of an event indicate the incidence of the irAE. CTLA-4, cytotoxic T-lymphocyte antigen 4; IPI, ipilimumab; irAEs, immune-related adverse events; NIV, nivolumab; PD-1/PD-L1, programmed cell death protein 1 or its ligand 1. a)p < 0.05 between the comparison of time to onset of all-grade irAEs and grade ≥ 3 irAEs. A total of 3,977 and 1,261 patients were included in the analysis of all-grade and grade ≥ 3 irAEs, respectively, for PD-1/PD-L1 inhibitors; 2,958 and 1,294 patients for CTLA-4 inhibitors; 828 and 867 patients for NIV+IPI.
    Fig. 2 The pattern of resolution (A, B, E, F, I, J) and immune-modulation resolution (C, D, G, H, K, L) of all-grade (A, E, I, C, G, K) and grade ≥ 3 (B, F, J, D, H, L) irAEs. Circles and bars represent median values and 95% confidence intervals, respectively. Number and percent of an event indicate the patients whose irAE resolved (A, B, E, F, I, J) and patients whose irAE resolved with usage of immune-modulation agents (C, D, G, H, K, L). CTLA-4, cytotoxic T-lymphocyte antigen 4; IM, immune-modulation; IPI, ipilimumab; irAEs, immune-related adverse events; NIV, nivolumab; PD-1/PD-L1, programmed cell death protein 1 or its ligand 1. a)p < 0.05 between the comparison of time to resolution of all-grade and grade ≥ 3 irAEs, b)p < 0.05 between the comparison of time to immune-modulation resolution of all-grade and grade ≥ 3 irAEs, c)p < 0.05 between the comparison of time to resolution and immune-modulation resolution of all-grade, d)p < 0.05 between the comparison of time to resolution and immune-modulation resolution of grade ≥ 3 irAEs. A total of 1,196 and 192 patients were included in the analysis of time to resolution and immune-modulation resolution of all-grade irAEs, respectively, for PD-1/PD-L1 inhibitors; 2,611 and 402 patients for CTLA-4 inhibitors; 1,572 and 247 patients for NIV+IPI. A total of 71 and 37 patients were included in the analysis of time to resolution and immune-modulation resolution of grade ≥ 3 irAEs, respectively, for PD-1/PD-L1 inhibitors; 348 and 194 patients for CTLA-4 inhibitors; 254 and 117 patients for NIV+IPI.
    Fig. 3 Kinetics (A–C) and ranking (D) of the onset and resolution of all-grade irAEs caused by nivolumab (A), IPI (B), and nivolumab plus IPI (C). The beginning and end of each curve in Fig. 3A–C represent the median time to the onset of an irAE and the median time to resolution, respectively; the peak and tail of each curve show the proportion of patients who developed an irAE and the proportion of patients whose irAE had not been resolved, respectively. The number in parentheses of Fig. 3D represents the pooled median time (weeks). The ranking is arranged from the shortest to the longest pooled median time. Items with underlining share the same ranking. IPI, ipilimumab; irAEs, immune-related adverse events; NA, not applicable; NIV, nivolumab. a)p < 0.05 between the comparison of NIV and NIV+IPI, b)p < 0.05 between the comparison of NIV and IPI, c)p < 0.05 between the comparison of IPI and NIV+IPI. A total of 1,815 and 1,196 patients were included in the analysis of time to onset and resolution, respectively, for NIV; 2,092 and 2,123 patients for IPI; 828 and 1,572 patients for NIV+IPI.
    The Pattern of Time to Onset and Resolution of Immune-Related Adverse Events Caused by Immune Checkpoint Inhibitors in Cancer: A Pooled Analysis of 23 Clinical Trials and 8,436 Patients

    Baseline characteristics of the included studies

    Author, year Study ID Region Cancer Phase Total No. Safety analysis No. Arm Treatment Median follow-up time (mo) CTCAE version
    Weber (2013) [21] MDX010-20 MN Melanoma III 676 403 1 IPI 3 mg/kg Q3W plus gp100 21.0 3.0
    131 2 IPI 3 mg/kg Q3W 27.8
    136 3 Gp 100 17.2
    Kwon (2014) [22] CA184-043 MN Prostate cancer III 799 399 1 IPI 10 mg/kg Q3W plus bone-directed radiotherapy 9.9 3.0
    400 2 Placebo plus bone-directed radiotherapy 9.3
    Brahmer (2015) [3] CheckMate 017 MN Lung cancer III 272 131 1 NIV 3 mg/kg Q2W Min 11.0 4.0
    129 2 DOC 75 mg/m2 Q3W Min 11.0
    Borghaei (2015) [23] CheckMate 057 MN Lung cancer III 582 287 1 NIV 3 mg/kg Q2W Min 13.2 4.0
    268 2 DOC 75 mg/m2 Q3W Min 13.2
    Reck (2016) [25] CA184-156 MN Lung cancer III 954 478 1 IPI 10 mg/kg Q3W, ETO, and DDP or CBP 10.5 3.0
    476 2 ETO and DDP or CBP 10.2
    Eggermont (2016) [24] EORTC 18071 MN Melanoma III 951 471 1 IPI 10 mg/kg Q3W 63.6 3.0
    476 2 Placebo Q3W 64.8
    Weber (2017) [27] CheckMate 238 MN Melanoma III 905 452 1 NIV 3 mg/kg Q2W 19.5 4.0
    453 2 IPI 10 mg/kg Q3W 19.5
    Ascierto (2017) [26] CA184-169 MN Melanoma III 727 364 1 IPI 10 mg/kg Q3W 14.5 3.0
    362 2 IPI 3 mg/kg Q3W 11.2
    Larkin (2017) [28] CheckMate 037 MN Melanoma II 405 268 1 NIV 3 mg/kg Q2W 24.0 4.0
    102 2 ICC (DTIC 1,000 mg/m2 Q3W or CBP AUC=6 and PTX 175 mg/m2 Q3W) 24.0
    Govindan (2017) [29] CA184-104 MN Lung cancer III 749 388 1 IPI 10 mg/kg Q3W, PTX and CBP 12.5 3.0
    361 2 PTX and CBP 11.8
    Horn (2017) [30] CheckMate 017 MN Lung cancer III 854 418 1 NIV 3 mg/kg Q2W Min 24.0 4.0
    CheckMate 057 MN Lung cancer III 397 2 DOC 75 mg/m2 Q3W Min 24.0
    Armand (2018) [31] CheckMate 205 MN Hodgkin lymphoma II 243 243 1 NIV 3 mg/kg Q2W 18.0 4.0
    Kelly (2018) [32] JAVELIN Solid Tumor MN Solid tumors Ia) 1,650 1,650 1 AVE 10 mg/kg Q2W Min 3.0 4.0
    JAVELIN Merkel 200 MN Merkel cell carcinoma II 88 88 1 AVE 10 mg/kg Q2W Min 9.0 4.0
    Larkin (2019) [34] CheckMate 067 MN Melanoma III 945 313 1 NIV 1 mg/kg plus IPI 3 mg/kg Q3W, followed by NIV 3 mg/kg Q2W Min 60.0 4.0
    313 2 NIV 3 mg/kg Q2W 36.9
    311 3 IPI 3 mg/kg Q3W 19.9
    Geoerger (2019) [35] Keynote 051 MN Advanced pediatric cancer I–II 154 154 1 PEM 2 mg/kg Q3W 8.6 4.0
    Fradet (2019) [33] Keynote 045 MN Urothelial carcinoma III 542 270 1 PEM 200 mg Q3W 27.7 4.0
    272 2 PTX 175 mg/m2 Q3W, DOC 75 mg/m2 Q3W, or VIN 320 mg/m2 Q3W 27.7
    Tomita (2020) [41] CheckMate 214 Japan Renal cell carcinoma III 72 38 1 NIV 3 mg/kg plus IPI 1 mg/kg Q3W, followed by NIV 3 mg/kg Q2W 32.4 4.0
    34 2 SUN 50 mg QD for 4 weeks Q6W 32.4
    Lebbe (2019) [38] CheckMate 511 MN Melanoma IIIB/IV 358 180 1 NIV 3 mg/kg plus IPI 1 mg/kg Q3W, followed by NIV 480 mg Q4W 18.8 4.0
    178 2 NIV 1 mg/kg plus IPI 3 mg/kg Q3W, followed by NIV 480 mg Q4W 18.6
    Sharma (2020) [40] CheckMate 032 MN Urothelial carcinoma I/II 274 78 1 NIV 3 mg/kg Q2W Min 37.7 4.0
    104 2 NIV 3 mg/kg plus IPI 1 mg/kg Q3W, followed by NIV 3 mg/kg Q2W Min 38.8
    92 3 NIV 1 mg/kg plus IPI 3 mg/kg Q3W, followed by NIV 3 mg/kg Q2W Min 7.9
    Morse (2019) [39] CheckMate 142 MN Colorectal cancer II 119 119 1 NIV 3 mg/kg plus IPI 1 mg/kg Q3W, followed by NIV 3 mg/kg Q2W 13.4 4.0
    Carneiro (2019) [36] NA MN Adrenocortical carcinoma II 10 10 1 NIV 240 mg Q2W 4.5 4.0
    Horinouchi (2019) [37] ONO 4538 05 Japan Lung cancer II 35 35 1 NIV 3 mg/kg Q2W 36.0 4.0
    ONO 4538 06 Japan Lung cancer II 76 76 1 NIV 3 mg/kg Q2W 36.0 4.0

    AUC, area under the curve; AVE, avelumab; CBP, carboplatin; CTCAE, Common Terminology Criteria for Adverse Events; DDP, cisplatin; DOC, docetaxel; DTIC, dacarbazine; ETO, etoposide; ICC, investigator’s choice chemotherapy; IPI, ipilimumab; MN, multinational; NA, not available; NIV, nivolumab; PEM, pembrolizumab; PTX, paclitaxel; Q2W, every 2 weeks; Q3W, every 3 weeks; Q6W, every 6 weeks; SUN, sunitinib; VIN, vinflunine.

    a)The study of Kelly et al. [32] reported pooled results of phase I and phase II clinical trials with a large sample size (n=1,738); thus, the phase I trial was also included in the analysis.

    Time to onset and resolution of all-grade irAEs based on ICI doses

    IPI-3 IPI-10 NIV-1+IPI-3 NIV-3+IPI-1
    All categories
     No. of patients with irAE 606 (13.5) 1,565 (20.3) 921 (29.9) 402 (19.9)
      Time to onset (wk) 5.1 (3.6–7.1) 6.3 (4.1–8.9) 4.9 (2.4–6.1) 6.1 (5.2–9.0)
     No. of patients with irAE 495 (87.3) 1,252 (85.2) 663 (79.0) 607 (82.8)
      Time to resolution (wk) 3.6 (2.9–11.0) 4.4 (3.1–7.0) 5.1 (2.9–10.9) 5.0 (1.8–6.3)
    Skin
     No. of patients with irAE 218 (32.4) 460 (35.7) 288 (58.7) 135 (40.1)
      Time to onset (wk) 3.6 (3.6–5.1) 2.6 (2.6–4.1) 2.1 (2.1–2.4)a) 5.1 (3.1–5.2)a)
     No. of patients with resolution 179 (82.1) 377 (82.0) 193 (67.2) 100 (70.9)
      Time to resolution (wk) 11 (5.1–11.0) 9.3 (3.1–9.3) 10.9 (10.9–24.1) 9.0 (9.0–13.1)
    Gastrointestinal
     No. of patients with irAE 231 (34.3) 567 (44.0) 207 (42.2) 84 (24.9)
      Time to onset (wk) 7.1 (4.6–7.6) 6.3 (4.4–7.6) 4.9 (3.9–4.9) 6.1 (3.6–9.1)
     No. of patients with resolution 218 (94.8) 539 (95.1) 197 (95.6) 170 (96.6)
      Time to resolution (wk) 2.9 (2.9–3.6) 3.1 (2.1–4.0) 2.9 (2.9–3.0)a) 1.5 (1.5–2.7)a)
    Hepatic
     No. of patients with irAE 32 (4.8) 223 (17.3) 163 (33.2) 58 (17.2)
      Time to onset (wk) 8.9 (6.1–9.0) 8.9 (8.1–8.9) 6.0 (6.0–6.1)a) 9.0 (7.0–10.0)a)
     No. of patients with resolution 30 (93.8) 205 (91.9) 148 (90.8) 117 (76.0)
      Time to resolution (wk) 4.1 (2.9–4.1) 4.4 (4.4–7.0) 5.1 (5.1–6.1) 5.0 (2.0–8.2)
    Endocrine
     No. of patients with irAE 57 (8.5) 269 (20.9) 192 (39.1) 89 (26.4)
      Time to onset (wk) 9.1 (8.9–9.1)b) 10.2 (8.9–10.2)b) 8.0 (6.0–8.0) 6.1 (6.1–12.0)
     No. of patients with resolution 14 (70.0) 93 (53.8) 57 (53.3) -
      Time to resolution (wk) 3.4 (3.4–3.4)b) 54.3 (13.9–54.3)b) 27.6 (27.6–27.6) NA
    Pulmonary
     No. of patients with irAE 6 (1.9) 11 (2.4) 25 (8.0) 22 (6.5)
      Time to onset (wk) 10.1 (10.1–10.1) 10.0 (10.0–10.0) 10.1 (10.1–10.1)a) 15.4 (10.5–16.6)a)
     No. of patients with resolution 5 (83.3) 11 (100) 29 (96.7) 114 (84.4)
      Time to resolution (wk) 6.3 (6.3–6.3) 3.7 (3.7–3.7) 7.0 (3.0–7.0) 4.5 (2.8–14.6)
    Renal
     No. of patients with irAE 8 (2.6) 7 (1.5) 32 (6.5) 14 (4.2)
      Time to onset (wk) 10.0 (10.0–10.0) 9.7 (9.7–9.7) 13.9 (8.7–13.9)a) 15.7 (12.6–36.4)a)
     No. of patients with resolution 7 (87.5) 4 (57.1) 27 (84.4) 106 (83.5)
      Time to resolution (wk) 2.5 (2.5–2.5) 52.7 (52.7–52.7) 2.1 (1.3–2.1) 6.3 (1.6–6.9)
    Hypersensitivity/Infusion reaction
     No. of patients with irAE 8 (2.6) 9 (2.0) 14 (4.5) -
      Time to onset (wk) 4.3 (4.3–4.3) 6.1 (6.1–6.1) 3.1 (3.1–3.1) NA
     No. of patients with resolution 8 (100) 9 (100) 12 (85.7) -
      Time to resolution (wk) 0.1 (0.1–0.1) 0.1 (0.1–0.1) 0.2 (0.2–0.2) NA
    Neurologic
     No. of patients with irAE 1 (0.3) 19 (2.3) - -
      Time to onset (wk) 11.7 (11.7–11.7)b) 13.1 (10.4–13.1)b) NA NA
     No. of patients with resolution 1 (100) 14 (73.7) - -
      Time to resolution (wk) 0.7 (0.7–0.7) 8.0 (8.0–11.6) NA NA

    Values are presented as number (%) or median (95% confidence interval). ICI, immune checkpoint inhibitor; IPI-1, ipilimumab 1 mg/kg Q3W; IPI-3, ipilimumab 3 mg/kg Q3W; IPI-10, ipilimumab 10 mg/kg Q3W; irAE, immune-related adverse event; NA, not available; NIV-1, nivolumab 1 mg/kg Q3W; NIV-3, nivolumab 3 mg/kg Q3W.

    a)p < 0.05 between the comparison of NIV1+IPI3 and NIV3+IPI1,

    b)p < 0.05 between the comparison of IPI3 and IPI10.

    Time to onset and resolution of all-grade immune-related adverse events based on cancer types

    Lung cancer Melanoma
    All categories
     No. of patients with irAE 800 (10.0) 4,359 (18.3)
      Time to onset (wk) 4.7 (4.7–5.7)a) 6.1 (5.7–7.6)a)
     No. of patients with irAE 502 (76.9) 3,222 (80.5)
      Time to resolution (wk) 4.0 (2.7–9.4) 4.4 (3.4–6.9)
    Skin
     No. of patients with irAE 270 (19.4) 1,496 (40.8)
      Time to onset (wk) 4.7 (2.9–5.7) 4.0 (2.6–5.7)
     No. of patients with resolution 178 (76.7) 1,026 (72.6)
      Time to resolution (wk) 9.4 (4.3–10.1) 10.9 (5.1–22.1)
    Gastrointestinal
     No. of patients with irAE 226 (16.2) 1,294 (35.3)
      Time to onset (wk) 4.5 (4.4–22.4) 6.3 (4.6–7.6)
     No. of patients with resolution 186 (86.5) 1,217 (94.3)
      Time to resolution (wk) 2.7 (2.3–2.9) 2.9 (2.4–3.1)
    Hepatic
     No. of patients with irAE 74 (5.3) 542 (14.8)
      Time to onset (wk) 8.0 (2.0–9.0) 8.9 (6.1–9.0)
     No. of patients with resolution 56 (83.6) 491 (90.6)
      Time to resolution (wk) 3.3 (2.0–4.0)a) 5.1 (4.4–6.1)a)
    Endocrine
     No. of patients with irAE 107 (7.7) 749 (20.4)
      Time to onset (wk) 11.2 (8.9–13.3) 8.9 (8.0–10.2)
     No. of patients with resolution 18 (52.9) 258 (53.6)
      Time to resolution (wk) 10.4 (10.4–10.4) 29.1 (13.9–54.3)
    Pulmonary
     No. of patients with irAE 25 (4.7) 77 (3.1)
      Time to onset (wk) 27.9 (4.8–27.9)a) 10.1 (8.7–10.1)a)
     No. of patients with resolution 16 (84.2) 69 (89.6)
      Time to resolution (wk) 5.9 (5.9–5.9) 6.3 (3.0–7.0)
    Renal
     No. of patients with irAE 17 (3.2) 70 (2.8)
      Time to onset (wk) 8.2 (8.2–17.8)a) 13.9 (9.7–15.7)a)
     No. of patients with resolution 6 (54.5) 54 (77.1)
      Time to resolution (wk) 10.5 (10.5–10.5)a) 2.3 (2.1–10.5)a)
    Hypersensitivity/Infusion reaction
     No. of patients with irAE 16 (3.0) 66 (3.1)
      Time to onset (wk) 0.2 (0.2–1.8)a) 3.3 (2.2–6.1)a)
     No. of patients with resolution 10 (100) 59 (89.4)
      Time to resolution (wk) 0.1 (0.1–0.1) 0.1 (0.1–0.2)
    Neurologic
     No. of patients with irAE 65 (7.5) 20 (1.7)
      Time to onset (wk) 4.0 (4.0–7.1)a) 13.1 (10.4–13.1)a)
     No. of patients with resolution 32 (49.2) 15 (75.0)
      Time to resolution (wk) 28.7 (28.7–28.9)a) 8.0 (0.7–11.6)a)

    Values are presented as number (%) or median (95% confidence interval). irAE, immune-related adverse event.

    a)p < 0.05 between the comparison of lung cancer and melanoma.

    Table 1 Baseline characteristics of the included studies

    AUC, area under the curve; AVE, avelumab; CBP, carboplatin; CTCAE, Common Terminology Criteria for Adverse Events; DDP, cisplatin; DOC, docetaxel; DTIC, dacarbazine; ETO, etoposide; ICC, investigator’s choice chemotherapy; IPI, ipilimumab; MN, multinational; NA, not available; NIV, nivolumab; PEM, pembrolizumab; PTX, paclitaxel; Q2W, every 2 weeks; Q3W, every 3 weeks; Q6W, every 6 weeks; SUN, sunitinib; VIN, vinflunine.

    The study of Kelly et al. [32] reported pooled results of phase I and phase II clinical trials with a large sample size (n=1,738); thus, the phase I trial was also included in the analysis.

    Table 2 Time to onset and resolution of all-grade irAEs based on ICI doses

    Values are presented as number (%) or median (95% confidence interval). ICI, immune checkpoint inhibitor; IPI-1, ipilimumab 1 mg/kg Q3W; IPI-3, ipilimumab 3 mg/kg Q3W; IPI-10, ipilimumab 10 mg/kg Q3W; irAE, immune-related adverse event; NA, not available; NIV-1, nivolumab 1 mg/kg Q3W; NIV-3, nivolumab 3 mg/kg Q3W.

    p < 0.05 between the comparison of NIV1+IPI3 and NIV3+IPI1,

    p < 0.05 between the comparison of IPI3 and IPI10.

    Table 3 Time to onset and resolution of all-grade immune-related adverse events based on cancer types

    Values are presented as number (%) or median (95% confidence interval). irAE, immune-related adverse event.

    p < 0.05 between the comparison of lung cancer and melanoma.


    Cancer Res Treat : Cancer Research and Treatment
    Close layer
    TOP