ObjectiveTo provide a complete toxicity profile, toxicity spectrum, and a safety ranking of immune checkpoint inhibitor (ICI) drugs for treatment of cancer.DesignSystematic review and network meta-analysis.Data sourcesElectronic databases (PubMed, Embase, Cochrane Library, and Web of Science) were systematically searched to include relevant studies published in English between January 2007 and February 2018.Review methodsOnly head-to-head phase II and III randomised controlled trials comparing any two or three of the following treatments or different doses of the same ICI drug were included: nivolumab, pembrolizumab, ipilimumab, tremelimumab, atezolizumab, conventional therapy (chemotherapy, targeted therapy, and their combinations), two ICI drugs, or one ICI drug with conventional therapy. Eligible studies must have reported site, organ, or system level data on treatment related adverse events. High quality, single arm trials and placebo controlled trials on ICI drugs were selected to establish a validation group.Results36 head-to-head phase II and III randomised trials (n=15 370) were included. The general safety of ICI drugs ranked from high to low for all adverse events was as follows: atezolizumab (probability 76%, pooled incidence 66.4%), nivolumab (56%, 71.8%), pembrolizumab (55%, 75.1%), ipilimumab (55%, 86.8%), and tremelimumab (54%, not applicable). The general safety of ICI drugs ranked from high to low for severe or life threatening adverse events was as follows: atezolizumab (49%, 15.1%), nivolumab (46%, 14.1%), pembrolizumab (72%, 19.8%), ipilimumab (51%, 28.6%), and tremelimumab (28%, not applicable). Compared with conventional therapy, treatment-related adverse events for ICI drugs occurred mainly in the skin, endocrine, hepatic, and pulmonary systems. Taking one ICI drug was generally safer than taking two ICI drugs or one ICI drug with conventional therapy. Among the five ICI drugs, atezolizumab had the highest risk of hypothyroidism, nausea, and vomiting. The predominant treatment-related adverse events for pembrolizumab were arthralgia, pneumonitis, and hepatic toxicities. The main treatment-related adverse events for ipilimumab were skin, gastrointestinal, and renal toxicities. Nivolumab had a narrow and mild toxicity spectrum, mainly causing endocrine toxicities. Integrated evidence from the pooled incidences, subgroup, and sensitivity analyses implied that nivolumab is the best option in terms of safety, especially for the treatment of lung cancer.ConclusionsCompared with other ICI drugs used to treat cancer, atezolizumab had the best safety profile in general, and nivolumab had the best safety profile in lung cancer when taking an integrated approach. The safety ranking of treatments based on ICI drugs is modulated by specific treatment-related adverse events.Systematic review registrationPROSPERO CRD42017082553.

Purpose: We aimed to evaluate the value of deep learning on positron emission tomography with computed tomography (PET/CT)-based radiomics for individual induction chemotherapy (IC) in advanced nasopharyngeal carcinoma (NPC). Experimental Design: We constructed radiomics signatures and nomogram for predicting disease-free survival (DFS) based on the extracted features from PET and CT images in a training set (n ¼ 470), and then validated it on a test set (n ¼ 237). Harrell's concordance indices (C-index) and time-independent receiver operating characteristic (ROC) analysis were applied to evaluate the discriminatory ability of radiomics nomogram, and compare radiomics signatures with plasma Epstein-Barr virus (EBV) DNA. Results: A total of 18 features were selected to construct CT-based and PET-based signatures, which were significantly associated with DFS (P < 0.001). Using these signatures , we proposed a radiomics nomogram with a C-index of 0.754 [95% confidence interval (95% CI), 0.709-0.800] in the training set and 0.722 (95% CI, 0.652-0.792) in the test set. Consequently, 206 (29.1%) patients were stratified as high-risk group and the other 501 (70.9%) as low-risk group by the radiomics nomogram, and the corresponding 5-year DFS rates were 50.1% and 87.6%, respectively (P < 0.0001). High-risk patients could benefit from IC while the low-risk could not. Moreover, radiomics nomogram performed significantly better than the EBV DNA-based model (C-index: 0.754 vs. 0.675 in the training set and 0.722 vs. 0.671 in the test set) in risk stratification and guiding IC. Conclusions: Deep learning PET/CT-based radiomics could serve as a reliable and powerful tool for prognosis prediction and may act as a potential indicator for individual IC in advanced NPC.

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Purpose:To evaluate the prognostic value of variables including nodal size, level, laterality, extranodal neoplastic spread (ENS), and necrosis in patients with nasopharyngeal carcinoma (NPC) and further explore the feasibility of an N-staging system using Radiation Therapy Oncology Group (RTOG) guidelines for lymph node levels based on magnetic resonance imaging (MRI). Experimental Design: The MRI scans of 924 patients with histologically diagnosed nondisseminated NPC were reviewed retrospectively. The distribution of the tumors was mapped using RTOG guidelines and laterality. The multiplicity of each tumor was calculated, as well as the size and status of ENS and the necrosis of individual nodes. Results: Nodal level, cervical lymph node laterality, and ENS were independent prognostic factors for disease failure and distant failure in multivariate analyses. There was no significant difference in the hazard ratios (HR) for distant failure between level II and retropharyngeal, level Ib, levelV, or level III involvement, whereas patients with level IVand supraclavicular fossa involvement had a significant increase in HRs. The subsets that made up a given N stage group had similar HRs for distant failure. Both the HRs for disease failure and distant failure by the proposed N staging system between one stage and the next were statistically significant (P < 0.05). The survival curves of disease-free survival and distant metastasis-free survival for all subclassifications of N stage showed significant difference from the adjacent stage (P < 0.05). The overall distribution pattern of the proposed N staging was more equitable than that of the 6th American Joint Committee on Cancer N staging. Conclusions: Nodal variables including level, cervical lymph node laterality, and ENS are independent prognostic factors for NPC. The proposed N staging system of NPC using RTOG guidelines based on MRI is highly predictive and may provide a more objective method for staging NPCs.

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