Trajectories of α-fetoprotein and unresectable hepatocellular carcinoma outcomes receiving atezolizumab plus bevacizumab: a secondary analysis of IMbrave150 study.

BACKGROUND: α-fetoprotein (AFP) response has been demonstrated as a biomarker for unresectable hepatocellular carcinoma (uHCC) patients receiving immunotherapy, but its definition is still unclear. This exploratory study investigated the AFP trajectory and clinical outcomes of receiving atezolizumab plus bevacizumab (Atez/Bev) therapy. METHODS: This secondary analysis used the Atez/Bev arm data of phase III IMbrave150 study to distinguish potential AFP changing rate trajectories through latent class trajectory models. The multivariable Cox models were applied to calculate adjusted hazard ratios (HRs) and 95% CIs for clinical outcomes. RESULTS: Three distinct trajectories were identified among the uHCC patients with 7 times (range, 3 to 28) of AFP measurements: low-stable (50.0%, n = 132), sharp-falling (13.3%, n = 35), and high-rising (36.7%, n = 97). Compared with the high-rising class, HRs of disease progression were 0.52 (95% CI: 0.39, 0.70) and 0.26 (95% CI: 0.16, 0.43) for the low-stable class and sharp-falling class, respectively. In contrast, HRs of death were 0.59 (95% CI: 0.40, 0.81) and 0.30 (95% CI: 0.16, 0.57) for the two groups after propensity score adjustment. Besides, AFP trajectories had the highest relative importance of each covariate to survival. DISCUSSION: There are three distinct AFP trajectories in uHCC patients receiving Atez/Bev, and it is an independent biomarker for clinical outcomes.

Development and Validation of Deep Learning Model for Intermediate-Stage Hepatocellular Carcinoma Survival with Transarterial Chemoembolization (MC-hccAI 002): a Retrospective, Multicenter, Cohort Study.

Background: There are few effective prediction models for intermediate-stage hepatocellular carcinoma (IM-HCC) patients treated with transarterial chemoembolization (TACE) to predict overall survival (OS) is available. The learning survival neural network (DeepSurv) was developed to showed a better performance than cox proportional hazards model in prediction of OS. This study aimed to develop a deep learning-based prediction model to predict individual OS. Methods: This multicenter, retrospective, cohort study examined data from the electronic medical record system of four hospitals in China between January 1, 2007, to December 31, 2016. Patients were divided into a training set(n=1075) and a test set(n=269) at a ratio of 8:2 to develop a deep learning-based algorithm (deepHAP IV). The deepHAP IV model was externally validated on an independent cohort(n=414) from the other three centers. The concordance index, the area under the receiver operator characteristic curves, and the calibration curve were used to assess the performance of the models. Results: The deepHAP IV model had a c-index of 0.74, whereas AUROC for predicting survival outcomes of 1-, 3-, and 5-year reached 0.80, 0.76, and 0.74 in the training set. Calibration graphs showed good consistency between the actual and predicted OS in the training set and the validation cohort. Compared to the other five Cox proportional-hazards models, the model this study conducted had a better performance. Patients were finally classified into three groups by X-tile plots with predicted 3-year OS rate (low: ≤ 0.11; middle: > 0.11 and ≤ 0.35; high: >0.35). Conclusion: The deepHAP IV model can effectively predict the OS of patients with IM-HCC, showing a better performance than previous Cox proportional hazards models.

Fatal Adverse Events Associated With Programmed Cell Death Ligand 1 Inhibitors: A Systematic Review and Meta-Analysis.

PURPOSE: We performed this systematic review and meta-analysis to assess the incidence of fatal adverse events that were associated with the use of programmed cell death ligand 1 (PD-L1) inhibitors, to describe them and to statistically depict factors that were associated with these events. METHOD: PubMed, Embase, and Cochrane Library were completely searched based on the following terms or relevant Medical Subject Heading ones: "atezolizumab", "durvalumab", "avelumab", and "cemiplimab". RESULTS: A total of 26 eligible studies were identified, incorporating 6,896 unique participants. The overall incidence was 1.24% (95% CI: 0.93-1.65%). The incidence and odds were higher in patients with non-squamous non-small cell lung cancer (NSCLC) than those with urothelial carcinoma [(2.25 vs. 0.85, p = 0.04), (odds ratio [OR]: 2.69; 95% CI: 1.04-6.97, p = 0.04)], higher in the middle-aged group than the young group [(1.74 vs. 0.89, p = 0.01), (OR: 2.13; 95% CI: 1.26-3.61, p = 0.01)], and higher in the trial phase I than the trial phase II [(1.76 vs. 0.60, p = 0.01), (OR: 0.31; 95% CI: 0.13-0.75, p = 0.01)]. Notably, the trial phase I had a higher incidence than trial phase II or III following regulating for cancer types and average age (OR: 0.28; 95% CI: 0.11-0.71, p = 0.01, OR: 0.48; 95% CI: 0.24-0.95, p = 0.04, respectively). In terms of organ-specific fatal adverse events, interstitial lung disease (ILD) was frequently documented. A variety of respiratory system-related fatal adverse events were recorded, including but not limited to pneumonia and respiratory failure. As for organ-unspecific fatal adverse events, substantial cases of sepsis and neutropenia were recorded. CONCLUSION: This study firstly provided a comprehensive incidence and the spectrum of fatal adverse events associated with PD-L1 inhibitors, and identified three potential susceptible factors of that, yielding a capability for clinicians to distinguish high-risk populations from relatively low-risk ones, and facilitating to improve the safety of PD-L1 inhibitors broadly used in the clinical setting.

Association of antibiotic exposure with the mortality in metastatic colorectal cancer patients treated with bevacizumab-containing chemotherapy: A hospital-based retrospective cohort study.

BACKGROUND: Preclinical studies showed that antibiotic exposure played a role in clinical outcomes in patients with chemotherapy via modulation of microbiota. However, it remains unknown whether antibiotic exposure during the bevacizumab therapy affects the clinical outcomes in metastatic colorectal cancer(mCRC) patients. This study aimed to examine the association between the antibiotic medication and the clinical outcomes in mCRC patients with bevacizumab therapy. METHODS: This retrospective cohort analysis included 147 mCRC patients treated with bevacizumab. The hazard ratio of death was estimated using three Cox proportional hazards models with (1) never vs ever; (2) never vs 1-6 days and 7-40 days;(3) increase per day, and further tested using propensity score matching (PSM) and landmark analysis. A smooth curve technique was used to explore the shape of dose-response relationship. RESULTS: Compared with the non-antibiotic group, antibiotic exposure was inversely associated with the mortality in the antibiotic group after adjustment for demographic and other potential confounders (a history of medication: HR, 0.650(95%CI: 0.360 to 1.173); an increase per day: HR, 0.967(CI: 0.924 to 1.011); 1-6 days: HR, 0.859(CI: 0.441 to 1.674); 7-40 days: HR, 0.474(CI: 0.225 to 0.999); P for trend = 0.040). A test for the interaction between sex was statistically significant (p = 0.016). A similar result was found as measured by landmark and PSM analysis. Significant negative dose-response relationship was shown by smooth curve analysis in the male patients but not female after adjustment for confounders(p = 0.028). No association was found between the antibiotic medication and adverse events of bevacizumab. CONCLUSION: Antibiotic exposure could be inversely associated with the mortality in mCRC patients treated with bevacizumab.