Background and aims: Hepatocellular carcinoma (HCC) with portal vein tumor thrombus (PVTT) predicts a poor prognosis. The aim of the present study was to evaluate the efficacy and safety of using lenvatinib and camrelizumab combined with transarterial chemoembolization (TACE) to treat HCC with PVTT.Methods: This was a single‐arm, open‐label, multicenter, and prospective study. Eligible patients with advanced HCC accompanied by PVTT were enrolled to receive TACE combined with lenvatinib and camrelizumab. The primary endpoint was progression‐free survival (PFS), while the secondary endpoints included objective response rate (ORR), disease control rate (DCR), overall survival (OS), and safety.Results: Between April 2020 and April 2022, 69 patients were successfully enrolled. With a median follow‐up time of 17.3 months, the median age of the patient cohort was 57 years (range: 49–64 years). According to modified Response Evaluation Criteria in Solid Tumors, the ORR was 26.1% (18 partial responses [PRs]) and the DCR was 78.3% (18 PRs, 36 stable diseases [SDs]). The median PFS (mPFS) and median OS (mOS) were 9.3 and 18.2 months, respectively. And tumor number >3 was identified as an adverse risk factor for both PFS and OS. The most common adverse events across all grades included fatigue (50.7%), hypertension (46.4%), and diarrhea (43.5%). Twenty‐four patients (34.8%) experienced Grade 3 toxicity that was relieved by dose adjustment and symptomatic treatment. No treatment‐related deaths occurred.Conclusions: TACE combined with lenvatinib and camrelizumab is a well‐tolerated modality treatment with promising efficacy for advanced HCC with PVTT.

Objective: To describe and analyze the predictive models of the prognosis of patients with hepatocellular carcinoma (HCC) undergoing systemic treatment. Design: Systematic review. Data sources: PubMed and Embase until December 2020 and manually searched references from eligible articles. Eligibility criteria for study selection: The development, validation, or updating of prognostic models of patients with HCC after systemic treatment. Results: The systematic search yielded 42 eligible articles: 28 articles described the development of 28 prognostic models of patients with HCC treated with systemic therapy, and 14 articles described the external validation of 32 existing prognostic models of patients with HCC undergoing systemic treatment. Among the 28 prognostic models, six were developed based on genes, of which five were expressed in full equations; the other 22 prognostic models were developed based on common clinical factors. Of the 28 prognostic models, 11 were validated both internally and externally, nine were validated only internally, two were validated only externally, and the remaining six models did not undergo any type of validation. Among the 28 prognostic models, the most common systemic treatment was sorafenib (n = 19); the most prevalent endpoint was overall survival (n = 28); and the most commonly used predictors were alpha-fetoprotein (n = 15), bilirubin (n = 8), albumin (n = 8), Child–Pugh score (n = 8), extrahepatic metastasis (n = 7), and tumor size (n = 7). Further, among 32 externally validated prognostic models, 12 were externally validated > 3 times. Conclusions: This study describes and analyzes the prognostic models developed and validated for patients with HCC who have undergone systemic treatment. The results show that there are some methodological flaws in the model development process, and that external validation is rarely performed. Future research should focus on validating and updating existing models, and evaluating the effects of these models in clinical practice. Systematic review registration: PROSPERO CRD42020200187.

Lenvatinib is a first-line agent for advanced hepatocellular carcinoma (HCC), but individual responses to treatment are highly heterogeneous. The aim of this study was to investigate the clinical parameters that influence the efficacy of Lenvatinib and to develop a prognostic model. We retrospectively enrolled 333 Lenvatinib-treated patients with HCC with a median age of 57 years. Two hundred nd sixty-three of these patients had BCLC (2022) stage C. The median overall survival (mOS) time within the cohort was 12.1 months, and the median progression-free survival (mPFS) time was 4.7 months. Univariate Cox regression, best subset regression, and Lasso regression were used to screen primary variables for possible contribution to OS, multivariate Cox analysis was used to fit selected models, and the final model was selected using the maximum area under the curve (AUC) and minimum AIC. Receiver operating curves (ROC), calibration curves, and decision curve analysis were plotted to assess model performance, and 5-fold cross-validation was performed for internal validation. X-tile software was used to select the best cutoff points and to divide the study cohort into 3 different risk groups. Seven variables were included in the final model: BCLC stage, prior transarterial chemoembolization and immunotherapy history, tumor number, prognostic nutritional index, log (alpha-fetoprotein), and log (platelet-to-lymphocyte ratio). We named this final model the “multivariate prognostic model for Lenvatinib” (MPML), and a nomogram was constructed to predict the probability of survival at 6, 9, and 12 months. The MPML had good discrimination, calibration, and applicability. Cross-validation showed mean AUC values of 0.7779, 0.7738, and 0.7871 at 6, 9, and 12 months, respectively. According to nomogram points, mOS time was 21.57, 8.70, and 5.37 months in the low, medium, and high-risk groups, respectively (P < .001), and these differences were also observed in the PFS survival curve (P < .001). The MPML stratified patients according to baseline clinical characteristics had a strong performance in predicting Lenvatinib efficacy and has the potential for use as an auxiliary clinical tool for individualized decision-making.

Background: Currently, there are a few treatment options for unresectable hepatocellular carcinoma (HCC) after progression following sorafenib (SOR) therapy, but with limited benefit. The purpose of this study was to investigate the efficacy and safety of tyrosine kinase inhibitors (TKIs) combined with immune checkpoint inhibitors (ICIs) as second-line treatment. Methods: From May 2018 to May 2021, a total of 93 HCCs who failed SOR treatment were included in this study and divided into TKI group (n = 37) and TKI-ICI group (n = 56). Overall survival (OS), progression-free survival (PFS), objective response rate (ORR), disease control rate (DCR) and safety were estimated among the two groups. In addition, univariate and multivariate Cox regression analyses were performed for OS and PFS to identify possible prognostic factors. Results: With a median follow-up time of 13.7 months, the median age of patients was 56 (range, 50–64) years and most were male. All of the patients were hepatitis virus-related HCC. Both median OS (7.63 months vs 19.23 months, P < 0.001) and median PFS (2.97 months vs 8.63 months, P < 0.001) were significantly improved in the TKI-ICI group compared to the TKI group. A significant increase in DCR was demonstrated in the TKI-ICI group compared to the TKI group (83.9% vs 45.9%, P = 0.0003), although no significant difference in ORR was reported (21.4% vs 8.1%, P = 0.1552). Multivariate Cox regression analysis of OS and PFS revealed that second-line regimen was an independent protective factor affecting death and progression in HCCs after SOR failure. In addition, Child–Pugh B7 was an independent risk factor of OS. Finally, there was no significant difference in the incidence of any grade or grade 3/4 adverse events (AEs) between the two groups, and no treatment-related deaths were observed. Conclusion: This real-world study suggests that the combination of TKIs and ICIs benefits more than mono-TKIs and is well tolerated in HCCs with hepatitis virus infection after SOR failure.

Background: Neoadjuvant chemoimmunotherapy (NACI) is promising for resectable nonsmall cell lung cancer (NSCLC), but predictive biomarkers are still lacking. The authors aimed to develop a model based on pretreatment parameters to predict major pathological response (MPR) for such an approach. Methods: The authors enrolled operable NSCLC treated with NACI between March 2020 and May 2023 and then collected baseline clinical-pathology data and routine laboratory examinations before treatment. The efficacy and safety data of this cohort was reported and variables were screened by Logistic and Lasso regression and nomogram was developed. In addition, receiver operating characteristic curves, calibration curves, and decision curve analysis were used to assess its power. Finally, internal cross-validation and external validation was performed to assess the power of the model. Results: In total, 206 eligible patients were recruited in this study and 53.4% (110/206) patients achieved MPR. Using multivariate analysis, the predictive model was constructed by seven variables, prothrombin time (PT), neutrophil percentage (NEUT%), large platelet ratio (P-LCR), eosinophil percentage (EOS%), smoking, pathological type, and programmed death ligand-1 (PD-L1) expression finally. The model had good discrimination, with area under the receiver operating characteristic curve (AUC) of 0.775, 0.746, and 0.835 for all datasets, cross-validation, and external validation, respectively. The calibration curves showed good consistency, and decision curve analysis indicated its potential value in clinical practice. Conclusion: This real world study revealed favorable efficacy in operable NSCLC treated with NACI. The proposed model based on multiple clinically accessible parameters could effectively predict MPR probability and could be a powerful tool in personalized medication.

Background: Immune checkpoint inhibitors (ICIs) bring significant clinical benefits to non-small-cell lung cancer (NSCLC), and convenient peripheral blood markers are still lacking. Human circulating cytokines play an important role in tumor growth and metastasis, and exploring their value in NSCLC immunotherapy helps to achieve precise treatment of patients. Methods: This study was a mixed design of prospective blood collection and retrospective data collection. Patients with NSCLC who received the first ICI combined with chemotherapy were included, and plasma samples were collected at baseline and after 2 cycles of treatment. MILLIPLEX MAP technology was used to detect the levels of a panel of cancer biomarkers and to explore the predictive potential of cytokines for survival and treatment response in such patients. Results: Baseline blood samples were collected from 79 NSCLC patients in this study, and survival analysis showed that high expression of 4 cytokines, carbohydrate antigen 125 (CA125), cytokeratin 19 fragment (CYFRA 21-1), human epididymis protein 4 (HE4), and hepatocyte growth factor (HGF), was associated with shorter overall survival (OS) and progression-free survival (PFS), low levels of stem cell factor (SCF) tended to have better OS than patients with high levels of SCF, and multivariate Cox regression showed that high levels of HGF were independent risk factors for OS (HR = 1.92, 95% CI: 1.02-3.70, P = .042) and PFS (HR = 3.23, 95% CI: 1.75-5.88, P < .001). HGF was more predictive of 1-year survival and 6-month PFS than programmed death ligand 1 expression. In addition, we collected blood samples from 53 patients after 2 cycles of treatment, CYFRA 21-1, HGF, interleukin-8 (IL-8), and tumor necrosis factor-related apoptosis-inducing ligand were associated with patient survival, and patients with increased HGF after treatment had shorter survival. In patients whose tumors responded to treatment, CA125 and CYFRA 21-1 levels increased from baseline, whereas soluble apoptosis-related factor (sFas) levels decreased. Conclusions: Soluble cytokines, especially HGF, have certain clinical value in immunotherapy combination therapy and prognosis of NSCLC patients and are worthy of validation in a larger prospective cohort and exploration of their potential mechanisms.