Prognostic value of inflammation-immunity-nutrition score in patients with hepatocellular carcinoma treated with anti-PD-1 therapy

Prognostic significance of pan-immune-inflammation value in hepatocellular carcinoma treated by curative radiofrequency ablation: potential role for individualized adjuvant systemic treatment

BACKGROUND

This study aimed to explore the prognostic role of pan-immune-inflammation value (PIV) and develop a new risk model to guide individualized adjuvant systemic treatment following radiofrequency ablation (RFA) for early-stage hepatocellular carcinoma (HCC).

MATERIALS AND METHODS

Patients with early-stage HCC treated by RFA were randomly divided into training cohort A (n = 65) and testing cohort B (n = 68). Another 265 counterparts were enrolled into external validating cohort C. Various immune-inflammatory biomarkers (IIBs) were screened in cohort A. Prognostic role of PIV was evaluated and validated in cohort B and C, respectively. A nomogram risk model was built in cohort C and validated in pooled cohort D. Clinical benefits of adjuvant anti-angiogenesis therapy plus immune checkpoint inhibitor (AA-ICI) following RFA was assessed in low- and high-risk groups.

RESULTS

The cutoff point of PIV was 120. High PIV was an independent predictor of unfavorable recurrence-free survival (RFS) and overall survival (OS). RFS and OS rates of patients with high PIV were significantly lower than those with low PIV both in cohort B (PRFS=0.016, POS=0.011) and C (PRFS<0.001, POS<0.001). The nomogram model based on PIV, tumor number and BCLC staging performed well in risk stratification in external validating cohort C. Adjuvant AA-ICI treatment showed an added benefit in OS (p = 0.011) for high-risk patients.

CONCLUSIONS

PIV is a feasible independent prognostic factor for RFS and OS in early-stage HCC patients who received curative RFA. The proposed PIV-based nomogram risk model could help clinicians identify high-risk patients and tailor adjuvant systemic treatment and disease follow-up scheme.

Prognostic biomarkers associated with immune checkpoint inhibitors in hepatocellular carcinoma

The treatment of hepatocellular carcinoma (HCC), particularly advanced HCC, has been a serious challenge. Immune checkpoint inhibitors (ICIs) are landmark drugs in the field of cancer therapy in recent years, which have changed the landscape of cancer treatment. In the field of HCC treatment, this class of drugs has shown good therapeutic prospects. For example, atezolizumab in combination with bevacizumab has been approved as first-line treatment for advanced HCC due to significant efficacy. However, sensitivity to ICI therapy varies widely among HCC patients. Therefore, there is an urgent need to search for determinants of resistance/sensitivity to ICIs and to screen biomarkers that can predict the efficacy of ICIs. This manuscript reviews the research progress of prognostic biomarkers associated with ICIs in HCC in order to provide a scientific basis for the development of clinically individualised precision medication regimens.

A Nomogram Model Based on the Inflammation-Immunity-Nutrition Score (IINS) and Classic Clinical Indicators for Predicting Prognosis in Extranodal Natural Killer/T-Cell Lymphoma

Background

Systemic inflammation, immunity, and nutritional status are closely related to patients' outcomes in several kinds of cancers. This study aimed to establish a new nomogram based on inflammation-immunity-nutrition score (IINS) to predict the prognosis of extranodal natural killer/T-cell lymphoma (ENKTL) patients.

Methods

The clinical data of 435 patients with ENTKL were retrospectively reviewed and randomly assigned to training cohort (n=305) and validation cohort (n=131) at a ratio of 7:3. Cox regression analysis was employed to identify independent prognostic factors and develop a nomogram in the training cohort. Harrell's concordance index (C-index), calibration curve, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA) curve were employed to assess the performance of the nomogram and compare it with traditional prognostic systems (PINK, IPI, KPI). Internal validation was performed using 1000 bootstrap resamples in the validation cohort. Kaplan-Meier survival analyses were conducted to compare the overall survival (OS) of patients in different risk groups.

Results

In the training cohort, in addition to several classic parameters, IINS was identified as an independent prognostic factor significantly associated with the OS of patients. The nomogram established based on the independent prognostic indicators showed superior survival prediction efficacy, with C-index of 0.733 in the training cohort and 0.759 in the validation cohort compared to the PINK (0.636 and 0.737), IPI (0.81 and 0.707), and KPI (0.693 and 0.639) systems. Furthermore, compared with PINK, IPI, and IPI systems, the nomogram showed relatively superior calibration curves and more powerful prognostic discrimination ability in predicting the OS of patients. DCA curves revealed some advantages in terms of clinical applicability of the nomogram compared to the PINK, IPI, and IPI systems.

Conclusion

Compared with traditional prognostic systems, the nomogram showed promising prospects for risk stratification in ENKTL patient prognosis, providing new insights into the personalized treatment.

Nomogram for predicting survival in patients with advanced hepatocellular carcinoma treated with PD-1 inhibitors: incorporating pre-treatment and post-treatment clinical parameters

BACKGROUND

Immunotherapy has transformed cancer treatment patterns for advanced hepatocellular carcinoma (aHCC) in recent years. Therefore, the identification of predictive biomarkers has important clinical implications.

METHODS

We collected medical records from 117 aHCC patients treated with anti-PD-1 antibody. Kaplan-Meier analysis and Cox proportional hazard regression were used to evaluate the association between peripheral blood biomarkers and overall survival (OS) and progression-free survival (PFS). Finally, the prognostic nomogram was constructed.

RESULTS

The mPFS and mOS were 7.0 months and 18.7 months, respectively. According to Kaplan-Meier analysis and Cox regression analysis, we regarded the treatment regimen (p = 0.020), hemoglobin (Hb) at 6-week (p = 0.042), neutrophil-to-lymphocyte ratio (NLR) at 6-week (p < 0.001), system immune inflammation index (SII) at 6-week (p = 0.125) as predictors of PFS, and alpha fetoprotein (AFP) (p = 0.035), platelet-to-lymphocyte ratio (PLR) (p = 0.012), Hb at 6-week (p = 0.010) and NLR at 6-week (p = 0.020) as predictors of OS. Furthermore, the results suggest that the OS and PFS nomogram model were in agreement with actual observations.

CONCLUSION

Biomarkers in peripheral blood can predict the prognosis of patients with aHCC treated with anti-PD-1 antibody. The development of nomogram models can help us to screen potential patients who can benefit from immunotherapy.

Blood biomarkers predict outcomes in patients with hepatocellular carcinoma treated with immune checkpoint Inhibitors: A pooled analysis of 44 retrospective sudies

OBJECTIVE

We conducted the first meta-analysis to identify the predictive significance of baseline blood biomarkers (such as neutrophil to lymphocyte ratio (NLR), early alpha-fetoprotein (AFP) response, albumin-bilirubin (ALBI), AFP, platelet to lymphocyte ratio (PLR), C-reactive protein (CRP), protein induced by vitamin K absence II (PIVKA-II), and lymphocyte to monocyte ratio (LMR)) in hepatocellular carcinoma (HCC) patients treated with immune checkpoint inhibitors (ICIs).

METHODS

Eligible articles were retrieved using PubMed, the Cochrane Library, EMBASE, and Google Scholar by November 24, 2022. Clinical outcomes were overall survival (OS), progression-free survival (PFS), objective response rate (ORR), disease control rate (DCR), and hyperprogressive disease (HPD).

RESULTS

A total of 44 articles with 5322 patients were included in this meta-analysis. The pooled results demonstrated that patients with high NLR levels had significantly poorer OS (HR: 1.951, P < 0.001) and PFS (HR: 1.632, P < 0.001), lower ORR (OR: 0.484, P < 0.001) and DCR (OR: 0.494, P = 0.027), and higher HPD (OR: 8.190, P < 0.001). The patients with high AFP levels had shorter OS (HR: 1.689, P < 0.001) and PFS (HR: 1.380, P < 0.001), and lower DCR (OR: 0.440, P < 0.001) than those with low AFP levels, however, there was no difference in ORR (OR: 0.963, P = 0.933). We also found that early AFP response was correlated with better OS (HR: 0.422, P < 0.001) and PFS (HR: 0.385, P < 0.001), higher ORR (OR: 7.297, P < 0.001) and DCR (OR: 13.360, P < 0.001) compared to non-responders. Besides, a high ALBI grade was significantly related to shorter OS (HR: 2.440, P = 0.009) and PFS (HR: 1.373, P = 0.022), lower ORR (OR: 0.618, P = 0.032) and DCR (OR: 0.672, P = 0.049) than those with an ALBI grade 1.

CONCLUSION

The NLR, early AFP response, and ALBI were useful predictors of outcomes in HCC patients treated with ICIs.

The association between albumin levels and survival in patients treated with immune checkpoint inhibitors: A systematic review and meta-analysis

Background: The albumin levels may potentially be used as a prognostic biomarker in patients with cancertreated with immune checkpoint inhibitors (ICIs) due to its close relationship with nutritional and inflammatory status. However, the available data is limited with heterogeneous patient cohorts, sample sizes and variable cut-offs. Therefore, we conducted a systematic review and meta-analysis to evaluate the association between survival outcomes and albumin levels in patients treated with ICIs. Methods: We conducted a systematic review using the PubMed, Web of Science, and Embase databases to filter the published studies up to 1 June 2022. The meta-analyses were performed with the generic inverse-variance method with a random-effects model due to the high degree of heterogeneity. The primary outcome measure was hazard ratio (HR) with 95% confidence intervals (CI). The study protocol was registered with the PROSPERO registry (Registration Number: CRD42022337746). Results: Thirty-six studies encompassing 8406 cancer patients with advanced disease were included in the meta-analyses. Almost half of the studies were conducted in NSCLC cohorts (n = 15), and 3.5 gr/dL was the most frequently used albumin cut-off in the included studies (n = 20). Patients with lower albumin levels had a significantly increased risk of death (HR: 1.65, 95% CI: 1.52-1.80, p < 0.0001) than patients with higher albumin levels. Subgroup analyses for study location, sample size, tumor type and albumin cut-off were demonstrated consistent results. Furthermore, in the subgroup analysis of eight studies using albumin levels as a continuous prognostic factor, every 1 gr/dL decrease in albumin levels was associated with significantly increased risk of death by a factor of 10% (HR: 1.10, 95% CI: 1.05-1.16, p = 0.0002). Similar to analyses with overall survival, the patients with lower albumin levels had an increased risk of progression or death compared to patients with higher albumin levels (HR: 1.76, 95% CI: 1.40-2.21, p < 0.001). Conclusion: The available evidence demonstrates that albumin levels may be a prognostic biomarker in advanced cancer patients treated with ICIs. Further research is needed to delineate the role of albumin levels in patients treated with ICIs in the adjuvant setting, as well as the possible benefit of therapeutic approaches to improve hypoalbuminemia.

Prognostic Value of Inflammation-Immunity-Nutrition Score and Inflammatory Burden Index for Hepatocellular Carcinoma Patients After Hepatectomy

PURPOSE

The study aimed to investigate the ability of inflammation-immunity-nutrition score (IINS) and inflammatory burden index (IBI), individually or in combination, to predict prognosis of hepatocellular carcinoma (HCC) patients after hepatectomy.

METHODS

A total of 701 patients who underwent HCC resection at Guangxi Medical University Cancer Hospital were enrolled in the study. An IINS ranging from 0 to 3 was defined based on preoperative C-reactive protein (CRP), lymphocyte count, and serum albumin level, while an IBI was based on CRP and neutrophil-to-lymphocyte ratio. The prognostic value of IINS and IBI was assessed using univariate and multivariate Cox regression and Kaplan-Meier survival curves. The concordance index and calibration curve were used for internal validation of models. Decision curve analysis, net reclassification index and integrated discrimination improvement were used to compare the predictive performance of the models with traditional staging systems.

RESULTS

IINS and IBI were able to predict poor prognosis in HCC patients after hepatectomy, and a nomogram based on the IINS predicted survival at 1, 3, and 5 years better than other models or traditional staging systems.

CONCLUSION

IINS may be accurate predictors of survival in HCC patients after hepatectomy, with potentially greater prognostic value than conventional markers.

Blood-based biomarkers for immune-based therapy in advanced HCC: Promising but a long way to go

The introduction of immune checkpoint inhibitors (ICIs) represents a key shift in the management strategy for patients with hepatocellular carcinoma (HCC). However, there is a paucity of predictive biomarkers that facilitate the identification of patients that would respond to ICI therapy. Although several researchers have attempted to resolve the issue, the data is insufficient to alter daily clinical practice. The use of minimally invasive procedures to obtain patient-derived specimen, such as using blood-based samples, is increasingly preferred. Circulating tumor DNA (ctDNA) can be isolated from the blood of cancer patients, and liquid biopsies can provide sufficient material to enable ongoing monitoring of HCC. This is particularly significant for patients for whom surgery is not indicated, including those with advanced HCC. In this review, we summarize the current state of understanding of blood-based biomarkers for ICI-based therapy in advanced HCC, which is promising despite there is still a long way to go.