Pretreatment absolute lymphocyte count is an independent predictor for survival outcomes for esophageal squamous cell carcinoma patients treated with neoadjuvant chemoradiotherapy and pembrolizumab: An analysis from a prospective cohort

Prognostic value of systemic inflammation response index in cancer patients treated with PD-1/PD-L1 immune checkpoint inhibitors: a meta-analysis

BACKGROUND

The prognostic significance of the systemic inflammatory response index (SIRI) in patients with cancer receiving programmed cell death 1 (PD-1)/PD-1 ligand 1 (PD-L1) immune checkpoint inhibitors (ICIs) has been widely investigated; however, the results have been conflicting. As such, the present meta-analysis aimed to analyze the precise significance of the SIRI in predicting prognosis in patients with cancer undergoing ICI therapy.

METHODS

A comprehensive literature search of the Web of Science, PubMed, Embase, and Cochrane Library databases for relevant studies, published from inception to April 25, 2024, was performed. The SIRI was analyzed for its prognostic utility in patients undergoing ICI therapy by calculating combined hazard ratios (HRs) and corresponding 95% confidence intervals (CIs).

RESULTS

Six studies comprising 1133 patients were included in the analysis. Pooled data revealed that a higher SIRI was significantly associated with poor overall survival (OS) (HR 1.96 [95% CI 1.55-2.47]; p < 0.001) and progression-free survival (PFS) (HR 1.41 [95% CI 1.19-1.67]; p < 0.001) for patients who underwent PD-1/PD-L1 ICI treatment. Subgroup analysis revealed that SIRI was markedly associated with dismal OS and PFS, independent of sample size, cut-off value, and survival analysis (p < 0.05). The findings were verified to be robust against publication bias and sensitivity analyses.

CONCLUSION

In summary, an elevated SIRI was significantly associated with OS and PFS in patients with cancer undergoing PD-1/PD-L1 ICI treatment. SIRI may a candidate indicator for predicting the prognosis of patients undergoing ICI therapy.

The efficacy of neoadjuvant immunotherapy and lymphocyte subset predictors in locally advanced esophageal squamous cell carcinoma: A retrospective study

BACKGROUND

Despite the recognized therapeutic potential of programmed cell death protein 1/programmed death-ligand 1 (PD-1/PD-L1) inhibitors in advanced esophageal squamous cell carcinoma (ESCC), their role in neoadjuvant therapy and reliable efficacy biomarkers remain elusive.

MATERIALS AND METHODS

We retrospectively analyzed locally advanced ESCC patients who underwent surgery following a 2-cycle platinum and paclitaxel-based treatment, with or without PD-1 inhibitors (January 2020-March 2023). We assessed peripheral blood indexes and tertiary lymphoid structures (TLS) density to evaluate their impact on pathological response and prognosis, leading to a clinical prediction model for treatment efficacy and survival.

RESULTS

Of the 157 patients recruited, 106 received immunochemotherapy (ICT) and 51 received chemotherapy (CT) alone. The ICT group demonstrated a superior pathological response rate (PRR) (47.2% vs. 29.4%, p = 0.034) with comparable adverse events and postoperative complications. The ICT group also showed a median disease-free survival (DFS) of 39.8 months, unattained by the CT group. The 1-year DFS and overall survival (OS) rates were 73% and 91% for the ICT group, and 68% and 81% for the CT group, respectively. We found higher baseline activated T cells, lower baseline Treg cells, and a decreased posttreatment total lymphocyte and CD4+/CD8+ ratio predicted an enhanced PRR. Reduced posttreatment CD4+/CD8+ ratio and increased NK cells were associated with prolonged survival, while higher TLS density indicated poorer prognosis. Among ICT group, a lower posttreatment CD4+/CD8+ ratio indicated longer DFS and reduced posttreatment B cells indicated longer OS. A nomogram integrating these predictors was developed to forecast treatment efficacy and survival.

CONCLUSION

The combination of PD-1 inhibitors and chemotherapy appears promising for locally advanced ESCC. Evaluating the differentiation status and dynamic changes of peripheral blood immune cells may provide valuable predictive insights into treatment efficacy and prognosis.

The addition of pembrolizumab to neoadjuvant chemoradiotherapy did not increase the risk of developing postoperative anastomotic leakage for ESCC: an analysis from a prospective cohort

BACKGROUND

To compare the difference of postoperative anastomotic leakage (AL) rate between neoadjuvant chemoradiotherapy (NCRT) with pembrolizumab and NCRT group, and investigate the risk factors of developing AL for locally advanced esophageal squamous cell cancer (ESCC).

MATERIALS AND METHODS

The GF was contoured on the pretreatment planning computed tomography and dosimetric parameters were retrospectively calculated. Univariate and multivariate logistic regression analysis was performed to determine the independent risk predictors for the entire cohort. A nomogram risk prediction model for postoperative AL was established.

RESULTS

A total of 160 ESCC patients were included for analysis. Of them, 112 were treated with NCRT with pembrolizumab and 44 patients with NCRT. Seventeen (10.6%) patients experienced postoperative AL with a rate of 10.7% (12/112) in NCRT with pembrolizumab and 11.4% (5/44) in NCRT group. For the entire cohort, mean, D50, Dmax, V5, V10 and V20 GF dose were statistically higher in those with AL (all p < 0.05). Multivariate logistic regression analysis indicated that tumor length (p = 0.012), volume of GF (p = 0.003) and mean dose of GF (p = 0.007) were independently predictors for postoperative AL. Using receiver operating characteristics analysis, the mean dose limit on the GF was defined as 14 Gy.

CONCLUSION

Based on our prospective database, no significant difference of developing AL were observed between NCRT with pembrolizumab and NCRT group. We established an individualized nomograms based on mean GF dose combined with clinical indicators to predict AL in the early postoperative period.

The Neutrophil-to-Lymphocyte Ratio as a Biomarker in Cutaneous Oncology: A Systematic Review of Evidence beyond Malignant Melanoma

With the ongoing progress of basic research along with the introduction of new pharmaceutical options spanning almost all therapeutic areas, the need for biomarkers that will be implemented into the personalized medical approach is higher than ever. Their use can be incorporated into clinical practice and can be applied to the classification of disorders and the evaluation of disease severity but also to the monitoring of the progress of therapeutic/pharmaceutical interventions. This systematic review collects the findings of hematologic biomarkers in various cutaneous malignancies, excluding malignant melanoma, to support their potential use in the prognosis but also in the assessment of therapeutic strategies for the specific category of skin disorders.

Pan-immune inflammation value as a prognostic biomarker for cancer patients treated with immune checkpoint inhibitors

Background

Immune checkpoint inhibitors (ICIs) represent a paradigm shift in the development of cancer therapy. However, the improved efficacy of ICIs remains to be further investigated. We conducted a systematic review and meta-analysis to evaluate the pan-immunoinflammatory value (PIV) and PILE score used to predict response to ICI therapy.

Methods

We searched selected databases for studies on pan-immune inflammation values and their association with outcomes of treatment with immune checkpoint inhibitors. We used hazard ratios (HRS) and 95% confidence intervals (CI) to summarize survival outcomes. All data analyses were performed using STATA 15.0.

Results

7 studies comprising 982 patients were included in the meta-analysis. The pooled results showed that higher PIV was significantly associated with shorter overall survival OS (HR = 1.895, 95%CI: 1.548-2.318) and progression-free survival (PFS) (HR = 1.582, 95%CI: 1.324-1.890). Subgroup analyses also confirmed the reliability of the results.

Conclusions

High PIV and PILE metrics are associated with lower survival in cancer patients receiving ICIs.

A machine learning approach using 18F-FDG PET and enhanced CT scan-based radiomics combined with clinical model to predict pathological complete response in ESCC patients after neoadjuvant chemoradiotherapy and anti-PD-1 inhibitors

Background

We aim to evaluate the value of an integrated multimodal radiomics with machine learning model to predict the pathological complete response (pCR) of primary tumor in a prospective cohort of esophageal squamous cell carcinoma (ESCC) treated with neoadjuvant chemoradiotherapy (nCRT) and anti-PD-1 inhibitors.

Materials and methods

Clinical information of 126 ESCC patients were included for analysis. Radiomics features were extracted from 18F-FDG PET and enhanced plan CT images. Four machine learning algorithms, including SVM (Support Vector Machine), Random Forest (RF), and eXtreme Gradient Boosting (XGB) and logistic regression (LR), were applied using k-fold cross-validation to predict pCR after nCRT. The predictive ability of the models was assessed using receiver operating characteristics (ROC) curve analysis.

Results

A total of 842 features were extracted. Among the four machine learning algorithms, SVM achieved the most promising performance on the test set for PET(AUC:0.775), CT (AUC:0.710) and clinical model (AUC:0.722). For all combinations of various modalities-based models, the combination model of 18 F-FDG PET, CT and clinical features with SVM machine learning had the highest AUC of 0.852 in the test set when compared to single-modality models in various algorithms. The other combined models had AUC ranged 0.716 to 0.775.

Conclusion

Machine learning models utilizing radiomics features from 18F-FDG PET and enhanced plan CT exhibit promising performance in predicting pCR in ESCC after nCRT and anti-PD-1 inhibitors. The fusion of features from multiple modalities radiomics and clinical features enhances the better predictive performance compared to using a single modality alone.

Prognostic significance of the pretreatment pan-immune-inflammation value in cancer patients: an updated meta-analysis of 30 studies

Background

The pan-immune-inflammation value (PIV) has been reported as a promising prognostic biomarker in multiple cancers but still remains inconclusive. The objective of this study is to systematically investigate the association of the pretreatment PIV with survival outcomes in cancer patients, based on available literature.

Methods

Online databases including PubMed, Embase and the Web of Science were thoroughly searched for studies evaluating the prognostic role of the pretreatment PIV in cancers from the inception to June 2023. Hazard ratios (HRs) with 95% confidence intervals (CIs) were always assessed using a random-effects model. Statistical analyses were performed using Stata 12.0.

Results

Thirty studies were finally included after comprehensively study searching. In total, 8,799 cancer patients were enrolled in this meta-analysis. The pooled results demonstrated that patients in the high PIV group had a significantly poorer overall survival (HR = 2.07; 95%CI: 1.77-2.41; I2 = 73.0%) and progression-free survival (HR = 1.83; 95%CI: 1.37-2.45; I2 = 98.2%) than patients in the low PIV group. The prognostic significance of the PIV score on overall survival and progression-free survival was observed across various geographical regions, tumor stages and treatment strategies. Sensitivity analyses supported the stability of the above combined results.

Conclusion

This meta-analysis demonstrated that the pretreatment PIV could be a non-invasive and efficacious prognostic biomarker for cancer patients.

Prognostic significance of the systemic inflammation response index in gastrointestinal malignancy patients: a pooled analysis of 10,091 participants

Background: We performed a meta-analysis to investigate the association of the systemic inflammation response index (SIRI) with long-term survival outcomes in patients with gastrointestinal malignancy. Methods: PubMed, Web of Science and Embase were searched for relevant studies evaluating the prognostic significance of the SIRI in gastrointestinal malignancies until May 2023. Results: 30 studies with 10,091 patients were included. The pooled results identified that patients in the high SIRI group had a worse overall survival and disease-free survival, which was observed across various tumor types, tumor stages and primary treatments. Conclusion: An elevated SIRI is negatively associated with worse survival outcomes of gastrointestinal malignancy patients and can be used as a risk stratification index for gastrointestinal malignancies.

Prognostic nutritional index as a prognostic biomarker for gastrointestinal cancer patients treated with immune checkpoint inhibitors

Objective

Our study represents the first meta-analysis conducted to evaluate the prognostic utility of the baseline prognostic nutritional index (PNI) in patients with gastrointestinal cancer (GIC) who received immune checkpoint inhibitor (ICI) therapy.

Methods

We searched PubMed, the Cochrane Library, EMBASE, and Google Scholar until April 23, 2023, to obtain relevant articles for this study. Our analysis examined several clinical outcomes, including overall survival (OS), progression-free survival (PFS), objective response rate (ORR), and disease control rate (DCR).

Results

In this analysis, a total of 17 articles with 2883 patients were included. Our pooled results indicated that patients with high PNI levels had longer OS (HR: 0.530, 95% CI: 0.456-0.616, p < 0.001) and PFS (HR: 0.740, 95% CI: 0.649-0.844, p < 0.001), as well as higher ORR (OR: 1.622, 95% CI: 1.251-2.103, p < 0.004) and DCR (OR: 1.846, 95% CI: 1.428-2.388, p < 0.001). Subgroup analysis showed that PNI cutoff values of 40 to 45 showed greater predictive potential. Subgroup analysis also confirmed that the above findings still hold true in patients with esophageal cancer, gastric cancer, and hepatocellular carcinomas.

Conclusion

The PNI were reliable predictors of outcomes in GIC patients treated with ICIs.

Pretreatment absolute lymphocyte count is an independent predictor for survival outcomes for esophageal squamous cell carcinoma patients treated with neoadjuvant chemoradiotherapy and pembrolizumab: An analysis from a prospective cohort

BACKGROUND

The aim of the study was to analyze the relationship between pretreatment inflammatory biomarkers (IBs) and survival outcomes for patients with esophageal squamous cell carcinoma (ESCC) treated with neoadjuvant chemoradiotherapy (neo-CRT) and pembrolizumab.

METHODS

Clinical variables and IBs (absolute monocyte count [AMC], absolute lymphocyte count [ALC], platelet count [PLT], neutrophil-to-lymphocyte ratio [NLR], platelet-to-lymphocyte ratio [PLR], lymphocyte-to-monocyte ratio [LMR], pan-immune inflammation value [PIV], systemic immunoinflammatory index [SII], systemic immunoreactivity index [SIRI] and prognostic nutritional index [PNI]) were collected. Univariate and multivariate analysis were performed to identify the independent factors for outcomes of ESCC.

RESULTS

A total of 51 patients were included. Of these, 35 patients achieved pathological complete response (pCR) after neo-CRT and pembrolizumab (pCR: 68.6%). With a median follow-up of 20 months, the two-year PFS and OS of the cohort was 64% and 91%, respectively. Multivariate logistic regression analysis indicated that ALC (overall response [OR] 4.4, p = 0.051) and PLT (OR 6.7, p = 0.023) were two independent predictors for achieving pCR among ESCC treated with neo-CRT and pembrolizumab. Multivariate Cox regression analysis showed that ALC (HR 0.27, p = 0.028) and SIRI (HR 3.13, p = 0.048) were two independent predictors associated with PFS. Kaplan Meier analysis demonstrated that the PFS of ESCC with high baseline ALC was significantly better than those with low ALC (2-year PFS: 77% vs. 47%, p = 0.027), but not for overall survival (2-year OS: 96% vs. 87%, p = 0.46).

CONCLUSIONS

This retrospective analysis based on a prospective cohort for the first time demonstrates that pretreatment ALC is an independent predictor for achieving pCR and favorable outcomes of ESCC treated with neo-CRT and pembrolizumab.