Prognostic Value of Combined Detection of Preoperative Albumin-to-Fibrinogen Ratio and Neutrophil-to-Lymphocyte Ratio in Operable Esophageal Squamous Cell Carcinoma Patients without Neoadjuvant Therapy

Establishing and validating models integrated with hematological biomarkers and clinical characteristics for the prognosis of non-esophageal squamous cell carcinoma patients

BACKGROUND

This study aimed to construct a novel model and validate its predictive power in non-esophageal squamous cell carcinoma (NESCC) patients.

METHODS

This retrospective study included 151 patients between October 2006 and September 2016. The LASSO Cox and Random Survival Forest (RSF) models were developed with the help of hematological biomarkers and clinical characteristics. The concordance index (C-index) was used to assess the prognostic power of the LASSO Cox model, RSF model, and TNM staging. Based on the risk scores of the LASSO Cox and RSF models, we divided patients into low-risk and high-risk subgroups.

RESULTS

We constructed two models in NESCC patients according to LASSO Cox regression and RSF models. The RSF model reached a C-index of 0.841 (95% CI: 0.792-0.889) in the primary cohort and 0.880 (95% CI: 0.830-0.930) in the validation cohort, which was higher than the C-index of the LASSO Cox model 0.656 (95% CI: 0.580-0.732) and 0.632 (95% CI: 0.542-0.720) in the two cohorts. The integrated C/D area under the ROC curve (AUC) values for the LASSO Cox and RSF models were 0.701 and 0.861, respectively. In both two models, Kaplan-Meier survival analysis and the estimated restricted mean survival time (RMST) values indicated that the low-risk subgroup had a better prognostic outcome than the high-risk subgroup (p < 0.05).

CONCLUSIONS

The RSF model has better prediction power than the LASSO Cox and the TNM staging models. It has a guiding value for the choice of individualized treatment in patients with NESCC.

Interpretations of the Role of Plasma Albumin in Prognostic Indices: A Literature Review

This review assesses how publications interpret factors that influence the serum or plasma albumin (PA) level in prognostic indices, focusing on inflammation and nutrition. On PubMed, a search for "albumin AND prognosis" yielded 23,919 results. From these records, prognostic indices were retrieved, and their names were used as search strings on PubMed. Indices found in 10 or more original research articles were included. The same search strings, restricted to "Review" or "Systematic review", retrieved yielded on the indices. The data comprised the 10 latest original research articles and up to 10 of the latest reviews. Thirty indices had 294 original research articles (6 covering two indices) and 131 reviews, most of which were from recent years. A total of 106 articles related the PA level to inflammation, and 136 related the PA level to nutrition. For the reviews, the equivalent numbers were 54 and 65. In conclusion, more publications mention the PA level as a marker of nutrition rather than inflammation. This is in contrast to several general reviews on albumin and nutritional guidelines, which state that the PA level is a marker of inflammation but not nutrition. Hypoalbuminemia should prompt clinicians to focus on the inflammatory aspects in their patients.

Preoperative BChE serves as a prognostic marker in patients with resectable AEG after neoadjuvant chemotherapy

BACKGROUND

Diminished systemic serum butyrylcholinesterase (BChE), a biomarker for chronic inflammation, cachexia, and advanced tumor stage, has shown to play a prognostic role in various malignancies. The aim of this study was to investigate the prognostic value of pretherapeutic BChE levels in patients with resectable adenocarcinoma of the gastroesophageal junction (AEG), treated with or without neoadjuvant therapy.

METHODS

Data of a consecutive series of patients with resectable AEG at the Department for General Surgery, Medical University of Vienna, were analyzed. Preoperative serum BChE levels were correlated to clinic-pathological parameters as well as treatment response. The prognostic impact of serum BChE levels on disease-free (DFS) and overall survival (OS) was evaluated by univariate and multivariate cox regression analysis, and Kaplan-Meier curves used for illustration.

RESULTS

A total of 319 patients were included in this study, with an overall mean (standard deviation, SD) pretreatment serum BChE level of 6.22 (± 1.91) IU/L. In univariate models, diminished preoperative serum BChE levels were significantly associated with shorter overall (OS, p < 0.003) and disease-free survival (DFS, p < 0.001) in patients who received neoadjuvant treatment and/or primary resection. In multivariated analysis, decreased BChE was significantly associated with shorter DFS (HR: 0.92, 95% CI: 0.84-1.00, p 0.049) and OS (HR: 0.92, 95% CI: 0.85-1.00, p < 0.49) in patients receiving neoadjuvant therapy. Backward regression identified the interaction between preoperative BChE and neoadjuvant chemotherapy as a predictive factor for DFS and OS.

CONCLUSION

Diminished serum BChE serves as a strong, independent, and cost-effective prognostic biomarker for worse outcome in patients with resectable AEG who had received neoadjuvant chemotherapy.

Predictive value of systemic immune-inflammation index for pathological complete response in patients receiving neoadjuvant immunochemotherapy for locally advanced esophageal cancer

Objectives

Neoadjuvant immunochemotherapy (nICT) has been confirmed with promising pathological complete response (pCR) among locally advanced esophageal squamous cell carcinoma (ESCC). However, there were still no reliable and accurate predictors to predict the treatment response. This study aimed to explore the predictive value of inflammatory and nutritional parameters.

Methods

Patients with ESCC who underwent radical surgery after nICT between January 2020 and April 2022 were included in the study. First, the least absolute shrinkage and selection operator regression (LASSO) logistic regression analysis was used to screen independent inflammatory and nutritional parameters. Secondly, univariate and multivariate logistic regression were used to screen and predict independent risk factors for pCR. Thirdly, a nomogram was constructed based on the independent predictive factors, and 30% of the included population was randomly selected as the validation cohort. We used the receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) curve to evaluate the nomogram model.

Results

A total of 97 ESCC patients were screened for analysis, with 20 patients with pCR (20.32%). Only the systemic immune-inflammation index (SII) was screened after LASSO-logistic regression when λ was 0.06. The cut-off value of SII was 921.80 with an area under curve (AUC) value of 0.62. We defined SII > 921.80 as high SII and SII ≦ 921.80 as low SII. Further, the univariate and multivariate analysis further determined SII(OR = 3.94, 95%CI:1.26-12.42, P = 0.02) and clinical stage(OR = 0.35, 95%CI:0.12-0.98, P = 0.05) were independent predictive factors of pCR. One novel nomogram was established with an AUC value of 0.72 in the training cohort and 0.82 in the validation cohort. The Brier score of the calibration curve was 0.13. The calibration curve showed good agreement between the predicted results and the actual results in both the training cohort and the validation cohort. Compared with the clinical stage, the DCA confirmed a better clinical value of the nomogram model in both the training cohort and the validation cohort.

Conclusions

High pretreatment SII and early clinical stage were independently associated with pCR among ESCC receiving nICT. We further established and validated one novel nomogram model to effectively predict pCR among ESCC after nICT.

Peripheral blood inflammation indices are effective predictors of anastomotic leakage in elective esophageal surgery

BACKGROUND

This study investigated the predictive value of peripheral inflammatory indices, including neutrophil count, lymphocyte count, platelet count, neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR), in anastomotic leakage during elective esophageal surgery.

METHODS

This retrospective study included all patients who underwent esophagectomy for esophageal squamous cell carcinoma from 2016 to 2020 in our institution. The peripheral blood inflammatory indices were obtained on preoperative days 1-7 (PRD 1-7), and postoperative days 1-3 (POD 1-3) and 4-7 (POD 4-7). Univariate, multivariate logistic, and receiver operating characteristic curve analyses were conducted to evaluate the diagnostic value of these peripheral blood inflammatory indices.

RESULTS

A total of 198 patients were included in the study, and 25 (13%) patients experienced anastomotic leakage. Multivariate analyses identified diet, neutrophil count, and PLR on POD 1-3, and NLR on POD 4-7 as independent factors associated with anastomotic leakage. Using the receiver operating characteristic curve, the variable with the best area under curve was a neutrophil cutoff count of 4.1 [0.737; 95% CI: 0.639-0.835], with a sensitivity and specificity of 60.0% and 66.5%, respectively. This was followed by an NLR cutoff value of 9.5 on POD 4-7 (0.628; 95% CI: 0.505-0.752) and a cutoff PLR value of 220.1 on POD 1-3 (0.643; 95% CI: 0.536-0.750). Diet showed a poor result on the receiver operating characteristic curve analysis.

CONCLUSIONS

Neutrophil count and PLR on POD 1-3 and NLR on POD 4-7 were shown to have predictive value for anastomotic leakage in elective esophageal surgery.

A New Index AGR-PLR Score (APS) for Patients with Esophageal Squamous Cell Carcinoma Undergoing Radical Esophagectomy

Purpose

Biomarkers of the systemic inflammatory response and nutritional-related indicators have been used to assess the host anti-tumor immune response and predict prognosis in esophageal squamous cell carcinoma (ESCC). However, a new indicator system combining platelet-to-lymphocyte ratio (PLR) and albumin-globulin ratio (AGR), AGR-PLR score (APS), has not yet been evaluated for the prognosis prediction among ESCC patients.

Methods

A retrospective analysis was performed, including 633 patients with ESCC, comprising 450 in the training cohort and 183 in the validation cohort.

Results

In this study, we found that the overall survival time among patients with an APS of 2 was significantly shorter than that among patients with an APS of 1, and the survival time of patients with an APS of 1 was significantly shorter than that of patients with an APS of 0. Multivariate analysis showed that the APS was an independent prognostic factor for patients with ESCC. The APS demonstrated better prognostic accuracy and effectiveness for ESCC patients than either PLR or AGR alone. In addition, a new prediction nomogram was established according to tumor grade, APS, and tumor, node, metastasis (TNM) stage. Compared with the traditional 8th version of TNM staging system, this nomogram demonstrated improved sensitivity and specificity for the prediction of 3- and 5-year survival.

Conclusion

APS is a novel independent prognostic indicator for the radical resection of ESCC and a potential biomarker for monitoring the therapeutic response.

Identification and Validation of a Ferroptosis-Related Long Non-coding RNA Signature for Predicting the Outcome of Lung Adenocarcinoma

BACKGROUND

Ferroptosis is a recently recognized type of programmed cell death that is involved in the biological processes of various cancers. However, the mechanism of ferroptosis in lung adenocarcinoma (LUAD) remains unclear. This study aimed to determine the role of ferroptosis-associated long non-coding RNAs (lncRNAs) in LUAD and to establish a prognostic model.

METHODS

We downloaded ferroptosis-related genes from the FerrDb database and RNA sequencing data and clinicopathological characteristics from The Cancer Genome Atlas. We randomly divided the data into training and validation sets. Ferroptosis-associated lncRNA signatures with the lowest Akaike information criteria were determined using COX regression analysis and the least absolute shrinkage and selection operator. The risk scores of ferroptosis-related lncRNAs were calculated, and patients with LUAD were assigned to high- and low-risk groups based on the median risk score. The prognostic value of the risk scores was evaluated using Kaplan-Meier curves, Cox regression analyses, and nomograms. We then explored relationships between ferroptosis-related lncRNAs and the immune response using gene set enrichment analysis (GSEA).

RESULTS

Ten ferroptosis-related lncRNA signatures were identified in the training group, and Kaplan-Meier and Cox regression analyses confirmed that the risk scores were independent predictors of LUAD outcome in the training and validation sets (all P < 0.05). The area under the curve confirmed that the signatures could determine the prognosis of LUAD. The predictive accuracy of the established nomogram model was verified using the concordance index and calibration curve. The GSEA showed that the 10 ferroptosis-related lncRNAs might be associated with tumor immune response.

CONCLUSION

We established a novel signature involving 10 ferroptosis-related lncRNAs (LINC01843, MIR193BHG, AC091185.1, AC027031.2, AL021707.2, AL031667.3, AL606834.1, AC026355.1, AC124045.1, and AC025048.4) that can accurately predict the outcome of LUAD and are associated with the immune response. This will provide new insights into the development of new therapies for LUAD.