Predictive value of nutritional indicators with regard to the survival outcomes in patients with metastatic esophageal squamous cell carcinoma treated with camrelizumab

Liu, Jiang; Hu, Guangyin; Zhai, Chentong; Wang, Jingjing; Xu, Wenjing; Xie, Jun; Zhu, Wugang; Jiang, Ping; Liu, Degan

doi:10.3892/ol.2023.13784

Cited by 3 publications

(1 citation statement)

References 38 publications

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“…Albumin is produced by hepatocytes and plays a crucial role in stabilizing cell growth and DNA replication, buffering various biochemical changes, as well as maintaining sex hormone homeostasis to prevent tumorigenesis. [ 30 , 31 ] The decrease in lymphocytes count will reduce the immune function of the body, making cancer cells more easily to immune escape and eventually lead to poor prognosis of cancer patients. [ 32 ] The reduction of PNI reflects malnutrition and decreased immunity, inhibiting inflammatory response and promoting tumor cell invasion function, thereby promoting tumorigenesis and progression, and ultimately leading to poor prognosis of cancer patients.…”

Section: Discussionmentioning

confidence: 99%

The prognostic value of preoperative laboratory data indicators in patients with esophageal carcinoma: An observational study

Ma,

Liu,

et al. 2024

Medicine

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Preoperative laboratory data indicators significantly affect the prognosis of a variety of tumors. Nevertheless, the combined effect of systemic immune-inflammation index (SII) and prognostic nutritional index (PNI) on overall survival (OS) in patients with esophageal carcinoma remains unclear. Thus, we examined these associations among patients with postoperative staged T3N0M0 esophageal carcinoma. The data of 246 patients with postoperative staged T3N0M0 esophageal carcinoma from January 1, 2010, to December 31, 2022, were retrospectively analyzed. OS was measured from the date of pathological diagnosis until either death or the last follow-up. The Kaplan–Meier method and multivariate Cox regression model were used to analyze the relationship between neutrophil-to-lymphocyte ratio (NLR), Platelet-to-lymphocyte ratio (PLR), Platelet-to-lymphocyte ratio (LMR), SII, PNI, and OS. The predictive value of SII and PNI as a combined index was analyzed by the receiver operating characteristic curve (ROC). A total of 246 patients aged 65.5 ± 7.4 years were included in this study and 181 (73.6%) were male. The univariate analysis revealed that differentiation, vessel involvement, postoperative treatment, NLR, SII, PLR, LMR, PNI were predictors of OS (P < .05). After adjusted for potential confounds, multivariate Cox regression analysis showed that the differentiation, SII, PNI, and postoperative treatment were independent prognostic factors correlated with OS in patients with postoperative staged T3N0M0 esophageal carcinoma (P < .05). SII and PNI, as a combined indicator, have a higher predictive value for OS. The NLR, SII, PLR, LMR, and PNI could all be used as independent predictors of OS in patients with postoperative staged T3N0M0 esophageal carcinoma. The combination of SII and PNI can significantly improve the accuracy of prediction.

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Section: Discussionmentioning

confidence: 99%

The prognostic value of preoperative laboratory data indicators in patients with esophageal carcinoma: An observational study

Ma,

Liu,

et al. 2024

Medicine

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Correlation between sarcopenia and esophageal cancer: a narrative review

Li,

Xie,

Xiao

et al. 2024

World J Surg Onc

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Background In recent years, the research on the relationship between sarcopenia before and after the treatment of esophageal cancer, as well as its impact on prognosis of esophageal cancer, has increased rapidly, which has aroused people’s attention to the disease of patients with esophageal cancer complicated with sarcopenia. This review examines the prevalence of sarcopenia in patients with esophageal cancer, as well as the relationship between sarcopenia (before and after surgery or chemotherapy) and prognosis in patients with esophageal cancer. Moreover, we summarized the potential pathogenesis of sarcopenia and pharmacologic and non-pharmacologic therapies. Methods A narrative review was performed in PubMed and Web of Science using the keywords (“esophageal cancer” or “esophageal neoplasm” or “neoplasm, esophageal” or “esophagus neoplasm” or “esophagus neoplasms” or “neoplasm, esophagus” or “neoplasms, esophagus” or “neoplasms, esophageal” or “cancer of esophagus” or “cancer of the esophagus” or “esophagus cancer” or “cancer, esophagus” or “cancers, esophagus” or “esophagus cancers” or “esophageal cancer” or “cancer, esophageal” or “cancers, esophageal” or “esophageal cancers”) and (“sarcopenia” or “muscular atrophy” or “aging” or “senescence” or “biological aging” or “aging, biological” or “atrophies, muscular” or “atrophy, muscular” or “muscular atrophies” or “atrophy, muscle” or “atrophies, muscle” or “muscle atrophies”). Studies reporting relationship between sarcopenia and esophageal cancer were analyzed. Results The results of the review suggest that the average prevalence of sarcopenia in esophageal cancer was 46.3% ± 19.6% ranging from 14.4 to 81% and sarcopenia can be an important predictor of poor prognosis in patients with esophageal cancer. Patients with esophageal cancer can suffer from sarcopenia due to their nutritional deficiencies, reduced physical activity, chemotherapy, and the effects of certain inflammatory factors and pathways. When classic diagnostic values for sarcopenia such as skeletal muscle index (SMI) are not available clinically, it is also feasible to predict esophageal cancer prognosis using simpler metrics, such as calf circumference (CC), five-count sit-up test (5-CST), and six-minute walk distance (6MWD). Conclusions Identifying the potential mechanism of sarcopenia in patients with esophageal cancer and implementing appropriate interventions may hold the key to improving the prognosis of these patients.

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An integrated prognosis prediction model based on real-word clinical characteristics for immunotherapy in advanced esophageal squamous cell carcinoma

Lu,

Dong,

et al. 2024

Preprint

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Introduction The efficacy of immune checkpoint inhibitors (ICIs) for advanced esophageal squamous cell carcinoma (ESCC) remains suboptimal. This study aims to construct and validate a clinically accessible model to better identify populations that may potentially benefit from ICIs. Methods This study enrolled advanced ESCC patients treated with ICIs at Peking University Cancer Hospital from January 14, 2016, to January 26, 2024, forming the training cohort. Combined positive score (CPS) was recorded to evaluate the predictive value of programmed cell death ligand-1 (PD-L1). Baseline clinical characteristics and laboratory test results were identified as predictors through a 2-phase selection based on Cox proportional hazard regression and minimization of Akaike information criterion (AIC). The prediction model was internally validated using bootstrapping and externally validated in patients from Harbin Medical University Cancer Hospital between January 10, 2019, and July 6, 2022. Results A total of 430 patients from Peking University Cancer Hospital and 184 patients from Harbin Medical University Cancer Hospital were ultimately enrolled. PD-L1 expression failed to discriminate survival outcomes (HR=0.94, 95% CI: 0.74-1.19, P = .6). The final model incorporates 10 variables: stage, bone metastasis, line of therapy, treatment, lactate dehydrogenase, carcinoembryonic antigen, carbohydrate antigen 199, lymphocyte count, prognostic nutritional index, and systemic immune-inflammation index. The C-index was 0.725 (95%CI: 0.694-0.756) in the training cohort, 0.722 (95%CI: 0.688-0.751) after bootstrapping, and 0.691 (95%CI: 0.650-0.733) in the external validation cohort, outperforming PD-L1 in prognostic prediction and risk stratification. An interactive online prediction tool (https://escc-survival.shinyapps.io/shiny_app/) was subsequently developed. Conclusions This is the first model for individualized survival prediction in advanced ESCC patients treated with ICIs based on large-scale, high-quality real-world data, potentially guiding clinical decision-making and optimize treatment strategies.

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Predictive value of nutritional indicators with regard to the survival outcomes in patients with metastatic esophageal squamous cell carcinoma treated with camrelizumab

Cited by 3 publications

References 38 publications

The prognostic value of preoperative laboratory data indicators in patients with esophageal carcinoma: An observational study

The prognostic value of preoperative laboratory data indicators in patients with esophageal carcinoma: An observational study

Correlation between sarcopenia and esophageal cancer: a narrative review

An integrated prognosis prediction model based on real-word clinical characteristics for immunotherapy in advanced esophageal squamous cell carcinoma

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