Prognostic value of the cholesterol-dependent nutritional prognostic index in patients receiving adjuvant chemotherapy after radical esophageal cancer treatment

Abstract

Background

Esophageal cancer is the 6th most common cancer in terms of incidence and the 4th most common cause of mortality in China. Given the limited survival outcomes observed in patients with locally advanced disease managed exclusively with surgical intervention, postoperative treatment is critically important. This study sought to assess the prognostic value of total cholesterol (TC) levels and the prognostic nutritional index (PNI) in patients undergoing postoperative chemotherapy for esophageal cancer.

Methods

A total of 101 patients who underwent postoesophagectomy chemotherapy were included in this retrospective analysis. PNI values for prechemotherapy were calculated for each patient [PNI = albumin + 5 × lymphocyte count] and TC. The optimal cutoff values for these indices were calculated from the receiver operating characteristic (ROC) curve. Patients were stratified into three groups on the basis of their PNI and TC levels. A novel nutritional prognostic index, termed the cholesterol-dependent nutritional prognostic index (CPNI), was developed on the basis of the PNI and TC. Univariate and multivariate Cox analyses were employed to determine the associations between each indicator and clinical outcomes.

Results

The prechemotherapy PNI, TC level, and TNM stage became independent risk factors for OS (p < 0.05). Patients in the high PNI-high TC group had significantly improved DFS and OS compared with those in the low PNI-low TC group (p < 0.001) and had a lower early recurrence rate (P = 0.008). In contrast, patients with a high CPNI had a higher mortality rate.

Conclusion

The prechemotherapy PNI combined with TC is an accurate and useful predictor of patient prognosis.

Introduction

Esophageal cancer ranks 7th among malignant tumors globally and is the 6th most common cancer in China, with a 5-year survival rate of 15%-25%. Unlike Western countries, in China, over 90% of esophageal cancer are squamous cell carcinoma (ESCC). A randomized controlled trial by LEE et al., showed that compared to surgery alone, postoperative chemotherapy increased the 3-year disease-free survival rate from 35.6% to 47.6% (p = 0.049) [1,2,3]. A meta-analysis showed that adjuvant chemotherapy improved overall survival (OS) (HR 0.78, 95% CI 0.66–0.91; P = 0.002) and disease-free survival (DFS) (HR 0.72, 95% CI 0.6–0.86; P < 0.001) [4, 5]. This highlights the critical role of adjuvant chemotherapy in improving postoperative survival outcomes for patients with esophageal squamous cell carcinoma (ESCC). The aggressiveness and poor prognosis of esophageal cancer indicate an urgent need for effective prognostic markers, especially serological indicators, to guide postoperative chemotherapy strategies and improve patient outcomes.

Nutrition significantly impacts treatment outcomes, survival rates, and quality of life in various cancers [6]. Malnutrition often presents with low serum albumin levels, and the PNI, calculated as the albumin + 5 × lymphocyte count, serves as a prognostic marker on the basis of these parameters. Previous reports have revealed that preoperative-low PNI level was associated with worse survival in patients with ESCC [7, 8]. Cholesterol plays a pivotal role in the body's anabolic processes and serves as a biomarker of nutritional status in patients. Studies suggest that total cholesterol levels may have prognostic value across different cancer types, including esophageal cancer [9]. Disrupted fatty acid metabolism resulting from excessive cholesterol intake can induce cell apoptosis and damage, potentially promoting esophageal cancer progression [10]. Some studies have indicated that lower total cholesterol levels are correlated with worse outcomes, possibly because cholesterol plays a role in maintaining cell membrane integrity and modulating critical signaling pathways involved in cancer development [11].

Effective management and optimization of nutritional status in patients could significantly influence survival outcomes, particularly in those undergoing treatment for esophageal cancer. However, current tools for assessing nutritional status in this cohort are notably insufficient. PNI is based on routine clinical data, is simple to calculate, and can reflect the nutritional status of patients; TC is simple and easy to measure, and can reflect the metabolic status of patients. Both have certain value in the prognosis evaluation of esophageal cancer patients, but the value of a single indicator is limited. Therefore, in this study, we stratified the risk of patients based on PNI and TC, and established a new nutritional prognostic index called CPNI by integrating these biomarkers. Subsequently, a comparative analysis was conducted to determine the predictive accuracy of PNI, TC, and CPNI. This article aims to identify high-risk individuals facing poor prognosis after surgical intervention and chemotherapy, thereby providing personalized treatment strategies for esophageal cancer patients.

Material and methods

Participants

In this study, we conducted a retrospective analysis involving 101 patients diagnosed with stage I-IV esophageal squamous cell carcinom. The patients underwent radical resection at Zhongda Hospital of Southeast University between January 2016 and December 2021. All patients underwent gastroscopy and computed tomography (CT) to determine their clinical stage. Clinical staging was based on the International Union for Cancer Control TNM Classification of Malignant Tumors, 8th edition, for diagnosis. The main inclusion criteria are as follows: (1) Age > 20 years (2) Diagnosis of esophageal squamous cell carcinoma confirmed by endoscopic biopsy (3) Radical esophagectomy (4) No preoperative antitumor treatment (5) Postoperative treatment with paclitaxel combined with platinum-based drugs 2–3 months after surgery (6) No use of lipid-lowering drugs 1 month before chemotherapy (7) No double cancer (8) Survival of at least 90 days after surgery. Patients who did not meet the inclusion criteria for the study were selected based on the following exclusion criteria: non-esophageal squamous cell carcinoma, death within 90 days post-surgery, dual cancers, incomplete clinical data, and interrupted follow-up. Figure 1 shows the specific inclusion process.

Fig. 1

Patient selection flow diagram

Data collection

The collected data includes patient gender, tumor stage, degree of differentiation, vascular invasion, neural invasion, depth of invasion, proportion of positive lymph nodes, Tumor circumference and maximum diameter, chemotherapy cycles, and Whether to receive immunotherapy after recurrence or metastasis. Serological indicators include complete blood count, liver function tests, and lipid profile (including lymphocyte count, monocyte count, eosinophil count, platelet count, albumin, and total cholesterol) within 1 week before the first chemotherapy after surgery and within 1 week after the end of the chemotherapy cycle. The formula for PNI is as follows: PNI = Albumin + 5 × Lymphocyte count.

Follow-up and endpoints

The enrolled patients underwent regular reviews and follow-ups, which included hospital visits, telephone consultations, and follow-ups by messaging apps such as WeChat. In addition to relevant hematological tests, the review protocol primarily involved CT scans, MRI scans, cytology examinations, and other imaging and pathology assessments. The follow-up period was extended until January 2023. In terms of clinical outcomes, overall survival (OS) time was defined as the duration from the initiation of chemotherapy to either death or the last follow-up date. Progression-free survival (DFS) was defined as the duration from the start of chemotherapy to disease progression or the last follow-up date.

Statistical analyses

Data analysis was performed via R version 4.3.3 and SPSS version 25.0. ROC curve analysis was employed to determine optimal cutoff values for continuous variables, which were subsequently categorized accordingly. Kaplan‒Meier curves were used to plot OS and DFS, with differences in survival assessed via the log-rank test. Variables showing significant differences in the univariate analysis were subjected to multivariate analysis via Cox regression, and hazard ratios with 95% confidence intervals were calculated. Statistical significance was defined as P < 0.05. Furthermore, the Delong test was used to compare the area under the curve (AUC) of the CPNI with those of other nutritional indicators.

Results

Baseline characteristics

The baseline characteristics of the patients are shown in Table 1. Among them, there are more males (85/101). Most patients have poorly differentiated tumors, with a tumor circumference of less than 4 cm, and fewer patients received immunotherapy after metastasis or recurrence. There are statistical differences in the median survival and recurrence times among patients with different tumor stages, pre-chemotherapy PNI and TC levels, lymph node positivity ratios, tumor circumference, and maximum diameter (P < 0.05).

Table 1 Baseline characteristics of patients and median survival and recurrence times

Cutoff values for PNI and TC before chemotherapy

The ROC curve in Fig. 2 indicates that PNI and TC before chemotherapy have potential value in predicting patient prognosis. Using these curves, the optimal critical values for pre-chemotherapy PNI (critical value: 43.65) and TC were determined. (cutoff: 5.07). Based on these thresholds, patients were divided into high PNI and low PNI groups, as well as high TC and low TC groups, to effectively assess their predictive value for patient prognosis.

Fig. 2

ROC curves of the prechemotherapy PNI and TC indicators in ESCC patients

Relationships between PNI and TC before chemotherapy and patient prognosis

The overall 1-year and 2-year survival rates for the entire group were 86.14% and 65.35%, respectively, with corresponding disease-free survival rates of 64.36% and 40.69%. The median OS and DFS were 29.9 months and 19.2 months, respectively. As shown in Fig. 3, the 1-year and 2-year OS and DFS of patients in the high PNI group and high TC group are significantly better than those in the low PNI group and low TC group.

Fig. 3

K‒M analysis of (A, C) OS and (B, D) DFS according to the prechemotherapy PNI and TC. OS, overall survival; DFS, disease-free survival

Independent risk factors for ESCC

Analyzed clinical and laboratory indicators that may affect patient prognosis using univariate and multivariate methods. Univariate analysis showed that pre-chemotherapy PNI, pre-chemotherapy TC, TNM staging, margin circumference, maximum lesion diameter, and positive lymph node ratio were significantly associated with OS and DFS (p < 0.05). In the univariate analysis, variables with p < 0.05 were subsequently evaluated using a multivariate Cox regression model. The results indicate that pre-chemotherapy PNI, pre-chemotherapy TC, and TNM staging are independent risk factors for OS; pre-chemotherapy PNI, pre-chemotherapy TC, TNM staging, and the proportion of positive lymph nodes are independent risk factors for DFS (p < 0.05). Table 2 shows the specific results of these prognostic analyses.

Table 2 Univariate and multivariate analyses for predictors of survival in patients with EC

Impact of pretreatment nutritional indices on survival

The OS and DFS of patients in the high PNI-high TC group, high PNI-low TC group, low PNI-high TC group, and low PNI-low TC group showed statistical differences (P < 0.05). The OS and DFS of patients in the high PNI-high TC group being significantly higher than those in the low PNI-low TC group (P < 0.001, Fig. 4A, B). Table 3 presents subgroup analyses based on pre-chemotherapy PNI and TC levels, focusing on stage, positive lymph node ratio, maximum lesion diameter, and tumor circumference. The results indicate that regardless of tumor stage and tumor length, low PNI-low TC is a significant risk factor for increased mortality in patients receiving adjuvant therapy after radical surgery for ESCC. In patients with a lymph node ratio positive ≤ 0.15 and circumference ≤ 4 cm, the mortality rate in the low PNI-low TC group was significantly higher than that in the high PNI-high TC group.

Fig. 4

New nutritional prognostic indicators for OS and PFS were risk stratified by risk group. A, B Risk stratification for 3 groups on OS and PFS (p < 0.001); C, D risk stratification for C-PNI on OS and PFS. E The AUCs of all the indices (the p values for the Delong test were all less than 0.05). OS, overall survival; DFS, disease-free survival. Group 1, high PNI-high TC; group 2, high PNI-low TC or low PNI-high TC; and group 3, low PNI-low TC

Table 3 Subgroup analysis of risk stratification in patients undergoing adjuvant chemotherapy after radical surgery for ESCC

New nutritional prognostic indicators based on the PNI and TC

Furthermore, we have developed a CPNI. CPNI is derived by multiplying PNI and TC by their respective β coefficients and summing them up. The formula for CPNI is as follows: CPNI = 2.346 * PNI + 1.234 * TC. According to the optimal cutoff value determined by the ROC, CPNI is divided into two groups. The Kaplan–Meier curves show that the mortality rate of patients with CPNI > 0.62 is higher than that of patients with CPNI ≤ 0.62 (OS: HR = 5.266 (2.218–12.503), DFS: HR = 4.538 (1.924–10.706), (Fig. 4C, D). To evaluate the prognostic value of CPNI, we conducted an ROC analysis comparing CPNI with other conventional indicators. The results show that the AUC of CPNI is greater than the AUC of other indicators. The DeLong test showed that the AUC of CPN is greater than the AUC of PNI and TC curves (P < 0.05, Fig. 4E). These findings indicate that compared to the individual PNI and TC, CPNI has better predictive ability.

Correlation between nutritional indices and recurrence timing and pattern

We investigated the relationship between nutritional indicators and the timing and pattern of recurrence. The results indicate that the early recurrence rate (within one year post-surgery) in low PNI-low TC patients is significantly higher than that in high PNI-high TC patients (p = 0.008) (Fig. 5A). In patients with early recurrence, PNI and TC levels are relatively low (Fig. 5B, C).

Fig. 5

Associations between nutritional indices and early recurrence. Early recurrence was significantly greater in patients with a low PNI-low TC (a). Both the PNI (b) and TC (c) were significantly lower in patients with early recurrence

Discussion

With the advancement of technology, the diagnosis rate of esophageal cancer has significantly increased, but the high mortality rate remains a concern. Analysis of the causes of death shows that approximately 25% of cancer-related deaths are due to malnutrition rather than the cancer itself [12]. Severe malnutrition in patients with gastrointestinal cancer is significantly associated with increased morbidity and mortality, reduced treatment efficacy, and prolonged hospital stays. Therefore, there is an urgent need to raise awareness about malnutrition and to cautiously apply nutritional interventions in clinical practice [13, 14]. Serum albumin levels are a recognized indicator of malnutrition and also a biomarker reflecting the body's protein reserves. Research indicates that hypoalbuminemia can trigger the release of inflammatory cytokines, such as IL-6 and TNF-α, exacerbating disease progression and leading to poorer outcomes [15, 16]. These findings emphasize the importance of rigorously assessing and managing nutritional status in cancer patients to potentially improve treatment outcomes and overall survival rates. Malnutrition can impair the maturation of lymphocytes and reduce the number of circulating lymphocytes. A meta-analysis shows that severe lymphocytopenia (grade ≥ 3) has a significant negative prognostic impact on overall survival (OS) in patients with solid tumors undergoing radiotherapy [17]. PNI was initially proposed by Buzby and later improved by Onodera as a comprehensive indicator of nutritional and immune status based on serum albumin levels and lymphocyte counts [18]. It has shown significant predictive value in a range of cancers, including pancreatic cancer, hepatocellular carcinoma, gastric cancer, colorectal cancer, and esophageal cancer. Multiple studies have shown that preoperative PNI is correlated with the prognosis of patients with esophageal squamous cell carcinoma [8, 19]. Furthermore, abnormal lipid metabolism is increasingly being recognized as a key factor in the development of cancer, having a profound impact on cancer prognosis [20]. Total cholesterol plays a crucial role in maintaining cell integrity, stabilizing cell membranes, regulating lipid metabolism, and participating in complex biological signaling pathways [20, 21], and Hypocholesterolemia is often observed in cancer patients because malignant cells increase their uptake of cholesterol, which may disrupt transmembrane signaling pathways and potentially worsen prognostic outcomes. These indicators and considerations emphasize the importance of conducting comprehensive nutritional and metabolic assessments in the clinical management of cancer patients, thereby influencing treatment methods and prognosis evaluation.

Compared to other studies, this research specifically focuses on patients who received adjuvant chemotherapy after radical esophagectomy. Due to the standardized surgical methods and chemotherapy protocols, the homogeneity of this cohort is quite strong. The research results indicate that patients with high PNI and high TC levels have significantly better OS and DFS compared to patients with low PNI and low TC levels (P < 0.001), and they also have a lower early recurrence rate (P = 0.008). Moreover, patients with CPNI > 0.62 had significantly worse prognosis than those with CPNI ≤ 0.62 (OS: HR = 5.267 [2.22–12.51], DFS: HR = 4.54 [1.92–10.71]). Compared to the individual markers PNI and TC, CPNI shows superior prognostic value in patients undergoing adjuvant chemotherapy after radical esophageal cancer treatment. However, our research has several limitations. This study is a preliminary investigation, including only patients from a single institution and relying on retrospective data, which may introduce selection bias. Secondly, the sample size is small, and the dynamic changes in CPNI may be related to prognosis. Future work will continue to expand the data to calculate longer-term survival rates and the relationship between dynamic CPNI and prognosis. Despite these limitations, our research findings provide reference data for predicting the survival outcomes of ESCC patients receiving adjuvant chemotherapy.

Conclusion

The prechemotherapy PNI combined with TC is a direct, accurate and useful predictor of patient prognosis.