Geriatric nutritional risk index as an independent prognostic factor in locally advanced nasopharyngeal carcinoma treated using radical concurrent chemoradiotherapy: a retrospective cohort study

Introduction

Nasopharyngeal carcinoma (NPC) is an endemic malignancy of the head and neck that is prevalent in Southeast Asia and Southern China and is associated with high death rates (1,2). The mainstay treatment of NPC is radiotherapy. With the use of intensity-modulated radiation therapy (IMRT) and chemotherapy and the development of modern imaging techniques, the survival rate of patients with NPC has been significantly improved (3-6). However, a significant number of affected patients still exhibit locoregional relapse, adverse reactions to treatment, and distant metastasis, ultimately leading to death (7,8). Thus, the identification of prognostic factors as markers of risk stratification as well as the development of individualized therapeutic strategies may provide significant advances in the treatment of patients with NPC.

Epstein-Barr virus (EBV) DNA is correlated with high tumor burden and poor long-term survival of patients with NPC. Circulating cell-free EBV DNA has been established as a tumor marker and is used for screening, diagnosis, risk stratification, and predicting the prognosis of patients (9-11). Malnutrition is a prevalent clinical complication in patients with NPC, which has a negative impact on disease prognosis and quality of life (12). Screening patients with high nutrition risk is necessary to provide appropriate interventions to reduce malnutrition-related mortality and improve prognosis. The Geriatric Nutritional Risk Index (GNRI) is a straightforward nutrition measurement tool used in clinical practice (13) that integrates two parameters, namely, serum albumin concentration and current body weight, compared to the ideal body weight. Previous studies have reported that patients with low GNRI score (GNRI <98) exhibit a worse prognosis than those with a normal GNRI score (GNRI >98). Furthermore, the GNRI score is useful in the assessment of nutritional status and the prediction of long-term outcomes in patients with and without cancer (14-16). As GNRI was developed by modifying the nutritional risk index for elderly patients, most studies focus on the study of GNRI in the elderly. However, studies evaluating young adults have confirmed that GNRI assessment is valuable in the evaluation of the nutritional status in this population (15,17-20).

In this study, we aimed to evaluate the prognostic value of the GNRI score of patients with NPC and investigate the potential of GNRI as a reliable parameter in the management of these patients. Moreover, we studied the effect of EBV DNA in risk stratification to understand if the combined determination of GNRI and EBV DNA could improve risk stratification in patients with NPC.

We present the following article in accordance with the REMARK reporting checklist (available at http://dx.doi.org/10.21037/atm-20-6493).

Methods

Patients

Patient data were retrospectively analyzed and a total of 1,065 newly diagnosed patients with non-disseminated NPC from the Sun Yat-sen University Cancer Center (SYSUCC) between January 2009 and July 2014 were included in this study. The eligibility criteria included (I) newly-diagnosed patients with NPC without metastasis; (II) age ≥18 years; (III) Eastern Cooperative Oncology Group (ECOG) performance status of 0 or 1; (IV) presence of NPC following the WHO histopathological type II or III grade; (V) treatment with IMRT and whole course concurrent chemotherapy (CCRT); (VI) availability of the complete medical history before treatment; (VII) availability of complete data with GNRI assessment and pretreatment plasma EBV DNA. Two patients with histopathological type I NPC, based on the WHO criteria, 9 patients who were lost to follow-up, and 11 patients with a history of other malignancies were excluded from this study. A total of 1,065 eligible patients were finally included. Categories are based on the 7^th edition of the Union for International Cancer Control/American Joint Committee on Cancer staging system. This study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). This study was approved by ethics board of Sun Yat-sen University Cancer Center and individual consent for this retrospective analysis was waived.

Treatment

All patients were treated with CCRT. The concurrent chemotherapy regimen that was chosen was mainly platinum-based chemotherapy, with only cisplatin (80 mg/m²) at weeks 1, 4, and 7 of the RT cycle or cisplatin 30–40 mg/m² weekly during radiotherapy, per the detailed regimens described as previous study (21). All patients received definitive radiotherapy in the form of IMRT. The IMRT plan followed the general design used at our institute (22). All patients were treated according to the treatment guidelines set for patients with NPC at SYSUCC.

GNRI calculation and EBV DNA detection

The data used for the calculation of the nutritional status were obtained within one week before treatment. GNRI was calculated as follows: 1.487 × serum albumin concentration (g/L) + 41.7 × present body weight/ideal body weight (kg). In this study, the ideal body weight was calculated from a body mass index (BMI) of 22 kg/m² and the patient’s height as follows: ideal body weight = 22× square of height (m) (13). When the body weight of the patient exceeded the ideal body weight, the ratio between actual body weight and ideal body weight was set to 1. According to the median GNRI score, all patients were assigned to the low GNRI group (GNRI ≤107.7) or the high GNRI group (GNRI >107.7). Pretreatment peripheral blood was collected from patients for plasma EBV DNA detection. Blood was collected in ethylene diamine tetra-acetic-coated tubes and analyzed using real-time quantitative polymerase chain reaction as reported in previously published studies (23,24). Moreover, patients were assigned to two groups based on a cutoff value of 1,500 copies/mL as reported in a previous study (25).

Follow-up and clinical outcome assessment

After treatment, patients were assessed at outpatient clinics every three months for the first three years, and every six months, until death. The primary study endpoint was the overall survival (OS), and the secondary endpoints were progress-free survival (PFS), local-regional recurrence-free survival (LRFS), and distant metastasis-free survival (DMFS). The definitions of these endpoints are as follows: OS, from the date of the first diagnosis of NPC to the date of death from any cause, or patient censoring at the date of the last follow-up; PFS, from the date of the first diagnosis of NPC to the date of the first progression at any site, or patient censoring at the date of the last follow-up; LRFS and DMFS, from the date of the first diagnosis of NPC to the date of locoregional relapse or distant metastasis, or patient censoring at the date of the last follow-up.

Statistical analysis

We classified categorical variables according to clinical findings and transformed continuous variables into categorical variables based on routine cutoff points or findings reported in previous studies (26,27). Chi-squared test or Fisher’s exact test were used to analyze the clinical characteristics of the two GNRI groups. Kruskal-Wallis rank-sum test was used to analyze ranked data. PFS, OS, DMFS, and LRFS were calculated using the Kaplan-Meier method and the differences were compared using the log-rank test. Cox regression analysis was used to calculate both crude and adjusted hazard ratios with 95% confidence intervals. The covariates included gender, age, pathology, smoking history, the family of cancer, tumor stage, node stage, lactate dehydrogenase (LDH) levels, hemoglobin (HGB) levels, platelet (PLT) levels, serum albumin (ALB) levels, BMI, EBV DNA levels, and GNRI score. We used two-tailed tests and a P value <0.05 was considered statistically significant. All statistical analyses were conducted using Statistical Package for the Social Sciences (SPSS) 25.0 software (IBM Corporation, Armonk, NY, USA).

Results

Clinical characteristics

Between January 2009 and July 2014, a total of 1,065 patients who were newly diagnosed with NPC were included in the study. The median duration of follow-up was 83 months (IQR, 72.1–90.5 months) and the median age of the whole study population was 45 years (IQR, 38–52 years). According to the median GNRI level (107.7, IQR, 104.1–110.6), patients were stratified into two groups with 527 (49.5%) in the high GNRI group and 538 (50.5%) in the low GNRI group. Patients in the low GNRI group had a higher proportion of women and the elderly (35.5% vs. 19.5%, 52.8% vs. 42.3%, respectively), higher levels of plasm EBV DNA and T stage, lower levels of hemoglobin (HGB) and serum albumin (ALB), and lower body mass index (BMI) than those in the high GNRI group. The clinical background characteristics and laboratory findings of the patients are provided in Table 1.

Table 1 NPC patient history and clinical features, according to GNRI
Full table

Clinical outcomes

According to baseline EBV DNA level, patients were divided into two groups: high EBV DNA group (>1,500 copies/mL) and low EBV DNA group (≤1,500 copies/mL). Patients in the high EBV DNA group showed worse OS (86.1% vs. 97.0%, P<0.001), PFS (78.8% vs. 91.6%, P<0.001), LRFS 91.9% vs. 95.3%, P=0.04), and DMFS (87.1% vs. 95.0%, P<0.001) compared to patients in the low EBV DNA group (Figure 1). Univariate Cox regression analysis revealed that gender, age, N stage, LDH levels, serum ALB levels, circulating EBV DNA levels, and GNRI score were significantly associated with OS. Furthermore, N stage, BMI, EBV DNA, and GNRI were significantly associated with PFS. Multivariate Cox regression analysis indicated that gender, age, N stage, LDH levels, PLT levels, circulating EBV DNA levels, and GNRI score could independently predict OS in NPC patients. Moreover, gender, N stage, circulating EBV DNA levels, and GNRI score could independently predict PFS (Table 2).

Figure 1 Kaplan-Meier survival curves for overall survival (A), progression-free survival (B), locoregional relapse-free survival (C), and distant metastasis-free survival (D) of patients with NPC stratified based on high and low baseline circulating EBV DNA levels. Categories are based on the 7^th edition of the Union for International Cancer Control/American Joint Committee on Cancer staging system. The cutoff value for baseline circulating EBV DNA levels was 1,500 copies/mL; five-year survival rates are presented.

Table 2 Univariate and multivariate Cox proportional hazards analysis of 1,065 patients with NPC
Full table

Prognostic value of pretreatment GNRI score

Compared to those in the low GNRI group, the five-year survival rate for OS, PFS, and DMFS was significantly higher in patients of the high GNRI group. However, there were no significant differences in the 5-year LRFS between the high and low GNRI groups (Figure 2). Multivariate analyses suggested that pretreatment GNRI score was an independent prognostic factor for OS and PFS (HR 0.471, 95% CI, 0.270–0.822, P=0.008; HR 0.638, 95% CI, 0.433–0.941, P=0.023, respectively) (Table 2). When analyzing the whole study population after adjusting for gender, age, pathology, smoking, the family of cancer, tumor stage, node stage, LDH levels, HGB levels, PLT levels, ALB levels, BMI, EBV DNA levels, and GNRI score, the interaction analysis showed no significant interaction effect between the GNRI score and other significant prognostic factors of OS and PFS (all P>0.05) (Table 3).

Figure 2 Kaplan-Meier survival curves for overall survival (A), progression-free survival (B), locoregional relapse-free survival (C), and distant metastasis-free survival (D) of patients with NPC stratified based on high and low baseline GNRI. Categories are based on the 7^th edition of the Union for International Cancer Control/American Joint Committee on Cancer staging system. The cutoff value for the baseline GNRI was 107.7; five-year survival rates are presented.

Table 3 Interaction analysis between GNRI and other significant prognostic factors and its effect on overall survival and progression-free survival
Full table

Prognostic value of the combination of GNRI score and EBV DNA level

In this study, we combined the pretreatment GNRI score and baseline EBV DNA level to stratify patients into the high-risk (high EBV DNA level and low GNRI score), low-risk (low EBV DNA level and high GNRI score), and medium-risk (both high level and both low level) groups. Our analysis showed significant separations between the OS, PFS, and DMFS survival curves of different risk groups. Survival was significantly poorer in patients in the high-risk group than those in the low- and medium-risk groups (all P<0.001). However, no significant differences in LRFS were observed among these three groups (P=0.159). Kaplan-Meier curves, stratified according to the combination of GNRI score and EBV DNA level, is shown in Figure 3. In the multivariate analysis, the combined classification was demonstrated to be an independent prognostic factor for OS and PFS after adjustment. In addition, the HRs for OS and PFS for the high-risk group were considerably higher than those observed when only baseline EBV DNA level was assessed (Table 4).

Figure 3 Kaplan-Meier survival curves for overall survival (A), progression-free survival (B), locoregional relapse-free survival (C), and distant metastasis-free survival (D) of patients with NPC stratified using a combination of GNRI and circulating EBV DNA levels. High-risk group: high EBV DNA and low GNRI; Low-risk group: low EBV DNA and high GNRI; Both high groups and both low groups were medium-risk group. Categories are based on the 7th edition of the Union for International Cancer Control/American Joint Committee on Cancer staging system; five-year survival rates are presented.

Table 4 Multivariate Cox proportional hazards analysis of 1,065 patients with NPC for the combination of GNRI and EBV DNA levels
Full table

Discussion

Radiotherapy and chemotherapy have been used as standard care in the treatment of NPC. Nevertheless, locoregional recurrence and distant metastasis occur frequently; hence, it is of great importance to explore new prognostic factors, which would potentially help establish individualized treatment regimens. In this study, our findings indicated that patients with NPC in the high GNRI score group exhibited better OS, PFS, and DMFS than those in the low GNRI score group. Multivariate analyses showed that GNRI was an independent prognostic factor for OS and PFS. Using GNRI, we could distinguish patients with high nutritional risk and provide more intensive nutritional treatment to improve patient outcomes. Moreover, the combination of GNRI and EBV DNA levels showed increased prognostic value when compared to the GNRI or EBV DNA data alone. Thus, intense treatment in subsequent phases, such as the inclusion of adjuvant chemotherapy, better nutritional treatment, or close follow-up, is required for patients in the high-risk group.

Malnutrition is a frequent comorbidity in patients with cancer, which is known to be associated with an increased incidence of complications and to have an adverse effect on long-term survival (17,18,20,28). It has been reported that malnutrition occurs in 35–60% of patients with NPC; a large proportion of these patients have problems related to nutrition before commencing treatment (29), which might significantly affect treatment responses. Previous studies show that anemia is associated with radiation resistance. Additionally, malnutrition reduces chemoradiotherapy tolerance, thereby prolonging treatment duration, which impairs immune function and increases the risk of secondary infections during treatment (15,30). Furthermore, poor nutritional status is often exacerbated during or after chemo- and radiotherapy. Adverse effects, such as nausea, vomiting, and radiation-induced oral mucositis, can decrease the food intake of patients and further worsen their nutritional status, which, in turn, can have an impact on treatment. Systematic nutritional monitoring and intervention in patients with head and neck cancer can significantly improve treatment outcomes. Subsequently, pretreatment nutrition screening and the identification of patients with NPC requiring nutritional interventions are essential to improve their treatment tolerance and survival.

Previous studies have demonstrated that low BMI, decreased hemoglobin, and serum albumin are markers of malnutrition. Those parameters have been used to identify patients suffering from nutritional deficits. However, their potential to assess nutritional status and predict prognosis is limited (20). The GNRI was originally developed to evaluate the nutritional status of elderly patients. Moreover, recent studies have confirmed the utility of GNRI to evaluate prognosis in patients with cancers, including esophageal carcinoma, lung cancer, and head and neck cancer (17-19,28,31). Hirahara et al. evaluated the impact of preoperative GNRI on clinical outcomes in 303 elderly patients with gastric cancer. Using preoperative GNRI level to categorize patients into low and normal GNRI groups, they found that GNRI is an important predictor of postoperative complications and overall survival in the elderly population afflicted with gastric cancer (28). Data from 248 patients with head and neck cancer (17) also showed that patients in the high-risk group had lower three-year survival rates compared to those in the intermediate- and normal-risk groups, and that the decreased GNRI score was significantly associated with an increased risk of mortality. In this study, a similar prognosis value of GNRI was investigated in the population afflicted with NPC

To the best of our knowledge, this is the first study to evaluate the prognostic relevance of GNRI determination in patients with NPC and to report that GNRI was independently associated with the prognosis of patients with NPC. As a useful biomarker of NPC, circulating EBV-DNA levels are associated with the early screening of patients with NPC, which has been shown to correlate with tumor burden, clinical-stage, treatment response, and patient survival (24). Here, to assess the mortality-risk prediction, we investigated the potential of the combined determination of GNRI and circulating EBV DNA levels in our cohort. Our results suggested that the integration of GNRI and circulating EBV DNA levels had an increased value in risk stratification and mortality prediction. Additionally, given the unbalanced distribution of gender, age, EBV DNA levels, and N stage in different GNRI groups, we conducted an interaction analysis. The results revealed no interaction between GNRI and other significant factors. We determined that the levels of circulating EBV DNA in patients with NPC in the high GNRI group were lower than those in patients in the low GNRI group. Therefore, we hypothesized that such results might correlate with good nutritional and immune status of the high GNRI group.

Although our study benefits from a large sample size, long follow-up time, and uniform CCRT treatment patterns, we acknowledge the presence of several limitations. This was a retrospective, non-randomized, observational study conducted in a single institute that had potential selection bias. A larger multicenter prospective study would be necessary to establish the role of the GNRI as a tool for predicting the outcomes of patients with NPC. Moreover, we failed to analyze the relationship between pretreatment GNRI and treatment-related side effects; therefore, further investigations are warranted. Despite these limitations, the current study could serve as a valuable reference for the survival prediction of patients with NPC.

Conclusions

Based on the large sample size, uniform treatment modality, and long-term follow-up study, our results confirmed the pretreatment GNRI score as an independent prognostic predictor for patients with NPC. The combination of baseline GNRI score and EBV DNA level improved the prognostic stratification of these patients. Therefore, we suggest that the GNRI score should be evaluated in patients with NPC.

Acknowledgments

Funding: This study was supported by grants from the National Key R&D Programme of China (2017YFC1309003 and 2017YFC0908500), the National Natural Science Foundation of China (81425018, 81672868, and 81802775), the Sci-Tech Project Foundation of Guangzhou City (201707020039), the Sun Yat-sen University Clinical Research 5010 Programme, the Special Support Plan of Guangdong Province (2014TX01R145), the Natural Science Foundation of Guangdong Province (2017A030312003 and 2018A0303131004), the Natural Science Foundation of Guangdong Province for Distinguished Young Scholars (2018B030306001), the Sci-Tech Project Foundation of Guangdong Province (2014A020212103), the Health & Medical Collaborative Innovation Project of Guangzhou City (201400000001 and 201803040003), the Pearl River S&T Nova Programme of Guangzhou (201806010135), the Planned Science and Technology Project of Guangdong Province (2019B020230002), the National Science and Technology Pillar Programme during the Twelfth Five-Year Plan Period (2014BAI09B10), and the Fundamental Research Funds for the Central Universities.

Footnote

Reporting Checklist: The authors have completed the REMARK reporting checklist. Available at http://dx.doi.org/10.21037/atm-20-6493

Data Sharing Statement: Available at http://dx.doi.org/10.21037/atm-20-6493

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at http://dx.doi.org/10.21037/atm-20-6493). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The study was approved by ethics board of Sun Yat-sen University Cancer Center and individual consent for this retrospective analysis was waived.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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