ABSTRACT
Hyponatremia, a prevalent electrolyte imbalance among tumor patients, has often been overlooked regarding its prognostic significance for immunotherapy. In this study, we delved into the prognostic ramifications of hyponatremia in advanced gastric cancer (AGC) patients undergoing immunotherapy. Enrolling AGC patients diagnosed between December 2014 and May 2021, we extracted pertinent data from electronic medical records, with a median follow-up of 35.8 months. Kaplan–Meier curves illuminated patients’ progression-free survival (PFS) and overall survival (OS), while survival disparities were tested using the Mantel–Haenszel log rank test. COX and logistic regressions were employed to scrutinize the correlation between serum sodium levels and prognosis in 268 AGC patients, both at baseline and during treatment. Notably, patients with hyponatremia exhibited shorter PFS (4.7 vs 2.1 months, p = .001*) and OS (12.5 vs 3.9 months, p < .001*). Serum sodium emerged as an independent prognostic factor for both PFS (HR = 1.773; 95% CI 1.067–2.945; p = .001*) and OS (HR = 1.773; 95% CI 1.067–2.945; p = .003*). Subgroup analysis revealed that AGC patients with hyponatremia derived no benefit from immunotherapy in terms of PFS and OS. Strikingly, a decrease in serum sodium during immunotherapy was associated with early relapse and mortality. Based on these findings, we hypothesize that hyponatremia portends poor prognostic outcomes in AGC patients treated with immunotherapy and may serve as a valuable prognostic biomarker. However, further large-scale prospective studies are warranted to validate these observations.
KEYWORDS: Gastric cancer, immunotherapy, natrium, prognostic analysis, biomarker
GRAPHICAL ABSTRACT
Introduction
Gastric cancer (GC) is one of the most common malignant tumors worldwide. According to the GLOBOCAN project of the International Agency for Research on Cancer (IARC), the estimated number of new cases of gastric cancer worldwide is as high as 1,089,000, which is the fourth highest incidence of tumors. GC-related deaths amounted to 768,000 cases, making it the fifth leading cause of cancer deaths worldwide.1 Of these, about 75% of new cases and deaths from GC occur in the Asian region.2
The clinical efficacy of traditional therapies for GC is limited. Due to the insidious onset and rapid progression of gastric cancer, most of the patients were in advanced stage when they were first diagnosed. Chemotherapy is the conventional treatment for advanced gastric cancer (AGC), but the median survival of conventional chemotherapy for AGC is less than 1 year.3,4 Targeted therapies have also not substantially improved the prognosis of GC patients due to their difficulty in screening the beneficiary population and their propensity for drug resistance.5,6
As one of the breakthroughs in the field of cancer treatment, immunotherapy has become another effective treatment modality after surgery, chemotherapy, radiotherapy, and targeted therapy, bringing hope to cancer patients, including GC patients.7 Based on promising results from the KEYNOTE-012 and KEYNOTE-059,8,9 pembrolizumab was approved in September 2017 as a third-line treatment for patients with programmed cell death 1 ligand 1 (PD-L1) Combined Positive Score (CPS) ≥1 with recurrent locally advanced or metastatic GC or gastro esophageal junction cancer (GEJC) patients. The ATTRACTION-2 study, which was conducted simultaneously in Asian gastric cancer patients, also showed promising results.10,11 As a result, nivolumab was approved in Japan for third-line treatment of GC. These programmed death-1 (PD-1) inhibitor therapies, represented by immune checkpoint inhibitors (ICIs), are gradually used in the clinic.
However, it is difficult for clinicians to assess the prognosis of GC patients treated with ICIs. There is an urgent need and necessity to explore potential biomarkers to screen GC patients who may benefit from treatment with ICIs. Although potential biomarkers such as PD-L1 expression, tumor mutational burden (TMB), microsatellite instability/mismatch repair (MSI/MMR) status, Epstein–Barr virus (EBV) infection, and circulating tumor DNA (ctDNA) have been reported in studies,12–20 less attention has been paid to the predictive value of sodium for the efficacy of GC patients treated with ICIs.
In the medical community, the diagnostic criterion for hyponatremia is a blood sodium concentration of less than 135 mmol/L, which is based on a large number of clinical practices and relevant studies.21 Hyponatremia, one of the most common electrolyte disorders associated with tumors, is nevertheless associated with a poor prognosis in a variety of tumors, such as hepatocellular carcinoma, gastric cancer, lung cancer, and gastrointestinal mesenchymal tumors.22–25 Some studies have shown that hyponatremia can be used as a prognostic biomarker in patients with lung cancer.26,27 However, research in GC needs to continue. On the one hand, the number of published studies in patients with GC is limited, and, on the other hand, no studies focusing on hyponatremia in patients with GC receiving immunotherapy have been reported. We hypothesized that hyponatremia still has an important role in suggesting poor immune prognosis in patients with AGC.
In view of the limitation of screening patients who can benefit from immunotherapy, the clinical data and follow-up data of 268 patients with AGC treated with ICIs were collected to analyze the relationship between ICIs and serum sodium, and its prognostic value in these patients.
Materials and methods
Research subjects
This study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee Of People’s Liberation Army General Hospital (protocol code S2021-642-01 and date of approval 30 December 2021). Informed consent was obtained from all subjects involved in the study. Clinical data, complete blood count, and basic metabolic panel results that were within 7 days prior to receiving immunotherapy were collected from 268 patients who were diagnosed with AGC in the Chinese People’s Liberation Army General Hospital from December 2014 to May 2021 and analyzed retrospectively. Inclusion criteria: 1) Patients with a definitive pathological diagnosis of GC stage III or IV; 2) Patients received multi-cycle immunotherapy (at least 2 treatment cycles); 3) During the treatment, the imaging efficacy evaluation of Response Evaluation Criteria In Solid Tumors (RECIST) 1.1 standard were completed multiple times (at least 1 evaluation completed); 4) Complete blood count and basic metabolic panel results were completed within 1 week before the first use of ICIs. Exclusion criteria: 1) Patients with infection, autoimmune disease, or idiopathic thrombocytopenic purpura; 2) Patients that had no assessable lesions; 3) Patients with other complications such as other tumors, heart failure, liver and kidney dysfunction, or other serious medical diseases; 4) Patients with missing complete blood count and basic metabolic panel results within 1 week before immunotherapy; 5) All patients taking drugs that can interfere with the sodium levels and hydration levels. Detailed treatment programs are available in Supplementary Material.
Assessment
During immunotherapy, imaging examination was performed every 4–6 weeks, and the short-term curative effect was evaluated according to RECIST1.1 standard of solid tumor. The evaluation results of curative effect were progressive disease (PD), partial response (PR), complete response (CR), and stable disease (SD), respectively. PD is defined as the increase in the total length and diameter of all measurable lesions by at least 20% or the appearance of new lesions. CR refers to the disappearance of tumor focus for more than 1 month. PR refers to the reduction of the sum of the length and diameter of all measurable focus by at least 30%. SD means that the therapeutic effect is between PR and PD. The short-term efficacy was evaluated by the overall response rate (ORR) = (CR+PR)/total cases × 100%, and the disease control rate (DCR) = (CR+PR+SD)/total cases × 100%. For long-term efficacy evaluation, progression-free survival (PFS) was defined as the time from the first treatment to the confirmation of PD, death, or the last follow-up, and overall survival (OS) which was defined as the time from the start of immunotherapy to death.
Statistical models by Na groups
We collected and recorded serum sodium levels in peripheral blood samples at baseline (within a window of 7 days prior to the first immunotherapy). The optimal cutoff value for serum sodium is 135 mmol/L. This criterion is based on a large number of clinical practices and relevant studies, and it is the lowest value within the normal range of basic metabolic panel results in the Oncology Center of the General Hospital of the Chinese People’s Liberation Army. Based on the optimal cutoff value of serum sodium, patients were divided into two groups: eunatremia group (145 mmol/L > serum sodium ≥135 mmol/L) and hyponatremia group (serum sodium <135 mmol/L).
Statistical analysis
All data were processed by SPSS 26.0 and GraphPad Prism9. Logistic regression analysis of the relationship between patients’ clinical characteristics and hyponatremia. We plotted Kaplan–Meier curves based on patients’ PFS and OS and assessed the difference in survival between patients in the hyponatremia group and those in the eunatremia group using the Mantel–Haenszel log rank test. Univariate and multivariate analyses were performed using the COX model to screen independent variables affecting prognosis and calculate their hazard ratios (HR). ORR and DCR, etc., were examined by Chi-squared Test or Fisher’s Exact Test. Reducing data bias and confounding factors through Propensity Score Matching (PSM). p < .05 is considered statistically significant and is indicated by *.
Results
Baseline characteristics
A total of 268 patients with AGC who received ICIs were enrolled in this study. Figure 1 provides an overview of the study population. Following stratification, 250 patients (93.3%) were categorized into the eunatremia group, while the remaining 18 patients (6.7%) comprised the hyponatremic group. The clinical characteristics of both groups are summarized in Table 1.
Figure 1.
Flow chart for the study of hyponatremia as a biomarker of poor immune prognosis. This study is a retrospective case analysis to investigate the predictive role of serum sodium indices on immune prognosis in patients with advanced gastric cancer, as well as a subgroup analysis close to the clinical reality, all of which showed that patients with hyponatremia were associated with a poor clinical prognosis. Abbreviations: AGC: advanced gastric cancer; ICIs: immune checkpoint inhibitors; PFS: progression-free survival; OS: overall survival.
Table 1.
General data and clinical feature of patients with advanced or metastatic gastric cancer.
| Characteristics | Number of patients (%) |
|||
|---|---|---|---|---|
| Overall (n = 268) |
The eunatremia group (n = 250) |
The hyponatremia group (n = 18) |
p | |
| Median age (range), years | 59 (18-86) | 59 (18-86) | 61 (34-77) | |
| Sex | ||||
| Female | 69 (25.7) | 66 (26.4) | 3 (16.7) | |
| Male | 199 (74.3) | 184 (73.6) | 15 (83.3) | .362 |
| Smoking history | ||||
| Yes | 101 (37.7) | 96 (38.4) | 5 (27.8) | |
| No | 167 (62.3) | 154 (61.6) | 13 (72.2) | .369 |
| Smoking exposure | ||||
| >30 packs per year | 48 (17.9) | 45 (18.0) | 3 (16.7) | |
| ≤30 packs per year | 220 (82.1) | 205 (82.0) | 15 (83.3) | .887 |
| ECOG PS | ||||
| ≥2 | 16 (6) | 13 (5.2) | 3 (16.7) | |
| 0-1 | 252 (94) | 237 (94.8) | 15 (83.3) | .047 |
| Pleural fluid | ||||
| Present | 19 (7.1) | 15 (6) | 4 (22.2) | |
| Absent | 249 (92.9) | 235 (94) | 14 (77.8) | .010* |
| Ascites | ||||
| Present | 66 (24.6) | 62 (24.8) | 4 (22.2) | |
| Absent | 202 (75.4) | 188 (75.2) | 14 (77.8) | .806 |
| Tumor location | ||||
| Cardia | 73 (27.2) | 68 (27.2) | 5 (27.8) | |
| Body/Fundus | 110 (41) | 102 (40.8) | 8 (44.4) | |
| Pylorus | 83 (31) | 78 (31.2) | 5 (27.8) | |
| Unknown | 2 (0.7) | 2 (0.8) | 0 (0) | .943 |
| HER-2 | ||||
| Present | 34 (12.7) | 32 (12.8) | 2 (13.1) | |
| Absent | 177 (66) | 165 (66) | 12 (65) | |
| Unknown | 57 (21.3) | 53 (21.2) | 4 (22.2) | .847 |
| Response to line before immunotherapy | ||||
| PD | 175 (65.3) | 160 (64) | 15 (83.3) | |
| Others | 93 (34.7) | 90 (36) | 3 (16.7) | .096 |
| Lines of immunotherapy | ||||
| ≥2 | 143 (53.4) | 131 (52.4) | 12 (66.7) | |
| <2 | 125 (46.6) | 119 (47.6) | 6 (33.3) | .241 |
| PD-1 inhibition agent | ||||
| Pembrolizumab | 36 (13.4) | 32 (12.8) | 4 (22.2) | |
| Nivolumab | 88 (32.8) | 81 (32.4) | 7 (38.9) | |
| Other | 144 (53.7) | 137 (54.8) | 7 (38.9) | .347 |
| ICIs combined with chemotherapy | ||||
| No | 173 (64.6) | 163 (65.2) | 10 (55.6) | |
| Yes | 95 (35.4) | 87 (34.8) | 8 (44.4) | .409 |
| Plasma osmolality | ||||
| ≤300mOsm | 250 (93.28) | 232 (92.80) | 18 (100.00) | |
| >300mOsm | 18 (6.72) | 18 (7.20) | 0 (0.00) | .489 |
PD: progressive disease; HER-2: human epidermal growth factor receptor-2; PD-1: programmed cell death-1; ECOG PS: eastern cooperative oncology group performance status scores; ICIs: immune checkpoint inhibitors. Plasma osmolality = 2 × (Na + K) + (Glucose/18) + (urea/2.8).
The median ages of patients in the eunatremia and hyponatremic groups were 59 and 61 years, respectively. In the eunatremia group, 184 patients (73.6%) were male, compared to 15 patients (83.3%) in the hyponatremic group (p = .362). More than half of the patients in both groups had no history of smoking (61.6% in the eunatremia group vs. 72.2% in the hyponatremic group, p = .369), and among those with a smoking history, most had smoked for less than 30 years (82.0% vs. 83.3%, p = .887). The proportions of patients with human epidermal growth factor receptor-2 (HER-2)-positive status were similar between the eunatremia and hyponatremic groups (12.8% vs. 13.1%, p = .847).
Notably, the proportion of patients without pleural effusion was significantly higher in the eunatremia group compared to the hyponatremic group (94% vs. 77.8%, p = .010*). However, there was no significant difference in the proportion of patients without ascites between the two groups (75.2% vs. 77.8%, p = .806). The tumor distribution was comparable between the groups, with similar proportions in the cardia, body/fundus, and pylorus regions.
Importantly, the general physical condition of patients in the eunatremia group was significantly better than that of the hyponatremic group, as evidenced by a higher proportion of patients with Eastern Cooperative Oncology Group performance status scores (ECOG PS) of 0–1 (94.8% vs. 83.3%, respectively; p = .047*).
Treatment characteristics
In the eunatremia group, 90 out of 250 patients (36.0%) had not progressed prior to immunotherapy, while 160 patients (64.0%) had. Among these patients, 32 (12.8%) received pembrolizumab, 81 (32.4%) received nivolumab, and 137 (54.8%) received other ICIs. Furthermore, 131 patients (52.4%) underwent multiple lines of immunotherapy, while 119 (47.6%) received first-line immunotherapy. Additionally, 163 patients (65.2%) were treated with ICIs in combination with chemotherapy, and 87 (34.8%) received ICIs without chemotherapy.
In the hyponatremia group, 3 out of 18 patients (16.7%) had not progressed before immunotherapy, while 15 (83.3%) had. Among these patients, four (22.2%) were treated with pembrolizumab, seven (38.9%) with nivolumab, and seven (38.9%) with other ICIs. Twelve patients (66.7%) underwent multiple lines of immunotherapy, while 6 (33.3%) received first-line immunotherapy. Ten patients (55.6%) were treated with ICIs in combination with chemotherapy, and 8 (44.4%) received ICIs without chemotherapy (as shown in Table 1).
Association between Na and efficacy
Based on the evaluation criteria of RECIST 1.1, the optimal response in the eunatremia group was observed as follows: 40.8% (102 patients) demonstrated PD, 1.6% (4 patients) exhibited CR, 28.8% (72 patients) showed PR, and 28.8% (72 patients) had SD. In the hyponatremia group, the study assessed the best efficacy and found that 50% (nine patients) had PD, 0% (zero patients) showed CR, 33.3% (six patients) exhibited PR, and 16.7% (three patients) presented with SD. No statistically significant differences were observed between the eunatremia and hyponatremic groups in terms of DCR (59.2% vs 50.0%, p = .444) or ORR (30.4% vs 33.3%; p = .794), as summarized in Table 2.
Table 2.
Response to PD-1 inhibitor therapy in patients with advanced or metastatic gastric cancer.
| Best Overall Response | Number of Patients (%) |
P value | ||
|---|---|---|---|---|
| Overall n = 268 |
The eunatremia group n = 250 (93.3) |
The hyponatremia group n = 18 (6.7) |
||
| CR | 4 (1.5) | 4 (1.6) | 0 (0.0) | 0.589 |
| PR | 78 (29.1) | 72 (28.8) | 6 (33.3) | 0.683 |
| SD | 75 (28) | 72 (28.8) | 3 (16.7) | 0.268 |
| PD | 111 (41.4) | 102 (40.8) | 9 (50.0) | 0.444 |
| Objective response | 82 (30.6) | 76 (30.4) | 6 (33.3) | 0.794 |
| Disease control rate | 157(58.6) | 148 (59.2) | 9 (50.0) | 0.444 |
PD-1: programmed cell death-1; CR: complete response; PR: partial response; SD: stable disease; PD: progressive disease; Objective response: CR+PR; Disease control rate: CR+PR+SD.
Association between Na and clinic-pathological features
Utilizing logistic regression equations, we conducted an analysis to determine the relationship between several fundamental factors – including age, sex, smoking history, smoking exposure, ECOG PS, family history, presence of pleural fluid, ascites, liver metastases, tumor site, and HER-2 expression – and sodium levels (Na). The findings from this comprehensive assessment are graphically represented in Figure 2. Notably, the existence of pleural fluid emerged as a significant risk factor for the development of hyponatremia, as evidenced by the Odds Ratio (OR) of 4.476 and a 95% Confidence Interval (CI) spanning from 1.311 to 15.279, with a statistically significant p-value of 0.017*. Conversely, the other clinical characteristics examined in this study, such as age and sex, did not exhibit any discernible correlation with hyponatremia.
Figure 2.
Most of the clinical-pathologic features did not correlate with Na. Logistic regression analysis showed that patients with the presence of pleural fluid would be at increased risk for lower serum sodium. Abbreviations: ECOG PS: eastern cooperative oncology group performance status score; HER-2: human epidermal growth factor receptor-2.
Association between Na and PFS
As of June 1, 2023, 17 patients with AGC exhibited no progression after immunotherapy. The median PFS was 4.7 months in the eunatremia group compared to 2.1 months in the hyponatremia group. Survival analysis revealed a significantly longer PFS benefit for AGC patients in the eunatremia group compared to those in the hyponatremia group (p = .001*) (Figure 3a).
Figure 3.
Poor immune prognosis in hyponatremic patients. Kaplan–Meier analysis for PFS(A) and OS(B) showed that patients with hyponatremia had a significantly poor survival prognosis. Abbreviations: PFS: progression free survival; OS: overall survival; AGC: advanced gastric cancer; Normal: the eunatremia group; Hypo: the hyponatremia group.
To further investigate the factors associated with disease progression, COX univariate and multivariate analyses were conducted. The dependent variable was disease progression after immunotherapy in AGC patients (no progression = 0, progression = 1), while independent variables included ECOG PS, number of treatment lines, presence of ascites, pleural fluid, and sodium levels. The results are presented in Figure 4.
Figure 4.
Hyponatremia is associated with increased risk of disease progression and death. After univariate COX regression analyses for PFS and OS, multivariate COX regression analyses were continued for variables with correlations. The corrected multivariate COX regression analysis showed that the risk of disease progression and death was 1.7 times higher in patients with hyponatremia than in patients with eunatremia. Abbreviations: PFS: progression-free survival; OS: overall survival; PD: progressive disease; ECOG PS: eastern cooperative oncology group performance status scores; Normal: the eunatremia group; Hypo: the hyponatremia group.
After adjusting for potential confounders in the COX multivariate model, the low sodium group emerged as an independent predictor of increased risk of progression (HR = 1.773; 95% CI, 1.067–2.945; p = .001*). Additionally, patients with ECOG PS ≥ 2 had a 1.6 times higher risk of disease progression compared to those with ECOG PS 0–1 (HR 1.634; 95% CI 0.960–2.779; p = .001*). Patients who received ≥ 2 lines of immunotherapy had a 1.6 times higher risk of progression compared to those who received immunotherapy as a first-line treatment (HR 1.629; 95% CI 1.255–2.115; p < .001*). The presence of ascites was associated with a 1.1 times higher risk of progression compared to the absence of ascites (HR 1.141; 95% CI 0.841–1.547; p = .035*), and the presence of pleural fluid was associated with a 1.5 times higher risk of progression compared to its absence (HR 1.550; 95% CI 0.923–2.603; p = .004*).
Association between Na and OS
As of June 1, 2023, 76 patients with AGC remained alive. The median OS was 12.5 months in the eunatremia group compared to 3.9 months in the hyponatremic group. Survival analysis demonstrated a significantly longer OS benefit for AGC patients in the eunatremia group compared to those in the hyponatremia group (p < .001*) (Figure 3b).
To further investigate the factors associated with survival after immunotherapy in AGC patients, COX univariate and multivariate analyses were conducted. The dependent variable was survival after immunotherapy (survival = 0, death = 1), while independent variables included ECOG PS, number of treatment lines, presence of ascites, pleural fluid, and sodium levels. The results are presented in Figure 4.
After adjusting for potential confounders in the COX multivariate model, the hyponatremic group emerged as an independent predictor of increased risk of death (HR = 1.773; 95% CI, 1.067–2.945; p = .003*). Additionally, patients with ECOG PS ≥ 2 had a 1.6 times higher risk of death compared to those with ECOG PS 0–1 (HR 1.634; 95% CI 0.960–2.779; p < .001*). Patients who received ≥2 lines of immunotherapy had a 1.6 times higher risk of death compared to those who received immunotherapy as a first-line treatment (HR 1.629; 95% CI 1.255–2.115; p = .001*). Although patients with ascites had a slightly higher risk of death compared to those without ascites, this difference was not statistically significant (HR 1.141; 95% CI 0.841–1.547; p = .247). However, patients with pleural fluid had a 1.5 times higher risk of death compared to those without pleural fluid (HR 1.550; 95% CI 0.923–2.603; p = .032*).
Association between Na and outcomes of one or multiple (≥2) immunotherapy lines: subgroup analysis
After adjusting for COX multivariate modeling, patients treated with first-line ICIs demonstrated significant improvements in both PFS (p < .001*) and overall survival (OS) (p = .001*). Given these findings, we conducted subgroup analyses stratified by the number of treatment lines.
In the subgroup of patients treated with subsequent ICI therapy, there were 131 individuals in the eunatremia group and 12 in the hyponatremic group. Notably, both PFS (p = .046*) and OS (p = .004*) were significantly better in the eunatremia group compared to the hyponatremia group, as shown in Supplementary figure 1.
For patients treated with first-line ICIs, the eunatremia group comprised 119 individuals, while the hyponatremic group had 6. When comparing PFS between these two groups, the eunatremia group exhibited a significant improvement (p = .014*), as depicted in Supplementary figure 2A. However, there was no statistically significant difference in OS between the groups (p = .060*), as illustrated in Supplementary figure 2B.
Association between Na and outcomes of ICIs with or without chemotherapy: subgroup analysis
To mitigate the sampling error stemming from the application of varying immunotherapy schemes across different treatment lines, we conducted a subgroup analysis based on distinct immunotherapy regimens. Specifically, within the eunatremia group, 163 patients underwent treatment with ICIs without chemotherapy, whereas in the hyponatremic group, 10 patients received the same ICI-only therapy. Notably, both PFS (p = .017*) and OS (p = .016*) were significantly better in the eunatremia group when compared to the hyponatremia group, as illustrated in Supplementary figure 3.
Among patients who received a combination of ICIs and chemotherapy, 87 belonged to the eunatremia group, and 8 were part of the hyponatremic group. In comparing PFS (p = .036*) and OS (p = .016*) between these two subgroups, the eunatremia group demonstrated improvements, as shown in Supplementary figure 4.
Association between Na and outcomes of ICIs in patients of different ages: subgroup analysis
To minimize the potential bias stemming from age differences in immunotherapy utilization among patients, we conducted subgroup analyses stratified by distinct age groups. With a median age of 59 years among the 268 patients enrolled in this study, and a similar median for the predominantly represented eunatremia group, we established 59 years as the threshold for defining these subgroups.
In the subgroup of patients aged 59 years or older, there were 128 individuals in the eunatremia group and 11 in the hyponatremic group. Notably, the eunatremia group exhibited significant prolongations in both PFS (p = .043*) and OS (p = .021*) compared to the hyponatremia group, as depicted in Supplementary figure 5.
Among the remaining patients younger than 59 years, 122 belonged to the eunatremia group, while 7 were categorized in the hyponatremia group. Once again, significant prolongations in both PFS (p = .001*) and OS (p = .003*) were observed in the eunatremia group compared to the hyponatremia group, as illustrated in Supplementary figure 6.
Relationship between Na changes during immunotherapy and prognosis: subgroup analysis
After conducting a comprehensive evaluation of the relationship between serum sodium changes and disease progression at distinct time points following immunotherapy administration, we observed notable trends. Specifically, 4 weeks into the immunotherapy regimen, serum sodium data were available for 224 patients. Of these, 119 patients (53.1%) exhibited a decrease in serum sodium levels (δ change <0 from baseline to 4 weeks), while 105 patients (46.9%) showed an increase or no change (δ change ≥0). By the eighth week of immunotherapy, serum sodium data were available for 207 patients, with 101 (48.8%) demonstrating a decrease and 106 (51.2%) showing an increase or no change in serum sodium levels (Supplementary figure 7).
Our findings revealed a significant association between a decrease in serum sodium levels from baseline to the eighth week of immunotherapy and an increased risk of recurrent tumor progression within 6 months (OR = 0.914, 95% CI 0.840–0.995, p = .039*) (Supplementary table 1). Furthermore, when comparing the fourth and eighth weeks of treatment, a decrease in serum sodium after 8 weeks of immunotherapy was significantly associated with an increased risk of death within 8 months (OR = 0.903, 95% CI 0.827–0.987, p = .024*) (Supplementary table 2). These results underscore the importance of monitoring serum sodium levels during immunotherapy treatment as they may serve as a valuable prognostic indicator for disease progression and patient survival.
Association of Na with OS and PFS, respectively, in the study population after PSM: subgroup analysis
After PSM, we observed significant elimination of between-group differences in the data. The standardized mean difference (SMD) after matching has decreased substantially compared to that before matching, and the SMD values of most covariates have dropped below 0.2, which suggests that the distributions of the two groups on these covariates have converged (Supplementary table 3). In addition, the probability density plots after PSM showed a higher graphical overlap between the hyponatremia group and eunatremia group than the overlap of the probability density plots before PSM (Supplementary figure 8). Our plotted Kaplan–Meier curves showed that patients in the hyponatremia group had shorter OS and PFS than those in the eunatremia group (Supplementary figure 9).
Discussion
Recent studies have reported that metal ions can enhance anti-tumor immunity and thus function as a cancer-clearing agent. The term “metalloimmunology” will be officially introduced in 2020,28 followed by a detailed report on “cancer metallotherapy” in 2021.29 These fully affirm the advantages of metal ions in tumor immunotherapy.
Since the important role of metal ions in tumors has been confirmed by research, we cannot help but wonder whether abnormal levels of sodium metal ions, which make up the largest portion of the extracellular fluid, are associated with tumors. The mechanism of cancer-related hyponatremia is still up for debate, however most of the research seem support the syndrome of inappropriate antidiuretic hormone secretion (SIADH).30 Abnormally elevated atrial natriuretic peptide can also reduce water and sodium retention, resulting in hyponatremia. Other possible mechanisms include renal salt wasting syndrome (RSWS), hypovolemia or hypervolemia, insufficient glucocorticoid secretion, hypothyroidism, and surgical treatment.31 In addition, anti-tumor drugs can also disrupt the regulation of serum sodium and water balance by the neurohumoral system, leading to hyponatremia. Relevant studies have reported that the use of platinum-based chemotherapy drugs is significantly related to the occurrence of hyponatremia.32-34 A prospective randomized phase III clinical trial evaluating the correlation between hyponatremia and targeted therapy showed that the incidence of hyponatremia was highest in patients treated with a combination of brivanib and cetuximab, and brivanib and pazopanib. Angiogenesis inhibitors are more likely to cause severe hyponatremia than anti-epidermal growth factor receptor drugs.35 ICIs represented by ipilimumab can also trigger hypophysitis and lead to hyponatremia.36-39
In addition, it has also been reported that blood sodium is closely related to dehydration status and is also one of the biochemical parameters for evaluating dehydration status. As for plasma osmolality, which is also a biochemical parameter for evaluating dehydration status, it was significantly positively correlated with heart rate and capillary refill and negatively correlated with systolic blood pressure.40 While in the present study, no statistically significant difference was found between elevated plasma osmolality and hyponatremia. Hyponatremia is a poor prognostic factor in patients with malignant tumors, and this conclusion has been supported by studies of various malignant tumors.41,42 A retrospective study of 320 elderly patients with small cell lung cancer was conducted to investigate the relationship between hyponatremia and the prognosis of small cell lung cancer. It was found that hyponatremia was closely related to the poor prognosis of patients with small cell lung cancer.43 Another study aimed to explore the relationship between preoperative hyponatremia and prognosis of patients with GC and conducted a retrospective study of 842 patients with GC. It was found that preoperative hyponatremia was a poor prognostic factor for elderly patients with GC, but this was not the case for young patients.44 At present, studies on hyponatremia are mainly focused on the combined event of patients after surgery and chemotherapy, and there are few reports on the relationship between hyponatremia and the prognosis of patients with AGC treated with ICIs.
In our study, we retrospectively analyzed the correlation between PFS and OS and Na in 268 AGC patients treated with immunotherapy for the first time. Our study found that hyponatremia was associated with shorter PFS and OS in AGC patients treated with ICIs. This is consistent with previous findings. We further analyzed the correlation between Na biomarkers and the prognosis of immunotherapy. Univariate analysis showed that PFS and OS were shorter in the hyponatremic group than in the eunatremia group. After adjustment for COX multivariate modeling, the hyponatremia group was independently associated with an increased risk of death and progression. Although studies between hyponatremia and AGC patients receiving immunotherapy are limited, there have been previous reports on hyponatremia and AGC patients receiving conventional chemotherapy.33 In a retrospective case analysis of gastric cancer patients receiving 5-fluorouracil in combination with cisplatin, Boku et al. concluded that hyponatremia after chemotherapy may be a serious warning sign of subsequent severe hematologic toxicity. In contrast, this study did not focus on the adverse effects of treatment, but rather explored hyponatremia and prognostic survival.
Due to variations in immunotherapy regimens among subjects of diverse ages included in the study, we conducted subgroup analyses to investigate the impact of hyponatremia on PFS and OS in patients stratified by age and treatment regimen. The results of the subgroup analysis showed that patients with low sodium were associated with shorter PFS whether they were treated with first- or multi-line immunotherapy. However, the effect of hyponatremia on shortening OS was only statistically significant with multi-line immunotherapy. In addition, AGC patients with hyponatremia did not benefit in PFS and OS regardless of whether immunotherapy was combined with chemotherapy or not, and regardless of whether the patients were older than 59 years. It was also interesting to note that patients with serum sodium levels below baseline at 8 weeks after the initial immunotherapy had an increased risk of tumor recurrence and progression within 6 months. Similarly, those with serum sodium levels lower at 8 weeks compared to 4 weeks after the initial immunotherapy had an elevated risk of death within 8 months. Decrease in serum sodium level in patients after treatment was also reported in the study by Boku et al. However, their study focused on short-term serum sodium changes after drug administration, whereas 8 weeks and 4 weeks were selected as time points in our study. Short-term decrease in serum sodium suggests that the subsequent occurrence of hematologic toxicity and the long-term decrease in serum sodium predict an increased risk of disease progression and death. However, we do not know the underlying mechanism for the poor prognosis of AGC patients receiving immunotherapy with concomitant hyponatremia, and continued in-depth studies are needed to explore the causal relationship between hyponatremia and immune tolerance.
This study also found that AGC patients with ECOG PS ≥ 2, subsequent treatment with ICIs, and with pleural effusions did not benefit from PFS and OS after immunotherapy. AGC patients with abdominal effusion did not benefit from PFS after immunotherapy. In addition to this, we noticed an interesting phenomenon that hyponatremia was significantly associated with pleural effusion. We hypothesize that this is due to hyponatremia resulting from excessive sodium loss from the body due to large pleural effusions. As to why the data in this experiment showed no statistically significant correlations between hyponatremia and pleural effusion, we hypothesize that it may be that the amount of pleural effusion in the AGC patients who participated in this study was not large enough and that the body could still compensate for the sodium loss through self-regulation. It is necessary to expand the sample size to verify the true association between the two.
There are some limitations in this study: 1) The current study is a single-center, small-sample retrospective study with low level of evidence and possible bias. In particular, there is a gap in the amount of data on patients with hyponatremia versus those with eunatremia. Therefore, these preliminary results need to be further verified by prospective research; 2) Lack of control group of patients who did not receive PD-1 inhibitor treatment; 3) Due to the large amount of missing data, the correlation between the serum sodium biomarker combined with the expression of PD-L1 and the prognosis of immunotherapy was not discussed; 4) The causal relationship between hyponatremia and immunotherapy tolerance in patients with GC was not explored.
Conclusion
Our study shows for the first time that baseline Na is an independent predictor of prognosis in AGC patients on immunotherapy. Nutrient Na as a biomarker can screen patients who may have a better prognosis after PD-1 therapy. This nutrient metric may help clinicians identify AGC patients who are more likely to benefit from anti-PD-1 therapy prior to treatment initiation. In addition, as routine attribute assessments, this marker is easier to apply in clinical practice.
Supplementary Material
Acknowledgments
The author gratefully acknowledges the advice and inspiration from Guanghai Dai.
Biography
Guanghai Dai is the Director of Department of Medical Oncology, Department of Medical Oncology, General Hospital of the People’s Liberation Army (PLA), Chief Physician, Professor, and Doctoral Supervisor. His main research interests are basic and clinical research on malignant tumors of the digestive system, and he mainly explores comprehensive treatment and individualized precision treatment under the MDT model; he has published more than 120 articles in domestic and international journals, including more than 40 SCI articles. He has undertaken one project of the 12th Five-Year Plan of the Ministry of Science and Technology, one project of the Capital Specialized Clinical Application and Promotion Project, one project of the National Key Research and Development Program of China for Precision Medicine Research, two projects of the National Natural Science Foundation of China, one project of the 11th Five-Year Plan of the Army, one project of the Beijing Natural Science Foundation, one project of the Capital Specialized Clinical Program, and four projects of the Wu Jiping Clinical Fund, with a cumulative total of more than 12 million RMB.
Funding Statement
The author(s) reported that there is no funding associated with the work featured in this article.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Author contributions
YP: Conceptualization; Writing – original draft; Writing – review & editing. YM: Data curation; Visualization; Writing – original draft. HG: Visualization; GD: Project administration; Writing – review & editing. All authors contributed to the completion of the article and approved the submitted version.
Author declarations
Y.P. and Y.M. contributed equally to this work. The authors have no conflict of interest. The paper is not under consideration at another journal but has been posted on Research Square as a preprint. The DOI link is https://doi.org/10.21203/rs.3.rs-2744774/v1.
Data availability statement
The data presented in this study are available on request from the corresponding author. The data are not publicly available due to future planned analysis.
Institutional review board statement
This study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee Of Chinese PLA General Hospital (protocol code S2021-642-01 and date of approval December 30, 2021).
Informed consent statement
Informed consent was obtained from all subjects involved in the study.
Supplementary Material
Supplemental data for this article can be accessed on the publisher’s website at https://doi.org/10.1080/21645515.2024.2414546
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The data presented in this study are available on request from the corresponding author. The data are not publicly available due to future planned analysis.