Abstract
Background
The adapted systemic inflammation score (aSIS), calculated from serum albumin and the lymphocyte‐to‐monocyte ratio, has been reported to be a novel prognostic marker for some types of cancers. However, the prognostic impact of aSIS in patients with esophageal squamous cell carcinoma (ESCC) remains controversial. This study aimed to examine the prognostic effects of aSIS in a large cohort of 509 ESCC patients.
Methods
Preoperative aSIS was retrospectively calculated for 509 ESCC patients who underwent curative resection. Time‐dependent receiver operating characteristics (t‐ROC) curves were used for comparing the prognostic impact.
Results
Patients with high aSIS showed significantly poorer overall survival (OS) than patients with low aSIS (log rank P < .001). The multivariate analysis revealed that aSIS was an independent prognostic factor for overall survival (multivariate hazard ratio 1.76; 95% confidence interval 1.13–2.75; P = .013). The t‐ROC analysis showed that aSIS was more sensitive than other nutritional prognostic factors (controlling for nutritional status, systemic inflammation score, and the neutrophil‐to‐lymphocyte ratio).
Conclusion
Preoperative aSIS may be a useful prognostic biomarker in ESCC patients who underwent curative resection.
Keywords: adapted systemic inflammation score, esophageal squamous cell carcinoma, prognosis
This study examined the prognostic effects of the adapted systemic inflammation score (aSIS), calculated from serum albumin and the lymphocyte‐to‐monocyte ratio, in a large cohort of 509 esophageal squamous cell carcinoma (ESCC) patients. ESCC patients with high aSIS showed significantly poorer overall survival than patients with low aSIS. aSIS was more sensitive than other nutritional prognostic factors (controlling for nutritional status, systemic inflammation score, and the neutrophil‐to‐lymphocyte ratio).
1. INTRODUCTION
Esophageal cancer is the sixth leading cause of cancer death and the seventh most common cancer worldwide.1 Despite the development of multidisciplinary treatment strategies, including surgery, chemotherapy, radiotherapy, and chemoradiotherapy, the prognosis of patients with esophageal cancer, including those who underwent complete resection, remains poor. Thus, better prognostic biomarkers are needed for making appropriate treatment decisions for esophageal cancer patients.
The systemic inflammation score (SIS) was developed as a new scoring system based on serum albumin (Alb) and the lymphocyte‐to‐monocyte ratio (LMR). SIS has been reported as a powerful prognostic marker for clear‐cell renal cell carcinoma and colorectal cancer.2, 3 The cutoff value of LMR in SIS was the median value for patients with renal cell carcinoma. Therefore, Lin et al developed a modified SIS (mSIS) with optimized LMR cutoff values for gastric cancer patients using the software X‐tile (Yale University, New Haven, CT).4 The mSIS has been shown to be superior to SIS as a predictive indicator for gastric cancer.5 Several studies have examined the prognostic role of SIS and mSIS in esophageal squamous cell carcinoma (ESCC).6, 7, 8 However, previous data on SIS, mSIS, and clinical outcomes for ESCC have been inconclusive because previous studies were limited by small sample sizes (n < 443). Considering the importance of a potential prognostic marker for ESCC, the assessment of SIS and clinical outcome using a large number of ESCC cases is needed.
In this study we reoptimized the LMR cutoff values as 3.3 using the software X‐tile according to esophageal cancer patients’ cohort, and defined adapted SIS (aSIS). The prognostic effects of aSIS were examined in a large cohort of 509 ESCC patients. Our nonbiased database enabled us to examine whether the influence of aSIS on clinical outcome was modified by numerous other variables. Furthermore, the predictive value of aSIS was compared with that of other known nutritional prognostic factors (Controlling Nutritional Status [CONUT] and Neutrophil‐to‐Lymphocyte ratio [NLR]).
2. MATERIALS AND METHODS
2.1. Patients
Between April 2005 and December 2017, 751 consecutive patients with esophageal cancer who underwent curative resection at Kumamoto University Hospital were enrolled. Of these patients, patients who underwent salvage esophagectomy (53), pharyngolaryngoesophagectomy (27), transhiatal esophagectomy (11), and noncurative surgery (R1 or R2 resection) (53) and with other histological types (93) and who lack peripheral monocyte data (5) were excluded from the study. Thus, a total of 509 patients with esophageal cancer who underwent subtotal esophagectomy were eventually included in the study. We classified the clinical tumor stage according to the Union for International Cancer Control (UICC) TNM classification of malignant tumors, seventh edition.9 Patients were followed up as outpatients every 1–3 mo after discharge until death or December 2019, whichever came first. Overall survival (OS) was defined as the period from the date of surgery to the date of death. Cancer‐specific survival (CSS) was defined as the period from the date of surgery to the date of death owing to esophageal cancer. Patients' clinicopathological characteristics were obtained retrospectively from the medical records. These characteristics included age, sex, body mass index (BMI), comorbidity, preoperative therapy, clinical tumor stage, OS, and CSS. Written informed consent was obtained from each patient, and the study was approved by the Institutional Review Board of Kumamoto University (#1909). The term “prognostic marker” was used throughout this article according to the Reporting Recommendations for Tumor Marker Prognostic Studies (REMARK) guidelines.10
2.2. The aSIS and other scoring systems
Serum samples were obtained and analyzed within 7 d before esophagectomy. The aSIS was calculated from serum albumin and peripheral LMR (Figure 1). The LMR cutoff value was calculated using the software X‐tile,4 which determined the LMR cutoff value as 3.3 (Figure S1).
FIGURE 1.
Flow chart of the analyzed cases and the definition of adapted systemic inflammation score
NLR and CONUT scores were calculated as described previously.11, 12, 13
2.3. Statistical analyses
All statistical analyses were performed using JMP v. 10 (SAS Institute, Cary, NC) and EZR (Saitama Medical Center, Jichi Medical University, Japan). Categorical variables were presented as numbers or percentages, and the groups were compared using the chi‐squared test or Fisher's exact test. Continuous variables are presented as mean values and standard deviations, and the mean values were compared using Student's t‐test. For survival analysis, the Kaplan–Meier method was used for evaluating the survival time distribution, and the log‐rank test was performed for comparisons. The multivariate Cox proportional hazards model was constructed for computing hazard ratios (HRs) and 95% confidence intervals (CIs) according to aSIS containing clinicopathological factors potentially related to the clinical outcome. Time‐dependent receiver operating characteristic curves (ROCs) for the prognostic values of NLR, CONUT, SIS, and aSIS were estimated using the R package “timeROC” (https://cran.r‐project.org/web/packages/timeROC/index.html). Variables with P < .05 in the univariate analysis were subjected to the multivariate model using a stepwise backward elimination procedure with a threshold P < .05. Statistical significance was set at P < .05.
3. RESULTS
3.1. mSIS and clinicopathological characteristics
Of the 509 ESCC patients, 446 (88%) were men and 63 (12%) were women. The mean age was 66.3 y (range, 41–89 y). Patients were segregated into three groups based on the aSIS: 207 patients (40%) in the aSIS = 0 group, 202 (40%) in the aSIS = 1 group, and 100 (20%) in the aSIS = 2 group (Figure 1). The relationships between aSIS and clinicopathological factors are presented in Table 1. Older age, poorer performance status (PS), lower BMI, and higher clinical stage were significantly associated with higher aSIS (each P < .05).
TABLE 1.
Patient characteristics
| Variables | Total N | aSIS | P value | ||
|---|---|---|---|---|---|
| 0 | 1 | 2 | |||
| All cases | 509 | 207 | 202 | 100 | |
| Mean age ±SD | 66.3 ± 8.0 | 64.6 ± 8.0 | 67.8 ± 7.8 | 67.2 ± 8.3 | < .01 |
| Sex, male | 446 (88%) | 178 (86%) | 176 (87%) | 92 (92%) | .31 |
| Performance status | |||||
| 0 | 443 (87%) | 190 (92%) | 175 (87%) | 78 (78%) | < .01 |
| 1 | 57 (11%) | 17 (8%) | 21 (10%) | 19 (19%) | |
| 2 | 9 (2%) | 0 (0%) | 6 (3%) | 3 (3%) | |
| Body Mass Index | |||||
| <18.5 | 61 (12%) | 16 (8%) | 26 (13%) | 19 (19%) | < .01 |
| 18.5 ≤, <25 | 368 (72%) | 146 (70%) | 151 (75%) | 71 (71%) | |
| 25≤ | 80 (16%) | 45 (22%) | 25 (12%) | 10 (10%) | |
| Alcohol use, Yes | 483 (95%) | 197 (95%) | 192 (95%) | 94 (94%) | .91 |
| Tobacco use, Yes | 436 (86%) | 168 (82%) | 176 (87%) | 92 (92%) | .026 |
| Comorbidity, Present | 392 (77%) | 145 (70%) | 166 (82%) | 81 (81%) | < .01 |
| Preoperative treatment | |||||
| Present | 195 (38%) | 44 (21%) | 91 (45%) | 60 (60%) | < .01 |
| Absent | 314 (62%) | 163 (79%) | 111 (55%) | 40 (40%) | |
| Tumor location | |||||
| Ce | 2 (1%) | 1 (1%) | 1 (1%) | 0 (0%) | .71 |
| Ut | 72 (14%) | 31 (15%) | 32 (16%) | 9 (9%) | |
| Mt | 279 (55%) | 112 (54%) | 113 (56%) | 54 (54%) | |
| Lt | 143 (28%) | 58 (28%) | 51 (25%) | 34 (34%) | |
| Ae | 13 (2%) | 5 (2%) | 5 (2%) | 3 (3%) | |
| Clinical stage | |||||
| I | 252 (50%) | 140 (68%) | 89 (44%) | 23 (23%) | < .01 |
| II | 89 (17%) | 30 (14%) | 39 (19%) | 20 (20%) | |
| III | 143 (28%) | 26 (13%) | 68 (34%) | 49 (49%) | |
| IV | 25 (5%) | 11 (5%) | 6 (3%) | 8 (8%) | |
| Postoperative treatment | |||||
| Present | 96 (19%) | 50 (24%) | 30 (15%) | 16 (16%) | .053 |
| Absent | 413 (81%) | 157 (76%) | 172 (85%) | 84 (84%) | |
Abbreviations: aSIS, adapted systemic inflammation score; SD; standard deviation.
3.2. Correlations between the aSIS and short‐term outcomes of surgery
The short‐term outcomes after surgery according to the aSIS are presented in Table 2. High aSIS was significantly associated with a higher incidence of pulmonary morbidity (P < .01). Other complications and complication severity were not associated with aSIS. We checked the correlation between aSIS and patients' characteristics affecting pulmonary morbidity such as a respiratory function or surgical procedure. Regarding a respiratory function, we analyzed percent vital capacity (%VC) and forced expiratory volume in 1 sec as a percentage of forced vital capacity (FEV1.0%). %VC decreased significantly as aSIS increased (Figure S2; P < .001). On the other hand, there was no significant correlation between FEV1.0% and aSIS (Figure S2; P = .698). Regarding a surgical procedure, we checked minimally invasive esophagectomy (MIE) and open esophagectomy (OE). There were more patients with aSIS:2 and fewer patients with aSIS:0 in the OE group than in the MIE group (Figure S2; P = .011).
TABLE 2.
Short‐term outcome of surgery
| Variables | Total N | aSIS | P value | ||
|---|---|---|---|---|---|
| 0 | 1 | 2 | |||
| All cases (Subtotal esophagectomy) | 509 | 207 | 202 | 100 | |
| Operating time (min) ±SD | 562 ± 121 | 579 ± 129 | 552 ± 115 | 548 ± 114 | .033 |
| Blood loss (g) ±SD | 475 ± 556 | 467 ± 684 | 437 ± 382 | 568 ± 555 | .15 |
| Postoperative morbidity, CDc ≥II | 193 (38%) | 81 (39%) | 67 (33%) | 45 (45%) | .12 |
| Postoperative morbidity, CDc ≥IV | 33 (6%) | 12 (6%) | 11 (5%) | 10 (10%) | .31 |
| Surgical site infection | 125 (25%) | 56 (27%) | 48 (24%) | 21 (21%) | .48 |
| Pulmonary morbidity | 87 (17%) | 31 (15%) | 28 (14%) | 28 (28%) | < .01 |
| Cardiovascular morbidity | 29 (6%) | 12 (6%) | 11 (5%) | 6 (6%) | .98 |
| Anastomotic leakage | 64 (13%) | 31 (15%) | 18 (9%) | 15 (15%) | .12 |
| Reoperation | 35 (7%) | 14 (7%) | 16 (8%) | 5 (5%) | .63 |
Abbreviations: aSIS, adapted systemic inflammation score; CDc, Clavien–Dindo classification; SD, standard deviation.
3.3. Adapted systemic inflammation score and patient survival
The impact of aSIS on clinical outcomes was assessed in ESCC patients. There were 168 deaths among the 509 patients, including 96 esophageal cancer‐specific deaths. The median follow‐up time for censored patients was 4.0 y. The Kaplan–Meier analysis showed that there was a significant difference in the OS and CSS among the three groups (both log rank P < .01). The 3‐y OS rates in groups 0, 1, and 2 were 84.1%, 74.6%, and 57.3%, respectively (Figure 2). The 3‐y CSS rates in groups 0, 1, and 2 were 87.5%, 81.3%, and 72.0%, respectively (Figure 2).
FIGURE 2.
Kaplan–Meier curves for the overall survival (OS) and cancer‐specific survival in esophageal squamous cell carcinoma patients according to adapted systemic inflammation score stratification
In the univariate analysis, a high aSIS score was associated with poor OS (HR 2.50, 95% CI 1.65–3.79, P < .01) (Table 3). For patient factors, advanced age (HR 1.56, 95% CI 1.14–2.17, P < .01), lower BMI (HR 1.81, 95% CI 1.16–2.71, P < .01), and poor PS (HR 2.09, 95% CI 1.41–3.01, P < .01) were significantly associated with poor OS. For tumor factors, clinical stage (HR 2.19, 95% CI 1.60–2.97, P < .01) was significantly associated with poor OS. In the multivariate analysis, aSIS was an independent prognostic factor for the OS (multivariate HR 1.81, 95% CI 1.16–2.81, P < .01). The other independent prognostic factors were advanced age, low BMI, poor PS, and postoperative complications.
TABLE 3.
Cox regression analysis for overall survival
| Variables | Univariate analysis | Multivariate analysis | ||
|---|---|---|---|---|
| HR (95% CI) | P value | HR (95% CI) | P value | |
| Age (≥ 65 vs <65) | 1.56 (1.14–2.17) | < .01 | 1.46 (1.03‐2.07) | .032 |
| Sex (male vs female) | 1.18 (0.74–1.98) | .52 | ||
| Brinkman Index (≥800 vs <800) | 1.05 (0.77–1.42) | .77 | ||
| Body Mass Index | ||||
| (≥25 vs <25) | 0.72 (0.44–1.12) | .15 | ||
| (<18.5 vs ≥18.5) | 1.81 (1.16–2.71) | < .01 | 1.67 (1.06–2.53) | .028 |
| Performance Status (1, 2 vs 0) | 2.09 (1.41–3.01) | < .01 | 1.54 (1.01–2.27) | .043 |
| Comorbidity (+ vs –) | 1.52 (1.04–2.29) | .028 | 1.16 (0.77–1.78) | .48 |
| cStage (III, IV vs I, II) | 2.19 (1.60–2.97) | < .01 | 1.38 (0.90–2.12) | .14 |
| Preoperative treatment (+ vs −) | 2.18 (1.59–2.97) | < .01 | 1.50 (0.98–2.27) | .060 |
| Preoperative aSIS | ||||
| (1 vs 0) | 1.76 (1.23–2.54) | < .01 | 1.36 (0.93–2.01) | .11 |
| (2 vs 0) | 2.50 (1.65–3.79) | < .01 | 1.81 (1.16–2.81) | < .01 |
| Postoperative complications | ||||
| CDc ≥IIIb (+ vs −) | 1.72 (1.11–2.56) | .016 | 1.74 (1.12–2.63) | .016 |
Abbreviations: CDc, Clavien–Dindo classification; CI, confidence interval; HR, hazard ratio.
3.4. Survival analysis of interactions between aSIS and other factors
We next determined whether the influence of aSIS on the OS was affected by any clinicopathological factors. The effect of aSIS was not significantly modified by comorbidity, BMI, Brinkman Index, sex, or age (P > .11 for all interactions) (Figure 3A). Interestingly, a potential modifying effect of preoperative treatment on the relationship between the aSIS and OS was observed (P for interaction = .055). Among patients who did not receive preoperative treatment, the high mSIS had a significantly shorter OS (log rank P < .001). In contrast, among patients who received preoperative treatment, there was no significant difference in the OS for the high aSIS and low aSIS (log rank P = .676) (Figure 3B). Similarly, a potential modifying effect of cStage on the relationship between the mSIS and OS was also observed (P for interaction = .030). Among patients with cStage I, II, the high mSIS had a significantly shorter OS (log rank P < .001) (Figure S3).
FIGURE 3.
A: Relationship between the adapted systemic inflammation score (aSIS) and OS. Loge(HRs) plots of the OS rate in aSIS 0 (low) and aSIS 1, 2 (high) groups are shown. B: Kaplan–Meier curves for OS in patients with esophageal squamous cell carcinoma, according to the aSIS stratification. The upper panel includes patients who did not receive any preoperative treatment. The lower panel includes patients who received preoperative treatment. aSIS, modified systemic inflammation score; OS, overall survival; HRs, hazards ratio
Furthermore, we divided the patients into those who received preoperative treatment and those who did not, and further analyzed the patients' characteristics and prognostic factors.
In patients without preoperative treatment, the relationships between aSIS and clinicopathological factors are presented in Table S1. Older age, poorer PS, lower BMI, and higher clinical stage were significantly associated with higher aSIS (each P < .05). High aSIS was significantly associated with a higher incidence of pulmonary morbidity (P < .01). In the multivariate Cox regression analysis for OS, aSIS was an independent prognostic factor for the OS (multivariate HR 2.27, 95% CI 1.18–4.19, P = .02; Table S3). These results for patients who did not receive preoperative treatment were in good agreement with the analysis results of all 509 patients.
On the other hand, in patients with preoperative treatment, the relationships between aSIS and clinicopathological factors are presented in Table S2. Older age, and smoker were significantly associated with higher aSIS (each P < .05). Unlike patients without preoperative treatment, high aSIS was not significantly associated with a higher incidence of pulmonary morbidity (P = .62). Furthermore, in the univariate and multivariate Cox regression analysis for OS, aSIS was not an independent prognostic factor for the OS (univariate HR 1.23, 95% CI 0.68–2.26, P = .50; Table S4).
3.5. Comparison of aSIS with other prognostic scoring systems
Time‐dependent area under the curve (AUC)‐of‐ROC curves of aSIS and other prognostic scoring systems (CONUT, SIS, and NLR) was constructed for the prediction of OS (Figure 4). When the predictive performance for the OS was compared after 1–5 y of follow‐up, the AUC values of the aSIS were similar to those of the SIS and CONUT, and were significantly higher than those of the NLR.
FIGURE 4.
The time‐dependent AUC‐of‐ROC curves of aSIS and other prognostic scoring systems (CONUT, SIS, NLR) for the prediction of OS. AUC‐of‐ROC, area under the curve of the receiver operating characteristics; CONUT, controlling nutritional status; SIS, systemic inflammation score; aSIS, adapted systemic inflammation score; NLR, neutrophil‐to‐lymphocyte ratio
4. DISCUSSION
In this study we examined the prognostic effects of aSIS in a large cohort of 509 patients with ESCC. We found that high aSIS was associated with poor prognosis, suggesting that aSIS status could be used as a marker to identify patients who are likely to have unfavorable clinical outcomes. Additionally, the t‐ROC analysis showed that aSIS was more sensitive than other nutritional prognostic factors (CONUT, NLR, and SIS). Given that better prognostic biomarkers are needed for making appropriate treatment decisions for patients with esophageal cancer, our observations are likely to have clinical implications.
Systemic inflammation plays an important role in the tumor microenvironment. Several investigations have revealed that inflammation in the tumor microenvironment promotes tumor proliferation, angiogenesis, metastasis, inhibition of tumor immunity, and resistance to anticancer treatment.14 Several studies have also shown the predictive value of nutrition and systemic inflammation markers (eg, CONUT and NLR) in patients who underwent curative resection for various cancers. CONUT was calculated from the serum Alb level, total cholesterol concentration, and total lymphocyte count. NLR was calculated from the neutrophil‐to‐lymphocyte ratio.
SIS is a new scoring system based on serum Alb and LMR. Chang et al first reported that SIS predicts the postoperative prognosis of patients with clear‐cell renal cell carcinoma, and the cutoff value of LMR was 4.44 based on the median value of LMR.2 Higher SIS was associated with poorer OS in colorectal cancer3, 15 and gastric cancer.16, 17 However, Lin et al showed that SIS was not an independent prognostic factor for gastric cancer patients based on a multivariate analysis.5 They determined a new cutoff value of LMR at 3.4 using the software X‐tile4 and constructed the mSIS. The mSIS was the only significant independent biomarker, and a higher mSIS score was associated with 5‐y OS.
Two previous studies on ESCC showed that a high SIS was significantly associated with poorer OS.6, 7 There was only one study focusing on the prognostic role of mSIS in ESCC patients.8 Kanda et al analyzed patients with esophageal cancer using Lin's cutoff value of 3.4, without using the software X‐tile, and reported that a higher mSIS was associated with poorer disease‐free survival in 443 ESCC patients.8 However, all of these studies were limited by small sample sizes (n < 450). In contrast to previous studies, our study evaluated preoperative aSIS in a much larger cohort of over 500 ESCC patients. Furthermore, the LMR cutoff value was optimized at 3.3 for ESCC patients using the software X‐tile. In our study aSIS was a significant independent prognostic biomarker and the higher aSIS was associated with poorer OS and CSS. Importantly, aSIS was more sensitive than other nutritional prognostic factors, namely, CONUT, NLR, and SIS. The reason why aSIS was more sensitive than SIS might be the difference in the LMR cutoff value (the LMR cutoff values in aSIS and SIS were 3.3 and 4.44, respectively). In ESCC patients, The LMR cutoff value 4.44 was strict and many patients were assigned to SIS:2 (SIS 2:32%, aSIS 2:20%), and it might not be possible to stratify patients with poor SIS. The reason why aSIS was more sensitive than CONUT and NLR might be the difference in each prognostic factor's components. Especially, it might be affected by the fact that only aSIS includes monocytes, not CONUT and NLR. Peripheral monocyte count appeared to be useful prognostic marker in a large cohort of patients with ESCC.18 However, the precise molecular mechanism by which monocytes might predict clinical survival is not understood. One hypothesized pathogenic mechanism is that monocytes are recruited by some cytokines and chemokines around the tumor and differentiate into tumor‐associated macrophages (TAMs), which facilitate multiple tumorigenic mechanisms. Type 2 macrophages, in particular, have a tumorigenic effect that includes tumor initiation, invasion, angiogenesis, and metastasis.19 We have previously reported that the presence of a high‐density of TAMs was associated with significantly worse OS in patients with resected ESCC.20 Therefore, an elevated absolute monocyte count may indicate the presence of TAMs.
The biological mechanism underlying the relationship between the systemic impact of aSIS and prognosis is still unknown. One mechanism may involve the relationship between systemic inflammation and tumor immunity (tumor infiltrating lymphocytes [TILs]). We have previously revealed the correlation between TIL status and total lymphocyte count in peripheral blood. TILs might promote antitumor immunity and might be associated with improved outcomes in ESCC patients.21 Further experimental studies are necessary for investigating these mechanisms in ESCC.
Interestingly, we found that the prognostic effect of the aSIS differed according to the neoadjuvant treatment status. Low aSIS was associated with high OS among patients who did not undergo neoadjuvant treatment. In contrast, in patients who underwent neoadjuvant treatment, there was no association between the aSIS and OS. The most probable reason could be that many patients with neoadjuvant treatment have advanced‐stage ESCC and poor prognosis (Table S2). On the other hand, 50% of patients without neoadjuvant treatment were cStage I (Table S1). Second, in the clinical setting for esophageal cancer treatment, preoperative therapy might negatively affect the patients’ systemic nutritional and immunological status. In fact, comparing preneoadjuvant treatment and preoperative blood sampling values, Alb levels and lymphocyte count decreased significantly (Alb 4.0 ± 0.4 vs 3.7 ± 0.4, P < .01; lymphocytes 1766 ± 597 vs 1486 ± 584, P < .01), and monocyte count tended to decrease (434 ± 174 vs 413 ± 160, P = .14). Approximately 67% of the patients with aSIS of 0 before neoadjuvant treatment showed elevated preoperative aSIS. This could affect their clinical outcome via the local tumor immune response.22
This study has several limitations. First, this was a retrospective study. Second, the patients were included from just our institution. The significance of aSIS needs to be validated using other cohorts.
In conclusion, our large cohort study with more than 500 cases revealed that the preoperative aSIS was associated with the clinical outcome in ESCC patients who underwent curative resection. Furthermore, aSIS was more sensitive than other nutritional prognostic factors. Considering the relationship between nutritional status and local tumor immunity, our findings may have considerable clinical implications. Future studies are needed for confirming our findings as well as for elucidating the exact mechanisms by which the nutritional status affects local tumor immunity.
CONFLICT OF INTEREST
No conflicts of interest exist.
ETHICAL STATEMENT
The study was approved by the Institutional Review Board of Kumamoto University (#1909).
Supporting information
Fig S1
Fig S2
Fig S3
Table S1‐4
Supplementary Material
ACKNOWLEDGMENT
We thank Editage (www.editage.com) for English language editing.
Nomoto D, Baba Y, Akiyama T, et al. Adapted systemic inflammation score as a novel prognostic marker for esophageal squamous cell carcinoma patients. Ann Gastroenterol Surg. 2021;5:669–676. 10.1002/ags3.12464
REFERENCES
- 1.Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018;68(6):394–424. [DOI] [PubMed] [Google Scholar]
- 2.Chang Y, An H, Xu L, Zhu Y, Yang Y, Lin Z, et al. Systemic inflammation score predicts postoperative prognosis of patients with clear‐cell renal cell carcinoma. Br J Cancer. 2015;113(4):626–33. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Suzuki Y, Okabayashi K, Hasegawa H, Tsuruta M, Shigeta K, Kondo T, et al. Comparison of preoperative inflammation‐based prognostic scores in patients with colorectal cancer. Ann Surg. 2018;267(3):527–31. [DOI] [PubMed] [Google Scholar]
- 4.Camp RL, Dolled‐Filhart M, Rimm DL. X‐tile: a new bio‐informatics tool for biomarker assessment and outcome‐based cut‐point optimization. Clin Cancer Res. 2004;10(21):7252–9. [DOI] [PubMed] [Google Scholar]
- 5.Lin J‐X, Lin J‐P, Xie J‐W, Wang J‐B, Lu J, Chen Q‐Y, et al. Prognostic importance of the preoperative modified systemic inflammation score for patients with gastric cancer. Gastric Cancer. 2019;22(2):403–12. [DOI] [PubMed] [Google Scholar]
- 6.Han L, Song Q, Jia Y, Chen X, Wang C, Chen P, et al. The clinical significance of systemic inflammation score in esophageal squamous cell carcinoma. Tumour Biol. 2016;37(3):3081–90. [DOI] [PubMed] [Google Scholar]
- 7.Fu X, Li T, Dai Y, Li J. Preoperative systemic inflammation score (SIS) is superior to neutrophil to lymphocyte ratio (NLR) as a predicting indicator in patients with esophageal squamous cell carcinoma. BMC Cancer. 2019;19(1):721. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Kanda M, Koike M, Tanaka C, Kobayashi D, Hattori N, Hayashi M, et al. Modified systemic inflammation score is useful for risk stratification after radical resection of squamous cell carcinoma of the esophagus. Ann Surg Oncol. 2019;26(13):4773–81. [DOI] [PubMed] [Google Scholar]
- 9.Sobin LH, Gospodarowicz MK, Wittekind C. TNM Classification of Malignant Tumours, 8th edn. Oxford: Wiley‐Blackwell; 2010. [Google Scholar]
- 10.McShane LM, Altman DG, Sauerbrei W, Taube SE, Gion M, Clark GM. Reporting recommendations for tumor marker prognostic studies (REMARK). J Natl Cancer Inst. 2005;97(16):1180–4. [DOI] [PubMed] [Google Scholar]
- 11.Sharaiha RZ, Halazun KJ, Mirza F, Port JL, Lee PC, Neugut AI, et al. Elevated preoperative neutrophil:lymphocyte ratio as a predictor of postoperative disease recurrence in esophageal cancer. Ann Surg Oncol. 2011;18(12):3362–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Yodying H, Matsuda A, Miyashita M, Matsumoto S, Sakurazawa N, Yamada M, et al. Prognostic significance of neutrophil‐to‐lymphocyte ratio and platelet‐to‐lymphocyte ratio in oncologic outcomes of esophageal cancer: a systematic review and meta‐analysis. Ann Surg Oncol. 2016;23(2):646–54. [DOI] [PubMed] [Google Scholar]
- 13.De Ulíbarri JI, González‐Madroño A, de Villar NG, et al. CONUT: a tool for controlling nutritional status. First validation in a hospital population. Nutr Hosp. 2005;20(1):38–45. [PubMed] [Google Scholar]
- 14.Mantovani A, Allavena P, Sica A, Balkwill F. Cancer‐related inflammation. Nature. 2008;454(7203):436–44. [DOI] [PubMed] [Google Scholar]
- 15.Feng Y, Liu L, Zhu Y. Systemic inflammation score in locally advanced rectal cancer patients following total mesorectal excision. Onco Targets Ther. 2019;12:6617–22. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Sato B, Kanda M, Tanaka C, Kobayashi D, Iwata N, Hattori N, et al. Significance of preoperative systemic inflammation score in short‐term and long‐term outcomes of patients with pathological T2–4 gastric cancer after radical gastrectomy. World J Surg. 2018;42(10):3277–85. [DOI] [PubMed] [Google Scholar]
- 17.Ma M, Weng M, Chen F, Hu Y, Lai J, Wang Y, et al. Systemic inflammation score is a prognostic marker after curative resection in gastric cancer. ANZ J Surg. 2019;89(4):377–82. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Han L, Jia Y, Song Q, Wang N, Wang J, Bai B, et al. Prognostic significance of preoperative absolute peripheral monocyte count in esophageal squamous cell carcinoma. Dis Esophagus. 2016;29(7):740–6. [DOI] [PubMed] [Google Scholar]
- 19.Quail DF, Joyce JA. Microenvironmental regulation of tumor progression and metastasis. Nat Med. 2013;19(11):1423–37. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Yagi T, Baba Y, Okadome K, Kiyozumi Y, Hiyoshi Y, Ishimoto T, et al. Tumour‐associated macrophages are associated with poor prognosis and programmed death ligand 1 expression in oesophageal cancer. Eur J Cancer. 2019;111:38–49. [DOI] [PubMed] [Google Scholar]
- 21.Yagi T, Baba Y, Ishimoto T, Iwatsuki M, Miyamoto Y, Yoshida N, et al. PD‐L1 expression, tumor‐infiltrating lymphocytes, and clinical outcome in patients with surgically resected esophageal cancer. Ann Surg. 2019;269(3):471–8. [DOI] [PubMed] [Google Scholar]
- 22.Okadome K, Baba Y, Yagi T, Kiyozumi Y, Ishimoto T, Iwatsuki M, et al. Prognostic nutritional index, tumor‐infiltrating lymphocytes, and prognosis in patients with esophageal cancer. Ann Surg. 2020;271(4):693–700. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Fig S1
Fig S2
Fig S3
Table S1‐4
Supplementary Material