Prognostic significance of the preoperative hemoglobin to albumin ratio for the short-term survival of gastric cancer patients.

BACKGROUND: Hemoglobin and albumin are associated with the prognosis of gastric cancer (GC) patients. However, the prognostic value of the hemoglobin to albumin ratio (HAR) for the short-term survival of GC patients with D2 radical resection has not been studied. AIM: To investigate the significance of the HAR in evaluating the short-term survival of GC patients after D2 radical resection and to construct a nomogram to predict the prognosis in GC patients after surgery, thus providing a reference for the development of postoperative individualized treatment and follow-up plans.
METHODS: Cox regression and Kaplan-Meier analysis was used for prognostic analysis. Logistic regression was used to analyze the relationships between HAR and the clinicopathological characteristics of the GC patients. A prognostic nomogram model for the short-term survival of GC patients was constructed by R software.
RESULTS: HAR was an independent risk factor for the short-term survival of GC patients. GC patients with a low HAR had a poor prognosis (P < 0.001). Low HAR was markedly related to high stage [odds ratio (OR) = 0.45 for II vs I; OR = 0.48 for III vs I], T classification (OR = 0.52 for T4 vs T1) and large tumor size (OR = 0.51 for ≥ 4 cm vs < 4 cm) (all P < 0.05). The nomogram model was based on HAR, age, CA19-9, CA125 and stage, and the C-index was 0.820.
CONCLUSION: Preoperative low HAR was associated with short-term survival in GC patients. The prognostic nomogram model can accurately predict the short-term survival of GC patients with D2 radical resection. ©The Author(s) 2022. Published by Baishideng Publishing Group Inc. All rights reserved.

Core Tip: Hemoglobin and albumin are associated with the prognosis of gastric cancer (GC) patients. However, the prognostic value of the hemoglobin to albumin ratio (HAR) for the short-term survival of GC patients with D2 radical resection has not been studied. HAR was an independent risk factor for the short-term survival of GC patients. GC patients with a low HAR had a poor prognosis. Low HAR was markedly related to high stage, T classification and tumor size. The nomogram model was based on HAR, age, CA19-9, CA125 and stage and can accurately predict the short-term survival of D2 radical resection GC patients.

INTRODUCTION

For resectable gastric cancer (GC), radical surgery and adjuvant therapy are the standard therapies[1,2]. Postoperative prognosis is evaluated by the American Joint Committee on Cancer TNM classification system[3,4]. However, prognostic factors such as age, tumor size and tumor location are not considered in the prediction of individual survival. Moreover, the prognosis of patients in the same stage with similar treatment regimens varies greatly[5,6]. Therefore, it is necessary to develop a comprehensive and accurate prognostic evaluation system to predict the prognosis of GC patients, which is of great significance in selecting individualized treatment plans for these patients.

In addition, studies have shown that the prognosis of cancer is not only correlated with tumor characteristics but also to the nutritional status and systemic inflammation of patients[7,8]. The systemic inflammatory response can affect the progression and metastasis of tumors[9]. Recently, studies also found that malnutrition is associated with decreased immunity, which increases the incidence of complications and mortality postoperatively, leading to poor postoperative prognosis in cancer patients[10,11].

Hemoglobin and albumin are used as the two most common indicators of nutritional status. Various perioperative nutritional parameters have been confirmed as independent prognostic factors in GC patients who underwent D2 radical resection[12]. Low hemoglobin levels can lead to tumor hypoxia, which can accelerate tumor growth and promote the angiogenesis of tumor cells[13]. Low serum albumin concentration was an independent risk factor affecting the survival of GC patients[14]. In addition, low serum albumin levels can impair cellular immune function, leading to poor prognosis in cancer patients[15]. Studies have demonstrated that preoperative low serum albumin and hemoglobin levels are closely associated with the poor prognosis of malignant tumors[16,17]; the high preoperative C-reactive protein to albumin ratio was related to poor outcome in patients with GC[18,19].

However, the clinical value of the hemoglobin to albumin ratio (HAR) in the prognosis of GC patients with D2 radical resection has not been reported. Nomogram can provide the overall probability of specific outcomes for individual patients and provide more accurate predictions than the traditional TNM staging system, thereby improving personalized treatment decisions[20,21]. Therefore, the aim of this study was to investigate the significance of the HAR in evaluating the short-term survival of GC patients after D2 radical resection and to construct a nomogram to predict the prognosis in GC patients after surgery, thus providing a reference for the development of postoperative individualized treatment and follow-up plans.

MATERIALS AND METHODS

Patient characteristics

The clinical and follow-up data of 312 GC patients who underwent D2 radical resection in our hospital were collected from January 2017 to January 2019. Tumor markers, serum albumin and fibrinogen levels and blood cell counts, including hemoglobin, neutrophils, platelets and lymphocytes, were extracted at the first admission. The HAR, platelet to hemoglobin ratio, platelet to lymphocyte ratio (PLR), platelet to albumin ratio (PAR), fibrinogen to lymphocyte ratio (FLR), albumin to fibrinogen ratio, hemoglobin to fibrinogen ratio (HFR), platelet to fibrinogen ratio, neutrophil to lymphocyte ratio (NLR) and albumin to lymphocyte ratio were calculated. According to the median HAR value, GC patients were divided into a high HAR group and a low HAR group. The stage of postoperative patients was based on the American Joint Committee on Cancer TNM classification system. Survival time was calculated from the day of surgery to the last follow-up. After surgery, all patients were followed up every 3 mo for the first 2 years and then every 6 mo until 5 years. The last follow-up date was March 1, 2020.

Inclusion and exclusion criteria

The inclusion criteria were as follows: (1) Patients with GC were diagnosed by pathology after surgery; and (2) Neoadjuvant chemoradiotherapy was not performed before surgery. The exclusion criteria were as follows: (1) Patients with a history of surgery 2 mo before admission; (2) Patients with a history of blood transfusion; (3) Patients using hemostatic and anticoagulant drugs; (4) Patients with bleeding, thrombotic disease or splenectomy; and (5) Patients with pregnancy, chronic disease, acute infection, relapse or other distant organ metastases and those who were lost to follow-up or had incomplete information.

Statistical analysis

Prognostic analysis was performed using Kaplan-Meier and Cox regression analyses. The Mann-Whitney U test was used for comparisons between two groups. The relationships between HAR and clinicopathological characteristics were determined by logistic regression. The receiver operating characteristic curve was used to evaluate the ability of a single factor or combined factors to predict the short-term survival of GC patients. The RMS package of R software was used to construct a prognostic nomogram model for the short-term survival of GC patients, and the scores of various indicators were obtained. In addition, Harrell’s concordance index (C-index) was calculated to evaluate the performance of the model’s prediction results[22]. A P value less than 0.05 was considered to indicate a statistically significant result. Analyses were performed by SPSS 22.0 for Windows (SPSS Inc., Chicago, IL, United States) and R (version x64 3.6.1).

RESULTS

Prognostic analysis of GC patients with D2 radical resection

The factors associated with prognosis were as follows: age, CEA, CA19-9, CA125, HAR, platelet to hemoglobin ratio, PLR, PAR, FLR, HFR, tumor size, vascular infiltration, nerve infiltration and stage (all P < 0.05). Multivariate Cox regression analysis found that age, HAR and stage were independent risk factors affecting prognosis (all P < 0.05) (Table 1). Kaplan-Meier analysis found that the difference in the survival time of GC patients with a low HAR and high HAR was statistically significant (P = 0.003), indicating that GC patients with low HAR had a poor prognosis (Figure 1).

Table 1

Prognostic analysis of clinical characteristics in patients with gastric cancer

Clinical variable	n	Univariate analysis		Multivariate analysis
	312	HR (95%CI)	P value	HR (95%CI)	P value
Age (yr)	62 (54-68)	1.046 (1.015-1.077)	0.003	1.049(1.017-1.081)	0.002
Sex (male/female)	225/87	0.715 (0.400-1.280)	0.259
BMI (kg/m2)	21.55 (19.53-23.55)	0.983 (0.911-1.062)	0.670
Smoking (yes/no)	64/248	0.442 (0.189-1.034)	0.060
Drinking (yes/no)	49/263	1.316 (0.641-2.701)	0.454
CEA (ng/mL)	2.94 (1.85-5.29)	1.006 (1.003-1.009)	0.000
CA19-9 (U/mL)	13.26 (7.36-23.70)	1.001 (1.000-1.002)	0.003
CA125 (U/mL)	8.50 (5.90-13.80)	1.008 (1.000-1.016)	0.049
CA72-4 (IU/mL)	1.81 (1.17-4.46)	1.004 (0.990-1.018)	0.57
HAR	3.18 (2.68-3.44)	0.425 (0.278-0.650)	0.000	0.466 (0.301-0.720)	0.001
PHR	1.86 (1.40-2.58)	1.371 (1.194-1.575)	0.000
PLR	157.74 (114.06-211.23)	1.003 (1.001-1.006)	0.004
PAR	5.75 (4.51-7.48)	1.184 (1.088-1.288)	0.000
FLR	2.05 (1.49-2.89)	1.171 (1.018-1.347)	0.028
AFR	13.16 (10.36-16.85)	0.970 (0.912-1.033)	0.344
HFR	42.52 ± 17.83	0.974 (0.955-0.993)	0.007
PFR	77.41 (57.84-101.46)	1.005 (0.998-1.012)	0.135
NLR	2.47 (1.76-3.59)	1.100 (0.974-1.242)	0.124
ALR	26.25 (22.16-35.08)	1.008 (0.986-1.030)	0.489
Tumor size (cm)	4.0 (2.5-5.5)	1.167 (1.079-1.262)	0.000
Vascular infiltration (present/absent)	168/144	3.230 (1.695-6.153)	0.000
Nerve infiltration (present/absent)	149/163	2.974 (1.651-5.359)	0.000
Histological grade (G1/G2/G3)	6/120/186	0.920 (0.553-1.530)	0.748
Stage (Ⅰ/Ⅱ/Ⅲ)	88/75/149	4.154 (2.291-7.531)	0.000	4.112 (2.225-7.602)	0.000
Survival status (death/survival)	53/259
Follow-up time (d)	531 (440-691)

BMI: Body mass index; PHR: Platelet to hemoglobin ratio; PLR: Platelet to lymphocyte ratio; PAR: Platelet to albumin ratio; FLR: Fibrinogen to lymphocyte ratio; AFR: Albumin to fibrinogen ratio; HFR: Hemoglobin to fibrinogen ratio; PFR: Platelet to fibrinogen ratio; NLR: Neutrophil to lymphocyte ratio; ALR: Albumin to lymphocyte ratio. HR: Hazard ratio; CI: Confidence interval; HAR: Hemoglobin to albumin ratio.

Figure 1

Survival curve of gastric cancer patients with low hemoglobin to albumin ratio and high hemoglobin to albumin ratio. HAR: Hemoglobin to albumin ratio; HR: Hazard ratio.

Association between HAR and clinicopathological characteristics

To analyze the association between HAR and clinicopathological characteristics, we performed logistic regression analysis. HAR was associated with stage, T classification and large tumor size (all P < 0.05) (Figure 2). Logistic regression analysis showed that a low HAR was effectively related to high stage [odds ratio (OR) = 0.45 for II vs I; OR = 0.48 for III vs I], T classification (OR = 0.52 for T4 vs T1) and large tumor size (OR = 0.51 for ≥ 4 cm vs < 4 cm) (all P < 0.05) in GC patients (Table 2). These results indicate that GC patients with a low HAR were more likely to have advanced GC.

Figure 2

Association between hemoglobin to albumin ratio and clinicopathological characteristics, including grade, stage, T classification, N classification, tumor size, vascular infiltration, nerve infiltration and age. HAR: Hemoglobin to albumin ratio.

Table 2

Hemoglobin to albumin ratio value associated with clinical pathological characteristics

Clinical characteristics	Total (n)	Odds ratio in HAR value	P value
Age (≥ 62 yr vs < 62 yr)	312	0.78 (0.50-1.21)	0.264
Size (≥ 4 cm vs < 4 cm)	312	0.51 (0.32-0.80)	0.004
Histological grade
(G2 vs G1)	126	0.91 (0.16-5.06)	0.905
(G3 vs G1)	192	1.00 (0.18-5.52)	1.000
Vascular infiltration (yes vs no)	312	1.14 (0.73-1.79)	0.552
Nerve infiltration (yes vs no)	312	1.00 (0.64-1.56)	0.988
Stage
(Ⅱ vs I)	163	0.45 (0.24-0.83)	0.012
(Ⅲ vs I)	237	0.48 (0.28-0.81)	0.007
T classification
(T2 vs T1)	106	0.61 (0.27-1.39)	0.243
(T3 vs T1)	112	0.62 (0.28-1.35)	0.227
(T4 vs T1)	236	0.52 (0.29-0.91)	0.022
N classification
(N1 vs N0)	169	0.76 (0.33-1.74)	0.518
(N2 vs N0)	201	0.56 (0.30-1.04)	0.067
(N3 vs N0)	226	0.68 (0.39-1.16)	0.160

HAR: Hemoglobin to albumin ratio.

Comparison between the low HAR group and the high HAR group

To further analyze the relationships between HAR and prognostic factors, we divided the GC patients into a low HAR group and a high HAR group according to the median HAR value. The factors with statistically significant differences between the two groups were sex, CA125, platelet to hemoglobin ratio, PLR, PAR, FLR, HFR, platelet to fibrinogen ratio, NLR, albumin to lymphocyte ratio, large tumor size, stage and T classification (all P < 0.05), suggesting that patients with a low HAR had high stage, T classification, CA125, FLR, PAR, PLR, large tumor sizes and low HFR (Table 3 and Figure 3).

Table 3

Comparison of the relevant factors between the high hemoglobin to albumin ratio group and low hemoglobin to albumin ratio group

Factors	High HAR group (n = 158)	Low HAR group (n = 154)	P value
Age (yr)	61 (53-67)	63 (54-69)	0.266
Sex (n)			0.000
Male	132	93
Female	26	61
BMI (kg/m2)	21.81 (19.90-23.82)	21.30 (19.32-23.33)	0.154
Smoking (n)			0.468
Yes	35	29
No	123	125
Drinking (n)			0.322
Yes	28	21
No	130	133
CEA (ng/mL)	2.89 (1.87-5.23)	2.97 (1.83-5.44)	0.581
CA19-9 (U/mL)	12.63 (7.43-21.52)	13.38 (7.23-24.20)	0.658
CA125 (U/mL)	8.30 (5.68-11.30)	9.15 (6.08-16.80)	0.034
CA72-4 (IU/mL)	1.91 (1.19-4.46)	1.73 (1.14-4.46)	0.396
PHR	1.55 (1.25-1.95)	2.29 (1.71-3.36)	0.000
PLR	138.71 (98.29-188.22)	177.27 (134.34-252.12)	0.000
PAR	5.49 (4.36-6.86)	6.04 (4.70-8.20)	0.002
FLR	1.83 (1.39-2.62)	2.26 (1.57-3.11)	0.001
AFR	13.73 (10.92-16.83)	12.62 (9.69-16.93)	0.162
HFR	48.46 ± 14.63	36.42 ± 18.78	0.000
PFR	73.48 (57.12-92.62)	79.78 (60.16-112.23)	0.040
NLR	2.32 (1.74-3.36)	2.89 (1.92-3.78)	0.024
ALR	24.40 (19.05-32.52)	27.87 (23.08-35.77)	0.000
Tumor size (cm)	3.5 (2.4-5.0)	4.5 (3.0-6.1)	0.009
Vascular infiltration (n)			0.507
present	88	80
absent	70	74
Nerve infiltration (n)			0.918
present	75	74
absent	83	80
Histological grade (n)			0.682
G1	3	3
G2	59	61
G3	96	90
Stage (n)			0.036
Ⅰ	56	32
Ⅱ	32	43
Ⅲ	70	79
T classification (n)			0.037
T1	44	27
T2	18	17
T3	20	21
T4	76	89
N classification (n)			0.141
N0	79	63
N1	14	13
N2	25	34
N3	40	44

HAR: Hemoglobin to albumin ratio; BMI: Body mass index; PHR: Platelet to hemoglobin ratio; PLR: Platelet to lymphocyte ratio; PAR: Platelet to albumin ratio; FLR: Fibrinogen to lymphocyte ratio; AFR: Albumin to fibrinogen ratio; HFR: Hemoglobin to fibrinogen ratio; PFR: Platelet to fibrinogen ratio; NLR: Neutrophil to lymphocyte ratio; ALR: Albumin to lymphocyte ratio.

Figure 3

Relationships between hemoglobin to albumin ratio and prognostic factors, including stage, T classification, and tumor size, CA125, fibrinogen to lymphocyte ratio, platelet to albumin ratio, platelet to lymphocyte ratio and hemoglobin to fibrinogen ratio. HAR: Hemoglobin to albumin ratio; FLR: Fibrinogen to lymphocyte ratio; HFR: Hemoglobin to fibrinogen ratio; PAR: Platelet to albumin ratio; PLR: Platelet to lymphocyte ratio.

Receiver operating characteristic curve analysis

To evaluate the ability of HAR or combined factors to predict the short-term survival of GC patients, we performed receiver operating characteristic curve analysis. The area under the curve (AUC) of HAR alone in predicting the 1-year survival of GC patients was 0.656, the sensitivity was 78.19%, and the specificity was 52.94%, while the AUC of predicting the 2.5-year survival was 0.804, the sensitivity was 85.29%, and the specificity was 74.95%. The AUC of HAR combined with age, CA19-9, CA125 and stage to predict the 1-year survival of GC patients was 0.833, the sensitivity was 86.83%, and the specificity was 84.77%, while the AUC of predicting the 2.5-year survival was 0.832, the sensitivity was 87.87%, and the specificity was 72.18% (Figure 4). These results indicate that HAR combined with prognostic factors can accurately predict the short-term survival of patients with GC.

Figure 4

Receiver operating characteristic curve of hemoglobin to albumin ratio or combined factors to predict the short-term survival of gastric cancer patients. HAR: Hemoglobin to albumin ratio; AUC: Area under the curve.

Construction of the prognostic nomogram

To predict the short-term survival probability of GC patients after surgery, we used the rms package to construct a logistic regression model of HAR combined with age, CA19-9, CA125 and stage, and the C-index evaluated by this model was 0.820, indicating that this prediction model had certain accuracy. Then, the plotting function was employed, and the nomogram was plotted (Figure 5). A score of HAR ≥ 3.18 was 0 points, while a score of HAR < 3.18 was 37 points. A score of age ≥ 62 years was 13 points, while a score of age < 62 years was 0 points. A score of CA19-9 ≥ 13.255 U/mL was 26 points, while a score of CA19-9 < 13.255 U/mL was 0 points. A score of CA125 ≥ 8.5 U/mL was 18 points, while a score of CA125 < 8.5 U/mL was 0 points. A score of stage Ⅰ was 0 points, a score of stage II was 63 points, and a score of stage Ⅲ was 100 points. The highest score was 194 points, indicating that the 1-year survival probability of GC patients was 60%-65% and that the 5-year survival probability was < 10%. According to the total points, the probability of the short-term survival of GC patients can be predicted.

Figure 5

Nomogram of the logistic regression model. HAR: Hemoglobin to albumin ratio.

DISCUSSION

The systemic inflammatory response and malnutrition are markedly related to the prognosis of cancer[10,11,13]. Neutrophils, lymphocytes, platelets and fibrinogen may play important roles in tumor-induced systemic inflammatory responses[23,24]. Hemoglobin and albumin are the two most common indicators of nutritional status. At the same time, serum albumin can also reflect the inflammation of patients. Various scores and indicators based on inflammation and nutritional status have been produced to predict the prognosis of cancer, such as the controlling nutritional status score, C-reactive protein to albumin ratio, NLR, PLR, prognostic nutrition index and systemic immune inflammation index[25-27].

Deng et al[28] showed that the preoperative PLR was significantly associated with poor prognosis in GC patients with surgical resection. Gu et al[29] also found that GC patients with elevated PLR had poor overall survival. Sun et al[30] indicated that the combination of NLR and PLR was an independent risk factor for the overall survival of stage III GC patients undergoing radical resection. In addition, Suzuki et al[31] found that high plasma fibrinogen was related to tumor progression and poor overall survival in GC patients. Huang et al[32] showed that elevated FLR was a high risk factor for peritoneal metastasis in patients with GC. This study also showed that PLR and FLR were significantly related to the prognosis of GC patients.

Hemoglobin is used to determine anemia. Hypoxia caused by anemia, on the one hand, may accelerate tumor angiogenesis to promote tumor progression; on the other hand, it may make tumor cells resistant to radiotherapy and chemotherapy through proteomics and genomic changes[13,33,34]. Moreover, it is well known that hypoxia-inducible factor 1 can regulate gene products that promote tumor progression, and hypoxia increases its expression[35]. However, the molecular mechanisms of hypoxia need to be further elucidated. Previous studies have found that anemia was an independent risk factor for poor prognosis in patients with malignant tumors[36,37].

Huang et al[38] found that GC patients with low hemoglobin levels before surgery had poor survival. Liu et al[39] demonstrated that preoperative low hemoglobin concentrations were significantly related to not only large tumor sizes but also poor 5-year overall survival and high postoperative complication rates in advanced GC patients. Shen et al[40] suggested that preoperative anemia was markedly related to large tumor sizes, deep invasion depths and high stages and showed that stage I and II GC patients with anemia before surgery had a low long-term survival rate compared with patients without anemia before surgery.

Malnutrition and inflammation can inhibit albumin synthesis. Serum albumin was an independent prognostic indicator of malignant tumors[14,41]. Lien et al[42] showed that serum albumin was effectively associated with the 5-year survival of GC patients. Moreover, relevant studies have indicated that low albumin levels are related to poor prognosis in GC[14,43]. However, Crumley et al[14] demonstrated that GC patients with low albumin levels had a poor prognosis compared with those with high albumin levels, but this factor was not an independent predictor of prognosis. Moreover, Toyokawa et al[44] believed that C-reactive protein to albumin ratio was an independent prognostic factor for overall survival in patients who underwent R0 resection for stage III gastric cancer.

This study indicated that HAR, stage and age were independent risk factors for the short-term survival of GC patients. Logistic regression analysis showed that a low HAR was markedly correlated with high stage, T classification and large tumor size in GC patients. To further analyze the relationships between HAR and prognostic factors, we divided GC patients into a low HAR group and a high HAR group according to the median HAR value, and the results showed that patients with low HAR had high stage, T classification, CA125 and large tumor size. In addition, Kaplan-Meier analysis indicated that low HAR was related to short survival in GC patients.

Serum tumor markers can be used to predict the prognosis of cancer. Previous studies have found that elevated CEA, CA19-9 and CA125 levels were related to the prognosis of GC[45-47]. Related studies have also indicated that preoperative CEA and CA19-9 levels are related to tumor invasion depth and stage and can be used to predict prognosis[48,49]. Kochi et al[50] indicated that serum CA125 and CA19-9 were independent predictors of GC prognosis. This study also showed that CEA, CA19-9 and CA125 were associated with the prognosis of GC patients. The prognosis of patients with GC was evaluated mainly according to the American Joint Committee on Cancer TNM classification system[3,4]. However, this system has some limitations in clinical application.

Currently, nomograms combining prognostic factors have been developed, and it has been found that nomograms including inflammation and tumor markers can predict the prognosis of cancer more accurately than the traditional TNM classification system[51-53]. In this study, HAR, stage, age, CA19-9 and CA125 were used to construct a nomogram model for the short-term survival of GC patients, and the C-index for model evaluation was 0.820. The accuracy, sensitivity and specificity of this model for predicting the 1-year survival of GC patients were 83.30%, 86.83% and 84.77%, respectively, and the accuracy, sensitivity and specificity of the model for predicting the 2.5-year survival of GC patients were 83.20%, 87.87% and 72.18%, respectively, indicating that the model had a certain validity in predicting the short-term survival of patients with GC.

This study has some limitations. First, this was a single-center, small-sample retrospective study. Second, several other inflammatory markers correlated with prognosis were not included. Therefore, multicenter large-scale prospective randomized controlled trials are necessary.

In conclusion, this is the first study to apply HAR to predict the prognosis of GC patients with D2 radical resection and to construct a short-term survival prognostic nomogram for GC patients. Preoperative low HAR was associated with short survival in GC patients. The prognostic nomogram model based on HAR, stage, age, CA19-9 and CA125 can correctly predict the short-term survival of GC patients with D2 radical resection, thus providing a reference for the development of personalized postoperative treatment and follow-up plans.

CONCLUSION

Preoperative low HAR was associated with short survival in GC patients. The prognostic nomogram model can accurately predict the short-term survival of GC patients with D2 radical resection.

ARTICLE HIGHLIGHTS

Research background

Hemoglobin and albumin are associated with the prognosis of gastric cancer (GC) patients. However, the prognostic value of the hemoglobin to albumin ratio (HAR) for the short-term survival of GC patients with D2 radical resection has not been studied.

Research motivation

The clinical value of the HAR in the prognosis of GC patients with D2 radical resection has not been reported. Nomogram can provide the overall probability of specific outcomes for individual patients and provide more accurate predictions than the traditional TNM staging system, thereby improving personalized treatment decisions.

Research objectives

The aim of this study was to investigate the significance of the HAR in evaluating the short-term survival of GC patients after D2 radical resection and to construct a nomogram to predict the prognosis in GC patients after surgery.

Research methods

Cox regression and Kaplan-Meier analysis was used for prognostic analysis. Logistic regression was used to analyze the relationships between HAR and the clinicopathological characteristics of the GC patients. A prognostic nomogram model for the short-term survival of GC patients was constructed by R software.

Research results

HAR was an independent risk factor for the short-term survival of GC patients. GC patients with a low HAR had a poor prognosis (P < 0.001). Low HAR was markedly related to high stage [odds ratio (OR) = 0.45 for II vs I; OR = 0.48 for III vs I], T classification (OR = 0.52 for T4 vs T1) and large tumor size (OR = 0.51 for ≥ 4 cm vs < 4 cm) (all P < 0.05). The nomogram model was based on HAR, age, CA19-9, CA125 and stage, and the C-index was 0.820.

Research conclusions

Preoperative low HAR was associated with short survival in GC patients. The prognostic nomogram model can accurately predict the short-term survival of GC patients with D2 radical resection.

Research perspectives

The significance of the HAR in evaluating the short-term survival of GC patients after D2 radical resection and to construct a nomogram to predict the prognosis in GC patients after surgery may provide a reference for the development of postoperative individualized treatment and follow-up plans.