Diagnostic Value of ABO Blood Group Combined with Tumor Markers in Gastric Cancer

Diagnostic Value of ABO Blood Group Combined with Tumor Markers in Gastric Cancer | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Diagnostic Value of ABO Blood Group Combined with Tumor Markers in Gastric Cancer Yuhuan Liu, Shasha Chen, Weina Shen, Xiaodong Qu, Songbo Li, Yongquan Shi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2192622/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Blood type is related to the occurrence and development of gastric cancer. The aim of this study is to explore the value of combined detection of ABO blood group and tumor markers in the diagnosis of gastric cancer. Methods A total of 3650 gastric cancer patients treated in our center from January 2015 to December 2019, and 5822 controls were recruited, and divided into training set and validation set according to 7:3. The clinicopathological characteristics were recorded. Receiver operating characteristic curve (ROC curve) was used to evaluate the diagnostic value of tumor markers and their combined blood type for gastric cancer. The results were validated using another group of people (validation group). Results In both the training set and the validation set, the levels of tumor markers in gastric cancer patients were higher than those in the healthy control group ( P B > O > AB, while that in healthy control group was: B > O > A > AB. Type B blood (AUC = 0.850,95%CI 0.837–0.863, P = 0.0006) and type AB blood (AUC = 0.837,95%CI 0.812–0.860, P = 0.0439) could improve the diagnostic value of CEA in gastric cancer. Conclusion The detection of blood group combined with tumor markers can improve the sensitivity and specificity for the diagnosis of gastric cancer, which has a high reference value for the diagnosis of gastric cancer patients, and is worthy of further clinical study. Gastric cancer Tumor markers ABO blood group Combined diagnosis Receiver operating curve Figures Figure 1 Figure 2 Figure 3 Figure 4 Background Gastric cancer (GC) is an important cancer worldwide. According to the latest data of the International Agency for Research on Cancer (IARC), it ranks the 5th in incidence and the 4th in mortality globally[ 1 ]. GC is the most common gastrointestinal tumor in China, of which the rate of early detection is low. Compared with 2015, GC ranked third in the number of new cases and mortality of common malignant tumors in 2020[ 2 ], posing a serious threat to human health. Early GC can be treated by surgery, and the 5-year survival rate is more than 90%, while advanced GC can be treated by surgery, and the 5-year survival rate is less than 30%[ 3 ]. The gold standard for screening early GC is gastroscopy, but its detection rate is less than 10%, it is invasive, it requires a lot of human resources, and its acceptance is low. It is not suitable for large-scale population screening and follow-up of GC. Tumor markers have the advantages of non-invasive, easy specimen acquisition and low cost, which are suitable for dynamic monitoring. However, the positive rate of tumor markers in advanced GC is only 20%-30%, and the positive rate in early GC is less than 10%[ 4 ]. Although the sensitivity of combined serum tumor markers in the diagnosis of GC has been improved, it is still low [ 5 ]. Since Aird et al. [ 6 ] first proposed that blood type A was associated with the occurrence of GC in 1953, a large number of studies on blood type and the incidence, clinicopathological characteristics and prognosis of GC have been carried out. However, the relationship between ABO blood group and GC cannot be concluded with certainty due to conflicting findings at different studies[ 7 , 8 ]. If the combined detection of blood group and tumor markers can improve the diagnostic efficiency of GC, the diagnostic timing, diagnostic cost and diagnostic accuracy of GC can be improved. Therefore, the purpose of the present study was to investigate the value of ABO blood group combined with serum tumor markers, including CEA, CA199, CA125, AFP and CA724, for the diagnosis of GC and provide additional reference indicators for the early diagnosis and treatment of the disease. Methods Patients A total of 3650 GC patients from January 2015 to December 2019 in the Xijing Hospital of Digestive Diseases were selected as the GC group, and 5822 healthy people from January 2015 to March 2022 in the physical examination center were selected as the control group. All patients in the GC group underwent radical gastrectomy and were confirmed to be GC by surgical pathology, excluding those with previous malignant tumor history and incomplete data. This study was approved by the Ethics Committee of Xijing Hospital. Clinicopathological data Baseline data included age, sex, ABO blood group, TNM stage, degree of differentiation, tumor location, lymph node metastasis, distant metastasis, and pathological typing. TNM staging was performed using American Joint Committee on Cancer (AJCC) Version 8. Tumor marker levels were measured 7 days before surgery. The serum tumor markers were determined after centrifugation of 3ml venous blood samples. Electrochemiluminescence (ECL) was used, and the instrument was the ECL analyzer and the matching kit provided by Roche Diagnostics (Germany). The reference values of CEA, CA199, CA125, AFP and CA724 were 5.0ng/ml, 27.0U/ml, 35 U/ml, 7.0ng/ml and 6.9U/ml, respectively. Statistical analysis All the research objects were divided into training set and validation set according to 7:3. SPSS26.0 software was used for data analysis. Measurement data were expressed as mean ± standard deviation or median and quartile. χ2 test was used for comparison of rates, and Mann-Whitney U test was used for comparison between groups. The area under the ROC curve (AUC) was used to evaluate the diagnostic efficacy of the index. The sensitivity, specificity, positive predictive value and negative predictive value were used to evaluate the efficacy. A P value of 0.05 was used as the threshold for statistical significance. Results Comparison of general clinical features The study population was divided into training set and validation set according to 7:3. There were 4091 healthy controls and 2552 GC patients in the training set, 1731 healthy controls and 1098 GC patients in the validation set. There was no significant difference in the basic clinical characteristics between the training set and the validation set ( P > 0.05, Table 1). Table 1. The clinicopathological characteristics of the study population, number (%) Characteristics Training set （ N=6643 ） Validation set （ N=2829 ） t /χ 2 P Healthy controls 4091 1731 Age, y Mean±standard deviation Gender Male Female ABO blood group A B O AB Patients with GC Age, y Mean±standard deviation Gender Male Female ABO blood group A B O AB TNM stage I II III IV Differentiation Well differentiation Well and middle differentiation Middle differentiation Middle and low differentiation Low differentiation Tumor site Pylorus Gastric body Antrum Whole stomach Lymphatic metastasis N0 N1-3 Remote metastasis M0 M1 Pathological stage Early stage Advanced stage 50±10 2134（52.2） 1957（47.8） 1178（28.8） 1259（30.8） 1224（29.9） 430（10.5） 2552 58±11 1896（74.3） 656（25.7） 818（32.1） 769（30.1） 714（28.0） 251（9.8） 716（28.1） 510（20.0） 1202（47.1） 124（4.9） 62（2.4） 57（2.2） 509（19.9） 316（12.4） 1608（63.0） 282（11.1） 838（32.8） 1283（50.3） 149（5.8） 1568（61.4） 984（38.6） 1883（73.8） 669（26.2） 601（23.6） 1951（76.4） 50±10 935（54.0） 796（46.0） 519（30.0） 525（30.3） 519（30.0） 168（9.7） 1098 58±11 823（75.0） 275（25.0） 358（32.6） 320（29.1） 302（27.5） 118（10.7） 335（30.5） 203（18.5） 515（46.9） 45（4.1） 43（3.9） 20（1.8） 222（20.2） 127（11.6） 686（62.5） 125（11.4） 349（31.8） 547（49.8） 77（7.0） 645（58.7） 453（41.3） 818（74.5） 280（25.5） 277（25.2） 821（74.8） 1.673 1.437 0.176 1.017 3.450 7.001 2.079 2.343 0.203 1.183 0.813 0.196 0.697 0.915 0.675 0.797 0.327 0.136 0.556 0.126 0.652 0.277 Tumor marker levels and blood group distribution In both the training and validation sets, the level of tumor markers in the GC group was significantly higher than that in the healthy control group, and the difference was statistically significant ( P B > O > AB, while that in healthy control group was: B > O > A > AB. There were statistically significant differences in ABO distribution constituent ratios in the whole population (χ2=10.920, P =0.012, Table 3) and the training set (χ2=8.495, P =0.037, Table 3). Table 2. Differences in tumor marker levels between GC group and healthy controls, median (IQR) Patients with GC Healthy subjects Z P CEA（ng/ml） Training set Validation set 3.875（2.250,105.000）* 4.280（2.378,106.250） 1.620（1.080,2.330） 1.600（1.030,2.360） -40.048 -27.908 .000 .000 CA199（U/ml） Training set Validation set 6.290（1.733,20.075） 6.305（1.850,15.650） 9.050（6.120,13.590） 8.620（5.890,12.890） -13.194 -7.871 .000 .000 CA125（U/ml） Training set Validation set AFP（ng/ml） Training set Validation set 5.505（1.560,8.868） 5.790（1.578,8.750） 3.720（2.590,27.095） 3.730（2.520,17.550） 10.180（7.680,13.590） 10.140（7.630,13.660） 2.880（2.100,3.910） 2.830（2.050,3.800） -35.102 -22.221 -23.428 -15.612 .000 .000 .000 .000 CA72-4（U/ml） Training set Validation set 4.580（2.022,47.600） 4.620（2.000,44.615） 1.610（0.980,2.960） 1.680（1.020,3.040） -32.623 -20.392 .000 .000 Note: *Values are expressed as medians and interquartile ranges. Table 3. Distribution of ABO blood groups Patients with GC Healthy subjects χ 2 P A Training set Validation set B Training set Validation set O Training set Validation set 818（32.1） 358（32.6） 769（30.1） 320（29.1） 714（28.0） 302（27.5） 1178（28.8） 519（30.0） 1259（30.8） 525（30.3） 1224（29.9） 519（30.0） 8.495 3.949 0.037 0.267 AB Training set Validation set 251（9.8） 118（10.7） 430（10.5） 168（9.7） Diagnostic value of single tumor marker and combined detection for GC The AUC of the five tumor markers ranged from 0.594-0.797, with a sensitivity of 32.22%-66.99%, which was at a low level (Table 4, Figure 1). The combined detection of tumor markers can improve its sensitivity and specificity. Compared with the combined detection of 5 tumor markers, the combination of type B and AB blood with 5 tumor markers can improve the diagnostic value of GC. The B blood group (AUC=0.936, 95%CI 0.927-0.945, P < 0.0001) combined with swelling mark detection was higher than that of swelling mark detection alone, and the difference was statistically significant. There was no significant difference in the AUC of AB blood (AUC=0.928, 95%CI 0.909-0.943, P =0.0566), but the P value was at the critical value of the test level (Table 5). Table 4. Diagnostic value of single tumor marker in patients with GC TM AUC 95%CI TPR （ % ） TNR （ % ） Youden index CEA 0.797 0.789-0.806 66.99 82.05 0.4904 CA199 0.594 0.584-0.604 34.05 91.64 0.2569 CA125 AFP CA724 0.753 0.672 0.734 0.744-0.762 0.662-0.681 0.725-0.743 44.68 32.22 42.79 99.07 99.71 99.02 0.4376 0.3193 0.4182 Note: TM: tumor maker, CI: confidence interval, TPR: true positive rate, TNR: true negative rate Table 5. Combined diagnosis compared with stratified combined diagnosis TM AUC 95%CI TPR (%) TNR (%) Youden index Z P TM A+TM 0.917 0.908 0.912-0.923 0.897-0.919 78.82 80.53 97.39 95.99 0.7621 0.7652 116.750 60.185 ＜0.0001 ＜0.0001 B+TM O+TM AB+TM 0.936 0.911 0.928 0.927-0.945 0.900-0.921 0.909-0.943 80.17 79.92 78.32 95.85 96.90 98.33 0.7602 0.7682 0.7665 81.086 57.473 42.531 ＜0.0001 ＜0.0001 ＜0.0001 Diagnostic value of blood group combined with single serum tumor marker for GC Stratified ABO blood group, in the training set, it was found that compared with the unstratified group, the stratified type A blood group could improve the diagnostic value of CA199, CA125, AFP and CA724 for GC, but the difference was not statistically significant (Table 6, Figure 2a). Blood type B could improve the diagnostic value of CEA (AUC=0.847, 95%CI 0.831-0.863, P =0.0081) in GC, and the difference was statistically significant (Table 6, Figure 2b). Blood type O could improve the diagnostic value of CA199 and CA724 for GC, and CA199 (AUC=0.611, 95%CI 0.589-0.633, P =0.0469) had statistical significance, while CA724 had no statistical difference (Table 6, Figure 2c). AB blood group can improve the diagnostic value of CEA, CA199, CA125 and AFP in GC, but no statistical difference was found (Table 6, Figure 2d). The same method was used to explore the diagnostic value of ABO blood group combined with tumor markers for GC in the validation set. It was found that compared with unstratified blood group, type A blood group could improve the diagnostic value of CA724 for GC, but the difference was not statistically significant (Table 7, Figure 3a). Consistent with the results of the training set, type B blood could improve the diagnostic value of CEA (AUC=0.857, 95%CI 0.832-0.880, P < 0.0001) for GC, and the difference was statistically significant (Table 7, Figure 3b). Type O blood can improve the diagnostic value of AFP in GC, but the difference was not statistically significant (Table 7, Figure 3c). AB blood group can improve the diagnostic value of CEA, CA199 and AFP in GC, but no statistical difference was found (Table 7, Figure 3d). In addition, the overall study population was stratified according to ABO blood group, it was found that in addition to type B blood (AUC=0.850,95%CI 0.837-0.863, P =0.0006) and type AB blood (AUC=0.837,95%CI 0.812-0.860, P =0.0439) could also improve the diagnostic value of CEA for GC, as shown in Figure 4. Table 6. Diagnostic Value of ABO blood group combined with tumor markers for GC (training set) TM AUC 95%CI TPR (%) TNR (%) Youden index Z P A CEA 0.740 0.720-0.759 48.29 98.22 0.4651 18.433 ＜0.0001 CA199 CA125 AFP CA724 0.601 0.762 0.677 0.742 0.579-0.622 0.743-0.780 0.656-0.698 0.722-0.761 35.09 45.23 31.54 42.42 90.32 99.24 99.99 99.15 0.2541 0.4470 0.3754 0.4157 7.083 21.343 14.276 19.966 ＜0.0001 ＜0.0001 ＜0.0001 ＜0.0001 B CEA 0.847 0.831-0.863 77.63 76.73 0.5436 36.781 ＜0.0001 CA199 0.571 0.549-0.593 31.21 92.53 0.2374 4.787 ＜0.0001 CA125 AFP CA724 O CEA CA199 CA125 AFP CA724 AB CEA CA199 CA125 AFP CA724 0.747 0.664 0.728 0.777 0.611 0.749 0.667 0.748 0.830 0.616 0.779 0.682 0.725 0.728-0.766 0.643-0.685 0.708-0.747 0.757-0.795 0.589-0.633 0.730-0.769 0.646-0.688 0.728-0.767 0.799-0.857 0.578-0.653 0.746-0.810 0.645-0.716 0.690-0.758 47.98 30.82 43.56 59.38 40.06 44.68 34.03 46.36 79.68 32.67 71.71 36.25 55.38 98.73 99.76 99.99 87.83 92.08 97.63 99.59 97.88 73.72 95.81 77.21 98.84 85.81 0.4671 0.3058 0.4356 0.4721 0.3213 0.4231 0.3363 0.4423 0.5340 0.2848 0.4892 0.3509 0.4119 19.100 12.76 17.802 21.969 7.283 18.572 12.695 19.361 18.195 4.562 12.824 8.000 9.978 ＜0.0001 ＜0.0001 ＜0.0001 ＜0.0001 ＜0.0001 ＜0.0001 ＜0.0001 ＜0.0001 ＜0.0001 ＜0.0001 ＜0.0001 ＜0.0001 ＜0.0001 Table 7. Diagnostic Value of ABO blood group combined with tumor markers for GC (validation set) TM AUC 95%CI TPR (%) TNR (%) Youden index Z P A CEA 0.782 0.753-0.809 52.79 99.61 0.5241 15.568 ＜0.0001 CA199 CA125 AFP CA724 0.576 0.741 0.658 0.735 0.542-0.609 0.711-0.770 0.626-0.689 0.705-0.764 50.28 47.77 33.80 45.81 73.32 94.61 99.81 98.84 0.2350 0.4237 0.3361 0.4465 3.476 12.431 8.063 12.698 ＜0.0001 ＜0.0001 ＜0.0001 ＜0.0001 B CEA 0.857 0.832-0.880 90.31 67.05 0.5736 26.005 ＜0.0001 CA199 CA125 AFP CA724 0.587 0.771 0.664 0.749 0.553-0.621 0.741-0.799 0.631-0.696 0.718-0.778 38.75 46.56 31.25 41.56 85.90 99.81 97.52 99.05 0.2465 0.4637 0.2877 0.4067 3.911 14.067 8.186 13.219 ＜0.0001 ＜0.0001 ＜0.0001 ＜0.0001 O CEA 0.781 0.751-0.808 69.21 77.84 0.4705 14.858 ＜0.0001 CA199 CA125 AFP CA724 0.592 0.750 0.695 0.696 0.558-0.626 0.719-0.779 0.662-0.726 0.663-0.727 35.76 57.62 39.40 43.05 86.90 83.82 94.99 98.84 0.2266 0.4143 0.3439 0.4189 4.031 12.414 9.754 8.938 ＜0.0001 ＜0.0001 ＜0.0001 ＜0.0001 AB CEA 0.852 0.805-0.891 74.58 85.12 0.5970 13.831 ＜0.0001 CA199 CA125 AFP CA724 0.612 0.696 0.695 0.711 0.553-0.669 0.639-0.748 0.638-0.748 0.655-0.763 46.61 44.92 33.90 46.61 86.90 97.62 99.99 94.05 0.3351 0.4253 0.3390 0.4066 2.955 5.391 5.926 6.274 ＜0.0001 ＜0.0001 ＜0.0001 ＜0.0001 Discussion Tumor marker is a kind of substance synthesized and released by tumor itself. In the process of tumor occurrence and development, it is also accompanied by the modified expression of blood group antigen in tumor cells. So far, a large number of studies have explored the value of tumor markers on the incidence of gastric cancer [ 9 , 10 ], clinicopathological features and prognosis[ 11 – 13 ]. However, there is no study on the diagnostic value of ABO blood group combined with tumor markers for gastric cancer. This study found that type B blood and AB blood can improve the diagnostic value of CEA in patients with GC. Combined detection of tumor markers can improve the sensitivity and specificity of GC diagnosis. Blood type B and AB can improve the diagnostic value of combined detection of tumor markers for gastric cancer. Furthermore, joint five kinds of tumor markers detection of blood type B blood AUC value was higher than 5 kinds of tumor markers detection, and statistically difference. However, AB blood there was no statistically significant difference, but the p value in the inspection level threshold. The sensitivity of single tumor markers in detecting gastric cancer is insufficient. Studies have explored the diagnostic value of CEA, CA724, CA199 and CA125 for gastric cancer, and the results suggest that the sensitivity of these tumor markers in diagnosing gastric cancer is between 20% and 40%, and the sensitivity of combining these four tumor markers is only 60.9%[ 14 ]. In this study, the sensitivity of the five tumor markers in the diagnosis of gastric cancer ranged from 32–67%, and the sensitivity of the combined detection increased to 91.7%. It is somewhat different from previous reports, which may be because this study only included gastric cancer patients and healthy people, and did not include population with gastric precancerous lesions, leading to increased sensitivity. It is well known that the occurrence and development of gastric cancer are related to genetic factors, environmental factors and Helicobacter pylori infection. Blood group is one of the most stable genetic factors, among which ABO blood group is by far the most important blood group system[ 15 ]. This study found that B type blood combined with tumor markers can improve the diagnostic value of gastric cancer. At present, there is no study on the combined detection of blood group and tumor markers for the diagnosis of gastric cancer, but some studies[ 16 , 17 ] have explored the correlation between ABO blood group and clinicopathological characteristics of gastric cancer, and proposed that the proportion of elevated CEA in blood group B and AB was higher than that in other blood groups, which could indirectly explain the results of this study. In addition, Qiu et al.[ 18 ] found that in patients with gastric adenocarcinoma, the proportion of increased CEA in blood group A was significantly higher than that in other blood groups ( P = 0.003), and the proportion of increased CEA and CA199 in blood group AB was significantly lower than that in other blood groups ( P < 0.001, P = 0.005) for untreated gastric cancer patients. In this study, the combination of blood group A and tumor markers did not improve the diagnostic value of gastric cancer. AB blood type can improve the diagnostic value of CEA and CA199 for gastric cancer, but the difference is not statistically significant. The main strength of our study is that the sample size is large and the subjects are divided into training set and validation set by 7:3 for double validation. In addition, our current study has several limitations. Firstly, due to the limitation of conditions, ABO blood group and tumor marker level information of patients with GC precancerous diseases could not be obtained, and patients with GC precancerous diseases were not included, so the objectivity of the results was slightly weak. Secondly, this study is a retrospective study, and prospective studies are needed to further verify the diagnostic value of ABO blood group combined with tumor markers for GC. Conclusion In summary, our results suggested that ABO blood group combined with tumor markers as screening indicators for GC can improve the diagnostic value of GC patients. Among them, type B and AB blood combined with tumor markers have the most significant value in the diagnosis of GC. Declarations Ethics approval and consent to participate This retrospective study was reviewed by the Ethics Committee of the First Affiliated Hospital of Air Force Medical University and approval was obtained. All methods were carried out in accordance with relevant guidelines and regulations. All experimental protocols were approved by the Ethics Committee of the First Affiliated Hospital of Air Force Medical University. Due to the retrospective nature of the study, the informed consent was waived by the Ethics Committee of the First Affiliated Hospital of Air Force Medical University. Consent for publication Not applicable. Availability of data and materials The datasets generated and analyzed during the current study are available from the corresponding authors on reasonable request. Conflict of Interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Funding This work was supported by grants from the National Natural Science Foundation of China (No. 82170560 to YQS). Authors' contributions YQS, YHL, SSC, WNS, XDQ and SBL contributed to the design of the study, interpretation of the data, and critical revision of the manuscript. YHL contributed to the analysis and interpretation of the data and drafted the manuscript. All authors approved the final version of the manuscript for submission. Acknowledgments We would like to thank the individuals who have contributed to the current study in various capacities. References Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, Bray F: Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries . CA: a cancer journal for clinicians 2021, 71 (3):209-249. doi: 10.3322/caac.21660. Cao W, Chen H, Yu Y, Li N, Chen W: Changing profiles of cancer burden worldwide and in China: a secondary analysis of the global cancer statistics 2020 . CHINESE MED J-PEKING 2021, 134 (7):783-791. doi: 10.1097/CM9.0000000000001474. 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Tan J: To study the correlation between ABO blood group and clinical characteristics and prognosis of gastric cancer patients. Yan 'an University, 2020. (in Chinese). Xu X-L, Wang R-F, Yuan J-S, Song W-Q: Correlation analysis between gastric cancer and ABO blood group. Chongqing Medicine . 2020, 49 (08):1307-1310. (in Chinese). Qiu M, Zhang D, Ruan D, Luo H, Wang Z, Zhou Z, Wang F, Li Y, Xu R: A relationship between ABO blood groups and clinicopathologic characteristics of patients with gastric adenocarcinoma in China . Medical oncology (Northwood, London, England) 2010, 28 (Suppl 1):268-273. doi: 10.1007/s12032-010-9735-5. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-2192622","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":148936916,"identity":"a6fa7369-d2a5-4c36-9ca3-d108bf6edb06","order_by":0,"name":"Yuhuan Liu","email":"","orcid":"","institution":"Xi’an Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yuhuan","middleName":"","lastName":"Liu","suffix":""},{"id":148936917,"identity":"ac072535-d1f0-45fe-ab10-b763ab80b0e6","order_by":1,"name":"Shasha Chen","email":"","orcid":"","institution":"Xi’an Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Shasha","middleName":"","lastName":"Chen","suffix":""},{"id":148936919,"identity":"116750c0-a6f6-4f46-bb30-0ad191438b81","order_by":2,"name":"Weina Shen","email":"","orcid":"","institution":"Xi’an Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Weina","middleName":"","lastName":"Shen","suffix":""},{"id":148936920,"identity":"47d5171d-5867-463c-86fc-ed170bbd831f","order_by":3,"name":"Xiaodong Qu","email":"","orcid":"","institution":"Air Force Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Xiaodong","middleName":"","lastName":"Qu","suffix":""},{"id":148936923,"identity":"6637f90f-4f81-4ec0-90cd-95502d4ef2a5","order_by":4,"name":"Songbo Li","email":"","orcid":"","institution":"Air Force Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Songbo","middleName":"","lastName":"Li","suffix":""},{"id":148936924,"identity":"42c59f37-fd94-401b-b91f-caf431e6da81","order_by":5,"name":"Yongquan Shi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2ElEQVRIiWNgGAWjYDACCcYGMM3PfABMQ7nEaJFsSyBaC5Q2OEasFvnZzW0Sb9vs8oyPcadu5mGwkd1wgPnZA3xaDO4cbJOc25ZcbHaMd9ttHoY04w0H2MwN8GqRSGyT5m1jTtx2vxek5XDihgM8bBL4tMjPAGupT9zcBrblP2EtDDfAWoCGs4G1HCCsxeBGYrPlnHPHE2cA/XJzjkGy8czDbGYEHJb+8MabsurEfqDDbrypsJPtO978DL/DGBhYJHgQlgIxMwH1ICUfeAgrGgWjYBSMgpEMAM+GTBT0pM5+AAAAAElFTkSuQmCC","orcid":"","institution":"Air Force Medical University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Yongquan","middleName":"","lastName":"Shi","suffix":""}],"badges":[],"createdAt":"2022-10-22 06:29:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2192622/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2192622/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":28669116,"identity":"98a2ea4c-5e64-43e0-a213-2e8431b58bde","added_by":"auto","created_at":"2022-11-04 14:24:46","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":135715,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDiagnostic value of single tumor marker for GC patients\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-2192622/v1/7ed5fac137046c0186a691ef.png"},{"id":28668801,"identity":"e019cdbe-aaf9-497a-b23b-bb7a79ba9f57","added_by":"auto","created_at":"2022-11-04 14:16:46","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1293741,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDiagnostic value of blood type A (a), B (b), O (c) and AB (d) combined with tumor markers for GC (training set)\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-2192622/v1/b7f41c472e9ef4b8caa9226b.png"},{"id":28669115,"identity":"76edf761-1e54-42d6-a3a4-f81fa9bf1277","added_by":"auto","created_at":"2022-11-04 14:24:46","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1245794,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDiagnostic value of blood type A (a), B (b), O (c) and AB (d) combined with tumor markers for GC (validation set)\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-2192622/v1/d23d48ada0698e359620e217.png"},{"id":28668804,"identity":"f8266422-6694-473b-99dd-8c1ccfad8c18","added_by":"auto","created_at":"2022-11-04 14:16:47","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":410058,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDiagnostic value of whole population blood group combined with CEA for GC\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-2192622/v1/ebd181fcf502de878ccfbf1f.png"},{"id":34858220,"identity":"b910a6fb-5f18-481c-a9b1-7bcc3d5095ea","added_by":"auto","created_at":"2023-03-27 13:29:34","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2021199,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2192622/v1/135f2600-54c5-4dce-ab56-5d7d95563a74.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Diagnostic Value of ABO Blood Group Combined with Tumor Markers in Gastric Cancer","fulltext":[{"header":"Background","content":"\u003cp\u003eGastric cancer (GC) is an important cancer worldwide. According to the latest data of the International Agency for Research on Cancer (IARC), it ranks the 5th in incidence and the 4th in mortality globally[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. GC is the most common gastrointestinal tumor in China, of which the rate of early detection is low. Compared with 2015, GC ranked third in the number of new cases and mortality of common malignant tumors in 2020[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], posing a serious threat to human health. Early GC can be treated by surgery, and the 5-year survival rate is more than 90%, while advanced GC can be treated by surgery, and the 5-year survival rate is less than 30%[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The gold standard for screening early GC is gastroscopy, but its detection rate is less than 10%, it is invasive, it requires a lot of human resources, and its acceptance is low. It is not suitable for large-scale population screening and follow-up of GC.\u003c/p\u003e \u003cp\u003eTumor markers have the advantages of non-invasive, easy specimen acquisition and low cost, which are suitable for dynamic monitoring. However, the positive rate of tumor markers in advanced GC is only 20%-30%, and the positive rate in early GC is less than 10%[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Although the sensitivity of combined serum tumor markers in the diagnosis of GC has been improved, it is still low [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Since Aird et al. [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] first proposed that blood type A was associated with the occurrence of GC in 1953, a large number of studies on blood type and the incidence, clinicopathological characteristics and prognosis of GC have been carried out. However, the relationship between ABO blood group and GC cannot be concluded with certainty due to conflicting findings at different studies[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. If the combined detection of blood group and tumor markers can improve the diagnostic efficiency of GC, the diagnostic timing, diagnostic cost and diagnostic accuracy of GC can be improved. Therefore, the purpose of the present study was to investigate the value of ABO blood group combined with serum tumor markers, including CEA, CA199, CA125, AFP and CA724, for the diagnosis of GC and provide additional reference indicators for the early diagnosis and treatment of the disease.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePatients\u003c/h2\u003e \u003cp\u003eA total of 3650 GC patients from January 2015 to December 2019 in the Xijing Hospital of Digestive Diseases were selected as the GC group, and 5822 healthy people from January 2015 to March 2022 in the physical examination center were selected as the control group. All patients in the GC group underwent radical gastrectomy and were confirmed to be GC by surgical pathology, excluding those with previous malignant tumor history and incomplete data. This study was approved by the Ethics Committee of Xijing Hospital.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eClinicopathological data\u003c/h2\u003e \u003cp\u003eBaseline data included age, sex, ABO blood group, TNM stage, degree of differentiation, tumor location, lymph node metastasis, distant metastasis, and pathological typing. TNM staging was performed using American Joint Committee on Cancer (AJCC) Version 8. Tumor marker levels were measured 7 days before surgery. The serum tumor markers were determined after centrifugation of 3ml venous blood samples. Electrochemiluminescence (ECL) was used, and the instrument was the ECL analyzer and the matching kit provided by Roche Diagnostics (Germany). The reference values of CEA, CA199, CA125, AFP and CA724 were 5.0ng/ml, 27.0U/ml, 35 U/ml, 7.0ng/ml and 6.9U/ml, respectively.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eAll the research objects were divided into training set and validation set according to 7:3. SPSS26.0 software was used for data analysis. Measurement data were expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation or median and quartile. χ2 test was used for comparison of rates, and Mann-Whitney U test was used for comparison between groups. The area under the ROC curve (AUC) was used to evaluate the diagnostic efficacy of the index. The sensitivity, specificity, positive predictive value and negative predictive value were used to evaluate the efficacy. A \u003cem\u003eP\u003c/em\u003e value of 0.05 was used as the threshold for statistical significance.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eComparison of general clinical features\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study population was divided into training set and validation set according to 7:3. There were 4091 healthy controls and 2552 GC patients in the training set, 1731 healthy controls and 1098 GC patients in the validation set. There was no significant difference in the basic clinical characteristics between the training set and the validation set (\u003cem\u003eP\u003c/em\u003e \u0026gt; 0.05, Table 1).\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1. The clinicopathological characteristics of the study population, number (%)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"709\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"30.649717514124294%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristics\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.1135%;\" valign=\"top\" width=\"24.01129943502825%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTraining set\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e（\u003c/strong\u003e\u003cstrong\u003eN=6643\u003c/strong\u003e\u003cstrong\u003e）\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21.4184%;\" valign=\"top\" width=\"21.327683615819208%\"\u003e\n \u003cp\u003e\u003cstrong\u003eValidation set\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e（\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;N=2829\u003c/strong\u003e）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.0284%;\" valign=\"top\" width=\"15.96045197740113%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003et\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e/\u0026chi;\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.0851%;\" valign=\"top\" width=\"8.05084745762712%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"30.649717514124294%\"\u003e\n \u003cp\u003e\u003cstrong\u003eHealthy controls\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.1135%;\" valign=\"top\" width=\"24.01129943502825%\"\u003e\n \u003cp\u003e4091\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21.4184%;\" valign=\"top\" width=\"21.327683615819208%\"\u003e\n \u003cp\u003e1731\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.0284%;\" valign=\"top\" width=\"15.96045197740113%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.0851%;\" valign=\"top\" width=\"8.05084745762712%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 29.5035%;\" valign=\"top\" width=\"29.37853107344633%\"\u003e\n \u003cp\u003eAge, y\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Mean\u0026plusmn;standard deviation\u003c/p\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Male\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Female\u003c/p\u003e\n \u003cp\u003eABO blood group\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; A\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; B\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; O\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; AB\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003ePatients with GC\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eAge, y\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;Mean\u0026plusmn;standard deviation\u003c/p\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;Male\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;Female\u003c/p\u003e\n \u003cp\u003eABO blood group\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;A\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;B\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;O\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;AB\u003c/p\u003e\n \u003cp\u003eTNM stage\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;I\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;II\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;III\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;IV\u003c/p\u003e\n \u003cp\u003eDifferentiation\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;Well differentiation\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;Well and middle differentiation\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;Middle differentiation\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;Middle and low differentiation\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;Low differentiation\u003c/p\u003e\n \u003cp\u003eTumor site\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;Pylorus\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;Gastric body\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;Antrum\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;Whole stomach\u003c/p\u003e\n \u003cp\u003eLymphatic metastasis\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;N0\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;N1-3\u003c/p\u003e\n \u003cp\u003eRemote metastasis\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;M0\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;M1\u003c/p\u003e\n \u003cp\u003ePathological stage\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;Early stage\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;Advanced stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 24.1135%;\" valign=\"top\" width=\"24.01129943502825%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e50\u0026plusmn;10 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2134（52.2）\u003c/p\u003e\n \u003cp\u003e1957（47.8）\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1178（28.8）\u003c/p\u003e\n \u003cp\u003e1259（30.8）\u003c/p\u003e\n \u003cp\u003e1224（29.9）\u003c/p\u003e\n \u003cp\u003e430（10.5）\u003c/p\u003e\n \u003cp\u003e2552\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e58\u0026plusmn;11\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1896（74.3）\u003c/p\u003e\n \u003cp\u003e656（25.7）\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e818（32.1）\u003c/p\u003e\n \u003cp\u003e769（30.1）\u003c/p\u003e\n \u003cp\u003e714（28.0）\u003c/p\u003e\n \u003cp\u003e251（9.8）\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e716（28.1）\u003c/p\u003e\n \u003cp\u003e510（20.0）\u003c/p\u003e\n \u003cp\u003e1202（47.1）\u003c/p\u003e\n \u003cp\u003e124（4.9）\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e62（2.4）\u003c/p\u003e\n \u003cp\u003e57（2.2）\u003c/p\u003e\n \u003cp\u003e509（19.9）\u003c/p\u003e\n \u003cp\u003e316（12.4）\u003c/p\u003e\n \u003cp\u003e1608（63.0）\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e282（11.1）\u003c/p\u003e\n \u003cp\u003e838（32.8）\u003c/p\u003e\n \u003cp\u003e1283（50.3）\u003c/p\u003e\n \u003cp\u003e149（5.8）\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1568（61.4）\u003c/p\u003e\n \u003cp\u003e984（38.6）\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1883（73.8）\u003c/p\u003e\n \u003cp\u003e669（26.2）\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e601（23.6）\u003c/p\u003e\n \u003cp\u003e1951（76.4）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 21.4184%;\" valign=\"top\" width=\"21.327683615819208%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e50\u0026plusmn;10\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e935（54.0）\u003c/p\u003e\n \u003cp\u003e796（46.0）\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e519（30.0）\u003c/p\u003e\n \u003cp\u003e525（30.3）\u003c/p\u003e\n \u003cp\u003e519（30.0）\u003c/p\u003e\n \u003cp\u003e168（9.7）\u003c/p\u003e\n \u003cp\u003e1098\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e58\u0026plusmn;11\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e823（75.0）\u003c/p\u003e\n \u003cp\u003e275（25.0）\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e358（32.6）\u003c/p\u003e\n \u003cp\u003e320（29.1）\u003c/p\u003e\n \u003cp\u003e302（27.5）\u003c/p\u003e\n \u003cp\u003e118（10.7）\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e335（30.5）\u003c/p\u003e\n \u003cp\u003e203（18.5）\u003c/p\u003e\n \u003cp\u003e515（46.9）\u003c/p\u003e\n \u003cp\u003e45（4.1）\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e43（3.9）\u003c/p\u003e\n \u003cp\u003e20（1.8）\u003c/p\u003e\n \u003cp\u003e222（20.2）\u003c/p\u003e\n \u003cp\u003e127（11.6）\u003c/p\u003e\n \u003cp\u003e686（62.5）\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e125（11.4）\u003c/p\u003e\n \u003cp\u003e349（31.8）\u003c/p\u003e\n \u003cp\u003e547（49.8）\u003c/p\u003e\n \u003cp\u003e77（7.0）\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e645（58.7）\u003c/p\u003e\n \u003cp\u003e453（41.3）\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e818（74.5）\u003c/p\u003e\n \u003cp\u003e280（25.5）\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e277（25.2）\u003c/p\u003e\n \u003cp\u003e821（74.8）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.0284%;\" valign=\"top\" width=\"15.96045197740113%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.673\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.437\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.176\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.017\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3.450\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e7.001\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2.079\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2.343\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.203\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.183\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.0851%;\" valign=\"top\" width=\"8.05084745762712%\"\u003e\n \u003cp\u003e0.813\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.196\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.697\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.915\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.675\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.797\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.327\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.136\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.556\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.126\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.652\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.277\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTumor marker levels and blood group distribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn both the training and validation sets, the level of tumor markers in the GC group was significantly higher than that in the healthy control group, and the difference was statistically significant (\u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u0026lt; 0.05), as shown in Table 2. The distribution of blood group in GC group was: A \u0026gt; B \u0026gt; O \u0026gt; AB, while that in healthy control group was: B \u0026gt; O \u0026gt; A \u0026gt; AB. There were statistically significant differences in ABO distribution constituent ratios in the whole population (\u0026chi;2=10.920, \u003cem\u003eP\u003c/em\u003e =0.012, Table 3) and the training set (\u0026chi;2=8.495, \u003cem\u003eP\u003c/em\u003e =0.037, Table 3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. Differences in tumor marker levels between GC group and healthy controls, median (IQR)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"680\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"20.851688693098385%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"30.54331864904552%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePatients with GC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.431718061674008%\"\u003e\n \u003cp\u003e\u003cstrong\u003eHealthy subjects\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.80323054331865%\"\u003e\n \u003cp\u003e\u003cstrong\u003eZ\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.370044052863436%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"20.851688693098385%\"\u003e\n \u003cp\u003eCEA（ng/ml）\u003c/p\u003e\n \u003cp\u003eTraining set\u003c/p\u003e\n \u003cp\u003eValidation set\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"30.54331864904552%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3.875（2.250,105.000）*\u003c/p\u003e\n \u003cp\u003e4.280（2.378,106.250）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.431718061674008%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.620（1.080,2.330）\u003c/p\u003e\n \u003cp\u003e1.600（1.030,2.360）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.80323054331865%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-40.048\u003c/p\u003e\n \u003cp\u003e-27.908\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.370044052863436%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"20.851688693098385%\"\u003e\n \u003cp\u003eCA199（U/ml）\u003c/p\u003e\n \u003cp\u003eTraining set\u003c/p\u003e\n \u003cp\u003eValidation set\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"30.54331864904552%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e6.290（1.733,20.075）\u003c/p\u003e\n \u003cp\u003e6.305（1.850,15.650）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.431718061674008%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e9.050（6.120,13.590）\u003c/p\u003e\n \u003cp\u003e8.620（5.890,12.890）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.80323054331865%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-13.194\u003c/p\u003e\n \u003cp\u003e-7.871\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.370044052863436%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"20.851688693098385%\"\u003e\n \u003cp\u003eCA125（U/ml）\u003c/p\u003e\n \u003cp\u003eTraining set\u003c/p\u003e\n \u003cp\u003eValidation set\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eAFP（ng/ml）\u003c/p\u003e\n \u003cp\u003eTraining set\u003c/p\u003e\n \u003cp\u003eValidation set\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"30.54331864904552%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e5.505（1.560,8.868）\u003c/p\u003e\n \u003cp\u003e5.790（1.578,8.750）\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3.720（2.590,27.095）\u003c/p\u003e\n \u003cp\u003e3.730（2.520,17.550）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.431718061674008%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e10.180（7.680,13.590）\u003c/p\u003e\n \u003cp\u003e10.140（7.630,13.660）\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2.880（2.100,3.910）\u003c/p\u003e\n \u003cp\u003e2.830（2.050,3.800）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.80323054331865%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-35.102\u003c/p\u003e\n \u003cp\u003e-22.221\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-23.428\u003c/p\u003e\n \u003cp\u003e-15.612\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.370044052863436%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"20.851688693098385%\"\u003e\n \u003cp\u003eCA72-4（U/ml）\u003c/p\u003e\n \u003cp\u003eTraining set\u003c/p\u003e\n \u003cp\u003eValidation set\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"30.54331864904552%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e4.580（2.022,47.600）\u003c/p\u003e\n \u003cp\u003e4.620（2.000,44.615）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.431718061674008%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.610（0.980,2.960）\u003c/p\u003e\n \u003cp\u003e1.680（1.020,3.040）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.80323054331865%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e-32.623\u003c/p\u003e\n \u003cp\u003e-20.392\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.370044052863436%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003cp\u003e.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eNote:\u003c/strong\u003e *Values are expressed as medians and interquartile ranges.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3. Distribution of ABO blood groups\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"680\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"20.88235294117647%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"29.11764705882353%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePatients with GC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e\u003cstrong\u003eHealthy subjects\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.61764705882353%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.382352941176471%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"20.88235294117647%\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003cp\u003eTraining set\u003c/p\u003e\n \u003cp\u003eValidation set\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eB\u003c/p\u003e\n \u003cp\u003eTraining set\u003c/p\u003e\n \u003cp\u003eValidation set\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eO\u003c/p\u003e\n \u003cp\u003eTraining set\u003c/p\u003e\n \u003cp\u003eValidation set\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"29.11764705882353%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e818（32.1）\u003c/p\u003e\n \u003cp\u003e358（32.6）\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e769（30.1）\u003c/p\u003e\n \u003cp\u003e320（29.1）\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e714（28.0）\u003c/p\u003e\n \u003cp\u003e302（27.5）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1178（28.8）\u003c/p\u003e\n \u003cp\u003e519（30.0）\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1259（30.8）\u003c/p\u003e\n \u003cp\u003e525（30.3）\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1224（29.9）\u003c/p\u003e\n \u003cp\u003e519（30.0）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.61764705882353%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e8.495\u003c/p\u003e\n \u003cp\u003e3.949\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.382352941176471%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.037\u003c/p\u003e\n \u003cp\u003e0.267\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"20.88235294117647%\"\u003e\n \u003cp\u003eAB\u003c/p\u003e\n \u003cp\u003eTraining set\u003c/p\u003e\n \u003cp\u003eValidation set\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"29.11764705882353%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e251（9.8）\u003c/p\u003e\n \u003cp\u003e118（10.7）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"25%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e430（10.5）\u003c/p\u003e\n \u003cp\u003e168（9.7）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.61764705882353%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.382352941176471%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eDiagnostic value of single tumor marker and combined detection for GC\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe AUC of the five tumor markers ranged from 0.594-0.797, with a sensitivity of 32.22%-66.99%, which was at a low level (Table 4, Figure 1). The combined detection of tumor markers can improve its sensitivity and specificity. Compared with the combined detection of 5 tumor markers, the combination of type B and AB blood with 5 tumor markers can improve the diagnostic value of GC. The B blood group (AUC=0.936, 95%CI 0.927-0.945, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.0001) combined with swelling mark detection was higher than that of swelling mark detection alone, and the difference was statistically significant. There was no significant difference in the AUC of AB blood (AUC=0.928, 95%CI 0.909-0.943, \u003cem\u003eP\u003c/em\u003e =0.0566), but the P value was at the critical value of the test level (Table 5).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4. Diagnostic value of single tumor marker in patients with GC\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"651\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"10.923076923076923%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTM\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.923076923076923%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAUC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.923076923076923%\"\u003e\n \u003cp\u003e\u003cstrong\u003e95%CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.23076923076923%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTPR\u003c/strong\u003e\u003cstrong\u003e（\u003c/strong\u003e\u003cstrong\u003e%\u003c/strong\u003e\u003cstrong\u003e）\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.23076923076923%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTNR\u003c/strong\u003e\u003cstrong\u003e（\u003c/strong\u003e\u003cstrong\u003e%\u003c/strong\u003e\u003cstrong\u003e）\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.76923076923077%\"\u003e\n \u003cp\u003e\u003cstrong\u003eYouden index\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"10.923076923076923%\"\u003e\n \u003cp\u003eCEA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.923076923076923%\"\u003e\n \u003cp\u003e0.797\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.923076923076923%\"\u003e\n \u003cp\u003e0.789-0.806\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.23076923076923%\"\u003e\n \u003cp\u003e66.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.23076923076923%\"\u003e\n \u003cp\u003e82.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.76923076923077%\"\u003e\n \u003cp\u003e0.4904\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"10.923076923076923%\"\u003e\n \u003cp\u003eCA199\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.923076923076923%\"\u003e\n \u003cp\u003e0.594\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.923076923076923%\"\u003e\n \u003cp\u003e0.584-0.604\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.23076923076923%\"\u003e\n \u003cp\u003e34.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.23076923076923%\"\u003e\n \u003cp\u003e91.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.76923076923077%\"\u003e\n \u003cp\u003e0.2569\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"10.923076923076923%\"\u003e\n \u003cp\u003eCA125\u003c/p\u003e\n \u003cp\u003eAFP\u003c/p\u003e\n \u003cp\u003eCA724\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"14.923076923076923%\"\u003e\n \u003cp\u003e0.753\u003c/p\u003e\n \u003cp\u003e0.672\u003c/p\u003e\n \u003cp\u003e0.734\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.923076923076923%\"\u003e\n \u003cp\u003e0.744-0.762\u003c/p\u003e\n \u003cp\u003e0.662-0.681\u003c/p\u003e\n \u003cp\u003e0.725-0.743\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.23076923076923%\"\u003e\n \u003cp\u003e44.68\u003c/p\u003e\n \u003cp\u003e32.22\u003c/p\u003e\n \u003cp\u003e42.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.23076923076923%\"\u003e\n \u003cp\u003e99.07\u003c/p\u003e\n \u003cp\u003e99.71\u003c/p\u003e\n \u003cp\u003e99.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.76923076923077%\"\u003e\n \u003cp\u003e0.4376\u003c/p\u003e\n \u003cp\u003e0.3193\u003c/p\u003e\n \u003cp\u003e0.4182\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eNote:\u003c/strong\u003e TM: tumor maker, CI: confidence interval, TPR: true positive rate, TNR: true negative rate\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5. Combined diagnosis compared with stratified combined diagnosis\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"654\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9.0659%;\" valign=\"top\" width=\"10.122699386503067%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTM\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.1648%;\" valign=\"top\" width=\"11.503067484662576%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAUC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.3765%;\" valign=\"top\" width=\"19.478527607361965%\"\u003e\n \u003cp\u003e\u003cstrong\u003e95%CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.4942%;\" valign=\"top\" width=\"9.355828220858896%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTPR (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.1265%;\" valign=\"top\" width=\"9.815950920245399%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTNR (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.9444%;\" valign=\"top\" width=\"17.791411042944784%\"\u003e\n \u003cp\u003e\u003cstrong\u003eYouden index\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.7658%;\" valign=\"top\" width=\"11.349693251533742%\"\u003e\n \u003cp\u003e\u003cstrong\u003eZ\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 21.8152%;\" valign=\"top\" width=\"10.122699386503067%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9.0659%;\" valign=\"top\" width=\"10.122699386503067%\"\u003e\n \u003cp\u003eTM\u003c/p\u003e\n \u003cp\u003eA+TM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.1648%;\" valign=\"top\" width=\"11.503067484662576%\"\u003e\n \u003cp\u003e0.917\u003c/p\u003e\n \u003cp\u003e0.908\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.3765%;\" valign=\"top\" width=\"19.478527607361965%\"\u003e\n \u003cp\u003e0.912-0.923\u003c/p\u003e\n \u003cp\u003e0.897-0.919\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.4942%;\" valign=\"top\" width=\"9.355828220858896%\"\u003e\n \u003cp\u003e78.82\u003c/p\u003e\n \u003cp\u003e80.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.1265%;\" valign=\"top\" width=\"9.815950920245399%\"\u003e\n \u003cp\u003e97.39\u003c/p\u003e\n \u003cp\u003e95.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.9444%;\" valign=\"top\" width=\"17.791411042944784%\"\u003e\n \u003cp\u003e0.7621\u003c/p\u003e\n \u003cp\u003e0.7652\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.7658%;\" valign=\"top\" width=\"10.276073619631902%\"\u003e\n \u003cp\u003e116.750\u003c/p\u003e\n \u003cp\u003e60.185\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 21.8152%;\" valign=\"top\" width=\"11.656441717791411%\"\u003e\n \u003cp\u003e＜0.0001\u003c/p\u003e\n \u003cp\u003e＜0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9.0659%;\" valign=\"top\" width=\"10.122699386503067%\"\u003e\n \u003cp\u003eB+TM\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eO+TM AB+TM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.1648%;\" valign=\"top\" width=\"11.503067484662576%\"\u003e\n \u003cp\u003e0.936\u003c/p\u003e\n \u003cp\u003e0.911\u003c/p\u003e\n \u003cp\u003e0.928\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 15.3765%;\" valign=\"top\" width=\"19.478527607361965%\"\u003e\n \u003cp\u003e0.927-0.945\u003c/p\u003e\n \u003cp\u003e0.900-0.921\u003c/p\u003e\n \u003cp\u003e0.909-0.943\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11.4942%;\" valign=\"top\" width=\"9.355828220858896%\"\u003e\n \u003cp\u003e80.17\u003c/p\u003e\n \u003cp\u003e79.92\u003c/p\u003e\n \u003cp\u003e78.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.1265%;\" valign=\"top\" width=\"9.815950920245399%\"\u003e\n \u003cp\u003e95.85\u003c/p\u003e\n \u003cp\u003e96.90\u003c/p\u003e\n \u003cp\u003e98.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.9444%;\" valign=\"top\" width=\"17.791411042944784%\"\u003e\n \u003cp\u003e0.7602\u003c/p\u003e\n \u003cp\u003e0.7682\u003c/p\u003e\n \u003cp\u003e0.7665\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.7658%;\" valign=\"top\" width=\"10.276073619631902%\"\u003e\n \u003cp\u003e81.086\u003c/p\u003e\n \u003cp\u003e57.473\u003c/p\u003e\n \u003cp\u003e42.531\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 21.8152%;\" valign=\"top\" width=\"11.656441717791411%\"\u003e\n \u003cp\u003e＜0.0001\u003c/p\u003e\n \u003cp\u003e＜0.0001\u003c/p\u003e\n \u003cp\u003e＜0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eDiagnostic value of blood group combined with single serum tumor marker for GC\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStratified ABO blood group, in the training set, it was found that compared with the unstratified group, the stratified type A blood group could improve the diagnostic value of CA199, CA125, AFP and CA724 for GC, but the difference was not statistically significant (Table 6, Figure 2a). Blood type B could improve the diagnostic value of CEA (AUC=0.847, 95%CI 0.831-0.863, \u003cem\u003eP\u003c/em\u003e=0.0081) in GC, and the difference was statistically significant (Table 6, Figure 2b). Blood type O could improve the diagnostic value of CA199 and CA724 for GC, and CA199 (AUC=0.611, 95%CI 0.589-0.633, \u003cem\u003eP\u003c/em\u003e=0.0469) had statistical significance, while CA724 had no statistical difference (Table 6, Figure 2c). AB blood group can improve the diagnostic value of CEA, CA199, CA125 and AFP in GC, but no statistical difference was found (Table 6, Figure 2d). The same method was used to explore the diagnostic value of ABO blood group combined with tumor markers for GC in the validation set. It was found that compared with unstratified blood group, type A blood group could improve the diagnostic value of CA724 for GC, but the difference was not statistically significant (Table 7, Figure 3a). Consistent with the results of the training set, type B blood could improve the diagnostic value of CEA (AUC=0.857, 95%CI 0.832-0.880, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.0001) for GC, and the difference was statistically significant (Table 7, Figure 3b). Type O blood can improve the diagnostic value of AFP in GC, but the difference was not statistically significant (Table 7, Figure 3c). AB blood group can improve the diagnostic value of CEA, CA199 and AFP in GC, but no statistical difference was found (Table 7, Figure 3d). In addition, the overall study population was stratified according to ABO blood group, it was found that in addition to type B blood (AUC=0.850,95%CI 0.837-0.863, \u003cem\u003eP\u003c/em\u003e =0.0006) and type AB blood (AUC=0.837,95%CI 0.812-0.860, \u003cem\u003eP\u003c/em\u003e =0.0439) could also improve the diagnostic value of CEA for GC, as shown in Figure 4.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 6. Diagnostic Value of ABO blood group combined with tumor markers for GC (training set)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" style=\"margin-right: calc(11%); width: 89%;\" width=\"652\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9.0154%;\" valign=\"top\" width=\"12.269938650306749%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTM\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.79%;\" valign=\"top\" width=\"11.963190184049079%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAUC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.5284%;\" valign=\"top\" width=\"15.797546012269938%\"\u003e\n \u003cp\u003e\u003cstrong\u003e95%CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.8255%;\" valign=\"top\" width=\"9.662576687116564%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTPR (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 9.8621%;\" valign=\"top\" width=\"9.815950920245399%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTNR (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.9872%;\" valign=\"top\" width=\"21.625766871165645%\"\u003e\n \u003cp\u003e\u003cstrong\u003eYouden index\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 13.8058%;\" valign=\"top\" width=\"8.282208588957054%\"\u003e\n \u003cp\u003e\u003cstrong\u003eZ\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 13.9528%;\" valign=\"top\" width=\"7.668711656441718%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9.0154%;\" valign=\"top\" width=\"12.288786482334869%\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.79%;\" valign=\"top\" width=\"11.981566820276498%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.5284%;\" valign=\"top\" width=\"15.821812596006144%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.8255%;\" valign=\"top\" width=\"9.67741935483871%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 9.8621%;\" valign=\"top\" width=\"13.978494623655914%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.9872%;\" valign=\"top\" width=\"15.360983102918587%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 13.8058%;\" valign=\"top\" width=\"8.90937019969278%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 13.9528%;\" valign=\"top\" width=\"11.981566820276498%\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9.0154%;\" valign=\"top\" width=\"12.288786482334869%\"\u003e\n \u003cp\u003e\u0026nbsp;CEA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.79%;\" valign=\"top\" width=\"11.981566820276498%\"\u003e\n \u003cp\u003e0.740\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.5284%;\" valign=\"top\" width=\"15.821812596006144%\"\u003e\n \u003cp\u003e0.720-0.759\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.8255%;\" valign=\"top\" width=\"9.67741935483871%\"\u003e\n \u003cp\u003e48.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 9.8621%;\" valign=\"top\" width=\"13.978494623655914%\"\u003e\n \u003cp\u003e98.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.9872%;\" valign=\"top\" width=\"15.360983102918587%\"\u003e\n \u003cp\u003e0.4651\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 13.8058%;\" valign=\"top\" width=\"8.90937019969278%\"\u003e\n \u003cp\u003e18.433\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 13.9528%;\" valign=\"top\" width=\"11.981566820276498%\"\u003e\n \u003cp\u003e＜0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9.0154%;\" valign=\"top\" width=\"12.288786482334869%\"\u003e\n \u003cp\u003e\u0026nbsp;CA199\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;CA125\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;AFP\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;CA724\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.79%;\" valign=\"top\" width=\"11.981566820276498%\"\u003e\n \u003cp\u003e0.601\u003c/p\u003e\n \u003cp\u003e0.762\u003c/p\u003e\n \u003cp\u003e0.677\u003c/p\u003e\n \u003cp\u003e0.742\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.5284%;\" valign=\"top\" width=\"15.821812596006144%\"\u003e\n \u003cp\u003e0.579-0.622\u003c/p\u003e\n \u003cp\u003e0.743-0.780\u003c/p\u003e\n \u003cp\u003e0.656-0.698\u003c/p\u003e\n \u003cp\u003e0.722-0.761\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.8255%;\" valign=\"top\" width=\"9.67741935483871%\"\u003e\n \u003cp\u003e35.09\u003c/p\u003e\n \u003cp\u003e45.23\u003c/p\u003e\n \u003cp\u003e31.54\u003c/p\u003e\n \u003cp\u003e42.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 9.8621%;\" valign=\"top\" width=\"13.978494623655914%\"\u003e\n \u003cp\u003e90.32\u003c/p\u003e\n \u003cp\u003e99.24\u003c/p\u003e\n \u003cp\u003e99.99\u003c/p\u003e\n \u003cp\u003e99.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.9872%;\" valign=\"top\" width=\"15.360983102918587%\"\u003e\n \u003cp\u003e0.2541\u003c/p\u003e\n \u003cp\u003e0.4470\u003c/p\u003e\n \u003cp\u003e0.3754\u003c/p\u003e\n \u003cp\u003e0.4157\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 13.8058%;\" valign=\"top\" width=\"8.90937019969278%\"\u003e\n \u003cp\u003e7.083\u003c/p\u003e\n \u003cp\u003e21.343\u003c/p\u003e\n \u003cp\u003e14.276\u003c/p\u003e\n \u003cp\u003e19.966\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 13.9528%;\" valign=\"top\" width=\"11.981566820276498%\"\u003e\n \u003cp\u003e＜0.0001\u003c/p\u003e\n \u003cp\u003e＜0.0001\u003c/p\u003e\n \u003cp\u003e＜0.0001\u003c/p\u003e\n \u003cp\u003e＜0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9.0154%;\" valign=\"top\" width=\"12.288786482334869%\"\u003e\n \u003cp\u003eB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.79%;\" valign=\"top\" width=\"11.981566820276498%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.5284%;\" valign=\"top\" width=\"15.821812596006144%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.8255%;\" valign=\"top\" width=\"9.67741935483871%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 9.8621%;\" valign=\"top\" width=\"13.978494623655914%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.9872%;\" valign=\"top\" width=\"15.360983102918587%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 13.8058%;\" valign=\"top\" width=\"8.90937019969278%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 13.9528%;\" valign=\"top\" width=\"11.981566820276498%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9.0154%;\" valign=\"top\" width=\"12.288786482334869%\"\u003e\n \u003cp\u003e\u0026nbsp;CEA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.79%;\" valign=\"top\" width=\"11.981566820276498%\"\u003e\n \u003cp\u003e0.847\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.5284%;\" valign=\"top\" width=\"15.821812596006144%\"\u003e\n \u003cp\u003e0.831-0.863\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.8255%;\" valign=\"top\" width=\"9.67741935483871%\"\u003e\n \u003cp\u003e77.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 9.8621%;\" valign=\"top\" width=\"13.978494623655914%\"\u003e\n \u003cp\u003e76.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.9872%;\" valign=\"top\" width=\"15.360983102918587%\"\u003e\n \u003cp\u003e0.5436\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 13.8058%;\" valign=\"top\" width=\"8.90937019969278%\"\u003e\n \u003cp\u003e36.781\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 13.9528%;\" valign=\"top\" width=\"11.981566820276498%\"\u003e\n \u003cp\u003e＜0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9.0154%;\" valign=\"top\" width=\"12.288786482334869%\"\u003e\n \u003cp\u003e\u0026nbsp;CA199\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.79%;\" valign=\"top\" width=\"11.981566820276498%\"\u003e\n \u003cp\u003e0.571\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.5284%;\" valign=\"top\" width=\"15.821812596006144%\"\u003e\n \u003cp\u003e0.549-0.593\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.8255%;\" valign=\"top\" width=\"9.67741935483871%\"\u003e\n \u003cp\u003e31.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 9.8621%;\" valign=\"top\" width=\"13.978494623655914%\"\u003e\n \u003cp\u003e92.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.9872%;\" valign=\"top\" width=\"15.360983102918587%\"\u003e\n \u003cp\u003e0.2374\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 13.8058%;\" valign=\"top\" width=\"8.90937019969278%\"\u003e\n \u003cp\u003e4.787\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 13.9528%;\" valign=\"top\" width=\"11.981566820276498%\"\u003e\n \u003cp\u003e＜0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 9.0154%;\" valign=\"top\" width=\"12.288786482334869%\"\u003e\n \u003cp\u003e\u0026nbsp;CA125\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;AFP\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;CA724\u003c/p\u003e\n \u003cp\u003eO\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;CEA\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;CA199\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;CA125\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;AFP\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;CA724\u003c/p\u003e\n \u003cp\u003eAB\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;CEA\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;CA199\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;CA125\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;AFP\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;CA724\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.79%;\" valign=\"top\" width=\"11.981566820276498%\"\u003e\n \u003cp\u003e0.747\u003c/p\u003e\n \u003cp\u003e0.664\u003c/p\u003e\n \u003cp\u003e0.728\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.777\u003c/p\u003e\n \u003cp\u003e0.611\u003c/p\u003e\n \u003cp\u003e0.749\u003c/p\u003e\n \u003cp\u003e0.667\u003c/p\u003e\n \u003cp\u003e0.748\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.830\u003c/p\u003e\n \u003cp\u003e0.616\u003c/p\u003e\n \u003cp\u003e0.779\u003c/p\u003e\n \u003cp\u003e0.682\u003c/p\u003e\n \u003cp\u003e0.725\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.5284%;\" valign=\"top\" width=\"15.821812596006144%\"\u003e\n \u003cp\u003e0.728-0.766\u003c/p\u003e\n \u003cp\u003e0.643-0.685\u003c/p\u003e\n \u003cp\u003e0.708-0.747\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.757-0.795\u003c/p\u003e\n \u003cp\u003e0.589-0.633\u003c/p\u003e\n \u003cp\u003e0.730-0.769\u003c/p\u003e\n \u003cp\u003e0.646-0.688\u003c/p\u003e\n \u003cp\u003e0.728-0.767\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.799-0.857\u003c/p\u003e\n \u003cp\u003e0.578-0.653\u003c/p\u003e\n \u003cp\u003e0.746-0.810\u003c/p\u003e\n \u003cp\u003e0.645-0.716\u003c/p\u003e\n \u003cp\u003e0.690-0.758\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.8255%;\" valign=\"top\" width=\"9.67741935483871%\"\u003e\n \u003cp\u003e47.98\u003c/p\u003e\n \u003cp\u003e30.82\u003c/p\u003e\n \u003cp\u003e43.56\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e59.38\u003c/p\u003e\n \u003cp\u003e40.06\u003c/p\u003e\n \u003cp\u003e44.68\u003c/p\u003e\n \u003cp\u003e34.03\u003c/p\u003e\n \u003cp\u003e46.36\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e79.68\u003c/p\u003e\n \u003cp\u003e32.67\u003c/p\u003e\n \u003cp\u003e71.71\u003c/p\u003e\n \u003cp\u003e36.25\u003c/p\u003e\n \u003cp\u003e55.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 9.8621%;\" valign=\"top\" width=\"13.978494623655914%\"\u003e\n \u003cp\u003e98.73\u003c/p\u003e\n \u003cp\u003e99.76\u003c/p\u003e\n \u003cp\u003e99.99\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e87.83\u003c/p\u003e\n \u003cp\u003e92.08\u003c/p\u003e\n \u003cp\u003e97.63\u003c/p\u003e\n \u003cp\u003e99.59\u003c/p\u003e\n \u003cp\u003e97.88\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e73.72\u003c/p\u003e\n \u003cp\u003e95.81\u003c/p\u003e\n \u003cp\u003e77.21\u003c/p\u003e\n \u003cp\u003e98.84\u003c/p\u003e\n \u003cp\u003e85.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.9872%;\" valign=\"top\" width=\"15.360983102918587%\"\u003e\n \u003cp\u003e0.4671\u003c/p\u003e\n \u003cp\u003e0.3058\u003c/p\u003e\n \u003cp\u003e0.4356\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.4721\u003c/p\u003e\n \u003cp\u003e0.3213\u003c/p\u003e\n \u003cp\u003e0.4231\u003c/p\u003e\n \u003cp\u003e0.3363\u003c/p\u003e\n \u003cp\u003e0.4423\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.5340\u003c/p\u003e\n \u003cp\u003e0.2848\u003c/p\u003e\n \u003cp\u003e0.4892\u003c/p\u003e\n \u003cp\u003e0.3509\u003c/p\u003e\n \u003cp\u003e0.4119\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 13.8058%;\" valign=\"top\" width=\"8.90937019969278%\"\u003e\n \u003cp\u003e19.100\u003c/p\u003e\n \u003cp\u003e12.76\u003c/p\u003e\n \u003cp\u003e17.802\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e21.969\u003c/p\u003e\n \u003cp\u003e7.283\u003c/p\u003e\n \u003cp\u003e18.572\u003c/p\u003e\n \u003cp\u003e12.695\u003c/p\u003e\n \u003cp\u003e19.361\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e18.195\u003c/p\u003e\n \u003cp\u003e4.562\u003c/p\u003e\n \u003cp\u003e12.824\u003c/p\u003e\n \u003cp\u003e8.000\u003c/p\u003e\n \u003cp\u003e9.978\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 13.9528%;\" valign=\"top\" width=\"11.981566820276498%\"\u003e\n \u003cp\u003e＜0.0001\u003c/p\u003e\n \u003cp\u003e＜0.0001\u003c/p\u003e\n \u003cp\u003e＜0.0001\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e＜0.0001\u003c/p\u003e\n \u003cp\u003e＜0.0001\u003c/p\u003e\n \u003cp\u003e＜0.0001\u003c/p\u003e\n \u003cp\u003e＜0.0001\u003c/p\u003e\n \u003cp\u003e＜0.0001\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e＜0.0001\u003c/p\u003e\n \u003cp\u003e＜0.0001\u003c/p\u003e\n \u003cp\u003e＜0.0001\u003c/p\u003e\n \u003cp\u003e＜0.0001\u003c/p\u003e\n \u003cp\u003e＜0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 7. Diagnostic Value of ABO blood group combined with tumor markers for GC (validation set)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"638\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12.5373%;\" valign=\"top\" width=\"13.77151799687011%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTM\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.7993%;\" valign=\"top\" width=\"10.7981220657277%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAUC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.9786%;\" valign=\"top\" width=\"14.710485133020343%\"\u003e\n \u003cp\u003e\u003cstrong\u003e95%CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.6828%;\" valign=\"top\" width=\"11.11111111111111%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTPR (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.8313%;\" valign=\"top\" width=\"10.328638497652582%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTNR (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.664%;\" valign=\"top\" width=\"17.683881064162755%\"\u003e\n \u003cp\u003e\u003cstrong\u003eYouden index\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 9.5024%;\" valign=\"top\" width=\"8.92018779342723%\"\u003e\n \u003cp\u003e\u003cstrong\u003eZ\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.1386%;\" valign=\"top\" width=\"11.11111111111111%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12.5373%;\" valign=\"top\" width=\"13.77151799687011%\"\u003e\n \u003cp\u003eA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.7993%;\" valign=\"top\" width=\"10.7981220657277%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.9786%;\" valign=\"top\" width=\"14.710485133020343%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.6828%;\" valign=\"top\" width=\"11.11111111111111%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.8313%;\" valign=\"top\" width=\"10.328638497652582%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.664%;\" valign=\"top\" width=\"17.683881064162755%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 9.5024%;\" valign=\"top\" width=\"9.23317683881064%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.1386%;\" valign=\"top\" width=\"12.363067292644757%\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12.5373%;\" valign=\"top\" width=\"13.77151799687011%\"\u003e\n \u003cp\u003eCEA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.7993%;\" valign=\"top\" width=\"10.7981220657277%\"\u003e\n \u003cp\u003e0.782\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.9786%;\" valign=\"top\" width=\"14.710485133020343%\"\u003e\n \u003cp\u003e0.753-0.809\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.6828%;\" valign=\"top\" width=\"11.11111111111111%\"\u003e\n \u003cp\u003e52.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.8313%;\" valign=\"top\" width=\"10.328638497652582%\"\u003e\n \u003cp\u003e99.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.664%;\" valign=\"top\" width=\"17.683881064162755%\"\u003e\n \u003cp\u003e0.5241\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 9.5024%;\" valign=\"top\" width=\"9.23317683881064%\"\u003e\n \u003cp\u003e15.568\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.1386%;\" valign=\"top\" width=\"12.363067292644757%\"\u003e\n \u003cp\u003e＜0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12.5373%;\" valign=\"top\" width=\"13.77151799687011%\"\u003e\n \u003cp\u003eCA199\u003c/p\u003e\n \u003cp\u003eCA125\u003c/p\u003e\n \u003cp\u003eAFP\u003c/p\u003e\n \u003cp\u003eCA724\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.7993%;\" valign=\"top\" width=\"10.7981220657277%\"\u003e\n \u003cp\u003e0.576\u003c/p\u003e\n \u003cp\u003e0.741\u003c/p\u003e\n \u003cp\u003e0.658\u003c/p\u003e\n \u003cp\u003e0.735\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.9786%;\" valign=\"top\" width=\"14.710485133020343%\"\u003e\n \u003cp\u003e0.542-0.609\u003c/p\u003e\n \u003cp\u003e0.711-0.770\u003c/p\u003e\n \u003cp\u003e0.626-0.689\u003c/p\u003e\n \u003cp\u003e0.705-0.764\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.6828%;\" valign=\"top\" width=\"11.11111111111111%\"\u003e\n \u003cp\u003e50.28\u003c/p\u003e\n \u003cp\u003e47.77\u003c/p\u003e\n \u003cp\u003e33.80\u003c/p\u003e\n \u003cp\u003e45.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.8313%;\" valign=\"top\" width=\"10.328638497652582%\"\u003e\n \u003cp\u003e73.32\u003c/p\u003e\n \u003cp\u003e94.61\u003c/p\u003e\n \u003cp\u003e99.81\u003c/p\u003e\n \u003cp\u003e98.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.664%;\" valign=\"top\" width=\"17.683881064162755%\"\u003e\n \u003cp\u003e0.2350\u003c/p\u003e\n \u003cp\u003e0.4237\u003c/p\u003e\n \u003cp\u003e0.3361\u003c/p\u003e\n \u003cp\u003e0.4465\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 9.5024%;\" valign=\"top\" width=\"9.23317683881064%\"\u003e\n \u003cp\u003e3.476\u003c/p\u003e\n \u003cp\u003e12.431\u003c/p\u003e\n \u003cp\u003e8.063\u003c/p\u003e\n \u003cp\u003e12.698\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.1386%;\" valign=\"top\" width=\"12.363067292644757%\"\u003e\n \u003cp\u003e＜0.0001\u003c/p\u003e\n \u003cp\u003e＜0.0001\u003c/p\u003e\n \u003cp\u003e＜0.0001\u003c/p\u003e\n \u003cp\u003e＜0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12.5373%;\" valign=\"top\" width=\"13.77151799687011%\"\u003e\n \u003cp\u003eB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.7993%;\" valign=\"top\" width=\"10.7981220657277%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.9786%;\" valign=\"top\" width=\"14.710485133020343%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.6828%;\" valign=\"top\" width=\"11.11111111111111%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.8313%;\" valign=\"top\" width=\"10.328638497652582%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.664%;\" valign=\"top\" width=\"17.683881064162755%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 9.5024%;\" valign=\"top\" width=\"9.23317683881064%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.1386%;\" valign=\"top\" width=\"12.363067292644757%\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12.5373%;\" valign=\"top\" width=\"13.77151799687011%\"\u003e\n \u003cp\u003eCEA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.7993%;\" valign=\"top\" width=\"10.7981220657277%\"\u003e\n \u003cp\u003e0.857\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.9786%;\" valign=\"top\" width=\"14.710485133020343%\"\u003e\n \u003cp\u003e0.832-0.880\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.6828%;\" valign=\"top\" width=\"11.11111111111111%\"\u003e\n \u003cp\u003e90.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.8313%;\" valign=\"top\" width=\"10.328638497652582%\"\u003e\n \u003cp\u003e67.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.664%;\" valign=\"top\" width=\"17.683881064162755%\"\u003e\n \u003cp\u003e0.5736\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 9.5024%;\" valign=\"top\" width=\"9.23317683881064%\"\u003e\n \u003cp\u003e26.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.1386%;\" valign=\"top\" width=\"12.363067292644757%\"\u003e\n \u003cp\u003e＜0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12.5373%;\" valign=\"top\" width=\"13.77151799687011%\"\u003e\n \u003cp\u003eCA199\u003c/p\u003e\n \u003cp\u003eCA125\u003c/p\u003e\n \u003cp\u003eAFP\u003c/p\u003e\n \u003cp\u003eCA724\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.7993%;\" valign=\"top\" width=\"10.7981220657277%\"\u003e\n \u003cp\u003e0.587\u003c/p\u003e\n \u003cp\u003e0.771\u003c/p\u003e\n \u003cp\u003e0.664\u003c/p\u003e\n \u003cp\u003e0.749\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.9786%;\" valign=\"top\" width=\"14.710485133020343%\"\u003e\n \u003cp\u003e0.553-0.621\u003c/p\u003e\n \u003cp\u003e0.741-0.799\u003c/p\u003e\n \u003cp\u003e0.631-0.696\u003c/p\u003e\n \u003cp\u003e0.718-0.778\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.6828%;\" valign=\"top\" width=\"11.11111111111111%\"\u003e\n \u003cp\u003e38.75\u003c/p\u003e\n \u003cp\u003e46.56\u003c/p\u003e\n \u003cp\u003e31.25\u003c/p\u003e\n \u003cp\u003e41.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.8313%;\" valign=\"top\" width=\"10.328638497652582%\"\u003e\n \u003cp\u003e85.90\u003c/p\u003e\n \u003cp\u003e99.81\u003c/p\u003e\n \u003cp\u003e97.52\u003c/p\u003e\n \u003cp\u003e99.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.664%;\" valign=\"top\" width=\"17.683881064162755%\"\u003e\n \u003cp\u003e0.2465\u003c/p\u003e\n \u003cp\u003e0.4637\u003c/p\u003e\n \u003cp\u003e0.2877\u003c/p\u003e\n \u003cp\u003e0.4067\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 9.5024%;\" valign=\"top\" width=\"9.23317683881064%\"\u003e\n \u003cp\u003e3.911\u003c/p\u003e\n \u003cp\u003e14.067\u003c/p\u003e\n \u003cp\u003e8.186\u003c/p\u003e\n \u003cp\u003e13.219\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.1386%;\" valign=\"top\" width=\"12.363067292644757%\"\u003e\n \u003cp\u003e＜0.0001\u003c/p\u003e\n \u003cp\u003e＜0.0001\u003c/p\u003e\n \u003cp\u003e＜0.0001\u003c/p\u003e\n \u003cp\u003e＜0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12.5373%;\" valign=\"top\" width=\"13.77151799687011%\"\u003e\n \u003cp\u003eO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.7993%;\" valign=\"top\" width=\"10.7981220657277%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.9786%;\" valign=\"top\" width=\"14.710485133020343%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.6828%;\" valign=\"top\" width=\"11.11111111111111%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.8313%;\" valign=\"top\" width=\"10.328638497652582%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.664%;\" valign=\"top\" width=\"17.683881064162755%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 9.5024%;\" valign=\"top\" width=\"9.23317683881064%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.1386%;\" valign=\"top\" width=\"12.363067292644757%\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12.5373%;\" valign=\"top\" width=\"13.77151799687011%\"\u003e\n \u003cp\u003eCEA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.7993%;\" valign=\"top\" width=\"10.7981220657277%\"\u003e\n \u003cp\u003e0.781\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.9786%;\" valign=\"top\" width=\"14.710485133020343%\"\u003e\n \u003cp\u003e0.751-0.808\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.6828%;\" valign=\"top\" width=\"11.11111111111111%\"\u003e\n \u003cp\u003e69.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.8313%;\" valign=\"top\" width=\"10.328638497652582%\"\u003e\n \u003cp\u003e77.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.664%;\" valign=\"top\" width=\"17.683881064162755%\"\u003e\n \u003cp\u003e0.4705\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 9.5024%;\" valign=\"top\" width=\"9.23317683881064%\"\u003e\n \u003cp\u003e14.858\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.1386%;\" valign=\"top\" width=\"12.363067292644757%\"\u003e\n \u003cp\u003e＜0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12.5373%;\" valign=\"top\" width=\"13.77151799687011%\"\u003e\n \u003cp\u003eCA199\u003c/p\u003e\n \u003cp\u003eCA125\u003c/p\u003e\n \u003cp\u003eAFP\u003c/p\u003e\n \u003cp\u003eCA724\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.7993%;\" valign=\"top\" width=\"10.7981220657277%\"\u003e\n \u003cp\u003e0.592\u003c/p\u003e\n \u003cp\u003e0.750\u003c/p\u003e\n \u003cp\u003e0.695\u003c/p\u003e\n \u003cp\u003e0.696\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.9786%;\" valign=\"top\" width=\"14.710485133020343%\"\u003e\n \u003cp\u003e0.558-0.626\u003c/p\u003e\n \u003cp\u003e0.719-0.779\u003c/p\u003e\n \u003cp\u003e0.662-0.726\u003c/p\u003e\n \u003cp\u003e0.663-0.727\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.6828%;\" valign=\"top\" width=\"11.11111111111111%\"\u003e\n \u003cp\u003e35.76\u003c/p\u003e\n \u003cp\u003e57.62\u003c/p\u003e\n \u003cp\u003e39.40\u003c/p\u003e\n \u003cp\u003e43.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.8313%;\" valign=\"top\" width=\"10.328638497652582%\"\u003e\n \u003cp\u003e86.90\u003c/p\u003e\n \u003cp\u003e83.82\u003c/p\u003e\n \u003cp\u003e94.99\u003c/p\u003e\n \u003cp\u003e98.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.664%;\" valign=\"top\" width=\"17.683881064162755%\"\u003e\n \u003cp\u003e0.2266\u003c/p\u003e\n \u003cp\u003e0.4143\u003c/p\u003e\n \u003cp\u003e0.3439\u003c/p\u003e\n \u003cp\u003e0.4189\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 9.5024%;\" valign=\"top\" width=\"9.23317683881064%\"\u003e\n \u003cp\u003e4.031\u003c/p\u003e\n \u003cp\u003e12.414\u003c/p\u003e\n \u003cp\u003e9.754\u003c/p\u003e\n \u003cp\u003e8.938\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.1386%;\" valign=\"top\" width=\"12.363067292644757%\"\u003e\n \u003cp\u003e＜0.0001\u003c/p\u003e\n \u003cp\u003e＜0.0001\u003c/p\u003e\n \u003cp\u003e＜0.0001\u003c/p\u003e\n \u003cp\u003e＜0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12.5373%;\" valign=\"top\" width=\"13.77151799687011%\"\u003e\n \u003cp\u003eAB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.7993%;\" valign=\"top\" width=\"10.7981220657277%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.9786%;\" valign=\"top\" width=\"14.710485133020343%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.6828%;\" valign=\"top\" width=\"11.11111111111111%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.8313%;\" valign=\"top\" width=\"10.328638497652582%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.664%;\" valign=\"top\" width=\"17.683881064162755%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 9.5024%;\" valign=\"top\" width=\"9.23317683881064%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.1386%;\" valign=\"top\" width=\"12.363067292644757%\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12.5373%;\" valign=\"top\" width=\"13.77151799687011%\"\u003e\n \u003cp\u003eCEA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.7993%;\" valign=\"top\" width=\"10.7981220657277%\"\u003e\n \u003cp\u003e0.852\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.9786%;\" valign=\"top\" width=\"14.710485133020343%\"\u003e\n \u003cp\u003e0.805-0.891\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.6828%;\" valign=\"top\" width=\"11.11111111111111%\"\u003e\n \u003cp\u003e74.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.8313%;\" valign=\"top\" width=\"10.328638497652582%\"\u003e\n \u003cp\u003e85.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.664%;\" valign=\"top\" width=\"17.683881064162755%\"\u003e\n \u003cp\u003e0.5970\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 9.5024%;\" valign=\"top\" width=\"9.23317683881064%\"\u003e\n \u003cp\u003e13.831\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.1386%;\" valign=\"top\" width=\"12.363067292644757%\"\u003e\n \u003cp\u003e＜0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12.5373%;\" valign=\"top\" width=\"13.77151799687011%\"\u003e\n \u003cp\u003eCA199\u003c/p\u003e\n \u003cp\u003eCA125\u003c/p\u003e\n \u003cp\u003eAFP\u003c/p\u003e\n \u003cp\u003eCA724\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.7993%;\" valign=\"top\" width=\"10.7981220657277%\"\u003e\n \u003cp\u003e0.612\u003c/p\u003e\n \u003cp\u003e0.696\u003c/p\u003e\n \u003cp\u003e0.695\u003c/p\u003e\n \u003cp\u003e0.711\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.9786%;\" valign=\"top\" width=\"14.710485133020343%\"\u003e\n \u003cp\u003e0.553-0.669\u003c/p\u003e\n \u003cp\u003e0.639-0.748\u003c/p\u003e\n \u003cp\u003e0.638-0.748\u003c/p\u003e\n \u003cp\u003e0.655-0.763\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.6828%;\" valign=\"top\" width=\"11.11111111111111%\"\u003e\n \u003cp\u003e46.61\u003c/p\u003e\n \u003cp\u003e44.92\u003c/p\u003e\n \u003cp\u003e33.90\u003c/p\u003e\n \u003cp\u003e46.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.8313%;\" valign=\"top\" width=\"10.328638497652582%\"\u003e\n \u003cp\u003e86.90\u003c/p\u003e\n \u003cp\u003e97.62\u003c/p\u003e\n \u003cp\u003e99.99\u003c/p\u003e\n \u003cp\u003e94.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.664%;\" valign=\"top\" width=\"17.683881064162755%\"\u003e\n \u003cp\u003e0.3351\u003c/p\u003e\n \u003cp\u003e0.4253\u003c/p\u003e\n \u003cp\u003e0.3390\u003c/p\u003e\n \u003cp\u003e0.4066\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 9.5024%;\" valign=\"top\" width=\"9.23317683881064%\"\u003e\n \u003cp\u003e2.955\u003c/p\u003e\n \u003cp\u003e5.391\u003c/p\u003e\n \u003cp\u003e5.926\u003c/p\u003e\n \u003cp\u003e6.274\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17.1386%;\" valign=\"top\" width=\"12.363067292644757%\"\u003e\n \u003cp\u003e＜0.0001\u003c/p\u003e\n \u003cp\u003e＜0.0001\u003c/p\u003e\n \u003cp\u003e＜0.0001\u003c/p\u003e\n \u003cp\u003e＜0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eTumor marker is a kind of substance synthesized and released by tumor itself. In the process of tumor occurrence and development, it is also accompanied by the modified expression of blood group antigen in tumor cells. So far, a large number of studies have explored the value of tumor markers on the incidence of gastric cancer [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], clinicopathological features and prognosis[\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. However, there is no study on the diagnostic value of ABO blood group combined with tumor markers for gastric cancer. This study found that type B blood and AB blood can improve the diagnostic value of CEA in patients with GC. Combined detection of tumor markers can improve the sensitivity and specificity of GC diagnosis. Blood type B and AB can improve the diagnostic value of combined detection of tumor markers for gastric cancer. Furthermore, joint five kinds of tumor markers detection of blood type B blood AUC value was higher than 5 kinds of tumor markers detection, and statistically difference. However, AB blood there was no statistically significant difference, but the p value in the inspection level threshold.\u003c/p\u003e \u003cp\u003eThe sensitivity of single tumor markers in detecting gastric cancer is insufficient. Studies have explored the diagnostic value of CEA, CA724, CA199 and CA125 for gastric cancer, and the results suggest that the sensitivity of these tumor markers in diagnosing gastric cancer is between 20% and 40%, and the sensitivity of combining these four tumor markers is only 60.9%[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. In this study, the sensitivity of the five tumor markers in the diagnosis of gastric cancer ranged from 32\u0026ndash;67%, and the sensitivity of the combined detection increased to 91.7%. It is somewhat different from previous reports, which may be because this study only included gastric cancer patients and healthy people, and did not include population with gastric precancerous lesions, leading to increased sensitivity.\u003c/p\u003e \u003cp\u003eIt is well known that the occurrence and development of gastric cancer are related to genetic factors, environmental factors and Helicobacter pylori infection. Blood group is one of the most stable genetic factors, among which ABO blood group is by far the most important blood group system[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. This study found that B type blood combined with tumor markers can improve the diagnostic value of gastric cancer. At present, there is no study on the combined detection of blood group and tumor markers for the diagnosis of gastric cancer, but some studies[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] have explored the correlation between ABO blood group and clinicopathological characteristics of gastric cancer, and proposed that the proportion of elevated CEA in blood group B and AB was higher than that in other blood groups, which could indirectly explain the results of this study. In addition, Qiu et al.[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] found that in patients with gastric adenocarcinoma, the proportion of increased CEA in blood group A was significantly higher than that in other blood groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.003), and the proportion of increased CEA and CA199 in blood group AB was significantly lower than that in other blood groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.005) for untreated gastric cancer patients. In this study, the combination of blood group A and tumor markers did not improve the diagnostic value of gastric cancer. AB blood type can improve the diagnostic value of CEA and CA199 for gastric cancer, but the difference is not statistically significant.\u003c/p\u003e \u003cp\u003eThe main strength of our study is that the sample size is large and the subjects are divided into training set and validation set by 7:3 for double validation. In addition, our current study has several limitations. Firstly, due to the limitation of conditions, ABO blood group and tumor marker level information of patients with GC precancerous diseases could not be obtained, and patients with GC precancerous diseases were not included, so the objectivity of the results was slightly weak. Secondly, this study is a retrospective study, and prospective studies are needed to further verify the diagnostic value of ABO blood group combined with tumor markers for GC.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn summary, our results suggested that ABO blood group combined with tumor markers as screening indicators for GC can improve the diagnostic value of GC patients. Among them, type B and AB blood combined with tumor markers have the most significant value in the diagnosis of GC.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eand consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis retrospective study was reviewed by\u0026nbsp;the Ethics Committee of the First Affiliated Hospital of Air Force Medical University\u0026nbsp;and approval was obtained.\u0026nbsp;All methods were carried out in accordance with relevant guidelines and regulations. All experimental protocols were approved by the\u0026nbsp;Ethics Committee of the First Affiliated Hospital of Air Force Medical University. Due to the retrospective nature of the study, the informed consent was waived by the Ethics Committee of the First Affiliated Hospital of Air Force Medical University.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and analyzed during the current study are available from the corresponding authors on reasonable request.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by grants from the National Natural Science Foundation of China (No. 82170560 to YQS).\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eYQS, YHL, SSC, WNS, XDQ and SBL contributed to the design of the study, interpretation of the data, and critical revision of the manuscript. YHL contributed to the analysis and interpretation of the data and drafted the manuscript. All authors approved the final version of the manuscript for submission.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank the individuals who have contributed to the current study in various capacities.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, Bray F: \u003cstrong\u003eGlobal Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries\u003c/strong\u003e. \u003cem\u003eCA: a cancer journal for clinicians\u003c/em\u003e 2021, \u003cstrong\u003e71\u003c/strong\u003e(3):209-249. doi: 10.3322/caac.21660.\u003c/li\u003e\n\u003cli\u003eCao W, Chen H, Yu Y, Li N, Chen W: \u003cstrong\u003eChanging profiles of cancer burden worldwide and in China: a secondary analysis of the global cancer statistics 2020\u003c/strong\u003e. \u003cem\u003eCHINESE MED J-PEKING\u003c/em\u003e 2021, \u003cstrong\u003e134\u003c/strong\u003e(7):783-791. doi: 10.1097/CM9.0000000000001474.\u003c/li\u003e\n\u003cli\u003eKatai H, Ishikawa T, Akazawa K, Isobe Y, Miyashiro I, Oda I, Tsujitani S, Ono H, Tanabe S, Fukagawa T\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eFive-year survival analysis of surgically resected gastric cancer cases in Japan: a retrospective analysis of more than 100,000 patients from the nationwide registry of the Japanese Gastric Cancer Association (2001\u003c/strong\u003e\u003cstrong\u003e\u0026ndash;\u003c/strong\u003e\u003cstrong\u003e2007)\u003c/strong\u003e. \u003cem\u003eGASTRIC CANCER\u003c/em\u003e 2018, \u003cstrong\u003e21\u003c/strong\u003e(1):144-154. doi: 10.1007/s10120-017-0716-7.\u003c/li\u003e\n\u003cli\u003eDu Y-C, Cai Q-C, Liao Z, Fang J, Zhu C-P: Chinese expert consensus on screening procedures for early gastric cancer (draft,2017, Shanghai)\u003cstrong\u003e.\u003c/strong\u003e \u003cem\u003eCHINESE JOURNAL OF DIGESTION \u003c/em\u003e 2018, \u003cstrong\u003e38\u003c/strong\u003e(02):87-92. (in Chinese).\u003c/li\u003e\n\u003cli\u003eYang A, Liu J, Lei H, Zhang Q, Zhao L, Yang G: \u003cstrong\u003eCA72-4 combined with CEA, CA125 and CAl9-9 improves the sensitivity for the early diagnosis of gastric cancer\u003c/strong\u003e. \u003cem\u003eCLIN CHIM ACTA\u003c/em\u003e 2014, \u003cstrong\u003e437\u003c/strong\u003e:183-186. doi: 10.1016/j.cca.2014.07.034.\u003c/li\u003e\n\u003cli\u003eAIRD I, BENTALL HH, ROBERTS JA: \u003cstrong\u003eA relationship between cancer of stomach and the ABO blood groups\u003c/strong\u003e. \u003cem\u003eBr Med J\u003c/em\u003e 1953, \u003cstrong\u003e1\u003c/strong\u003e(4814):799-801. doi: 10.1136/bmj.1.4814.799.\u003c/li\u003e\n\u003cli\u003eQiu M, Zhang D, Ruan D, Luo H, Wang Z, Zhou Z, Wang F, Li Y, Xu R: \u003cstrong\u003eA relationship between ABO blood groups and clinicopathologic characteristics of patients with gastric adenocarcinoma in China\u003c/strong\u003e. \u003cem\u003eMED ONCOL\u003c/em\u003e 2011, \u003cstrong\u003e28\u003c/strong\u003e(S1):268-273. doi: 10.1007/s12032-010-9735-5.\u003c/li\u003e\n\u003cli\u003eSong H, Shin M, Kim HN, Piao J, Choi J, Hwang J, Park Y, Ryang D, Cho D, Kweon S: \u003cstrong\u003eSex-specific differences in the association between ABO genotype and gastric cancer risk in a Korean population\u003c/strong\u003e. \u003cem\u003eGASTRIC CANCER\u003c/em\u003e 2013, \u003cstrong\u003e16\u003c/strong\u003e(2):254-260. doi: 10.1007/s10120-012-0176-z.\u003c/li\u003e\n\u003cli\u003eHuang JY, Wang R, Gao Y, Yuan J: \u003cstrong\u003eABO blood type and the risk of cancer \u003c/strong\u003e\u003cstrong\u003e\u0026ndash;\u003c/strong\u003e\u003cstrong\u003e Findings from the Shanghai Cohort Study\u003c/strong\u003e. \u003cem\u003ePLOS ONE\u003c/em\u003e 2017, \u003cstrong\u003e12\u003c/strong\u003e(9):e184295. doi: 10.1371/journal.pone.0184295.\u003c/li\u003e\n\u003cli\u003eMao Y, Yang W, Qi Q, Yu F, Wang T, Zhang H, Dai J, Ma H, Hu Z, Shen H\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eBlood groups A and AB are associated with increased gastric cancer risk: evidence from a large genetic study and systematic review\u003c/strong\u003e. \u003cem\u003eBMC CANCER\u003c/em\u003e 2019, \u003cstrong\u003e19\u003c/strong\u003e(1):164. doi: 10.1186/s12885-019-5355-4.\u003c/li\u003e\n\u003cli\u003eSun X, Ai L, Feng Y: \u003cstrong\u003eThe Value of ABO Blood Group and Complete Blood Count for the Prognosis Analysis of Gastric Cancer Patients\u003c/strong\u003e. 2020, \u003cstrong\u003eVolume 13\u003c/strong\u003e:4627-4633. doi: 10.2147/OTT.S248065.\u003c/li\u003e\n\u003cli\u003eWang Z, Liu L, Ji J, Zhang J, Yan M, Zhang J, Liu B, Zhu Z, Yu Y: \u003cstrong\u003eABO Blood Group System and Gastric Cancer: A Case-Control Study and Meta-Analysis\u003c/strong\u003e. \u003cem\u003eINT J MOL SCI\u003c/em\u003e 2012, \u003cstrong\u003e13\u003c/strong\u003e(12):13308-13321. doi: 10.3390/ijms131013308.\u003c/li\u003e\n\u003cli\u003eChen Y, Hu N, Liao L, Yu K, Shu X, Zheng W, Yuan J, Koh W, Qiao Y, Fan J\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eABO genotypes and the risk of esophageal and gastric cancers\u003c/strong\u003e. \u003cem\u003eBMC CANCER\u003c/em\u003e 2021, \u003cstrong\u003e21\u003c/strong\u003e(1). doi: 10.1186/s12885-021-08334-1.\u003c/li\u003e\n\u003cli\u003eChen C, Chen Q, Zhao Q, Liu M, Guo J: \u003cstrong\u003eValue of Combined Detection of Serum CEA, CA72-4, CA19-9, CA15-3 and CA12-5 in the Diagnosis of Gastric Cancer\u003c/strong\u003e. \u003cem\u003eANN CLIN LAB SCI\u003c/em\u003e 2017, \u003cstrong\u003e47\u003c/strong\u003e(3):260-263.\u003c/li\u003e\n\u003cli\u003eStorry JR, Olsson ML: \u003cstrong\u003eThe ABO blood group system revisited: a review and update.\u003c/strong\u003e \u003cem\u003eImmunohematology\u003c/em\u003e 2009, \u003cstrong\u003e25\u003c/strong\u003e(2):102-109.\u003c/li\u003e\n\u003cli\u003eTan J: To study the correlation between ABO blood group and clinical characteristics and prognosis of gastric cancer patients. Yan \u0026apos;an University, 2020. (in Chinese).\u003c/li\u003e\n\u003cli\u003eXu X-L, Wang R-F, Yuan J-S, Song W-Q: Correlation analysis between gastric cancer and ABO blood group. \u003cem\u003eChongqing Medicine\u003c/em\u003e. 2020, \u003cstrong\u003e49\u003c/strong\u003e(08):1307-1310. (in Chinese).\u003c/li\u003e\n\u003cli\u003eQiu M, Zhang D, Ruan D, Luo H, Wang Z, Zhou Z, Wang F, Li Y, Xu R: \u003cstrong\u003eA relationship between ABO blood groups and clinicopathologic characteristics of patients with gastric adenocarcinoma in China\u003c/strong\u003e. \u003cem\u003eMedical oncology (Northwood, London, England)\u003c/em\u003e 2010, \u003cstrong\u003e28\u003c/strong\u003e(Suppl 1):268-273. doi: 10.1007/s12032-010-9735-5.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Gastric cancer, Tumor markers, ABO blood group, Combined diagnosis, Receiver operating curve","lastPublishedDoi":"10.21203/rs.3.rs-2192622/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2192622/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eBlood type is related to the occurrence and development of gastric cancer. The aim of this study is to explore the value of combined detection of ABO blood group and tumor markers in the diagnosis of gastric cancer.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA total of 3650 gastric cancer patients treated in our center from January 2015 to December 2019, and 5822 controls were recruited, and divided into training set and validation set according to 7:3. The clinicopathological characteristics were recorded. Receiver operating characteristic curve (ROC curve) was used to evaluate the diagnostic value of tumor markers and their combined blood type for gastric cancer. The results were validated using another group of people (validation group).\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eIn both the training set and the validation set, the levels of tumor markers in gastric cancer patients were higher than those in the healthy control group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The distribution of blood group in gastric cancer group was: A\u0026thinsp;\u0026gt;\u0026thinsp;B\u0026thinsp;\u0026gt;\u0026thinsp;O\u0026thinsp;\u0026gt;\u0026thinsp;AB, while that in healthy control group was: B\u0026thinsp;\u0026gt;\u0026thinsp;O\u0026thinsp;\u0026gt;\u0026thinsp;A\u0026thinsp;\u0026gt;\u0026thinsp;AB. Type B blood (AUC\u0026thinsp;=\u0026thinsp;0.850,95%CI 0.837\u0026ndash;0.863, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0006) and type AB blood (AUC\u0026thinsp;=\u0026thinsp;0.837,95%CI 0.812\u0026ndash;0.860, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0439) could improve the diagnostic value of CEA in gastric cancer.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThe detection of blood group combined with tumor markers can improve the sensitivity and specificity for the diagnosis of gastric cancer, which has a high reference value for the diagnosis of gastric cancer patients, and is worthy of further clinical study.\u003c/p\u003e","manuscriptTitle":"Diagnostic Value of ABO Blood Group Combined with Tumor Markers in Gastric Cancer","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-11-04 14:16:42","doi":"10.21203/rs.3.rs-2192622/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6669034a-1798-4ba5-9311-e01bd9538f89","owner":[],"postedDate":"November 4th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2023-03-27T13:29:21+00:00","versionOfRecord":[],"versionCreatedAt":"2022-11-04 14:16:42","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-2192622","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2192622","identity":"rs-2192622","version":["v1"]},"buildId":"cBFmMYwuxLRRLfASyISRj","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}