Application of chronic inflammation comprehensive index or 3C score in prognosis prediction system of II-III stage colorectal cancer patient

Abstract

The invention provides application of a chronic inflammation comprehensive index or a 3C score in a prognosis prediction system of a II-III stage colorectal cancer patient, and belongs to the technical field of biomedicine. The method comprises the following steps: firstly, acquiring blood sample data of II-III stage colorectal cancer patients; then, according to the measured blood marker content, a chronic inflammation comprehensive index (CII) is calculated based on patient prognosis. And finally, predicting the recurrence-free lifetime and the total lifetime of the patient in combination with the CII value and the tumor position subgroup. In addition, the invention further provides an alternative scheme, namely, CII is replaced with 3C score, and the prognosis prediction accuracy of the colorectal cancer patient is further improved by measuring the content of carcino-embryonic antigen and carbohydrate chain antigen 19-9 in the body of the patient and CII and calculating the 3C score. The method disclosed by the invention has relatively high prediction accuracy and is expected to improve the prognosis of II-III stage colorectal cancer patients.

Description

Technical Field

[0001] The present invention relates to the field of biomedical technology, and in particular to the application of a chronic inflammation comprehensive index or a 3C score in a prognosis prediction system for patients with stage II-III colorectal cancer. Background Art

[0002] Colorectal cancer (CRC) is a highly heterogeneous disease, and its development is affected by a variety of complex factors, including chronic inflammation, intestinal flora imbalance, and epigenetic modification. Among them, the location of the primary tumor has attracted much attention in recent years as an important parameter for predicting the survival prognosis of CRC patients. Although the traditional view is that the survival rate of right-sided tumors is usually lower than that of left-sided tumors, this conclusion is not consistent in different studies and is controversial.

[0003] It is worth noting that a large number of studies in recent years have revealed that a more detailed classification of the primary site of the tumor (rather than a simple two-stage classification based on the splenic flexure) can more accurately describe the prognostic information and molecular characteristics of CRC. These findings strongly suggest that the method of simply dividing the colon into two major segments, the proximal and distal, is no longer sufficient to meet the current needs for accurate diagnosis and treatment of CRC.

[0004] Furthermore, there is an inextricable link between chronic inflammation and colorectal cancer. Cancer-related inflammation not only weakens the efficacy of chemotherapy, but also promotes CRC progression and metastasis, becoming an important reference indicator for evaluating CRC prognosis. Previous studies have confirmed that chronic inflammation at the primary tumor site shows significant heterogeneity. Specifically, the level of chronic inflammation in the right colon is significantly higher than that in the left colon, which may explain to some extent why the prognosis of patients with right colon CRC is often poor.

[0005] However, although this finding provides us with valuable clues, there is still a lack of research on how chronic inflammatory heterogeneity based on detailed tumor location specifically affects patient prognosis, and related reports are relatively scarce. Summary of the invention

[0006] The purpose of the present invention is to provide an application of a chronic inflammation comprehensive index or 3C score in a prognosis prediction system for patients with stage II-III colorectal cancer. It is not intended for the diagnosis and treatment of the disease, but provides a holistic perspective to illustrate changes in patient prognosis based on specific tumor locations and chronic inflammatory states.

[0007] To achieve the above objectives, the present invention provides the application of a chronic inflammation comprehensive index or a 3C score in a prognosis prediction system for patients with stage II-III colorectal cancer.

[0008] Among them, the prognosis prediction system for patients with stage II-III colorectal cancer is composed of a chronic inflammation comprehensive index (CII) calculation module and a primary tumor location information module, or a 3C score calculation module and a primary tumor location information module.

[0009] The primary tumor location information included rectum, distal colon, transverse colon, and proximal colon.

[0010] Preferably, the calculation formula of the chronic inflammation comprehensive index is as follows:

[0011] CII=2.816×NFPS+0.659×MFAS+2.180×MFPS+1.538×NFAR;

[0012] Among them, CII represents the comprehensive chronic inflammation index; NFPS represents the scores of neutrophils and the ratio of fibrinogen to prealbumin; MFAS represents the scores of monocytes and the ratio of fibrinogen to albumin; MFPS represents the scores of monocytes and the ratio of fibrinogen to prealbumin; NFAR represents the ratio of the product of neutrophils and fibrinogen to albumin.

[0013] Preferably, the 3C score calculation formula is as follows:

[0014] 3C=3.646×CII+1.455×CEA+1.673×CA19-9;

[0015] Among them, 3C represents 3C score; CEA represents the content of carcinoembryonic antigen in the patient's body; CA19-9 represents the content of sugar chain antigen 19-9 in the patient's body.

[0016] Therefore, the present invention adopts the above-mentioned chronic inflammation comprehensive index or 3C score in the prognosis prediction system for patients with stage II-III colorectal cancer, and the beneficial technical effects are as follows:

[0017] (1) Innovative integration of biomarkers and tumor location: This method combines the chronic inflammation index (CII) with the location of the primary tumor for the first time, providing a comprehensive prognostic assessment system for patients with stage II-III colorectal cancer. This integration improves the accuracy of prediction.

[0018] (2) High-precision prediction of prognosis: CII, as an independent prognostic biomarker, shows high reliability. Patients with higher CII values ​​at different primary tumor locations all show poor prognosis, which verifies the universal applicability of CII in different situations. Through CII assessment, doctors can more accurately judge the patient's survival outcome and provide patients with more accurate prognostic information.

[0019] (3) Development of a new combination index 3C score: In order to further improve the accuracy of prognosis prediction, the present invention also proposes a 3C scoring system. This method integrates three biomarkers, CII, carcinoembryonic antigen (CEA) and carbohydrate antigen 19-9 (CA19-9), and achieves a more accurate prediction of patient prognosis by comprehensively evaluating multiple indicators.

[0020] (4) Clinical validation and support: This method has been validated by large-scale clinical data, demonstrating its effectiveness in predicting the prognosis of patients with stage II-III colorectal cancer. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 Forest plots and time-dependent ROC curves were used to analyze the prognostic value of CEA, CA19-9 and 12 novel inflammatory biomarkers in the discovery cohort and validation cohort populations. Figure 1 (A) in the figure is the recurrence-free survival of the discovery cohort; Figure 1 (B) in the middle is the overall survival of the discovery cohort; Figure 1 (C) in the middle is the recurrence-free survival of the validation cohort; Figure 1 (D) in the figure is the overall survival of the validation cohort; Figure 1 (E) is the time-dependent ROC curve of the above indicators for judging the recurrence-free survival of the total population; Figure 1 (F) in the figure is the time-dependent ROC curve of the above indicators for judging the overall survival of the total population;

[0022] Figure 2 The prognostic value of CII in predicting patients with stage II-III colorectal cancer was analyzed. Figure 2 (A) is the Kaplan-Meier curve analysis of recurrence-free survival in the discovery cohort; Figure 2 (B) is the Kaplan-Meier curve analysis of overall survival of the discovery cohort; Figure 2 (C) is the Kaplan-Meier curve analysis of recurrence-free survival in the validation cohort; Figure 2 (D) in the figure is the Kaplan-Meier curve analysis of the overall survival of the validation cohort; Figure 2 (E) in the figure is a restricted cubic bar graph of CII predicting recurrence-free survival in the overall population; Figure 2 (F) in the figure is a restricted cubic bar graph of CII predicting overall survival in the general population; Figure 2 (G) in the figure shows the time-dependent ROC curve for CII predicting recurrence-free survival in the overall population; Figure 2 (H) in the figure is the time-dependent ROC curve for the prediction of overall survival by CII in the general population;

[0023] Figure 3The relationship between CII and primary tumor location and clinical parameters. Figure 3 (A), (B), and (C) are the relationships between CII and tumor invasion depth, size, and cell differentiation, respectively; Figure 3 (D) and (E) are comparisons of the mean CII and high CII ratio distribution in eight primary tumor sites; Figure 3 (F) and (G) are comparisons of the mean CII value and high CII ratio distribution in the four newly classified tumor primary sites; Figure 3 (H) and (I) in the figure are the changes in recurrence rate and mortality rate of the four newly classified tumor primary sites;

[0024] Figure 4 This is a prognostic analysis of patients with CII and four new tumor primary sites. Figure 4 (A), (C), (E), and (G) are Kaplan-Meier curve analyses of CII predicting recurrence-free survival in patients with rectum, distal colon, transverse colon, and proximal colon, respectively; Figure 4 (B), (D), (F), and (H) are Kaplan-Meier curve analyses of CII predicting overall survival in patients with rectum, distal colon, transverse colon, and proximal colon, respectively; Figure 4 (I) in the figure is a comparison of the recurrence rates between patients with high and low CII in the rectum, distal colon, transverse colon, and proximal colon; Figure 4 (J) in the middle shows the comparison of mortality between patients with high and low CII in the rectum, distal colon, transverse colon, and proximal colon;

[0025] Figure 5 This is an analysis of the relationship between 3C score and the prognosis of the general population of patients. Figure 5 (A) is the Kaplan-Meier curve analysis of 3C score and patients' recurrence-free survival; Figure 5 (B) is the Kaplan-Meier curve analysis of 3C score and overall survival of patients; Figure 5 (C) is a comparative analysis of the area under the curve of 3C, CII, CEA and CA19-9 in predicting patients' recurrence-free survival; Figure 5 (D) is a comparative analysis of the area under the curve of 3C, CII, CEA and CA19-9 in predicting the overall survival of patients; Figure 5 (E) is the time-dependent ROC curve analysis of 3C in predicting the recurrence-free survival of patients at 12, 24, and 36 months; Figure 5 (F) is the time-dependent ROC curve analysis of 3C in predicting patients' 12-, 24-, and 36-month overall survival. DETAILED DESCRIPTION

[0026] The technical solution of the present invention is further described below through the accompanying drawings and embodiments.

[0027] Unless otherwise defined, technical or scientific terms used in the present invention shall have the common meanings understood by one having ordinary skills in the field to which the present invention belongs.

[0028] Embodiment 1

[0029] In this example, the data source is: 1413 patients with stage II-III CRC who visited a hospital between June 2011 and February 2021. The patients were divided into two cohorts: a discovery cohort diagnosed before 2017 and a validation cohort diagnosed after 2017. Patients were included according to specific inclusion and exclusion criteria. Inclusion criteria are: 1) Patients with clinical and pathological diagnosis of stage II-III colorectal cancer according to the "Guidelines for the Diagnosis and Treatment of Colorectal Cancer in China"; 2) Patients undergoing radical resection. Exclusion criteria are: 1) Patients with concurrent malignant tumors, blood diseases, autoimmune diseases, benign chronic inflammatory bowel disease, or recent infection or injury; 2) Patients under 18 years of age; 3) Patients with non-first clinical diagnosis or previous clinical intervention before diagnosis. This study has been approved by the ethics committee of the participating hospital.

[0030] The clinical pathological characteristic parameters of the included patients included gender, age, smoking and drinking status, diabetes, hypertension, cell differentiation, tumor size, tumor invasion depth, lymph node involvement, distant metastasis, primary tumor location, and clinical treatment methods.

[0031] 5 mL of peripheral blood was collected from patients 1 week before radical surgical resection and tested and analyzed by clinical laboratories. The inter-batch and intra-batch coefficients of variation of the above indicators were kept below 10%. Based on the test results, 12 new inflammatory biomarkers were constructed using the corresponding calculation formulas: NFAR, NFPR, MFAR, MFPR, PFAR, PFPR, NFAS, NFPS, MFAS, MFPS, PFAS and PFPS. The last 6 of them are scoring indicators, with scores of 0, 1 or 2 points respectively. The details are shown in Table 1.

[0032] Table 1 Definitions, cutoff values ​​and scoring criteria of 12 novel inflammatory biomarkers

[0033]

[0034]

[0035] Among them, Neu, neutrophil count; Mon, monocyte count; PLT, platelet count; Alb, albumin; pAlb, prealbumin; Fib, fibrinogen; FAR, fibrinogen to albumin ratio; FPR, fibrinogen to prealbumin ratio; NFAR, ratio of neutrophil to fibrinogen product to albumin; NFAS, score of neutrophil and fibrinogen to albumin ratio; NFPR, ratio of neutrophil to fibrinogen product to prealbumin; NFPS, score of neutrophil and fibrinogen to prealbumin ratio; MFAR, monocyte-fibrinogen product-albumin ratio; MFAS, monocyte-fibrinogen-albumin ratio score; MFPR, monocyte-fibrinogen product-prealbumin ratio; MFPS, monocyte-fibrinogen-prealbumin ratio score; PFAR, platelet-fibrinogen product-albumin ratio; PFAS, platelet-fibrinogen-albumin ratio score; PFPR, platelet-fibrinogen product-prealbumin ratio; PFPS, platelet-fibrinogen-prealbumin ratio score.

[0036] Over a three-year period, each included patient was followed up every three months in the first two years and every six months in the third year. Follow-up was performed by clinical follow-up, telephone, email, and review of medical records. Clinical imaging examinations were used to determine whether the patient had recurrence or distant metastasis. The primary follow-up endpoints were recurrence-free survival and overall survival. The follow-up deadline was December 31, 2023.

[0037] Relapse-free survival refers to the period from the moment surgery is completed until the patient's first recurrence or metastasis or the end of follow-up (i.e., the patient is still alive but the study or treatment cycle has been completed).

[0038] Overall survival refers to the period from the moment the surgery is completed until the patient's death or the end of follow-up (that is, the patient is still alive but the study or treatment cycle has been completed).

[0039] The cutoff values ​​for each inflammatory biomarker and inflammation-based ratio were precisely set by X-tile software, as shown in Table 1. In data analysis, categorical variables were described by counts and proportions, and the chi-square test or Fisher's exact test was used to analyze the differences between groups; continuous values ​​were expressed as mean ± standard deviation, and the differences between groups were evaluated by Kruskal-Wallis H test. In addition, Kaplan-Meier curves (combined with log-rank test) were used for survival analysis, and univariate and multivariate Cox regression models were used to explore independent prognostic factors for recurrence-free survival and overall survival, and hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated. Time-dependent receiver operating characteristic (ROC) curves were used to evaluate the predictive power of these indicators. All statistical analyses were performed using SPSS27.0, R 4.3.3, and GraphPad Prism 10 software.

[0040] This example finally included 1413 CRC patients, of which 981 patients (before 2017) were included in the discovery cohort and 432 patients (after 2017) were included in the validation cohort. Table 2 shows demographic data, treatment methods, 6 inflammatory ratios (NFAR, NFPR, MFAR, MFPR, PFAR, PFPR), 6 inflammatory scores (NFAS, NFPS, MFAS, MFPS, PFAS, PFPS), recurrence and death data. In both cohorts, approximately 60% of the participants were male, and more than half of the participants were over 60 years old. All recipients received radical treatment, and more than 80% of the patients received postoperative chemotherapy. The percentage of patients receiving postoperative radiotherapy was 9% in the discovery cohort and 4.2% in the validation cohort. After 3 years of follow-up, the recurrence rate and mortality rate of the discovery cohort were 28.6% and 17.1%, respectively, and the recurrence rate and mortality rate of the validation cohort were 22.7% and 12%, respectively.

[0041] Table 2 Analysis of clinical characteristics parameters of the discovery cohort and validation cohort populations

[0042]

[0043]

[0044] In the discovery cohort, multivariate analysis was performed based on multiple factors including sex, age, smoking, drinking, hypertension, T stage, lymph node (LN) status, tumor differentiation, tumor size, postoperative chemotherapy and radiotherapy. The results showed that CA19-9 and 12 new inflammatory biomarkers were significantly correlated with the clinical prognosis of patients.

[0045] Specifically, the hazard ratios (HRs) and their 95% confidence intervals (CIs) of CA19-9, NFAR, NFAS, NFPR, NFPS, MFAR, MFAS, MFPR, MFPS, PFAR, PFAS, PFPR, PFPS and recurrence-free survival were as follows: 1.57 (1.22–2.01), 1.77 (1.38–2.27), 1.88 (1.46–2.41), 2.09 (1.63–2.91), and 3.91 (1.97–2.11). (1.63–2.69), 3.71 (2.88–4.76), 1.72 (1.32–2.24), 1.72 (1.34–2.22), 2.40 (1.85–3.11), 3.25 (2.53–4.18), 1.71 (1.33–2.20), 1.74 (1.35–2.24), 2.52 (1.95–3.25), 3.08 (2.37–4.01) (see Figure 1 (A) in the figure.

[0046] The HRs and 95% CIs for CA19-9, NFAR, NFAS, NFPR, NFPS, MFAR, MFAS, MFPR, MFPS, PFAR, PFAS, PFPR, PFPS, and overall survival were as follows: 1.78 (1.29–2.45), 2.31 (1.67–3.18), 2.03 (1.46–2.82), 2.97 (2.13–4.14), and 3.89 (2.71–3.91) for both groups. ), 4.41 (3.18–6.10), 2.10 (1.46–3.02), 1.74 (1.26–2.41), 2.88 (2.03–4.10), 3.52 (2.55–4.85), 2.22 (1.69–3.10), 1.68 (1.21–2.33), 3.01 (2.18–4.17), 3.26 (2.36–4.49) (see Figure 1 (B) in the figure.

[0047] In addition, multivariate analysis in the validation cohort showed that carcinoembryonic antigen (CEA), CA19-9, and 10 of the 12 novel inflammatory biomarkers (excluding PFAR and PFAS) remained significantly correlated with patients' clinical prognosis.

[0048] Specifically, the HRs and 95% CIs of CEA, CA19-9, NFAR, NFAS, NFPR, NFPS, MFAR, MFAS, MFPR, MFPS, PFPR, PFPS and recurrence-free survival were as follows: 3.08 (1.84–5.16), 2.52 (1.63–3.89), 2.77 (1.78–4.30), 2.92 (1.88–4.52), 3.37 (2.06–5.53), 4.62 (2.99–7.12), 2.45 (1.55–3.86), 1.93 (1.26–2.95), 2.85 (1.79–4.53), 3.58 (2.35–5.46), 3.18 (1.96–5.17), and 3.81 (2.50–5.80) (see Table 5 ). Figure 1 (C) in the.

[0049] The HRs and 95% CIs of CEA, CA19-9, NFAR, NFAS, NFPR, NFPS, MFAR, MFAS, MFPR, MFPS, PFPR, PFPS and overall survival were as follows: 3.44 (1.65–7.14), 2.98 (1.64–5.42), 3.09 (1.65–5.82), 1.91 (1.05–3.47), 3.06 (1.56–6.00), 5.23 (2.80–9.77), 2.78 (1.40–5.53), 2.24 (1.24–4.06), 3.89 (1.96–7.71), 5.34 (2.92–9.75), 2.86 (1.47–5.55), and 4.42 (2.42–8.10) (see Figure 1 (D) in the.

[0050] Since the predictive performance of the above inflammatory markers is relatively similar, it is challenging to identify the best predictor of CRC prognosis ( Figure 1 To address this question, these markers were included in multivariate Cox regression analysis and a comprehensive chronic inflammation index (CII) was developed:

[0051] CII=2.816×NFPS+0.659×MFAS+2.180×MFPS+1.538×NFAR;

[0052] like Figure 2 As shown in (A)-(D) in Figure 3, high CII was associated with worse recurrence-free survival and overall survival in both the discovery and validation cohorts.

[0053] In addition, multivariate analysis showed that CII was significantly associated with patient prognosis in subgroup analysis.

[0054] In the discovery cohort, the adjusted HRs and 95% CIs for CII and recurrence-free survival and overall survival were 3.71 (2.88–4.76) and 4.42 (3.20–6.12), respectively; in the validation cohort, the adjusted HRs and 95% CIs for CII and recurrence-free survival and overall survival were 4.84 (3.13–7.49) and 5.78 (3.06–10.92), respectively. In patients with stage II colorectal cancer, the adjusted HRs and 95% CIs for CII and recurrence-free survival and overall survival were 5.54 (3.71–8.26) and 6.19 (3.66–10.46), respectively; in patients with stage III colorectal cancer, the adjusted HRs and 95% CIs for CII and recurrence-free survival and overall survival were 3.43 (2.66–4.43) and 3.98 (2.82–5.61), respectively (Table 3).

[0055] Table 3 Kaplan-Meier curves and Cox analysis of CII index and recurrence-free survival and overall survival

[0056]

[0057] Note: Multivariate Cox regression analysis was adjusted for sex, age, smoking, drinking, diabetes, hypertension, chemotherapy, radiotherapy, tumor invasion depth, lymph node metastasis, cell differentiation and tumor size.

[0058] It is noteworthy that, regardless of whether CII was considered as a continuous variable or a categorical variable, multivariate Cox regression analysis identified CII as an independent prognostic factor for patients with colorectal cancer. When CII was classified according to quartiles, it was found that the risk of poor prognosis gradually increased among the Q2, Q3, and Q4 groups, with adjusted HRs (95% CI) for recurrence-free survival of 1.49 (0.72–3.08), 2.63 (1.27–5.46), and 6.90 (3.39–14.04), and adjusted HRs (95% CI) for overall survival of 1.44 (0.51–4.06), 3.39 (1.22–9.43), and 8.83 (3.25–23.96), respectively (Table 4).

[0059] Table 4 Analysis of recurrence-free survival and overall survival between CII and the general population

[0060]

[0061] Model a: unadjusted; Model b: adjusted for sex, age, smoking, drinking, diabetes, hypertension, chemotherapy, radiotherapy, tumor invasion depth, lymph node metastasis, cell differentiation and tumor size.

[0062] Multivariate restricted cubic spline (RCS) analysis further demonstrated a linear correlation between CII and poor survival prognosis in patients with colorectal cancer ( Figure 2 (E)-(F) in the figure). Time-dependent ROC analysis showed that the area under the curve (AUC) of CII in predicting 12-month relapse-free survival and overall survival of patients in the overall population was 0.70 and 0.73, respectively, the AUC for predicting 24-month relapse-free survival and overall survival was 0.70 and 0.72, respectively, and the AUC for predicting 36-month relapse-free survival and overall survival was 0.71 and 0.74, respectively. Figure 2 (G)-(H)). The results showed that CII is a robust and effective clinical indicator for CRC prognosis.

[0063] Further analysis revealed that high CII was significantly associated with high tumor invasion depth (T3-4) (p = 0.02), high tumor burden (≥5 cm) (p < 0.001), and low / undifferentiated cancer cells (p = 0.001). Figure 3 (A)-(C)). CII and eight parts of the colon to rectum (ileocecal, ascending colon, hepatic flexure, transverse colon, splenic flexure, descending colon, sigmoid colon and rectum) were analyzed. CII and high CII ratios gradually increased from the rectum to the splenic flexure, decreased in the transverse colon, and increased to the highest point from the hepatic flexure to the ileocecal (p<0.001) ( Figure 3 The trends of recurrence and mortality from the rectum to the ileocecal region were basically consistent with the trends of CII and high CII ratios (Table 5).

[0064] Table 5 Changes in recurrence rate and mortality rate in patients with different tumor sites

[0065]

[0066] According to the trend of CII in different primary tumor sites of colorectal cancer patients, the population was classified into four tumor sites: the proximal colon from the ileocecal region to the ascending colon, the transverse colon from the hepatic flexure to the splenic flexure, the distal colon consisting of the descending colon and sigmoid colon, and the rectum. Among patients in the above four sites, the CII and high CII ratios, recurrence rates, and mortality rates gradually increased from the rectum to the proximal colon (p<0.001)( Figure 3 Similarly, the recurrence-free survival of patients with CII and the above four different sites ( Figure 4 (A), (C), (E), (G)) and overall survival ( Figure 4 (B), (D), (F), (H)), recurrence rate ( Figure 4 of (I)) and mortality ( Figure 4 (J)) in are all significantly correlated.

[0067] The results of multivariate Cox regression analysis showed that CII was a prognostic factor for recurrence-free survival in the rectum [adjusted HR and 95% CI = 3.53 (2.54-4.90)] and overall survival [adjusted HR and 95% CI = 4.95 (3.15-7.78)], and for recurrence-free survival in the distal colon [adjusted HR and 95% CI = 2.87 (1.82-4.51)] and overall survival [adjusted HR and 95% CI = 3.59 (2.02-6.39)]. , recurrence-free survival in the transverse colon [adjusted HR and 95% CI = 4.50 (2.50–8.11)] and overall survival [adjusted HR and 95% CI = 4.24 (2.02–8.89)], and recurrence-free survival in the proximal colon [adjusted HR and 95% CI = 7.51 (3.99–14.12) and overall survival [adjusted HR and 95% CI = 4.92 (2.41–10.06)] (Table 6).

[0068] Table 6 Cox regression analysis of the prognosis of patients with CII in the four newly classified sites

[0069]

[0070] In addition, a new composite index 3C was developed, which integrates CII, CEA, and CA19-9, and the calculation formula is as follows:

[0071] 3C=3.646×CII+1.455×CEA+1.673×CA19-9;

[0072] Survival analysis showed that high levels of 3C were significantly associated with poor recurrence-free survival and overall survival, with recurrence rates and mortality rates of 38.9% and 24.8% in the 3C-high subgroup and 13.2% and 5.2% in the 3C-low subgroup, respectively. Figure 5 (A)-(B) in Figure 5). Notably, 3C was superior to any index (CII, CEA, or CA19-9) in predicting CRC prognosis at all observed time points ( Figure 5 (C)-(D) in Figure 3). Time-dependent ROC analysis confirmed the superior predictive performance of 3C for 36-month survival in the overall population, with an AUC of 0.74 for predicting recurrence-free survival and 0.76 for predicting overall survival ( Figure 5 (E)-(F) in the figure.

[0073] It is worth noting that the contents not elaborated in detail in the present invention are all prior art and are well known to those skilled in the art.

[0074] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that they can still modify or replace the technical solution of the present invention with equivalents, and these modifications or equivalent replacements cannot cause the modified technical solution to deviate from the spirit and scope of the technical solution of the present invention.

Claims

1. Application of the chronic inflammation comprehensive index or 3C score in the prognostic prediction system for patients with stage II-III colorectal cancer.

2. The use according to claim 1, characterized in that: The calculation formula of the chronic inflammation comprehensive index is as follows: CII=2.816×NFPS+0.659×MFAS+2.180×MFPS+1.538×NFAR; Among them, CII represents the comprehensive chronic inflammation index; NFPS represents the scores of neutrophils and the ratio of fibrinogen to prealbumin; MFAS represents the scores of monocytes and the ratio of fibrinogen to albumin; MFPS represents the scores of monocytes and the ratio of fibrinogen to prealbumin; NFAR represents the ratio of the product of neutrophils and fibrinogen to albumin.

3. The use according to claim 2, characterized in that: The 3C score calculation formula is as follows: Among them, 3C represents 3C score; CEA represents the content of carcinoembryonic antigen in the patient's body; CA19-9 represents the content of sugar chain antigen 19-9 in the patient's body.

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