Serum FGF19-based biliary atresia preoperative prognosis evaluation product and method

Abstract

The invention relates to the field of biological medicine, and discloses a biliary atresia preoperative prognosis evaluation product and method based on serum FGF19. The invention provides a metabolite combination for biliary atresia preoperative prognosis evaluation, the metabolite combination comprises FGF19, GGT, DBIL and ALB, a formula for evaluating the prognosis risk according to the concentration of the metabolite is provided, and the risk can be graded according to the grading result of the formula. According to the scheme provided by the invention, more theoretical bases are provided for selection of treatment schemes for children with biliary atresia in the future, and a doctor can be helped to judge whether the children still have the possibility of benefiting from the Kuzhi surgery before the Kuzhi surgery or directly perform liver transplantation so as to avoid unnecessary operative wounds.

Description

Technical Field

[0001] The present application relates to the field of biomedicine, and more specifically, to a product and method for preoperative prognosis assessment of biliary atresia based on serum FGF19. Background Art

[0002] Biliary atresia is a serious pediatric hepatobiliary disease. The current main treatment is to perform a portojejunostomy (Kasai procedure) in the early stages of the disease (optimally within 60 days of birth). However, the prognosis of the Kasai procedure is poor, with approximately 40% to 50% of children with biliary atresia requiring a liver transplant within a relatively short or long period of time after the procedure (most children undergo a liver transplant within 2 years of the procedure). This results in some children undergoing two major surgeries in succession within less than two years of birth. If children who may require a liver transplant in the short term after the procedure can be identified before the Kasai procedure, studies have shown that direct liver transplantation can achieve graft survival and patient survival rates that are no less than those achieved with liver transplantation after the Kasai procedure. However, there is currently a lack of clinical markers that can be used to assess prognosis before the Kasai procedure. Summary of the Invention

[0003] To fill the gap in the existing technology, the present invention proposes a scheme using preoperative serum fibroblast growth factor 19 (FGF19) as an effective marker for preoperative Kasai prognosis assessment of biliary atresia (BA), and combines it with preoperative serum gamma-glutamyltransferase (GGT), direct bilirubin (DBIL) and albumin (ALB) for multifactor analysis to further improve the accuracy of preoperative Kasai prognosis prediction.

[0004] In a first aspect, the present invention discloses the use of FGF19 as a marker in the preparation of a product for pre-operative prognosis assessment of biliary atresia Kasai surgery.

[0005] In a second aspect, the present invention discloses a metabolite combination for pre-procedure prognosis evaluation of biliary atresia Kasai surgery, characterized in that the metabolites include FGF19, GGT, DBIL, and ALB.

[0006] In a third aspect, the present invention discloses the use of the metabolite combination described in the second aspect in the preparation of a product for pre-operative prognosis assessment of biliary atresia Kasai surgery.

[0007] In a fourth aspect, the present invention discloses a kit for evaluating the prognosis of biliary atresia before Kasai surgery, comprising a reagent for detecting the concentration of the metabolite combination described in the second aspect.

[0008] Furthermore, the kit also includes a product instruction manual, which records the formula:

[0009] Risk Score=FGF19 / 100+GGT*0.97+DBIL*1.03-ALB*0.58;

[0010] Among them, FGF19 represents the concentration of serum FGF19 before surgery expressed in pg / ml;

[0011] GGT is a binary variable converted according to the cutoff value, 0 or 1. When GGT concentration is expressed in U / L, concentration >400 U / L = 1, otherwise it is 0;

[0012] DBIL is a binary variable converted to 0 or 1 according to the cutoff value. When DBIL is expressed in μmol / L, the concentration >146.2 μmol / L = 1, otherwise it is 0;

[0013] ALB is a binary variable converted to 0 or 1 according to the cutoff value. When ALB concentration is expressed in g / L, the concentration >37.3 g / L = 1, otherwise it is 0.

[0014] Furthermore, the instructions also record the risk stratification criteria:

[0015] Low risk: Risk Score ≤2.6;

[0016] High risk: Risk Score > 2.6.

[0017] In a fifth aspect, the present invention discloses a method for pre-operative prognosis assessment of biliary atresia Kasai surgery, wherein all steps are implemented by a computer, comprising the following steps:

[0018] Step 1: Obtaining the concentration information of the metabolic composition FGF19, GGT, DBIL, and ALB in the patient's serum;

[0019] Step 2: Input the concentration information obtained in step 1 into the formula: Risk Score = FGF19 / 100 + GGT*0.97 + DBIL*1.03 - ALB*0.58;

[0020] Among them, FGF19 represents the concentration of serum FGF19 before surgery expressed in pg / ml;

[0021] GGT is a binary variable converted according to the cutoff value, 0 or 1. When GGT concentration is expressed in U / L, the concentration > FGF19 cutoff value = 1, otherwise it is 0;

[0022] DBIL is a binary variable converted to 0 or 1 according to the cutoff value. When DBIL is expressed in μmol / L, the concentration > DBIL cutoff value = 1, otherwise it is 0;

[0023] ALB is a binary variable converted to 0 or 1 according to the cutoff value. When ALB is expressed in g / L, the concentration > ALB cutoff value = 1, otherwise it is 0;

[0024] Step 3: Output the risk level based on the Risk Score obtained in step 2:

[0025] Low risk: Risk Score ≤ optimal assessment threshold;

[0026] High risk: Risk Score > optimal assessment threshold.

[0027] Furthermore, in step 2:

[0028] FGF19 cutoff value = 400 U / L;

[0029] DBIL cutoff value = 146.2 μmol / L;

[0030] ALB cutoff value = 37.3 g / L.

[0031] Furthermore, in step 3:

[0032] The optimal assessment threshold for Risk Score is 2.6

[0033] In summary, this application has the following beneficial effects:

[0034] Currently, in clinical practice, doctors are often unable to determine whether a child with biliary atresia needs a liver transplant after surgery based on preoperative non-invasive examinations, such as laboratory indicators. Whether a child needs a liver transplant after surgery often requires long-term postoperative follow-up of the child, and the judgment is made based on the child's condition each time. The conventional treatment of Kasai maneuver plus subsequent secondary liver transplantation is often still the first choice. This may cause some children who may not benefit from Kasai maneuver to continue to experience two surgical traumas within two years after birth. The scheme proposed in this application provides more theoretical basis for the selection of treatment options for children with biliary atresia in the future, and can help doctors determine whether the child is still likely to benefit from Kasai maneuver before Kasai maneuver, or whether to directly undergo liver transplantation to avoid unnecessary surgical trauma. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 : Preoperative elevation of serum FGF19 in biliary atresia and its correlation with biological markers;

[0036] A) Scatter plot of biliary atresia (BA) patients and controls (grouped by sample storage year and gender);

[0037] B) Correlation analysis between serum FGF19 level and age at Kasai surgery;

[0038] C) Scatter plot of serum FGF19 levels and total bile acid (TBA);

[0039] D) Correlation analysis between serum FGF19 level and total bilirubin 3 months after Kasai surgery (TBIL 3M);

[0040] E) Correlation analysis between serum FGF19 level and total bilirubin clearance rate (TBIL 3M CR) 3 months after Kasai surgery.

[0041] Figure 2 : Correlation analysis between preoperative serum FGF19 level and KPE surgical outcome;

[0042] A) Correlation between FGF19 and jaundice clearance rate 3 months after surgery;

[0043] B) Correlation between FGF19 and 2-year native liver survival (NLS);

[0044] C) Correlation between FGF19 and 2-year NLS in patients with KPE ≤ 60 days old;

[0045] D) Correlation between FGF19 and 2-year NLS in patients with KPE >60 days old;

[0046] E) AUC curves of FGF19 and 2-year NLS in patients ≤60 days old;

[0047] F) AUC curves of FGF19 and 2-year NLS in patients >60 days old.

[0048] Note: COJ: jaundice cleared 3 months after surgery; NCOJ: jaundice not cleared 3 months after surgery; NLS: autologous liver survival > 2 years; NNLS: autologous liver survival ≤ 2 years.

[0049] Figure 3 : Nomogram model.

[0050] Figure 4 : Define HRBA;

[0051] A) ROC analysis and definition of risk score cutoffs;

[0052] B) determination of the optimal cutoff value for risk score;

[0053] C) Comparison of FG19 and GGT levels between HRBA and BA; RS, risk score; HRBA, high-risk BA.

[0054] Figure 5 : Nomogram A calibration curve;

[0055] A) Calibration curve of the predicted autologous liver survival rate six months after Kasai surgery based on the Nomogram A training set;

[0056] B) Calibration curve of the predicted value of autologous liver survival rate after 1-year Kasai surgery based on the Nomogram A training set;

[0057] C) Calibration curve of the predicted value of autologous liver survival rate 2 years after Kasai surgery based on the Nomogram A training set;

[0058] D) Calibration curve of the predicted value of autologous liver survival rate after Kasai surgery in the validation set of Nomogram A;

[0059] E) Calibration curve of the predicted value of autologous liver survival rate after 1-year Kasai surgery in the validation set of Nomogram A;

[0060] F) Calibration curve of the predicted value of autologous liver survival rate 2 years after Kasai surgery in the Nomogram A validation set. DETAILED DESCRIPTION

[0061] The technical solutions and effects of the present application are further described in detail below with reference to the embodiments and accompanying drawings. It should be understood that the specific embodiments described herein are merely for explaining the present invention, and are not intended to limit the present invention. It should also be noted that, for ease of description, the accompanying drawings only illustrate portions of the present invention, not all of its components.

[0062] Example 1: Analysis of expression characteristics of serum fibroblast growth factor 19 (FGF19) before biliary atresia surgery

[0063] 1. Sample Source

[0064] Inclusion criteria for children with biliary atresia (BA group):

[0065] 1. BA was diagnosed by intraoperative cholangiography and postoperative liver pathology;

[0066] 2. Standardized follow-up after surgery, with records of serum TBIL three months after surgery and autologous liver survival two years after surgery;

[0067] 3. The total volume of residual preoperative serum is >500ul;

[0068] 4. Standardized drug treatment (ursodeoxycholic acid, antibiotics, vitamins, Chinese herbal medicine and steroids) should be carried out after surgery.

[0069] Inclusion criteria for the control group (non-BA group):

[0070] 1. Children with non-BA cholestasis diagnosed by intraoperative cholangiography and postoperative liver pathology;

[0071] 2. Similar age to the child with BA;

[0072] 3. The total volume of residual preoperative serum is >500ul.

[0073] 2. Sampling process

[0074] 1. Centrifuge whole blood at 3000 rpm, 4°C for 10 min and collect the supernatant;

[0075] 2. Serum samples should be stored at -80℃ before use to avoid repeated freezing and thawing.

[0076] 3. Correlation Analysis Process

[0077] 1. Analysis of intergroup differences

[0078] Nonparametric tests: Because the serum FGF19 level data showed non-normal distribution (Shapiro-Wilk test, P < 0.05), the Mann-Whitney U test was used to compare the differences in FGF19 levels between the BA group and the non-BA cholestasis group. The results are expressed as median (interquartile range, IQR).

[0079] Gender subgroup analysis: Based on the non-normal distribution, the Mann-Whitney U test was used to evaluate the difference in FGF19 levels between male and female BA patients.

[0080] Depend on Figure 1 It can be seen that the serum FGF19 level in the BA group before Kasai surgery was significantly higher than that in children with non-BA cholestasis [95.67 (58.97-140.6) vs 58.73 (43.59-85.35) pg / ml, P = 0.0003] ( Figure 1 A); FGF19 levels were also higher in the male group [78.17 (47.72-137.1) vs 110.0 (75.03-142.2) pg / ml, P = 0.0031] ( Figure 1 A).

[0081] 2. Correlation Analysis

[0082] Linear regression model: To explore the relationship between preoperative FGF19 levels and continuous variables (such as surgical age, TBA, and postoperative TBIL), a univariate linear regression model was constructed:

[0083] Y=β0+β1*XFGF19+∈

[0084] where Y represents age at KPE, preoperative TBA level, TBIL level or TBIL clearance rate 3 months after surgery, and X represents preoperative FGF19 level.

[0085] The strength of association between variables was quantified by the coefficient of determination (R2), and the statistical significance of regression coefficients was assessed using t-test.

[0086] Depend on Figure 1 It can be seen that the preoperative serum FGF19 level was positively correlated with the age at KPE (R2=0.0211, P=0.0423) and the preoperative serum total bile acid (TBA) level (R2=0.0217, P=0.0393). Figure 1 B, C). Preoperative serum FGF19 levels were positively correlated with serum total bilirubin (TBIL) levels 3 months after KPE (R2=0.0479, P=0.0021), and negatively correlated with TBIL clearance rate (R2=0.05710, P=0.0008) ( Figure 1 D,E)

[0087] 3. Statistical Power and Correction for Multiple Testing

[0088] All P values were two-sided, and the significance threshold was set at α = 0.05.

[0089] For analyses involving multiple group comparisons (such as gender differences and between-group differences), the Bonferroni correction was used to adjust the family-wise error rate (corrected significance threshold: α = 0.025).

[0090] 4. Correlation Analysis Conclusion

[0091] 1. Determination of significant differences

[0092] The FGF19 level in the BA group was significantly higher than that in the non-BA group (P=0.0003), and the effect size Cliff's delta was 0.32 (95% CI: 0.15-0.49), indicating a moderate difference.

[0093] The FGF19 level in male BA patients was higher than that in female patients (P=0.0031), with Cohen's d=0.61 (calculated based on rank-transformed data), which was a medium effect.

[0094] 2. Clinical significance of correlation results

[0095] Although the R2 values of FGF19, surgical age, and TBA were low (~2%), their regression coefficients were statistically significant (P<0.05), suggesting that FGF19 had an independent but weak effect on clinical parameters.

[0096] The negative correlation between FGF19 and postoperative TBIL clearance rate (R2=5.7%, P=0.0008) has a higher clinical interpretation, which may reflect its potential as a prognostic factor.

[0097] Example 2: Correlation analysis between serum FGF19 and prognosis before biliary atresia surgery

[0098] 1. Sample Source:

[0099] Inclusion criteria for children with biliary atresia (BA group):

[0100] 1. BA was diagnosed by intraoperative cholangiography and postoperative liver pathology;

[0101] 2. Standardized follow-up after surgery, with records of serum TBIL three months after surgery and autologous liver survival two years after surgery;

[0102] 3. The total volume of residual preoperative serum is >500ul;

[0103] 4. Standardized drug treatment (ursodeoxycholic acid, antibiotics, vitamins, Chinese herbal medicine and steroids) should be carried out after surgery.

[0104] Inclusion criteria for the control group (non-BA group):

[0105] 1. Children with non-BA cholestasis diagnosed by intraoperative cholangiography and postoperative liver pathology;

[0106] 2. Similar age to the child with BA;

[0107] 3. The total volume of residual preoperative serum is >500ul.

[0108] 2. Sampling process:

[0109] 1. Centrifuge whole blood at 3000 rpm, 4°C for 10 min and collect the supernatant;

[0110] 2. Serum samples should be stored at -80℃ before use to avoid repeated freezing and thawing.

[0111] 3. Correlation Analysis Process

[0112] 1. Analysis of intergroup differences

[0113] For the two binary prognostic indicators of postoperative jaundice clearance status (yes / no) and 2-year autologous liver survival (NLS ≤ 2 years vs > 2 years), the Mann-Whitney U test was used to compare the differences in preoperative serum FGF19 levels between the groups. Data are reported as median (IQR) ( Figure 2 A, B). Mann-Whitney U test was used to evaluate the association between FGF19 and 2-year NLS after stratification by age at KPE surgery (≤60 days vs >60 days).

[0114] Depend on Figure 2 It can be seen that patients who failed to achieve jaundice clearance within 3 months after KPE had significantly higher preoperative serum FGF19 levels [109.0 (70.38-148.9) vs. 75.52 (50.98-115.3) pg / ml, P = 0.0006; AUC = 64.10%, P = 0.0007, optimal cutoff value: 88.57 pg / ml]. Similarly, patients with NLS ≤ 2 years after surgery also showed higher FGF19 levels [77.9 (52.28-113.6) vs. 121.0 (77.33-154.5) pg / ml, P < 0.0001; AUC = 66.39%, P < 0.0001, optimal cutoff value: 94.47 pg / ml] ( Figure 2 A, B).

[0115] 2. Diagnostic efficacy analysis:

[0116] The predictive efficacy of FGF19 was calculated by receiver operating characteristic (ROC) curve analysis.

[0117] 3. Statistical control

[0118] Multiple testing correction: Holm-Bonferroni correction was performed for subgroup comparisons (≤60 days vs. >60 days) in stratified analyses, and the adjusted significance threshold was α = 0.025.

[0119] 4. Correlation Analysis Conclusion

[0120] 1. Determination of significant differences

[0121] The FGF19 level in the jaundice-uncleared group was significantly higher (109.0 vs 75.52 pg / ml, P=0.0006), with an effect size of Cliff's delta=0.27 (95% CI: 0.12-0.42).

[0122] The FGF19 level in the NLS ≤ 2 years group was increased (121.0 vs 77.9 pg / ml, P < 0.0001), with an effect size of Cliff's delta = 0.35 (95% CI: 0.21-0.49).

[0123] ≤60 days subgroup: FGF19 was significantly elevated in patients with poor NLS (117.1 vs 72.9 pg / ml, P<0.0001), with an effect size of Cliff's delta = 0.41 (95% CI: 0.24-0.57).

[0124] >60-day subgroup: There was no statistically significant difference between the two groups (124.1 vs 90.5 pg / ml, P=0.3045), with Cliff's delta effect size = 0.18 (95% CI: -0.15-0.46).

[0125] 2. Diagnostic efficacy verification

[0126] Failure of jaundice clearance: AUC = 64.10% (P = 0.0007), the optimal cutoff value determined by Youden index was 88.57 pg / ml (sensitivity = 72.3%, specificity = 58.1%).

[0127] 2-year NLS poor prognosis: AUC = 66.39% (P < 0.0001), the best cutoff value was 94.47 pg / ml (sensitivity = 65.4%, specificity = 63.8%).

[0128] ROC analysis was performed for the ≤60-day subgroup:

[0129] AUC=70.80% (P<0.0001), optimal cutoff value 103.2 pg / ml (sensitivity=68.9%, specificity=71.2%).

[0130] Depend on Figure 2 It can be seen that in patients with KPE age ≤ 60 days, preoperative serum FGF19 levels were significantly correlated with 2-year NLS results [72.9 (51.75-104.1) vs 117.1 (77.97-158.3) pg / ml, P < 0.0001; AUC = 70.80%, P < 0.0001, optimal cutoff value: 103.2 pg / ml], while in patients with KPE age > 60 days, this correlation was not significant [90.5 (52.96-149.7) vs 124.1 (71.93-151.6) pg / ml, P = 0.3045; AUC = 57.37%, P = 0.2995] ( Figure 2 CF).

[0131] 3. Clinical significance of the results

[0132] Preoperative FGF19 levels have predictive value for both short-term (jaundice clearance) and long-term (2-year NLS) postoperative prognosis, and its predictive efficacy is significantly improved with the optimization of surgical timing (≤60 days) (AUC increased from 64.1% to 70.8%).

[0133] Age-stratified analysis suggested that the prognostic value of FGF19 was time-dependent, and the predictive efficacy of FGF19 was more significant in patients undergoing early surgery (≤60 days), which may reflect the critical time window for the progression of biliary fibrosis.

[0134] The determined cutoff value (such as 103.2 pg / ml) can provide a quantitative threshold for clinical decision-making to identify high-risk patients and guide individualized intervention.

[0135] Example 3: Prognosis prediction using preoperative serum FGF19 and other markers in BA patients with KPE age ≤ 60 days

[0136] 1. Sample Source:

[0137] Inclusion criteria for children with biliary atresia (BA group):

[0138] 1. BA was diagnosed by intraoperative cholangiography and postoperative liver pathology;

[0139] 2. Standardized follow-up after surgery, with records of serum TBIL three months after surgery and autologous liver survival two years after surgery;

[0140] 3. The total volume of residual preoperative serum is >500ul;

[0141] 4. Standardized drug treatment (ursodeoxycholic acid, antibiotics, vitamins, Chinese herbal medicine and steroids) should be carried out after surgery.

[0142] Inclusion criteria for the control group (non-BA group):

[0143] 1. Children with non-BA cholestasis diagnosed by intraoperative cholangiography and postoperative liver pathology;

[0144] 2. Similar age to the child with BA;

[0145] 3. The total volume of residual preoperative serum is >500ul.

[0146] 2. Sampling process:

[0147] 1. Centrifuge whole blood at 3000 rpm, 4°C for 10 min and collect the supernatant;

[0148] 2. Serum samples should be stored at -80℃ before use to avoid repeated freezing and thawing.

[0149] 3. Division of training set and validation set:

[0150] According to the time division method: the total cohort was divided into the order of surgery time, the first 67.8% (March 2019-December 2021) was used as the training set (N=133 cases), and the last 32.2% (February 2018-February 2019) was used as the validation set (N=63 cases).

[0151] 4. How to obtain and use the formula:

[0152] 1. Formula derivation method

[0153] Multivariate Cox regression analysis: In the training set, 2-year autologous liver survival (NLS) was used as the endpoint event. FGF19 (continuous variable), GGT (>400 U / L = 1), DBIL (>146.2 μmol / L = 1), and ALB (>37.3 g / L = 1) were included in the multivariate Cox proportional hazard model to obtain the regression coefficient (β value) of each variable.

[0154] 2. Nomogram score conversion: Based on the regression coefficient, the variable is converted into a risk score using the following formula:

[0155] Risk Score=FGF19 / 100+GGT*0.97+DBIL*1.03-ALB*0.58

[0156] 3. Clinical application steps

[0157] Data input:

[0158] Serum FGF19 (pg / ml), GGT (U / L), DBIL (μmol / L), and ALB (g / L) were measured before surgery.

[0159] GGT, DBIL, and ALB were converted into binary variables (0 or 1) according to the cutoff value.

[0160] Rating calculation:

[0161] The original value of FGF19 was multiplied by 0.01, and the categorical values of other variables were added and multiplied by the corresponding weights, and the sum was calculated to obtain the total risk score.

[0162] Example: A child's FGF19 = 120pg / ml, GGT = 450U / L, DBIL = 160μmol / L, ALB = 35g / L, then:

[0163] Rating = (120 × 0.01) + (1 × 0.97) + (1 × 1.03) - (0 × 0.58) = 1.2 + 0.97 + 1.03 - 0 = 3.2

[0164] Risk stratification:

[0165] Low risk: score ≤ 2.6 → routine postoperative management

[0166] High risk: score > 2.6 → requires intensive postoperative intervention or priority liver transplantation evaluation

[0167] V. Model Evaluation and Judgment Criteria

[0168] 1. Prediction effectiveness verification

[0169] Discrimination: C-index = 0.767±0.039 for the training set and C-index = 0.721±0.062 for the validation set. Overfitting was corrected by Bootstrap resampling (1000 times). Compared with the single-factor model (FGF19 only, C-index = 0.664±0.044) and the model without FGF19 (Nomogram A_1, C-index = 0.715±0.042), the prediction efficiency of the combined model was significantly improved.

[0170] 2. Clinical interpretation of risk thresholds

[0171] The cutoff value of 2.6 was chosen based on the following: In the training set, a score >2.6 had a specificity of 100% (positive predictive value = 100%), meaning that all children with a score >2.6 required liver transplantation within 2 years; in the validation set, the specificity of the score was 78.6%, meaning that 78.6% of children with a score >2.6 required liver transplantation within 2 years.

[0172] 3. Calibration Verification

[0173] The calibration curve ( Figure 6 ) shows the consistency between the predicted survival probability and the actual observed probability, indicating that the model is well calibrated.

[0174] VI. Conclusion

[0175] 1. The Nomogram A constructed using FGF19, GGT, DBIL, and ALB can effectively predict the prognosis of BA children with KPE age ≤ 60 days in both the training and validation sets (training set C index: 0.767±0.039, validation set C index: 0.721±0.062), and its predictive efficiency is better than that of Nomogram A_1 (GGT, DBIL, ALB) with FGF19 alone or without FGF19 ( Figure 3 , Table 1).

[0176] 2. Based on Nomogram A, a risk score formula was constructed, where FGF19 was a continuous variable and the other variables were converted into dichotomous variables according to the cutoff value, with > cutoff value as 1 and ≤ cutoff value as 0 (GGT cutoff value: 400 U / L, DBIL cutoff value: 146.2 μmol / L, ALB cutoff value: 37.3 g / L). Children with BA whose risk score >1.36 had a significantly lower 2-year autologous liver survival rate after surgery ( Figure 4 B).

[0177] 3. The model specificity reached its best value in the training set (specificity: 100%, sensitivity: 22.2%) when the risk score cutoff value was 2.6. In the validation set, the specificity was 78.6% when the risk score cutoff value was 2.6. This means that if a BA patient with a preoperative risk score >2.6 who underwent KPE surgery at an age of ≤60 days has a BA, there is an approximately 89.3% probability that the patient will require liver transplantation within 2 years after KPE. Therefore, we define this group of patients (preoperative risk score >2.6) as high-risk BA.

[0178] Table 1 Comparison of model C index

[0179]

[0180] This specific embodiment is merely an explanation of the present application and is not a limitation of the present application. After reading this specification, those skilled in the art may make non-creative modifications to the present embodiment as needed, but as long as they are within the scope of the claims of the present application, they are protected by the patent law.

Claims

1. Application of FGF19 as a marker in the preparation of preoperative prognostic evaluation products for biliary atresia Kasai surgery.

2. A metabolite combination for preoperative prognosis assessment of biliary atresia Kasai surgery, characterized in that: The metabolites include FGF19, GGT, DBIL, and ALB.

3. Use of the metabolite combination according to claim 2 in the preparation of a product for preoperative prognosis assessment of biliary atresia Kasai surgery.

4. A kit for evaluating the prognosis of biliary atresia before Kasai surgery, characterized in that: Comprising a reagent for detecting the concentration of the metabolite combination according to claim 2.

5. The kit according to claim 4, characterized in that It also includes a product instruction manual, which contains the formula: Risk Score=FGF19 / 100+GGT*0.97+DBIL*1.03-ALB*0.58; Among them, FGF19 represents the concentration of serum FGF19 before surgery expressed in pg / ml; GGT is a binary variable converted according to the cutoff value, 0 or 1. When GGT concentration is expressed in U / L, concentration >400 U / L = 1, otherwise it is 0; DBIL is a binary variable converted to 0 or 1 according to the cutoff value. When DBIL is expressed in μmol / L, the concentration >146.2 μmol / L = 1, otherwise it is 0; ALB is a binary variable converted to 0 or 1 according to the cutoff value. When ALB concentration is expressed in g / L, the concentration >37.3 g / L = 1, otherwise it is 0.

6. The kit according to claim 5, characterized in that The instructions also record the risk stratification criteria: Low risk: Risk Score ≤2.6; High risk: Risk Score > 2.

6.

7. A method for evaluating the prognosis of biliary atresia before Kasai surgery, wherein all steps are implemented by a computer, characterized in that: The following steps are involved: Step 1: Obtaining the concentration information of the metabolic composition FGF19, GGT, DBIL, and ALB in the patient's serum; Step 2: Input the concentration information obtained in step 1 into the formula: Risk Score = FGF19 / 100 + GGT*0.97 + DBIL*1.03 - ALB*0.58; Among them, FGF19 represents the concentration of serum FGF19 before surgery expressed in pg / ml; GGT is a binary variable converted according to the cutoff value, 0 or 1. When GGT concentration is expressed in U / L, the concentration > FGF19 cutoff value = 1, otherwise it is 0; DBIL is a binary variable converted to 0 or 1 according to the cutoff value. When DBIL is expressed in μmol / L, the concentration > DBIL cutoff value = 1, otherwise it is 0; ALB is a binary variable converted to 0 or 1 according to the cutoff value. When ALB is expressed in g / L, the concentration > ALB cutoff value = 1, otherwise it is 0; Step 3: Output the risk level based on the Risk Score obtained in step 2: Low risk: Risk Score ≤ optimal assessment threshold; High risk: Risk Score > optimal assessment threshold.

8. The method according to claim 7, characterized in that In step 2: FGF19 cutoff value = 400 U / L; DBIL cutoff value = 146.2 μmol / L; ALB cutoff value = 37.3 g / L.

9. The method according to claim 7, characterized in that In step 3: The optimal assessment threshold for Risk Score is 2.6.

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