Prognosis prediction device, system for central nervous system idiopathic inflammatory demyelination after bone marrow transplantation and application thereof

Abstract

The application relates to a prognosis prediction device and system for central nervous system idiopathic demyelinating disease of a malignant blood disease patient after haplo-HSCT and application thereof. By acquiring spinal cord involvement when the patient is diagnosed with CNS IIDD or reviewing the diagnosis of CNS IIDD when the patient is reexamined, measuring or reviewing the CMV infection, EBV infection and IgG-syn when the patient is diagnosed with CNS IIDD, the death risk of a CNS IIDD patient after haplo-HSCT is judged by using a death risk prediction device of the CNS IIDD patient after haplo-HSCT, and the greater the CELS score of the CNS IIDD patient is, the greater the death risk of the CNS IIDD patient is. The CELS score model for the death risk of the CNS IIDD patient after haplo-HSCT is developed and verified, and high-risk patients can be early identified and timely treatment can be provided only by history inquiry, virus detection and cerebrospinal fluid detection.

Description

Technical Field

[0001] This invention relates to a prognostic prediction device, system, and application of central nervous system idiopathic immune demyelinating disease following haploidentical allogeneic hematopoietic stem cell transplantation in patients with malignant hematological diseases. Background Technology

[0002] Allogeneic hematopoietic stem cell transplantation (allo-HSCT) remains a primary treatment for hematologic malignancies. Furthermore, since 2013, haploidentical hematopoietic stem cell transplantation (haplo-HSCT) has become the largest donor source, accounting for 59.4% of allo-HSCTs. However, the widespread use of haplo-HSCT has led to an increasing number of complications, such as neurological complications (NCs). NCs are a significant cause of bone marrow transplant-related death, with an incidence rate of 8.9%–65% and a mortality rate of 4.7%–50%.

[0003] Idiopathic inflammatory demyelinating diseases (IIDDs) of the central nervous system are increasingly recognized as NCs following haplo-HSCT. Central nervous system IIDDs represent a range of central nervous system diseases that can be differentiated based on severity, clinical course, lesion location, and imaging, laboratory, and pathological findings. The main characteristic of this series of diseases is central nervous system demyelination, particularly of the brain. Major types of IIDDs include multiple sclerosis (MS), neuromyelitis optica (NMO), and acute disseminated encephalomyelitis (ADEM). In addition to these diseases, IIDDs also include variants of multiple sclerosis, including Schilder's disease, Marburg variant, Balo concentric sclerosis (BCS), and childhood-onset multiple sclerosis (POMS), which generally have a worse prognosis than typical MS.

[0004] Our previous studies estimated the incidence of CNS second-degree neural tube defects (IIDDs) after allo-HSCT to be between 1.96% and 3.6%, and found a correlation between cerebrospinal fluid (CSF) immunobiomarkers and the occurrence of IIDDs. Delios et al. demonstrated that central nervous system demyelination after allo-HSCT has a high rate of disability and can severely impact patients' quality of life. Furthermore, Scalfari et al. concluded that MS may increase the risk of death, with MS patients having a 7-14 year shorter life expectancy compared to the general population. These studies indicate that although the incidence of CNS IIDDs is low, the rates of disability and mortality are high. However, risk factors and prognostic factors for CNS IIDDs remain lacking. Moreover, there is currently no method for predicting the prognosis of CNS IIDDs after transplantation. Summary of the Invention

[0005] The first objective of this invention is to provide a device for predicting the risk of death in patients with CNS IIDD after haplo-HSCT.

[0006] The device for predicting mortality risk in CNS IIDD patients after haplo-HSCT provided by this invention includes the following processing module:

[0007] (1) Data input module: This module is used to input the cytomegalovirus (CMV) infection status, EBV infection status, spinal cord involvement status, and central nervous system IgG synthesis index (IgG-syn) of the test subject at the time of diagnosis of CNS IIDD; the test subject is a CNS IIDD patient after haplo-HSCT;

[0008] (2) Data recording module: This module is used to receive and store the test subject's cytomegalovirus (CMV) infection status, EBV infection status, spinal cord involvement status, and central nervous system IgG synthesis index (IgG-syn) output from the data input module;

[0009] (3) Data Assignment Module: This data assignment module consists of CMV infection status assignment module, EBV infection status assignment module, spinal cord involvement status assignment module, and IgG-syn assignment module.

[0010] The CMV infection status assignment module is used to retrieve the CMV infection status of the test subject stored in the data recording module, assign a value to the CMV infection status, and output f(CMV infection status): when "the test subject has CMV infection", f(CMV infection status) is 1 point; when "the test subject does not have CMV infection", f(CMV infection status) is 0 points.

[0011] The EBV infection status assignment module is used to retrieve the EBV infection status of the test subject stored in the data recording module, assign a value to the EBV infection status, and output f(EBV infection status): when "the test subject has EBV infection", f(EBV infection status) is 1 point; when "the test subject does not have EBV infection", f(EBV infection status) is 0 points.

[0012] The spinal cord involvement assignment module is used to retrieve the spinal cord involvement information of the test subject stored in the data recording module, assign a value to the spinal cord involvement information, and output f(spinal cord involvement information): when "the test subject has spinal cord involvement", f(spinal cord involvement information) is 1 point; when "the test subject has no spinal cord involvement", f(spinal cord involvement information) is 0 points.

[0013] The IgG-syn assignment module is used to retrieve the IgG synthesis index of the test subject stored in the data recording module, assign a value to the IgG synthesis index, and output f(IgG-syn): when "the test subject's IgG-syn is positive", f(IgG-syn) is 1 point; when "the test subject's IgG-syn is negative", f(IgG-syn) is 0 points.

[0014] (4) Data calculation module: This module is used to receive f(CMV infection status) output from the CMV infection status assignment module, f(EBV infection status) output from the EBV infection status assignment module, f(spinal cord involvement status) output from the spinal cord involvement assignment module and f(IgG-syn) output from the IgG-syn assignment module, and then calculate the test subject's CELS score according to Equation I;

[0015] CELS score = f(CMV infection status) + f(EBV infection status) + f(spinal cord involvement status) + f(IgG-syn) Equation I;

[0016] The CELS score indicates the risk of death in patients with CNS IIDD following haplo-HSCT.

[0017] (5) Data grouping module: This module is used to receive the CELS score of the tester output from the data calculation module, then group the tester into risk groups based on the CELS score, and output the risk grouping results;

[0018] The criteria for risk grouping test subjects based on CELS scores are as follows: test subjects with CELS scores of 3-4 are in the high-risk group, test subjects with CELS scores of 1-2 are in the medium-risk group, and test subjects with CELS scores of 0 are in the low-risk group.

[0019] (6) Conclusion output module: This module is used to receive the risk grouping results output from the data grouping module and output the conclusion based on the risk grouping results: that is, the test subjects in the high-risk group are CNS IIDD patients with a high risk of death; the test subjects in the intermediate-risk group are CNS IIDD patients with a medium risk of death; and the test subjects in the low-risk group are CNSIIDD patients with a low risk of death.

[0020] In the aforementioned prediction device, the CMV infection status refers to CMV infection in all organ systems other than the central nervous system when diagnosing CNS IIDD; the specific counting method is real-time quantitative PCR detection of CMV-DNA, and the kit used is the CMV real-time PCR kit (Shanghai Zhongjie Biotechnology Co., Ltd., with CE certificate, detection limit is 500 samples / ml).

[0021] In the aforementioned prediction device, the EBV infection status refers to EBV infection in all other organ systems except the central nervous system when diagnosing CNS IIDD; the specific counting method is real-time quantitative PCR detection of EBV-DNA, and the kit used is the EBV DNA diagnostic kit (PCR fluorescent probe) (Sun Yat-sen University Da'an Gene Co., Ltd., CE certificate, detection limit is 500 copies / ml).

[0022] In the aforementioned predictive device, the IgG-syn is the detection of the IgG synthesis index in cerebrospinal fluid during the diagnosis of CNS IIDD. The specific detection method is rate turbidity immunoassay performed using an IMMAGE800 (Beckman Coulter, USA).

[0023] In the aforementioned prediction device, the CMV infection status, EBV infection status, spinal cord involvement status, and IgG-syn are all data used in diagnosing CNS IIDD.

[0024] A second objective of this invention is to provide a method for predicting the risk of death in patients with CNS IIDD after haplo-HSCT.

[0025] The method for predicting mortality risk in CNS IIDD patients after haplo-HSCT provided by this invention includes the following steps:

[0026] 1) Obtain the CMV infection status, EBV infection status, spinal cord involvement status, and IgG-syn at the time of diagnosis of CNS IIDD in the test subject;

[0027] 2) Based on the data obtained in step 1), assign values ​​according to the following criteria to obtain the test subject's f(CMV infection status), f(EBV infection status), f(spinal cord involvement status), and f(IgG-syn):

[0028] When the test subject has "CMV infection", f(CMV infection status) is 1 point; when the test subject does not have "CMV infection", f(CMV infection status) is 0 points.

[0029] When "the test subject has EBV infection", f(EBV infection status) is 1 point; when "the test subject does not have EBV infection", f(EBV infection status) is 0 points.

[0030] When "the test subject has spinal cord involvement", f(spinal cord involvement status) is 1 point; when "the test subject does not have spinal cord involvement", f(spinal cord involvement status) is 0 points.

[0031] When the test subject's IgG-syn is positive, f(IgG-syn) is 1 point; when the test subject's IgG-syn is negative, f(IgG-syn) is 0 points.

[0032] 3) Calculate the CELS score of the test subject according to Formula I based on f(CMV infection status), f(EBV infection status), f(spinal cord involvement status), and f(IgG-syn);

[0033] CELS score = f(CMV infection status) + f(EBV infection status) + f(spinal cord involvement status) + f(IgG-syn) Equation I;

[0034] 4) Based on the test taker's CELS score, test takers are grouped into risk groups: those with a CELS score of 3-4 are in the high-risk group, those with a CELS score of 1-2 are in the medium-risk group, and those with a CELS score of 0 are in the low-risk group.

[0035] Furthermore, the method also includes the following steps: 5) predicting the mortality risk of CNS IIDD patients based on the risk group of the test subjects: that is, test subjects in the high-risk group are CNS IIDD patients with high risk of death; test subjects in the intermediate-risk group are CNS IIDD patients with intermediate risk of death; and test subjects in the low-risk group are CNS IIDD patients with low risk of death.

[0036] A third objective of this invention is to provide a predictive system for the risk of death in patients with CNS IIDD following haplo-HSCT.

[0037] The prediction system for the risk of death in CNS IIDD patients after haplo-HSCT provided by the present invention includes the above-mentioned prediction device for the risk of death in CNS IIDD patients after haplo-HSCT, a CMV infection detection device, an EBV infection detection device, and an IgG-syn detection device.

[0038] In the aforementioned prediction system for the risk of death in CNS IIDD patients after haplo-HSCT, the CMV infection detection device is a CMV DNA detection device; the detection of CMV DNA in cerebrospinal fluid includes reagents and / or instruments for detecting CMV DNA. The reagents and / or instruments for detecting CMV DNA can be conventional reagents and / or instruments for detecting CMV DNA in the prior art. In a specific embodiment of the present invention, the reagents and / or instruments for detecting CMV DNA are real-time quantitative PCR, and the kit used is a cytomegalovirus (CMV) real-time PCR kit (Shanghai Zhongjie Biotechnology Co., Ltd.).

[0039] In the aforementioned prediction system for the risk of death in CNS IIDD patients after haplo-HSCT, the EBV infection detection device is an EBV DNA detection device; the EBV DNA detection in cerebrospinal fluid includes reagents and / or instruments for detecting EBV DNA. The reagents and / or instruments for detecting EBV DNA can be conventional reagents and / or instruments for detecting EBV DNA in the prior art. In a specific embodiment of the present invention, the reagents and / or instruments for detecting EBV DNA are real-time quantitative PCR, and the kit used is an EBV DNA diagnostic kit (PCR fluorescent probe) (Sun Yat-sen University Da'an Gene Co., Ltd.).

[0040] In the aforementioned prediction system for the risk of death in CNS IIDD patients after haplo-HSCT, the IgG-syn detection device is a cerebrospinal fluid IgG-syn detection device; the reagents and / or instruments used to detect IgG-syn can be conventional reagents and / or instruments used for detecting IgG-syn in the prior art. In a specific embodiment of the present invention, the specific detection method is rate turbidity immunoassay using an IMMAGE800 (Beckman Coulter, USA).

[0041] A fourth objective of this invention is to provide a method for using the above-described system for predicting the risk of death in CNS IIDD patients after haplo-HSCT.

[0042] The method of using the above-mentioned prediction system for mortality risk in CNS IIDD patients after haplo-HSCT provided by the present invention includes the following steps:

[0043] The following data were obtained from patients diagnosed with CNS IIDD after haplo-HSCT: CMV infection status, EBV infection status, spinal cord involvement, and IgG-syn.

[0044] Based on the data, the mortality risk of CNS IIDD patients after haplo-HSCT is determined using the aforementioned prediction device and the aforementioned prediction method for the mortality risk of CNS IIDD patients after haplo-HSCT.

[0045] The application of the above-mentioned device for predicting the risk of death in CNS IIDD patients after haplo-HSCT or the above-mentioned system for predicting the risk of death in CNS IIDD patients after haplo-HSCT in the preparation of products for predicting or assisting in predicting the risk of death in CNS IIDD patients after haplo-HSCT is also within the scope of protection of this invention.

[0046] The application of the above-mentioned device for predicting the risk of death in CNS IIDD patients after haplo-HSCT, the above-mentioned CMV infection detection device, EBV infection detection device and IgG-syn detection device in the preparation of products for predicting or assisting in predicting the risk of death in CNS IIDD patients after haplo-HSCT is also within the scope of protection of this invention.

[0047] When using the device or system of this invention to predict the mortality risk of CNS IIDD patients after haplo-HSCT, the risk is determined by acquiring records of spinal cord involvement at the time of CNS IIDD diagnosis or reviewing records of spinal cord involvement at the time of CNS IIDD diagnosis during follow-up visits, measuring or reviewing CMV infection status, EBV infection status, and IgG-syn at the time of CNS IIDD diagnosis, and using the aforementioned device for predicting the mortality risk of CNS IIDD patients after haplo-HSCT. The higher the CELS score of a CNS IIDD patient, the greater the risk of death. Specifically, test subjects with a CELS score of 0 are classified as low-risk, those with a CELS score of 1-2 as intermediate-risk, and those with a CELS score of 3-4 as high-risk. Patients in the high-risk group have a high risk of death, those in the intermediate-risk group have a medium risk of death, and those in the low-risk group have a low risk of death.

[0048] This invention develops and validates a CELS scoring model for the mortality risk of CNS IIDD patients after haplo-HSCT, which can identify high-risk patients early and provide timely treatment simply by taking a medical history, conducting virus testing, and performing cerebrospinal fluid testing. Attached Figure Description

[0049] Figure 1 A flowchart for patient enrollment, model development, and validation.

[0050] Figure 2 To assess the predictive accuracy of the CELS model. (A) ROC curve in the development cohort predicting the risk of death in CNS IIDD patients after haplo-HSCT, with an AUC of 0.864. (B) ROC curve in the validation cohort predicting the risk of death in CNS IIDD patients after haplo-HSCT, with an AUC of 0.871.

[0051] Figure 3Calibration curves for a CELS model used to predict the risk of death in CNS IIDD patients after haplo-HSCT. (A) CELS model in the development cohort. (B) CELS model in the validation cohort. The x-axis represents the probability of death in CNS IIDD patients after haplo-HSCT predicted by the model; the y-axis represents the probability of death in actual CNS IIDD patients after haplo-HSCT. An ideal calibration plot is represented by a 45° diagonal line. Solid lines represent actual calibration plots, and dashed lines represent ideal calibration plots.

[0052] Figure 4 This is a decision curve analysis of the CELS model used to predict the risk of death in CNS IIDD patients after haplo-HSCT in the development cohort. Black line (no benefit): assumes no ITP patients develop CAP. Gray line (all benefit): assumes all ITP patients develop CAP. These two lines are for reference only. Detailed Implementation

[0053] Unless otherwise specified, the experimental methods used in the following examples are conventional methods.

[0054] Unless otherwise specified, all materials and reagents used in the following examples are commercially available.

[0055] In the quantitative experiments in the following examples, three replicate experiments were set up, and the average value of the results was taken.

[0056] Example 1: Development and validation of a CELS scoring model for predicting the risk of death in CNS IIDD patients after haplo-HSCT.

[0057] This invention develops and validates a CELS scoring model for predicting the risk of death in CNS IIDD patients after haplo-HSCT, the process of which is as follows: Figure 1 As shown. The specific steps are as follows:

[0058] I. Patient Sample and Research Methods for Developing a CELS Scoring Model to Predict Mortality Risk in CNS IIDD Patients After Haplo-HSCT

[0059] 1. Patient sample

[0060] Between January 2008 and October 2019, a total of 4,532 patients at the Clinical Center of Peking University People's Hospital underwent haplo-HSCT for hematologic malignancies. Among them, 184 patients were diagnosed with CNS IIDD (Supplemental). Figure 1We first conducted a nested case-control study to identify risk factors for IIDD and randomly selected three control groups for each case based on transplant time (±1 month) and follow-up time (±3 months). Then, we analyzed 184 patients with CNSIIDD to establish and validate a prognostic model. The derivative cohort included 124 patients who received allogeneic hematopoietic stem cell transplantation between 2014 and 2019, and the validation cohort included 60 patients who received allogeneic hematopoietic stem cell transplantation between 2008 and 2013. Figure 1 We only analyzed the first episode of IIDD that occurred multiple times during the study period. Patient information collected in this study included demographic characteristics such as age, sex, hematologic disorders, transplant type, donor and recipient ABO blood type, donor and recipient sex, white blood cell and platelet engraftment time, viral infection status, graft-versus-host disease status, laboratory and imaging results at the time of CNS diagnosis, and treatment regimens for CNS IIDD. This study complied with the ethical review standards of the Ethics Committee of the Clinical Center of Peking University People's Hospital.

[0061] The clinical characteristics of the patient population in this study are shown in Table 1. Patients with CNS IIDD after haplo-HSCT and those without CNS IIDD after haplo-HSCT (control group) were comparable in terms of sex, donor / recipient ABO blood type, donor / recipient sex, leukocyte graft survival time, hepatitis B virus infection status, herpes simplex virus infection, herpes zoster virus infection, and human herpesvirus 6 infection status (P>0.05). However, patients with CNS IIDD were significantly younger than the control group (P<0.001), and there were significant differences in transplantation methods (P=0.006). Platelet graft survival time was significantly longer in patients with CNS IIDD than in the control group (P=0.021). GVHD infection was also significantly higher in patients with CNS IIDD than in the control group (P<0.001). Furthermore, CMV infection and EBV infection were significantly higher in patients with CNS IIDD than in the control group (P=0.001) (P=0.025).

[0062] Table 1. Baseline characteristics of patients

[0063]

[0064] 2. Definition and Diagnosis

[0065] IIDD of the central nervous system is induced by antibodies or T cells that specifically target myelin, and involves immune-mediated attack on the myelin sheath. The diagnostic definition of IIDD is as follows: (1) new neurological symptoms, namely seizures, vision loss, altered level of consciousness (ALOC), tremor, weakness of the limbs, ataxia and speech disorders; (2) abnormal brain or spinal cord MRI within 1 month after the onset of neurological symptoms - ≥1 case of high signal T2 lesion ≥1 typical area in the brain or spinal cord (periventricular, paracortical or infratentorial); (3) normal or abnormal cerebrospinal fluid examination, the latter including increased lymphocytes and monocytes and mild protein elevation; (4) response to immunosuppressive therapy; and (5) no other cause can explain the event: other causes of CNS disease are excluded, including CNS infection, neurotoxicity [calcineurin inhibitors (CNIs) etc.], metabolic encephalopathy (organ dysfunction or failure, electrolyte disturbance, ketoacidosis etc.), ischemic demyelinating disease, and patients who do not meet the diagnostic criteria are excluded from the analysis. Brain biopsy or autopsy is not a mandatory criterion for the diagnosis of IIDD, and none of the patients in our study underwent biopsy or autopsy. Each patient in this study was evaluated by three specialists in hematology, neurology, and radiology based on their clinical presentation, laboratory results, and radiological findings. The final diagnosis was determined based on the opinions of all three specialists.

[0066] 3. Data Analysis

[0067] This study investigated high-risk factors for mortality in CNS IIDD patients described in previous literature. These factors could be obtained through detailed medical history taking and routine laboratory tests. The factors ultimately included patients' CMV infection status, EBV infection status, spinal cord involvement, and IgG-syn, all of which were retrospectively collected from electronic medical records at each center. In logistic regression analysis, variables with more than 30% missing values ​​were excluded; only complete cases were used to develop and validate the predictive model. Logistic univariate and multivariate regression analyses were performed on the development cohort. Variables with p-values ​​< 0.10 in the univariate analysis were included in the multivariate regression model. The final predictive model was selected using stepwise logistic regression based on the Akaike information criterion. The regression coefficients of each factor in the multivariate analysis results were used to assign scores to the model. The model underwent bootstrap (n = 1000) internal validation and geographic external validation in both the development and validation cohorts. Validation metrics included discrimination, calibration, and net clinical benefit. All data analyses were performed using IBM SPSS 24.0 and R software.

[0068] II. Acquisition and validation of the CELS scoring model for predicting the risk of death in patients with CNS IIDD after haplo-HSCT

[0069] 1. Risk factors for death from CNS IIDD

[0070] Univariate analysis showed that age ≥50, cGVHD at 90 days post-transplantation, CMV and EBV infection, CSF IgG syn, ALC <700 / μL, donor lymphocyte infusion (DLI), and spinal cord injury were significantly associated with the prognosis of post-transplant CNS IIDDs. Variables with p < 0.10 were further included in multivariate analysis. The results indicated that CMV and EBV infection, CSF IgG syn, and spinal cord injury were independent prognostic factors for CNS IIDDs after haploHSCT (Table 2). Furthermore, we found no significant association between abnormal immune reconstitution and IIDD prognosis.

[0071] Table 2. Regression coefficients and scores of the model based on independent risk factors in the development cohort.

[0072]

[0073]

[0074] 3. Model Establishment

[0075] A model was built by assigning scores to the regression coefficients of independent risk factors for CNS IIDD following haplo-HSCT, thus establishing a model (Table 2): Each factor was scored using a logarithmic scale based on the regression coefficients. These four factors determined the overall risk score, ranging from 0 to 4. Based on the identified risk factors, the model was named the CELS model. Scoring patients in the development cohort using the CELS model revealed an increased risk of death as the CELS score increased (Table 3): In the development cohort, the mortality frequency was 0 for patients with a score of 0 during follow-up; in contrast, 22 out of 79 patients with scores of 1-2 (27.8%) died, and 20 out of 24 patients with scores of 3-4 (83.3%) died. In the validation cohort, there were no deaths among the 10 patients with a score of 0, while 12 out of 42 patients with scores of 1-2 (28.6%) died, and 7 out of 8 patients with scores of 3-4 (87.5%) died. (Table 3)

[0076] Table 3. Number of CNS IIDD patients who died in different risk stratification zones

[0077]

[0078] 4. Internal and external validation of the model

[0079] The established CELS integral model was validated using a bootstrap method with 1000 iterations based on the development and validation queues. The performance of the CELS integral model was evaluated by analyzing discrimination and calibration. Discrimination was calculated using the ROC curve (area under the curve (AUC)). Calibration was evaluated using a calibration plot, with a perfect calibration plot represented by a 45° diagonal line. Net benefit was evaluated using decision curve analysis (DCA).

[0080] Results showed that, in the development cohort, the CELS scoring model demonstrated good discriminative power in predicting the risk of death in CNS IIDD patients after haplo-HSCT, with an AUC of 0.864 (95% CI 0.803–0.925). Figure 2 A). Furthermore, the calibration curves show good agreement between the actual probabilities and the predictions of the model of this invention (A). Figure 3 A). In the validation cohort, the AUC of the CELS integral model was 0.871 (95% CI 0.806–0.931), indicating good discrimination. Figure 2 B). Figure 3 B shows the calibration curve of the validation queue, which reflects a relatively good agreement between actual risk and predicted risk. Figure 3 B). Additionally, similar to the development cohort, the validation cohort had CELS scores ranging from 0 to 4. Among the 10 patients with a score of 0, no deaths occurred, while 12 out of 42 patients (28.6%) with scores of 1-2 died, and 7 out of 8 patients (87.5%) with scores of 3-4 died (Table 3). Based on the results obtained from the development and validation cohorts, the CELS scoring model of this invention defines the risk of death in CNS IIDD patients after haplo-HSCT into three categories: a CELS score of 0 indicates a low risk of death in ITP patients, a CELS score of 1-2 indicates a medium risk of death in ITP patients, and a CELS score of 3-4 indicates a high risk of death in CELS patients. This is the scoring system of the CELS scoring model of this invention (hereinafter referred to as the CELS scoring system). ITP patients with a CELS score of 1-2 have a higher risk of death than patients with a CELS score of 0; ITP patients with an ACPA score of 3-4 have a higher risk of death than patients with a CELS score of 1-2.

[0081] DCA analysis results indicate that patients can achieve certain clinical benefits using the CELS scoring model. Figure 4 ).

[0082] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the technical principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A device for predicting mortality risk in CNS IIDD patients after haplo-HSCT, comprising the following processing module: (1) Data input module: This module is used to input the CMV infection status, EBV infection status, spinal cord involvement status and IgG-syn when the test subject is diagnosed with CNS IIDD; The test subjects were patients who developed CNS IIDD after haplo-HSCT; (2) Data recording module: This module is used to receive and store the CMV infection status, EBV infection status, spinal cord involvement status and IgG-syn of the test subject output from the data input module; (3) Data assignment module: This data assignment module consists of a CMV infection status assignment module, an EBV infection status assignment module, a spinal cord involvement status assignment module, and an IgG-syn assignment module. The CMV infection status assignment module is used to retrieve the CMV infection status of the test subject stored in the data recording module, assign a value to the CMV infection status, and output f(CMV infection status): when "the test subject has CMV infection", f(CMV infection status) is 1 point; when "the test subject does not have CMV infection", f(CMV infection status) is 0 points. The EBV infection status assignment module is used to retrieve the EBV infection status of the test subject stored in the data recording module, assign a value to the EBV infection status, and output f(EBV infection status): when "the test subject has EBV infection", f(EBV infection status) is 1 point; when "the test subject does not have EBV infection", f(EBV infection status) is 0 points. The spinal cord involvement assignment module is used to retrieve the spinal cord involvement information of the test subject stored in the data recording module, assign a value to the spinal cord involvement information, and output f(spinal cord involvement information): when "the test subject has spinal cord involvement", f(spinal cord involvement information) is 1 point; when "the test subject has no spinal cord involvement", f(spinal cord involvement information) is 0 points. The IgG-syn assignment module is used to retrieve the IgG synthesis index of the test subject stored in the data recording module, assign a value to the IgG synthesis index, and output f(IgG-syn): when "the test subject's IgG-syn is positive", f(IgG-syn) is 1 point; when "the test subject's IgG-syn is negative", f(IgG-syn) is 0 points. (4) Data calculation module: This module is used to receive f(CMV infection status) output from the CMV infection status assignment module, f(EBV infection status) output from the EBV infection status assignment module, f(spinal cord involvement status) output from the spinal cord involvement assignment module, and f(IgG-syn) output from the IgG-syn assignment module; and then calculate the test subject's CELS score according to Equation I; CELS score = f(CMV infection status) + f(EBV infection status) + f(spinal cord involvement status) + f(IgG-syn) Equation I; The CELS score indicates the risk of death in patients with CNS IIDD following haplo-HSCT. (5) Data grouping module: This module is used to receive the CELS score of the tester output from the data calculation module, then group the tester into risk groups based on the CELS score, and output the risk grouping results; The criteria for risk grouping test subjects based on CELS scores are as follows: test subjects with CELS scores of 3-4 are in the high-risk group, test subjects with CELS scores of 1-2 are in the medium-risk group, and test subjects with CELS scores of 0 are in the low-risk group. (6) Conclusion output module: This module is used to receive the risk grouping results output from the data grouping module and output the conclusion based on the risk grouping results: that is, the test subjects in the high-risk group are CNS IIDD patients with a high risk of death; the test subjects in the intermediate-risk group are CNS IIDD patients with a medium risk of death; and the test subjects in the low-risk group are CNS IIDD patients with a low risk of death.

2. The apparatus according to claim 1, characterized in that: The CMV or EBV infection refers to CMV or EBV infection in all other organ systems except for the central nervous system.

3. The apparatus according to claim 1 or 2, characterized in that: The IgG-syn mentioned is cerebrospinal fluid IgG-syn.

4. A method for predicting the risk of death in CNS IIDD patients after haplo-HSCT, comprising the following steps: 1) Obtain the CMV infection status, EBV infection status, spinal cord involvement status, and IgG-syn at the time of diagnosis of CNS IIDD in the test subject; 2) Based on the data obtained in step 1), assign values ​​according to the following criteria to obtain the test subject's f(CMV infection status), f(EBV infection status), f(spinal cord involvement status), and f(IgG-syn): When the test subject has CMV infection, f (CMV infection status) is 1 point; when the test subject does not have CMV infection, f (CMV infection status) is 0 points. When "the test subject has EBV infection", f (EBV infection status) is 1 point; when "the test subject does not have EBV infection", f (EBV infection status) is 0 points. When "the test subject has spinal cord involvement", f (spinal cord involvement status) is 1 point; when "the test subject does not have spinal cord involvement", f (spinal cord involvement status) is 0 points. When "the test subject's IgG-syn is positive", f(IgG-syn) is 1 point; when "the test subject's IgG-syn is negative", f(IgG-syn) is 0 points. 3) Calculate the CELS score of the test subject according to Formula I based on f(CMV infection status), f(EBV infection status), f(spinal cord involvement status), and f(IgG-syn); CELS score = f(CMV infection status) + f(EBV infection status) + f(spinal cord involvement status) + f(IgG-syn) Formula I; 4) Based on the test subjects' CELS scores, test subjects were grouped into risk groups: those with a CELS score of 3-4 were in the high-risk group, those with a CELS score of 1-2 were in the medium-risk group, and those with a CELS score of 0 were in the low-risk group.

5. A prediction system for the risk of death in patients with CNS IIDD after haplo-HSCT, comprising the device according to any one of claims 1-3, a CMV detection device, an EBV detection device, and an IgG-syn detection device.

6. The system according to claim 5, characterized in that: The CMV or EBV infection refers to CMV or EBV infection in all other organ systems except for the central nervous system.

7. The system according to claim 5 or 6, characterized in that: The IgG-syn mentioned is cerebrospinal fluid IgG-syn.

8. A method of using the system according to any one of claims 5-7, comprising the following steps: acquiring the following data when a patient is diagnosed with CNS IIDD after haplo-HSCT: CMV infection status, EBV infection status, spinal cord involvement status, and IgG-syn; and predicting the risk of death in a CNS IIDD patient after haplo-HSCT using the device according to any one of claims 1-3 according to the method of claim 4 based on the data.

9. The use of the apparatus of any one of claims 1-3 or the system of any one of claims 5-7 in the preparation of products for predicting or assisting in predicting the risk of death in CNS IIDD patients after haplo-HSCT.

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