CN114255883A - Voriconazole maintenance dose prediction mathematical model and construction method and application thereof - Google Patents

Voriconazole maintenance dose prediction mathematical model and construction method and application thereof Download PDF

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CN114255883A
CN114255883A CN202111237650.4A CN202111237650A CN114255883A CN 114255883 A CN114255883 A CN 114255883A CN 202111237650 A CN202111237650 A CN 202111237650A CN 114255883 A CN114255883 A CN 114255883A
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vcz
voriconazole
dose
crp
body weight
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周丽娟
李敏
曹巍
李慧红
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Zhengzhou Central Hospital
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Abstract

The invention discloses a mathematical model for predicting voriconazole maintenance dosage by integrating multiple factors and application, relating to the technical field of medical treatment, wherein the model comprises the following components: (1) analysis of variance to determine steady-state blood voriconazole concentration (VCZ-C) of CYP2C19 gene polymorphism in invasive fungal infection patientsmin) The influence of (a); (2) confirmation of CRP, PCT, IL-6 and combination of proton pump inhibitor on VCZ-Cmin(ii) an effect; (3) confirming the influence of different CYP2C19 genotypes on the curative effect and adverse reaction of patients by guiding voriconazole use and non-guiding medication; (4) predicting impact VCZ-CminRisk factors of (a) and risk factors affecting the maintenance dosage of voriconazole; (5) and establishing a mathematical model for predicting the voriconazole maintenance dose and verifying the model. The influence factors and the mathematical prediction model disclosed by the invention improve the accuracy of clinically using voriconazole to maintain the dosage, can quickly stabilize the drug concentration in a target valley concentration range, enable the voriconazole to be more accurate, safe and effective, and reduce adverse reactions.

Description

Voriconazole maintenance dose prediction mathematical model and construction method and application thereof
Technical Field
The invention relates to the technical field of medical treatment, in particular to a mathematical model for predicting voriconazole maintenance dosage by integrating multiple factors and application thereof.
Background
Voriconazole belongs to the second generation triazole broad-spectrum antifungal drug, and is a first-line drug which is commonly used for treating invasive mycosis such as invasive pulmonary aspergillosis, candidemia and the like. Due to the saturability of the metabolism of voriconazole and the nonlinear pharmacokinetics of voriconazole, the blood concentration of voriconazole has great correlation with clinical efficacy and safety. Many factors influence the in vivo metabolic process of voriconazole, so that the blood concentration of voriconazole varies highly in different patients and even in the same patient at different times. The clinical aim of clinical accurate treatment cannot be achieved by using the same dose for many patients according to voriconazole specifications approved by the national food and drug administration, and repeatedly adjusting the voriconazole dose for many times by continuously determining whether the blood concentration of voriconazole reaches the target valley concentration range.
At present, domestic and foreign documents report different factors influencing the blood concentration of voriconazole, whether the CYP2C19 gene state can guide the dosage of voriconazole still needs to be researched, no document forms a consistent conclusion on the factors clearly influencing the stable maintenance dosage of voriconazole, and a mathematical model for establishing the drug use of voriconazole based on the risk factors is still a blank. Therefore, in order to quickly guide the stable maintenance dosage of the voriconazole to be used and ensure the safety, effectiveness, economy and applicability of the drug administration, the establishment of a mathematical model for predicting the maintenance dosage of the voriconazole by integrating various factors has important significance so as to facilitate the accurate drug administration of patients. Meanwhile, the repeated blood drawing of the patient can be avoided, the medication compliance of the patient is improved, the hospitalization period is shortened, and the medical resources are saved.
Disclosure of Invention
The invention aims to provide a mathematical model for predicting the voriconazole sustained dose by integrating multiple factors, and provides accurate prediction of the dose for clinical patients using voriconazole.
The invention is realized by the following technical scheme:
a mathematical model for predicting voriconazole maintenance dosage using a combination of factors, comprising the steps of:
confirming various influencing factors influencing the maintenance dose of voriconazole, which is characterized by comprising the following steps:
(1) determination of whether the CYP2C19 gene polymorphism is used for Voriconazole steady state plasma concentration (VCZ-C) of invasive fungal infection patients by using anovamin) An influence is produced. Characterized by the polymorphism or phenotype of the CYP2C19 gene: UM: ultrafast metabolic type (*17/*17) (ii) a EM: fast metabolism type (A)*1/*17) (ii) a NM: normal metabolic type (A)*1/*1) (ii) a IM: intermediate metabolic form (A)*1/*2，*1/*3，*2/*17，3/*17) (ii) a PM: slow metabolism type (*2/*2，*2/*3，*3/*3)；
(2) Confirmation of inflammatory factors (CRP, PCT and IL-6) vs VCZ-CminThe influence of (c). The method comprises the following steps: analysis of the respective inflammatory factors and blood levels (C) using Pearson correlation coefficientsmin) The correlation between the two is evaluated by a correlation coefficient r, the larger the absolute value of r is, the stronger the correlation is, | r |0.8-1.0 is, the medium strength correlation is | r |0.4-0.6, and | r |0.2-0.4 is weak. Analysis of variance comparison of subtherapeutic Range (C)minLess than 0.5mg/L) and the treatment range (0.5mg/L is less than or equal to Cmin< 5.0mg/L) and a supra-therapeutic range (C)minNot less than 5.0mg/L) of CRP, PCT and IL-6 among the three groups, and the difference with P less than 0.05 has statistical significance. It is characterized by three inflammatory factors, CRP: c-reactive protein; PCT: procalcitonin; IL-6: interleukin-6;
(3) confirmation of the Combined use of different classes of Proton Pump Inhibitors (PPIs) on VCZ-CminThe influence of (c). The method comprises the following steps: ANOVA comparison of post-dose normalization VCZ-C between different proton pump inhibitor groupsmin(Dose-normalized VCZ-Cmin) The difference (2) has statistical significance when P is less than 0.05. Dose-normalized VCZ-CminComputingThe formula is as follows:
Dose-normalized VCZ-Cmin＝VCZ-Cmin(mg/L)/average daily dose (mg)/body weight (Kg);
chi fang (X)2) The test compares the differences between the different classes of proton pump inhibitor groups in achieving sub-therapeutic range, therapeutic range and over-therapeutic range ratios. Characterized in that the Proton Pump Inhibitors (PPIs) comprise: omeprazole, esomeprazole, pantoprazole, rabeprazole.
(4) The influence of the phenotype-oriented use and non-oriented use of VCZ of different CYP2C19 genes on the curative effect and adverse reaction of patients is confirmed. The method comprises the following steps: chi shape2The difference of VCZ curative effect and various adverse reactions among different gene phenotype groups is compared by inspection. It is characterized in that the adverse reaction comprises: hepatotoxicity, adverse visual effects, neurotoxicity and others;
(5) multiple linear stepwise regression prediction of impact VCZ-CminThe risk factors of (a) are CRP, average daily dose/body weight and CYP2C19 gene phenotype. Regression equation Y ═ 1.616+0.015X9+0.169X10+0.379X5(F＝24.649，P＜0.001)。Y： VCZ-Cmin；X9：CRP；X10: average daily dose/body weight; x5: CYP2C19 gene phenotype;
(6) multiple linear stepwise regression predicts risk factors affecting VCZ maintenance dose as CYP2C19 gene phenotype, CRP, and body weight. The regression equation is that Y is 360.126-30.325X5-0.215X8+0.888X4(F-12.190, P < 0.001), Y: VCZ stable maintenance dose; x5: CYP2C19 gene phenotype; x8：CRP；X4: body weight.
2. A voriconazole sustained dose prediction mathematical model and a construction method and application thereof are characterized by comprising the following steps:
(1) multivariate linear regression establishes a mathematical model for predicting VCZ maintenance dose based on a variety of risk factors. Regression equation Y-286.779-0.734X1+2.925X2-22.223X3-0.3195X4(F-20.868, P < 0.001). Y: VCZ stable maintenance dose; x1: age (year of age); x2: body weight (Kg); x3: CYP2C19 gene phenotype (UM/EM/NM: 0, IM: 1, PM: 2); x4：CRP (mg/L)；
(2) The mathematical model for maintenance dose prediction for patients using VCZ was validated. the t-test compares the difference between the predicted and actual values.
Compared with the prior art, the invention has the advantages that:
(1) the multi-factor voriconazole sustained dose prediction system established by the method is based on the combination of the main influencing factors of age, weight, CYP2C19 gene phenotype, inflammatory factors (CRP, PCT and IL-6), average daily dose/weight and any influencing factor, and fills the gap of a multi-factor accurate prediction-based voriconazole sustained dose model in medicine.
(2) The method establishes a prediction model, can realize accurate medication of each patient, achieves individualized medication effect, and ensures safe, effective, economic and applicable clinical use of voriconazole.
(3) The prediction model established by the method can avoid the pain of repeated blood drawing of the patient, improve the medication compliance of the patient, shorten the hospitalization period and save medical resources. Therefore, in order to rapidly guide the stable maintenance dosage of voriconazole to be used, it is of great significance to establish a mathematical model for predicting the maintenance dosage of voriconazole by integrating various factors, so as to facilitate accurate medication of patients.
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The following describes embodiments of the present invention in further detail with reference to the accompanying drawings.
Fig. 1 is a flow chart of an embodiment of a mathematical model prediction system for voriconazole sustained dose optimization according to the present invention;
FIG. 2 is an average VCZ-CminA comparison of the phenotype group and the non-gene-targeted group of the different CYP2C19 genes;
FIG. 3 is a graph comparing the ratio of sub-therapeutic range, therapeutic range and super-therapeutic range of voriconazole plasma concentration obtained between different CYP2C19 gene phenotype groups and non-gene targeting groups;
FIG. 4 shows CRP, PCT and IL-6 with VCZ-C, respectivelyminOfA correlation graph;
FIG. 5 is a graph showing comparison of a plurality of index values measured 4 times per patient (four patients AA, AB, AC and AD);
FIG. 6 is a comparison of CRP, PCT and IL-6 in the sub-therapeutic range, therapeutic range and supra-therapeutic range of voriconazole plasma concentrations; (A) CRP (B) PCT (C) IL-6;
FIG. 7 prediction of VCZ-C for CRP, PCT, and IL-6minAn ROC curve of not less than 5.0 mg/L; (A) CRP (B) PCT (C) IL-6;
FIG. 8 is a graph comparing the dose normalized mean plasma concentrations between the control group and different groups of PPIs;
FIG. 9 is a graph showing the frequency of adverse reactions occurring between different groups; (A) different VCZ treatment intervals (B) between different genotypic panel groups for CYP2C 19.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
1 Subjects and methods
1.1 subject: invasive fungal infections in hospital in zheng zhou city, 3 months-2021 months in 2018 in patients with voriconazole. Grouping standard: firstly, the age is more than or equal to 18 years; the treatment lasts for more than or equal to 14 days; ③ taking at least one steady-state blood sample from each patient; fourthly, the data is complete. Exclusion criteria: allergy to voriconazole; using other antifungal medicines together; taking at least one blood sample meeting the requirement in steady state from each patient; (iv) severe liver function impairment (ALT or AST is more than 5 times higher than the upper normal limit before voriconazole treatment, TBIL is more than 3 times higher than the upper normal limit; pregnant or lactating women; sixth, participating in other clinical trials; all patients or families sign informed consent, ethical approval No. (201903), clinical trial registration No. (NCT 04004078).
1.2 grouping and administration: all subjects pressed whether or notGene testing is divided into gene-targeted and non-gene-targeted groups. Gene targeting groups were divided based on the CYP2C19 gene phenotype: UM: ultrafast metabolic type (*17/*17) (ii) a EM: fast metabolism type (A)*1/*17) (ii) a NM: normal metabolic type (A)*1/*1) (ii) a IM: intermediate metabolic form (A)*1/*2，*1/*3，*2/*17，3/*17) (ii) a PM: slow metabolism type (*2/*2，*2/*3，*3/*3). Non-gene-targeted group dosing: the loading dose is 6mg/Kg for intravenous injection or 400mg for oral administration, and the dosage is 12 h; the maintenance dose is 4mg/Kg for intravenous injection or 200mg for oral administration, and the dosage is 12 h. Patients in the EM, IM and NM groups were dosed as in the non-gene-targeted group. Patients in PM group (adjustment of voriconazole dose) were dosed: the loading dose is 4mg/Kg for intravenous injection or 300mg for oral administration, and the dosage is 12 h; the maintenance dose is 3mg/Kg by intravenous injection or 100mg by oral administration, and the dosage is 12 h. The PM group (dose of voriconazole was not adjusted) was dosed at the same NM group. The UM group was dosed with a 50% normal dose.
1.3 validity judgment: efficacy is assessed according to clinical symptoms, laboratory data and galactomannan experiments (GM), bacteriological examination, CT, etc. Complete response is complete disappearance of signs and symptoms. Partial responses were improved in signs and symptoms, and lung infiltration was improved by 50%. Failure of treatment is no improvement in signs of symptoms, toxicity or death from related infections.
1.4 evaluation of safety: related hepatotoxicity, visual disturbance, adverse visual effects (pseudoscopic vision, etc.), and other adverse effects (rash, dry mouth, alopecia, renal function injury, etc.). Hepatotoxicity was assessed according to the national cancer institute adverse event criteria (CTCAE version 5.0).
1.5 statistical methods: according to SPSS19.0 version, continuous variables are used
Figure RE-RE-GSB0000197010280000042
Median (min-max), interquartile range. The classified variables are subjected to chi-square test or Fisher precise test, two groups of tests are subjected to t test or Mann-Whitney U test, and three groups of tests are subjected toThe test is performed by one-way analysis of variance or Kruskal-Wallis test, CRP, PCT and IL-6 and VCZ-CminCorrelation between the two is analyzed by Pearson and multiple stepwise regression analysis for influence on VCZ-CminAnd significant factors of the stable maintenance dosage, and a prediction system and a method for VCZ stable maintenance dosage are established by multiple linear regression analysis. The difference is statistically significant when P is less than 0.05.
2 results
2.1 general clinical data of patients: 306 patients, 190 women, age 18-98 years. There was no significant difference in each index (P > 0.05) between the gene-targeted, non-gene-targeted, UM/EM/NM, IM and PM (adjusted dose) groups, as shown in Table 1.
TABLE 1 general clinical data of patients between different groups
Figure RE-RE-GSB0000197010280000041
Figure RE-RE-GSB0000197010280000051
Note: values are for VCZ treatment 1 d. 1) Chi 2 test 2) t test
2.2 plasma concentration comparison of VCZ: mean plasma concentrations between the gene-targeted and non-gene-targeted groups were not significantly different (3.91 ± 2.31mg/L vs.4.11 ± 2.43mg/L, t ═ 0.756, P ═ 0.450) as shown in fig. 2. VCZ-C in non-Gene-targeting groupminThe ratios in the subtherapeutic range and the supratherapeutic range were 1.90% and 27.82%, respectively. The ratio of the PM group (adjusted dose patients) in the treatment range was significantly higher than the non-gene-targeted, UM/EM/NM and IM groups (93.75%, 70.25%, 72.30%, 67.19% and 72.59%, P < 0.05), respectively, as shown in fig. 3. Indicating that the blood concentration of VCZ is affected by the PM phenotype in the CYP2C19 gene phenotype.
2.3 inflammatory factors (CRP, PCT and IL-6) and VCZ-CminCorrelation between them: pearson correlation analysis showed that CRP, PCT and IL-6 were all related to VCZ-CminHas good correlation (CRP: r is 0.428, P is less than 0.001, 370 cases; PCT: r is 0.423, P is less than 0.001, 318 cases; IL-6: r 0.463, P < 0.001, 190 cases), see fig. 4A, 4B and 4C.
2.4 VCZ-CminVariability in the same patient with inflammatory factors (CRP, PCT, and IL-6): 4 VCZ-C determinations of 4 patients during hospitalizationminMapping with each of the corresponding inflammation indices (CRP, PCT and IL-6) revealed VCZ-Cmin(iii) high variability at different time points in 4 patients, and VCZ-CminThe trend of (A) is substantially consistent with the trend of CRP, PCT and IL-6, respectively, as shown in FIG. 5.
2.5 comparison of inflammatory factors (CRP, PCT and IL-6) in different treatment ranges: CRP, PCT and IL-6 were significantly different in the sub-therapeutic range, therapeutic range and super-therapeutic range, respectively (CRP: 28.09mg/L [2.68-37.30 ]]，n＝6vs.38.04 mg/L[0.80-336.70]，n＝250vs.65.33mg/L[2.94-453.00]，n＝114，χ2＝43.43，P＜0.001；PCT：0.12 ng/mL[0.02-0.13]，n＝5vs.0.19ng/mL[0.02-22.84]，n＝211vs.0.86ng/mL[0.02-43.00]，n＝102，χ2＝45.71，P＜0.001；IL-6：13.60pg/ml[6.80-14.90]，n＝3vs.18.90pg/ml[1.50-423.10]，n＝118vs. 49.60pg/ml[1.60-1362.00]N is 69, χ 2 is 26.63, P < 0.001). Studies have shown that the median values of CRP, PCT and IL-6 follow VCZ-CminGradually, see fig. 6.
2.6 CRP, PCT and IL-6 vs VCZ-CminROC prediction curve of not less than 5.0 mg/L: results the AUC and cut-off values for the CRP, PCT and IL-6ROC curves were 0.714. + -. 0.028 (95% CI: 0.659-0.768, P < 0.001), 48.82mg/L, respectively; 0.728 +/-0.031 (95% CI: 0.668-0.788, P < 0.001), 0.995 ng/mL; 0.722. + -. 0.039 (95% CI: 0.646-0.798, P < 0.001), 28.50 pg/mL. See fig. 7.
2.7 pair of PPIs with VCZ-CminThe influence of (a): patients in the control group (without PPIs), omeprazole group, esomeprazole group, rabeprazole group and pantoprazole group have no significant difference in general clinical data such as sex, age, weight, albumin, ALT, AST, ALP, GGT, CRP, Scr, BUN, CRP, PCT and IL-6(P > 0.05). We will use VCZ-CminConversion to dose-normalized VCZ-Cmin＝VCZ-Cmin(mg/L)/average day dose (mg)/body weight (Kg). Analysis of variance showed VCZ-C normalized by mean dose among the five groupsminThere was no significant difference (F ═ 1.802, P ═ 0.129). Dose-normalized VCZ-C for omeprazole and esomeprazole groupsminIt was significantly higher than the control group ((t 2.286, P0.023; t 2.186, P0.031)), as shown in fig. 8, but there was no significant difference in the ratio in the therapeutic range between the five groups (χ)2＝0.519， P＝0.972；χ2＝1.787，P＝0.775)。
2.8 clinical efficacy of VCZ: the overall good response (complete response + partial response) was not significantly different between the gene-targeted and non-gene-targeted groups (83.78% vs. 86.08%, χ 2 ═ 0.314, P ═ 0.575). There was no significant difference in clinical efficacy in four groups (UM/EM, NM, IM and PM groups (VCZ dose adjusted)) of patients (χ 2 ═ 0.702, P ═ 0.873). See table 2.
TABLE 2 comparison of clinical efficacy between groups
Figure RE-RE-GSB0000197010280000061
2.9 adverse reaction (ADR) evaluation: 56 of 322 had ADR. VCZ-C at various levels of overall ADR, hepatotoxicity, adverse visual events and neurotoxic ADRminThere was a significant difference (< 0.5, 0.5-5.0, ≧ 0.5mg/L) (χ 2 ═ 31.800, P < 0.001; χ 2 ═ 25.022, P < 0.001; χ 2 ═ 18.294, P < 0.001; χ 2 ═ 23.081, P < 0.001). The incidence of ADR at the supratherapeutic concentration range was significantly higher than both the therapeutic and subtherapeutic concentration ranges (both P < 0.001), as shown in FIG. 9A.
The incidence of total ADR, hepatotoxicity, adverse visual events and neurotoxicity did not differ significantly between the non-gene-targeted and gene-targeted groups (P > 0.05). UM/EM/NM, IM, PM (unadjusted VCZ dose), PM (adjusted VCZ dose), and no significant differences in all ADRs (P > 0.05). However, the incidence of visual adverse events was significantly higher in the PM (unadjusted VCZ dose) group than in the IM group (P < 0.05). The ADR was significantly higher (P < 0.05) in the PM (non-adjusted VCZ dose) group compared to the PM (adjusted VCZ dose) group, as shown in FIG. 9B.
2.10 influence VCZ-CminAnalysis of risk factors
2.10.1X 2 test to assess the impact on VCZ-CminRisk factors of (2): chi 2 test showed that age, CYP2C19 gene phenotype (PM type), CRP, PCT, IL-6 and the average daily dose/body weight was VCZ-CminMore than or equal to 5.0mg/L of risk factor (P is less than 0.05). The values for CRP, PCT, IL-6, and average daily dose/body weight were stratified according to the cutoff values predicted by the ROC curve.
2.10.2 multivariate stepwise regression analysis influence VCZ-CminRisk factors of (2): by using stabilized VCZ-Cmin(Y) as a dependent variable and sex (X)1) Age (X)2) Body weight (X)3) VCZ administration route (X)4) CYP2C19 Gene phenotype (X)5) Average daily dose (X)6) Combined PPI (X)7) Combined with a glucocorticoid (X)8)、CRP(X9) And average daily dose/body weight (X)10) As independent variables, multiple linear stepwise regression analysis was performed. The regression equation is that Y is 1.616+0.015X9 +0.169X10+0.379X5(F-24.649, P < 0.001). Analysis showed that CRP, average daily dose/body weight and CYP2C19 gene phenotype affect VCZ-C, respectivelyminThe significant factors (P < 0.05) are shown in Table 4.
TABLE 4 multiple regression analysis Effect VCZ-CminRisk factors of
Figure RE-RE-GSB0000197010280000071
2.11 multiple stepwise regression analysis of risk factors affecting stable maintenance doses of VCZ: the VCZ stable maintenance dose (i.e., the stable maintenance dose at which the patient first reached the target trough concentration) (Y) was used as a dependent variable and sex (X)1) Age (X)2) VCZ administration route (X)3) Body weight (X)4) CYP2C19 Gene phenotype (X)5) Combinations of PPIs (X)6) The combination of glucocorticoid (methylprednisolone) (X)7)，CRP(X8) As independent variables, multiple linear stepwise regression analysis was performed. The regression equation is that Y is 360.126-30.325X5-0.215X8+0.888X4(F-12.190, P < 0.001). Analysis showed that CYP2C19 gene phenotype, CRP and body weight were significant factors in the stable VCZ maintenance dose (P.ltoreq.0.05). Age can also affect VCZ maintenance dose, but not significantly (P ═ 0.242), see table 5.
TABLE 5 Risk factors affecting VCZ Stable maintenance dose by multiple regression analysis
Figure RE-RE-GSB0000197010280000072
2.12 establishment of VCZ Stable maintenance dose prediction System and method: patients were divided into model group (202 cases) and validation group (100 cases), and there were no significant differences between the two groups in sex, age, body mass index, albumin, pooled PPIs, pooled glucocorticoids, CYP2C19 gene phenotype, pooled basal disease, inflammatory factors, etc. (P > 0.05). The VCZ stable maintenance dose (Y) was used as a dependent variable for 202 patients in the model group, age (X)1) Body weight (X)2) CYP2C19 Gene phenotype (X)3) And CRP (X)4) As independent variables. The multiple linear regression is used for establishing a prediction model of Y-286.779-0.734X1+2.925X2-22.223X3-0.3195X4(F-20.868, P < 0.001). Indicating that the predictive model is meaningful. X1: age (year of age); x2: body weight (Kg); x3: CYP2C19 gene phenotype (UM/EM/NM: 0, IM: 1, PM: 2); x4：CRP (mg/L)。
2.13 validation of the established prediction system and method: the voriconazole maintenance dose is predicted by using the established prediction system and method in 100 patients to be grouped, and no significant difference is generated between the actual maintenance dose and the predicted maintenance dose of the verification group of patients ((376.10 + -57.87) mg vs. (373.97 + -46.46) mg, t is 0.425, and P is 0.672). The predicted difference rates at > 20% and > 50% at the predicted and actual maintenance doses were 11.00% (11/100) and 0% (0/100), respectively. The established VCZ maintenance dose prediction system and method are accurate in prediction, the VCZ of a patient can quickly reach an effective target valley concentration range (0.5-5.0mg/L), the curative effect of the medicine can be improved, and the incidence rate of adverse reactions can be reduced.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.

Claims (7)

1. Confirming various influencing factors influencing the maintenance dose of voriconazole, which is characterized by comprising the following steps:
(1) determination of whether the CYP2C19 gene polymorphism is used for Voriconazole steady state plasma concentration (VCZ-C) of invasive fungal infection patients by using anovamin) An influence is produced.
(2) Confirmation of inflammatory factors (CRP, PCT and IL-6) vs VCZ-CminThe method comprises the following steps: analysis of the respective inflammatory factors and blood levels (C) using Pearson correlation coefficientsmin) The correlation between the two is evaluated by a correlation coefficient r, the larger the absolute value of r is, the stronger the correlation is, the extremely strong correlation of | r |0.8-1.0, | r |0.4-0.6 is, the medium strength correlation is, and | r |0.2-0.4 is, the weak correlation is; analysis of variance comparison of subtherapeutic Range (C)minLess than 0.5mg/L) and the treatment range (0.5mg/L is less than or equal to Cmin< 5.0mg/L) and a supra-therapeutic range (C)minNot less than 5.0mg/L) among the three groups, the difference between C-reactive protein (CRP, mg/L), procalcitonin (PCT, ng/mL) and interleukin-6 (IL-6, pg/mL), and the difference with P less than 0.05 has statistical significance.
(3) Confirmation of the Combined use of different classes of Proton Pump Inhibitors (PPIs) on VCZ-CminThe method comprises the following steps: ANOVA comparison of post-dose normalization VCZ-C between different proton pump inhibitor groupsmin(Dose-normalized VCZ-Cmin) The difference of (3) is statistically significant when P is less than 0.05, Dose-normalized VCZ-CminThe calculation formula is as follows:
Dose-normalized VCZ-CminVCZ-Cmin (mg/L)/average daily dose (mg)/body weight (Kg)
Chi fang (X)2) Testing and comparing the sub-therapeutic range, therapeutic range and super-therapeutic range among different proton pump inhibitor groupsDifferences in treatment range ratios.
(4) Confirming the effect of different CYP2C19 gene phenotype-directed use and non-directed use of VCZ on the curative effect and adverse reaction of patients, including: chi shape2The difference of VCZ curative effect and various adverse reactions among different gene phenotype groups is compared by inspection.
(5) Multiple linear stepwise regression predicted risk factors affecting VCZ-Cmin as CRP, average daily dose/body weight, and CYP2C19 gene phenotype with the regression equation Y of 1.616+0.015X9+0.169X10+0.379X5(F＝24.649，P＜0.001)，
Y：VCZ-Cmin；X9：CRP；X10: average daily dose/body weight; x5: CYP2C19 Gene phenotype
(6) Multiple linear stepwise regression predicts risk factors affecting VCZ maintenance dose as CYP2C19 gene phenotype, CRP, and body weight. The regression equation is that Y is 360.126-30.325X5-0.215X8+0.888X4(F＝12.190，P＜0.001)。
Y: VCZ stable maintenance dose; x5: CYP2C19 gene phenotype; x8：CRP；X4: body weight.
2. A multifactor-based voriconazole sustained dose prediction system and method are characterized by comprising the following steps:
(1) multiple linear regression with the regression equation Y being 286.779-0.734X, based on the risk factors identified in step (6) to build a mathematical model for predicting VCZ maintenance dose1+2.925X2-22.223X3-0.3195X4(F＝20.868，P＜0.001)。
Y: VCZ stable maintenance dose; x1: age (year of age); x2: body weight (Kg); x3: CYP2C19 gene phenotype (UM/EM/NM: 0, IM: 1, PM: 2); x4：CRP(mg/L)。
(2) The mathematical model for maintenance dose prediction for patients using VCZ was validated and the t-test compared the difference between the predicted and actual values.
3. The method according to claim 1, step (1), wherein the polymorphism or phenotype in the CYP2C19 gene is: UM: ultrafast metabolic type (./17); EM: fast metabolic (. about.1/. about.17); NM: normal metabolic type (. about.1/. about.1); IM: intermediate metabolic forms (. about.1/. about.2,. about.1/. about.3,. about.2/. about.17, 3/. about.17); PM: slow metabolic type (. about.2/. about.2,. about.2/. about.3,. about.3/. about.3).
4. The method of claim 1 step (2), wherein the ratio of three inflammatory factors, CRP: c-reactive protein; PCT: procalcitonin; IL-6: interleukin-6.
5. The method of claim 1 step (3), wherein the Proton Pump Inhibitors (PPIs) comprise: omeprazole, esomeprazole, pantoprazole, rabeprazole.
6. The method according to claim 1, step (4), wherein the adverse reaction (ADR) comprises: hepatotoxicity, visual adverse reactions, neurotoxicity and others.
7. The method of claim 2, wherein the multiple linear regression modeling factors in the predictive VCZ maintenance dose mathematical model include: age (year), body weight (Kg), CYP2C19 gene phenotype (UM/EM/NM, IM, PM), CRP (mg/L), PCT (ng/mL), and IL-6 (pg/mL).
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