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Gut Microbiota in ITP

Conditions
ITP
Registration Number
NCT05118126
Lead Sponsor
Peking University People's Hospital
Brief Summary

Prospective, observational study to explore the significance of gut microbiome in the diagnosis of ITP, and to identify the predictive value of baseline gut microbiome for GC resistance/relapse.

Detailed Description

A prospective, observational study to (1) collect fecal samples from ITP patients at initial diagnosis (baseline) and after first-line GC treatment, (2) detect the composition of gut microbiome and related metabolites using metagenomic sequencing combined with metabolomics, (3) observe the impact of first-line treatment on gut microbiome, (4) explore the significance of gut microbiome in the diagnosis of ITP, and (5) identify the predictive value of baseline gut microbiome for GC resistance/relapse, thus to provide new ideas for clinical diagnosis and treatment of ITP.

Recruitment & Eligibility

Status
UNKNOWN
Sex
All
Target Recruitment
240
Inclusion Criteria
  • 18 years or older;
  • Isolated thrombocytopenia (platelet count of less than 100×10^9/L);
  • Normal leukocyte and erythrocyte counts according to routine blood tests;
  • Did not receive any medication for thrombocytopenia for 6 months.
Exclusion Criteria
  • Secondary ITP such as drug-associated thrombocytopenia;
  • Thrombocytopenia caused by viral infection (HIV, Hepatitis B virus or Hepatitis C virus);
  • Nursing or pregnant women;
  • Severe dysfunction of the heart, kidney, lung or liver;
  • Active or previous malignancy;
  • Patients with other diseases were undergoing treatment with immunosuppressants;
  • Myelodysplastic disorder or myelofibrosis;
  • Patients who were undergoing first - or second-line therapy for thrombocytopenia within 6 months.

Study & Design

Study Type
OBSERVATIONAL
Study Design
Not specified
Primary Outcome Measures
NameTimeMethod
AUC value of 1-month drug resistance/relapse using baseline gut microbiota efficacy prediction model1 month

The prediction model is constructed and calculated using machine learning methods

Secondary Outcome Measures
NameTimeMethod
AUC value of 3-month drug resistance/relapse using baseline gut microbiota efficacy prediction model3 months

The prediction model is constructed and calculated using machine learning

AUC value of 6-month drug resistance/relapse using baseline gut microbiota6 months

The prediction model is constructed and calculated using machine learning

Duration of response6 months

The duration of achieve platelet count ≥ 30×10\^9/L and at least 2-fold increase of the baseline count and absence of bleeding since start of treatment

Time to response6 months

The time to achieve platelet count ≥ 30×10\^9/L and at least 2-fold increase of the baseline count and absence of bleeding since start of treatment.

Trial Locations

Locations (1)

Peking University Insititute of Hematology, Peking University People's Hospital

🇨🇳

Beijing, Beijing, China

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