Machine-learning Based Prediction Model in Primary Immune Thrombocytopenia

NCT05116423 | Unknown DMC

• 1 other identifier: PKU-ITP031
• Study Type: observational
• Target: 100
• Locations: 1 country
• Sites: 1

Brief Summary

This study developed the first prediction model for risk of critical ITP bleeds for ITP inpatients using a novel machine learning algorithm. This model has been implemented as a web-based model so that clinicians can obtain the estimated probability of critical ITP bleeds for ITP inpatients. The objective of this study is to prospectively and externally validate the risk of critical ITP bleeds in newly admitted ITP patients.

Conditions

Immune Thrombocytopenia; ITP

Keywords

Immune Thrombocytopenia; Prediction Model

Outcome Measures

Primary Outcomes (1)

• Performance of model

  Area under receiver operating characteristic curve (AUC) of the model in predicting critical ITP bleeds in patients with ITP.

  3 months

Secondary Outcomes (1)

• Comparison between different machine learning algorithms used in the model

  3 months

Study Arms (1)

ITP inpatients

The study population included nonsplenectomized primary ITP inpatients 18 years of age or older. Patients who had a diagnosis of connective tissue disease, cancer (solid tumor or leukemia), or primary immune deficiency were excluded.

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

The study population included nonsplenectomized primary ITP inpatients 18 years of age or older. Patients who had a diagnosis of connective tissue disease, cancer (solid tumor or leukemia), or primary immune deficiency were excluded.

You may qualify if:

• \. Confirmed ITP diagnosis;

You may not qualify if:

• Received chemotherapy or anticoagulants or other drugs affecting the platelet counts within 6 months before the screening visit;
• Current HIV infection or hepatitis B virus or hepatitis C virus infections;
• Maligancy;
• Female patients who are nursing or pregnant, who may be pregnant, or who contemplate pregnancy during the study period; a history of clinically significant adverse reactions to previous corticosteroid therapy
• Have a known diagnosis of other autoimmune diseases, established in the medical history and laboratory findings with positive results for the determination of antinuclear antibodies, anti-cardiolipin antibodies, lupus anticoagulant or direct Coombs test;
• Patients who are deemed unsuitable for the study by the investigator.

Sponsors & Collaborators

• Peking University People's Hospital: lead
• Affiliated Zhongshan Hospital of Dalian University: collaborator
• Jiangsu Provincial People's Hospital: collaborator
• Qilu Hospital of Shandong University: collaborator
• Shanghai Zhongshan Hospital: collaborator

Study Sites (1)

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

Beijing, Beijing Municipality, 100010, China

RECRUITING

MeSH Terms

Conditions

Purpura, Thrombocytopenic, Idiopathic

Condition Hierarchy (Ancestors)

Purpura, Thrombocytopenic; Purpura; Blood Coagulation Disorders; Hematologic Diseases; Hemic and Lymphatic Diseases; Thrombotic Microangiopathies; Thrombocytopenia; Blood Platelet Disorders; Cytopenia; Hemorrhagic Disorders; Autoimmune Diseases; Immune System Diseases; Hemorrhage; Pathologic Processes; Pathological Conditions, Signs and Symptoms; Skin Manifestations; Signs and Symptoms

Study Officials

• Xiao-Hui Zhang, MD

  Peking University People's Hospital, Peking University Institute of Hematology, National Clinical Research Center for Hematologic Disease, Beijing Key Laboratory of Hematopoietic Stem Cell Transplantation, Collaborative Innovation Center of Hematology

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Xiao-Hui Zhang, MD

CONTACT

+8615010638916; zhangxh100@sina.com

Zhuo-Yu An, MD

CONTACT

+8615010638916; anzhuoyu@pku.edu.cn

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Vice President of Peking University Institute of Hematology

Study Record Dates

• First Submitted: November 9, 2021
• First Posted: November 11, 2021
• Study Start: November 10, 2021
• Primary Completion: March 1, 2022
• Study Completion: June 30, 2022
• Last Updated: February 8, 2022

Record last verified: 2022-01

Locations

CN (1)