Risk Model for Metastasis Detection of Neuroblastoma

NCT06703944 | Enrolling By Invitation

• 1 other identifier: XH-24-008
• Study Type: observational
• Target: 500
• Locations: 1 country
• Sites: 3

Brief Summary

Neuroblastoma (NB) is the most common extracranial solid tumor in children, accounting for about 15% of tumor-related mortality. NB patients in high-risk group are prone to bone marrow and/or bone metastases with low five-year overall survival rate. The artificial intelligence (AI) and deep learning technologies have potential to identifying morphological characteristics of bone marrow cytology in clinical practice. In this study, the investigators construct and evaluate the bone marrow cytology-based AI model for detection and prognosis of NB. The main questions of the study as follows: The question 1: Dose bone marrow cytology-based AI model work for prediction of bone marrow metastasis in NB? The question 2: Dose bone marrow cytology-based AI model work for prediction of bone metastasis in NB? The question 3: Dose bone marrow cytology-based AI model have potential to assist doctors in making individualized predictions of survival outcome? The investigators will retrospectively obtain the participants with NB between January 2019 and June 2024. The follow-up date ended on June 30, 2024. The internal cohort including participants from Xinhua Hospital, Shanghai Jiao Tong University School of Medicine. The independent external cohorts including participants form Children's Hospital, Zhejiang University School of Medicine and Shenzhen Children's Hospital. The investigators collect the clinical data of enrolled participants at the time of the patients' initial admission to the hospital, prior to receiving treatment. The clinical information including age, gender, primary tumor location, tumor grade, bone marrow metastasis state, bone metastasis state, genetic aberrations (MYCN amplification, Chromosome 1p deletion, Chromosome 11q deletion) and lab variables (peripheral blood cell count, bone marrow cytology indicators, the serum concentration of lactate dehydrogenase, neuron specific enolase). This study is a non-interventional observational study, there is no risk to the participants and investigators. Participants get these benefits:

1. 1.Early Detection: The model helps in early risk identification and personalize treatment.
2. 2.Convenience: Because the model relies on general lab tests, it is easy to carry out can reduce invasive diagnostic procedures.
3. 3.Cost-Effective: Using existing clinical data from routine tests can make the prediction process more cost-effective.
4. 4.Data-Driven Decisions: The AI model improve diagnostic efficiency and support the medical decision.

Conditions

Neuroblastoma (NB); Prognosis; Bone Marrow Metastasis; Bone Metastases

Keywords

Neuroblastoma; Bone Marrow Metastasis; Bone Metastasis; Machine Learning Algorithms; Risk Prediction Models; artificial intelligence mode; Prognosis

Outcome Measures

Primary Outcomes (2)

• Neuroblastoma with bone marrow metastasis

  the medical practices in diagnosis of bone marrow metastasis including as follows: bone marrow biopsy, bone marrow cytology of aspiration smear, flow cytometry and PET/CT. Bone marrow biopsy or smear analysis may reveal characteristic NB cells. Flow cytometry may detect NB cells with phenotype of CD45-/CD56+/CD81+/GD2+. PET/CT imaging reveal the metastatic NB cells in term of metabolic activity and spatial distribution of metastatic involvement. A positive result from any of these methods is sufficient for diagnosed as NB with bone marrow metastasis.

  The period from the initial diagnosis of neuroblastoma to the initiation of chemotherapy or radiotherapy, up to 3 months.

• Neuroblastoma with bone metastasis

  We diagnosed NB with bone metastasis if bone destruction or discontinuity of the bone cortex in radiology test including CT, PET/CT, MRI.

  The period from the initial diagnosis of neuroblastoma to the initiation of chemotherapy or radiotherapy, up to 3 months.

Secondary Outcomes (1)

• Overall survival time

  through study completion, up to 60 months.

Study Arms (2)

Neuroblastoma With Bone Marrow Metastasis Group

For the diagnosis of neuroblastoma with bone marrow metastasis, the medical practices including as follows: bone marrow biopsy, bone marrow cytology of aspiration smear, flow cytometry and positron emission tomography-computed tomography(PET-CT). Bone marrow biopsy or smear analysis may reveal characteristic NB cells. Flow cytometry may detect NB cells with phenotype of cluster of differentiation antigen 45(CD45)-/cluster of differentiation antigen 56(CD56)+/cluster of differentiation antigen 81(CD81)+/GD2 ganglioside (GD2)+. PET/CT imaging reveal the metastatic NB cells in term of metabolic activity and spatial distribution of metastatic involvement. A positive result from any of these methods is sufficient for diagnosed as NB with bone marrow metastasis.

Other: risk model in diagnosis and prognosis

Neuroblastoma Without Bone Marrow Metastasis Group

For the diagnosis of bone marrow metastasis in the enrolled participants, if there is no positive result from any of these tests as follows: bone marrow biopsy, bone marrow cytology of smear, flow cytometry or PET/CT, the participant is classified into the Neuroblastoma Without Bone Marrow Metastasis Group.

Interventions

risk model in diagnosis and prognosis OTHER

In this study, we construct and evaluate the bone marrow cytology-based AI model for detection and prognosis of NB. 1. For the diagnostic model, we use AUC metrics to evaluate the model in terms of sensitivity, specificity, accuracy, positive predictive value and negative predictive value at different classification thresholds. 2. For the prognostic model, we use AUC as the performance metric and calculating sensitivity and specificity. Survival curves were constructed according to the Kaplan-Meier method.

Neuroblastoma With Bone Marrow Metastasis Group

Eligibility Criteria

• Sex: all
• Healthy Volunteers: No
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

This study included participants who were newly diagnosed with NB between January 2019 and June 2024. The follow-up date ended on June 30, 2024. The internal cohort including participants from Xinhua Hospital, Shanghai Jiao Tong University School of Medicine. The independent external cohorts including participants form Children's Hospital, Zhejiang University School of Medicine and Shenzhen Children's Hospital. All the participants have performed bone marrow smear analysis as routine examination. The bone marrow smear stained with Wright-Giemsa was made according to standard protocols.The diagnosis completed by experienced pathologist and correlated with clinical and/or radiological findings.

You may qualify if:

• The participant newly diagnosed with NB according to the International Neuroblastoma Risk Group Staging System (INRGSS). The diagnosis completed by experienced pathologist and correlated with clinical and/or radiological findings.
• The participant diagnosed with NB at other hospitals who have not received chemotherapy or radiotherapy.
• The participant with NB has performed bone marrow smear analysis as routine examination. The bone marrow smear stained with Wright-Giemsa was made according to standard protocols.

You may not qualify if:

• The participant with concurrent diagnosis of other malignancies.
• The participant with NB who has previously received chemotherapy and/or radiotherapy.
• The participant with incomplete clinical data, the metastasis state of bone marrow and/or bone is unclear.
• The participant was excluded due to non-representative specimens, such as unclear or faded Wright-Giemsa staining of bone marrow smear.

Sponsors & Collaborators

• Xinhua Hospital, Shanghai Jiao Tong University School of Medicine: lead
• Shenzhen Children's Hospital: collaborator
• The Children's Hospital of Zhejiang University School of Medicine: collaborator

Study Sites (3)

Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine

Shanghai, Shanghai Municipality, 200092, China

Location

The Children's Hospital, Zhejiang University School of Medicine

Hangzhou, Zhejiang, China

Location

Shenzhen Children's Hospital

Shenzhen, 518038, China

Location

Biospecimen

Retention: SAMPLES WITH DNA

We use bone marrow smears for cytological evaluation and image collection.

MeSH Terms

Conditions

Neuroblastoma

Condition Hierarchy (Ancestors)

Neuroectodermal Tumors, Primitive, Peripheral; Neuroectodermal Tumors, Primitive; Neoplasms, Neuroepithelial; Neuroectodermal Tumors; Neoplasms, Germ Cell and Embryonal; Neoplasms by Histologic Type; Neoplasms; Neoplasms, Glandular and Epithelial; Neoplasms, Nerve Tissue

Study Officials

• juan ma, Doctor

  Xin Hua Hospital, Shanghai Jiao Tong University School of Medicine

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Associate Chief Physician of the Clinical Laboratory Department

Study Record Dates

• First Submitted: November 19, 2024
• First Posted: November 25, 2024
• Study Start: December 1, 2024
• Primary Completion: July 1, 2025
• Study Completion (Estimated): December 1, 2026
• Last Updated: May 15, 2025

Record last verified: 2024-12

Data Sharing

• IPD Sharing: Will share
• Shared Documents: STUDY PROTOCOL, SAP, ICF, CSR, ANALYTIC CODE
• Time Frame: The investigators anticipate that the data will be available for sharing six months after the primary study results have been published in a peer-reviewed journal and will remain accessible within one years after publication.
• Access Criteria: Access Plan for IPD: Who will be able to access: Researchers, academic institutions, and other scientists interested in conducting research in related fields. What they will be able to access: Clinical outcomes, laboratory test results, demographic information, and other supporting information related to the study. How they will be able to access it: They will need to submit an access request form, outlining the purpose of their research. All requests will be reviewed by the principal investigator of the study, who will determine whether access is granted based on research ethics and data use policies. Data will be provided through a secure online platform to ensure privacy and security.

Locations

CN (3)