Predicting Metastatic Oral Squamous Cell Carcinomas With Molecular Biomarkers Using Machine Learning

The University of Hong Kong500 enrolled

Overview

Application Management Team: PI - Siu Wai Choi; email - htswchoi@hku.hk Delegates - Chui Shan Chu; email: sunshine.c@connect.hku.hk FollowUpUsers - Chui Shan Chu; email:sunshine.c@connect.hku.hk

Eligibility Criteria: \- patients were diagnosed with a baseline disease of oral squamous carcinoma. Exclusion Criteria: \- N/A Sample size: \- \~500 subjects Source of Data: \- The data, such as age and medical records, would be obtained from Hospital Authority Clinical Management System (HACMS) Statistical analysis: \- machine learning will be applied into analysis plan

Study Type

OBSERVATIONAL

Enrollment

500

Conditions

Oral Squamous Cell Carcinoma

Interventions

SurgeryPROCEDURE

Resection of tumors

Eligibility

Sex: ALL

Medical Language ↔ Plain English

Inclusion Criteria: * patients with oral squamous carcinoma * received surgery from 1st October 2000 to 1st October 2019 Exclusion Criteria: N/A

Locations (1)

The University of Hong Kong

Hong Kong, Hong Kong

RECRUITING

Outcomes

Primary Outcomes

The primary outcomes of the study are metastasis and recurrent disease

These outcomes will be entered as the dependent variables into the machine learning model

Time frame: Baseline of OSCC

Central Contacts

SW Choi, PhD

CONTACT

+85228590390 htswchoi@hku.hk

Chui Shan Chu, MMedSc

CONTACT

+85252227292 sunshine.c@connect.hku.hk

Data from ClinicalTrials.gov

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