Machine Learning to Construct an Association Model for Lung Cancer and Environmental Hormone

NCT06259461 | Active Not Recruiting

• 1 other identifier: 202204055RINA
• Study Type: observational
• Target: 128
• Locations: 1 country
• Sites: 2

Brief Summary

To apply machine learning to construct an association model regarding lung cancer and environmental hormones to more comprehensively identify factors that may lead to lung cancer and to improve existing lung cancer nursing assessments.

Conditions

Lung Neoplasms

Keywords

Environmental Substance

Outcome Measures

Primary Outcomes (1)

• identify factors that may lead to lung cancer and environmental hormones.

  This association model can assist in identifying the risk groups of lung cancer and advising physicians on the appropriate environmental hormone testing and treatment to provide nursing guidance and medical advice

  the database research samples from May 2014 to December 2020.

Eligibility Criteria

• Age: 20 Years+
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

The study focused on lung cancer cases and investigated the association with exposure to environmental hormones

You may qualify if:

• years or older;
• conscious, without mental disorders;
• able to use Mandarin to communicate, had a smartphone or tablet computer and could operate it by themselves,
• and were willing to participate in the study after the reasons for participation were explained and a consent form was signed, indicating their consent.

Sponsors & Collaborators

• Pei-Hung Liao: lead

Study Sites (2)

National Taipei university of nursing and health science

Taipei, Taiwan

Location

National Taiwan University, Cancer Center

Taipei, Taiwan

Location

Biospecimen

Retention: SAMPLES WITHOUT DNA

(1) 20 years or older; (2) conscious, without mental disorders; (3) able to use Mandarin to communicate, had a smartphone or tablet computer and could operate it by themselves, and were willing to participate in the study after the reasons for participation were explained and a consent form was signed, indicating their consent.

MeSH Terms

Conditions

Lung Neoplasms

Condition Hierarchy (Ancestors)

Respiratory Tract Neoplasms; Thoracic Neoplasms; Neoplasms by Site; Neoplasms; Lung Diseases; Respiratory Tract Diseases

Study Design

• Study Type: observational
• Observational Model: CASE CONTROL
• Time Perspective: CROSS SECTIONAL
• Sponsor Type: OTHER
• Responsible Party: SPONSOR INVESTIGATOR
• PI Title: Associate Professor

Study Record Dates

• First Submitted: January 20, 2024
• First Posted: February 14, 2024
• Study Start: January 1, 2023
• Primary Completion: June 30, 2024
• Study Completion: June 30, 2024
• Last Updated: February 14, 2024

Record last verified: 2024-02

Data Sharing

• IPD Sharing: Will not share

Locations

TW (2)