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Not yet recruiting NCT07685028

LEGACY: Lung Cancer Screening in Individuals With a Lung Cancer Family History-Protocol A

No phase Interventional Family History of Lung Cancer

For patients and families

In plain language

An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.

What is being studied
The protocol lists: CT scan, Sybil.
Who it may be relevant to
Registry conditions: Family History of Lung Cancer. Basic parameters: 18 years — 80 years · All.
What needs checking
Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
Where it takes place
United States
Next step
Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →

Overview

This research is being done to determine if an image-based deep learning model (Sybil) can accurately predict the likelihood of future lung cancer based on chest computed tomography (CT) imaging from individuals.

Detailed description

This non-therapeutic study will enroll individuals who have family history of lung cancer. Participants will undergo a low-dose non-contrast computed tomography of the chest (LDCT) and may also send images from any chest CT scan(s) obtained as part of routine clinical care, outside of the study. The images and data collected will be analyzed by an image-based deep learning model (Sybil). Sybil is a type of artificial intelligence model that has been shown to accurately predict individuals' future risk of lung cancer based solely on images from a CT Chest scan, but it remains unclear whether Sybil works well in people with a family history of lung cancer. The goals of this study are: 1) to obtain CT Chest images from individuals with a family history of lung cancer in order to test whether Sybil continues to work well, and 2) offer free screening CT scans to qualifying individuals. It is expected that 250 people will take part in this research study.

Interventions

  • Diagnostic test CT scan
    Computed tomography scan
  • Other Sybil
    Image-based deep learning model

Primary outcome measures

  • Sybil's performance in predicting future lung cancer diagnoses [Time frame: Annually, from time of initial CT scan to up to 5 years after the scan.]
Secondary outcome measures (5)
  • Compare the distribution of Sybil lung cancer risk scores in this trial to the distribution of Sybil risk scores from the NLST clinical trial [Time frame: Initial provided CT scan will represent time 0. Additional provided CT scans will vary between individuals and will be measured in years relative to time 0 (e.g., time -3.5 years, time +2 years, etc). Sybil risk scores will be calculated for each scan.]
  • Incidence and prevalence of lung cancer in the study population [Time frame: Annually, from time of initial CT scan to up to 5 years after the scan.]
  • Incidence of lung nodules in this population [Time frame: Annually, from time of initial CT scan to up to 5 years after the scan.]
  • Prevalence of lung nodules in this population [Time frame: Annually, from time of initial CT scan to up to 5 years after the scan.]
  • Describe the characteristics of lung nodules in this population [Time frame: At time of each provided CT scan to up to 5 years after the scan.]

Eligibility criteria

Inclusion criteria

  • Age: Must meet both the upper and lower age limit criteria.
  • Upper age limit: ≤80 years of age
  • Lower age limit:
  • ≥40 years of age OR
  • ≥18 years of age AND ≤10 years of youngest relative's age at time of lung cancer diagnosis (e.g., if a relative was diagnosed at 35 years of age, participant can enroll at ≥25 years of age)
  • Positive family history of lung cancer (defined as):
  • Has ≥1 first-degree relative, OR
  • Has ≥2 second-degree relatives with a diagnosis of non-small cell lung cancer or small cell lung cancer (NB: a first-degree relative = parent, sibling, or child, a second-degree relative = grandparent, blood-related aunt or uncle, grandchild, blood-related niece or nephew, half-sibling)

Exclusion criteria

  • Must not have a personal history of lung cancer at the time of enrollment.
  • Must not have a personal history of stage IV cancer of any type at the time of enrollment.
  • Must not have had surgical removal of any portion of the lung, excluding needle or core lung biopsy at the time of enrollment.
  • Must not have had a chest CT within 12 months prior to trial enrollment.

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: No

Study design

Allocation
N/A
Model
Single group
Masking
Open label
Primary purpose
Screening

Study locations

United States · 1 center
  • Massachusetts General Hospital — Boston

Identifiers

NCT: NCT07685028 · 26-044

Primary sources (government registries)

View this study on ClinicalTrials.gov ↗