LEGACY: Lung Cancer Screening in Individuals With a Lung... | NCT07600801

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

NCT07600801

Sponsor

Massachusetts General Hospital

Status

Not yet recruiting

Last Update Posted

May 27, 2026Actual

Enrollment

2,250Estimated

Phase

Not provided

Conditions

Family History of Lung Cancer

Interventions

CT scan
Sybil

Countries

United States

Protocol Section

Identification Module Status Module Sponsor/Collaborators Module Oversight Module Description Module Conditions Module Design Module Arms/Interventions Module Outcomes Module Eligibility Module Contacts/Locations Module References Module IPD Sharing Statement Module

Results Section

Participant Flow Module Baseline Characteristics Module Outcome Measures Module Adverse Events Module More Info Module

Annotation Section

Annotation Module

Document Section

Large Document Module

Derived Section

Miscellaneous Info Module Condition Browse Module Intervention Browse Module

Protocol Section

Identification Module

NCT ID

Results Section

No data available

No data is available for this block.

Annotation Section

No data available

No data is available for this block.

Document Section

No data available

No data is available for this block.

Derived Section

Miscellaneous Info Module

Version Holder

Status Module

Record Verification Date

May 2026

Overall Recruitment Status or Expanded Access Status

Not yet recruiting

Last Known Status

Not provided

Delayed Posting

Not provided

Why Stopped

Not provided

Expanded Access Info

Start Date

Jun 15, 2026Estimated

Primary Completion Date

Dec 31, 2033Estimated

Completion Date

Dec 31, 2035Estimated

First Submitted Date

May 14, 2026

First Submission Date that Met QC Criteria

May 14, 2026

First Posted Date

May 22, 2026Actual

Results Waived

Not provided

Results First Submitted Date

Not provided

Results First Submitted that Met QC Criteria

Not provided

Results First Posted Date

Not provided

Certification/Extension (aka Delayed Results) First Submitted Date

Not provided

Certification/Extension First Submitted that Passed QC Review

Not provided

Certification/Extension First Posted Date

Not provided

Last Update Submitted Date

May 22, 2026

Last Update Posted Date

May 27, 2026Actual

Oversight Module

Has Data Monitoring Committee (DMC)

Yes

Is FDA Regulated Drug

Is FDA Regulated Device

Is Unapproved Device

Not provided

Pediatric Postmarket Surveillance of a Device Product

Not provided

Product Exported from US

Not provided

FDAAA801 Violation

Not provided

Description Module

Brief Summary

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 with a family history of lung cancer.

Detailed Description

This is a non-therapeutic study that will enroll individuals who have a family history of lung cancer. During the study, participants will provide questionnaire responses regarding their personal medical history, family lung cancer history, and exposures along with contributing images from at least one previously obtained CT chest scan. 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 is unknown if it works well in people with a family history of lung cancer. It is expected that 2,250 will take part in this research study.

Design Module

Study Type

Observational

Number of References to an Expanded Access Study

Not provided

Expanded Access Types

Not provided

Patient Registry

Target Follow-Up Duration

Not provided

Phases

Not provided

Interventional Study Design

Allocation

Not provided

Intervention Model

Biospecimen

No data available

No data is available for this block.

Enrollment

2,250Estimated

Arms/Interventions Module

Arm Groups

Label	Type	Description	Intervention Names
Retrospective CT scan		Participants will contribute images and corresponding radiology reports from at least one retrospective CT chest scan.	Diagnostic Test: CT scan Other: Sybil

Interventions

Name	Type	Description	Arm Group Labels	Other Names
CT scan	Diagnostic Test	Previously obtained computed tomography scan	Retrospective CT scan

Outcomes Module

Primary Outcomes

Measure	Description	Time Frame
Sybil's performance in predicting future lung cancer diagnoses	We will estimate future lung cancer diagnoses using the area under the receiver operating curve (AUROC).	From date of receival of retrospective CT scan for up to 2 years.

Secondary Outcomes

Measure	Description	Time Frame
Distribution of Sybil lung cancer risk scores compared to participants in the NLST clinical trial	We will compare the distribution of Sybil scores between participants in the LEGACY study and National Lung Screening Trial.	From receival of retrospective CT scan for up to 2 years.
Incidence and prevalence of lung cancer in the study population

Other Outcomes

Not provided

Eligibility Module

Eligibility Criteria

Inclusion Criteria:

≥18 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)
Willing to provide images from at least one previously obtained CT Chest scan, if available.

Exclusion Criteria:

- None

Accepts Healthy Volunteers

Not provided

Sex

All

Sex/Gender Based

Not provided

Sex/Gender Description

Not provided

Minimum Age

18 Years

Maximum Age

Not provided

Standard Ages

AdultOlder Adult

Study Population

This study will enroll individuals who have a family history of lung cancer (≥1 first-degree relative or ≥2 second-degree relatives).

Sampling Method

Non-Probability Sample

Contacts/Locations Module

Central Contacts

Name	Role	Phone	Extension	Email
Allison Chang, MD	Contact	617-724-4000		aechang@mgb.org

Overall Officials

Name	Affiliation	Role
Allison Chang, MD	Massachusetts General Hospital	Principal Investigator

Locations

Facility	Status	City	State	ZIP	Country	Contacts
Massachusetts General Hospital		Boston	Massachusetts	02114	United States

IPD Sharing Statement Module

Plan to Share IPD

Yes

Description

The Dana-Farber / Harvard Cancer Center encourages and supports the responsible and ethical sharing of data from clinical trials. De-identified participant data from the final research dataset used in the published manuscript may only be shared under the terms of a Data Use Agreement. Requests may be directed to: Allison Chang, MD (aechang@mgb.org). The protocol and statistical analysis plan will be made available on Clinicaltrials.gov only as required by federal regulation or as a condition of awards and agreements supporting the research.

Types

Study Protocol
Statistical Analysis Plan (SAP)
Informed Consent Form (ICF)

Time Frame

Data can be shared no earlier than 1 year following the date of publication

Access Criteria

Contact the Partners Innovations team at http://www.partners.org/innovation

URL

Not provided

Condition Browse Module

MeSH Terms

ID	Term
D008175	Lung Neoplasms

Ancestor Terms

ID	Term
D012142	Respiratory Tract Neoplasms
D013899	Thoracic Neoplasms
D009371	Neoplasms by Site
D009369	Neoplasms

Browse Leaves

Not provided

Browse Branches

Not provided

Intervention Browse Module

MeSH Terms

ID	Term
D014057	Tomography, X-Ray Computed

Ancestor Terms

ID	Term
D007090	Image Interpretation, Computer-Assisted
D003952	Diagnostic Imaging
D019937	Diagnostic Techniques and Procedures
D003933	Diagnosis

Browse Leaves

Not provided

Browse Branches

Not provided