Observational Study That Will Analyse the Spread and Stratification of Lung Cancer Risk Using Artificial Intelligence

N/ANot Yet RecruitingNCT07617636

AstraZeneca1,500 enrolled

Overview

Observational cohort study involving individuals of both sexes with a history of smoking, residing in municipalities in the state of Bahia and attended by the mobile unit, with the aim of evaluating the integration of artificial intelligence (AI) in the detection of pulmonary nodules and the prediction of ASCT in high-risk individuals undergoing CT screening.

The main objective of the study is compare the performance of a Sybil AI tool with the LungRADS classifications assigned by radiologists for the risk stratification of pulmonary nodules. Furthermore, it aims to assess the correlation between the AI-predicted STAS and histopathological confirmation, alongside imaging and AI results. The hypothesis is that the Sybil AI model will demonstrate comparable predictive accuracy and that the features predicted by the AI will correlate with the presence of STAS.

Study Type

OBSERVATIONAL

Enrollment

1,500

Conditions

Lung Cancer

Eligibility

Sex: ALLMin age: 50 YearsMax age: 80 Years

Medical Language ↔ Plain English

Inclusion Criteria: * Individuals of both sexes, smokers or former smokers for a maximum of 15 years; * Smoking history of 20 pack-years or more; * Between 50 and 80 years old; * Provision of Free and Informed Consent in writing, signed and dated. Exclusion Criteria: * Individuals who are unable to undergo a CT scan; * Individuals who cannot tolerate lying on their back for more than 10 minutes continuously; * Individuals who present with symptoms highly suggestive of lung cancer (hemoptysis, chest pain, altered cough pattern, unintentional weight loss greater than 10 kg); * Diagnosis of severe heart disease while using multiple medications; * Diagnosis of severe lung disease, using multiple medications and/or requiring home oxygen therapy; * History of radiation therapy to the chest area; * Individuals undergoing cancer evaluation or treatment; * Individuals exhibiting signs of respiratory distress (nasal flaring, suprasternal retraction, use of accessory muscles, cyanosis); * Pregnancy.

Locations (1)

Research Site

São Paulo, Brazil

Outcomes

Primary Outcomes

Lung cancer risk stratification

Measured by the agreement between the results of the Sybil AI model and the LungRADS classifications assigned by the radiologist

Time frame: through study completion, an average of 1 year

Secondary Outcomes

Presence of STAs

Conceptual definition: STAS is a histopathological finding in lung adenocarcinoma, in which tumor cells are observed disseminated in the alveolar spaces beyond the main tumor margin. o Operational definition: Presence of STAS confirmed by centralized histopathological review of lung tissue samples (biopsy or resection). The review is performed by pathologists who are unfamiliar with IA/radiological assessments

Time frame: through study completion, an average of 1 year

Histological diagnosis of lung cancer

Confirmed by means of biopsy or surgical specimen with pathological subtyping.

Time frame: through study completion, an average of 1 year

Central Contacts

AstraZeneca Clinical Study Information Center

CONTACT

1-877-240-9479 information.center@astrazeneca.com

Data from ClinicalTrials.gov

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