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Respiratory Tract Neoplasms

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Respiratory Distress Syndrome, Infant

Acute Respiratory Distress Syndrome

Acute Graft Versus Host Disease

Subjects who provide informed consent and meet the eligibility criteria will have 50 ml of blood collected and sent to Freenome or Freenome's designee for processing, testing, and storage, and will then complete a standard-of-care screening LDCT.

blood draw

April Allison, BS

Harris Naemi, BS / Joye Choy, BS

Study Coordinator

Chuanbo Xu, PhD

Nasibeh Vatankhah, MD

The PROACT LUNG study is a prospective multi-center observational study to validate a blood-based test for the early detection of lung cancer by collecting blood samples from high-risk participants who will undergo a routine, standard-of-care screening Low-Dose Computed Tomography (LDCT).

This is a prospective, multi-center, observational study to evaluate the performance of the Freenome Multiomics Blood Test in screening eligible participants for lung cancer.

Enrollment will be open to all eligible participants for screening chest CT scan as part of the Standard of Care (SOC) for lung cancer. Subjects who meet the eligibility criteria for this study and provide informed consent will be enrolled and blood sample collection must be completed within 30 days of signing the informed consent. Optimally, the screening chest CT will be completed on the same day of the study blood collection, however up to 45 days will be allowed after study blood collection to obtain a screening chest CT.

The study will also collect demographic data and relevant clinical data, such as medical history, lifestyle, occupational and environmental exposure(s), family history, and clinical laboratory data. All reports and clinical notes regarding the diagnostic tests and procedures related to lung cancer diagnosis or lung lesion assessment, such as histopathology and bronchoscopy reports, and diagnostic/follow-up images and imaging reports will be collected as part of follow up to the screening chest CT scan.

All enrolled subjects will be followed prospectively from the date of the baseline screening chest CT until a minimum of 24 months, or until a premature study endpoint inclusive of withdrawal of consent or death.

Blood specimens will be de-identified and used to validate the performance characteristics of the Freenome Multiomics Blood Test

Clinical Validation of Freenome Multiomics Blood Test for Lung Cancer Screening

The PROACT LUNG Study: A Prospective, Observational,Clinical Validation Study of the Freenome Multiomics Blood Test for Lung Cancer Screening (FRNM-007)

Clinical performance of the Freenome Blood Test, including sensitivity and specificity, in detecting lung cancer in subjects with positive and negative lung cancer outcomes during a 12-month follow-up period

Clinical performance of the Freenome Blood Test, including sensitivity and specificity, in detecting lung cancer in subjects with positive and negative lung cancer outcomes during a 24-month follow-up period

Freenome Holdings Inc.

Immune System Diseases

Skin and Connective Tissue Diseases

Hypersensitivity

Sarcoma

Osteosarcoma

Neoplasms, Connective and Soft Tissue

Neoplasms by Histologic Type

Neoplasms, Bone Tissue

Neoplasms, Connective Tissue

Soft Tissue Sarcoma

thoracic CT examinations for pre-treatment staging and/or subsequent post-treatment follow-up.

computed tomography

Osteosarcoma is regarded as most common malignant bone tumor in children and adolescents. Approximately 15% to 20% of patients with osteosarcoma present with detectable metastatic disease, and the majority of whom (85%) have pulmonary lesions as the sole site of metastasis. Previous studies have shown that the overall survival rate among patients with localized osteosarcoma without metastatic disease is approximately 60% to 70% whereas survival rate reduces to 10% to 30% in patients with metastatic disease. Though lately, neoadjuvant and adjuvant chemotherapeutic regimens can decline the mortality rate, 30% to 50% of patients still die of pulmonary metastases. Number, distribution and timing of lung metastases are of prognostic value for survival and hence computed tomography (CT) thorax imaging still plays a vital role in disease surveillance. In the last decade, the technology of multidetector CT scanner has enhanced the detection of numerous smaller lung lesions, which on one hand can increase the diagnostic sensitivity for lung metastasis, however, the specificity may be reduced. In recent years, deep-learning artificial intelligence (AI) algorithm in a wide variety of imaging examinations is a hot topic. Currently, an increasing number of Computer-Aided Diagnosis (CAD) systems based on deep learning technologies aiming for faster screening and correct interpretation of pulmonary nodules have been rapidly developed and introduced into the market. So far, the researches concentrating on the improving the accuracy of benign/malignant nodule classification have made substantial progress, inspired by tremendous advancement of deep learning techniques. Consequently, the majority of the existing CAD systems can perform pulmonary nodule classification with accuracy of 90% above. In clinical practice, not only the malignancy determination for pulmonary nodule, but also the distinction between primary carcinoma and intrapulmonary metastasis is crucial for patient management. However, most existing classification of pulmonary nodule applied in CAD system remains to be binary pattern (benign Vs malignant), in the lack of more thorough nodule classification characterized with splitting of primary and metastatic nodule. To the best of our knowledge, only a few studies have focuses on the performance of deep learning-based CAD system for identifying metastatic pulmonary nodule till now. In this proposed study, the investigators sought to determine the accuracy and sensitivity of one computer-aided system based on deep-learning artificial intelligence algorithm for detection and risk stratification of lung nodules in osteogenic sarcoma patients.

Accuracy of Deep-learning Algorithm for Detection and Risk Stratification of Lung Nodules

Feasibility Study: Accuracy and Sensitivity of Deep-learning Artificial Intelligence (AI) Algorithm for Detection and Risk Stratification of Lung Nodules in Osteogenic Sarcoma Patients

proportion of true results(both true positives and true negatives) among whole instances

true positive rate in percentage(%) derived by ROC analysis

true negative rate in percentage (%) derived by ROC analysis

FPs/scan in number (N) based on free-response receiver operating characteristic (FROC) analysis

Competitive performance metric (CPM) is a criterion used for CAD system evaluation. Based on FROC paradigm, CPM score is computed as an average sensitivity at seven predefined average false positive rates. CPM score ranges from 0 to 1, with higher CPM score indicating better CAD performance.

IBM China/Hong Kong Limited

Chinese University of Hong Kong

Professor

Video

2 questionnaires pre and post procedure taking approximately 15 minutes each to complete.

Questionnaires

Stephen McRae, MD

Objective:

To compare changes in patient anxiety levels between groups of patients who either were or were not exposed to an informative multimedia patient education tool, in order to determine how the addition of such a multimedia tool will affect this parameter. Specifically, the study will focus on subjective anxiety as measured on pre procedure and post procedure patient surveys as detailed under study components.

If you agree to take part in this study, you will complete a questionnaire that asks how you feel before the procedure. It will take about 5 minutes to complete.

After you have completed the questionnaire, you will be randomly assigned (as in the flip of a coin) to Group 1 or Group 2. You will have an equal chance of being in either group.

If you are in Group 1, you will receive routine information before the lung biopsy and you will watch a video on a handheld or laptop machine with headphones. The video is designed to help you understand the biopsy procedure. This video should last about 5 minutes. You will then complete a questionnaire that asks how you feel after watching the video. It will take about 5 minutes to complete.

If you are in Group 2, you will receive routine information before the lung biopsy. You will then complete another questionnaire that asks how you feel before the procedure. It will take about 5 minutes to complete.

After your routine lung biopsy, both groups will complete a questionnaire that asks how you feel after the procedure. It will take about 5 minutes to complete.

For Group 1, the total time to complete the questionnaires and watch the video will be 20 minutes.

For Group 2, the total time to complete the questionnaires will be 15 minutes.

Length of Study:

Your participation in this study will be over once you complete the questionnaire after your lung biopsy.

This is an investigational study.

Up to 100 patients will take part in this study. All will be enrolled at M. D. Anderson.

Multimedia Patient Education

Increasing Patient Preparedness for the Procedural Experience and Improving Qualitative Outcomes Through Patient Education

Subjective anxiety as measured on pre procedure and post procedure patient surveys.

M.D. Anderson Cancer Center

thoracic CT examinations for diagnosis, and/or follow-up.

Lung cancer is one of main cause of cancer death in worldwide, characterized of low 5-year survival rate of less than 20%. Pulmonary nodule is considered as the typical imaging manifestation in early stage of lung cancer. The National Lung Screen Trial has demonstrated that the mortality rates could decline greatly, by the utility of low-dose helical computed tomography for screen of pulmonary nodules. Thus, automatic detection, diagnosis and management of pulmonary nodules, play the vital roles in computer-aided lung cancer screening and early intervention.

D-Lung: An Analytics Platform for Lung Cancer Based on Deep Learning Technology

D-Lung: An Analytics Platform for Primary Lung Cancer Screening, Diagnosis and Management Based on Deep Learning Technology

Department of Computer Science & Engineering, CUHK

Multiple Pulmonary Nodules

Patients with one or more pulmonary nodules 5-15 mm in diameter.

All patients will undergo serial CT scans after 3 months, 6 months, 9 months, 12 months, 18 months, and 24 months as is standard care. Nodules are to be scanned at 2.5mm collimation / 1.25 mm reconstruction. This resolution is necessary for volume measurements of nodules less than 1cm in diameter.

CT Scan

Marc Feinstein, MD

In recent years, more and more people are having lung CT scans performed to screen for various cancers. Many of them have small abnormalities detected, called "nodules", which - for a variety of reasons - doctors are unable to biopsy. As a result, many patients have their CT scans repeated on a regular basis to see if their nodules grow. This process can last several years.

Many patients experience significant anxiety during this process, when they are aware of a spot in the lung, but are not told any specific cause.

Researchers at Memorial Sloan-Kettering have developed a new way to look at lung nodules in three dimensions. The purpose of this project is to see if any change in the nodules can be detected sooner by this method than by traditional CT scans.

Study title	NCT ID	Conditions	Interventions	Eligibility	Organization
Clinical Validation of Freenome Multiomics Blood Test for Lung Cancer Screening	NCT06122077	Lung Cancer Dia...	blood draw	50 Years -	Freenome Holdings Inc.
Accuracy of Deep-learning Algorithm for Detection and Risk Stratification of Lung Nodules	NCT04022512	Osteogenic Sarc...	computed tomogr...	- 18 Years	Chinese University of Hong Kong
Multimedia Patient Education	NCT01184534	Lung Cancer	Video Questionnaires	18 Years -	M.D. Anderson Cancer Center
D-Lung: An Analytics Platform for Lung Cancer Based on Deep Learning Technology	NCT04036903	Lung Cancer	computed tomogr...	-	Chinese University of Hong Kong
3-D Reconstruction of CT Scan Images in the Evaluation of Non-Specific Pulmonary Nodules	NCT00613041	Undiagnosed Pul... Lung Nodules	CT Scan	18 Years -	Memorial Sloan Kettering Cancer Center

Spots Global Cancer Trial Database for lung nodules

Every month we try and update this database with for lung nodules cancer trials from around the world to help patients and their families find trials that might be right for them.
We offer this 100% free of charge and do not endorse any of the trials listed here, we hope it helps you or a loved one.