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Successful validation study results for LungLB®

2 Jan 2024 07:00

RNS Number : 2731Y
LungLife AI, INC
02 January 2024
 

 

LungLife AI, Inc. (the "Company" or "LungLife")

 

Successful validation of LungLB® in multi-site, prospective clinical study

 

LungLife AI (AIM: LLAI), a developer of clinical diagnostic solutions for the early detection of lung cancer, announces the successful validation of its LungLB® test for indeterminate lung nodules from a prospective, multi-site clinical study in the clinically important small nodules patient group.

 

In the study, LungLB® demonstrated:

 

· A strong positive predictive value (PPV) of 81% in discriminating benign from cancerous lung nodules in patients with smaller nodules (1, leading to material delays in diagnosis of deadly cancers.

· This performance in smaller nodules, similarly demonstrated in LungLife AI's lead-in study published in June 20232, typically represents earlier detection capability and improved patient outcomes and highlights the test's consistency.

· The small nodule group in this study is of utmost importance because it is comprised of ~87% "intermediate" risk nodules, which are the most challenging to evaluate and diagnose. Previous studies lack sufficient numbers of intermediate-risk nodules and is the reason why existing diagnostic tools perform poorly in this group. We believe this will also be of significant value to physicians.

· In-line with a high percentage of intermediate risk nodules, the test also outperformed the highly-validated Mayo Risk Model nodule evaluation tool, which is a commonly used baseline comparator, with an area under the curve (AUC)3 of 72% for LungLB® compared to 62% for Mayo.

· The results were also compared to Positron emission tomography (PET) scan, another tool often employed in nodule evaluation clinics. LungLB® outperformed PET by ~21% (81% vs 67% PPV) in the small nodule group, providing physicians with a more robust diagnostic tool in this area.

 

"Small lung nodules measuring less than 15 mm are often dismissed as 'probably benign' and monitored with serial imaging to avoid a potentially unnecessary biopsy. Yet, as the results of the latest LungLB® study demonstrated, many of these nodules are actually malignant and best managed with an immediate biopsy and treatment initiation without delay. LungLB® performed remarkably well in this validation study, warranting its consideration as a clinical biomarker for patients presenting with indeterminate pulmonary nodules," said Drew Moghanaki, MD, MPH, Professor and Chief of Thoracic Oncology at the University of California Los Angeles (UCLA) Department of Radiation Oncology, and Scientific Advisor to LungLife AI.

 

The validation study enrolled 425 patients across 17 hospital study sites who were scheduled to receive a lung nodule biopsy, of which 347 provided data that could be analysed. These results were driven by a 98-patient small nodules (

 

Paul Pagano, CEO of LungLife AI, said "The key finding from our validation study is LungLB® performed strongly in participants with smaller lung nodules. This is where physicians consistently indicate the greatest unmet need and where currently available tools fall short. This important clinical validation of the LungLB® test is a significant milestone for our Company. While we have identified small nodules as an early commercialisation opportunity, in the background we will continue to optimise the LungLB® test for additional indicated uses, while progressing on the next stage of our programme."

 

The study results are sufficient for publication and executing our commercial programme for LungLB® under our CLIA license and New York State CLEP permit. The initial launch of LungLB® will be through an Early Access Program in Q1 2024 as a Laboratory Developed Test offered from LungLife AI's CLIA laboratory in California and with follow-on work to support utility studies through its network of clinical investigators and early adopters.

 

1 Lokhandwala T, et al. Costs of Diagnostic Assessment for Lung Cancer: A Medicare Claims Analysis. Clin Lung Cancer. 2017 Jan;18(1):e27-e34. doi: 10.1016/j.cllc.2016.07.006. Epub 2016 Jul 21. PMID: 27530054.

2 https://bmcpulmmed.biomedcentral.com/articles/10.1186/s12890-023-02433-4

3 AUC is a commonly used metric that demonstrates an aggregate measure of performance and is useful in comparing diagnostic tests.

 

For further information please contact:

 

LungLife AI, Inc.

www.lunglifeai.com

Paul Pagano, CEO 

Via Walbrook PR

David Anderson, CFO

 

 

 

Investec Bank plc (Nominated Adviser & Joint Broker)

Tel: +44 (0)20 7597 5970

Virginia Bull / Cameron MacRitchie / Lydia Zychowska

Goodbody (Joint Broker)

Tom Nicholson / Cameron Duncan

 

Tel: +44 (0) 20 3841 6202 / +353 (1) 667 0420

Walbrook PR Limited

 Tel: +44 (0)20 7933 8780 or LungLifeAI@walbrookpr.com

Paul McManus / Alice Woodings / Phillip Marriage

Mob: 07980 541 893 / 07407 804 654 / 07867 984 082

 

About LungLife

LungLife AI is a developer of clinical diagnostic solutions designed to make a significant impact in the early detection of lung cancer, the deadliest cancer globally. Using a minimally invasive blood draw, the Company's LungLB® test is designed to deliver additional information to clinicians who are evaluating indeterminate lung nodules. For more information visit www.lunglifeai.com

 

About Lung Cancer

Lung cancer is the most fatal form of cancer worldwide and early detection is critical to achieve better outcomes. Early detection involves the evaluation of indeterminate lung nodules, of which there are over 1.5M identified by CT scan each year in the United States alone. Evaluation often involves significant unnecessary invasive procedures such as biopsy for patients with benign nodules and long delays in potentially curative treatment for patients with cancerous nodules that are selected for monitoring via non-invasive imaging. LungLB® is intended to help with earlier diagnosis in the evaluation process.

 

 

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