Currently, several models are used to pre-screen patients for lung cancer and to determine eligibility for CT scans. However, most of these models are designed specifically for smokers and cannot accurately predict the risk of lung cancer in non-smokers. Furthermore, many of these models impose age restrictions, typically between 55 and 75 years, and their effectiveness has been tested against limited racial demographics.
The Brock Calculator, for one, is widely used in clinical settings to evaluate the likelihood of lung nodules being cancerous. As it requires information regarding nodule size, a CT scan must be completed to accurately determine a patient’s risk of lung cancer. The fact of the matter is, CT scans are expensive and put patients at risk of radiation exposure. How do we accurately determine if a patient even needs to get a CT scan?
There are other pre-CT calculators. The LLP version 3 pre-screens patients and determines their likelihood of developing cancer without the need for a CT scan. However, not only is it limited to patients between 50 and 79 years of age,its reliance on clinical and radiological parameters without incorporating biomarker data or individualised patient information results in an oversimplification of the complexity of lung cancer. This leads to inaccuracies in the model, which may affect patient care or clinical decisions. How do we take a patient-centric approach that accounts for the genetic background of patients?
That’s where we come in! Analysing patient biomarker data against our model, we provide an individualised method of determining whether patients are at likely to develop cancer in the future. We believe that this improvement will lead to more personalised screening strategies, ensuring that CT scans are reserved for those who truly need them, thus optimising patient care and resource allocation.