Cleveland Clinic Risk Calculator Surpasses Other Clinical Measures in Predicting Overall Survival of Patients with Non-Small Cell Lung Cancer

Researchers at Cleveland Clinic have developed a risk calculator to predict overall survival of patients with non-small cell lung cancer (NSCLC) after stereotactic body radiation therapy (SBRT), a type of external radiation therapy that uses special equipment to position the patient and precisely deliver radiation to a tumor. This work was recently published in JCO Clinical Cancer Informatics.

Risk calculators are crucial for treating NSCLC, due to the high variability in survival rates. The newly published research demonstrates that use of the persistent homology (PHOM) score of a patient’s CT scan, which is information derived from the risk calculator, is the strongest predictor of overall survival of any standard clinical measure.

Researchers developed a radiomic nomogram, representing the relations between key variables, as a new method of calculating risk beyond patient-specific histopathologic and clinical variables. A subdiscipline of machine learning, radiomics involves extracting high-dimensional data from images such as CT scans to better understand tumor biology and behavior. By extracting features from imaging data and applying predictive models, researchers can visualize disease characteristics not visible to the human eye.

“Traditionally, when we thought about patient survival, we relied on factors such as tumor size, patient age and whether the disease had metastasized,” said Jacob Scott, M.D., DPhil, study co-author and head of the Theory Division Laboratory in the Department of Translational Hematology and Oncology Research at Cleveland Clinic. “Adding the radiomic nomogram factor transforms the way we predict outcomes.”

Using a PHOM score, researchers can analyze and quantify a tumor’s structure so it can be used in predictive modeling. The resulting metric quantifies the 3D structure of a tumor and connects that to a patient’s clinical outcome.

The risk calculator is available for clinicians to use to help support treatment-related decisions. In addition to helping predict overall survival, the risk calculator has the potential to guide clinicians in choosing the appropriate treatment option for each patient. To further validate the nomogram, researchers hope to study matched sets of patients with early-stage NSCLC treated by removing a tumor from their lung alone.