Spotlight Medical Announces Successful Independent Evaluation of Its Digital Slide-Based Test for Assessing Recurrence Risk in Early Breast Cancer

An independent, blinded evaluation of 620 patients from the phase III PANTHER trial identified nearly one-quarter as Low Risk despite clinically high-risk breast cancer, with favorable ten-year outcomes.

Spotlight Medical, a company developing AI-powered prognostic tests in oncology, today announced results from an independent evaluation of myStage Dx, its CE-IVDR-marked test for assessing recurrence risk in patients with hormone receptor-positive, HER2-negative early breast cancer. The study was conducted by researchers at Karolinska Institutet in Sweden.

Independent, Blinded Evaluation Using Phase III Trial Data

The study used data from 620 patients enrolled in PANTHER, an international randomized phase III trial comparing dose-dense with standard chemotherapy. myStage Dxpredictions were generated blinded to clinical outcomes. Researchers at Karolinska Institutet linked the predictions to patient outcomes and independently assessed prognostic performance according to a prespecified protocol and statistical analysis plan.

Within this clinically high-risk population, myStage Dx identified two groups with markedly different long-term outcomes. The Low Risk group comprised 23.5% of patients. At ten years, the estimated proportion alive and free from breast cancer recurrence was 96.1% in the Low Risk group, compared with 76.6% in the Not Low Risk group. The difference remained statistically significant after adjustment for standard clinicopathological prognostic factors. These findings build on earlier evidence from the CANTO and UNIRAD trial cohorts, published in the Journal of Clinical Oncology in 2025.

“Confidence in a clinical test has to be earned through independent scrutiny. We chose a blinded evaluation of myStage Dx by an independent research team, accepting that the results were outside our control. These findings are consistent with our previous studies and reinforce the test’s ability to address a concrete clinical problem: identifying patients with a favorable prognosis despite clinically high-risk disease, with a clear risk classification to inform treatment discussions,” says Dr. Marvin Lerousseau, co-founder and CSO of Spotlight Medical.

Refining Recurrence Risk Assessment to Support Clinical Decision-Making

Patients considered clinically high-risk may be eligible for additional treatment, including CDK4/6 inhibitors, yet their individual recurrence risks can vary substantially. In PANTHER, patients received chemotherapy and endocrine therapy without CDK4/6 inhibitors. By identifying a subgroup with favorable long-term outcomes under those treatment conditions, myStage Dx provides prognostic information to inform discussions about treatment strategy. These discussions should consider individual recurrence risk, the expected benefits and risks of additional treatment, and patient preferences, consistent with ASCO guidance.

“As ASCO guidelines highlight, accurately assessing recurrence risk is essential to treatment decisions. For patients, additional therapies can mean up to three more years of treatment, with side effects, anxiety, and a real impact on daily life. We are proud to show how myStage Dx can help oncologists better assess individual risk and support more informed clinical decisions, with the aim of improving patient care,” said Sylvain Berlemont, co-founder and CEO of Spotlight Medical.

About Spotlight Medical

Spotlight Medical is an oncology diagnostics company developing evidence-driven, clinical-grade AI tests to support more precise cancer care. The company combines routine pathology, clinical data and explainable AI to develop prognostic assays designed for practical adoption in oncology workflows.

About myStage Dx

myStage Dx is a software-only in vitro diagnostic medical device that has received CE marking under the European Union IVDR. It combines the analysis of a digitized histopathology slide with routinely available clinicopathological data to generate a prognostic classification intended for use by qualified healthcare professionals.

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