Study confirms clinical decision impact of genomic diagnostic test in breast cancer

A new study has revealed that the HER2DX diagnostics test impacts clinical decision making in early-stage HER2-positive breast cancer, leading to modifications in treatment plans.

Developed by Reveal Genomics, HER2DX was shown to impact treatment decisions in a cohort of 297 patients with stage I-III HER2+ breast cancer across multiple hospitals in Spain.

The primary findings reveal that HER2DX led to a modification in the treatment plan in 48.1 per cent of cases, with most changes (75.5 per cent) leading to a reduction in treatment intensity, reducing chemotherapy and/or anti-HER2 without compromising outcomes.

HER2DX also demonstrated strong predictive capability, accurately identifying patients with a higher likelihood of achieving a pathologic complete response (pCR [remission]).

Additionally, oncologists reported a significant increase in confidence when making treatment decisions based on HER2DX data.

Finally, the study also underscored the economic benefits of incorporating HER2DX into clinical practice, with healthcare cost savings when drug costs and type of vein access were taken into account.

Dr. Olga Martínez Sáez, breast medical oncologist at Clinic Barcelona Comprehensive Cancer Center and principal investigator of the study, said: “This study represents a significant step forward in personalised oncology. HER2DX enables physicians to make precision-guided decisions with greater confidence, improving patient care.”

Dr. Juan Miguel Cejalvo, breast medical oncologist at Hospital Clínico Universitario de Valencia/INCLIVA, and co-PI of the study, said: “These results confirm that HER2DX provides valuable information that can refine treatment strategies, allowing for more personalised care while maintaining excellent outcomes.”

Dr. Antonio Llombart-Cussac, head of the medical oncology department at Hospital Arnau de Vilanova in Valencia, and investigator of the study, highlighted the impact on clinical practice, said: “The capacity to forecast a patient’s therapeutic response prior to treatment initiation allows oncologists to adjust treatment intensity appropriately, effectively reducing unnecessary toxicity and healthcare costs.”