Bringing New Dimensions to Breast Cancer Research with Dynamic RWD

Detailed real-world dataset covering bio and genetic markers for comprehensive breast cancer research.

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The Briya Breast Cancer Dynamic Dataset Coverage includes:

> 40,000 patients
> 16 years of longitudinal, linked patient data spanning hospitalizations, outpatient encounters, and community care (HMO) follow-up for the full continuum of care
Detailed patient demographics (incl. age, ethnicity, gender)
Family history (incl. genetic disorders)
Genetic tests: BRCA1, BRCA2, PALB2, CHEK2, TP53
Pregnancy history
Lab tests: Complete Blood Count (CBC), Liver Function Tests (LFTs), Renal Function Test, Serum Tumor Markers (CA 15-3, CEA)
Imaging Studies: Mammography, Ultrasound, MRI, CT or PET/CT, bone scan
Pathology reports: biopsy Type (CNB, Excisional Biopsy), Histologic Grade, Tumor Stage (TNM Classification), Molecular Subtype (ER / PR / HER2)
Medication reports
Number of encounters

Briya’s Dynamic Dataset: Transforming Breast Cancer Research

Breast cancer remains the most commonly diagnosed cancer among women worldwide, accounting for approximately 30% of all new cancer cases in U.S. women each year. Beyond its high prevalence, breast cancer outcomes continue to show significant disparities by geography and across races and ethnicities, with higher incidence rates observed in transitioning and developing countries.

The disease’s variability underscores the need for more data-driven, personalized treatment plans. These plans must consider patients’ ethnic backgrounds, genetic biomarkers (both somatic, such as PIK3CA, GATA3, TP53, and MAP3K1 mutations, and germline, such as BRCA1), as well as other variables that define high-risk populations. This information is crucial for delivering personalized treatments that meet individual patient needs and accurately predict therapy response.

Big data is at the heart of this transformation, enabling life sciences and research teams to conduct clinical studies that have the potential to reshape cancer care. Briya’s Breast Cancer Dynamic Dataset is a game-changing resource designed to increase research efficiency and improve the accuracy of real-world evidence (RWE) at scale.

By integrating dynamic, high-quality real-world data from diverse sources – including patient demographics, treatment histories, physicians’ notes, imaging studies, and genetic profiles – the dataset offers a comprehensive view of the patient journey. Spanning multiple sites and over a decade of coverage, it captures a highly accurate and complete picture of the patient-journey. With data points that are continuously revisitable and updatable, the dataset stays relevant and evolves alongside ongoing research.

This level of granularity empowers researchers to build highly personalized treatment strategies, improve therapeutic efficacy, identify high-risk populations for earlier secondary detection, predict disease progression, and optimize screening protocols, all with the goal of enhancing early detection and improving outcomes for patients around the world.