RlapsRisk® BC

Prognostic risk profiling for breast cancer

Next-generation AI testing from routine H&E to inform the treatment pathway for early breast cancer patients

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Relapse risk assessment helps oncologists select the best treatment plan for patients

14 secs

Incidence is high. Every 14 seconds, across the globe, a woman is diagnosed with breast cancer.⁴

+20%

Since 2008, worldwide breast cancer incidence has increased by more than 20 percent.⁴

10%

Approximately 10% of all patients will relapse after their initial treatment.⁵

70%

Nearly 70% of patients fall into the ER+/HER2- subgroup where there are a variety of treatments for oncologists to consider.

Risk of recurrence plays a significant role in the prognosis of the largest patient subgroup, ER+/HER2-.

Those who relapse enter a chronic disease phase and are significantly more likely to have worse outcomes. It’s pivotal to identify these patients as early as possible to adapt their treatment strategies and evaluate their eligibility for treatment escalation, including newer targeted therapies, like CDK4/6 inhibitors^{1 2}.

Identifying patients who are unlikely to relapse is also critical and a challenge. These patients may be able to safely avoid chemotherapies³, which often carry harsh side effects. But the risks attributed to relapse prompt oncologists to be conservative to avoid wrongly classifying high-risk patients, causing many to be potentially over-treated.

Current testing methods either lack consistency in accuracy^{6 7 8} do not address all subgroups effectively^{9 10} or they are expensive and not always accessible¹¹, such as gene expression tests. The stakes are high for risk assessment in early breast cancer to limit the number of patients who are under or over treated.

RlapsRisk® BC outperforms standard testing in accurately classifying patients as high or low risk in studies

International clinical studies show that RlapsRisk® BC can more precisely stratify patients into high and low risk groups than both traditional clinical factors assessments and gene expression tests*.

In the pre-specified pooled analysis, It significantly separated patients into two groups of risk with an hazard ratio of 7.42 (95% CI, 4.32–12.75). With a consistently high Negative Predictive Value (NPV) across different cohorts (88% – 97.4%), RlapsRisk® BC demonstrates it can also support safe identification of low risk patients. It also reclassifies those patients in the intermediate clinical risk category, and adds novel pathological based insights into the therapeutic decision making workflow¹².

By adding additional information to the diagnostic workflow, used stand-alone or in combination with genomic signatures, RlapsRisk® BC shows potential to help clinicians both reduce overtreatment and identify patients at higher risk who may benefit from adjuvant chemotherapy and other precision therapies¹².

* Based on a cohort containing patients only treated with endocrine therapy and enriched with patients who experienced a metastatic relapse

Pathology-based risk profiling makes precision testing more accessible and scalable

Risk stratification

Identifies typically difficult to classify subpopulations, such as grade 2 patients¹².

Rapid results

With a quick turn around time, results are ready in time for the tumor board.

Routine samples

By analyzing routine multi-modal data, level the playing field for patients with greater access to precision testing and personalized care.

Additional insights

RlapsRisk® BC’s AI image analysis is an independent prognostic factor¹², delivering critical tissue-level insights beyond standard clinical variables.

Meeting pathologists where they are to deliver results where they’re needed

Indication

Suitable for adults with primary invasive early breast cancer (ER+/HER2-).

Multimodal AI

Combines image analysis and patient clinical information: age, number of invaded lymph nodes, and tumor size.

PDF report

Easily accessible and supports pathologist interpretation.

Workflow agnostic

Deployment is feasible across existing IMS systems or IT settings.

RlapsRisk® BC’s development and clinical studies set the foundation for product robustness and generalizability

10k+ images

Developed and evaluated with high-quality imaging data from varied clinical settings and geographic regions.

9 centers

RlapsRisk® BC and previous prototypes have been tested in various international lab settings, for three years.

48 experts

Product development fostered in collaboration and informed by international breast oncology and pathology experts.

Solution Type	Specific AI Algorithm/App
Deployment Environment	Research Use Only (RUO)
Target	Breast Cancer
Platform Dependency	Platform Agnostic
Deployment Options	Hybrid (Cloud analysis, local viewer)