RlapsRisk® BC
Prognostic risk profiling
for breast cancer
Clinical context
Relapse risk assessment helps oncologists select the best treatment plan for patients
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 inhibitors1,2.
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 accuracy6, 7, 8, do not address all subgroups effectively9,10, 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
The study population illustrated in the animation has been condensed to a representative population of 100 patients. The circles represent a percentage of patients who did not experience an event during the 10 year time period. The diamonds represent a percentage of patients who did experience an event during the 10 year time period.
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
Benefits
Pathology-based risk profiling makes precision testing more accessible and scalable
Identifies typically difficult to classify subpopulations, such as grade 2 patients12
With a quick turn around time, results are ready in time for the tumor board
By analyzing routine multi-modal data, level the playing field for patients with greater access to precision testing and personalized care
RlapsRisk BC’s AI image analysis is an independent prognostic factor12, delivering critical tissue-level insights beyond standard clinical variables
RlapsRisk® BC features
Meeting pathologists where they are to deliver results where they’re needed
Suitable for adults with primary invasive early breast cancer (ER+/HER2-).
Combines image analysis and patient clinical information: age, number of invaded lymph nodes, and tumor size.
Easily accessible and supports pathologist interpretation.
Deployment is feasible across existing IMS systems or IT settings.
In clinical routine
Integrating AI diagnostics seamlessly into the therapeutic and pathology workflows
Clinical utility
RlapsRisk BC’s development and clinical studies set the foundation for product robustness and generalizability
Read the research behind RlapsRisk BC
Research and development
Timeline of milestones
![POC clinical validation published in Nature Communications [13]](https://cdn.prod.website-files.com/6408a35ee5a5ec2f39a4afc9/6862bc082733bcb238954cd6_nature-comms-timeline.png)
Citations
- Mastro LD, Mansutti M, Bisagni G, Ponzone R, Durando A, Amaducci L, et al. Extended therapy with letrozole as adjuvant treatment of postmenopausal patients with early-stage breast cancer: a multicentre, open-label, randomised, phase 3 trial. Lancet Oncol. 1 oct 2021;22(10):1458‑67
- Harbeck N, Rastogi P, Martin M, Tolaney SM, Shao ZM, Fasching PA, et al. Adjuvant abemaciclib combined with endocrine therapy for high-risk early breast cancer: updated efficacy and Ki-67 analysis from the monarchE study. Ann Oncol. 1 déc 2021;32(12):1571‑81
- Ferreira AR, Di Meglio A, Pistilli B, Gbenou AS, El-Mouhebb M, Dauchy S, et al. Differential impact of endocrine therapy and chemotherapy on quality of life of breast cancer survivors: a prospective patient-reported outcomes analysis. Ann Oncol Off J Eur Soc Med Oncol. 1 nov 2019;30(11):1784‑95
- Breast Cancer Statistics And Resources
- Long-term hazard of recurrence in HER2+ breast cancer patients untreated with anti-HER2 therapy, Strasser-Weippl et al. 2015, BMC.
- Gown AM. Current issues in ER and HER2 testing by IHC in breast cancer. Mod Pathol. 2008 May;21 Suppl 2:S8-S15. doi: 10.1038/modpathol.2008.34. PMID: 18437174
- Casterá C, Bernet L. HER2 immunohistochemistry inter-observer reproducibility in 205 cases of invasive breast carcinoma additionally tested by ISH. Ann Diagn Pathol. 2020 Apr;45:151451. doi: 10.1016/j.anndiagpath.2019.151451. Epub 2019 Dec 17. PMID: 31955049.
- Polley MY, Leung SC, McShane LM, et al. An international Ki67 reproducibility study. J Natl Cancer Inst. 2013 Dec 18;105(24):1897-906. doi: 10.1093/jnci/djt306
- Kalinsky K, Barlow WE, Gralow JR, et al. 21-Gene Assay to Inform Chemotherapy Benefit in Node-Positive Breast Cancer. New England Journal of Medicine (NEJM), 2021. DOI:10.1056/NEJMoa2108873
- Del Mastro L, Lambertini M, Pondé N, et al. Tailoring adjuvant chemotherapy and ovarian function suppression in premenopausal patients with HR+/HER2− early breast cancer: a critical review. Cancer Treatment Reviews, 2021. DOI: 10.1016/j.ctrv.2021.102010
- Blok EJ, Bastiaannet E, van den Hout WB, et al. Systematic review of the clinical and economic value of gene expression profiles for invasive early breast cancer available in Europe. Cancer Treat Rev. 2018 Jan;62:74-90. doi: 10.1016/j.ctrv.2017.10.012
- Manuscript under review with peer reviewed journal, and available as a pre-print on medRxiv: https://www.medrxiv.org/content/10.1101/2025.07.18.25331788v2
- Garberis, I., Gaury, V., Saillard, C. et al. Deep learning assessment of metastatic relapse risk from digitized breast cancer histological slides. Nat Commun 16, 5876 (2025)