From Binary to Spectrum

While I’m still processing the fantastic learnings that I took away from the SGO Congress in April, the ESMO Breast Cancer 2026 congress in Berlin (May 6-8) provided me with a crucial look into the future of breast cancer treatment. 

Major breakthroughs are often reserved for ASCO or the main ESMO congress, but when reviewing my notes from different sessions at ESMO Breast Cancer, I spotted some interesting trends that are likely to redefine the market in the future. As a researcher at Ipsos, identifying these under-the-radar strategic shifts is one of my favourite tasks.

The key words here are ‘ultra precision’. If you are familiar with the world of oncology, you might think this is not new. However, here we are reaching levels signalling a proper revolution. Four examples:

1. Deconstruction of "ER-Positive": From Binary to Spectrum: The simple distinction between HR+ and TNBC is becoming obsolete. The ‘Rapid Fire Oral 1’ session featured an intense debate on ER-low (1-10%) tumours. From a business perspective, this could result in a ‘market migration’, i.e., if the "Swedish perspective" (where ER<10% is considered ER-negative) gains traction, a significant patient segment could shift from the endocrine therapy market to the chemo/IO/ADC market. This creates a direct commercial threat for some portfolios and a major opportunity for others, while simultaneously creating a new market for diagnostics that can properly stratify this ambiguous group.
    
2. AI-powered risk stratification and expansion of the ‘high-risk’ group: Clinical factors or single genomic scores are no longer the only asset to define risk status. The PathClinRS AI model was a great example. By integrating digital pathology (H&E slides), genomics (Oncotype score), and clinical data, the model proved superior at predicting long-term recurrence. The model identified almost twice as many "high-risk" node-negative patients as the NATALEE trial criteria. For companies with adjuvant therapies like CDK4/6 inhibitors, AI tools represent a potential gateway to a significantly larger addressable market.
    
3. ctDNA could be used as a strategy to treat only those patients who really need it. Two examples: 
   
   — On the de-escalation strategy: in the 5-year update of the PHERGain trial including HER2+ patients, ctDNA was used to validate a chemo-free approach. Patients who achieved early ctDNA clearance had outstanding long-term outcomes; with such patients, clinicians could adopt less intensive, less toxic regimens. 
   
   — On escalation treatment: in the Pyrotinib study, ctDNA helped identify treatment failure long before scans could. If ctDNA was still detectable, the patient was almost certain to have residual disease, prompting escalation to more intensive therapy.
    
4. The outcome of neoadjuvant treatment is no longer a ‘yes/no’ situation: The neoadjuvant setting has long been dominated by Pathological Complete Response (pCR). However, the Destiny Breast-11 trial focused on Residual Cancer Burden (RCB). A drug no longer needs to achieve complete response to prove value; shifting patients from RCB-II to RCB-I is now considered clinically meaningful.

To find out more about Ipsos’ real-world research solutions in oncology, contact [email protected].