Understanding the HER2⁺ Metastatic Breast Cancer Patient Journey

A leading biopharmaceutical company sought a clearer, data driven understanding of the HER2⁺ metastatic breast cancer (mBC) patient journey to inform forecasting, brand strategy, and medical engagement.

Although the team possessed directional insights, they lacked a unified view across several critical areas.

• Limited visibility into the real world patient landscape
  The client needed to accurately identify newly diagnosed HER2⁺ mBC patients and profile them by demographics, comorbidities, previous radiation or surgery, and treating provider types. Fragmented data sources made it difficult to build a robust foundation for strategic planning.
• Unclear diagnosing and treating HCP dynamics
  Understanding how different specialists — including oncologists, surgeons and radiologists — contribute across the care continuum was essential to optimising field force targeting and enhancing patient support pathways.
• Inconsistent line of therapy (LOT) definitions
  A major barrier to generating meaningful insight was the absence of standardised, repeatable LOT logic. Without consistent rules governing regimen definition, switching, discontinuation and line advancement, treatment patterns could not be analysed reliably.
• Need for accurate volume projections
  The client required dependable projected patient volumes by regimen and line of therapy to support commercial, medical and operational planning.

A streamlined analytics framework was developed to create a clear, end-to-end understanding of the HER2⁺ mBC patient journey.

• Precise patient identification and profiling
  Newly diagnosed patients were accurately identified and profiled using validated clinical and claims based criteria, capturing demographics, comorbidities, previous treatments and provider involvement.
• Development of standardised LOT logic
  A consistent methodology for defining lines of therapy was implemented, ensuring clarity around treatment initiation, discontinuation, switching behaviour and line advancement.
• Mapping real world treatment patterns
  Applying this LOT logic revealed distinct real world treatment patterns, including the dominance of dual agent therapy in first line (94%), greater variability and more frequent therapy gaps in later lines, and highly stable treatment behaviour in fourth line, where 98% of patients remained on the same regimen.
• Forecasting patient volumes
  Projection factors were used to translate real world patterns into reliable patient volume estimates by line and regimen, supporting more accurate planning and strategic decision making.

Most patients began treatment with a dual agent targeted regimen, with 94% initiating therapy this way. As patients progressed, treatment choices in later lines became increasingly variable, and therapy gaps were more common — often reflecting tolerability challenges or comorbidity-related considerations. By the fourth line of therapy, treatment patterns stabilised significantly, with 98% of patients remaining on the same regimen.

• Real-world treatment patterns are more consistent than expected
  The confirmation of widespread dual agent first line use and stable fourth line treatment behaviour provided robust evidence to support strategic alignment across brand and medical functions.
• Later-line gaps highlight opportunities
  Patterns of treatment interruption pointed to opportunities for enhanced patient support, improved toxicity management education and more targeted HCP engagement.
• LOT standardisation creates a single source of truth
  A unified LOT logic enabled cross-functional teams to work from consistent insights — strengthening forecasting, strategic planning and portfolio discussions.
• Enhanced HCP targeting
  Understanding which HCPs diagnose, initiate or maintain therapy enables more effective engagement strategies and more tailored medical education initiatives.