Introduction
We help to transform complex clinical data into meaningful, patient-focused insights. In a recent post-marketing initiative, our Evidence & Value Generation (EVG) team applied the Q-TWiST methodology to evaluate a novel oncology treatment—delivering a compelling narrative around benefit-risk balance.
What is Q-TWiST?
Q-TWiST (Quality-adjusted Time Without Symptoms or Toxicity) is a health economics method that integrates survival outcomes with quality of life. It breaks down survival time into three key health states:
- TOX – Time with treatment-related toxicity
- TWiST – Time without symptoms or toxicity
- REL – Time after disease relapse
Each state is weighted using EQ-5D-5L utility scores, reflecting the patient’s experience and preferences.
Key Findings
Using restricted mean survival time (RMST) and non-parametric bootstrapping, we compared Q-TWiST across treatment arms and biomarker-defined subgroups. The results were clear:
- >15% Q-TWiST gain for the investigational therapy
- Longer TWiST and reduced TOX exposure
- Clinically meaningful improvements in both survival and tolerability
These insights support a strong value proposition for modern cancer therapies – where quality of life matters as much as quantity.
Why It Matters
This analysis goes beyond traditional endpoints to answer a critical question: “What does this treatment mean for the patient’s day-to-day life?”
It’s a powerful tool for:
- HTA submissions
- Global value dossiers
- Strategic evidence generation
Our Expertise
We specialize in bridging the gap between clinical trial outcomes and payer-relevant evidence. Our team brings deep expertise in:
- Advanced statistical modelling
- Utility integration
- Real-world value communication
Whether you’re preparing for reimbursement discussions or building a global evidence strategy, we deliver credible, data-driven insights tailored to today’s evolving healthcare landscape.
Services Provided
- Evidence and Value Generation
Discover how Veramed can also provide you with flexible and collaborative statistical support, from study design through to submission and beyond.
