When strong
clinical results are
not enough

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The critical evidence challenge

Behind HTA and market access decisions.

Strong clinical results do not automatically translate into robust comparative evidence.

As evidence requirements evolve, the relevance of populations, comparators, outcomes and analytical approaches is increasingly scrutinised. The challenge is not simply whether evidence exists, but whether it remains credible, transparent and decision-relevant under assessment.


Strong clinical results do not
automatically translate into robust comparative evidence.


As evidence requirements evolve, the relevance of populations, comparators, outcomes and analytical approaches is increasingly scrutinised. The challenge is not simply whether evidence exists, but whether it remains credible, transparent and decision-relevant under assessment.


Explore evidence decoded ➝

The questions evidence teams face

  • How much residual uncertainty will HTA reviewers tolerate?

  • Can comparative evidence remain credible without head-to-head data?

  • What happens when the original comparator no longer reflects clinical practice?

  • Which assumptions are most vulnerable under critical review?

  • Can heterogeneous evidence sources be combined without weakening interpretability?

  • How can uncertainty be communicated transparently without undermining confidence in the evidence?

Where comparative evidence becomes vulnerable

Comparator relevance

When the decision

context changes from

design to submission

Clinical programmes are often designed years before HTA assessment begins. During that time, standards of care, treatment pathways and local requirements can change.

• PICO relevance
• Alignment with local treatment pathways
• Transferability across markets
• Interpretation of comparative benefit

How can comparative effectiveness be demonstrated when the original study design no longer fully reflects the assessment context?

➝ Comparative Evidence Strategy

➝ Comparator Alignment

➝ Evidence Feasibility

No head-to-head data

When direct

comparative

data do not exist

In many therapeutic areas, randomised head-to-head trials are unavailable, particularly for rare diseases. Consequently, comparative decisions are forced to rely on indirect evidence.

• Study populations may differ
• Prognostic variables and effect modifiers are not adequately addressed
• Methodological assumptions remain unclear
• Heterogeneity remains unresolved

How can indirect comparative evidence provide a robust basis for HTA decisions when head-to-head data are unavailable?

➝ MAIC

➝ ML-NMR

➝ STC

➝ ITCs based on full IPD

➝ Quantifying uncertainty

Heterogeneous evidence

When evidence comes

from multiple and

fragmented sources

Rare diseases, oncology and accelerated development programmes often require evidence from clinical trials and real-world sources to build a broader evidence base.

• Selection bias
• Missing data
• Inconsistent endpoint definitions
• Unmeasured confounding
• Study heterogeneity

How can heterogeneous evidence be synthesised transparently without losing interpretability or credibility?

➝ Evidence Synthesis

➝ Real-World Evidence

➝ Data Harmonisation

➝ Sensitivity Analysis

Why this matters

HTA and reimbursement decisions increasingly depend not only on what the evidence shows, but on how uncertainty is understood and addressed.

This includes:

  • How assumptions are justified
  • How uncertainty is characterised
  • How transparent the analytical framework remains
  • How reproducible the analyses are
  • How relevant the comparative evidence remains under review


The critical question is often not:
What do the results show?

But:
How much uncertainty remains acceptable for decision-making?


Utilising real-world data for EU HTA ➝

Explore the relevant evidence
pathways

Evidence Decoded

Understanding how regulators and HTA reviewers evaluate evidence.

Explore evidence decoded ➝

Robust Analytics

Building confidence through transparent statistical thinking.

Explore robust analytics ➝

In Practice

Applying robust analytics to real-world evidence challenges.

Explore in practice ➝

Our work in practice

Selected examples of complex statistical questions and how we addressed them across clinical development, HTA and market access.

Over 1,000 projects delivered.


See selected case studies ➝

Implementation of ML-NMR for Rate Outcomes

Lessons from a Recent EU HTA Submission

View scientific poster ➝

Case Snapshot ➝

Numerus invented a new MAIC methodology

Case Snapshot ➝

Hyper complex NMA successfully executed

Your next evidence challenge

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