# Enhancing confidence in complex health technology assessments by using real-world evidence: highlighting existing strategies for effective drug evaluation

**Authors:** Alison Antoine, Katia Desroziers, Julien Dupin, David Pérol, Rémy Choquet

PMC · DOI: 10.1186/s12874-025-02683-2 · 2025-11-03

## TL;DR

This paper explores how real-world evidence can complement clinical trials to improve the evaluation of new therapies and enhance healthcare decision-making.

## Contribution

The paper proposes a categorization of complex clinical situations and provides methodological guidance for using real-world evidence in drug evaluations.

## Key findings

- A categorization of complex clinical situations was proposed to guide the use of real-world evidence.
- Recommendations were made to improve data quality, methodology, and transparency in real-world evidence studies.
- Collaboration between stakeholders was highlighted as essential for effective drug evaluation using real-world data.

## Abstract

Randomised controlled trials (RCTs) are the gold standard for evaluating new therapies but have limitations, notably in terms of external validity. Real-world data (RWD) studies could complement RCT evidence. However, a consensus has not yet been reached on situations where RWD could offer rigorous complementary evidence to an RCT when evaluating the effectiveness of therapeutic innovations. This research aims to: (1) propose a categorisation of complex clinical situations; (2) classify the real-world evidence (RWE) approaches to be used in each situation to help reduce uncertainties or provide further evidence in drug benefit assessments; (3) summarise the best methodological considerations to adopt when using these RWE approaches; and (4) propose general recommendations to increase confidence in the use of RWE approaches during the assessment process. The main recommendations within the framework around the RWD-generation plan for complex evaluations are related to four main issues: quality (establishing criteria and standards for quality data), methodology (ensuring the use of the best methodological approaches), transparency (from the industry and from the health technology agencies (HTAs) and sharing/collaborating across countries and HTAs (promoting collaboration between HTAs and involving all parties). Our proposal and recommendations could help the scientific community better consider the therapeutic value of innovations through RWD, so that their potential can be fully realised to benefit the quality of care and the regulation of the healthcare system.

## Full-text entities

- **Genes:** ERG (ETS transcription factor ERG) [NCBI Gene 2078] {aka LMPHM14, erg-3, p55}, MUC1 (mucin 1, cell surface associated) [NCBI Gene 4582] {aka ADMCKD, ADMCKD1, ADTKD2, CA 15-3, CD227, Ca15-3}
- **Diseases:** non-small cell lung cancer (MESH:D002289), PREMS (MESH:C535616), RWD (MESH:D016773), death (MESH:D003643)
- **Chemicals:** PS (MESH:D010758), DAG (-)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Figures

1 figure with captions in the complete paper: https://tomesphere.com/paper/PMC12581489/full.md

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Source: https://tomesphere.com/paper/PMC12581489