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Applying the estimand and target trial frameworks to external control analyses using observational data: a case study

Letizia Polito1, Qixing Liang2, Navdeep Pal3

  • 1Product Development Data Sciences, F Hoffmann-La Roche Ltd., Basel, Switzerland.

Frontiers in Pharmacology
|February 12, 2024
PubMed
Summary

Causal inference methods were used to compare real-world data with clinical trial controls for metastatic non-small cell lung cancer patients. The study found similar long-term survival between external and randomized control groups, validating the approach.

Keywords:
causal inferenceestimand frameworkexternal controloncologyreal-world datatarget trial emulation framework

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Area of Science:

  • Causal inference
  • Health services research
  • Oncology

Background:

  • Accurate scientific question formulation is vital in causal inference.
  • External control arms using real-world data (RWD) are increasingly used in clinical research.
  • Challenges exist in aligning RWD with randomized controlled trial (RCT) definitions.

Purpose of the Study:

  • To apply causal inference principles to external control analysis using observational data.
  • To illustrate defining estimand attributes for robust comparative effectiveness research.
  • To compare long-term survival in metastatic non-small cell lung cancer (NSCLC) patients.

Main Methods:

  • Pooled data from three Phase 3 RCTs and observational data from an electronic health record (EHR) database.
  • Utilized the estimand framework and target trial framework for precise estimand definition.
  • Adjusted for baseline confounders, index date, and subsequent therapies.

Main Results:

  • The estimand and aligned estimator were clearly defined using the combined frameworks.
  • The hazard ratio comparing the RCT control arm with the external control was approximately 1.
  • This indicates similar long-term survival outcomes between the two groups.

Conclusions:

  • The combined estimand and target trial frameworks enhance clarity in defining causal contrasts.
  • This approach facilitates the design and interpretation of comparative effectiveness studies using RWD.
  • The findings support the validity of using external controls in oncology research.