Planning clinically relevant biomarker validation studies using the "number needed to treat" concept

Area of Science:

• Biostatistics
• Clinical Trial Design
• Biomarker Validation

Background:

• Translational research has not significantly impacted clinical practice despite advances in biomarker discovery.
• A key limitation is the failure to define how a biomarker will improve patient decision-making in validation studies.
• Current methods for designing validation studies are underdeveloped, particularly in assessing value-based outcome tradeoffs.

Purpose of the Study:

• To propose a novel framework for designing biomarker validation studies that ensures clinical utility.
• To establish methods for articulating precise performance requirements for biomarkers to improve medical care.
• To bridge the gap between biomarker development and meaningful clinical application.

Main Methods:

• Utilizes an unconventional application of the
• number needed to treat
• (NNT) to structure value-based outcome tradeoffs.
• Employs a
• contra-Bayes
• theorem to convert predictive values into sensitivity and specificity criteria.
• Applies these methods to guide the design of both prospective and retrospective validation studies.

Main Results:

• NNT-guided dialogues facilitate the planning of validation studies by linking them to patient-oriented translational goals.
• The framework provides clear criteria for designing studies, ensuring the biomarker's performance is evaluated against clinical decision challenges.
• Demonstrated through several examples, showing the practical application of the proposed methods.

Conclusions:

• The proposed NNT-based approach enhances the design of biomarker validation studies, ensuring focus on clinical utility.
• This method improves communication among trial design teams by clearly defining value-based outcome tradeoffs.
• Ultimately, this leads to biomarker reports that better communicate the test's value to patients and clinicians.