Invited Commentary: Beyond Overdiagnosis-Diagnosis Without Benefit

Area of Science:

• Epidemiology
• Medical Diagnosis

Background:

• Overdiagnosis by screening is a growing concern, often stemming from prognostic uncertainty.
• Existing models of disease progression may not fully capture individual patient experiences.

Purpose of the Study:

• To clarify the concept of overdiagnosis by screening and address prognostic uncertainty.
• To propose a simpler framework for evaluating diagnostic practices and screening programs.

Main Methods:

• Critically analyzing Hofmann's (2019) categorical model of disease progression and prognostic uncertainty.
• Developing a probabilistic understanding of the link between diagnostic indicators, patient suffering, and time.

Main Results:

• Hofmann's model can be improved by considering patient-condition heterogeneity and the temporal aspect of suffering.
• A simpler approach focusing on 'diagnosis without benefit' and 'diagnosis without net benefit' is proposed.

Conclusions:

• Reconnecting diagnosis with patient suffering is crucial for understanding overdiagnosis.
• A focus on diagnosis without net benefit can better guide clinical practice and policy regarding screening programs.
• Reducing harm from overly aggressive screening requires a clear understanding of diagnostic benefit.