Estimation of Cancer Incidence Trends Adjusted for Changes in Screening and Detection Processes

Area of Science:

• Epidemiology
• Biostatistics
• Public Health

Background:

• Monitoring cancer incidence is crucial for evaluating public health interventions.
• Changes in screening and detection methods can distort observed cancer incidence trends.
• Accurate incidence data is vital for effective cancer control strategies.

Purpose of the Study:

• To develop and validate a new statistical method for estimating cancer incidence trends adjusted for screening changes.
• To provide a tool that does not require prior knowledge of cancer progression or detailed screening evolution.
• To apply the method to real-world data for breast cancer incidence estimation.

Main Methods:

• Utilized a constrained Almon distributed lag model for incidence trend estimation.
• Required only the registration of cancer stages (I-IV) at detection.
• Assumed stage distribution remains constant without screening practice changes.

Main Results:

• The proposed method successfully recovered true underlying cancer incidence in simulated data with various screening change scenarios.
• Applied to Geneva, Switzerland breast cancer registry data (1991-2016).
• Downwardly corrected observed breast cancer incidence following the introduction of an organized screening program.

Conclusions:

• The novel method provides a robust approach to estimating adjusted cancer incidence trends.
• This method offers a valuable tool for epidemiological research and public health policy, particularly when screening practices evolve.
• Accurate cancer incidence trend estimation is essential for assessing the impact of cancer control measures.