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Surveillance Intensity Comparison by Risk for T1NX Locally Excised Rectal Adenocarcinoma: a Cost-Effective Analysis.

Mason McCain¹, Yohanis O'Neill^1,2, Hernan Hernandez³

¹Colon and Rectal Surgery Inc, Omaha, NE, USA.

Journal of Gastrointestinal Surgery : Official Journal of the Society for Surgery of the Alimentary Tract

|November 15, 2019

Summary

Medium-intensity surveillance is the most cost-effective strategy for patients with locally excised T1NX rectal adenocarcinoma. This approach balances costs and effectiveness, offering optimal outcomes in most clinical scenarios.

Keywords:

Cost-effectiveness Local excision Markov model Rectal cancer Rectal cancer surveillance

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Area of Science:

Oncology
Health Economics
Clinical Decision Making

Background:

Optimal surveillance after local excision of T1NX rectal adenocarcinoma remains debated.
Risk stratification based on histopathology and local staging is crucial for tailoring follow-up strategies.

Purpose of the Study:

To determine the cost-effectiveness of different surveillance intensities (low, medium, high) for locally excised T1NX rectal adenocarcinoma.
To identify the optimal surveillance strategy based on patient risk factors.

Main Methods:

A 10-year Markov model was developed for cost-effectiveness analysis.
Data on state/transition probabilities and rewards were derived from literature review and expert consensus.
Healthcare costs were based on Centers for Medicare and Medicaid Services data; analyses included sensitivity testing.

Main Results:

Medium-intensity surveillance yielded the highest net monetary benefit ($397,978.80).
Sensitivity analyses indicated medium-intensity surveillance is optimal for cohorts with 73-94% low-risk patients.
High-intensity surveillance is preferred for <73% low-risk, and low-intensity for >94% low-risk.

Conclusions:

Medium-intensity surveillance represents the most cost-effective strategy for locally excised T1NX rectal adenocarcinoma.
This strategy is optimal in a clinically representative population model, balancing resource utilization and patient outcomes.