The economic implications of three biochemical screening algorithms for pheochromocytoma

Anna M Sawka1, Amiram Gafni, Lehana Thabane

  • 1Division of Endocrinology, Metabolism, Nutrition, and Internal Medicine, Mayo Clinic, Rochester, Minnesota 55905, USA.

Insights

This study evaluated the cost-effectiveness of different pheochromocytoma detection strategies. Algorithm C, a combined plasma and urine test approach, was found to be the least costly and most sensitive for moderate-risk patients.

Area of Science:

  • Endocrinology
  • Health Economics
  • Diagnostic Imaging

Background:

  • Pheochromocytoma is a rare but life-threatening tumor.
  • Accurate and cost-effective detection strategies are crucial.

Purpose of the Study:

  • To model and compare the economic implications of various pheochromocytoma detection strategies.
  • To identify the most cost-effective diagnostic algorithm from a third-party payer perspective.

Main Methods:

  • A modeling technique was employed to simulate diagnostic algorithms for pheochromocytoma detection.
  • Diagnostic efficacy was based on data from Mayo Clinic Rochester.
  • Algorithms involved biochemical tests followed by imaging (computerized tomography and scintigraphy).

Main Results:

  • Algorithm A (plasma metanephrines alone): 489 pheochromocytoma cases detected, costing $56.6 million.
  • Algorithm B (24-h urinary measurements): 457 cases detected, costing $39.5 million.
  • Algorithm C (combined plasma and urine tests): 478 cases detected, costing $28.6 million.

Conclusions:

  • Routine screening for pheochromocytoma is not affordable for extremely low-risk patients.
  • Algorithm C offers the lowest cost and reasonable sensitivity for patients with moderate suspicion of pheochromocytoma.

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