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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.
Abstract:
Pheochromocytoma is a rare, life-threatening condition. Using a modeling technique, we studied the economic implications of detection strategies for pheochromocytoma (third-party payer perspective). The diagnostic efficacy of biochemical tests was based on Mayo Clinic Rochester data. In all hypothetical algorithms, positive biochemical tests were followed by abdominal computerized tomography and, if negative, metaiodobenzylguanidine scintigraphy. In each hypothetical algorithm, imaging would be indicated after positive biochemical testing as follows: algorithm A, fractionated plasma metanephrine measurements above the laboratory reference range; or algorithm B, abnormal measurements of 24-h urinary total metanephrines or catecholamines. In algorithm C, subjects with fractions of plasma metanephrine at or above 0.5 nmol/liter or normetanephrine at or above 1.80 nmol/liter would undergo imaging, whereas those with values between the reference range and these cutoffs would undergo 24-h urinary measurements (total metanephrines and fractionated catecholamines) and be imaged if positive. We determined that, if 100,000 hypertensive patients (including 500 patients with pheochromocytoma) were tested, algorithm A (measurement of fractionated plasma metanephrines alone) would detect 489 pheochromocytoma patients at a cost of 56.6 million dollars, whereas B (24-h urinary measurements) would detect 457 pheochromocytoma patients for 39.5 million dollars, and C (combination of measurements of fractionated plasma metanephrines and urines) would detect 478 patients for 28.6 million dollars. None of the screening strategies for pheochromocytoma described are affordable if implemented on a routine basis in extremely low-risk patients. However, algorithm C may be the least costly, and at a reasonable level of sensitivity, for subjects in whom the suspicion of disease is moderate.
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