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Clin Gastroenterol Hepatol. 2018 Sep;16(9):1434-1441.e21. doi: 10.1016/j.cgh.2018.03.025. Epub 2018 Mar 27.

Cost Effectiveness of Biomarker Tests for Irritable Bowel Syndrome With Diarrhea: A Framework for Payers.

Author information

1
Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, California; Division of Digestive and Liver Diseases, Cedars-Sinai Medical Center, Los Angeles, California; Division of Health Services Research, Cedars-Sinai Medical Center, Los Angeles, California; Cedars-Sinai Center for Outcomes Research and Education (CS-CORE), Los Angeles, California.
2
Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, California; Cedars-Sinai Center for Outcomes Research and Education (CS-CORE), Los Angeles, California.
3
Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, California; Cedars-Sinai Center for Outcomes Research and Education (CS-CORE), Los Angeles, California; Department of Health Policy and Management, UCLA Fielding School of Public Health, Los Angeles, California.
4
Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, California.
5
Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, California; Division of Digestive and Liver Diseases, Cedars-Sinai Medical Center, Los Angeles, California; Division of Health Services Research, Cedars-Sinai Medical Center, Los Angeles, California; Cedars-Sinai Center for Outcomes Research and Education (CS-CORE), Los Angeles, California; Department of Health Policy and Management, UCLA Fielding School of Public Health, Los Angeles, California. Electronic address: Brennan.Spiegel@cshs.org.

Abstract

BACKGROUND & AIMS:

Diagnosis of diarrhea-predominant irritable bowel syndrome (IBS-D) relies on the Rome IV symptom-based criteria, which are imperfect for separating functional vs organic disease. Biomarker tests for IBS-D might be added to symptom data to allow clinicians to make more accurate and precise diagnoses in a cost-effective manner. We tested the economic consequences of using a range of hypothetical IBS-D biomarkers, and explored at what cost and level of accuracy a biomarker becomes cost effective. We produced a framework for payers to evaluate the return on an investment of implementing IBS-D biomarkers of varying accuracy and cost.

METHODS:

We used decision analysis software to evaluate a hypothetical cohort of patients who met Rome IV criteria for IBS-D. We conducted cost-utility and budget impact analyses of 2 competing approaches: usual care or an IBS biomarker-based diagnostic approach. Patients in the usual care group received empiric IBS treatment; non-responders received additional diagnostic tests for organic disease. In the group evaluated with a biomarker test, those with a positive result received IBS treatment before additional diagnostic analyses, whereas patients with a negative result underwent upfront diagnostic testing. Outcomes were incremental cost per quality-adjusted life year gained (third-party payer perspective) and incremental per-member per-month cost.

RESULTS:

In the base-case analysis, using a willingness-to-pay threshold of $100,000/quality-adjusted life year, we found that biomarkers are not cost effective when the biomarker test costs more than $846, even if the test is 100% accurate in detecting IBS-D. In probabilistic analysis using 1,000 simulations, most trials (75% or more) show that the biomarker-based diagnostic approach is cost effective above the following accuracy thresholds: a $100 biomarker test with 51% accuracy, a $200 test with 57% accuracy, a $300 test with 63% accuracy, a $400 test with 69% accuracy, a $500 test with 76% accuracy, a $600 test with 82% accuracy, a $700 test with 89% accuracy, and a $800 test with 94% accuracy.

CONCLUSIONS:

In decision analysis of a hypothetical cohort of patients who met Rome IV criteria for IBS-D, we identified cost and accuracy thresholds that can guide investigators and payers as they develop, validate, price, and/or reimburse IBS-D biomarker tests for use in everyday clinical practice.

KEYWORDS:

Budget Impact; Diagnostic; Modeling; QALY

PMID:
29596984
PMCID:
PMC6098734
[Available on 2019-09-01]
DOI:
10.1016/j.cgh.2018.03.025

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