Herráiz-Adillo Á, Cavero-Redondo I, Álvarez-Bueno C, Bidner J, Martínez-Vizcaíno V, Notario-Pacheco B. Spectrum effect and spectrum bias in the oscillometric ankle brachial index to diagnose peripheral arterial disease: Clinical implications.
Atherosclerosis 2018. [PMID:
29529395 DOI:
10.1016/j.atherosclerosis.2018.03.003]
[Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
Abstract
BACKGROUND AND AIMS
The diagnostic performance of the oscillometric ankle brachial index (ABI) to detect peripheral arterial disease (PAD) varies among populations, suggesting a spectrum effect. When this heterogeneity modifies post-test probabilities, a spectrum bias arises. This study evaluates the presence and influence of spectrum effect and spectrum bias on test performance and clinical decisions.
METHODS
Oscillometric and Doppler ABI were compared in two settings: Primary-Care (333 legs) and Vascular-Service (41 legs). Spectrum effect was assessed using stratification and logistic regression, while spectrum bias was assessed through graphical and statistical tests based on predictive values and likelihood ratios, respectively.
RESULTS
Across subgroups, sensitivity ranged from 61.5% to 90.9%, and specificity from 81.8% to 99.1%. Logistic regression confirmed a spectrum effect in setting, diabetes, smoking status and age (univariate), and setting and diabetes (multivariate model). The positive likelihood ratio ranged from 5.0 to 89.1 in subgroups, leading to a spectrum bias in diabetic, smoking (both subgroups) and age (both subgroups). Therefore, a positive test ruled in differently the disease across subgroups, with a high rate of false positives in diabetic, smoking and >75-year-old patients. The negative likelihood ratio ranged from 0.09 to 0.39 in subgroups, with significant spectrum bias in Primary-Care patients, non-diabetics and smokers. Thus, in these subgroups, a negative test ruled out the disease with less certainty.
CONCLUSIONS
Spectrum effect and spectrum bias were found in oscillometric ABI to detect PAD, potentially affecting clinical decisions, especially for positive tests. Information about spectrum variables and the application of specific subgroups indicators are necessary.
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