Point: HOMA—Satisfactory for the Time Being

McAuley, Kirsten A.; Mann, Jim; Chase, J. Geoffrey; Lotz, Thomas; Shaw, Geoffrey M.

doi:10.2337/dc07-1067

Cited by 49 publications

(33 citation statements)

References 28 publications

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“…It is a privilege to reflect on the impact of this landmark publication ('Then'), and to place it in the context of the challenges of present day diabetes research and clinical care ('Now'). The paper by Matthews et al and the topic of HOMA in general have been extensively reviewed and discussed by experts in the field over the years [5][6][7][8][9], including Matthews and his colleagues [10], and it is not our purpose here to provide yet another critique or systematic review of HOMA. Instead we will consider the impact of this classic paper in the context of the overlapping modern 'eras' in diabetes research and care that have provided the backdrop to this scientific study (Fig.…”

Section: Challenges Of a Rapidly Changing Environmentmentioning

confidence: 99%

“…Despite limitations that have been the subject of previous reviews [5][6][7][8][9], HOMA has endured owing to its solid foundations in physiology. In the original study [4], fasting insulin concentrations were measured from three samples over 10 min, thereby taking account of the pulsatility of insulin secretion.…”

Section: Addressing the Gap Between Clinical Physiology And Clinical mentioning

confidence: 99%

“…HOMA was originally devised as a simple mathematical algorithm for quantification of the relative contributions of insulin resistance and beta cell dysfunction to an individual's fasting hyperglycaemia. Given certain limitations [5][6][7][8][9], and despite the relatively small number of individuals studied to derive the 1985 model, HOMA has been widely accepted as a convenient surrogate marker of insulin resistance and beta cell function. To summarise expert critique, HOMA-IR has been well validated against the clamp technique and reflects hepatic more than peripheral insulin resistance, whereas HOMA-%B has been less rigorously evaluated, and is a much less robust estimate of beta cell function [5][6][7][8][9]20].…”

Section: Addressing the Gap Between Clinical Physiology And Clinical mentioning

confidence: 99%

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Estimating insulin sensitivity and beta cell function: perspectives from the modern pandemics of obesity and type 2 diabetes

Nolan

Færch

2012

Diabetologia

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The 1985 manuscript describing the HOMA model, by Matthews and colleagues, is the most cited paper in the history of Diabetologia. In this edition of 'Then and now' we assess the impact of this seminal paper by considering the contribution of this elegant work in the context of the most rapidly changing period in the history of diabetes. HOMA was born in the middle of an 'era' of insulin resistance, and was subsequently nurtured and grew during the 'eras' of insulin sensitisers and diabetes prevention. From the modern era of insulin resistance onward, researchers have sought a convenient method for measuring insulin sensitivity and secretion, and found this in HOMA. However, the explosion in the prevalence of diabetes clearly underlines that an understanding of insulin resistance and how it can be measured has been insufficient to make any impact on the growing pandemic of diabetes. Knowledge of individual physiology is important, but the dramatic impact of the modern environment may be the factor that has escaped attention until very recently. An optimist can only state that the coming 'era' in diabetes research will be a period of true translation of scientific insight and implementation of effective disease prevention.

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Section: Challenges Of a Rapidly Changing Environmentmentioning

confidence: 99%

Section: Addressing the Gap Between Clinical Physiology And Clinical mentioning

confidence: 99%

Section: Addressing the Gap Between Clinical Physiology And Clinical mentioning

confidence: 99%

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Estimating insulin sensitivity and beta cell function: perspectives from the modern pandemics of obesity and type 2 diabetes

Nolan

Færch

2012

Diabetologia

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“…Commonly used diagnostic tests that do not use a patient specific dosing protocol, such as the two-hour oral glucose tolerance test or dynamic insulin sensitivity test (DIST) [10][11][12], may be affected, at least in some cases, by saturation. In particular, differing patient specific volumes of distribution will cause inter-subject variation in concentration for the same dose, and thus, the insulin efficiency may not be measured equally across subjects leading to greater error in these critical values.…”

Section: Introductionmentioning

confidence: 99%

The Identification of Insulin Saturation Effects During the Dynamic Insulin Sensitivity Test~!2010-03-19~!2010-05-13~!2010-07-22~!

Docherty¹

2010

TOMINFOJ

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Abstract:Background: Many insulin sensitivity (SI) tests identify a sensitivity metric that is proportional to the total available insulin and measured glucose disposal despite general acceptance that insulin action is saturable. Accounting for insulin action saturation may aid inter-participant and/or inter-test comparisons of insulin efficiency, and model-based glycaemic regulation.Method: Eighteen subjects participated in 46 dynamic insulin sensitivity tests (DIST, low-dose 40-50 minute insulinmodified IVGTT). The data was used to identify and compare SI metrics from three models: a proportional model (SI L ), a saturable model (SI S and Q 50 ) and a model similar to the Minimal Model (SG and SI G ). The three models are compared using inter-trial parameter repeatability, and fit to data. Results:The single variable proportional model produced the metric with least intra-subject variation: 13.8% vs 40.1%/55.6%, (SI S /I 50 ) for the saturable model and 15.8%/88.2% (SI G /SG) for the third model. The average plasma insulin concentration at half maximum action (I 50 ) was 139.3 mU·L -1 , which is comparable to studies which use more robust stepped EIC protocols. Conclusions:The saturation model and method presented enables a reasonable estimation of an overall patient-specific saturation threshold, which is a unique result for a test of such low dose and duration. The detection of previously published population trends and significant bias above noise suggests that the model and method successfully detects actual saturation signals. Furthermore, the saturation model allowed closer fits to the clinical data than the other models, and the saturation parameter showed a moderate distinction between NGT and IFG-T2DM subgroups. However, the proposed model did not provide metrics of sufficient resolution to enable confidence in the method for either SI metric comparisons across dynamic tests or for glycamic control.

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“…McAuley et al (1) provide an overview of methods to assess insulin sensitivity and secretion. The conditional nature of the title of their article implies that there is room for improvement and that something better will come along to assess insulin resistance and secretion with the convenience of HOMA but with better accuracy.…”

mentioning

confidence: 99%

Do We Know What Homeostasis Model Assessment Measures?

Jensen

2007

Diabetes Care

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Point: HOMA—Satisfactory for the Time Being

Cited by 49 publications

References 28 publications

Estimating insulin sensitivity and beta cell function: perspectives from the modern pandemics of obesity and type 2 diabetes

Estimating insulin sensitivity and beta cell function: perspectives from the modern pandemics of obesity and type 2 diabetes

The Identification of Insulin Saturation Effects During the Dynamic Insulin Sensitivity Test~!2010-03-19~!2010-05-13~!2010-07-22~!

Do We Know What Homeostasis Model Assessment Measures?

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