Assessing the predictive accuracy of oral glucose effectiveness index using a calibration model
Purpose Current reference methods for measuring glucose effectiveness (GE) are the somatostatin pancreatic glucose clamp and minimal model analysis of frequently sampled intravenous glucose tolerance test (FSIVGTT), both of which are laborious and not feasible in large epidemiological studies. Conse...
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| Veröffentlicht in: | Endocrine 2019-02, Vol.63 (2), p.391-397 |
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| creator | Glicksman, Michael Grewal, Shivraj Sortur, Shrayus Abel, Brent S. Auh, Sungyoung Gaillard, Trudy R. Osei, Kwame Muniyappa, Ranganath |
| description | Purpose
Current reference methods for measuring glucose effectiveness (GE) are the somatostatin pancreatic glucose clamp and minimal model analysis of frequently sampled intravenous glucose tolerance test (FSIVGTT), both of which are laborious and not feasible in large epidemiological studies. Consequently, surrogate indices derived from an oral glucose tolerance test (OGTT) to measure GE (oGE) have been proposed and used in many studies. However, the predictive accuracy of these surrogates has not been formally validated. In this study, we used a calibration model analysis to evaluate the accuracy of surrogate indices to predict GE from the reference FSIVGTT (Sg
MM
).
Methods
Subjects (
n
= 123, mean age 48 ± 11 years; BMI 35.9 ± 7.3 kg/m
2
) with varying glucose tolerance (NGT,
n
= 37; IFG/IGT,
n
= 78; and T2DM,
n
= 8) underwent FSIVGTT and OGTT on two separate days. Predictive accuracy was assessed by both root mean squared error (RMSE) of prediction and leave-one-out cross-validation-type RMSE of prediction (CVPE).
Results
As expected, insulin sensitivity, Sg
MM
, and oGE were reduced in subjects with T2DM and IFG/IGT when compared with NGT. Simple linear regression analyses revealed a modest but significant relationship between oGE and Sg
MM
(
r
= 0.25,
p
|
| doi_str_mv | 10.1007/s12020-018-1804-0 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_6448593</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2183251360</sourcerecordid><originalsourceid>FETCH-LOGICAL-c470t-b355db0e50d3d69a0cef90bc0c1bd588ab94e8dd1c4e95ff85cc86f146c0a06a3</originalsourceid><addsrcrecordid>eNp1kU9v1DAQxS1ERf_AB-CCLHHhEhgndta5IFUVFKRKXIrEzXLG462rrL3YSUW_Pd5uKRSpJ488v3l-48fYawHvBcDqQxEttNCA0I3QIBt4xo6EUkO9AXhe606pBkD_OGTHpVwDtG3br16www4k1EoeMXNaCpUS4prPV8S3mVzAOdwQt4hLtnjLk-cp24mvpwVTIU7e0x0S6yAP0dEvvtwpWI52CmO2c0iRb5Kj6SU78HYq9Or-PGHfP3-6PPvSXHw7_3p2etGgXMHcjNWpG4EUuM71gwUkP8CIgGJ0Sms7DpK0cwIlDcp7rRB174XsESz0tjthH_e622XckEOKc_VstjlsbL41yQbzuBPDlVmnG9NLqdXQVYF39wI5_VyozGYTCtI02UhpKaYVHej60ytV0bf_oddpybGuVyndtUp0PVRK7CnMqZRM_sGMALOLz-zjM1XU7OIzu5k3_27xMPEnrwq0e6DUVlxT_vv006q_AQA6p9k</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2183251360</pqid></control><display><type>article</type><title>Assessing the predictive accuracy of oral glucose effectiveness index using a calibration model</title><source>MEDLINE</source><source>Springer Nature - Complete Springer Journals</source><creator>Glicksman, Michael ; Grewal, Shivraj ; Sortur, Shrayus ; Abel, Brent S. ; Auh, Sungyoung ; Gaillard, Trudy R. ; Osei, Kwame ; Muniyappa, Ranganath</creator><creatorcontrib>Glicksman, Michael ; Grewal, Shivraj ; Sortur, Shrayus ; Abel, Brent S. ; Auh, Sungyoung ; Gaillard, Trudy R. ; Osei, Kwame ; Muniyappa, Ranganath</creatorcontrib><description>Purpose
Current reference methods for measuring glucose effectiveness (GE) are the somatostatin pancreatic glucose clamp and minimal model analysis of frequently sampled intravenous glucose tolerance test (FSIVGTT), both of which are laborious and not feasible in large epidemiological studies. Consequently, surrogate indices derived from an oral glucose tolerance test (OGTT) to measure GE (oGE) have been proposed and used in many studies. However, the predictive accuracy of these surrogates has not been formally validated. In this study, we used a calibration model analysis to evaluate the accuracy of surrogate indices to predict GE from the reference FSIVGTT (Sg
MM
).
Methods
Subjects (
n
= 123, mean age 48 ± 11 years; BMI 35.9 ± 7.3 kg/m
2
) with varying glucose tolerance (NGT,
n
= 37; IFG/IGT,
n
= 78; and T2DM,
n
= 8) underwent FSIVGTT and OGTT on two separate days. Predictive accuracy was assessed by both root mean squared error (RMSE) of prediction and leave-one-out cross-validation-type RMSE of prediction (CVPE).
Results
As expected, insulin sensitivity, Sg
MM
, and oGE were reduced in subjects with T2DM and IFG/IGT when compared with NGT. Simple linear regression analyses revealed a modest but significant relationship between oGE and Sg
MM
(
r
= 0.25,
p
< 0.001). However, using calibration model, measured Sg
MM
and predicted Sg
MM
derived from oGE were modestly correlated (
r
= 0.21,
p
< 0.05) with the best fit line suggesting poor predictive accuracy. There were no significant differences in CVPE and RMSE among the surrogates, suggesting similar predictive ability.
Conclusions
Although OGTT-derived surrogate indices of GE are convenient and feasible, they have limited ability to robustly predict GE.</description><identifier>ISSN: 1355-008X</identifier><identifier>EISSN: 1559-0100</identifier><identifier>DOI: 10.1007/s12020-018-1804-0</identifier><identifier>PMID: 30402674</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>Accuracy ; Administration, Intravenous ; Administration, Oral ; Adult ; Blood Glucose - metabolism ; Calibration ; Cohort Studies ; Diabetes ; Diabetes Mellitus, Type 2 - blood ; Diabetes Mellitus, Type 2 - diagnosis ; Diabetes Mellitus, Type 2 - metabolism ; Endocrine Methods and Techniques ; Endocrinology ; Female ; Glucose ; Glucose - administration & dosage ; Glucose - metabolism ; Glucose Clamp Technique - methods ; Glucose Clamp Technique - standards ; Glucose Intolerance - blood ; Glucose Intolerance - diagnosis ; Glucose Intolerance - metabolism ; Glucose tolerance ; Glucose Tolerance Test - methods ; Glucose Tolerance Test - standards ; Health Status Indicators ; Humanities and Social Sciences ; Humans ; Insulin ; Insulin Resistance ; Internal Medicine ; Intravenous administration ; Male ; Medicine ; Medicine & Public Health ; Middle Aged ; Models, Biological ; multidisciplinary ; Pancreas ; Prediabetic State - blood ; Prediabetic State - diagnosis ; Prediabetic State - metabolism ; Predictive Value of Tests ; Reference Standards ; Reproducibility of Results ; Science ; Somatostatin</subject><ispartof>Endocrine, 2019-02, Vol.63 (2), p.391-397</ispartof><rights>This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2018</rights><rights>Copyright Springer Nature B.V. 2019</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c470t-b355db0e50d3d69a0cef90bc0c1bd588ab94e8dd1c4e95ff85cc86f146c0a06a3</citedby><cites>FETCH-LOGICAL-c470t-b355db0e50d3d69a0cef90bc0c1bd588ab94e8dd1c4e95ff85cc86f146c0a06a3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s12020-018-1804-0$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s12020-018-1804-0$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>230,314,776,780,881,27901,27902,41464,42533,51294</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/30402674$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Glicksman, Michael</creatorcontrib><creatorcontrib>Grewal, Shivraj</creatorcontrib><creatorcontrib>Sortur, Shrayus</creatorcontrib><creatorcontrib>Abel, Brent S.</creatorcontrib><creatorcontrib>Auh, Sungyoung</creatorcontrib><creatorcontrib>Gaillard, Trudy R.</creatorcontrib><creatorcontrib>Osei, Kwame</creatorcontrib><creatorcontrib>Muniyappa, Ranganath</creatorcontrib><title>Assessing the predictive accuracy of oral glucose effectiveness index using a calibration model</title><title>Endocrine</title><addtitle>Endocrine</addtitle><addtitle>Endocrine</addtitle><description>Purpose
Current reference methods for measuring glucose effectiveness (GE) are the somatostatin pancreatic glucose clamp and minimal model analysis of frequently sampled intravenous glucose tolerance test (FSIVGTT), both of which are laborious and not feasible in large epidemiological studies. Consequently, surrogate indices derived from an oral glucose tolerance test (OGTT) to measure GE (oGE) have been proposed and used in many studies. However, the predictive accuracy of these surrogates has not been formally validated. In this study, we used a calibration model analysis to evaluate the accuracy of surrogate indices to predict GE from the reference FSIVGTT (Sg
MM
).
Methods
Subjects (
n
= 123, mean age 48 ± 11 years; BMI 35.9 ± 7.3 kg/m
2
) with varying glucose tolerance (NGT,
n
= 37; IFG/IGT,
n
= 78; and T2DM,
n
= 8) underwent FSIVGTT and OGTT on two separate days. Predictive accuracy was assessed by both root mean squared error (RMSE) of prediction and leave-one-out cross-validation-type RMSE of prediction (CVPE).
Results
As expected, insulin sensitivity, Sg
MM
, and oGE were reduced in subjects with T2DM and IFG/IGT when compared with NGT. Simple linear regression analyses revealed a modest but significant relationship between oGE and Sg
MM
(
r
= 0.25,
p
< 0.001). However, using calibration model, measured Sg
MM
and predicted Sg
MM
derived from oGE were modestly correlated (
r
= 0.21,
p
< 0.05) with the best fit line suggesting poor predictive accuracy. There were no significant differences in CVPE and RMSE among the surrogates, suggesting similar predictive ability.
Conclusions
Although OGTT-derived surrogate indices of GE are convenient and feasible, they have limited ability to robustly predict GE.</description><subject>Accuracy</subject><subject>Administration, Intravenous</subject><subject>Administration, Oral</subject><subject>Adult</subject><subject>Blood Glucose - metabolism</subject><subject>Calibration</subject><subject>Cohort Studies</subject><subject>Diabetes</subject><subject>Diabetes Mellitus, Type 2 - blood</subject><subject>Diabetes Mellitus, Type 2 - diagnosis</subject><subject>Diabetes Mellitus, Type 2 - metabolism</subject><subject>Endocrine Methods and Techniques</subject><subject>Endocrinology</subject><subject>Female</subject><subject>Glucose</subject><subject>Glucose - administration & dosage</subject><subject>Glucose - metabolism</subject><subject>Glucose Clamp Technique - methods</subject><subject>Glucose Clamp Technique - standards</subject><subject>Glucose Intolerance - blood</subject><subject>Glucose Intolerance - diagnosis</subject><subject>Glucose Intolerance - metabolism</subject><subject>Glucose tolerance</subject><subject>Glucose Tolerance Test - methods</subject><subject>Glucose Tolerance Test - standards</subject><subject>Health Status Indicators</subject><subject>Humanities and Social Sciences</subject><subject>Humans</subject><subject>Insulin</subject><subject>Insulin Resistance</subject><subject>Internal Medicine</subject><subject>Intravenous administration</subject><subject>Male</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Middle Aged</subject><subject>Models, Biological</subject><subject>multidisciplinary</subject><subject>Pancreas</subject><subject>Prediabetic State - blood</subject><subject>Prediabetic State - diagnosis</subject><subject>Prediabetic State - metabolism</subject><subject>Predictive Value of Tests</subject><subject>Reference Standards</subject><subject>Reproducibility of Results</subject><subject>Science</subject><subject>Somatostatin</subject><issn>1355-008X</issn><issn>1559-0100</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp1kU9v1DAQxS1ERf_AB-CCLHHhEhgndta5IFUVFKRKXIrEzXLG462rrL3YSUW_Pd5uKRSpJ488v3l-48fYawHvBcDqQxEttNCA0I3QIBt4xo6EUkO9AXhe606pBkD_OGTHpVwDtG3br16www4k1EoeMXNaCpUS4prPV8S3mVzAOdwQt4hLtnjLk-cp24mvpwVTIU7e0x0S6yAP0dEvvtwpWI52CmO2c0iRb5Kj6SU78HYq9Or-PGHfP3-6PPvSXHw7_3p2etGgXMHcjNWpG4EUuM71gwUkP8CIgGJ0Sms7DpK0cwIlDcp7rRB174XsESz0tjthH_e622XckEOKc_VstjlsbL41yQbzuBPDlVmnG9NLqdXQVYF39wI5_VyozGYTCtI02UhpKaYVHej60ytV0bf_oddpybGuVyndtUp0PVRK7CnMqZRM_sGMALOLz-zjM1XU7OIzu5k3_27xMPEnrwq0e6DUVlxT_vv006q_AQA6p9k</recordid><startdate>20190201</startdate><enddate>20190201</enddate><creator>Glicksman, Michael</creator><creator>Grewal, Shivraj</creator><creator>Sortur, Shrayus</creator><creator>Abel, Brent S.</creator><creator>Auh, Sungyoung</creator><creator>Gaillard, Trudy R.</creator><creator>Osei, Kwame</creator><creator>Muniyappa, Ranganath</creator><general>Springer US</general><general>Springer Nature B.V</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20190201</creationdate><title>Assessing the predictive accuracy of oral glucose effectiveness index using a calibration model</title><author>Glicksman, Michael ; Grewal, Shivraj ; Sortur, Shrayus ; Abel, Brent S. ; Auh, Sungyoung ; Gaillard, Trudy R. ; Osei, Kwame ; Muniyappa, Ranganath</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c470t-b355db0e50d3d69a0cef90bc0c1bd588ab94e8dd1c4e95ff85cc86f146c0a06a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Accuracy</topic><topic>Administration, Intravenous</topic><topic>Administration, Oral</topic><topic>Adult</topic><topic>Blood Glucose - metabolism</topic><topic>Calibration</topic><topic>Cohort Studies</topic><topic>Diabetes</topic><topic>Diabetes Mellitus, Type 2 - blood</topic><topic>Diabetes Mellitus, Type 2 - diagnosis</topic><topic>Diabetes Mellitus, Type 2 - metabolism</topic><topic>Endocrine Methods and Techniques</topic><topic>Endocrinology</topic><topic>Female</topic><topic>Glucose</topic><topic>Glucose - administration & dosage</topic><topic>Glucose - metabolism</topic><topic>Glucose Clamp Technique - methods</topic><topic>Glucose Clamp Technique - standards</topic><topic>Glucose Intolerance - blood</topic><topic>Glucose Intolerance - diagnosis</topic><topic>Glucose Intolerance - metabolism</topic><topic>Glucose tolerance</topic><topic>Glucose Tolerance Test - methods</topic><topic>Glucose Tolerance Test - standards</topic><topic>Health Status Indicators</topic><topic>Humanities and Social Sciences</topic><topic>Humans</topic><topic>Insulin</topic><topic>Insulin Resistance</topic><topic>Internal Medicine</topic><topic>Intravenous administration</topic><topic>Male</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Middle Aged</topic><topic>Models, Biological</topic><topic>multidisciplinary</topic><topic>Pancreas</topic><topic>Prediabetic State - blood</topic><topic>Prediabetic State - diagnosis</topic><topic>Prediabetic State - metabolism</topic><topic>Predictive Value of Tests</topic><topic>Reference Standards</topic><topic>Reproducibility of Results</topic><topic>Science</topic><topic>Somatostatin</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Glicksman, Michael</creatorcontrib><creatorcontrib>Grewal, Shivraj</creatorcontrib><creatorcontrib>Sortur, Shrayus</creatorcontrib><creatorcontrib>Abel, Brent S.</creatorcontrib><creatorcontrib>Auh, Sungyoung</creatorcontrib><creatorcontrib>Gaillard, Trudy R.</creatorcontrib><creatorcontrib>Osei, Kwame</creatorcontrib><creatorcontrib>Muniyappa, Ranganath</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Endocrine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Glicksman, Michael</au><au>Grewal, Shivraj</au><au>Sortur, Shrayus</au><au>Abel, Brent S.</au><au>Auh, Sungyoung</au><au>Gaillard, Trudy R.</au><au>Osei, Kwame</au><au>Muniyappa, Ranganath</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Assessing the predictive accuracy of oral glucose effectiveness index using a calibration model</atitle><jtitle>Endocrine</jtitle><stitle>Endocrine</stitle><addtitle>Endocrine</addtitle><date>2019-02-01</date><risdate>2019</risdate><volume>63</volume><issue>2</issue><spage>391</spage><epage>397</epage><pages>391-397</pages><issn>1355-008X</issn><eissn>1559-0100</eissn><abstract>Purpose
Current reference methods for measuring glucose effectiveness (GE) are the somatostatin pancreatic glucose clamp and minimal model analysis of frequently sampled intravenous glucose tolerance test (FSIVGTT), both of which are laborious and not feasible in large epidemiological studies. Consequently, surrogate indices derived from an oral glucose tolerance test (OGTT) to measure GE (oGE) have been proposed and used in many studies. However, the predictive accuracy of these surrogates has not been formally validated. In this study, we used a calibration model analysis to evaluate the accuracy of surrogate indices to predict GE from the reference FSIVGTT (Sg
MM
).
Methods
Subjects (
n
= 123, mean age 48 ± 11 years; BMI 35.9 ± 7.3 kg/m
2
) with varying glucose tolerance (NGT,
n
= 37; IFG/IGT,
n
= 78; and T2DM,
n
= 8) underwent FSIVGTT and OGTT on two separate days. Predictive accuracy was assessed by both root mean squared error (RMSE) of prediction and leave-one-out cross-validation-type RMSE of prediction (CVPE).
Results
As expected, insulin sensitivity, Sg
MM
, and oGE were reduced in subjects with T2DM and IFG/IGT when compared with NGT. Simple linear regression analyses revealed a modest but significant relationship between oGE and Sg
MM
(
r
= 0.25,
p
< 0.001). However, using calibration model, measured Sg
MM
and predicted Sg
MM
derived from oGE were modestly correlated (
r
= 0.21,
p
< 0.05) with the best fit line suggesting poor predictive accuracy. There were no significant differences in CVPE and RMSE among the surrogates, suggesting similar predictive ability.
Conclusions
Although OGTT-derived surrogate indices of GE are convenient and feasible, they have limited ability to robustly predict GE.</abstract><cop>New York</cop><pub>Springer US</pub><pmid>30402674</pmid><doi>10.1007/s12020-018-1804-0</doi><tpages>7</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1355-008X |
| ispartof | Endocrine, 2019-02, Vol.63 (2), p.391-397 |
| issn | 1355-008X 1559-0100 |
| language | eng |
| recordid | cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_6448593 |
| source | MEDLINE; Springer Nature - Complete Springer Journals |
| subjects | Accuracy Administration, Intravenous Administration, Oral Adult Blood Glucose - metabolism Calibration Cohort Studies Diabetes Diabetes Mellitus, Type 2 - blood Diabetes Mellitus, Type 2 - diagnosis Diabetes Mellitus, Type 2 - metabolism Endocrine Methods and Techniques Endocrinology Female Glucose Glucose - administration & dosage Glucose - metabolism Glucose Clamp Technique - methods Glucose Clamp Technique - standards Glucose Intolerance - blood Glucose Intolerance - diagnosis Glucose Intolerance - metabolism Glucose tolerance Glucose Tolerance Test - methods Glucose Tolerance Test - standards Health Status Indicators Humanities and Social Sciences Humans Insulin Insulin Resistance Internal Medicine Intravenous administration Male Medicine Medicine & Public Health Middle Aged Models, Biological multidisciplinary Pancreas Prediabetic State - blood Prediabetic State - diagnosis Prediabetic State - metabolism Predictive Value of Tests Reference Standards Reproducibility of Results Science Somatostatin |
| title | Assessing the predictive accuracy of oral glucose effectiveness index using a calibration model |
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