The Diabetes Technology Society Error Grid and Trend Accuracy Matrix for Glucose Monitors

David C Klonoff; Guido Freckmann; Stefan Pleus; Boris P Kovatchev; David Kerr; Chui Cindy Tse; Chengdong Li; Michael S D Agus; Kathleen Dungan; Barbora Voglová Hagerf; Jan S Krouwer; Wei-An Andy Lee; Shivani Misra; Sang Youl Rhee; Ashutosh Sabharwal; Jane Jeffrie Seley; Viral N Shah; Nam K Tran; Kayo Waki; Chris Worth; Tiffany Tian; Rachel E Aaron; Keetan Rutledge; Cindy N Ho; Alessandra T Ayers; Amanda Adler; David T Ahn; Halis Kaan Aktürk; Mohammed E Al-Sofiani; Timothy S Bailey; Matt Baker; Lia Bally; Raveendhara R Bannuru; Elizabeth M Bauer; Yong Mong Bee; Julia E Blanchette; Eda Cengiz; James Geoffrey Chase; Kong Y Chen; Daniel Cherñavvsky; Mark Clements; Gerard L Cote; Ketan K Dhatariya; Andjela Drincic; Niels Ejskjaer; Juan Espinoza; Chiara Fabris; G Alexander Fleming; Monica A L Gabbay; Rodolfo J Galindo; Ana María Gómez-Medina; Lutz Heinemann; Norbert Hermanns; Thanh Hoang; Sufyan Hussain; Peter G Jacobs; Johan Jendle; Shashank R Joshi; Suneil K Koliwad; Rayhan A Lal; Lawrence A Leiter; Marcus Lind; Julia K Mader; Alberto Maran; Umesh Masharani; Nestoras Mathioudakis; Michael McShane; Chhavi Mehta; Sun-Joon Moon; James H Nichols; David N O'Neal; Francisco J Pasquel; Anne L Peters; Andreas Pfützner; Rodica Pop-Busui; Pratistha Ranjitkar; Connie M Rhee; David B Sacks; Signe Schmidt; Simon M Schwaighofer; Bin Sheng; Gregg D Simonson; Koji Sode; Elias K Spanakis; Nicole L Spartano; Guillermo E Umpierrez; Maryam Vareth; Hubert W Vesper; Jing Wang; Eugene Wright; Alan H B Wu; Sewagegn Yeshiwas; Mihail Zilbermint; Michael A Kohn

doi:10.1177/19322968241275701

The Diabetes Technology Society Error Grid and Trend Accuracy Matrix for Glucose Monitors

David C Klonoff, Guido Freckmann, Stefan Pleus, Boris P Kovatchev, David Kerr, Chui Cindy Tse, Chengdong Li, Michael S D Agus, Kathleen Dungan, Barbora Voglová Hagerf, Jan S Krouwer, Wei-An Andy Lee, Shivani Misra, Sang Youl Rhee, Ashutosh Sabharwal, Jane Jeffrie Seley, Viral N Shah, Nam K Tran, Kayo Waki, Chris WorthTiffany Tian, Rachel E Aaron, Keetan Rutledge, Cindy N Ho, Alessandra T Ayers, Amanda Adler, David T Ahn, Halis Kaan Aktürk, Mohammed E Al-Sofiani, Timothy S Bailey, Matt Baker, Lia Bally, Raveendhara R Bannuru, Elizabeth M Bauer, Yong Mong Bee, Julia E Blanchette, Eda Cengiz, James Geoffrey Chase, Kong Y Chen, Daniel Cherñavvsky, Mark Clements, Gerard L Cote, Ketan K Dhatariya, Andjela Drincic, Niels Ejskjaer, Juan Espinoza, Chiara Fabris, G Alexander Fleming, Monica A L Gabbay, Rodolfo J Galindo, Ana María Gómez-Medina, Lutz Heinemann, Norbert Hermanns, Thanh Hoang, Sufyan Hussain, Peter G Jacobs, Johan Jendle, Shashank R Joshi, Suneil K Koliwad, Rayhan A Lal, Lawrence A Leiter, Marcus Lind, Julia K Mader, Alberto Maran, Umesh Masharani, Nestoras Mathioudakis, Michael McShane, Chhavi Mehta, Sun-Joon Moon, James H Nichols, David N O'Neal, Francisco J Pasquel, Anne L Peters, Andreas Pfützner, Rodica Pop-Busui, Pratistha Ranjitkar, Connie M Rhee, David B Sacks, Signe Schmidt, Simon M Schwaighofer, Bin Sheng, Gregg D Simonson, Koji Sode, Elias K Spanakis, Nicole L Spartano, Guillermo E Umpierrez, Maryam Vareth, Hubert W Vesper, Jing Wang, Eugene Wright, Alan H B Wu, Sewagegn Yeshiwas, Mihail Zilbermint, Michael A Kohn

Research output: Contribution to journal › Article › peer-review

Abstract

INTRODUCTION: An error grid compares measured versus reference glucose concentrations to assign clinical risk values to observed errors. Widely used error grids for blood glucose monitors (BGMs) have limited value because they do not also reflect clinical accuracy of continuous glucose monitors (CGMs).

METHODS: Diabetes Technology Society (DTS) convened 89 international experts in glucose monitoring to (1) smooth the borders of the Surveillance Error Grid (SEG) zones and create a user-friendly tool-the DTS Error Grid; (2) define five risk zones of clinical point accuracy (A-E) to be identical for BGMs and CGMs; (3) determine a relationship between DTS Error Grid percent in Zone A and mean absolute relative difference (MARD) from analyzing 22 BGM and nine CGM accuracy studies; and (4) create trend risk categories (1-5) for CGM trend accuracy.

RESULTS: The DTS Error Grid for point accuracy contains five risk zones (A-E) with straight-line borders that can be applied to both BGM and CGM accuracy data. In a data set combining point accuracy data from 18 BGMs, 2.6% of total data pairs equally moved from Zones A to B and vice versa (SEG compared with DTS Error Grid). For every 1% increase in percent data in Zone A, the MARD decreased by approximately 0.33%. We also created a DTS Trend Accuracy Matrix with five trend risk categories (1-5) for CGM-reported trend indicators compared with reference trends calculated from reference glucose.

CONCLUSION: The DTS Error Grid combines contemporary clinician input regarding clinical point accuracy for BGMs and CGMs. The DTS Trend Accuracy Matrix assesses accuracy of CGM trend indicators.

Original language	English
Pages (from-to)	19322968241275701
Journal	Journal of Diabetes Science and Technology
DOIs	https://doi.org/10.1177/19322968241275701
State	E-pub ahead of print - 6 Oct 2024

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10.1177/19322968241275701

Cite this

Klonoff, D. C., Freckmann, G., Pleus, S., Kovatchev, B. P., Kerr, D., Tse, C. C., Li, C., Agus, M. S. D., Dungan, K., Voglová Hagerf, B., Krouwer, J. S., Lee, W.-A. A., Misra, S., Rhee, S. Y., Sabharwal, A., Seley, J. J., Shah, V. N., Tran, N. K., Waki, K., ... Kohn, M. A. (2024). The Diabetes Technology Society Error Grid and Trend Accuracy Matrix for Glucose Monitors. Journal of Diabetes Science and Technology, 19322968241275701. Advance online publication. https://doi.org/10.1177/19322968241275701

@article{1e83877222984d7783f203344452e00e,

title = "The Diabetes Technology Society Error Grid and Trend Accuracy Matrix for Glucose Monitors",

abstract = "INTRODUCTION: An error grid compares measured versus reference glucose concentrations to assign clinical risk values to observed errors. Widely used error grids for blood glucose monitors (BGMs) have limited value because they do not also reflect clinical accuracy of continuous glucose monitors (CGMs).METHODS: Diabetes Technology Society (DTS) convened 89 international experts in glucose monitoring to (1) smooth the borders of the Surveillance Error Grid (SEG) zones and create a user-friendly tool-the DTS Error Grid; (2) define five risk zones of clinical point accuracy (A-E) to be identical for BGMs and CGMs; (3) determine a relationship between DTS Error Grid percent in Zone A and mean absolute relative difference (MARD) from analyzing 22 BGM and nine CGM accuracy studies; and (4) create trend risk categories (1-5) for CGM trend accuracy.RESULTS: The DTS Error Grid for point accuracy contains five risk zones (A-E) with straight-line borders that can be applied to both BGM and CGM accuracy data. In a data set combining point accuracy data from 18 BGMs, 2.6% of total data pairs equally moved from Zones A to B and vice versa (SEG compared with DTS Error Grid). For every 1% increase in percent data in Zone A, the MARD decreased by approximately 0.33%. We also created a DTS Trend Accuracy Matrix with five trend risk categories (1-5) for CGM-reported trend indicators compared with reference trends calculated from reference glucose.CONCLUSION: The DTS Error Grid combines contemporary clinician input regarding clinical point accuracy for BGMs and CGMs. The DTS Trend Accuracy Matrix assesses accuracy of CGM trend indicators.",

author = "Klonoff, {David C} and Guido Freckmann and Stefan Pleus and Kovatchev, {Boris P} and David Kerr and Tse, {Chui Cindy} and Chengdong Li and Agus, {Michael S D} and Kathleen Dungan and {Voglov{\'a} Hagerf}, Barbora and Krouwer, {Jan S} and Lee, {Wei-An Andy} and Shivani Misra and Rhee, {Sang Youl} and Ashutosh Sabharwal and Seley, {Jane Jeffrie} and Shah, {Viral N} and Tran, {Nam K} and Kayo Waki and Chris Worth and Tiffany Tian and Aaron, {Rachel E} and Keetan Rutledge and Ho, {Cindy N} and Ayers, {Alessandra T} and Amanda Adler and Ahn, {David T} and Akt{\"u}rk, {Halis Kaan} and Al-Sofiani, {Mohammed E} and Bailey, {Timothy S} and Matt Baker and Lia Bally and Bannuru, {Raveendhara R} and Bauer, {Elizabeth M} and Bee, {Yong Mong} and Blanchette, {Julia E} and Eda Cengiz and Chase, {James Geoffrey} and {Y Chen}, Kong and Daniel Cher{\~n}avvsky and Mark Clements and Cote, {Gerard L} and Dhatariya, {Ketan K} and Andjela Drincic and Niels Ejskjaer and Juan Espinoza and Chiara Fabris and Fleming, {G Alexander} and Gabbay, {Monica A L} and Galindo, {Rodolfo J} and G{\'o}mez-Medina, {Ana Mar{\'i}a} and Lutz Heinemann and Norbert Hermanns and Thanh Hoang and Sufyan Hussain and Jacobs, {Peter G} and Johan Jendle and Joshi, {Shashank R} and Koliwad, {Suneil K} and Lal, {Rayhan A} and Leiter, {Lawrence A} and Marcus Lind and Mader, {Julia K} and Alberto Maran and Umesh Masharani and Nestoras Mathioudakis and Michael McShane and Chhavi Mehta and Sun-Joon Moon and Nichols, {James H} and O'Neal, {David N} and Pasquel, {Francisco J} and Peters, {Anne L} and Andreas Pf{\"u}tzner and Rodica Pop-Busui and Pratistha Ranjitkar and Rhee, {Connie M} and Sacks, {David B} and Signe Schmidt and Schwaighofer, {Simon M} and Bin Sheng and Simonson, {Gregg D} and Koji Sode and Spanakis, {Elias K} and Spartano, {Nicole L} and Umpierrez, {Guillermo E} and Maryam Vareth and Vesper, {Hubert W} and Jing Wang and Eugene Wright and Wu, {Alan H B} and Sewagegn Yeshiwas and Mihail Zilbermint and Kohn, {Michael A}",

year = "2024",

month = oct,

day = "6",

doi = "10.1177/19322968241275701",

language = "English",

pages = "19322968241275701",

journal = "Journal of Diabetes Science and Technology",

issn = "1932-2968",

}

Klonoff, DC, Freckmann, G, Pleus, S, Kovatchev, BP, Kerr, D, Tse, CC, Li, C, Agus, MSD, Dungan, K, Voglová Hagerf, B, Krouwer, JS, Lee, W-AA, Misra, S, Rhee, SY, Sabharwal, A, Seley, JJ, Shah, VN, Tran, NK, Waki, K, Worth, C, Tian, T, Aaron, RE, Rutledge, K, Ho, CN, Ayers, AT, Adler, A, Ahn, DT, Aktürk, HK, Al-Sofiani, ME, Bailey, TS, Baker, M, Bally, L, Bannuru, RR, Bauer, EM, Bee, YM, Blanchette, JE, Cengiz, E, Chase, JG, Y Chen, K, Cherñavvsky, D, Clements, M, Cote, GL, Dhatariya, KK, Drincic, A, Ejskjaer, N, Espinoza, J, Fabris, C, Fleming, GA, Gabbay, MAL, Galindo, RJ, Gómez-Medina, AM, Heinemann, L, Hermanns, N, Hoang, T, Hussain, S, Jacobs, PG, Jendle, J, Joshi, SR, Koliwad, SK, Lal, RA, Leiter, LA, Lind, M, Mader, JK, Maran, A, Masharani, U, Mathioudakis, N, McShane, M, Mehta, C, Moon, S-J, Nichols, JH, O'Neal, DN, Pasquel, FJ, Peters, AL, Pfützner, A, Pop-Busui, R, Ranjitkar, P, Rhee, CM, Sacks, DB, Schmidt, S, Schwaighofer, SM, Sheng, B, Simonson, GD, Sode, K, Spanakis, EK, Spartano, NL, Umpierrez, GE, Vareth, M, Vesper, HW, Wang, J, Wright, E, Wu, AHB, Yeshiwas, S, Zilbermint, M & Kohn, MA 2024, 'The Diabetes Technology Society Error Grid and Trend Accuracy Matrix for Glucose Monitors', Journal of Diabetes Science and Technology, pp. 19322968241275701. https://doi.org/10.1177/19322968241275701

TY - JOUR

T1 - The Diabetes Technology Society Error Grid and Trend Accuracy Matrix for Glucose Monitors

AU - Klonoff, David C

AU - Freckmann, Guido

AU - Pleus, Stefan

AU - Kovatchev, Boris P

AU - Kerr, David

AU - Tse, Chui Cindy

AU - Li, Chengdong

AU - Agus, Michael S D

AU - Dungan, Kathleen

AU - Voglová Hagerf, Barbora

AU - Krouwer, Jan S

AU - Lee, Wei-An Andy

AU - Misra, Shivani

AU - Rhee, Sang Youl

AU - Sabharwal, Ashutosh

AU - Seley, Jane Jeffrie

AU - Shah, Viral N

AU - Tran, Nam K

AU - Waki, Kayo

AU - Worth, Chris

AU - Tian, Tiffany

AU - Aaron, Rachel E

AU - Rutledge, Keetan

AU - Ho, Cindy N

AU - Ayers, Alessandra T

AU - Adler, Amanda

AU - Ahn, David T

AU - Aktürk, Halis Kaan

AU - Al-Sofiani, Mohammed E

AU - Bailey, Timothy S

AU - Baker, Matt

AU - Bally, Lia

AU - Bannuru, Raveendhara R

AU - Bauer, Elizabeth M

AU - Bee, Yong Mong

AU - Blanchette, Julia E

AU - Cengiz, Eda

AU - Chase, James Geoffrey

AU - Y Chen, Kong

AU - Cherñavvsky, Daniel

AU - Clements, Mark

AU - Cote, Gerard L

AU - Dhatariya, Ketan K

AU - Drincic, Andjela

AU - Ejskjaer, Niels

AU - Espinoza, Juan

AU - Fabris, Chiara

AU - Fleming, G Alexander

AU - Gabbay, Monica A L

AU - Galindo, Rodolfo J

AU - Gómez-Medina, Ana María

AU - Heinemann, Lutz

AU - Hermanns, Norbert

AU - Hoang, Thanh

AU - Hussain, Sufyan

AU - Jacobs, Peter G

AU - Jendle, Johan

AU - Joshi, Shashank R

AU - Koliwad, Suneil K

AU - Lal, Rayhan A

AU - Leiter, Lawrence A

AU - Lind, Marcus

AU - Mader, Julia K

AU - Maran, Alberto

AU - Masharani, Umesh

AU - Mathioudakis, Nestoras

AU - McShane, Michael

AU - Mehta, Chhavi

AU - Moon, Sun-Joon

AU - Nichols, James H

AU - O'Neal, David N

AU - Pasquel, Francisco J

AU - Peters, Anne L

AU - Pfützner, Andreas

AU - Pop-Busui, Rodica

AU - Ranjitkar, Pratistha

AU - Rhee, Connie M

AU - Sacks, David B

AU - Schmidt, Signe

AU - Schwaighofer, Simon M

AU - Sheng, Bin

AU - Simonson, Gregg D

AU - Sode, Koji

AU - Spanakis, Elias K

AU - Spartano, Nicole L

AU - Umpierrez, Guillermo E

AU - Vareth, Maryam

AU - Vesper, Hubert W

AU - Wang, Jing

AU - Wright, Eugene

AU - Wu, Alan H B

AU - Yeshiwas, Sewagegn

AU - Zilbermint, Mihail

AU - Kohn, Michael A

PY - 2024/10/6

Y1 - 2024/10/6

N2 - INTRODUCTION: An error grid compares measured versus reference glucose concentrations to assign clinical risk values to observed errors. Widely used error grids for blood glucose monitors (BGMs) have limited value because they do not also reflect clinical accuracy of continuous glucose monitors (CGMs).METHODS: Diabetes Technology Society (DTS) convened 89 international experts in glucose monitoring to (1) smooth the borders of the Surveillance Error Grid (SEG) zones and create a user-friendly tool-the DTS Error Grid; (2) define five risk zones of clinical point accuracy (A-E) to be identical for BGMs and CGMs; (3) determine a relationship between DTS Error Grid percent in Zone A and mean absolute relative difference (MARD) from analyzing 22 BGM and nine CGM accuracy studies; and (4) create trend risk categories (1-5) for CGM trend accuracy.RESULTS: The DTS Error Grid for point accuracy contains five risk zones (A-E) with straight-line borders that can be applied to both BGM and CGM accuracy data. In a data set combining point accuracy data from 18 BGMs, 2.6% of total data pairs equally moved from Zones A to B and vice versa (SEG compared with DTS Error Grid). For every 1% increase in percent data in Zone A, the MARD decreased by approximately 0.33%. We also created a DTS Trend Accuracy Matrix with five trend risk categories (1-5) for CGM-reported trend indicators compared with reference trends calculated from reference glucose.CONCLUSION: The DTS Error Grid combines contemporary clinician input regarding clinical point accuracy for BGMs and CGMs. The DTS Trend Accuracy Matrix assesses accuracy of CGM trend indicators.

AB - INTRODUCTION: An error grid compares measured versus reference glucose concentrations to assign clinical risk values to observed errors. Widely used error grids for blood glucose monitors (BGMs) have limited value because they do not also reflect clinical accuracy of continuous glucose monitors (CGMs).METHODS: Diabetes Technology Society (DTS) convened 89 international experts in glucose monitoring to (1) smooth the borders of the Surveillance Error Grid (SEG) zones and create a user-friendly tool-the DTS Error Grid; (2) define five risk zones of clinical point accuracy (A-E) to be identical for BGMs and CGMs; (3) determine a relationship between DTS Error Grid percent in Zone A and mean absolute relative difference (MARD) from analyzing 22 BGM and nine CGM accuracy studies; and (4) create trend risk categories (1-5) for CGM trend accuracy.RESULTS: The DTS Error Grid for point accuracy contains five risk zones (A-E) with straight-line borders that can be applied to both BGM and CGM accuracy data. In a data set combining point accuracy data from 18 BGMs, 2.6% of total data pairs equally moved from Zones A to B and vice versa (SEG compared with DTS Error Grid). For every 1% increase in percent data in Zone A, the MARD decreased by approximately 0.33%. We also created a DTS Trend Accuracy Matrix with five trend risk categories (1-5) for CGM-reported trend indicators compared with reference trends calculated from reference glucose.CONCLUSION: The DTS Error Grid combines contemporary clinician input regarding clinical point accuracy for BGMs and CGMs. The DTS Trend Accuracy Matrix assesses accuracy of CGM trend indicators.

U2 - 10.1177/19322968241275701

DO - 10.1177/19322968241275701

M3 - Article

C2 - 39369312

SN - 1932-2968

SP - 19322968241275701

JO - Journal of Diabetes Science and Technology

JF - Journal of Diabetes Science and Technology

ER -