Metabolic Risk Panel

Metabolic Risk Panel

This panel is used to assess early metabolic dysfunction and cardiometabolic risk.

See also 6 related tests 7 related guides Test Guide List

Metabolic Risk Panel

Test Summary

 

Metabolic Risk Panel

Test code: 39447

 

Clinical use

  • Assess early metabolic dysfunction and cardiometabolic risk

Clinical background

In the context of aging and weight gain, individuals can develop cardiometabolic disease, the hallmark of which is insulin resistance (IR). IR is characterized by cells being less sensitive to the effects of insulin and not absorbing enough glucose from the bloodstream. More than 40% of nondiabetic young adults in the United States are estimated to have IR.1 When clustered with other clinical features, such as dyslipidemia and hypertension, IR can contribute to progression to type 2 diabetes (T2D) and cardiovascular disease (CVD).2 Early identification of the drivers of cardiometabolic disease, namely hyperglycemia and hyperlipidemia, provides an opportunity for early intervention to prevent the development of end-organ dysfunction of the heart, liver, and kidneys. 

IR progression to T2D

One early indicator of metabolic dysfunction is excess insulin production, which reflects a developing IR state.3,4 In response to reduced insulin sensitivity, pancreatic beta-cells may produce high levels of insulin to maintain normal levels of blood glucose. High levels of C-peptide, a byproduct of insulin processing, are also produced as insulin production increases (Table 1).3-6 By measuring combined serum levels of insulin and C-peptide using a specific, high-throughput liquid chromatography-tandem mass spectrometry (LC/MS/MS)–based test,7 an "IR score" can be calculated that represents the likelihood of an individual having IR.3

Table 1. Markers of Progression of Metabolic Dysfunction Through IR, Prediabetes, and Diabetes

Condition

Fasting insulin and
C-peptide3,4,6

Fasting glucose, mg/dL5

Hemoglobin A1c, %5

Normoglycemic

In range

70-99

<5.7

Insulin resistance, early stage

↑

70-99

<5.7

Prediabetesa

↑

100-125

5.7-6.4

Type 2 diabetesa

↑, in range, or ↓

≥126

≥6.5

a Fasting glucose or hemoglobin A1c levels help define these conditions.

 

Individuals with IR are at risk of subsequently developing prediabetes and T2D, which is reflected by fasting glucose and hemoglobin A1c (HbA1c) levels (Table 1). A 2025 study demonstrated this progression in individuals with normoglycemic fasting glucose and HbA1c levels at baseline but who subsequently developed incident prediabetes or T2D. Compared to those who didn't progress, these individuals were characterized by higher and increasing IR scores when followed for 3 years regardless of their age, sex, and overweight status and HbA1c levels at baseline.8

In addition to its role in diagnosing diabetes and prediabetes, HbA1c measurement also improves risk prediction for diabetic progression compared with fasting plasma glucose and oral glucose tolerance tests, which measure glucose levels only in the short term.9 HbA1c assays more reliably estimate average glucose levels over a longer term (about 3 months).5

IR and dyslipidemia

IR is also characterized by several CVD risk factors that contribute to the development of cardiometabolic disease, including high blood pressure; high levels of triglycerides (TGs), apolipoprotein B (apoB), and small dense low-density lipoprotein cholesterol (sdLDL-C); low levels of high density lipoprotein–cholesterol (HDL-C); inflammation; and coagulant disorders.10 Individuals with IR frequently exhibit "lipid discordance," in which apoB levels increase disproportionately relative to LDL-C levels.11,12 Discordance is related to discrepancies between blood cholesterol concentrations and atherogenic particle number, which is a better indicator of CVD risk.11,13

Although this discordance (low LDL-C relative to apoB) is most often observed in individuals with diabetes or obesity who often have high TGs,11 a 2025 study has shown increasing prevalence of IR, apoB-LDL-C discordance, vascular inflammation, and triglyceridemia, even within a population within the normal range of HbA1c.14 Discordance is reflected in guidelines, which indicate that apoB gives a better estimate of CVD risk than LDL-C when TG levels are high (>200 mg/dL).15,16 An elevated apoB despite controlled LDL-C identifies patients who may benefit from more aggressive LDL-lowering targets.

Quest Diagnostics and Cleveland HeartLab offer the Metabolic Risk Panel (test code 39447) to assess early metabolic dysfunction (Table 2).17 Metabolic risk is profiled by comparing test results for all the components (apoB, HbA1c, intact insulin, C-peptide, calculated IR score, lipid panel [total cholesterol, TGs, LDL-, HDL-, and nonHDL-C]). Components include actionable indicators of diabetes and CVD risk that can be mitigated through lifestyle changes early in disease progression.18

Individuals suitable for testing

  • Individuals at risk of early metabolic dysfunction, including those undergoing CVD risk assessment
  • Individuals at risk of insulin resistance, which can lead to prediabetes or T2D (eg, overweight/obese; have a family history of diabetes; history of gestational diabetes, polycystic ovary syndrome [PCOS], or acanthosis nigricans)

Method

For panel components and methods used, see Table 2.

Table 2. Panelsa and Tests Included in the Metabolic Risk Panel

Test code

Test name (component tests and codes)

Method(s)

 Reference ranges for adultsb

91726

Cardio IQ® Apolipoprotein B

Immunoassay
  • <90 mg/dL

91732

Cardio IQ® Hemoglobin A1c

Immunoturbidimetry
  • <5.7%

36509

Cardio IQ® Insulin Resistance Panel with Scorec

Includes insulin, intact LC/MS/MS (93103), C-peptided and calculated IR score.

High-throughput immunochemical enrichment, LC/MS/MS
  • C-peptide 0.68-2.16 ng/mL
  • Insulin ≤16 μIU/mL

91716

Lipid Panel, Cardio IQ®

Includes total cholesterol (334), triglycerides (896), HDL-C (608), calculated LDL-C,e cholesterol/HDL ratio, non-HDL-C, and Cardio IQ interpretive report.

Spectrophotometry
  • Total <200 mg/dL
  • HDL-C≥50 mg/dL (female)
    ≥40 mg/dL (male)
  • Total/HDL-C ratio <5
  • non-HDL-C <130 mg/dL
  • TG <150 mg/dL
  • LDL-C, calc <100 mg/dL
Calc, calculated; HDL-C, high-density lipoprotein cholesterol; IR, insulin resistance; LC/MS/MS, liquid chromatography-tandem mass spectrometry; LDL-C, low-density lipoprotein cholesterol.
a Panel components may be ordered separately.
b For IR score, see CardioIQ Insulin Resistance Panel With Score.
c This test was developed and its analytical performance characteristics have been determined by Quest Diagnostics. It has not been cleared or approved by FDA. This assay has been validated pursuant to the CLIA regulations and is used for clinical purposes.
d The C-peptide LC/MS/MS panel component cannot be ordered separately. C-peptide by immunoassay (test code 372) is not an equivalent test and cannot be used in calculation of the IR score.
e This is calculated using the Martin-Hopkins equation.17

Interpretive information

Results for HbA1c, TGs, LDL-C, total cholesterol/HDL-C, nonHDL-C, apoB, and the IR score are interpreted as "optimal," "moderate," or "high" in terms of cardiometabolic risk. ApoB levels can also be used to help assess risk for a cardiovascular event and as targets for lipid-lowering therapies.19-22 Results for total cholesterol, HDL-C, glucose, intact insulin, and C-peptide are interpreted as "optimal" or "high" risk using single cutpoints.

HbA1c levels define presence or absence of prediabetes and T2D (Table 1).5 For more information, see the related Test Guide: Laboratory Testing for Diabetes Diagnosis and Management.

Lipid cutpoints for risk are based on literature but vary depending on the patient characteristics and guidelines used.16,23 For more information, see the related Test Summary: LDL Cholesterol.

ApoB levels can also be used to help assess risk for a cardiovascular event and, in combination with LDL-C, can be used to refine targets for lipid-lowering therapies.15,21,23 For more information, see the related Test Summary: Apolipoprotein B.

IR is most likely if an individual has an IR score >66%; they are >15-fold more likely to have IR than an individual with a score <33%.3 The IR score reflects excess insulin production, which in nondiabetic obese individuals reflects a developing IR state.4 For more information, see the related Test Summary: CardioIQ Insulin Resistance Panel With Score.

A high IR score may also be characterized by several CVD risk factors, including high blood pressure; high levels of TGs, apoB, and highly atherogenic sdLDL-C (test code 36406); low levels of HDL-C; inflammation; and coagulant disorders.10 Consequently, a high IR score is associated with incident CVD.24

Elevated HbA1c levels and an IR state independently predict an elevated risk of incident T2D, even in the context of normal fasting plasma glucose (<100 mg/dL); classification of risk improves when markers are combined.25

References

  1. Parcha V, Heindl B, Kalra R, et al. Insulin resistance and cardiometabolic risk profile among nondiabetic American young adults: insights from NHANES. J Clin Endocrinol Metab. 2022;107(1):e25-e37. doi:10.1210/clinem/dgab645
  2. Xu H, Li X, Adams H, et al. Etiology of metabolic syndrome and dietary intervention. Int J Mol Sci. 2018;20(1). doi:10.3390/ijms20010128
  3. Abbasi F, Shiffman D, Tong CH, et al. Insulin resistance probability scores for apparently healthy individuals. J Endocr Soc. 2018;2(9):1050-1057. doi:10.1210/js.2018-00107
  4. Thomas DD, Corkey BE, Istfan NW, et al. Hyperinsulinemia: an early indicator of metabolic dysfunction. J Endocr Soc. 2019;3(9):1727-1747. doi:10.1210/js.2019-00065
  5. American Diabetes Association Professional Practice Committee. 2. Diagnosis and classification of diabetes: standards of care in diabetes—2025. Diabetes Care. 2025;48(suppl 1):S27–S49. doi:10.2337/dc25-S002
  6. Maddaloni E, Bolli GB, Frier BM, et al. C-peptide determination in the diagnosis of type of diabetes and its management: a clinical perspective. Diabetes Obes Metab. 2022;24(10):1912-1926. doi:10.1111/dom.14785
  7. Taylor SW, Clarke NJ, Chen Z, et al. A high-throughput mass spectrometry assay to simultaneously measure intact insulin and C-peptide. Clin Chim Acta. 2016;455:202-208. doi:10.1016/j.cca.2016.01.019
  8. Louie JZ, Shiffman D, Melander M, et al. Among those with normoglycemia, insulin resistance risk score (IRRS) elevation is observed up to 3 years prior to diagnosis of diabetes or prediabetes. Presented at: American Diabetes Association 85th Scientific Sessions; June 20-23, 2025; Chicago, IL.
  9. Leong A, Daya N, Porneala B, et al. Prediction of type 2 diabetes by hemoglobin A1c in two community-based cohorts. Diabetes Care. 2018;41(1):60-68. doi:10.2337/dc17-0607
  10. Garber AJ, Handelsman Y, Grunberger G, et al. Consensus statement by the American Association of Clinical Endocrinologists and American College of Endocrinology on the comprehensive type 2 diabetes management algorithm - 2020 executive summary. Endocr Pract. 2020;26(1):107-139. doi:10.4158/CS-2019-0472
  11. Carr SS, Hooper AJ, Sullivan DR, et al. Non-HDL-cholesterol and apolipoprotein B compared with LDL-cholesterol in atherosclerotic cardiovascular disease risk assessment. Pathology. 2019;51(2):148-154. doi:10.1016/j.pathol.2018.11.006
  12. Varvel SA, Dayspring TD, Edmonds Y, et al. Discordance between apolipoprotein B and low-density lipoprotein particle number is associated with insulin resistance in clinical practice. J Clin Lipidol. 2015;9(2):247-255. doi:10.1016/j.jacl.2014.11.005
  13. Sniderman AD, Williams K, Contois JH, et al. A meta-analysis of low-density lipoprotein cholesterol, non-high-density lipoprotein cholesterol, and apolipoprotein B as markers of cardiovascular risk. Circ Cardiovasc Qual Outcomes. 2011;4(3):337-345. doi:10.1161/circoutcomes.110.959247
  14. Penn MS, Winchester TB, Saghir J, et al. Cardiometabolic disease associated markers increase at an A1C >5%. Presented at: National Lipid Associations; 2025 Annual Scientific Sessions; May 29-June 1, 2025; Miami, FL.
  15. Arnett DK, Blumenthal RS, Albert MA, et al. 2019 ACC/AHA guideline on the primary prevention of cardiovascular disease: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Circulation. 2019;140(11):e596-e646. doi:10.1161/CIR.0000000000000678
  16. Grundy SM, Stone NJ, Bailey AL, et al. 2018 AHA/ACC/AACVPR/AAPA/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA guideline on the management of blood cholesterol: a report of the American College of Cardiology/American Heart Association task force on clinical practice guidelines. Circulation. 2019;139(25):e1082-e1143. doi:10.1161/CIR.0000000000000625
  17. Martin SS, Blaha MJ, Elshazly MB, et al. Comparison of a novel method vs the Friedewald equation for estimating low-density lipoprotein cholesterol levels from the standard lipid profile. JAMA. 2013;310(19):2061-2068. doi:10.1001/jama.2013.280532
  18. Galaviz KI, Narayan KMV, Lobelo F, et al. Lifestyle and the prevention of type 2 diabetes: a status report. Am J Lifestyle Med. 2018;12(1):4-20. doi:10.1177/1559827615619159
  19. Jacobson TA, Ito MK, Maki KC, et al. National Lipid Association recommendations for patient-centered management of dyslipidemia: part 1—full report. J Clin Lipidol. 2015;9(2):129-169. doi:10.1016/j.jacl.2015.02.003
  20. Jellinger PS, Handelsman Y, Rosenblit PD, et al. American Association of Clinical Endocrinologists and American College of Endocrinology guidelines for management of dyslipidemia and prevention of cardiovascular disease. Endocr Pract. 2017;23(Suppl 2):1-87. doi:10.4158/ep171764.Appgl
  21. Wilson PWF, Jacobson TA, Martin SS, et al. Lipid measurements in the management of cardiovascular diseases: practical recommendations a scientific statement from the National Lipid Association writing group. J Clin Lipidol. 2021;15(5):629-648. doi:10.1016/j.jacl.2021.09.046
  22. Soffer DE, Marston NA, Maki KC, et al. Role of apolipoprotein B in the clinical management of cardiovascular risk in adults: an expert clinical consensus from the National Lipid Association. J Clin Lipidol. 2024;18(5):e647-e663. doi:10.1016/j.jacl.2024.08.013
  23. Handelsman Y, Jellinger PS, Guerin CK, et al. Consensus statement by the American Association of Clinical Endocrinologists and American College of Endocrinology on the management of dyslipidemia and prevention of cardiovascular disease algorithm—2020 executive summary. Endocr Pract. 2020;26(10):1196-1224. doi:10.4158/CS-2020-0490
  24. Louie JZ, Shiffman D, McPhaul MJ, et al. Insulin resistance probability score and incident cardiovascular disease. J Intern Med. 2023;294(4):531-535. doi:10.1111/joim.13687
  25. Meigs JB, Porneala B, Leong A, et al. Simultaneous consideration of HbA1c and insulin resistance improves risk assessment in white individuals at increased risk for future type 2 diabetes. Diabetes Care. 2020;43(8):e90-e92. doi:10.2337/dc20-0718
     

Content reviewed 10/2025

top of page

This panel is used to assess early metabolic dysfunction and cardiometabolic risk.

Test Guide List

Metabolic Risk Panel

Test Summary

 

Metabolic Risk Panel

Test code: 39447

 

Clinical use

  • Assess early metabolic dysfunction and cardiometabolic risk

Clinical background

In the context of aging and weight gain, individuals can develop cardiometabolic disease, the hallmark of which is insulin resistance (IR). IR is characterized by cells being less sensitive to the effects of insulin and not absorbing enough glucose from the bloodstream. More than 40% of nondiabetic young adults in the United States are estimated to have IR.1 When clustered with other clinical features, such as dyslipidemia and hypertension, IR can contribute to progression to type 2 diabetes (T2D) and cardiovascular disease (CVD).2 Early identification of the drivers of cardiometabolic disease, namely hyperglycemia and hyperlipidemia, provides an opportunity for early intervention to prevent the development of end-organ dysfunction of the heart, liver, and kidneys. 

IR progression to T2D

One early indicator of metabolic dysfunction is excess insulin production, which reflects a developing IR state.3,4 In response to reduced insulin sensitivity, pancreatic beta-cells may produce high levels of insulin to maintain normal levels of blood glucose. High levels of C-peptide, a byproduct of insulin processing, are also produced as insulin production increases (Table 1).3-6 By measuring combined serum levels of insulin and C-peptide using a specific, high-throughput liquid chromatography-tandem mass spectrometry (LC/MS/MS)–based test,7 an "IR score" can be calculated that represents the likelihood of an individual having IR.3

Table 1. Markers of Progression of Metabolic Dysfunction Through IR, Prediabetes, and Diabetes

Condition

Fasting insulin and
C-peptide3,4,6

Fasting glucose, mg/dL5

Hemoglobin A1c, %5

Normoglycemic

In range

70-99

<5.7

Insulin resistance, early stage

↑

70-99

<5.7

Prediabetesa

↑

100-125

5.7-6.4

Type 2 diabetesa

↑, in range, or ↓

≥126

≥6.5

a Fasting glucose or hemoglobin A1c levels help define these conditions.

 

Individuals with IR are at risk of subsequently developing prediabetes and T2D, which is reflected by fasting glucose and hemoglobin A1c (HbA1c) levels (Table 1). A 2025 study demonstrated this progression in individuals with normoglycemic fasting glucose and HbA1c levels at baseline but who subsequently developed incident prediabetes or T2D. Compared to those who didn't progress, these individuals were characterized by higher and increasing IR scores when followed for 3 years regardless of their age, sex, and overweight status and HbA1c levels at baseline.8

In addition to its role in diagnosing diabetes and prediabetes, HbA1c measurement also improves risk prediction for diabetic progression compared with fasting plasma glucose and oral glucose tolerance tests, which measure glucose levels only in the short term.9 HbA1c assays more reliably estimate average glucose levels over a longer term (about 3 months).5

IR and dyslipidemia

IR is also characterized by several CVD risk factors that contribute to the development of cardiometabolic disease, including high blood pressure; high levels of triglycerides (TGs), apolipoprotein B (apoB), and small dense low-density lipoprotein cholesterol (sdLDL-C); low levels of high density lipoprotein–cholesterol (HDL-C); inflammation; and coagulant disorders.10 Individuals with IR frequently exhibit "lipid discordance," in which apoB levels increase disproportionately relative to LDL-C levels.11,12 Discordance is related to discrepancies between blood cholesterol concentrations and atherogenic particle number, which is a better indicator of CVD risk.11,13

Although this discordance (low LDL-C relative to apoB) is most often observed in individuals with diabetes or obesity who often have high TGs,11 a 2025 study has shown increasing prevalence of IR, apoB-LDL-C discordance, vascular inflammation, and triglyceridemia, even within a population within the normal range of HbA1c.14 Discordance is reflected in guidelines, which indicate that apoB gives a better estimate of CVD risk than LDL-C when TG levels are high (>200 mg/dL).15,16 An elevated apoB despite controlled LDL-C identifies patients who may benefit from more aggressive LDL-lowering targets.

Quest Diagnostics and Cleveland HeartLab offer the Metabolic Risk Panel (test code 39447) to assess early metabolic dysfunction (Table 2).17 Metabolic risk is profiled by comparing test results for all the components (apoB, HbA1c, intact insulin, C-peptide, calculated IR score, lipid panel [total cholesterol, TGs, LDL-, HDL-, and nonHDL-C]). Components include actionable indicators of diabetes and CVD risk that can be mitigated through lifestyle changes early in disease progression.18

Individuals suitable for testing

  • Individuals at risk of early metabolic dysfunction, including those undergoing CVD risk assessment
  • Individuals at risk of insulin resistance, which can lead to prediabetes or T2D (eg, overweight/obese; have a family history of diabetes; history of gestational diabetes, polycystic ovary syndrome [PCOS], or acanthosis nigricans)

Method

For panel components and methods used, see Table 2.

Table 2. Panelsa and Tests Included in the Metabolic Risk Panel

Test code

Test name (component tests and codes)

Method(s)

 Reference ranges for adultsb

91726

Cardio IQ® Apolipoprotein B

Immunoassay
  • <90 mg/dL

91732

Cardio IQ® Hemoglobin A1c

Immunoturbidimetry
  • <5.7%

36509

Cardio IQ® Insulin Resistance Panel with Scorec

Includes insulin, intact LC/MS/MS (93103), C-peptided and calculated IR score.

High-throughput immunochemical enrichment, LC/MS/MS
  • C-peptide 0.68-2.16 ng/mL
  • Insulin ≤16 μIU/mL

91716

Lipid Panel, Cardio IQ®

Includes total cholesterol (334), triglycerides (896), HDL-C (608), calculated LDL-C,e cholesterol/HDL ratio, non-HDL-C, and Cardio IQ interpretive report.

Spectrophotometry
  • Total <200 mg/dL
  • HDL-C≥50 mg/dL (female)
    ≥40 mg/dL (male)
  • Total/HDL-C ratio <5
  • non-HDL-C <130 mg/dL
  • TG <150 mg/dL
  • LDL-C, calc <100 mg/dL
Calc, calculated; HDL-C, high-density lipoprotein cholesterol; IR, insulin resistance; LC/MS/MS, liquid chromatography-tandem mass spectrometry; LDL-C, low-density lipoprotein cholesterol.
a Panel components may be ordered separately.
b For IR score, see CardioIQ Insulin Resistance Panel With Score.
c This test was developed and its analytical performance characteristics have been determined by Quest Diagnostics. It has not been cleared or approved by FDA. This assay has been validated pursuant to the CLIA regulations and is used for clinical purposes.
d The C-peptide LC/MS/MS panel component cannot be ordered separately. C-peptide by immunoassay (test code 372) is not an equivalent test and cannot be used in calculation of the IR score.
e This is calculated using the Martin-Hopkins equation.17

Interpretive information

Results for HbA1c, TGs, LDL-C, total cholesterol/HDL-C, nonHDL-C, apoB, and the IR score are interpreted as "optimal," "moderate," or "high" in terms of cardiometabolic risk. ApoB levels can also be used to help assess risk for a cardiovascular event and as targets for lipid-lowering therapies.19-22 Results for total cholesterol, HDL-C, glucose, intact insulin, and C-peptide are interpreted as "optimal" or "high" risk using single cutpoints.

HbA1c levels define presence or absence of prediabetes and T2D (Table 1).5 For more information, see the related Test Guide: Laboratory Testing for Diabetes Diagnosis and Management.

Lipid cutpoints for risk are based on literature but vary depending on the patient characteristics and guidelines used.16,23 For more information, see the related Test Summary: LDL Cholesterol.

ApoB levels can also be used to help assess risk for a cardiovascular event and, in combination with LDL-C, can be used to refine targets for lipid-lowering therapies.15,21,23 For more information, see the related Test Summary: Apolipoprotein B.

IR is most likely if an individual has an IR score >66%; they are >15-fold more likely to have IR than an individual with a score <33%.3 The IR score reflects excess insulin production, which in nondiabetic obese individuals reflects a developing IR state.4 For more information, see the related Test Summary: CardioIQ Insulin Resistance Panel With Score.

A high IR score may also be characterized by several CVD risk factors, including high blood pressure; high levels of TGs, apoB, and highly atherogenic sdLDL-C (test code 36406); low levels of HDL-C; inflammation; and coagulant disorders.10 Consequently, a high IR score is associated with incident CVD.24

Elevated HbA1c levels and an IR state independently predict an elevated risk of incident T2D, even in the context of normal fasting plasma glucose (<100 mg/dL); classification of risk improves when markers are combined.25

References

  1. Parcha V, Heindl B, Kalra R, et al. Insulin resistance and cardiometabolic risk profile among nondiabetic American young adults: insights from NHANES. J Clin Endocrinol Metab. 2022;107(1):e25-e37. doi:10.1210/clinem/dgab645
  2. Xu H, Li X, Adams H, et al. Etiology of metabolic syndrome and dietary intervention. Int J Mol Sci. 2018;20(1). doi:10.3390/ijms20010128
  3. Abbasi F, Shiffman D, Tong CH, et al. Insulin resistance probability scores for apparently healthy individuals. J Endocr Soc. 2018;2(9):1050-1057. doi:10.1210/js.2018-00107
  4. Thomas DD, Corkey BE, Istfan NW, et al. Hyperinsulinemia: an early indicator of metabolic dysfunction. J Endocr Soc. 2019;3(9):1727-1747. doi:10.1210/js.2019-00065
  5. American Diabetes Association Professional Practice Committee. 2. Diagnosis and classification of diabetes: standards of care in diabetes—2025. Diabetes Care. 2025;48(suppl 1):S27–S49. doi:10.2337/dc25-S002
  6. Maddaloni E, Bolli GB, Frier BM, et al. C-peptide determination in the diagnosis of type of diabetes and its management: a clinical perspective. Diabetes Obes Metab. 2022;24(10):1912-1926. doi:10.1111/dom.14785
  7. Taylor SW, Clarke NJ, Chen Z, et al. A high-throughput mass spectrometry assay to simultaneously measure intact insulin and C-peptide. Clin Chim Acta. 2016;455:202-208. doi:10.1016/j.cca.2016.01.019
  8. Louie JZ, Shiffman D, Melander M, et al. Among those with normoglycemia, insulin resistance risk score (IRRS) elevation is observed up to 3 years prior to diagnosis of diabetes or prediabetes. Presented at: American Diabetes Association 85th Scientific Sessions; June 20-23, 2025; Chicago, IL.
  9. Leong A, Daya N, Porneala B, et al. Prediction of type 2 diabetes by hemoglobin A1c in two community-based cohorts. Diabetes Care. 2018;41(1):60-68. doi:10.2337/dc17-0607
  10. Garber AJ, Handelsman Y, Grunberger G, et al. Consensus statement by the American Association of Clinical Endocrinologists and American College of Endocrinology on the comprehensive type 2 diabetes management algorithm - 2020 executive summary. Endocr Pract. 2020;26(1):107-139. doi:10.4158/CS-2019-0472
  11. Carr SS, Hooper AJ, Sullivan DR, et al. Non-HDL-cholesterol and apolipoprotein B compared with LDL-cholesterol in atherosclerotic cardiovascular disease risk assessment. Pathology. 2019;51(2):148-154. doi:10.1016/j.pathol.2018.11.006
  12. Varvel SA, Dayspring TD, Edmonds Y, et al. Discordance between apolipoprotein B and low-density lipoprotein particle number is associated with insulin resistance in clinical practice. J Clin Lipidol. 2015;9(2):247-255. doi:10.1016/j.jacl.2014.11.005
  13. Sniderman AD, Williams K, Contois JH, et al. A meta-analysis of low-density lipoprotein cholesterol, non-high-density lipoprotein cholesterol, and apolipoprotein B as markers of cardiovascular risk. Circ Cardiovasc Qual Outcomes. 2011;4(3):337-345. doi:10.1161/circoutcomes.110.959247
  14. Penn MS, Winchester TB, Saghir J, et al. Cardiometabolic disease associated markers increase at an A1C >5%. Presented at: National Lipid Associations; 2025 Annual Scientific Sessions; May 29-June 1, 2025; Miami, FL.
  15. Arnett DK, Blumenthal RS, Albert MA, et al. 2019 ACC/AHA guideline on the primary prevention of cardiovascular disease: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Circulation. 2019;140(11):e596-e646. doi:10.1161/CIR.0000000000000678
  16. Grundy SM, Stone NJ, Bailey AL, et al. 2018 AHA/ACC/AACVPR/AAPA/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA guideline on the management of blood cholesterol: a report of the American College of Cardiology/American Heart Association task force on clinical practice guidelines. Circulation. 2019;139(25):e1082-e1143. doi:10.1161/CIR.0000000000000625
  17. Martin SS, Blaha MJ, Elshazly MB, et al. Comparison of a novel method vs the Friedewald equation for estimating low-density lipoprotein cholesterol levels from the standard lipid profile. JAMA. 2013;310(19):2061-2068. doi:10.1001/jama.2013.280532
  18. Galaviz KI, Narayan KMV, Lobelo F, et al. Lifestyle and the prevention of type 2 diabetes: a status report. Am J Lifestyle Med. 2018;12(1):4-20. doi:10.1177/1559827615619159
  19. Jacobson TA, Ito MK, Maki KC, et al. National Lipid Association recommendations for patient-centered management of dyslipidemia: part 1—full report. J Clin Lipidol. 2015;9(2):129-169. doi:10.1016/j.jacl.2015.02.003
  20. Jellinger PS, Handelsman Y, Rosenblit PD, et al. American Association of Clinical Endocrinologists and American College of Endocrinology guidelines for management of dyslipidemia and prevention of cardiovascular disease. Endocr Pract. 2017;23(Suppl 2):1-87. doi:10.4158/ep171764.Appgl
  21. Wilson PWF, Jacobson TA, Martin SS, et al. Lipid measurements in the management of cardiovascular diseases: practical recommendations a scientific statement from the National Lipid Association writing group. J Clin Lipidol. 2021;15(5):629-648. doi:10.1016/j.jacl.2021.09.046
  22. Soffer DE, Marston NA, Maki KC, et al. Role of apolipoprotein B in the clinical management of cardiovascular risk in adults: an expert clinical consensus from the National Lipid Association. J Clin Lipidol. 2024;18(5):e647-e663. doi:10.1016/j.jacl.2024.08.013
  23. Handelsman Y, Jellinger PS, Guerin CK, et al. Consensus statement by the American Association of Clinical Endocrinologists and American College of Endocrinology on the management of dyslipidemia and prevention of cardiovascular disease algorithm—2020 executive summary. Endocr Pract. 2020;26(10):1196-1224. doi:10.4158/CS-2020-0490
  24. Louie JZ, Shiffman D, McPhaul MJ, et al. Insulin resistance probability score and incident cardiovascular disease. J Intern Med. 2023;294(4):531-535. doi:10.1111/joim.13687
  25. Meigs JB, Porneala B, Leong A, et al. Simultaneous consideration of HbA1c and insulin resistance improves risk assessment in white individuals at increased risk for future type 2 diabetes. Diabetes Care. 2020;43(8):e90-e92. doi:10.2337/dc20-0718
     

Content reviewed 10/2025

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Reference ranges are provided as general guidance only. To interpret test results use the reference range in the laboratory report.

The tests listed by specialty and category are a select group of tests offered. For a complete list of Quest Diagnostics tests, please adjust the filter options chosen, or refer to our Directory of Services.