Abstract

Background and Aims

Insulin resistance determination in kidney transplant recipients (KTRs) plays an important role to identify KTRs at risk of posttransplantation diabetes mellitus (PTDM) development. Current methods to measure insulin resistance include the hyperinsulinemic-euglycemic (HIEG) clamp technique, and minimal model approximation of the metabolism of glucose (MMAMG). These methods, however, require considerable time and are expense, complex, and invasive. As a result, indirect insulin resistance indices such as homeostasis model assessment-insulin resistance (HOMA-IR), visceral adiposity index (VAI), lipid accumulation product (LAP), or triglycerides-glucose (TyG) index, are used in epidemiological and clinical studies in the general population due to their simplicity and ease of use. However, it is unknown to what extent those indices may contribute to determine insulin resistance and PTDM development in KTRs. Therefore, this study aimed to investigate the role of indirect insulin resistance indices to determine insulin resistance and PTDM development in KTRs.

Method

We included 472 stable outpatient KTRs (with a functioning graft ≥1 year) without diabetes from a prospective cohort study. Crude and multivariable Cox proportional hazards regression analysis were performed to determine whether indirect insulin resistance indices (HOMA-IR, VAI, LAP, and TyG index) were prospectively associated with incident PTDM. We analyzed each measure using receiver operating characteristic (ROC) curve for the development of PTDM. The cut-off value was determined as the value with the highest Youden index score in the specificity dominant area.

Results

During a median 9.6 years [interquartile range (IQR) 6.6–10.2] of follow up, 68 (14%) KTRs developed PTDM. In Cox regression analyses, all indirect insulin resistance indices associated with incident PTDM, independent of potential confounders. ROC curve was 0.764 (95% CI,0.703-0.826) for HOMA-IR, 0.685 (95% CI,0.615-0.757) for VAI, 0.743 (95% CI,0.678-0.808) for LAP, and 0.698 (95% CI,0.629-0.766) for TyG index, with no significant difference between them (p = 0.05). The cut-off values with their corresponding sensitivity and specificity for each indices are presented in Table 1. To test this cut-off value, the association between the indices and incident PTDM was examined by using each index as a categorical variable (HOMA-IR<2.47 vs ≥2.47; VAI<4.01 vs ≥4.01; LAP<87.04 vs ≥87.04; TyG index<4.94 vs ≥4.94). Indirect insulin resistance indices as a categorical variable predicted incident PTDM independent of age, sex, smoking, time to transplantation, systolic blood pressure, eGFR, and medication.

Conclusion

Indirect insulin resistance indices could be used to predict incident PTDM in KTRs. In addition to HOMA-IR, insulin-free surrogates of insulin resistance might serve as useful methods to identify KTRs at risk for PTDM development.

Table 1:

AUC and cut-off values indirect insulin resistance indices with their corresponding sensitivity, specificity, and hazard ratio (HR).

Insulin resistance indexAUC(95% CI)Cut-off valueSensitivitySpecificityHR (95% CI) per SD-increase
HOMA-IR0.764 (0.703-0.826)2.4775.071.36.42 (3.67-11.25)
VAI0.685 (0.615-0.757)4.0161.872.84.10 (2.48-6.77)
LAP0.743 (0.678-0.808)87.0464.775.25.82 (3.46-9.80)
TyG index0.698 (0.629-0.766)4.9451.583.95.73 (3.45-9.52)
Insulin resistance indexAUC(95% CI)Cut-off valueSensitivitySpecificityHR (95% CI) per SD-increase
HOMA-IR0.764 (0.703-0.826)2.4775.071.36.42 (3.67-11.25)
VAI0.685 (0.615-0.757)4.0161.872.84.10 (2.48-6.77)
LAP0.743 (0.678-0.808)87.0464.775.25.82 (3.46-9.80)
TyG index0.698 (0.629-0.766)4.9451.583.95.73 (3.45-9.52)

HRs (95% CIs) were derived from Cox proportional hazard model adjusted for age, sex, smoking, time since transplantation, SBP, eGFR, medication use (prednisolone dosage, calcineurin inhibitors, proliferation inhibitor).

AUC: area under the curve; HOMA-IR: homeostasis model assessment-insulin resistance; VAI: visceral adiposity index; LAP: lipid accumulation product; TyG index; triglycerides-glucose index; HR: hazard ratio; SBP: systolic blood pressure

Table 1:

AUC and cut-off values indirect insulin resistance indices with their corresponding sensitivity, specificity, and hazard ratio (HR).

Insulin resistance indexAUC(95% CI)Cut-off valueSensitivitySpecificityHR (95% CI) per SD-increase
HOMA-IR0.764 (0.703-0.826)2.4775.071.36.42 (3.67-11.25)
VAI0.685 (0.615-0.757)4.0161.872.84.10 (2.48-6.77)
LAP0.743 (0.678-0.808)87.0464.775.25.82 (3.46-9.80)
TyG index0.698 (0.629-0.766)4.9451.583.95.73 (3.45-9.52)
Insulin resistance indexAUC(95% CI)Cut-off valueSensitivitySpecificityHR (95% CI) per SD-increase
HOMA-IR0.764 (0.703-0.826)2.4775.071.36.42 (3.67-11.25)
VAI0.685 (0.615-0.757)4.0161.872.84.10 (2.48-6.77)
LAP0.743 (0.678-0.808)87.0464.775.25.82 (3.46-9.80)
TyG index0.698 (0.629-0.766)4.9451.583.95.73 (3.45-9.52)

HRs (95% CIs) were derived from Cox proportional hazard model adjusted for age, sex, smoking, time since transplantation, SBP, eGFR, medication use (prednisolone dosage, calcineurin inhibitors, proliferation inhibitor).

AUC: area under the curve; HOMA-IR: homeostasis model assessment-insulin resistance; VAI: visceral adiposity index; LAP: lipid accumulation product; TyG index; triglycerides-glucose index; HR: hazard ratio; SBP: systolic blood pressure

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