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Association between various insulin resistance indices and cardiovascular disease in middle-aged and elderly individuals: evidence from two prospectives nationwide cohort surveys.
The estimated glucose disposal rate (eGDR), triglyceride glucose (TyG), triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) ratio, and metabolic score for insulin resistance (METS-IR) are dependent indicators of insulin resistance (IR). We aimed to evaluate the association between these indicators and the current or feature incidence of cardiovascular disease (CVD) in middle-aged and elderly individuals. This study tests the hypothesis that IR indices positively or negatively correlate with CVD, and that the potential predictive performance of the IR indices was not the same.
Middle-aged and elderly individuals from the National Health and Nutrition Examination Survey (NHANES) and the China Health and Retirement Longitudinal Study (CHARLS) with complete data on eGDR, TyG, TG/HDL-C, and METS-IR at baseline were obtained. The association between the four indices and CVD was evaluated using multivariate logistic regression analysis. In addition, an adjusted restricted cubic spline (RCS) was applied. Finally, the potential predictive performance of the IR indices was assessed using receiver operating characteristic (ROC) curves.
We included 7,220 participants (mean age: 61.9 ± 10.7 years; 54.0% male) from the NHANES cohort and 6,426 participants (mean age: 57.9 ± 8.4 years; 45.2% male) from the CHARLS cohort in the study. Multivariate logistic regression analysis indicated that a decreasing eGDR significantly increased the incidence of CVD both presently and in the future. Similarly, a higher TyG level and METS-IR were significantly associated with a higher incidence of CVD at both timeframes. However, the TG/HDL-C ratio was not significantly associated with CVD, heart disease, or stroke. No significant interactions were observed between the continuous or quartile variables of eGDR, TyG, TG/HDL-C, or METS-IR, and the incidence of various endpoints across most subgroups. The ROC curve indicated the superior predictive performance of the IR indices. Furthermore, the eGDR was superior to other IR indices for the prediction of CVD both at present and in the future in middle-aged and elderly individuals.
As continuous variables, eGDR, TyG, and METS-IR were significantly associated with the incidence of CVD, both currently and in the future, among middle-aged and elderly individuals. Notably, incorporating eGDR, TyG, or METS-IR and the basic model significantly increased the predictive value for CVD. Among these indices, the eGDR index stands out as the most promising parameter for predicting CVD, both at present and in the future.
Li Y
,Li H
,Chen X
,Liang X
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《Frontiers in Endocrinology》
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Longitudinal analysis of insulin resistance and sarcopenic obesity in Chinese middle-aged and older adults: evidence from CHARLS.
The correlation between surrogate insulin resistance (IR) indices and sarcopenic obesity (SO) remains uncertain. This study aimed to assess the association between six IR surrogates-triglyceride-glucose (TyG), TyG-waist circumference (TyG-WC), TyG-waist-to-height ratio (TyG-WHtR), triglyceride-to-high-density lipoprotein-cholesterol ratio (TG/HDL), metabolic score for insulin resistance (METS-IR), and Chinese visceral adiposity index (CVAI)-and SO risk in a middle-aged and older population in China.
The study employed longitudinal data obtained from the China Health and Retirement Longitudinal Study (CHARLS) between 2011 and 2015, involving 6,395 participants. We used multivariate logistic regression models to examine the link between six surrogates and SO. Nonlinear relationships were evaluated using restricted cubic spline analysis, and subgroup analyses were conducted for validation. Receiver operating characteristic (ROC) curves were used to assess predictive capabilities.
Over the course of a 4-year follow-up period, 319 participants (5.0%) developed SO. In the fully adjusted model, all six surrogates were significantly associated with SO. The adjusted odds ratios (ORs) with a 95% confidence interval (95% CI) per standard deviation increase were 1.21 (1.08-1.36) for TyG, 1.56 (1.39-1.75) for TyG-WC, 2.04 (1.81-2.31) for TyG-WHtR, 1.11 (1.01-1.21) for TG/HDL, 1.67 (1.50-1.87) for METS-IR, and 1.74 (1.55-1.97) for CVAI. Notably, TyG-WC, TyG-WHtR, TG/HDL, METS-IR, and CVAI exhibited nonlinear correlations with SO. Conversely, TG/HDL did not exhibit a significant association during subgroup analysis. Furthermore, TyG-WHtR had a significantly larger area under the receiver operating characteristic curve than other indices.
The results indicated that TyG, TyG-WC, TyG-WHtR, METS-IR, and CVAI were significantly and positively associated with SO incidence. Meanwhile, TyG-WC, TyG-WHtR, METS-IR, and CVAI showed nonlinear relationships with SO. Specifically, TyG-WHtR may be the most appropriate indicator for predicting SO among middle-aged and older Chinese adults.
Xu C
,He L
,Tu Y
,Guo C
,Lai H
,Liao C
,Lin C
,Tu H
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《Frontiers in Public Health》
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Comparison of Two Modern Survival Prediction Tools, SORG-MLA and METSSS, in Patients With Symptomatic Long-bone Metastases Who Underwent Local Treatment With Surgery Followed by Radiotherapy and With Radiotherapy Alone.
Survival estimation for patients with symptomatic skeletal metastases ideally should be made before a type of local treatment has already been determined. Currently available survival prediction tools, however, were generated using data from patients treated either operatively or with local radiation alone, raising concerns about whether they would generalize well to all patients presenting for assessment. The Skeletal Oncology Research Group machine-learning algorithm (SORG-MLA), trained with institution-based data of surgically treated patients, and the Metastases location, Elderly, Tumor primary, Sex, Sickness/comorbidity, and Site of radiotherapy model (METSSS), trained with registry-based data of patients treated with radiotherapy alone, are two of the most recently developed survival prediction models, but they have not been tested on patients whose local treatment strategy is not yet decided.
(1) Which of these two survival prediction models performed better in a mixed cohort made up both of patients who received local treatment with surgery followed by radiotherapy and who had radiation alone for symptomatic bone metastases? (2) Which model performed better among patients whose local treatment consisted of only palliative radiotherapy? (3) Are laboratory values used by SORG-MLA, which are not included in METSSS, independently associated with survival after controlling for predictions made by METSSS?
Between 2010 and 2018, we provided local treatment for 2113 adult patients with skeletal metastases in the extremities at an urban tertiary referral academic medical center using one of two strategies: (1) surgery followed by postoperative radiotherapy or (2) palliative radiotherapy alone. Every patient's survivorship status was ascertained either by their medical records or the national death registry from the Taiwanese National Health Insurance Administration. After applying a priori designated exclusion criteria, 91% (1920) were analyzed here. Among them, 48% (920) of the patients were female, and the median (IQR) age was 62 years (53 to 70 years). Lung was the most common primary tumor site (41% [782]), and 59% (1128) of patients had other skeletal metastases in addition to the treated lesion(s). In general, the indications for surgery were the presence of a complete pathologic fracture or an impending pathologic fracture, defined as having a Mirels score of ≥ 9, in patients with an American Society of Anesthesiologists (ASA) classification of less than or equal to IV and who were considered fit for surgery. The indications for radiotherapy were relief of pain, local tumor control, prevention of skeletal-related events, and any combination of the above. In all, 84% (1610) of the patients received palliative radiotherapy alone as local treatment for the target lesion(s), and 16% (310) underwent surgery followed by postoperative radiotherapy. Neither METSSS nor SORG-MLA was used at the point of care to aid clinical decision-making during the treatment period. Survival was retrospectively estimated by these two models to test their potential for providing survival probabilities. We first compared SORG to METSSS in the entire population. Then, we repeated the comparison in patients who received local treatment with palliative radiation alone. We assessed model performance by area under the receiver operating characteristic curve (AUROC), calibration analysis, Brier score, and decision curve analysis (DCA). The AUROC measures discrimination, which is the ability to distinguish patients with the event of interest (such as death at a particular time point) from those without. AUROC typically ranges from 0.5 to 1.0, with 0.5 indicating random guessing and 1.0 a perfect prediction, and in general, an AUROC of ≥ 0.7 indicates adequate discrimination for clinical use. Calibration refers to the agreement between the predicted outcomes (in this case, survival probabilities) and the actual outcomes, with a perfect calibration curve having an intercept of 0 and a slope of 1. A positive intercept indicates that the actual survival is generally underestimated by the prediction model, and a negative intercept suggests the opposite (overestimation). When comparing models, an intercept closer to 0 typically indicates better calibration. Calibration can also be summarized as log(O:E), the logarithm scale of the ratio of observed (O) to expected (E) survivors. A log(O:E) > 0 signals an underestimation (the observed survival is greater than the predicted survival); and a log(O:E) < 0 indicates the opposite (the observed survival is lower than the predicted survival). A model with a log(O:E) closer to 0 is generally considered better calibrated. The Brier score is the mean squared difference between the model predictions and the observed outcomes, and it ranges from 0 (best prediction) to 1 (worst prediction). The Brier score captures both discrimination and calibration, and it is considered a measure of overall model performance. In Brier score analysis, the "null model" assigns a predicted probability equal to the prevalence of the outcome and represents a model that adds no new information. A prediction model should achieve a Brier score at least lower than the null-model Brier score to be considered as useful. The DCA was developed as a method to determine whether using a model to inform treatment decisions would do more good than harm. It plots the net benefit of making decisions based on the model's predictions across all possible risk thresholds (or cost-to-benefit ratios) in relation to the two default strategies of treating all or no patients. The care provider can decide on an acceptable risk threshold for the proposed treatment in an individual and assess the corresponding net benefit to determine whether consulting with the model is superior to adopting the default strategies. Finally, we examined whether laboratory data, which were not included in the METSSS model, would have been independently associated with survival after controlling for the METSSS model's predictions by using the multivariable logistic and Cox proportional hazards regression analyses.
Between the two models, only SORG-MLA achieved adequate discrimination (an AUROC of > 0.7) in the entire cohort (of patients treated operatively or with radiation alone) and in the subgroup of patients treated with palliative radiotherapy alone. SORG-MLA outperformed METSSS by a wide margin on discrimination, calibration, and Brier score analyses in not only the entire cohort but also the subgroup of patients whose local treatment consisted of radiotherapy alone. In both the entire cohort and the subgroup, DCA demonstrated that SORG-MLA provided more net benefit compared with the two default strategies (of treating all or no patients) and compared with METSSS when risk thresholds ranged from 0.2 to 0.9 at both 90 days and 1 year, indicating that using SORG-MLA as a decision-making aid was beneficial when a patient's individualized risk threshold for opting for treatment was 0.2 to 0.9. Higher albumin, lower alkaline phosphatase, lower calcium, higher hemoglobin, lower international normalized ratio, higher lymphocytes, lower neutrophils, lower neutrophil-to-lymphocyte ratio, lower platelet-to-lymphocyte ratio, higher sodium, and lower white blood cells were independently associated with better 1-year and overall survival after adjusting for the predictions made by METSSS.
Based on these discoveries, clinicians might choose to consult SORG-MLA instead of METSSS for survival estimation in patients with long-bone metastases presenting for evaluation of local treatment. Basing a treatment decision on the predictions of SORG-MLA could be beneficial when a patient's individualized risk threshold for opting to undergo a particular treatment strategy ranged from 0.2 to 0.9. Future studies might investigate relevant laboratory items when constructing or refining a survival estimation model because these data demonstrated prognostic value independent of the predictions of the METSSS model, and future studies might also seek to keep these models up to date using data from diverse, contemporary patients undergoing both modern operative and nonoperative treatments.
Level III, diagnostic study.
Lee CC
,Chen CW
,Yen HK
,Lin YP
,Lai CY
,Wang JL
,Groot OQ
,Janssen SJ
,Schwab JH
,Hsu FM
,Lin WH
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Association between the triglyceride to high-density lipoprotein cholesterol ratio and cardiovascular diseases in people living with human immunodeficiency virus: Evidence from a retrospectively cohort study 2005-2022.
The triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) ratio, a novel biomarker for metabolic syndrome (MetS), has been validated in the general population as being significantly correlated with cardiovascular disease (CVD) risk. However, its capabilities to predict CVD in people living with human immunodeficiency virus (HIV; PLWH) remain underexplored.
We conducted a retrospective cohort study of 16,081 PLWH who initiated antiretroviral therapy (ART) at the Third People's Hospital of Shenzhen (China) from 2005 to 2022. The baseline TG/HDL-C ratio was calculated as TG (mmol/L) divided by HDL-C (mmol/L). We employed a multivariate Cox proportional hazards model to assess the association between the TG/HDL-C ratio and CVD occurrence, using Kaplan-Meier curves and log-rank tests to compare survival distributions. The increase in prediction risk upon the addition of the biomarker to the conventional risk model was examined through the assessment of changes in net reclassification improvement (NRI) and integrated discrimination improvement (IDI). Nonlinear relationships were investigated using a restricted cubic spline plot, complemented by a two-piecewise Cox proportional hazards model to analyze threshold effects.
At the median follow-up of 70 months, 213 PLWH developed CVD. Kaplan-Meier curves demonstrated a significant association between the increased risk of CVD and a higher TG/HDL-C ratio (log-rank P <0.001). The multivariate-adjusted Cox proportional hazards regression model indicated that the CVD hazard ratios (HR) (95% confidence intervals [95% CIs]) for Q2, Q3, and Q4 versus Q1 of the TG/HDL-C ratio were 2.07 (1.24, 3.45), 2.17 (1.32, 3.57), and 2.20 (1.35, 3.58), respectively ( P <0.05). The consideration of the TG/HDL-C ratio in the model, which included all significant factors for CVD incidence, improved the predictive risk, as indicated by the reclassification metrics (NRI 16.43%, 95% CI 3.35%-29.52%, P = 0.014). The restriction cubic spline plot demonstrated an upward trend between the TG/HDL-C ratio and the CVD occurrence ( P for non-linear association = 0.027, P for overall significance = 0.009), with the threshold at 1.013. Significantly positive correlations between the TG/HDL-C ratio and CVD were observed below the TG/HDL-C ratio threshold with HR 5.88 (95% CI 1.58-21.88, P = 0.008), but not above the threshold with HR 1.01 (95% CI 0.88-1.15, P = 0.880).
Our study confirms the effectiveness of the TG/HDL-C ratio as a predictor of CVD risk in PLWH, which demonstrates a significant nonlinear association. These findings indicate the potential of the TG/HDL-C ratio in facilitating early prevention and treatment strategies for CVD among PLWH.
Sun L
,Luo Y
,Jia X
,Wang H
,Zhao F
,Zhang L
,Ju B
,Wang H
,Shan D
,He Y
,Lu H
,Liu J
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Relationship between four insulin resistance surrogates and regression to normoglycemia from prediabetes among Chinese adults: A longitudinal Cohort Study.
We aimed to investigate the association of the triglyceride glucose-body mass index(TyG-BMI), metabolic score for insulin resistance (METS-IR) with regression to normoglycaemia, and further to compare the value of the four insulin resistance(IR) related indices(TyG-BMI, METS-IR, TyG and triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) ratio) in identifying regressions to normoglycaemia from prediabetes.
A total of 15,025 patients with prediabetes from the DATA-DRYAD database were included. Cox proportional hazards regression models and restricted cubic spline functions were performed to explore the association and nonlinearity between the indices with the incidence rate of normoglycaemia. Sensitivity and subgroup analyses evaluated the robustness of our findings.
Compared with the first quintile, TyG-BMI and METS-IR was negatively linked with the probability of regression to normoglycaemia from prediabetes, the adjusted effect size of the highest quintiles of METS-IR were the most obvious (HR:0.456,95% CI:0.4-0.519), followed by TG/HDL (HR:0.792, 95% CI:0.733-0.856), TyG-BMI (HR:0.816, 95% CI:0.73-0.911) and TyG (HR:0.841, 95% CI: 0.754-0.937) (all p for trend <0.001). A 1.0 SD increase in METS-IR induced a 43% decrease in the probability of regression to normoglycaemia, with 9.8% for TyG-BMI. There were nonlinear associations between TyG-BMI and METS-IR and outcomes, with the inflection point of the TyG-BMI being 218.2 and that of the METS-IR being 37.
The METS-IR might be the most superior indicator among the four non-insulin indices in identifying regressions to normoglycaemia from prediabetes in clinical application. The inflection points of the METS-IR and TyG-BMI may be instructive therapeutic points for assessing the status of prediabetes in advance and making more appropriate management and health care decisions.
Yang L
,Feng Y
,Wang Y
,Liu C
,Gao D
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