Rationale, Design, and Baseline Characteristics of Beijing Prediabetes Reversion Program: A Randomized Controlled Clinical Trial to Evaluate the Efficacy of Lifestyle Intervention and/or Pioglitazone in Reversion to Normal Glucose Tolerance in Prediabetes

Differential effect of interventions in patients with prediabetes stratified by a machine learning-based diabetes progression prediction model

AIM

To investigate whether stratifying participants with prediabetes according to their diabetes progression risks (PR) could affect their responses to interventions.

METHODS

We developed a machine learning-based model to predict the 1-year diabetes PR (ML-PR) with the least predictors. The model was developed and internally validated in participants with prediabetes in the Pinggu Study (a prospective population-based survey in suburban Beijing; n = 622). Patients from the Beijing Prediabetes Reversion Program cohort (a multicentre randomized control trial to evaluate the efficacy of lifestyle and/or pioglitazone on prediabetes reversion; n = 1936) were stratified to low-, medium- and high-risk groups using ML-PR. Different effect of four interventions within subgroups on prediabetes reversal and diabetes progression was assessed.

RESULTS

Using least predictors including fasting plasma glucose, 2-h postprandial glucose after 75 g glucose administration, glycated haemoglobin, high-density lipoprotein cholesterol and triglycerides, and the ML algorithm XGBoost, ML-PR successfully predicted the 1-year progression of participants with prediabetes in the Pinggu study [internal area under the curve of the receiver operating characteristic curve 0.80 (0.72-0.89)] and Beijing Prediabetes Reversion Program [external area under the curve of the receiver operating characteristic curve 0.80 (0.74-0.86)]. In the high-risk group pioglitazone plus intensive lifestyle therapy significantly reduced diabetes progression by about 50% at year l and the end of the trial in the high-risk group compared with conventional lifestyle therapy with placebo. In the medium- or low-risk group, intensified lifestyle therapy, pioglitazone or their combination did not show any benefit on diabetes progression and prediabetes reversion.

CONCLUSIONS

This study suggests personalized treatment for prediabetes according to their PR is necessary. ML-PR model with simple clinical variables may facilitate personal treatment strategies in participants with prediabetes.

Predictive performance of triglyceride glucose index (TyG index) to identify glucose status conversion: a 5-year longitudinal cohort study in Chinese pre-diabetes people

OBJECTIVE

Triglyceride glucose index (TyG index) has been recommended as an alternative indicator of insulin resistance. However, the association between TyG and regression from prediabetes to normoglycemia remains to be elucidated.

METHODS

This retrospective cohort study involved 25,248 subjects with prediabetes at baseline conducted from 2010 to 2016. A Cox proportional hazard regression model was designed to evaluate the role of TyG in identifying people at converting from prediabetes to normoglycemia. Cox proportional hazards regression with cubic spline functions and smooth curve fitting was used to dig out the nonlinear relationship between them. Detailed evaluations for TyG were also performed using sensitivity and subgroup analyse.

RESULTS

Among the included prediabetes subjects (n = 25,248), the mean age was 49.27 ± 13.84 years old, and 16,701 (66.15%) were male. The mean TyG was 8.83 ± 0.60. The median follow-up time was 2.96 ± 0.90 years. 11,499 (45.54%) individuals had a final diagnosis of normoglycemia. After adjusting for covariates, TyG was negatively affecting the results of glucose status conversion in prediabetes people (HR 0.895, 95% CI 0.863, 0.928). There was a nonlinear connection between TyG and normoglycemia in prediabetes people, and the inflection point was 8.88. The effect sizes (HR) on the left and right sides of the inflection point were 0.99 (0.93, 1.05) and 0.79 (0.74, 0.85), respectively. Sensitivity analysis confirmed the robustness of these results. Subgroup analysis showed that TyG was more strongly associated with incident glucose status conversion in male, BMI ≥ 25. In contrast, there was a weaker relationship in those with female, BMI < 25.

CONCLUSION

Based on sample of subjects evaluated between 2010 and 2016, TyG index appears to be a promising marker for predicting normoglycemic conversion among prediabetes people in China. This study demonstrates a negative and non-linear association between TyG and glucose status conversion from prediabetes to normoglycemia. TyG is strongly related to glucose status conversion when TyG is above 8.88. From a therapeutic point of view, it is meaningful to maintain TyG levels within the inflection point to 8.88.

Short Mediterranean diet screener detects risk of prediabetes in Taiwan, a cross-sectional study

We aimed to determine whether the 14-item Mediterranean diet adherence screener (MEDAS) is suitable in Taiwan and associate the MEDAS score with the risk of prediabetes. In this cross-sectional study 346 patients were recruited between 2014 and 2019 at Taipei Tzu Chi Hospital. The MEDAS score was obtained with a 14-item MEDAS used in the PREDIMED trial. The blood glucose level is measured by fasting glucose and HbA1c. The results of the screener were analyzed for internal consistency and compared with the blood glucose level using multivariate regression models. The MEDAS score was significantly (p = 0.001) and inversely associated with both measures of blood glucose level. Adjusted data (95% CI) showed that each additional point in the MEDAS score decreases the risk of prediabetes with abnormal fasting glucose (> 100 mg/dL) level by 60% and the risk of prediabetes with abnormal HbA1c (> 5.7%) by 22.4%. Consuming at least 3 servings of legumes each week was significantly (p = 0.007) related to a lower risk of prediabetes under logistic regression. A higher score on the 14-item MEDAS screener was significantly associated with a lower risk of prediabetes.

Baseline characteristics of participants in the Pre-Diabetes Interventions and Continued Tracking to Ease-out Diabetes (Pre-DICTED) Program

OBJECTIVE

The Pre-Diabetes Interventions and Continued Tracking to Ease-out Diabetes (Pre-DICTED) Program is a diabetes prevention trial comparing the diabetes conversion rate at 3 years between the intervention group, which receives the incentivized lifestyle intervention program with stepwise addition of metformin, and the control group, which receives the standard of care. We describe the baseline characteristics and compare Pre-DICTED participants with other diabetes prevention trials cohort.

RESEARCH DESIGN AND METHODS

Participants were aged between 21 and 64 years, overweight (body mass index (BMI) ≥23.0 kg/m²), and had pre-diabetes (impaired fasting glucose (IFG) and/or impaired glucose tolerance (IGT)).

RESULTS

A total of 751 participants (53.1% women) were randomized. At baseline, mean (SD) age was 52.5 (8.5) years and mean BMI (SD) was 29.0 (4.6) kg/m². Twenty-three per cent had both IFG and IGT, 63.9% had isolated IGT, and 13.3% had isolated IFG. Ethnic Asian Indian participants were more likely to report a family history of diabetes and had a higher waist circumference, compared with Chinese and Malay participants. Women were less likely than men to meet the physical activity recommendations (≥150 min of moderate-intensity physical activity per week), and dietary intake varied with both sex and ethnicity. Compared with other Asian diabetes prevention studies, the Pre-DICTED cohort had a higher mean age and BMI.

CONCLUSION

The Pre-DICTED cohort represents subjects at high risk of diabetes conversion. The study will evaluate the effectiveness of a community-based incentivized lifestyle intervention program in an urban Asian context.

A Randomized Controlled Clinical Trial of Lifestyle Intervention and Pioglitazone for Normalization of Glucose Status in Chinese with Prediabetes

AIMS

Prediabetes has been proved as an important risk factor of both diabetes and cardiovascular disease (CVD). Previous studies have shown that both lifestyle intervention and pioglitazone may delay the development of diabetes in patients with prediabetes. However, no study has ever explored whether these interventions could revert prediabetes to normal glycemic status as the primary outcome. Interventions that may revert prediabetes back to normal glucose status would be of great clinical importance.

MATERIALS AND METHODS

We conducted a randomized, multicenter, 2 × 2 factorial designed study to examine whether intensive lifestyle intervention and/or pioglitazone could revert prediabetes to normal glucose tolerance. The participants were followed up for three years unless they reverted to normal glucose state or developed diabetes at the annual oral glucose tolerance test (OGTT). Reversion to normal glucose tolerance was confirmed on the basis of the results of OGTT.

RESULTS

In our study, 1945 eligible patients were ultimately randomized into four groups. In this three-year follow-up study, overall, 60.0%, 50.3%, 56.6% and 65.1% reverted back to normoglycemic state over 3 years of follow-up in the conventional lifestyle intervention plus placebo, intensive lifestyle intervention plus placebo, conventional lifestyle intervention plus pioglitazone, and intensive lifestyle intervention plus pioglitazone groups, respectively. Compared to the conventional lifestyle intervention plus placebo group, all the other three groups did not show any significant benefit in terms of reverting back to normoglycemic state.

CONCLUSION

In our study, for patients with prediabetes, neither intensive lifestyle intervention nor pioglitazone had led to a higher reversion rate to normal glucose state. Trail registration.http://www.chictr.org.cn: ChiCTR-PRC-06000005.

Pioglitazone for prevention or delay of type 2 diabetes mellitus and its associated complications in people at risk for the development of type 2 diabetes mellitus

BACKGROUND

The term prediabetes is used to describe a population with an elevated risk of developing type 2 diabetes mellitus (T2DM). With projections of an increase in the incidence of T2DM, prevention or delay of the disease and its complications is paramount. It is currently unknown whether pioglitazone is beneficial in the treatment of people with increased risk of developing T2DM.

OBJECTIVES

To assess the effects of pioglitazone for prevention or delay of T2DM and its associated complications in people at risk of developing T2DM.

SEARCH METHODS

We searched CENTRAL, MEDLINE, Chinese databases, ICTRP Search Portal and ClinicalTrials.gov. We did not apply any language restrictions. Further, we investigated the reference lists of all included studies and reviews. We tried to contact all study authors. The date of the last search of databases was November 2019 (March 2020 for Chinese databases).

SELECTION CRITERIA

We included randomised controlled trials (RCTs) with a minimum duration of 24 weeks, and participants diagnosed with intermediate hyperglycaemia with no concomitant diseases, comparing pioglitazone as monotherapy or part of dual therapy with other glucose-lowering drugs, behaviour-changing interventions, placebo or no intervention.

DATA COLLECTION AND ANALYSIS

Two review authors independently screened abstracts, read full-text articles and records, assessed risk of bias and extracted data. We performed meta-analyses with a random-effects model and calculated risk ratios (RRs) for dichotomous outcomes and mean differences (MDs) for continuous outcomes, with 95% confidence intervals (CIs) for effect estimates. We evaluated the certainty of the evidence with the GRADE.

MAIN RESULTS

We included 27 studies with a total of 4186 randomised participants. The size of individual studies ranged between 43 and 605 participants and the duration varied between 6 and 36 months. We judged none of the included studies as having low risk of bias across all 'Risk of bias' domains. Most studies identified people at increased risk of T2DM by impaired fasting glucose or impaired glucose tolerance (IGT), or both. Our main outcome measures were all-cause mortality, incidence of T2DM, serious adverse events (SAEs), cardiovascular mortality, nonfatal myocardial infarction or stroke (NMI/S), health-related quality of life (QoL) and socioeconomic effects. The following comparisons mostly reported only a fraction of our main outcome set. Three studies compared pioglitazone with metformin. They did not report all-cause and cardiovascular mortality, NMI/S, QoL or socioeconomic effects. Incidence of T2DM was 9/168 participants in the pioglitazone groups versus 9/163 participants in the metformin groups (RR 0.98, 95% CI 0.40 to 2.38; P = 0.96; 3 studies, 331 participants; low-certainty evidence). No SAEs were reported in two studies (201 participants; low-certainty evidence). One study compared pioglitazone with acarbose. Incidence of T2DM was 1/50 participants in the pioglitazone group versus 2/46 participants in the acarbose group (very low-certainty evidence). No participant experienced a SAE (very low-certainty evidence).One study compared pioglitazone with repaglinide. Incidence of T2DM was 2/48 participants in the pioglitazone group versus 1/48 participants in the repaglinide group (low-certainty evidence). No participant experienced a SAE (low-certainty evidence). One study compared pioglitazone with a personalised diet and exercise consultation. All-cause and cardiovascular mortality, NMI/S, QoL or socioeconomic effects were not reported. Incidence of T2DM was 2/48 participants in the pioglitazone group versus 5/48 participants in the diet and exercise consultation group (low-certainty evidence). No participant experienced a SAE (low-certainty evidence). Six studies compared pioglitazone with placebo. No study reported on QoL or socioeconomic effects. All-cause mortality was 5/577 participants the in the pioglitazone groups versus 2/579 participants in the placebo groups (Peto odds ratio 2.38, 95% CI 0.54 to 10.50; P = 0.25; 4 studies, 1156 participants; very low-certainty evidence). Incidence of T2DM was 80/700 participants in the pioglitazone groups versus 131/695 participants in the placebo groups (RR 0.40, 95% CI 0.17 to 0.95; P = 0.04; 6 studies, 1395 participants; low-certainty evidence). There were 3/93 participants with SAEs in the pioglitazone groups versus 1/94 participants in the placebo groups (RR 3.00, 95% CI 0.32 to 28.22; P = 0.34; 2 studies, 187 participants; very low-certainty evidence). However, the largest study for this comparison did not distinguish between serious and non-serious adverse events. This study reported that 121/303 (39.9%) participants in the pioglitazone group versus 151/299 (50.5%) participants in the placebo group experienced an adverse event (P = 0.03). One study observed cardiovascular mortality in 2/181 participants in the pioglitazone group versus 0/186 participants in the placebo group (RR 5.14, 95% CI 0.25 to 106.28; P = 0.29; very low-certainty evidence). One study observed NMI in 2/303 participants in the pioglitazone group versus 1/299 participants in the placebo group (RR 1.97: 95% CI 0.18 to 21.65; P = 0.58; very low-certainty evidence). Twenty-one studies compared pioglitazone with no intervention. No study reported on cardiovascular mortality, NMI/S, QoL or socioeconomic effects. All-cause mortality was 11/441 participants in the pioglitazone groups versus 12/425 participants in the no-intervention groups (RR 0.85, 95% CI 0.38 to 1.91; P = 0.70; 3 studies, 866 participants; very low-certainty evidence). Incidence of T2DM was 60/1034 participants in the pioglitazone groups versus 197/1019 participants in the no-intervention groups (RR 0.31, 95% CI 0.23 to 0.40; P < 0.001; 16 studies, 2053 participants; moderate-certainty evidence). Studies reported SAEs in 16/610 participants in the pioglitazone groups versus 21/601 participants in the no-intervention groups (RR 0.71, 95% CI 0.38 to 1.32; P = 0.28; 7 studies, 1211 participants; low-certainty evidence). We identified two ongoing studies, comparing pioglitazone with placebo and with other glucose-lowering drugs. These studies, with 2694 participants. may contribute evidence to future updates of this review.

AUTHORS' CONCLUSIONS

Pioglitazone reduced or delayed the development of T2DM in people at increased risk of T2DM compared with placebo (low-certainty evidence) and compared with no intervention (moderate-certainty evidence). It is unclear whether the effect of pioglitazone is sustained once discontinued. Pioglitazone compared with metformin neither showed advantage nor disadvantage regarding the development of T2DM in people at increased risk (low-certainty evidence). The data and reporting of all-cause mortality, SAEs, micro- and macrovascular complications were generally sparse. None of the included studies reported on QoL or socioeconomic effects.

A P4 Medicine Perspective of Gut Microbiota and Prediabetes: Systems Analysis and Personalized Intervention

Type 2 diabetes (T2D) accounts for approximately 90% of diabetes worldwide and has become a global public health problem. Generally, individuals go to hospitals and get healthcare only when they have obvious T2D symptoms. While the underlying cause and mechanism of the disease are usually not well understood, treatment is for the symptoms, but not for the disease cause, and patients often continue to progress with more symptoms. Prediabetes is the early stage of diabetes and provides a good time window for intervention and prevention. However, with few symptoms, prediabetes is usually ignored without any treatment. Obviously, it is far from ideal to rely on the traditional medical system for diabetes healthcare. As a result, the medical system must be transformed from a reactive approach to a proactive approach. Root cause analysis and personalized intervention should be conducted for patients with prediabetes. Based on systems medicine, also known as P4 medicine, with a predictive, preventive, personalized, and participatory approach, new medical system is expected to significantly promote the prevention and treatment of chronic diseases such as prediabetes and diabetes. Many studies have shown that the occurrence and development of diabetes is closely related to gut microbiota. However, the relationship between diabetes and gut microbiota has not been fully elucidated. This review describes the research on the relationship between gut microbiota and diabetes and some exploratory trials on the interventions of prediabetes based on P4 medicine model. Furthermore, we also discussed how these findings might influence the diagnosis, prevention and treatment of diabetes in the future, thereby to improve the wellness of human beings.

The Cost-Effectiveness of Lifestyle Interventions for Preventing Diabetes in a Health Resource-Limited Setting

AIMS

Type 2 diabetes mellitus (T2DM) is a health challenge in China, and the economic outcomes of lifestyle intervention are critically important for policymakers. This study estimates the lifetime economic outcomes of lifestyle intervention among the prediabetic population in the Chinese context.

METHODS

We developed a mathematical model to compare the cost-effectiveness of lifestyle intervention and no prevention in the prediabetic population. Efficacy and safety, medical expenditure, and utility data were derived from the literature, which was assigned to model variables for estimating the quality-adjusted life-years (QALYs) and costs as well as incremental cost-effectiveness ratios (ICERs). The analysis was conducted from the perspective of Chinese healthcare service providers. One-way and probabilistic sensitivity analyses were performed.

RESULTS

Compared with no prevention, lifestyle intervention averted 9.53% of T2DM, which translated into an additional 0.52 QALYs at a saved cost of $700 by substantially reducing the probabilities of macro- and microvascular diseases. This finding indicated that lifestyle intervention was a dominant strategy. The sensitivity analyses showed the model outputs were robust.

CONCLUSIONS

Lifestyle intervention is a very cost-effective alternative for prediabetic subjects and worth implementing in the Chinese healthcare system to reduce the disease burden related to T2DM.

Postprandial Reactive Hypoglycemia

Reactive hypoglycemia (RH) is the condition of postprandially hypoglycemia occurring 2-5 hours after food intake. RH is clinically seen in three different forms as follows: idiopathic RH (at 180 min), alimentary (within 120 min), and late RH (at 240–300 min). When the first-phase insulin response decreases, firstly, blood glucose starts to rise after the meal. This leads to late but excessive secretion of the second-phase insulin secretion. Thus, late reactive hypoglycemia occurs. Elevated insulin levels also cause down-regulation of the insulin post-receptor on the muscle and fat cells, thus decreasing insulin sensitivity. The cause of the increase in insulin sensitivity in IRH at 3 h is not completely clear. However, there is a decrease in insulin sensitivity in late reactive hypoglycaemia at 4 or 5 hours. Thus, patients with hypoglycemia at 4 or 5 h who have a family history of diabetes and obesity may be more susceptible to diabetes than patients with hypoglycemia at 3 h. We believe that some cases with normal glucose tolerance in OGTT should be considered as prediabetes at <55 or 60 mg/dl after 4-5 hours after OGTT. Metformin and AGI therapy may be recommended if there is late RH with IFG. Also Metformin, AGİ, TZD, DPP-IVInhibitors, GLP1RA therapy may be recommended if there is late RH with IGT. As a result, postprandial RH (<55 or 60 mg/dl), especially after 4 hours may predict diabetes. Therefore, people with RH along with weight gain and with diabetes history in the family will benefit from a lifestyle modification as well as the appropriate antidiabetic approach in the prevention of diabetes.

The effect of community-based programs on diabetes prevention in low- and middle-income countries: a systematic review and meta-analysis

BACKGROUND

The increasing prevalence of type 2 diabetes mellitus (T2DM) can have a substantial impact in low- and middle-income countries (LMICs). Community-based programs addressing diet, physical activity, and health behaviors have shown significant benefits on the prevention and management of T2DM, mainly in high-income countries. However, their effects on preventing T2DM in the at-risk population of LMICs have not been thoroughly evaluated.

METHODS

The Cochrane Library (CENTRAL), MEDLINE, EMBASE and two clinical trial registries were searched to identify eligible studies. We applied a 10 years limit (from 01 Jan 2008 to 06 Mar 2018) on English language literature. We included randomized controlled trials (RCTs) with programs focused on lifestyle changes such as weight loss and/or physical activity increase, without pharmacological treatments, which aimed to alter incidence of diabetes or one of the T2DM risk factors, of at least 6 months duration based on follow-up, conducted in LMICs.

RESULTS

Six RCTs randomizing 2574 people were included. The risk of developing diabetes in the intervention groups reduced more than 40%, RR (0.57 [0.30, 1.06]), for 1921 participants (moderate quality evidence), though it was not statistically significant. Significant differences were observed in weight, body mass index, and waist circumference change in favor of community-based programs from baseline, (MD [95% CI]; - 2.30 [- 3.40, - 1.19], p < 0.01, I2 = 87%), (MD [95% CI]; - 1.27 [- 2.10, - 0.44], p < 0.01, I2 = 96%), and (MD [95% CI]; - 1.66 [- 3.17, - 0.15], p = 0.03, I2 = 95%), respectively. The pooled effect showed a significant reduction in fasting blood glucose and HbA1C measurements in favor of the intervention (MD [95% CI]; - 4.94 [- 8.33, - 1.55], p < 0.01, I2 = 62%), (MD [95% CI]; - 1.17 [- 1.51, - 0.82], p < 0.01, I2 = 46%), respectively. No significant difference was observed in 2-h blood glucose values, systolic or diastolic blood pressure change between the two groups.

CONCLUSION

Based on available literature, evidence suggests that community-based interventions may reduce the incidence rate of T2DM and may positively affect anthropometric indices and HbA1C. Due to the heterogeneity observed between trials we recommend more well-designed RCTs with longer follow-up durations be executed, to confirm whether community-based interventions lead to reduced T2DM events in the at-risk population of LMIC settings.

Identification of Potential Therapeutic Targets in the Liver of Pioglitazone-Treated Type 2 Diabetes Sprague-Dawley Rats via Expression Profile Chip and iTRAQ Assay

The aim of the present study was to identify key antidiabetic nodes in the livers of pioglitazone-treated type 2 diabetes mellitus Sprague-Dawley rats by transcriptomic and proteomic analysis. Rats were randomly divided into the control, the diabetes model, and the pioglitazone-treated groups. After treatment with pioglitazone for 11 weeks, the effects on fasting blood glucose, body weight, and blood biochemistry parameters were evaluated. Microarray and iTRAQ analysis were used to determine the differentially expressed genes/proteins in rat livers. 1.5-fold changes in gene expression and 1.2-fold changes in protein were set as the screening criteria. After treatment with pioglitazone for 11 weeks, fasting blood glucose in pioglitazone-treated rats was significantly lower than that in the model group. There was a tendency for pioglitazone to reduce TC, TG, TP, ALB, BUN, and HDL-c levels. Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene ontology (GO) were applied to analyze differentially expressed genes/proteins. Furthermore, Western blotting and RT-qPCR were used to validate the results of microarray and iTRAQ. In conclusion, Cyp7a1, Cp, and RT1-EC2 are differentially expressed genes/proteins since they showed a similar trend in rats in the model group and the pioglitazone-treated group.