Effectiveness and safety of basal insulin therapy in type 2 diabetes mellitus patients with or without metformin observed in a national cohort in China.

BACKGROUND: Though many randomized control trials had examined the effectiveness and safety of taking insulin therapy with or without metformin, there are limited real-world data, especially among Chinese type 2 diabetes patients initiating basal insulin (BI) with uncontrolled hyperglycemia by oral agents. This study was designed to assess the effectiveness and safety of BI therapy combined with or without metformin in a real-world national cohort study. METHODS: Patients with type 2 diabetes mellitus who initiated BI treatment due to uncontrolled hyperglycemia (HbA1c≥7 %) by oral antidiabetic drugs (OADs) were recruited in Chinese real-world settings between 2011 and 2013. A total of 12,358 patients initiated BI without bolus insulin and completed a 6-month follow-up were selected as the study population and divided into BI with metformin or BI without metformin group based on whether metformin was simultaneously prescribed or not at baseline. Propensity score adjustment was used to balance baseline covariates between two groups. A sub-analysis was also conducted among 8,086 patients who kept baseline treatment regimen during the follow-up. Outcomes were HbA1c, hypoglycemia, weight gain and insulin dose in two groups. RESULTS: 53.6 % (6,621 out of 12,358) patients initiated BI therapy concomitant with metformin. After propensity score adjustment, multivariate regression analysis controlled with number of OADs, total insulin dose, physical activity and diet consumption showed that BI with metformin group had a slightly higher control rate of HbA1c <7.0 % (39.9 % vs. 36.4 %, P = 0.0011) at 6-month follow-up, and lower dose increment from baseline to 6-month (0.0064 vs. 0.0068 U/day/kg, P = 0.0035). The sub-analysis with patients remained at same BI therapy further showed that BI with metformin group had higher HbA1c control rate (47.9 % vs. 41.9 %, P = 0.0001), less weight gain (-0.12 vs. 0.15 kg P = 0.0013), and lower dose increment during 6-month follow-up (0.0033 vs. 0.0037 U/day/kg, P = 0.0073) when compared with BI without metformin group. CONCLUSIONS: In alliance with current guidelines, the real-world findings also support the insulin initiation together with metformin. Continuous patients' education and clinicians training are needed to improve the use of metformin when initiating BI treatment.

Evaluation of an mHealth-enabled hierarchical diabetes management intervention in primary care in China (ROADMAP): A cluster randomized trial.

BACKGROUND: Glycemic control remains suboptimal in developing countries due to critical system deficiencies. An innovative mobile health (mHealth)-enabled hierarchical diabetes management intervention was introduced and evaluated in China with the purpose of achieving better control of type 2 diabetes in primary care. METHODS AND FINDINGS: A community-based cluster randomized controlled trial was conducted among registered patients with type 2 diabetes in primary care from June 2017 to July 2019. A total of 19,601 participants were recruited from 864 communities (clusters) across 25 provinces in China, and 19,546 completed baseline assessment. Moreover, 576 communities (13,037 participants) were centrally randomized to the intervention and 288 communities (6,509 participants) to usual care. The intervention was centered on a tiered care team-delivered mHealth-mediated service package, initiated by monthly blood glucose monitoring at each structured clinic visit. Capacity building and quarterly performance review strategies upheld the quality of delivered primary care. The primary outcome was control of glycated hemoglobin (HbA1c; <7.0%), assessed at baseline and 12 months. The secondary outcomes include the individual/combined control rates of blood glucose, blood pressure (BP), and low-density lipoprotein cholesterol (LDL-C); changes in levels of HbA1c, BP, LDL-C, fasting blood glucose (FBG), and body weight; and episodes of hypoglycemia. Data were analyzed using intention-to-treat (ITT) generalized estimating equation (GEE) models, accounting for clustering and baseline values of the analyzed outcomes. After 1-year follow-up, 17,554 participants (89.8%) completed the end-of-study (EOS) assessment, with 45.1% of them from economically developed areas, 49.9% from urban areas, 60.5 (standard deviation [SD] 8.4) years of age, 41.2% male, 6.0 years of median diabetes duration, HbA1c level of 7.87% (SD 1.92%), and 37.3% with HbA1c <7.0% at baseline. Compared with usual care, the intervention led to an absolute improvement in the HbA1c control rate of 7.0% (95% confidence interval [CI] 4.0% to 10.0%) and a relative improvement of 18.6% (relative risk [RR] 1.186, 95% CI 1.105 to 1.267) and an absolute improvement in the composite ABC control (HbA1c <7.0%, BP <140/80 mm Hg, and LDL-C <2.6 mmol/L) rate of 1.9% (95% CI 0.5 to 3.5) and a relative improvement of 21.8% (RR 1.218, 95% CI 1.062 to 1.395). No difference was found on hypoglycemia episode and weight gain between groups. Study limitations include noncentralized laboratory tests except for HbA1c, and caution should be exercised when extrapolating the findings to patients not registered in primary care system. CONCLUSIONS: The mHealth-enabled hierarchical diabetes management intervention effectively improved diabetes control in primary care and has the potential to be transferred to other chronic conditions management in similar contexts. TRIAL REGISTRATION: Chinese Clinical Trial Registry (ChiCTR) IOC-17011325.

The prevalence of multimorbidity and its association with physical activity and sleep duration in middle aged and elderly adults: a longitudinal analysis from China.

BACKGROUND: Preventing chronic disease is important in health policy in countries with significantly ageing populations. This study aims to examine the prevalence of chronic disease multimorbidity and its association with physical activity and sleep duration; and to understand whether physical activity modifies associations between sleep duration and multimorbidity. METHODS: We utilized longitudinal data of a nationally-representative sample from the China Health and Retirement Longitudinal Study (in year 2011 and 2015; N = 5321; 54.7% female; age ≥ 45 years old). Fourteen chronic diseases were used to measure multimorbidity (ten self-reported, and four by blood test). Participants were grouped into high, moderate, and low level based on self-reported frequencies and durations of physical activity with different intensities for at least 10 min at a time in a usual week. Poor and good sleepers were categorized according to average hours of actual sleep at each night during the past month. Panel data method of random-effects logistic regression model was applied to estimate the association of physical activity and sleep with multimorbidity, adjusting for social-demographic and behavioural confounders. RESULTS: From 2011 to 2015, the prevalence of multimorbidity increased from 52.2 to 62.8%. In 2015, the proportion of participants engaging in high, moderate, and low level of physical activity was 30.3, 24.4 and 45.3%, respectively, and 63.6% of adults had good sleep. For both genders, compared with good sleep, poor sleep was associated with higher odds of multimorbidity (OR = 1.527, 95% CI: 1.277, 1.825). Compared to the high-level group, participants with a low level of physical activity were significantly more likely to have multimorbidity (OR = 1.457, 95% CI: 1.277, 1.825), but associations were stronger among women. The relative excess risk due to interaction between poor sleep and moderate or low physical activity was positive but non-significant on multimorbidity. CONCLUSIONS: The burden of multimorbidity was high in China. Low physical activity and poor sleep was independently and significantly associated with a higher likelihood of multimorbidity in women and both genders, separately. Physical activity could modify the association between sleep and multimorbidity.

Changes of health-related quality of life after initiating basal insulin treatment among people with type 2 diabetes.

To assess the association between insulin regimens and health-related quality of life (HRQoL) after the introduction of basal insulin (BI) among people with type 2 diabetes in real-world clinical settings. 16,339 registered people with diabetes who had inadequate glycaemic control by oral agents initiated BI (either single BI or Basal-bolus) and completed a 6-month follow-up from 209 hospitals were included in the analyses. At the end of the follow-up, the switches of insulin regimens, change of HRQoL (EQ-5D-3L) and their associations were assessed. Initial insulin regimens of single BI and of basal-bolus (BI included Glargine, Detemir, and Neutral Protamine Hagedorn) accounted for 75.6% and 24.4%, respectively. At 6 months, regimens used were BI alone (65.2%), basal-bolus (10.4%), and premixed (6.4%), whereas 17.9% stopped all insulin therapy. The visual analogue scale score increased by 5.46 (P < .001), and the index value increased slightly by 0.02 (P < .001). Univariate analysis showed that people with diabetes taking basal-bolus regimen had the greatest improvement on HRQoL in all dimensions, especially in the reduction of the percentage of Pain/Discomfort (by 10.03%) and Anxiety/Depression (by 11.21%). In multivariable analysis, single BI or premixed insulin at 6 months was associated with more improvement of visual analogue scale score compared with stopping all insulin. Improved HRQoL was observed after initiating BI in people with type 2 diabetes . If the same achievement on HbA1c control can be guaranteed, single BI is preferred to other regimens from the viewpoint of HRQoL. Basal-bolus has the most significant potential to increase HRQoL, however, the people with diabetes characteristics differ from those initiating BI alone. Further longitudinal cohort study with a longer study period might be necessary to evaluate the certain effect.

Where to Initiate Basal Insulin Therapy: Inpatient or Outpatient Department? Real-World Observation in China.

Background: This study aims to compare the effectiveness of initiating insulin therapy in inpatient and outpatient settings during a 6-month follow-up period among patients with type 2 diabetes mellitus (T2DM) in real-world settings. Materials and Methods: The study was based on the ORBIT study, a real-world observational study which recruited patients with inadequate glycemic control by oral antidiabetic drugs (OAD) and initiated basal insulin (BI). We compare difference in initiation and evolution of insulin therapy and glycemic control after six months were compared between patients initiating basal insulin in the inpatient department (inpatient initiators) and those starting in outpatient (outpatient initiators) among participants without rehospitalization during the six months follow-up. Results: Among all 18,995 participants in the ORBIT study, 56.0% were inpatient initiators and 44.0% outpatient. We conducted in-depth analysis among 14,860 patients without rehospitalization, 8129 inpatient initiators and 6731 outpatient initiators. (1) Inpatient initiators had lower insulin therapy persistence during six months (64.2%) than outpatient ones (78.6%) (p<0.001), which was mainly explained by more therapy switches from basal-bolus regimen to other therapies among inpatient initiators (50.1%) than that among outpatient initiators (37.5%) (p<0.001). (2) Inpatient initiation had a higher proportion of people achieving glucose targets (HbA1c <7%) than outpatient initiation. However, the benefit of inpatient initiation versus outpatient initiation was mainly observed among patients persisting with the initial insulin therapies (46.3% vs 39.5% p<0.001), rather than those nonpersistent (37.3% vs 36.2%, p=0.723). (3) Among patients with HbA1c <9%, taking only one OAD and without complications at baseline, inpatient insulin initiation did not show a higher proportion of people achieving glucose target than outpatient initiation (adjusted odds ratio=0.96, 95% CI: 0.76-1.21). Conclusion: For patients with HbA1c ≥9%, who were taking more than one OAD and had complications at baseline, initiating insulin treatment during hospitalization has a higher proportion of people achieving glucose target than that in the outpatient department, but the premise is that the initial therapy is acceptable and can be maintained after discharge. Patient-centered approach with co-agreed decision-making to select a suitable insulin regimen should be strengthened.

Provincial heterogeneity in the management of care cascade for hypertension, diabetes, and dyslipidaemia in China: Analysis of nationally representative population-based survey.

Background: This study aims to examine (1) province-level variations in the levels of cardiovascular disease (CVD) risk and behavioral risk for CVDs, (2) province-level variations in the management of cascade of care for hypertension, diabetes, and dyslipidaemia, and (3) the association of province-level economic development and individual factors with the quality of care for hypertension, diabetes, and dyslipidaemia. Methods: We used nationally representative data from the China Health and Retirement Longitudinal Study in 2015, which included 12,597 participants aged 45 years. Using a care cascade framework, we examined the quality of care provided to patients with three prevalent NCDs: hypertension, diabetes, and dyslipidaemia. The proportion of WHO CVD risk based on the World Health Organization CVD risk prediction charts, Cardiovascular Risk Score (CRS) and Behavior Risk Score (BRS) were calculated. We performed multivariable logistic regression models to determine the individual-level drivers of NCD risk variables and outcomes. To examine socio-demographic relationships with CVD risk, linear regression models were applied. Results: In total, the average CRS was 4.98 (95% CI: 4.92, 5.05), while the average BRS was 3.10 (95% confidence interval: 3.04, 3.15). The weighted mean CRS (BRS) in Fujian province ranged from 4.36 to 5.72 (P < 0.05). Most of the provinces had a greater rate of hypertension than diabetes and dyslipidaemia awareness and treatment. Northern provinces had a higher rate of awareness and treatment of all three diseases. Similar patterns of regional disparity were seen in diabetes and dyslipidaemia care cascades. There was no evidence of a better care cascade for CVDs in patients who reside in more economically advanced provinces. Conclusion: Our research found significant provincial heterogeneity in the CVD risk scores and the management of the cascade of care for hypertension, diabetes, and dyslipidaemia for persons aged 45 years or more. To improve the management of cascade of care and to eliminate regional and disparities in CVD care and risk factors in China, local and population-based focused interventions are necessary.

Medical costs and out-of-pocket expenditures associated with multimorbidity in China: quantile regression analysis.

OBJECTIVE: Multimorbidity is a growing challenge in low-income and middle-income countries. This study investigates the effects of multimorbidity on annual medical costs and the out-of-pocket expenditures (OOPEs) along the cost distribution. METHODS: Data from the nationally representative China Health and Retirement Longitudinal Study (CHARLS 2015), including 10 592 participants aged ≥45 years and 15 physical and mental chronic diseases, were used for this nationally representative cross-sectional study. Quantile multivariable regressions were employed to understand variations in the association of chronic disease multimorbidity with medical cost and OOPE. RESULTS: Overall, 69.5% of middle-aged and elderly Chinese had multimorbidity in 2015. Increased number of chronic diseases was significantly associated with greater health expenditures across every cost quantile groups. The effect of chronic diseases on total medical cost was found to be larger among the upper tail than those in the lower tail of the cost distributions (coefficients 12, 95% CI 6 to 17 for 10th percentile; coefficients 296, 95% CI 71 to 522 for 90th percentile). Annual OOPE also increased with chronic diseases from the 10th percentile to the 90th percentile. Multimorbidity had larger effects on OOPE and was more pronounced at the upper tail of the health expenditure distribution (regression coefficients of 8 and 84 at the 10th percentile and 75th percentile, respectively). CONCLUSION: Multimorbidity is associated with escalating healthcare costs in China. Further research is required to understand the impact of multimorbidity across different population groups.

Road to Hierarchical Diabetes Management at Primary Care (ROADMAP) Study in China: Protocol for the Statistical Analysis of a Cluster Randomized Controlled Trial.

BACKGROUND: As the management of type 2 diabetes remains suboptimal in primary care, the Road to Hierarchical Diabetes Management at Primary Care (ROADMAP) study was designed and conducted in diverse primary care settings to test the effectiveness of a three-tiered diabetes management model of care in China. OBJECTIVE: This paper aims to predetermine the detailed analytical methods for the ROADMAP study before the database lock to reduce potential bias and facilitate transparent analyses. METHODS: The ROADMAP study adopts a community-based, cluster randomized controlled trial design that compares the effectiveness of a tiered diabetes management model on diabetes control with usual care among patients with diabetes over a 1-year study period. The primary outcome is the control rate of glycated hemoglobin (HbA1c) <7% at 1 year. Secondary outcomes include the control rates of ABC (HbA1c, blood pressure, and low-density lipoprotein cholesterol [LDL-C], individual and combined) and fasting blood glucose, and the change in each outcome. The primary analysis will be the log-binomial regression with generalized estimating equation (GEE), which accounts for the clustering within communities, for binary outcomes and linear regression with GEE for continuous outcomes. For both, the baseline value of the analyzed outcome will be the covariate. The other covariate further adjusted models and the repetitive models after multiple imputation (when more than 10% of observations in HbA1c after 1 year are missing) will be used for sensitivity analysis. Five prespecified subgroup analyses have also been planned to explore the heterogeneity of the intervention effects by adding the subgroup variable and its interaction with the intervention to the primary model. RESULTS: This plan has been finalized, approved, and signed off by the principle investigator, co-principle investigator, and lead statisticians as of November 22, 2019, and made public on the institutional website without any knowledge of intervention allocation. Templates for the main figure and tables are presented. CONCLUSIONS: This statistical analysis protocol was developed for the main results of the ROADMAP study by authors blinded to group allocation and with no access to study data, which will guarantee the transparency and reduce potential bias during statistical analysis. TRIAL REGISTRATION: Chinese Clinical Trial Registry ChiCTR-IOC-17011325; https://tinyurl.com/ybpr9xrq. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/18333.

Study protocol for the road to hierarchical diabetes management at primary care (ROADMAP) study in China: a cluster randomised controlled trial.

INTRODUCTION: Diabetes management in primary care remains suboptimal in China, despite its inclusion in the essential public health service (EPHS). We aimed to evaluate the effectiveness of a mobile health (mHealth) based and three-tiered diabetes management system in diverse Chinese contexts. METHODS AND ANALYSIS: This is a cluster randomised controlled trial, named road to hierarchical diabetes management at primary care (ROADMAP). 19 008 patients with type 2 diabetes (T2D) were recruited from primary care clinics in 864 communities across 144 counties/districts of 24 provinces. Eligible participants were adult patients diagnosed with T2D and registered for diabetes management in communities. Patients within the same communities (clusters) were randomly allocated into the intervention or control arm for 1 year in a 2:1 ratio. The control arm patients received usual care as EPHS packaged: at least four blood glucose (BG) and blood pressure (BP) tests, and lifestyle and medication instruction, yearly, from primary care providers. The intervention arm patients received at least two BG and one BP tests, monthly, and lifestyle and treatment instruction from a three-tiered contracted team. A mHealth platform, Graded ROADMAP, enabled test results uploading and sharing, and patient referral within the team. The intervention participants will be further divided into basic or intensive intervention group according to whether they were actively using the Your Doctor App. The primary outcome is the BG control rate with glycated haemoglobin (HbA1c)<7.0%. Secondary outcomes include control rates and changes of ABC (HbA1c, BP and low-density lipoprotein cholesterol) and fasting BG, hypoglycaemia episodes and health-related quality of life (EuroQol (EQ-5D)). ETHICS AND DISSEMINATION: The trial has been approved by the Institutional Review Board at Shanghai Sixth People's Hospital. Findings on the intervention effectiveness will be disseminated through peer-reviewed journals, conference presentations and other relevant mechanisms. TRIAL REGISTRATION NUMBER: ChiCTR-IOC-17011325.