Dataset Information

Management of type 2 diabetes with a treat-to-benefit approach improved long-term cardiovascular outcomes under routine care.

ABSTRACT:

Background

Results of cardiovascular outcome trials enabled a shift from "treat-to-target" to "treat-to-benefit" paradigm in the management of type 2 diabetes (T2D). However, studies validating such approach are limited. Here, we examined whether treatment according to international recommendations for the pharmacological management of T2D had an impact on long-term outcomes.

Methods

This was an observational study conducted on outpatient data collected in 2008-2018 (i.e. prior to the "treat-to-benefit" shift). We defined 6 domains of treatment based on the ADA/EASD consensus covering all disease stages: first- and second-line treatment, intensification, use of insulin, cardioprotective, and weight-affecting drugs. At each visit, patients were included in Group 1 if at least one domain deviated from recommendation or in Group 2 if aligned with recommendations. We used Cox proportional hazard models with time-dependent co-variates or Cox marginal structural models (with inverse-probability of treatment weighing evaluated at each visit) to adjust for confounding factors and evaluate three outcomes: major adverse cardiovascular events (MACE), hospitalization for heart failure or cardiovascular mortality (HF-CVM), and all-cause mortality.

Results

We included 5419 patients, on average 66-year old, 41% women, with a baseline diabetes duration of 7.6 years. Only 11.7% had pre-existing cardiovascular disease. During a median follow-up of 7.3 years, patients were seen 12 times at the clinic, and we recorded 1325 MACE, 1593 HF-CVM, and 917 deaths. By the end of the study, each patient spent on average 63.6% of time in Group 1. In the fully adjusted model, being always in Group 2 was associated with a 45% lower risk of MACE (HR 0.55; 95% C.I. 0.46-0.66; p < 0.0001) as compared to being in Group 1. The corresponding HF-CVM and mortality risk were similar (HR 0.56; 95%CI 0.47-0.66, p < 0.0001 and HR 0.56; 95% C.I. 0.45-0.70; p < 0.0001. respectively). Sensitivity analyses confirmed these results. No single domain individually explained the better outcome of Group 2, which remained significant in all subgroups.

Conclusion

Managing patients with T2D according to a "treat-to-benefit" approach based international standards was associated with a lower risk of MACE, heart failure, and mortality. These data provide ex-post validation of the ADA/EASD treatment algorithm.

SUBMITTER: Morieri ML

PROVIDER: S-EPMC9738028 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Management of type 2 diabetes with a treat-to-benefit approach improved long-term cardiovascular outcomes under routine care.

Morieri Mario Luca ML Longato Enrico E Di Camillo Barbara B Sparacino Giovanni G Avogaro Angelo A Fadini Gian Paolo GP

Cardiovascular diabetology 20221209 1

<h4>Background</h4>Results of cardiovascular outcome trials enabled a shift from "treat-to-target" to "treat-to-benefit" paradigm in the management of type 2 diabetes (T2D). However, studies validating such approach are limited. Here, we examined whether treatment according to international recommendations for the pharmacological management of T2D had an impact on long-term outcomes.<h4>Methods</h4>This was an observational study conducted on outpatient data collected in 2008-2018 (i.e. prior to ...[more]

PMID: 36494815

Similar Datasets

Project description:IntroductionThe World Health Organization recommends the Treat-All policy of immediate antiretroviral therapy (ART) initiation, but questions persist about its feasibility in resource-poor settings. We assessed the feasibility of Treat-All compared with standard of care (SOC) under routine conditions.MethodsThis prospective cohort study from southern Eswatini followed adults from HIV care enrolment to ART initiation. Between October 2014 and March 2016, Treat-All was offered in one health zone and SOC according to the CD4 350 and 500 cells/mm3 treatment eligibility thresholds in the neighbouring health zone, each of which comprised one secondary and eight primary care facilities. We used Kaplan-Meier estimates, multivariate flexible parametric survival models and standardized survival curves to compare ART initiation between the two interventions.ResultsOf the 1726 (57.3%) patients enrolled under Treat-All and 1287 (42.7%) under SOC, cumulative three-month ART initiation was higher under Treat-All (91%) than SOC (74%; p < 0.001) with a median time to ART of 1 (IQR 0 to 14) and 10 (IQR 2 to 117) days respectively. Under Treat-All, ART initiation was higher in pregnant women (vs. non-pregnant women: adjusted hazard ratio (aHR) 1.96, 95% confidence interval (CI) 1.70 to 2.26), those with secondary education (vs. no formal education: aHR 1.48, 95% CI 1.12 to 1.95), and patients with an HIV-positive diagnosis before care enrolment (aHR 1.22, 95% CI 1.10 to 1.36). ART initiation was lower in patients attending secondary care facilities (aHR 0.64, 95% CI 0.58 to 0.72) and for CD4 351 to 500 when compared with CD4 201 to 350 cells/mm3 (aHR 0.84, 95% CI 0.72 to 1.00). ART initiation varied over time for TB cases, with lower hazard during the first two weeks after HIV care enrolment and higher hazards thereafter. Of patients with advanced HIV disease (n = 1085; 36.0%), crude 3-month ART initiation was similar in both interventions (91% to 92%) although Treat-All initiated patients more quickly during the first month after HIV care enrolment.ConclusionsART initiation was high under Treat-All and without evidence of de-prioritization of patients with advanced HIV disease. Additional studies are needed to understand the long-term impact of Treat-All on patient outcomes.

Project description:BackgroundIn medicine, clinicians treat individuals under an implicit assumption that high-risk patients would benefit most from the treatment ('high-risk approach'). However, treating individuals with the highest estimated benefit using a novel machine-learning method ('high-benefit approach') may improve population health outcomes.MethodsThis study included 10 672 participants who were randomized to systolic blood pressure (SBP) target of either <120 mmHg (intensive treatment) or <140 mmHg (standard treatment) from two randomized controlled trials (Systolic Blood Pressure Intervention Trial, and Action to Control Cardiovascular Risk in Diabetes Blood Pressure). We applied the machine-learning causal forest to develop a prediction model of individualized treatment effect (ITE) of intensive SBP control on the reduction in cardiovascular outcomes at 3 years. We then compared the performance of high-benefit approach (treating individuals with ITE >0) versus the high-risk approach (treating individuals with SBP ≥130 mmHg). Using transportability formula, we also estimated the effect of these approaches among 14 575 US adults from National Health and Nutrition Examination Surveys (NHANES) 1999-2018.ResultsWe found that 78.9% of individuals with SBP ≥130 mmHg benefited from the intensive SBP control. The high-benefit approach outperformed the high-risk approach [average treatment effect (95% CI), +9.36 (8.33-10.44) vs +1.65 (0.36-2.84) percentage point; difference between these two approaches, +7.71 (6.79-8.67) percentage points, P-value <0.001]. The results were consistent when we transported the results to the NHANES data.ConclusionsThe machine-learning-based high-benefit approach outperformed the high-risk approach with a larger treatment effect. These findings indicate that the high-benefit approach has the potential to maximize the effectiveness of treatment rather than the conventional high-risk approach, which needs to be validated in future research.

Project description:BackgroundCardiovascular disease (CVD) has become a major cause of morbidity and mortality in patients with type 2 diabetes mellitus (T2DM). Although there is also evidence that multifactorial interventions to control blood glucose, blood pressure, and lipid profiles can reduce macrovascular complications and mortality in patients with T2DM, the link between these risk factors has not been established.MethodsOn 10 December 2018, 1,920 people in four cities in Anhui Province were included. Latent category analysis (LCA) was used to explore the clustering mode of HRBs (health risk behaviors). The primary exposure was HRBs and exercise and diet interventions, and the primary outcome was CVD and other variables, including zMS, triglyceride-glucose index (TyG), TyG-WC (waist circumference), TyG-BMI, TG/HDL, and cardiovascular health (CVH). A multivariable logistic regression model was used to establish the relationship between HRBs, exercise, diet interventions, and CVD. Moderate analysis and mediation moderation analysis were employed by the PROCESS method to explore the relationship between these variables. Sensitivity analysis explored the robustness of the model.ResultsThe mean age was 57.10 ± 10.0 years old. Overall, CVD affects approximately 19.9% of all persons with T2DM. Macrovascular complications of T2DM include coronary heart disease, myocardial infarction (MI), cardiac insufficiency, and cerebrovascular disease. Elderly age (χ 2 = 22.70), no occupation (χ 2 = 20.97), medium and high socioeconomic status (SES) (χ 2 = 19.92), higher level of TyG-WC (χ 2 = 6.60), and higher zMS (χ 2 = 7.59) were correlated with high CVD. Many metabolic indices have shown a connection with T2DM combined with CVD, and there was a dose-response relationship between HRB co-occurrence and clustering of HRBs and zMS; there was a dose-response relationship between multifactorial intervention and CVH. In the mediation moderation analysis, there was an association between HRB, gender, TyG, TyG-BMI, and CVD. From an intervention management perspective, exercise and no diet intervention were more significant with CVD; moreover, there was an association between intervention management, gender, zMS, TyG-WC, TyG-BMI, TG/HDL, and CVD. Finally, there was an association between sex, CVH, and CVD. Sensitivity analysis demonstrated that our results were robust.ConclusionsCVD is one of the common complications in patients with type 2 diabetes, and its long-term outcome will have more or less impact on patients. Our findings suggest the potential benefits of scaling up multifactorial and multifaceted interventions to prevent CVD in patients with T2DM.

Dataset Information

Management of type 2 diabetes with a treat-to-benefit approach improved long-term cardiovascular outcomes under routine care.

Background

Methods

Results

Conclusion

Publications

Management of type 2 diabetes with a treat-to-benefit approach improved long-term cardiovascular outcomes under routine care.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets