Development and Internal Validation of A Prediction Tool To Assist Clinicians Selecting Second-Line Therapy Following Metformin Monotherapy For Type 2 Diabetes

OBJECTIVE

Adults with type 2 diabetes (T2D) face increased risk of many long-term adverse outcomes. While managing patients with T2D, clinicians are challenged to stay informed regarding all new therapies and must consider potential risks and benefits resultant to their use. Metformin (MET) is typically prescribed as first-line therapy, but a second line is often needed, given MET can be insufficient for maintaining long-term glycemic control. Our objective was to develop a predictive decision-making tool to help clinicians use an outcome-based approach to select second-line therapies for patients when MET monotherapy is insufficient for glycemic control.

METHODS

Electronic health records of 19 277 adults with T2D on MET monotherapy and ≥3 months of either GLP-1RA, DPP-4i, Insulin, SGLT-2i, SFU, or TZD therapy were reviewed at Cleveland Clinic from patient visits occurring between 2005 and 2019. Separate models were developed to predict likelihood of each main outcome measure (stroke, myocardial infarction, worsening hypertension, renal failure, and death). Discrimination and calibration were assessed with bootstrapping.

RESULTS

The median follow-up time for those without an event was 3.6 years (interquartile range 1.9, 6.3). Model discrimination ability was evaluated by concordance indices (goodness of fit metric with values ranging between 0 and 1: 1 indicates perfect discrimination ability; 0.5 reflects same discrimination ability as chance) demonstrating strong discrimination ability, with concordance index values for outcomes as follows: myocardial infarction (0.786), stroke (0.805), worsening hypertension (0.855), renal failure (0.808), and death (0.827).

CONCLUSION

A decision-making tool has been developed that may afford clinicians a more objective and individualized approach to choosing a second-line therapy to control glycemia for persons with T2D.

3-point major cardiovascular event outcome for patients with T2D treated with dipeptidyl peptidase-4 inhibitor or glucagon-like peptide-1 receptor agonist in addition to metformin monotherapy

Background

The global incidence of type 2 diabetes (T2D) continues to increase annually, and persons with T2D typically require regular changes in pharmacologic invention for achieving glycemic targets. Healthcare providers must consider multiple factors when selecting a 2nd line. This retrospective cohort study evaluates impact of two common anti-diabetes medication classes (dipeptidyl peptidase-4 inhibitors and glucagon-like peptide-1 receptor agonists) on the well-known composite 3-point major cardiovascular events outcome (3P-MACE, comprised of cardiovascular death, nonfatal myocardial infarction, or nonfatal stroke). No significant impact was found. Persons with T2D face increased risks of many adverse cardiovascular outcomes. This study duplicated common inclusion and exclusion criteria to create an observational cohort from a large healthcare system's electronic health records for testing DPP-4i and GLP-1RA against each other to evaluate impact on likelihood to develop 3P-MACE.

Methods

The statistical model and analyses were based on a cohort of 5,518 adult patients with T2D who were prescribed metformin and either DPP-4i or GLP-1RA to control glycemia during clinic visits between January 2005 and September 2019. A Cox proportional hazards model was developed from the cohort to predict the 3P-MACE endpoint.

Results

The model did not show a meaningful difference in likelihood of developing the 3P-MACE outcome between patients treated with DPP-4i compared to patients treated with GLP-1RA.

Conclusions

Prior history of cardiovascular disease (CVD) did not impact this small difference between the two classes of drug.

Stealth filaments: Polymer chain length and conformation affect the in vivo fate of PEGylated potato virus X

Nanoparticles hold great promise for delivering medical cargos to cancerous tissues to enhance contrast and sensitivity of imaging agents or to increase specificity and efficacy of therapeutics. A growing body of data suggests that nanoparticle shape, in combination with surface chemistry, affects their in vivo fates, with elongated filaments showing enhanced tumor targeting and tissue penetration, while promoting immune evasion. The synthesis of high aspect ratio filamentous materials at the nanoscale remains challenging using synthetic routes; therefore we turned toward nature's materials, developing and studying the filamentous structures formed by the plant virus potato virus X (PVX). We recently demonstrated that PVX shows enhanced tumor homing in various preclinical models. Like other nanoparticle systems, the proteinaceous platform is cleared from circulation and tissues by the mononuclear phagocyte system (MPS). To increase bioavailability we set out to develop PEGylated stealth filaments and evaluate the effects of PEG chain length and conformation on pharmacokinetics, biodistribution, as well as potential immune and inflammatory responses. We demonstrate that PEGylation effectively reduces immune recognition while increasing pharmacokinetic profiles. Stealth filaments show reduced interaction with cells of the MPS; the protein:polymer hybrids are cleared from the body tissues within hours to days indicating biodegradability and biocompatibility. Tissue compatibility is indicated with no apparent inflammatory signaling in vivo. Tailoring PEG chain length and conformation (brush vs. mushroom) allows tuning of the pharmacokinetics, yielding long-circulating stealth filaments for applications in nanomedicine.