Study design choices for evaluating the comparative safety of diabetes medications: An evaluation of pioglitazone use and risk of bladder cancer in older US adults with type-2 diabetes

Sodium-glucose cotransporter 2 inhibitors and renal cancer in the US FDA adverse event reporting system

BACKGROUND

Recent evidence suggests an association between sodium-glucose cotransporter 2 (SGLT2) inhibitors and a higher risk of renal cancer.

OBJECTIVE

We conducted a pharmacovigilance analysis using the US FDA Adverse Event Reporting System (FAERS) to investigate the disproportionate association between SGLT2 inhibitors and renal cancer.

METHODS

We used AERSMine to mine data from FAERS, covering the period from 2014 Q1 to 2023 Q3. The control group was treated with other glucose-lowering medications (ATC-A10B). Disproportionality analysis results were performed using a proportional reporting ratio (PRR) with a 95% confidence interval (CI) and an information component (IC) with 95% credible interval.

RESULTS

Compared to the control group, the SGLT2 inhibitor group had a higher disproportionate renal cancer reporting frequency (0.92 vs 0.27/1000 reports; PRR 3.38; 95% CI 2.68-4.25; p < 0.001) with an IC of 1.36 (0.60-2.06), comprising dapagliflozin (PRR 4.14; 2.95-5.80; p < 0.001), empagliflozin (PRR 2.74; 1.94-3.89; p < 0.001), and canagliflozin (PRR 3.56; 2.48-5.12; p < 0.001). Consistent results were obtained in the diabetes indication with the primary outcomes only for the SGLT2 inhibitors group (not individual molecule). The results of the sensitivity analysis (excluding hypertension indication or antihypertensive drugs, obesity, smoking, alpha-1 blockers, or anti-renal cancer drugs) were highly consistent with the main outcomes, indicating good robustness of the results. The results from 2004 Q1 to 2023 Q3 were similar to those from 2014 Q1 to 2023 Q3, with the exception of empagliflozin.

CONCLUSION

There was a disproportionate association between SGLT2 inhibitors and renal cancer, which supports the current meta-analysis results indicating an increased risk of renal cancer associated with SGLT2 inhibitors.

Instituting a Successful Discharge Plan for Patients With Type 2 Diabetes: Challenges and Solutions

Achieving target inpatient glycemic management outcomes has been shown to influence important clinical outcomes such as hospital length of stay and readmission rates. However, arguably the most profound, lasting impact of inpatient diabetes management is achieved at the time of discharge-namely reconciling and prescribing the right medications and making referrals for follow-up. Discharge planning offers a unique opportunity to break through therapeutic inertia, offer diabetes self-management education, and institute an individualized treatment plan that prepares the patient for discharge and promotes self-care and engagement. However, the path to a successful discharge plan can be fraught with potential pitfalls for clinicians, including lack of knowledge and experience with newer diabetes medications, costs, concerns over insurance coverage, and lack of time and resources. This article presents an algorithm to assist clinicians in selecting discharge regimens that maximize benefits and reduce barriers to self-care for patients and a framework for creating an interdisciplinary hospital diabetes discharge program.

Pioglitazone, Bladder Cancer and the Presumption of Innocence

BACKGROUND

Thiazolidinediones are potent exogenous agonists of PPAR-γ, which augment the effects of insulin to its cellular targets and mainly at the level of adipose tissue. Pioglitazone, the main thiazolidinedione in clinical practice, has shown cardiovascular and renal benefits in patients with type 2 diabetes, durable reduction of glycated hemoglobulin levels, important improvements of several components of the metabolic syndrome and beneficial effects of non-alcoholic fatty liver disease.

OBJECTIVE

Despite all of its established advantages, the controversy for an increased risk of developing bladder cancer, combined with the advent of newer drug classes that achieved major cardiorenal effects have significantly limited its use spreading a persistent shadow of doubt for its future role.

METHODS

Pubmed, Google and Scope databases have been thoroughly searched and relevant studies were selected.

RESULTS

This paper explores thoroughly both in vitro and in vivo (animal models and humans) studies that investigated the possible association of pioglitazone with bladder cancer.

CONCLUSION

Currently the association of pioglitazone with bladder cancer cannot be based on solid evidence. This evidence cannot justify its low clinical administration, especially in the present era of individualised treatment strategies. Definite clarification of this issue is imperative and urgently anticipated from future high quality and rigorous pharmacoepidemiologic research, keeping in mind its unique mechanism of action and its significant pleiotropic effects.

Conducting Real-world Evidence Studies on the Clinical Outcomes of Diabetes Treatments

Real-world evidence (RWE), the understanding of treatment effectiveness in clinical practice generated from longitudinal patient-level data from the routine operation of the healthcare system, is thought to complement evidence on the efficacy of medications from randomized controlled trials (RCTs). RWE studies follow a structured approach. (1) A design layer decides on the study design, which is driven by the study question and refined by a medically informed target population, patient-informed outcomes, and biologically informed effect windows. Imagining the randomized trial we would ideally perform before designing an RWE study in its likeness reduces bias; the new-user active comparator cohort design has proven useful in many RWE studies of diabetes treatments. (2) A measurement layer transforms the longitudinal patient-level data stream into variables that identify the study population, the pre-exposure patient characteristics, the treatment, and the treatment-emergent outcomes. Working with secondary data increases the measurement complexity compared to primary data collection that we find in most RCTs. (3) An analysis layer focuses on the causal treatment effect estimation. Propensity score analyses have gained in popularity to minimize confounding in healthcare database analyses. Well-understood investigator errors, like immortal time bias, adjustment for causal intermediates, or reverse causation, should be avoided. To increase reproducibility of RWE findings, studies require full implementation transparency. This article integrates state-of-the-art knowledge on how to conduct and review RWE studies on diabetes treatments to maximize study validity and ultimately increased confidence in RWE-based decision making.

Careful use to minimize adverse events of oral antidiabetic medications in the elderly

INTRODUCTION

An increasing number of older patients has type 2 diabetes treated with different oral antidiabetic agents whose safety may raise concern considering some particularities of a heterogeneous elderly population.

AREAS COVERED

This article discusses some characteristics of older patients that could increase the risk of adverse events, with a focus on hypoglycemia. It describes the most frequent and/or severe complications reported in the elderly in both randomized controlled trials and observational studies with metformin, sulfonylureas, meglitinides, alpha-glucosidase inhibitors, thiazolidinediones, dipeptidyl peptidase-4 inhibitors (gliptins) and sodium-glucose cotransporter type 2 inhibitors (gliflozins).

EXPERT OPINION

Old patients may present comorbidities (renal impairment, vascular disease, heart failure, risk of dehydration, osteoporosis, cognitive dysfunction) that could increase the risk of severe adverse events. Sulfonylureas (and meglitinides) induce hypoglycemia, which may be associated with falls/fractures and cardiovascular events. Medications lacking hypoglycemia should be preferred. Gliptins appear to have the best tolerance/safety profile whereas gliflozins exert a cardiorenal protection. However, data are lacking in very old or frailty old patients so that caution and appropriate supervision of such patients are required. Taking advantage of a large choice of pharmacotherapies, personalized treatment is recommended based upon both drug safety profiles and old patient individual characteristics.

The present and future scope of real-world evidence research in diabetes: What questions can and cannot be answered and what might be possible in the future?

The last decade has witnessed an exponential growth in the opportunities to collect and link health-related data from multiple resources, including primary care, administrative, and device data. The availability of these "real-world," "big data" has fuelled also an intense methodological research into methods to handle them and extract actionable information. In medicine, the evidence generated from "real-world data" (RWD), which are not purposely collected to answer biomedical questions, is commonly termed "real-world evidence" (RWE). In this review, we focus on RWD and RWE in the area of diabetes research, highlighting their contributions in the last decade; and give some suggestions for future RWE diabetes research, by applying well-established and less-known tools to direct RWE diabetes research towards better personalized approaches to diabetes care. We underline the essential aspects to consider when using RWD and the key features limiting the translational potential of RWD in generating high-quality and applicable RWE. Only if viewed in the context of other study designs and statistical methods, with its pros and cons carefully considered, RWE will exploit its full potential as a complementary or even, in some cases, substitutive source of evidence compared to the expensive evidence obtained from randomized controlled trials.

Transparency in real-world evidence (RWE) studies to build confidence for decision-making: Reporting RWE research in diabetes

Transparency of real-world evidence (RWE) studies is critical to understanding how findings of a specific study were derived and is a necessary foundation to assessing validity and determination of whether decisions should be informed by the findings. In the present paper, we lay out strategies to improve clarity in the reporting of comparative effectiveness studies using real-world data that were generated by the routine operation of a healthcare system. This may include claims data, electronic health records, wearable devices, patient-reported outcomes or patient registries. These recommendations were discussed with multiple stakeholders, including regulators, payers, academics and journal editors, and endorsed by two professional societies that focus on RWE. We remind readers interested in diabetes research of the utility of conceptualizing a target trial that is then emulated by a RWE study when planning and communicating about RWE study implementation. We recommend the use of a graphical representation showcasing temporality of key longitudinal study design choices. We highlight study elements that should be reported to provide the clarity necessary to make a study reproducible. Finally, we suggest registering study protocols to increase process transparency. With these tools the readership of diabetes RWE studies will be able to more efficiently understand each study and be more able to assess a study's validity with reasonably high confidence before making decisions based on its findings.