Medical Costs Associated with High/Moderate/Low Likelihood of Adult Growth Hormone Deficiency: A Healthcare Claims Database Analysis.

Purpose: Adult growth hormone deficiency (AGHD) is often underdiagnosed and undertreated, leading to costly comorbidities. Previously, we developed an algorithm to identify individuals in a commercially insured US population with high, moderate, or low likelihood of having AGHD. Here, we estimate and compare direct medical costs by likelihood level. Patients and Methods: Retrospective, observational analysis using the Truven Health MarketScan database to analyze direct medical costs relating to inpatient and outpatient claims, outpatient prescription claims, medication usage, clinical utilization records, and healthcare expenditures. Patients were categorized into groups based on algorithmically determined likelihoods of AGHD. Likelihood groups were further stratified by age and sex. Trajectories of annual costs (USD) by likelihood level were also investigated. Results: The study cohort comprised 135 million US adults (aged ≥18 years). Individuals ranked as high-likelihood AGHD had a greater burden of comorbid illness, including cardiovascular disease and diabetes, than those ranked moderate- or low-likelihood. Those in the high-likelihood group had greater mean total direct medical monthly costs ($1844.51 [95% confidence interval (CI): 1841.24;1847.78]) than those in the moderate- ($945.65 [95% CI: 945.26;946.04]) and low-likelihood groups ($459.10 [95% CI: 458.95;459.25]). Outpatient visits accounted for the majority of costs overall, although cost per visit was substantially lower than for inpatient services. Costs tended to increase with age and peaked around the time that individuals were assigned a level of AGHD likelihood. Total direct medical costs in individuals with a high likelihood of AGHD exceeded those for individuals with moderate or low likelihood. Conclusion: Understanding the trajectory of healthcare costs in AGHD may help rationalize allocation of healthcare resources.

Growth hormone is an important substance found in the body. Adult growth hormone deficiency (AGHD) is the reduced production of growth hormone unrelated to the normal reduction seen with aging. Untreated AGHD can result in the development of other conditions, known as comorbidities, which can be expensive to manage. Previously, 135 million privately insured people in the US, aged 18­64 years, were categorized into groups by their likelihood (high, medium, or low) of having AGHD. This study compared the estimated direct medical costs (eg hospital care and medication) across the different likelihood levels. People with a high likelihood of AGHD had more comorbidities than people with a medium/low likelihood, and an average total direct medical monthly cost of $1844.51, nearly twice as much as those with a medium likelihood ($945.65), and four times as much as those with a low likelihood ($459.10). These costs tended to increase with age, with the highest costs associated with people aged 50­59 years and 60­64 years. Outpatient costs (for treatments not requiring an overnight hospital stay) accounted for the greatest proportion of total medical costs, ahead of inpatient costs (for treatments requiring an overnight hospital stay) and medication costs. These findings suggest that diagnosing and treating AGHD earlier may help to reduce medical costs over time. Increased testing and treatment will cause an initial increase in the use of healthcare resources, but could improve overall cost effectiveness by reducing the long-term impact of the disease and avoiding unnecessary healthcare use.

Case study of semaglutide and cardiovascular outcomes: An application of the Causal Roadmap to a hybrid design for augmenting an RCT control arm with real-world data.

Introduction: Increasing interest in real-world evidence has fueled the development of study designs incorporating real-world data (RWD). Using the Causal Roadmap, we specify three designs to evaluate the difference in risk of major adverse cardiovascular events (MACE) with oral semaglutide versus standard-of-care: (1) the actual sequence of non-inferiority and superiority randomized controlled trials (RCTs), (2) a single RCT, and (3) a hybrid randomized-external data study. Methods: The hybrid design considers integration of the PIONEER 6 RCT with RWD controls using the experiment-selector cross-validated targeted maximum likelihood estimator. We evaluate 95% confidence interval coverage, power, and average patient time during which participants would be precluded from receiving a glucagon-like peptide-1 receptor agonist (GLP1-RA) for each design using simulations. Finally, we estimate the effect of oral semaglutide on MACE for the hybrid PIONEER 6-RWD analysis. Results: In simulations, Designs 1 and 2 performed similarly. The tradeoff between decreased coverage and patient time without the possibility of a GLP1-RA for Designs 1 and 3 depended on the simulated bias. In real data analysis using Design 3, external controls were integrated in 84% of cross-validation folds, resulting in an estimated risk difference of -1.53%-points (95% CI -2.75%-points to -0.30%-points). Conclusions: The Causal Roadmap helps investigators to minimize potential bias in studies using RWD and to quantify tradeoffs between study designs. The simulation results help to interpret the level of evidence provided by the real data analysis in support of the superiority of oral semaglutide versus standard-of-care for cardiovascular risk reduction.

Increased Derived Time in Range Is Associated with Reduced Risk of Major Adverse Cardiovascular Events, Severe Hypoglycemia, and Microvascular Events in Type 2 Diabetes: A Post Hoc Analysis of DEVOTE.

Time spent in glycemic target range (time in range [TIR]; plasma glucose 70-180 mg/dL [3.9-10.0 mmol/L]) as a surrogate endpoint for long-term diabetes-related outcomes requires validation. This post hoc analysis investigated the association between TIR, derived from 8-point glucose profiles (derived TIR [dTIR]) at 12 months, and time to cardiovascular or severe hypoglycemic episodes in people with type 2 diabetes in the DEVOTE trial. At 12 months, dTIR was significantly negatively associated with time to first major adverse cardiovascular event (P = 0.0087), severe hypoglycemic episode (P < 0.0001), or microvascular event (P = 0.024). A nonsignificant trend was seen toward association between 12-month hemoglobin A1c (HbA1c) and these outcomes, but this was no longer seen after addition of dTIR to the model. The results support targeting TIR >70% and suggest dTIR could be used in addition to, or in some instances in place of, HbA1c as a clinical biomarker. Trial registration details: ClinicalTrials.gov, NCT01959529.

Early Glycemic Control Assessment Based on Consensus CGM Metrics.

Continuous glucose monitoring (CGM) has revolutionized the world of diabetes and transformed the approach to diabetes care. In this context, an expert panel has reached consensus on clinical targets for CGM data interpretation based on eight CGM metrics. At least 70% of 14 consecutive CGM days (referred to as a period) are recommended to assess glycemic control based on the metrics. In clinical practice less CGM data may be available. Therefore, the primary aim of this study is to explore the ability to recover the consensus metrics utilizing less than 14 days of CGM data (intra-period). As a secondary aim, we investigate the recovery considering two consecutive periods (inter-period). The analyses are based on real-world CGM data from 484 diabetes users (4726 periods) acquired from the Cornerstones4Care® Powered by Glooko app. Using up to 14 accumulated days, the consensus metrics are calculated for each user and period, and compared to the fully 14 accumulated intra- and inter-period days. Relatively low deviations were observed for time in range (TIR) and average based metrics when using less than 14 days, however, we observed large deviations in metrics characterizing infrequent events such as time below range (TBR). Furthermore, the consensus metrics obtained in two consecutive 14 day periods have clear discrepancies (inter-period). Recovering consensus metrics using less than 14 days might still be valuable in terms of interpreting CGM data in certain clinical contexts. However, caution should be taken if treatment decisions would be made with less than 14 days of data on critical metrics such as TBR, since the metrics characterizing infrequent events deviate substantially when less data are available. Substantial deviation is also seen when comparing across two consecutive periods, which means that care should be taken not to over-generalize consensus metric based glycemic control conclusions from one period to subsequent periods.

Dynamics of cancerous tissue correlates with invasiveness.

Two of the classical hallmarks of cancer are uncontrolled cell division and tissue invasion, which turn the disease into a systemic, life-threatening condition. Although both processes are studied, a clear correlation between cell division and motility of cancer cells has not been described previously. Here, we experimentally characterize the dynamics of invasive and non-invasive breast cancer tissues using human and murine model systems. The intrinsic tissue velocities, as well as the divergence and vorticity around a dividing cell correlate strongly with the invasive potential of the tissue, thus showing a distinct correlation between tissue dynamics and aggressiveness. We formulate a model which treats the tissue as a visco-elastic continuum. This model provides a valid reproduction of the cancerous tissue dynamics, thus, biological signaling is not needed to explain the observed tissue dynamics. The model returns the characteristic force exerted by an invading cell and reveals a strong correlation between force and invasiveness of breast cancer cells, thus pinpointing the importance of mechanics for cancer invasion.