Search

Diabetic kidney disease (DKD) develops in 1 in 3 people with type 2 diabetes (T2D) and is the leading cause of end-stage renal disease (ESRD). DKD currently costs the US healthcare system USD 50 billion annually. PromarkerD is a simple biomarker-based blood test that can predict future renal function decline in T2D patients who have no or mild existing DKD (eGFR >30). This study estimated the net savings to US payers from covering the PromarkerD test versus current standard of care (SOC). Model inputs included costs and frequency of testing, costs associated with changes to patient medication strategies, and cost-savings from slowed DKD progression and averted ESRD interventions (dialysis and kidney transplants). All estimates and inputs for the model were collected from recent peer-reviewed literature, established insurance payment rates, and PromarkerD clinical studies. Results showed that over ten years the net savings for US payers by adopting PromarkerD testing for T2D patients (KDIGO DKD category G1-3b) would exceed USD 14 billion and the equilibrium point (costs equal savings) can be achieved after two years. Primarily, savings arise from slower DKD stage progression, with contributions from delayed dialysis and transplants, and also from fewer unplanned dialyses. This economic study demonstrates that improved management of T2D patients through the use of early, accurate and cost-effective prognosis with the PromarkerD test could result in substantial savings to US payers in the treatment of DKD. Employing this alternative PromarkerD testing regime over the current SOC would enable early interventions for at-risk patients, thereby decreasing the need for expensive interventions such as dialysis and transplants, or unnecessary adoption of new therapeutic treatments. Disclosure W. Burchenal: Research Support; Self; Proteomics International. M. Datar: Research Support; Self; Proteomics International. K. E. Peters: Employee; Self; Proteomics International, Stock/Shareholder; Self; Proteomics International. G. C. Fernandez: Employee; Self; Proteomics International, Stock/Shareholder; Self; Proteomics International. J. C. Morrison: Consultant; Self; Proteomics International. R. J. Lipscombe: Employee; Self; Proteomics International.

Introduction Timely and effective resolution of multiple sclerosis (MS) relapse is critical to minimizing residual deficits, which can result in neurologic disability. Oral corticosteroids (OCS) and intravenous corticosteroids [intravenous methylprednisolone (IVMP)] are earlier line treatments; alternatives include repository corticotropin injection (RCI; H.P. Acthar® Gel), plasmapheresis (PMP), and intravenous immunoglobulin (IVIG). Contemporary insight into the use of relapse treatments and their effectiveness is needed. Objective To evaluate relapse rates, frequency of treatments used, and treatment effectiveness (i.e., relapse resolution). Methods A retrospective analysis of patients ages 18–89 years experiencing MS relapse from 1 January 2008 to 30 June 2015 was conducted using administrative claims data. MS relapse was defined based on established claims-based methodology. The first claim for relapse treatment (i.e., prescription or administration) was used to designate the treatment group and relapse date, respectively. Relapses occurring ≤ 30 days were considered an episode. The first relapse episode was identified for every patient. Treatment was deemed effective in resolving the relapse if no additional relapses followed within the episode; otherwise, the relapse was considered unresolved. A 5-day OCS taper following IVMP administration, designated IVMP ± OCS, was allowed. Relapse frequency, treatment use, and relapse resolution were quantified. Relapse resolution was likewise evaluated in patients continuously enrolled for 12 months before and after first treatment with RCI or PMP/IVIG, with PMP/IVIG administrations within 7 days of each other being considered a single course of therapy. Results During the study period, 9574 patients experienced ≥ 1 relapse; 26.0% of patients had ≥ 2 relapses/year. The mean number of relapse episodes was 2.6 over a mean follow-up of 2.7 years for an annualized relapse rate of 1.0. Corticosteroids were the first treatment used in 90.4% of relapses (OCS = 51.8%, IVMP = 38.6%), followed by IVIG (6.0%), RCI (2.2%) and PMP (1.5%). The proportion of patients achieving relapse resolution with their first treatment was 90.5% with OCS (n = 5710), 47.8% with IVMP ± OCS (n = 3425), 96.9% with RCI (n = 195), 50.7% with PMP (n = 73), and 43.9% with IVIG (n = 171). Among continuously enrolled patients (n = 373), relapse resolution was 95.7% with RCI (n = 232) and 66.0% with PMP/IVIG (n = 141); significant cohort differences were observed. Conclusions As demonstrated in other studies, OCS were generally effective. However, real-world effectiveness varied with other treatments. Relapse resolution of the first treatment with OCS was higher than with IVMP ± OCS; similarly, relapse resolution was higher with RCI as the first treatment than with PMP/IVIG. Results demonstrate RCI’s effectiveness in appropriate patients. Limitations pertaining to claims-based research apply. Funding Mallinckrodt Pharmaceuticals (Bedminster, NJ).

Purpose To compare patients with atrial fibrillation (AF) initiating direct oral anticoagulants (DOACs) versus warfarin on clinical outcomes including stroke, systemic embolism (SE), bleeding events, and cost of care. Methods This retrospective observational study used Medicare Advantage Prescription Drug and fully insured commercial claims from the Humana Research Database. Patients with AF who initiated a DOAC or warfarin from January 1, 2012, through September 30, 2015, were included. Date of the first prescription of DOAC or warfarin was the index date. Patients in the DOAC and warfarin groups were matched on propensity scores. Patients were censored at end of enrollment or study period, discontinuation, or switch of index medication. Clinical outcomes were compared in the matched groups using Cox proportional hazards models. Annualized costs and costs adjusted for censoring using Lin's interval method were also compared between the two cohorts. Results Patients on DOACs had a significantly lower risk of ischemic stroke (hazard ratio [HR], 0.88; 95% confidence interval [CI], 0.79-0.98), hemorrhagic stroke (HR, 0.65; CI, 0.46-0.92), SE (HR, 0.53; 95% CI, 0.43-0.65), and composite outcome of stroke or SE (HR, 0.78; 95% CI, 0.71-0.86) compared with patients on warfarin. Bleeding risk was not statistically significant (HR, 0.85; 95% CI, 0.71-1.01). While annualized pharmacy costs were higher, annualized medical and total costs were lower in the DOAC group compared with the warfarin group. Conclusion The results of the study indicated that patients on DOACs had lower rates of ischemic stroke, hemorrhagic stroke, SE, and composite outcome of stroke or SE compared with patients on warfarin. No significant differences in bleeding rates between the DOAC and warfarin groups were observed, while total cost of care was lower in the DOAC group.

Background A majority of diabetic kidney disease (DKD) patients receive medical care in the primary care setting, making it an important opportunity to improve patient management. There is limited evidence evaluating whether primary care physicians (PCPs) are equipped to effectively manage these patients in routine clinical practice. The present study was undertaken to identify gaps in primary care and unmet needs in the diagnosis and monitoring of DKD in type 2 diabetes (T2D) patients among PCPs. Methods This was a qualitative analysis based on 30–45-min interviews with PCPs treating T2D patients. PCPs were recruited via email and were board-certified, in practice for more than 3 years, spent most of their time in direct clinical care, and provided care for more than three T2D patients in a week. Descriptive data analysis was conducted to identify and examine themes that were generated by interviews. Two reviewers evaluated interview data to identify themes and developed consensus on the priority themes identified. Results A total of 16 PCPs satisfying the inclusion criteria were recruited for qualitative interviews. Although the PCPs recognized kidney disease as an important comorbidity in T2D patients, testing for kidney disease was not consistently top of mind, with 56% reportedly performing kidney function testing in their T2D patients. PCPs most frequently reported using estimated glomerular filtration rate (eGFR) alone to monitor and stage DKD; only 25% PCPs reported testing for albuminuria. Most PCPs incorrectly believed that a majority of DKD patients are diagnosed in early stages. Also, early stages of DKD emerged as ambiguous areas of decision-making, wherein treatments prescribed greatly varied among PCPs. Lastly, early and accurate risk stratification of DKD patients emerged as the most important unmet need; which, if it could be overcome, was consistently identified by PCPs as a key to monitoring, appropriate nephrologist referrals, and intervening to improve outcomes in patients with DKD. Conclusions Our study highlights important unmet needs in T2D DKD testing, staging, and stratification in the PCP setting that limit effective patient care. Health systems and insurers in the U.S. should prioritize the review and approval of new strategies that can improve DKD staging and risk stratification.

Aim To evaluate the U.S. payer budget-impact of KidneyIntelX, an artificial intelligence-enabled in vitro diagnostic to predict kidney function decline in Type 2 Diabetic Kidney Disease (T2DKD) patients, stages 1-3b. Materials and methods We developed an Excel-based model according to International Society of Pharmacoeconomics and Outcomes Research (ISPOR) good practices to assess U.S. payer budget impact associated with the use of the KidneyIntelX test to optimize therapy T2DKD patients compared to standard of care (SOC) (without KidneyIntelX). A hypothetical cohort of 100,000 stages 1-3b T2DKD patients was followed for 5 years. Peer-reviewed publications were used to identify model parameter estimates. KidneyIntelX costs incremental to SOC (without KidneyIntelX) included test cost, additional prescription medication use, specialist referrals and PCP office visits. Patients managed with KidneyIntelX experienced a 20% slowed progression rate compared to SOC (without KidneyIntelX) attributed to slowed DKD progression, delayed or prevented dialysis and transplants, and reduced dialysis crashes. Associated costs were compared to SOC (without KidneyIntelX). Sensitivity analyses were conducted by varying the definition of progression and the DKD progression rate associated with KidneyIntelX testing and related interventions. Results Projected undiscounted base case 5-year savings for 100,000 patients tested with KidneyIntelX were $1.052 billion, attributed mostly to slowed progression through DKD stages. The breakeven point for the health plan adopting KidneyIntelX is expected to occur prior to year 2 after adoption. Sensitivity analysis based on the assessment of the most conservative definition of progression and a 5% reduction in progression rate attributed to KidneyIntelX, resulted in a projected 5-year savings of $145 million associated with KidneyIntelX. Limitations and conclusions Limitations included reliance on literature-based parameter estimates, including effect size of delayed progression supported by the literature. Incorporating KidneyIntelX in contemporary care of early-stage T2DKD patients is projected to result in substantial savings to payers.

Aim: To compare adherence, healthcare utilization and costs among real world, Medicare-eligible patients with schizophrenia using long-acting injectable paliperidone palmitate (PP) versus oral atypical antipsychotics. Patients & methods: Historical cohort study used Medicare Advantage claims data. Inverse probability of treatment weighting was applied to adjust for baseline differences. 12-month adherence, healthcare utilization and costs were compared. Results: Patients using PP were more adherent (proportion of days covered ≥0.8; 48.1 vs 32.6%; p Conclusion: Compared with patients using oral atypical antipsychotics, PP had lower hospitalizations and medical costs with greater medication adherence accompanied by higher pharmacy costs.

Statistical shape modeling (SSM) was used to quantify 3D variation and morphologic differences between femurs with and without cam femoroacetabular impingement (FAI). 3D surfaces were generated from CT scans of femurs from 41 controls and 30 cam FAI patients. SSM correspondence particles were optimally positioned on each surface using a gradient descent energy function. Mean shapes for groups were defined. Morphological differences between group mean shapes and between the control mean and individual patients were calculated. Principal component analysis described anatomical variation. Among all femurs, the first six modes (or principal components) captured significant variations, which comprised 84% of cumulative variation. The first two modes, which described trochanteric height and femoral neck width, were significantly different between groups. The mean cam femur shape protruded above the control mean by a maximum of 3.3 mm with sustained protrusions of 2.5-3.0 mm along the anterolateral head- neck junction/distal anterior neck. SSM described variations in femoral morphology that corresponded well with areas prone to damage. Shape variation described by the first two modes may facilitate objective characterization of cam FAI deformities; variation beyond may be inherent population variance. SSM could characterize disease severity and guide surgical resection of bone. 2013 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 31:1620-1626, 2013

Individuals with multiple osteochondromas (MO) demonstrate shortened long bones. Ext1 or Ext2 haploinsufficiency cannot recapitulate the phenotype in mice. Loss of heterozygosity for Ext1 may induce shortening by steal of longitudinal growth into osteochondromas or by a general derangement of physeal signaling. We induced osteochondromagenesis at different time points during skeletal growth in a mouse genetic model, then analyzed femora and tibiae at 12 weeks using micro-CT and a point-distribution-based shape analysis. Bone lengths and volumes were compared. Metaphyseal volume deviations from normal, as a measure of phenotypic widening, were tested for correlation with length deviations. Mice with osteochondromas had shorter femora and tibiae than controls, more consistently when osteochondromagenesis was induced earlier during skeletal growth. Volumetric metaphyseal widening did not correlate with longitudinal shortening, although some of the most severe shortening was in bones with abundant osteochondromas. Loss of heterozygosity for Ext1 was sufficient to drive bone shortening in a mouse model of MO, but shortening did not correlate with osteochondroma volumetric growth. While a steal phenomenon seems apparent in individual cases, some other mechanism must also be capable of contributing to the short bone phenotype, independent of osteochondroma formation. Clones of chondrocytes lacking functional heparan sulfate must blunt physeal signaling generally, rather than stealing growth potential focally. © 2012 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 31: 651–657, 2013

Prostate cancer is the most common cancer among men, excluding skin cancer. It is diagnosed by histopathology interpretation of Hematoxylin and Eosin (H&E)-stained tissue sections. Gland and nuclei distributions vary with the disease grade, and the morphological features vary with the advance of cancer. A tissue microarray with known disease stages can be used to enable efficient pathology slide image analysis. We focus on an intuitive approach for segmenting such images, using the Hierarchical Self-Organizing Map (HSOM). Our approach introduces the use of unsupervised clustering using both color and texture features, and the use of unsupervised color merging outside of the HSOM framework. The HSOM was applied to segment 109 tissues composed of four tissue clusters: glands, epithelia, stroma, and nuclei. These segmentations were compared with the results of an EM Gaussian clustering algorithm. The proposed method confirms that the self-learning ability and adaptability of the HSOM, coupled with the information fusion mechanism of the hierarchical network, leads to superior segmentation results for tissue images.