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Objectives: We examined whether an array of scleroderma autoantibodies associates with risk of cancer and could be useful tools for risk stratification. Methods: Scleroderma cancer cases and scleroderma controls without cancer from the Johns Hopkins Scleroderma Center and the University of Pittsburgh Scleroderma Center were studied. Sera were assayed by Lineblot and enzyme‐linked immunosorbent assay (ELISA) for autoantibodies against centromere, topoisomerase 1, RNA polymerase (POLR) 3, PM/Scl, Th/To, NOR90, U3 RNP, Ku, Ro52, U1RNP, and RNPC3. Logistic regression models were constructed to examine whether distinct autoantibodies associated with overall cancer at any time and cancer‐associated scleroderma (cancer occurring three years before and after scleroderma onset). The effects of having more than one autoantibody on cancer were further examined using random forest analysis. Results: A total of 676 cases and 687 controls were studied. After adjusting for relevant covariates, anti‐POLR3 (odds ratio [OR] 1.47, 95% confidence interval [CI] 1.03–2.11) and monospecific anti‐Ro52 (OR 2.19, 95% CI 1.29–3.74) were associated with an increased overall cancer risk, whereas anticentromere (OR 0.69, 95% CI 0.51–0.93) and anti‐U1RNP (OR 0.63, 95% CI 0.43–0.93) were associated with lower risk. When examining risk of cancer‐associated scleroderma, these immune responses remained associated with increased or decreased risk: anti‐POLR3 (OR 2.28, 95% CI 1.33–3.91), monospecific anti‐Ro52 (OR 2.58, 95% CI 1.05–6.30), anticentromere (OR 0.39, 95% CI 0.20–0.74), and anti‐U1RNP (OR 0.32, 95% CI 0.11–0.93). Anti‐Ro52 plus anti‐U1RNP or anti‐Th/To was associated with decreased cancer risk compared with anti‐Ro52 alone. Conclusions: These data suggest that five distinct scleroderma immune responses, alone or in combination, may be useful tools to stratify the risk of cancer for scleroderma patients. Further study examining cancer risk in autoantibody subgroups relative to the general population is warranted. [ABSTRACT FROM AUTHOR]

INTRODUCTION: In addition to the accumulation of amyloid plaques and neurofibrillary tangles, the presence of excess neural activity is a pathological hallmark of Alzheimer's disease (AD) and a prognostic indicator for progression of AD pathology and clinical/cognitive worsening in mild cognitive impairment due to Alzheimer's disease (MCI due to AD). The HOPE4MCI clinical study tested the efficacy of a therapeutic with demonstrated ability to normalize heightened neural activity in the hippocampus in a randomized controlled trial of 78 weeks duration in patients with MCI due to AD. METHODS: One hundred and sixty‐four participants were randomized to placebo (n = 83) or AGB101 (n = 81), an extended‐release formulation of low dose (220 mg) levetiracetam. The primary endpoint was the change in Clinical Dementia Rating Scale Sum of Boxes score (CDR‐SB) comparing follow up at 18 months to baseline. The goal of the primary efficacy analysis was to estimate the difference between the AGB101 and placebo arms in the mean change of the primary endpoint. RESULTS: The mean change in CDR‐SB was estimated to be 1.12 (95% confidence interval [CI]: 0.66, 1.69) for the AGB101 arm and 1.22 (95% CI: 0.75, 1.78) for the placebo arm. The estimated difference between arms is ‐0.10 (95% CI: ‐0.85, 0.58), which was not statistically significant. In a prespecified analysis, the difference was ‐0.45 (95% CI: ‐1.43, 0.53) for ApoE‐4 noncarriers and ‐0.10 (95% CI: ‐0.92, 0.72) for apolipoprotein E (ApoE)‐4 carriers. DISCUSSION: The possibility that ApoE‐4 carriers and noncarriers will respond differently to therapeutic intervention is consistent with recently reported findings from biologics and the present results show further testing of AGB101 in patients with MCI due to AD who are noncarriers of the ApoeE‐4 allele is warranted. Conclusions from the HOPE4MCI study are limited primarily due to the small sample size and results can only be regarded as a guide to future research. [ABSTRACT FROM AUTHOR]

Policy PointsSocial determinants of health are an important predictor of future health care costs.Medicaid must partner with other sectors to address the underlying causes of its beneficiaries' poor health and high health care spending. Context: Social determinants of health are an important predictor of future health care costs but little is known about their impact on Medicaid spending. This study analyzes the role of social determinants of health (SDH) in predicting future health care costs for adult Medicaid beneficiaries with similar past morbidity burdens and past costs. Methods: We enrolled into a prospective cohort study 8,892 adult Medicaid beneficiaries who presented for treatment at an emergency department or clinic affiliated with two hospitals in Washington, DC, between September 2017 and December 31, 2018. We used SDH information measured at enrollment to categorize our participants into four social risk classes of increasing severity. We used Medicaid claims for a 2‐year period; 12 months pre‐ and post‐study enrollment to measure past and future morbidity burden according to the Adjusted Clinical Groups system. We also used the Medicaid claims data to characterize total annual Medicaid costs one year prior to and one year after study enrollment. Results: The 8,892 participants were primarily female (66%) and Black (91%). For persons with similar past morbidity burdens and past costs (p < 0.01), the future morbidity burden was significantly higher in the upper two social risk classes (1.15 and 2.04, respectively) compared with the lowest one. Mean future health care spending was significantly higher in the upper social risk classes compared with the lowest one ($2,713, $11,010, and $17,710, respectively) and remained significantly higher for the two highest social risk classes ($1,426 and $3,581, respectively), given past morbidity burden and past costs (p < 0.01). When we controlled for future morbidity burden (measured concurrently with future costs), social risk class was no longer a significant predictor of future health care costs. Conclusions: SDH are statistically significant predictors of future morbidity burden and future costs controlling for past morbidity burden and past costs. Further research is needed to determine whether current payment systems adequately account for differences in the care needs of highly medically and socially complex patients. [ABSTRACT FROM AUTHOR]

Rationale, Aims and Objectives: In the management of symptomatic bone metastases, current practice guidelines do not provide clear methodology for selecting palliative radiotherapy (RT) regimens based on specific patient and disease features. Decision support aids may offer an effective means for translating the complex data needed to render individualised treatment decisions, yet no such tools are available for use in this setting. Thus, we describe the development of the Bone Metastases Ensemble Trees for Survival‐Decision Support Platform (BMETS‐DSP), which aims to optimise selection of evidence‐based, individualised palliative RT regimens. Method: The Ottawa Decision Support Framework was used as the theoretical basis for development of BMETS‐DSP. First, we utilised stakeholder input and review of the literature to assess determinants underlying the provider decision. Based on this assessment and iterative stakeholder feedback, we developed the web‐based, provider‐facing BMETS‐DSP. Consistent with the underlying theoretical framework, our design also included assessment of decision quality using the International Patient Decision Aids Standards (IPDAS) certification checklist. Results: Stakeholder input and review of 54 evidence‐based publications identified the following determinants of the provider decision: estimated prognosis, characteristics of the target symptomatic lesion and the primary cancer type, consideration of alternative interventions, access to patient‐specific recommendations, and patient preferences. Based on these determinants, we developed the BMETS‐DSP that (1) collects patient‐specific data, (2) displays an individualised predicted survival curve, and (3) provides case‐specific, evidence‐based recommendations regarding RT, open surgery, systemic therapy, and hospice referral to aid in the decision‐making process. The finalised tool met IPDAS quality requirements. Preliminary results of a pilot assessment suggest impact of clinical outcomes. Conclusions: We describe the successful development of a provider‐facing decision support platform to aid in the provision of palliative RT in better alignment with patient and disease features. Impact of the BMETS‐DSP on decision outcomes will be further assessed in a randomised, controlled study. [ABSTRACT FROM AUTHOR]