Background

Disparities in depression care exist among the poor. Community Partners in Care (CPIC) compared a community coalition model with technical assistance to improve depression services in under-resourced communities. We examine effects on health, social, and utilization outcomes among the poor and, non-poor depressed, and poor subgroups.

Methods

This study analyzed clients living above (n = 268) and below (n = 750) the federal-poverty level and, among the poor, 3 nonoverlapping subgroups: justice-involved (n = 158), homeless and not justice-involved (n = 298), and other poor (n = 294). Matched programs (n = 93) from health and community sectors were randomly assigned to community engagement and planning (CEP) or resources for services (RS). Primary outcomes were poor mental health-related quality of life and 8-item Patient Health Questionnaire scores, whereas community-prioritized and utilization outcomes were secondary. Effects were scrutinized using false discovery rate-adjusted P values to account for multiple comparisons.

Results

In the impoverished group, CEP and RS clients of participating study programs did not differ in primary outcomes, but CEP more than RS improved mental wellness among the depressed poor (unadjusted P = .004) while providing suggestive evidence for other secondary outcomes. Within the poor subgroups, evidence favoring CEP was only suggestive but was strongest among justice-involved clients.

Conclusions

A coalition approach to improving outcomes for low-income clients with depression, particularly those involved in the justice system, may offer additional benefits over standard technical assistance programs.

BACKGROUND: The Veterans Health Administration (VA) has invested substantially in evidence-based mental health care. Yet no electronic performance measures for assessing the level at which the population of Veterans with depression receive appropriate care have proven robust enough to support rigorous evaluation of the VAs depression initiatives. OBJECTIVE: Our objectives were to develop prototype longitudinal electronic population-based measures of depression care quality, validate the measures using expert panel judgment by VA and non-VA experts, and examine detection, follow-up and treatment rates over a decade (2000-2010). We describe our development methodology and the challenges to creating measures that capture the longitudinal course of clinical care from detection to treatment. DESIGN AND PARTICIPANTS: Data come from the National Patient Care Database and Pharmacy Benefits Management Database for primary care patients from 1999 to 2011, from nine Veteran Integrated Service Networks. MEASURES: We developed four population-based quality metrics for depression care that incorporate a 6-month look back and 1-year follow-up: detection of a new episode of depression, 84 and 180 day follow-up, and minimum appropriate treatment 1-year post detection. Expert panel techniques were used to evaluate the measure development methodology and results. Key challenges to creating valid longitudinal measures are discussed. KEY RESULTS: Over the decade, the rates for detection of new episodes of depression remained stable at 7-8 %. Follow-up at 84 and 180 days were 37 % and 45 % in 2000 and increased to 56 % and 63 % by 2010. Minimum appropriate treatment remained relatively stable over the decade (82-84 %). CONCLUSIONS: The development of valid longitudinal, population-based quality measures for depression care is a complex process with numerous challenges. If the full spectrum of care from detection to follow-up and treatment is not captured, performance measures could actually mask the clinical areas in need of quality improvement efforts.

The myeloma bone marrow microenvironment promotes proliferation of malignant plasma cells and resistance to therapy. Activation of JAK/STAT signaling is thought to be a central component of these microenvironment-induced phenotypes. In a prior drug repurposing screen, we identified tofacitinib, a pan-JAK inhibitor Food and Drug Administration (FDA) approved for rheumatoid arthritis, as an agent that may reverse the tumor-stimulating effects of bone marrow mesenchymal stromal cells. Herein, we validated in vitro, in stromal-responsive human myeloma cell lines, and in vivo, in orthotopic disseminated xenograft models of myeloma, that tofacitinib showed efficacy in myeloma models. Furthermore, tofacitinib strongly synergized with venetoclax in coculture with bone marrow stromal cells but not in monoculture. Surprisingly, we found that ruxolitinib, an FDA approved agent targeting JAK1 and JAK2, did not lead to the same anti-myeloma effects. Combination with a novel irreversible JAK3-selective inhibitor also did not enhance ruxolitinib effects. Transcriptome analysis and unbiased phosphoproteomics revealed that bone marrow stromal cells stimulate a JAK/STAT-mediated proliferative program in myeloma cells, and tofacitinib reversed the large majority of these pro-growth signals. Taken together, our results suggest that tofacitinib reverses the growth-promoting effects of the tumor microenvironment. As tofacitinib is already FDA approved, these results can be rapidly translated into potential clinical benefits for myeloma patients.

Enhancing the efficacy of proteasome inhibitors (PI) is a central goal in myeloma therapy. We proposed that signaling-level responses after PI may reveal new mechanisms of action that can be therapeutically exploited. Unbiased phosphoproteomics after treatment with the PI carfilzomib surprisingly demonstrates the most prominent phosphorylation changes on splicing related proteins. Spliceosome modulation is invisible to RNA or protein abundance alone. Transcriptome analysis after PI demonstrates broad-scale intron retention, suggestive of spliceosome interference, as well as specific alternative splicing of protein homeostasis machinery components. These findings lead us to evaluate direct spliceosome inhibition in myeloma, which synergizes with carfilzomib and shows potent anti-tumor activity. Functional genomics and exome sequencing further support the spliceosome as a specific vulnerability in myeloma. Our results propose splicing interference as an unrecognized modality of PI mechanism, reveal additional modes of spliceosome modulation, and suggest spliceosome targeting as a promising therapeutic strategy in myeloma.

Proteasome inhibitor (PI) resistance remains a central challenge in multiple myeloma. To identify pathways mediating resistance, we first mapped proteasome-associated genetic co-dependencies. We identified heat shock protein 70 (HSP70) chaperones as potential targets, consistent with proposed mechanisms of myeloma cells overcoming PI-induced stress. We therefore explored allosteric HSP70 inhibitors (JG compounds) as myeloma therapeutics. JG compounds exhibited increased efficacy against acquired and intrinsic PI-resistant myeloma models, unlike HSP90 inhibition. Shotgun and pulsed SILAC mass spectrometry demonstrated that JGs unexpectedly impact myeloma proteostasis by destabilizing the 55S mitoribosome. Our data suggest JGs have the most pronounced anti-myeloma effect not through inhibiting cytosolic HSP70 proteins but instead through mitochondrial-localized HSP70, HSPA9/mortalin. Analysis of myeloma patient data further supports strong effects of global proteostasis capacity, and particularly HSPA9 expression, on PI response. Our results characterize myeloma proteostasis networks under therapeutic pressure while motivating further investigation of HSPA9 as a specific vulnerability in PI-resistant disease.

We conducted a preregistered multilaboratory project (k = 36; N = 3,531) to assess the size and robustness of ego-depletion effects using a novel replication method, termed the paradigmatic replication approach. Each laboratory implemented one of two procedures that was intended to manipulate self-control and tested performance on a subsequent measure of self-control. Confirmatory tests found a nonsignificant result (d = 0.06). Confirmatory Bayesian meta-analyses using an informed-prior hypothesis (δ = 0.30, SD = 0.15) found that the data were 4 times more likely under the null than the alternative hypothesis. Hence, preregistered analyses did not find evidence for a depletion effect. Exploratory analyses on the full sample (i.e., ignoring exclusion criteria) found a statistically significant effect (d = 0.08); Bayesian analyses showed that the data were about equally likely under the null and informed-prior hypotheses. Exploratory moderator tests suggested that the depletion effect was larger for participants who reported more fatigue but was not moderated by trait self-control, willpower beliefs, or action orientation.