Association of Medication Treatment for Opioid Use Disorder With Suicide Mortality.

OBJECTIVE: Understanding the effectiveness of medication treatment for opioid use disorder to decrease the risk of suicide mortality may inform clinical and policy decisions. The authors sought to describe the effect of medications for opioid use disorder (MOUD) on risk of suicide mortality. METHODS: This was a retrospective cohort study in Department of Veterans Affairs (VA) patients from 2003 to 2017. The authors linked three data sources: the VA Corporate Data Warehouse, Centers for Medicare and Medicaid Services Claims Data, and the VA-Department of Defense Mortality Data Repository. The exposure of interest was MOUD, including starting periods (first 14 days on treatment), stopping periods (first 14 days off treatment), stable time on treatment, and stable time off treatment (reference category). The main outcome measures included suicide mortality, external-cause mortality, and all-cause mortality in the 5 years following initiation of MOUD. RESULTS: Over 60,000 VA patients received MOUD. Patients were typically male (92.8%) and their mean age was 46.5 years (SD=13.1). After adjusting for demographic characteristics, mental health and physical health conditions, and health care utilization, the adjusted hazard ratio during stable MOUD was 0.45 (95% CI=0.32, 0.63) for suicide mortality, 0.35 (95% CI=0.31, 0.40) for external-cause mortality, and 0.34 (95% CI=0.31, 0.37) for all-cause mortality. MOUD starting periods were associated with an adjusted hazard ratio for suicide mortality of 0.55 (95% CI=0.25, 1.21), and MOUD stopping periods were associated with an adjusted hazard ratio for suicide mortality of 1.38 (95% CI=0.82, 2.34). CONCLUSIONS: Treatment with MOUD was associated with a substantial reduction in suicide mortality as well external causes of mortality and all-cause mortality.

Recent trends in the rural-urban suicide disparity among veterans using VA health care.

There is an elevated risk of suicide among people living in rural areas, and the rural-urban disparity in death by suicide is growing in the general United States population. The department of Veterans Affairs (VA) implemented programs targeting rural health in 2007 and suicide prevention in 2008. Rural-urban differences in suicide rates among VA users have not been examined since 2010. We sought to understand whether the rural-urban disparity in suicide risk among VA users decreased during a time of contemporaneous VA efforts to improve access to mental health care for rural Veterans and to improve the effectiveness of mental health services at preventing suicide. We performed a retrospective cohort study examining differences in the raw and adjusted annual suicide rate among rural and urban VA users between 2003 and 2017. All VHA users 2003-2017. Descriptive statistics are presented for all VHA users in 2017. This includes 6,120,355 unique VA users, 32.0% (n = 1,955,935) of whom lived at a rural address. Raw rates of death by suicide were higher in rural VA users than urban VA users overall (33.3 vs. 29.1 deaths per 100,000 population) and across years, but the age, sex, and race-adjusted rates converged in 2005. White VA users had over triple the rate of death by suicide as black VA users, and lived disproportionally in rural areas. The rural-urban suicide disparity among VA users persists. However, the disparity appears to be driven by differences in the racial composition of rural and urban patients, which were not accounted for in prior studies.

Natural language processing of clinical mental health notes may add predictive value to existing suicide risk models.

BACKGROUND: This study evaluated whether natural language processing (NLP) of psychotherapy note text provides additional accuracy over and above currently used suicide prediction models. METHODS: We used a cohort of Veterans Health Administration (VHA) users diagnosed with post-traumatic stress disorder (PTSD) between 2004-2013. Using a case-control design, cases (those that died by suicide during the year following diagnosis) were matched to controls (those that remained alive). After selecting conditional matches based on having shared mental health providers, we chose controls using a 5:1 nearest-neighbor propensity match based on the VHA's structured Electronic Medical Records (EMR)-based suicide prediction model. For cases, psychotherapist notes were collected from diagnosis until death. For controls, psychotherapist notes were collected from diagnosis until matched case's date of death. After ensuring similar numbers of notes, the final sample included 246 cases and 986 controls. Notes were analyzed using Sentiment Analysis and Cognition Engine, a Python-based NLP package. The output was evaluated using machine-learning algorithms. The area under the curve (AUC) was calculated to determine models' predictive accuracy. RESULTS: NLP derived variables offered small but significant predictive improvement (AUC = 0.58) for patients that had longer treatment duration. A small sample size limited predictive accuracy. CONCLUSIONS: Study identifies a novel method for measuring suicide risk over time and potentially categorizing patient subgroups with distinct risk sensitivities. Findings suggest leveraging NLP derived variables from psychotherapy notes offers an additional predictive value over and above the VHA's state-of-the-art structured EMR-based suicide prediction model. Replication with a larger non-PTSD specific sample is required.

Global assessment of its network dynamics reveals that the kinase Plk1 inhibits the phosphatase PP6 to promote Aurora A activity.

Polo-like kinase 1 (Plk1) is an essential protein kinase that promotes faithful mitotic progression in eukaryotes. The subcellular localization and substrate interactions of Plk1 are tightly controlled and require its binding to phosphorylated residues. To identify phosphorylation-dependent interactions within the Plk1 network in human mitotic cells, we performed quantitative proteomics on HeLa cells cultured with kinase inhibitors or expressing a Plk1 mutant that was deficient in phosphorylation-dependent substrate binding. We found that many interactions were abolished upon kinase inhibition; however, a subset was protected from phosphatase opposition or was unopposed, resulting in persistent interaction of the substrate with Plk1. This subset includes phosphoprotein phosphatase 6 (PP6), whose activity toward Aurora kinase A (Aurora A) was inhibited by Plk1. Our data suggest that this Plk1-PP6 interaction generates a feedback loop that coordinates and reinforces the activities of Plk1 and Aurora A during mitotic entry and is terminated by the degradation of Plk1 during mitotic exit. Thus, we have identified a mechanism for the previously puzzling observation of the Plk1-dependent regulation of Aurora A.

Mapping disease at an approximated individual level using aggregate data: a case study of mapping New Hampshire birth defects.

BACKGROUND: Limited by data availability, most disease maps in the literature are for relatively large and subjectively-defined areal units, which are subject to problems associated with polygon maps. High resolution maps based on objective spatial units are needed to more precisely detect associations between disease and environmental factors. METHOD: We propose to use a Restricted and Controlled Monte Carlo (RCMC) process to disaggregate polygon-level location data to achieve mapping aggregate data at an approximated individual level. RCMC assigns a random point location to a polygon-level location, in which the randomization is restricted by the polygon and controlled by the background (e.g., population at risk). RCMC allows analytical processes designed for individual data to be applied, and generates high-resolution raster maps. RESULTS: We applied RCMC to the town-level birth defect data for New Hampshire and generated raster maps at the resolution of 100 m. Besides the map of significance of birth defect risk represented by p-value, the output also includes a map of spatial uncertainty and a map of hot spots. CONCLUSIONS: RCMC is an effective method to disaggregate aggregate data. An RCMC-based disease mapping maximizes the use of available spatial information, and explicitly estimates the spatial uncertainty resulting from aggregation.

Assessment of the changes in 9L and C6 glioma pO2 by EPR oximetry as a prognostic indicator of differential response to radiotherapy.

Tumor hypoxia impedes the outcome of radiotherapy. As the extent of hypoxia in solid tumors varies during the course of radiotherapy, methods that can provide repeated assessment of tumor pO2 such as EPR oximetry may enhance the efficacy of radiotherapy by scheduling irradiations when the tumors are oxygenated. The repeated measurements of tumor pO2 may also identify responders, and thereby facilitate the design of better treatment plans for nonresponding tumors. We have investigated the temporal changes in the ectopic 9L and C6 glioma pO2 irradiated with single radiation doses less than 10 Gy by EPR oximetry. The 9L and C6 tumors were hypoxic with pO2 of approximately 5-9 mmHg. The pO2 of C6 tumors increased significantly with irradiation of 4.8-9.3 Gy. However, no change in the 9L tumor pO2 was observed. The irradiation of the oxygenated C6 tumors with a second dose of 4.8 Gy resulted in a significant delay in growth compared to hypoxic and 2 Gy × 5 treatment groups. The C6 tumors with an increase in pO2 of greater than 50% from the baseline of irradiation with 4.8 Gy (responders) had a significant tumor growth delay compared to nonresponders. These results indicate that the ectopic 9L and C6 tumors responded differently to radiotherapy. We propose that the repeated measurement of the oxygen levels in the tumors during radiotherapy can be used to identify responders and to design tumor oxygen guided treatment plans to improve the outcome.

RESPECT-PTSD: re-engineering systems for the primary care treatment of PTSD, a randomized controlled trial.

BACKGROUND: Although collaborative care is effective for treating depression and other mental disorders in primary care, there have been no randomized trials of collaborative care specifically for patients with Posttraumatic stress disorder (PTSD). OBJECTIVE: To compare a collaborative approach, the Three Component Model (3CM), with usual care for treating PTSD in primary care. DESIGN: The study was a two-arm, parallel randomized clinical trial. PTSD patients were recruited from five primary care clinics at four Veterans Affairs healthcare facilities and randomized to receive usual care or usual care plus 3CM. Blinded assessors collected data at baseline and 3-month and 6-month follow-up. PARTICIPANTS: Participants were 195 Veterans. Their average age was 45 years, 91% were male, 58% were white, 40% served in Iraq or Afghanistan, and 42% served in Vietnam. INTERVENTION: All participants received usual care. Participants assigned to 3CM also received telephone care management. Care managers received supervision from a psychiatrist. MAIN MEASURES: PTSD symptom severity was the primary outcome. Depression, functioning, perceived quality of care, utilization, and costs were secondary outcomes. KEY RESULTS: There were no differences between 3CM and usual care in symptoms or functioning. Participants assigned to 3CM were more likely to have a mental health visit, fill an antidepressant prescription, and have adequate antidepressant refills. 3CM participants also had more mental health visits and higher outpatient pharmacy costs. CONCLUSIONS: Results suggest the need for careful examination of the way that collaborative care models are implemented for treating PTSD, and for additional supports to encourage primary care providers to manage PTSD.

Breast cancer stage at diagnosis and geographic access to mammography screening (New Hampshire, 1998-2004).

INTRODUCTION: Early detection of breast cancer by screening mammography aims to increase treatment options and decrease mortality. Recent studies have shown inconsistent results in their investigations of the possible association between travel distance to mammography and stage of breast cancer at diagnosis. OBJECTIVE: The purpose of the study was to investigate whether geographic access to mammography screening is associated with the stage at breast cancer diagnosis. METHODS: Using the state's population-based cancer registry, all female residents of New Hampshire aged > or =40 years who were diagnosed with breast cancer during 1998-2004 were identified. The factors associated with early stage (stages 0 to 2) or later stage (stages 3 and 4) diagnosis of breast cancer were compared, with emphasis on the distance a woman lived from the closest mammography screening facility, and residence in rural and urban locations. RESULTS: A total of 5966 New Hampshire women were diagnosed with breast cancer during 1998-2004. Their mean driving distance to the nearest mammography facility was 8.85 km (range 0-44.26; 5.5 miles, range 0-27.5), with a mean estimated travel time of 8.9 min (range 0.0-42.2). The distribution of travel distance (and travel time) was substantially skewed to the right: 56% of patients lived within 8 km (5 miles) of a mammography facility, and 65% had a travel time of less than 10 min. There was no significant association between later stage of breast cancer and travel time to the nearest mammography facility. Using 3 categories of rural/urban residence based on Rural Urban Commuting Area classification, no significant association between rural residence and stage of diagnosis was found. New Hampshire women were more likely to be diagnosed with breast cancer at later stages if they lacked private health insurance (p<0.001), were not married (p<0.001), were older (p<0.001), and there was a borderline association with diagnosis during non-winter months (p=0.074). CONCLUSIONS: Most women living in New Hampshire have good geographical access to mammography, and no indication was found that travel time or travel distance to mammography significantly affected stage at breast cancer diagnosis. Health insurance, age and marital status were the major factors associated with later stage breast cancer. The study contributes to an ongoing debate over geographic access to screening mammography in different states, which have given contradictory results. These inconsistencies in the rural health literature highlight a need to understand the complexity of defining rural and urban residence; to characterize more precisely the issues that contribute to good preventive care in different rural communities; and to appreciate the efforts already made in some rural states to provide good geographic access to preventive care. In New Hampshire, specific subgroups such as the uninsured and the elderly remain at greatest risk of being diagnosed with later stage breast cancer and may benefit from targeted interventions to improve early detection.