Human Pharmacokinetic and CYP3A Drug-Drug Interaction Prediction of GDC-2394 Using Physiologically Based Pharmacokinetic Modeling and Biomarker Assessment.

Physiologically based pharmacokinetic (PBPK) modeling was used to predict the human pharmacokinetics and drug-drug interaction (DDI) of GDC-2394. PBPK models were developed using in vitro and in vivo data to reflect the oral and intravenous PK profiles of mouse, rat, dog, and monkey. The learnings from preclinical PBPK models were applied to a human PBPK model for prospective human PK predictions. The prospective human PK predictions were within 3-fold of the clinical data from the first-in-human study, which was used to optimize and validate the PBPK model and subsequently used for DDI prediction. Based on the majority of PBPK modeling scenarios using the in vitro CYP3A induction data (mRNA and activity), GDC-2394 was predicted to have no-to-weak induction potential at 900 mg twice daily (BID). Calibration of the induction mRNA and activity data allowed for the convergence of DDI predictions to a narrower range. The plasma concentrations of the 4ß-hydroxycholesterol (4ß-HC) were measured in the multiple ascending dose study to assess the hepatic CYP3A induction risk. There was no change in plasma 4ß-HC concentrations after 7 days of GDC-2394 at 900 mg BID. A dedicated DDI study found that GDC-2394 has no induction effect on midazolam in humans, which was reflected by the totality of predicted DDI scenarios. This work demonstrates the prospective utilization of PBPK for human PK and DDI prediction in early drug development of GDC-2394. PBPK modeling accompanied with CYP3A biomarkers can serve as a strategy to support clinical pharmacology development plans. SIGNIFICANCE STATEMENT: This work presents the application of physiologically based pharmacokinetic modeling for prospective human pharmacokinetic (PK) and drug-drug interaction (DDI) prediction in early drug development. The strategy taken in this report represents a framework to incorporate various approaches including calibration of in vitro induction data and consideration of CYP3A biomarkers to inform on the overall CYP3A-related DDI risk of GDC-2394.

Community, Hospital, and Patient Factors Contributing to Ethnoracial Disparities in Follow-Up After Psychiatric Hospitalization.

OBJECTIVE: This study used an ecosocial perspective to examine ethnoracial disparities in timely outpatient follow-up care after psychiatric hospitalization in a cohort of Medicaid recipients. METHODS: This retrospective analysis used 2012-2013 New York State Medicaid claims data for 17,488 patients ages <65 years who were treated in hospital psychiatric units and discharged to the community. Claims data were linked to other administrative data sets capturing key social conditions and determinants of mental health for non-Latinx White (White hereafter), non-Latinx Black (Black), Latinx, non-Latinx Asian/Pacific Islander (Asian/Pacific Islander), non-Latinx American Indian or Native Alaskan (American Indian or Native Alaskan), and other ethnoracial groups. Regression models were used to estimate the variations in disparities in timely follow-up care that were attributable to community, organization (i.e., hospital), and individual patient characteristics. RESULTS: Overall, 60.1% of patients attended an outpatient mental health visit within 30 days of discharge. Compared with the rate for White patients, the attendance rates were 9.5 percentage points lower for Black patients and 7.8 percentage points higher for Asian/Pacific Islander patients. No significant difference in attendance rates was found between Latinx and White patients. Community factors, specifically urban versus rural classification and county poverty status, accounted for the greatest variation in timely follow-up care in all comparisons. CONCLUSIONS: Efforts to increase connection to outpatient mental health follow-up care after psychiatric hospitalization should incorporate cultural and structural competencies to address social conditions and determinants of mental health that underly ethnoracial disparities.

Gap in Willingness and Access to Video Visit Use Among Older High-risk Veterans: Cross-sectional Study.

BACKGROUND: The recent shift to video care has exacerbated disparities in health care access, especially among high-need, high-risk (HNHR) adults. Developing data-driven approaches to improve access to care necessitates a deeper understanding of HNHR adults' attitudes toward telemedicine and technology access. OBJECTIVE: This study aims to identify the willingness, access, and ability of HNHR veterans to use telemedicine for health care. METHODS: WWe designed a questionnaire conducted via mail or telephone or in person. Among HNHR veterans who were identified using predictive modeling with national Veterans Affairs data, we assessed willingness to use video visits for health care, access to necessary equipment, and comfort with using technology. We evaluated physical health, including frailty, physical function, performance of activities of daily living (ADL) and instrumental ADL (IADL); mental health; and social needs, including Area Deprivation Index, transportation, social support, and social isolation. RESULTS: The average age of the 602 HNHR veteran respondents was 70.6 (SD 9.2; range 39-100) years; 99.7% (600/602) of the respondents were male, 61% (367/602) were White, 36% (217/602) were African American, 17.3% (104/602) were Hispanic, 31.2% (188/602) held at least an associate degree, and 48.2% (290/602) were confident filling medical forms. Of the 602 respondents, 327 (54.3%) reported willingness for video visits, whereas 275 (45.7%) were unwilling. Willing veterans were younger (P<.001) and more likely to have an associate degree (P=.002), be health literate (P<.001), live in socioeconomically advantaged neighborhoods (P=.048), be independent in IADLs (P=.02), and be in better physical health (P=.04). A higher number of those willing were able to use the internet and email (P<.001). Of the willing veterans, 75.8% (248/327) had a video-capable device. Those with video-capable technology were younger (P=.004), had higher health literacy (P=.01), were less likely to be African American (P=.007), were more independent in ADLs (P=.005) and IADLs (P=.04), and were more adept at using the internet and email than those without the needed technology (P<.001). Age, confidence in filling forms, general health, and internet use were significantly associated with willingness to use video visits. CONCLUSIONS: Approximately half of the HNHR respondents were unwilling for video visits and a quarter of those willing lacked requisite technology. The gap between those willing and without requisite technology is greater among older, less health literate, African American veterans; those with worse physical health; and those living in more socioeconomically disadvantaged neighborhoods. Our study highlights that HNHR veterans have complex needs, which risk being exacerbated by the video care shift. Although technology holds vast potential to improve health care access, certain vulnerable populations are less likely to engage, or have access to, technology. Therefore, targeted interventions are needed to address this inequity, especially among HNHR older adults.

Green Remanufacturer's Mixed Collection Channel Strategy Considering Enterprise's Environmental Responsibility and the Fairness Concern in Reverse Green Supply Chain.

In reverse green supply chain, the mixed collection channel strategy of green remanufacturer is analyzed by building a dynamic game model in which we consider that the green remanufacturer undertakes the environmental responsibility and the green collector shows strong fairness concern for the profit. We analyze the impact of the environmental responsibility level of the green remanufacturer, the preference coefficient of the green remanufacturer, the fairness concern coefficient of the green collector, and the coefficient of cross collection price on optimal decision and profit of the green remanufacturer. The result shows that (1) the green remanufacturer can further improve the collection price, so that it makes many more customers participate in the collection activity; (2) the green remanufacturer pays more attention to fulfill the environmental responsibility, which will increase the intensity of collection of the waste green product, and improve the collection price, as the old green product's remanufacturing cost is lower than the production cost of the new product, and it can improve the green remanufacturer's profits; (3) the green remanufacturer's profit in the mixed collection channel is higher than those in online or offline collection channels.

A Modified Hybrid Wald's Approximation Method for Efficient Covariate Selection in Population Pharmacokinetic Analysis.

One important objective of population pharmacokinetic (PPK) analyses is to identify and quantify relationships between covariates and model parameters such as clearance and volume. To improve upon existing covariate model development methods including stepwise procedures and Wald's approximation method (WAM), this paper introduces an innovative method named the hybrid first-order conditional estimation (FOCE)/Monte-Carlo parametric expectation maximization (MCPEM)-based Wald's approximation method with backward elimination (BE), or H-WAM-BE. Compared with WAM, this new method uses MCPEM to obtain full covariance matrix after running FOCE to obtain full model parameter estimates, followed by BE to select the final covariate model. Two groups of datasets (simulation datasets and rituximab datasets) were used to compare the performance of H-WAM-BE with two other methods, likelihood ratio test (LRT)-based stepwise covariate method (SCM) and H-WAM with full subset approach (H-WAM-F) in NONMEM. Different scenarios with different sample sizes and sampling schemes were used for simulating datasets. The nominal model was used as the reference to evaluate the three methods for their ability to accurately identify parameter-covariate relationships. The methods were compared using the number of true and false positive covariates identified, number of times that they identified the reference model, computation times, and predictive performance. Best-performing H-WAM-BE methods (M2 and M4) showed comparable results with LRT-based SCM. H-WAM-BE required shorter or comparable computation times than LRT-based SCM and H-WAM-F regardless of the model structure, sample size, or sampling design used in this study.

Medical comorbid diagnoses among adult psychiatric inpatients.

OBJECTIVE: Shortened life expectancy of people with mental disorders has been attributed to medical comorbidities, yet these conditions remain under-recognized and under-treated. This study characterizes the medical demands placed on inpatient psychiatric units to help guide medical assessment and management practices in these settings. METHODS: Medicaid claims records and clinician data were linked with hospital and regional data for individuals with a principal diagnosis of any mental disorder admitted to psychiatric inpatient units in New York State from 2012 to 2013. A modified Elixhauser Comorbidity Index (ECI) score was calculated for each unique individual (n = 14,458). Adjusted odds ratios (AORs) of having a medical comorbidity were calculated using logistic regression analyses. RESULTS: 74.9% of psychiatric inpatients had at least one medical comorbidity, including 57.5% of people ages 18-24. Higher rates of medical comorbidity were associated with older age, female gender, non-schizophrenia diagnoses, and engagement in care prior to hospitalization. Patients with medical comorbidities had lower odds (AOR 0.54; 99% CI 0.35-0.83) of being treated in hospitals with 100 or more total beds compared to smaller hospitals. CONCLUSIONS: A high prevalence of common medical diagnoses among psychiatric inpatients underscores the importance of adequate detection and medical treatment of medical comorbidities in psychiatric inpatient settings.

Using medical claims database to develop a population disease progression model for leuprorelin-treated subjects with hormone-sensitive prostate cancer.

Androgen deprivation therapy (ADT) is a widely used treatment for patients with hormone-sensitive prostate cancer (PCa). However, duration of treatment response varies, and most patients eventually experience disease progression despite treatment. Leuprorelin is a luteinizing hormone-releasing hormone (LHRH) agonist, a commonly used form of ADT. Prostate-specific antigen (PSA) is a biomarker for monitoring disease progression and predicting treatment response and survival in PCa. However, time-dependent profile of tumor regression and growth in patients with hormone-sensitive PCa on ADT has never been fully characterized. In this analysis, nationwide medical claims database provided by Humana from 2007 to 2011 was used to construct a population-based disease progression model for patients with hormone-sensitive PCa on leuprorelin. Data were analyzed by nonlinear mixed effects modeling utilizing Monte Carlo Parametric Expectation Maximization (MCPEM) method in NONMEM. Covariate selection was performed using a modified Wald's approximation method with backward elimination (WAM-BE) proposed by our group. 1113 PSA observations from 264 subjects with malignant PCa were used for model development. PSA kinetics were well described by the final covariate model. Model parameters were well estimated, but large between-patient variability was observed. Hemoglobin significantly affected proportion of drug-resistant cells in the original tumor, while baseline PSA and antiandrogen use significantly affected treatment effect on drug-sensitive PCa cells (Ds). Population estimate of Ds was 3.78 x 10-2 day-1. Population estimates of growth rates for drug-sensitive (Gs) and drug-resistant PCa cells (GR) were 1.96 x 10-3 and 6.54 x 10-4 day-1, corresponding to a PSA doubling time of 354 and 1060 days, respectively. Proportion of the original PCa cells inherently resistant to treatment was estimated to be 1.94%. Application of population-based disease progression model to clinical data allowed characterization of tumor resistant patterns and growth/regression rates that enhances our understanding of how PCa responds to ADT.

Relationship Between Continuity of Care and Discharge Planning After Hospital Psychiatric Admission.

OBJECTIVE: This study examined whether communication between inpatient and outpatient mental health providers during patients' inpatient stays was associated with whether patients attended postdischarge appointments. METHODS: Psychiatric inpatient medical records of 189 Medicaid recipients at two hospitals were reviewed to document whether inpatient staff had communicated with current or prior outpatient providers. Medicaid claims provided demographic, clinical, and outpatient attendance data. Associations between provider communications and follow-up care for patients who had or had not received outpatient mental health care within the 30 days prior to admission were evaluated. RESULTS: Inpatient staff communicated with outpatient providers for 118 (62%) patients. For patients who had not received outpatient care within 30 days of admission, compared with those who had, communication was associated with increased odds of attending timely outpatient appointments (odds ratio=2.73, 95% confidence interval=1.09-6.84). CONCLUSIONS: Communication with outpatient providers may be especially important for patients who were not engaged in outpatient care prior to admission.

Family Involvement in Psychiatric Hospitalizations: Associations With Discharge Planning and Prompt Follow-Up Care.

OBJECTIVE: Involving family in the care of inpatients with serious mental illness is known to be beneficial. This study examined frequencies of involvement by family in the care and discharge planning for 179 psychiatric inpatients. METHODS: Involvement by family in care and discharge planning was assessed from randomly selected medical records of inpatients with Medicaid and severe mental illness at two New York hospitals from 2012 to 2013. "Family" also included anyone close to the patient who provided support. Medicaid claims were reviewed for patient demographic and clinical characteristics and for postdischarge outpatient attendance data. Multiple regression models were used to test whether involvement by family was associated with comprehensive discharge planning (contacting outpatient providers, scheduling follow-up appointments, and forwarding a discharge summary to a provider) and initiation of outpatient treatment. RESULTS: Inpatient staff contacted a family member for 134 (75%) patients. Sixty-seven (37%) patients received comprehensive discharge planning, and 96 (53%) and 139 (78%) attended an outpatient appointment within 7 and 30 days of discharge, respectively. Inpatient staff contacting family, communicating about the patient's health and/or mental health, and communicating about the discharge plan were significantly associated with entry into follow-up care by 7 and 30 days postdischarge. Family phone calls and/or visits with patients, attendance at family therapy sessions, and communication with inpatient staff about services available to families were significantly associated with patients receiving comprehensive discharge planning. When analyses controlled for demographic and clinical factors, having any involvement between family members and inpatient staff was significantly associated with patients' attending an outpatient appointment by 7 days (odds ratio [OR]=2.79, 95% confidence interval [CI]=1.28-6.08) or 30 days (OR=3.07, 95% CI=1.29-7.32) after discharge. CONCLUSIONS: The association of family involvement with comprehensive discharge planning and prompt entry into outpatient care underscores the importance of family contact and communication with staff during inpatient hospitalizations.

[Built-up land change and its impact on ecological quality in a fast-growing economic zone: Jinjiang County, Fujian Province, China]. / ç»æµŽå¿«é€Ÿå¢žé•¿åŒºå»ºç­‘ç”¨åœ°å˜åŒ–åŠå ¶å¯¹ç”Ÿæ€è´¨é‡çš„å½±å“­­ä»¥ç¦å»ºæ™‹æ±Ÿä¸ºä¾‹.

Since China's reform and opening-up, the rapid growth of China's economy has greatly accelerated the expansion of built-up land, which has affected regional ecological environment to a great extent. Taking Jinjiang County of Fujian Province, one of the fastest economic-developing counties in the coastal areas of southeastern China, as a case study area, this paper focused on analyzing the rapid built-up land expansion process of the county and its impact on county's ecological quality using remote sensing techniques. Based on two Landsat images of 1996 and 2015 of Jinjiang, the built-up land of the county was extracted using the index-based built-up index (IBI) and its change was analyzed. In the meantime, the ecological status of Jinjiang was evaluated with a recently-proposed remote sensing based ecological index (RSEI) and the relationship between the built-up land dynamics and the ecological status changes of the county was quantitatively examined. The results showed that during the period from 1996 to 2015, the area of built-up land of Jinjiang had a net increase of 68.54 km2, a growth of 45%, and the expansion intensity was 0.55. The expansion of the built-up lands has caused overall degradation of the county's ecological quality. The mean value of RSEI of the county had declined from 0.532 in 1996 to 0.460 in 2015, a drop of13.5%. The area proportion of high ecological-quality grades also significantly fell from 39% in 1996 to 21% in 2015. The built-up land expansion intensity was negatively correlated with the ecological quality change.

Hydroxyurea Use in Young Children With Sickle Cell Anemia in New York State.

INTRODUCTION: This study examined hydroxyurea usage in young children with sickle cell anemia within New York State (NYS). The cohort was 273 children with sickle cell anemia born in NYS in 2006-2009 and enrolled essentially continuously in Medicaid for the first 4 years of life. METHODS: Medicaid data were used to examine hydroxyurea usage in this group by age at first prescription fill, persistence, region, treatment institution, and year. Log-binomial regression models were used to estimate the likelihood of receiving hydroxyurea treatment. Data from birth through 2014 for all members of the study group were assembled and analyzed in 2015. RESULTS: About 25% of the cohort had at least one filled hydroxyurea prescription by their fifth birthday, and nearly 40% by the end of the study period. The mean proportion of days covered for the first year of therapy was 56.3%. Adherence was also assessed by calculating medication possession ratios for individual treatment periods. Slightly more than one third of treated children showed 80% coverage by these measures. There was a consistent, but not statistically significant, trend toward younger age at first fill. Significant regional and treatment center differences in initiation of hydroxyurea use, but not in persistence after initiation, were noted among NYS centers. CONCLUSIONS: Subsequent to clinical studies demonstrating safety, current NYS-wide use of hydroxyurea in young children with sickle cell anemia appears to be widespread and increasing. However, practice differences between treatment centers and inadequate adherence may limit the full disease-modifying effects of hydroxyurea.

Pulsed Direct Current Electrospray: Enabling Systematic Analysis of Small Volume Sample by Boosting Sample Economy.

We had developed pulsed direct current electrospray ionization mass spectrometry (pulsed-dc-ESI-MS) for systematically profiling and determining components in small volume sample. Pulsed-dc-ESI utilized constant high voltage to induce the generation of single polarity pulsed electrospray remotely. This method had significantly boosted the sample economy, so as to obtain several minutes MS signal duration from merely picoliter volume sample. The elongated MS signal duration enable us to collect abundant MS(2) information on interested components in a small volume sample for systematical analysis. This method had been successfully applied for single cell metabolomics analysis. We had obtained 2-D profile of metabolites (including exact mass and MS(2) data) from single plant and mammalian cell, concerning 1034 components and 656 components for Allium cepa and HeLa cells, respectively. Further identification had found 162 compounds and 28 different modification groups of 141 saccharides in a single Allium cepa cell, indicating pulsed-dc-ESI a powerful tool for small volume sample systematical analysis.