Basket trials in oncology: a systematic review of practices and methods, comparative analysis of innovative methods, and an appraisal of a missed opportunity.

Background: Basket trials are increasingly used in oncology drug development for early signal detection, accelerated tumor-agnostic approvals, and prioritization of promising tumor types in selected patients with the same mutation or biomarker. Participants are grouped into so-called baskets according to tumor type, allowing investigators to identify tumors with promising responses to treatment for further study. However, it remains a question as to whether and how much the adoption of basket trial designs in oncology have translated into patient benefits, increased pace and scale of clinical development, and de-risking of downstream confirmatory trials. Methods: Innovation in basket trial design and analysis includes methods that borrow information across tumor types to increase the quality of statistical inference within each tumor type. We build on the existing systematic reviews of basket trials in oncology to discuss the current practices and landscape. We conceptually illustrate recent innovative methods for basket trials, with application to actual data from recently completed basket trials. We explore and discuss the extent to which innovative basket trials can be used to de-risk future trials through their ability to aid prioritization of promising tumor types for subsequent clinical development. Results: We found increasing adoption of basket trial design in oncology, but largely in the design of single-arm phase II trials with a very low adoption of innovative statistical methods. Furthermore, the current practice of basket trial design, which does not consider its impact on the clinical development plan, may lead to a missed opportunity in improving the probability of success of a future trial. Gating phase II with a phase Ib basket trial reduced the size of phase II trials, and losses in the probability of success as a result of not using innovative methods may not be recoverable by running a larger phase II trial. Conclusion: Innovative basket trial methods can reduce the size of early phase clinical trials, with sustained improvement in the probability of success of the clinical development plan. We need to do more as a community to improve the adoption of these methods.

Predicting Severe Complications from Cytoreductive Surgery with Hyperthermic Intraperitoneal Chemotherapy: A Data-Driven, Machine Learning Approach to Augment Clinical Judgment.

BACKGROUND: CRS-HIPEC provides oncologic benefit in well-selected patients with peritoneal carcinomatosis; however, it is a morbid procedure. Decision tools for preoperative patient selection are limited. We developed a risk score to predict severity of 90 day complications for cytoreductive surgery with hyperthermic intraperitoneal chemotherapy (CRS-HIPEC). PATIENTS AND METHODS: Adults who underwent CRS-HIPEC at the University of Pittsburgh Medical Center (March 2001-April 2020) were analyzed as part of this study. Primary endpoint was severe complications within 90 days following CRS-HIPEC, defined using Comprehensive Complication Index (CCI) scores as a dichotomous (determined using restricted cubic splines) and continuous variable. Data were divided into training and test sets. Several machine learning and traditional algorithms were considered. RESULTS: For the 1959 CRS-HIPEC procedures included, CCI ranged from 0 to 100 (median 32.0). Adjusted restricted cubic splines model defined severe complications as CCI > 61. A minimum of 20 variables achieved optimal performance of any of the models. Linear regression achieved the highest area under the receiving operator characteristic curve (AUC, 0.74) and outperformed the NSQIP Surgical Risk calculator (AUC 0.80 vs. 0.66). Factors most positively associated with severe complications included peritoneal carcinomatosis index score, symptomatic status, and undergoing pancreatectomy, while American Society of Anesthesiologists 2 class, appendiceal diagnosis, and preoperative albumin were most negatively associated with severe complications. CONCLUSIONS: This study refines our ability to predict severe complications within 90 days of discharge from a hospitalization in which CRS-HIPEC was performed. This advancement is timely and relevant given the growing interest in this procedure and may have implications for patient selection, patient and referring provider comfort, and survival.

Maternal Plasma RNA in First Trimester Nullipara for the Prediction of Spontaneous Preterm Birth ≤ 32 Weeks: Validation Study.

The first-trimester prediction of spontaneous preterm birth (sPTB) has been elusive, and current screening is heavily dependent on obstetric history. However, nullipara lack a relevant history and are at higher risk for spontaneous (s)PTB ≤ 32 weeks compared to multipara. No available objective first-trimester screening test has proven a fair predictor of sPTB ≤ 32 weeks. We questioned whether a panel of maternal plasma cell-free (PCF) RNAs (PSME2, NAMPT, APOA1, APOA4, and Hsa-Let-7g) previously validated at 16-20 weeks for the prediction of sPTB ≤ 32 weeks might be useful in first-trimester nullipara. Sixty (60) nulliparous women (40 with sPTB ≤ 32 weeks) who were free of comorbidities were randomly selected from the King's College Fetal Medicine Research Institute biobank. Total PCF RNA was extracted and the expression of panel RNAs was quantitated by qRT-PCR. The analysis employed, primarily, multiple regression with the main outcome being the prediction of subsequent sPTB ≤ 32 weeks. The test performance was judged by the area under the curve (AUC) using a single threshold cut point with observed detection rates (DRs) at three fixed false positive rates (FPR). The mean gestation was 12.9 ± 0.5 weeks (range 12.0-14.1 weeks). Two RNAs were differentially expressed in women destined for sPTB ≤ 32 weeks: APOA1 (p < 0.001) and PSME2 (p = 0.05). APOA1 testing at 11-14 weeks predicted sPTB ≤ 32 weeks with fair to good accuracy. The best predictive model generated an AUC of 0.79 (95% CI 0.66-0.91) with observed DRs of 41%, 61%, and 79% for FPRs of 10%, 20%, and 30%, including crown-rump length, maternal weight, race, tobacco use, and age.

Association of Minimal Residual Disease Negativity Rates With Progression Free Survival in Frontline Therapy Trials for Newly Diagnosed Multiple Myeloma: A Meta-analysis.

Current frontline therapies for newly diagnosed multiple myeloma patients have significantly prolonged progression-free survival (PFS). This has led to interest in minimal residual disease negativity (MRDng) as an efficacy-response biomarker and possible surrogate endpoint. A meta-analysis was conducted to explore the surrogacy of MRD for PFS and quantify the relationship between MRDng rates and PFS at the trial level. A systematic search was conducted on phase II and III trials reporting MRDng rates along with median PFS (mPFS) or PFS hazard ratios (HR). Weighted linear regressions were conducted relating mPFS to MRDng rates, and relating PFS HRs to either odds ratios (OR) or rate differences (RD) for MRDng in comparative trials. A total of 14 trials were available for the mPFS analysis. log(MRDng rate) was moderately associated with log (mPFS), with a slope of ß = 0.37 (95% CI, 0.26 to 0.48) and R2 = 0.62. A total of 13 trials were available for the PFS HR analysis. Treatment effects on MRDng rates were correlated with the corresponding effects on PFS: log (PFS HR) and log (MRDng OR) had a moderate association with ß = -0.36 (95% CI, -0.56 to -0.17) and R2 = 0.53 (95% CI, 0.21 to 0.77); log (PFS HR) and the MRDng RD had a stronger association with slope ß = -0.03 (95% CI, -0.04 to -0.02) and R2 = 0.67 (95% CI, 0.31 to 0.86). MRDng rates moderately associate with PFS outcomes. MRDng RDs are more strongly associated with HRs than MRDng ORs, with evidence suggestive of potential surrogacy.

First-in-human phase I study of the OX40 agonist GSK3174998 with or without pembrolizumab in patients with selected advanced solid tumors (ENGAGE-1).

BACKGROUND: The phase I first-in-human study ENGAGE-1 evaluated the humanized IgG1 OX40 agonistic monoclonal antibody GSK3174998 alone (Part 1 (P1)) or in combination with pembrolizumab (Part 2 (P2)) in patients with advanced solid tumors. METHODS: GSK3174998 (0.003-10 mg/kg) ± pembrolizumab (200 mg) was administered intravenously every 3 weeks using a continuous reassessment method for dose escalation. Primary objectives were safety and tolerability; secondary objectives included pharmacokinetics, immunogenicity, pharmacodynamics, and clinical activity. RESULTS: 138 patients were enrolled (45 (P1) and 96 (P2, including 3 crossovers)). Treatment-related adverse events occurred in 51% (P1) and 64% (P2) of patients, fatigue being the most common (11% and 24%, respectively). No dose-toxicity relationship was observed, and maximum-tolerated dose was not reached. Dose-limiting toxicities (P2) included Grade 3 (G3) pleural effusion and G1 myocarditis with G3 increased troponin. GSK3174998 ≥0.3 mg/kg demonstrated pharmacokinetic linearity and >80% receptor occupancy on circulating T cells; 0.3 mg/kg was selected for further evaluation. Limited clinical activity was observed for GSK3174998 (P1: disease control rate (DCR) ≥24 weeks 9%) and was not greater than that expected for pembrolizumab alone (P2: overall response rate 8%, DCR ≥24 weeks 28%). Multiplexed immunofluorescence data from paired biopsies suggested that increased infiltration of natural killer (NK)/natural killer T (NKT) cells and decreased regulatory T cells (Tregs) in the tumor microenvironment may contribute to clinical responses: CD16+CD56-CD134+ NK /NKT cells and CD3+CD4+FOXP3+CD134+ Tregs exhibited the largest magnitude of change on treatment, whereas CD3+CD8+granzyme B+PD-1+CD134+ cytotoxic T cells were the least variable. Tumor gene expression profiling revealed an upregulation of inflammatory responses, T-cell proliferation, and NK cell function on treatment with some inflammatory cytokines upregulated in peripheral blood. However, target engagement, evidenced by pharmacologic activity in peripheral blood and tumor tissue, did not correlate with clinical efficacy. The low number of responses precluded identifying a robust biomarker signature predictive of response. CONCLUSIONS: GSK3174998±pembrolizumab was well tolerated over the dose range tested and demonstrated target engagement. Limited clinical activity does not support further development of GSK3174998±pembrolizumab in advanced cancers. TRIAL REGISTRATION NUMBER: NCT02528357.

Model-based meta-analysis of non-small cell lung cancer with standard of care PD-1 inhibitors and chemotherapy for early development decision making.

Single-arm cohorts/trials are often used in early phase oncology programs to support preliminary clinical activity assessments for investigational products, administered alone or in combination with standard of care (SOC) agents. Benchmarking clinical activity of those combinations against other treatments, including SOC, requires indirect comparisons against external trials, which presents challenges including cross-study differences in trial populations/other factors. To facilitate such nonrandomized comparisons, we developed a comprehensive model-based meta-analysis (MBMA) framework to quantitatively adjust for factors related to efficacy in metastatic non-small cell lung cancer (mNSCLC). Data were derived from 15 published studies assessing key programmed cell death protein-1 (PD-1) inhibitors pembrolizumab (n = 8) and nivolumab (n = 7), representing current SOC in mNSCLC. In the first stage, a mixed-effects logistic regression model for overall response rate (ORR) was developed accounting for effects of various population covariates on ORR. The ORR model results indicated an odds ratio (OR) of 1.02 for squamous versus non-squamous histology and OR of 1.20 for PD-ligand 1 tumor proportion score (TPS) per every 10% increase of TPS level. Next, a nonparametric mixed-effects model for overall survival (OS) was developed with ORR/other clinical covariates as input. Subsequently, MBMA simulations of relevant hypothetical scenarios involving single-arm trial design predicted OS hazard ratios as a function of ORR with matched patient characteristics. Findings from this MBMA and derived parameter estimates can be generally applied by the reader as a framework for interpreting efficacy data from early phase trials to support ORR-based go/no-go decisions and futility rules, illustrated through examples in this report.

Developing a Novel Interactive Colorectal Cancer Educational Session for First-Year Medical Students to Enhance Interest in Public Health.

Medical students need more exposure to and a greater understanding of their role in public health throughout their training, which may influence more of them to pursue careers in public health or change how they practice medicine in the future. A novel colorectal cancer education session was created for first year medical students to attempt to increase public health interest, improve colorectal cancer knowledge and discuss barriers to colorectal cancer screening. We constructed a novel integrated interactive peer led colorectal cancer educational session of panelists with a wide range of experiences in colorectal cancer and colorectal cancer screening. The session involved a didactic component, case presentation, and group exercises followed by assembly discussion. We surveyed first-year medical students over two consecutive years to assess their interest in public health, knowledge of colorectal cancer, and perceptions of barriers to colorectal cancer screening before and after the educational session. We also evaluated student satisfaction with the session. We compared the pre- and post-survey results to assess for changes in interest, knowledge and perceptions. 74.63% of students in 2018 and 67.7% in 2019 evaluated the session as excellent or good, with knowledge regarding colorectal cancer screening markedly increased after the educational session. Students reported knowledge and access to healthcare among the biggest patient barriers to colorectal cancer screening. Interest in public health increased by 7.5% and 5.6% in 2018 and 2019, respectively. The implementation of this interactive educational peer led exercise can increase interest in public health, improve knowledge of colorectal cancer prevention and facilitate discussions of colorectal cancer screening barriers. We hope to encourage other programs to adopt this preliminary model.

Evaluation of a Maternal Plasma RNA Panel Predicting Spontaneous Preterm Birth and Its Expansion to the Prediction of Preeclampsia.

Preterm birth is the principal contributor to neonatal death and morbidity worldwide. We previously described a plasma cell-free RNA panel that between 16 and 20 weeks of pregnancy had potential to predict spontaneous preterm birth (sPTB) ≤ 32 weeks caused by preterm labor (PTL) or preterm premature rupture of membranes (PPROM). The present study had three objectives: (1) estimate the RNA panel prognostic accuracy for PTL/PPROM ≤ 32 weeks in a larger series; (2) improve accuracy by adding clinical characteristics to the predictive model; and (3) examine the association of the RNA panel with preeclampsia. We studied 289 women from Memphis TN prospectively sampled 16.0-20.7 weeks and found: (1) PSME2 and Hsa-Let 7g were differentially expressed in cases of PTL/PPROM ≤ 32 weeks and together provided fair predictive accuracy with AUC of 0.76; (2) combining the two RNAs with clinical characteristics improved good predictive accuracy for PTL/PPROM ≤ 32 weeks (AUC 0.83); (3) NAMPT and APOA1 were differentially expressed in women with 'early-onset preeclampsia' (EOP) and together provided good predictive accuracy with AUC of 0.89; and (4) combining the two RNAs with clinical characteristics provided excellent predictive accuracy (AUC 0.96). Our findings suggest an underlying common pathophysiological relationship between PTL/PPROM ≤ 32 weeks and EOP and open inroads for the prognostication of high-risk pregnancies.

Detection of Embryonic Trisomy 21 in the First Trimester Using Maternal Plasma Cell-Free RNA.

Prenatal trisomy 21 (T21) screening commonly involves testing a maternal blood sample for fetal DNA aneuploidy. It is reliable but poses a cost barrier to universal screening. We hypothesized maternal plasma RNA screening might provide similar reliability but at a lower cost. Discovery experiments used plasma cell-free RNA from 20 women 11−13 weeks tested by RNA and miRNA microarrays followed by qRT-PCR. Thirty-six mRNAs and 18 small RNAs of the discovery cDNA were identified by qPCR as potential markers of embryonic T21. The second objective was validation of the RNA predictors in 998 independent pregnancies at 11−13 weeks including 50 T21. Initial analyses identified 9−15 differentially expressed RNA with modest predictive power (AUC < 0.70). The 54 RNAs were then subjected to machine learning. Eleven algorithms were trained on one partition and tested on an independent partition. The three best algorithms were identified by Kappa score and the effects of training/testing partition size and dataset class imbalance on prediction were evaluated. Six to ten RNAs predicted T21 with AUCs up to 1.00. The findings suggest that maternal plasma collected at 11−13 weeks, tested by qRT-PCR, and classified by machine learning, may accurately predict T21 for a lower cost than plasma DNA, thus opening the door to universal screening.

Augmented early aged neutrophil infiltration contributes to late remodeling post myocardial infarction.

Neutrophils oscillate in number and phenotype after being released from bone marrow. Myocardial infarction (MI) outcome is associated with the time-of-day of ischemia onset. However, the underlying contributive factors of neutrophils to cardiac remodeling post MI remain unknown. We examined neutrophil infiltration into the heart and cardiac function and remodeling in C57BL/6J MI model created by permanent coronary ligation at different zeitgeber times (ZT). We found that cell surface markers (CD62L, CXCR2, CXCR4) of neutrophils in peripheral blood lost diurnal oscillation 24 h post MI. Meanwhile, circadian gene Bmal1, Nr1d1, and Clock mRNA expression displayed disrupted diurnal patterns. Flow cytometry showed augmented aged neutrophil (CD11b+Ly6G+CD62Llow) infiltration into the heart along with increased circulating aged neutrophils in MI groups with more infiltration at ZT5 (p < 0.05), but no difference for aged neutrophil infiltration at different ZT points in late stage. Infiltrated neutrophils had significantly higher CXCL2 and CXCR2 but lower CXCR4 gene expression (p < 0.05). Mice that underwent ligation at ZT5 had high mortality rate and large infarct size. Echocardiography showed that those mice had significantly larger end diastolic and systolic volume and lower ejection fraction (p < 0.05). Immunohistology revealed that those mice displayed more fibrosis, cardiomyocyte hypertrophy, and less angiogenesis compared to ZT13 or ZT21 group (p < 0.05). However, treatment with anti-CXCL2 antibody significantly reduced LV dilatation, fibrosis, hypertrophy and improved cardiac function. These results indicate greater aged neutrophil infiltration into the heart contributes to cardiac hypertrophy, fibrosis, and dysfunction which suggests that blocking neutrophil aging may be a therapeutic alternative following acute myocardial infarction.

Parallel Binary Image Cryptosystem Via Spiking Neural Networks Variants.

Due to the inefficiency of multiple binary images encryption, a parallel binary image encryption framework based on the typical variants of spiking neural networks, spiking neural P (SNP) systems is proposed in this paper. More specifically, the two basic units in the proposed image cryptosystem, the permutation unit and the diffusion unit, are designed through SNP systems with multiple channels and polarizations (SNP-MCP systems), and SNP systems with astrocyte-like control (SNP-ALC systems), respectively. Different from the serial computing of the traditional image permutation/diffusion unit, SNP-MCP-based permutation/SNP-ALC-based diffusion unit can realize parallel computing through the parallel use of rules inside the neurons. Theoretical analysis results confirm the high efficiency of the binary image proposed cryptosystem. Security analysis experiments demonstrate the security of the proposed cryptosystem.

Risk Factors for Opioid Utilization in Patients with Intracerebral Hemorrhage.

BACKGROUND: Headache is a common presenting symptom of intracerebral hemorrhage (ICH) and often necessitates treatment with opioid medications. However, opioid prescribing patterns in patients with ICH are not well described. We aimed to characterize the prevalence and risk factors for short and longer-term opioid use in patients with ICH. METHODS: We conducted a retrospective cohort study using data from a single-center registry of patients with nontraumatic ICH. This registry included data on demographics, ICH-related characteristics, and premorbid, inpatient, and postdischarge medications. After excluding patients who died or received end-of-life care, we used multivariable regression models adjusted for premorbid opioid use to determine demographic and ICH-related risk factors for inpatient and postdischarge opioid use. RESULTS: Of 468 patients with ICH in our cohort, 15% (n = 70) had premorbid opioid use, 53% (n = 248) received opioids during hospitalization, and 12% (n = 53) were prescribed opioids at discharge. The most commonly used opioids during hospitalization were fentanyl (38%), oxycodone (30%), morphine (26%), and hydromorphone (7%). Patients who received opioids during hospitalization were younger (univariate: median [interquartile range] 64 [53.5-74] vs. 76 [67-83] years, p < 0.001; multivariable: odds ratio [OR] 0.96 per year, 95% confidence interval [CI] 0.94-0.98) and had larger ICH volumes (univariate: median [interquartile range] 10.1 [2.1-28.6] vs. 2.7 [0.8-9.9] cm3, p < 0.001; multivariable: OR 1.05 per cm3, 95% CI 1.03-1.08) than those who did not receive opioids. All patients who had external ventricular drain placement and craniotomy/craniectomy received inpatient opioids. Additional risk factors for increased inpatient opioid use included infratentorial ICH location (OR 4.8, 95% CI 2.3-10.0), presence of intraventricular hemorrhage (OR 3.9, 95% CI 2.2-7.0), underlying vascular lesions (OR 3.0, 95% CI 1.1-8.1), and other secondary ICH etiologies (OR 7.5, 95% CI 1.7-32.8). Vascular lesions (OR 4.0, 95% CI 1.3-12.5), malignancy (OR 5.0, 95% CI 1.5-16.4), vasculopathy (OR 10.0, 95% CI 1.8-54.2), and other secondary etiologies (OR 7.2, 95% CI 1.8-29.9) were also risk factors for increased opioid prescriptions at discharge. Among patients who received opioid prescriptions at discharge, 43% (23 of 53) continued to refill their prescriptions at 3 months post discharge. CONCLUSIONS: Inpatient opioid use in patients with ICH is common, with some risk factors that may be mechanistically connected to primary headache pathophysiology. However, the lower frequency of opioid prescriptions at discharge suggests that inpatient opioid use does not necessarily lead to a high rate of long-term opioid dependence in patients with ICH.

Learning Clinical Concepts for Predicting Risk of Progression to Severe COVID-19.

With COVID-19 now pervasive, identification of high-risk individuals is crucial. Using data from a major healthcare provider in Southwestern Pennsylvania, we develop survival models predicting severe COVID-19 progression. In this endeavor, we face a tradeoff between more accurate models relying on many features and less accurate models relying on a few features aligned with clinician intuition. Complicating matters, many EHR features tend to be under-coded degrading the accuracy of smaller models. In this study we develop two sets of high-performance risk scores: (i) an unconstrained model built from all available features; and (ii) a pipeline that learns a small set of clinical concepts before training a risk predictor. Learned concepts boost performance over the corresponding features (C-index 0.858 vs. 0.844) and demonstrate improvements over (i) when evaluated out-of-sample (subsequent time periods). Our models outperform previous works (C-index 0.844-0.872 vs. 0.598-0.810).

Analyzing the Relationship between Mental Health Courts and the Prison Industrial Complex.

Mental health courts (MHCs) were designed to address the high rates of incarcerated individuals with serious mental illness in the United States by providing mental health treatment and social supports to those facing criminal charges. In the setting of national uprisings and grassroots demands for abolition of the prison industrial complex (PIC), which is the broad construct of economic and sociopolitical drivers of imprisonment, we draw upon the scholarship of community activists to examine the role of MHCs within the PIC. Specifically, we explore whether MHCs exacerbate harms caused by the criminal justice system or work to reduce its oppressive power. In this analysis, we argue that MHCs can perpetuate harmful assumptions about mental illness and crime, can legitimize the harsh punishment of individuals unfairly deemed undeserving of policy intervention, and can preserve power differentials between courts and court participants. Our analysis underscores the need for a critical reassessment of the role of MHCs in communities and in the PIC. We advocate for an open discussion between community members and advocates, policymakers, and health professionals about how to address the need for mental health treatment and social support without expanding and entrenching the power of the PIC.

Entinostat, a selective HDAC1/2 inhibitor, potentiates the effects of olaparib in homologous recombination proficient ovarian cancer.

OBJECTIVE: Poly ADP ribose polymerase inhibitors (PARPi) are most effective in BRCA1/2 mutated ovarian tumors. Better treatments are needed for homologous recombination HR-proficient cancer, including CCNE1 amplified subtypes. We have shown that histone deacetylase inhibitors (HDACi) sensitize HR-proficient ovarian cancer to PARPi. In this study, we provide complementary preclinical data for an investigator-initiated phase 1/2 clinical trial of the combination of olaparib and entinostat in recurrent, HR-proficient ovarian cancer. METHODS: We assessed the in vitro effects of the combination of olaparib and entinostat in SKOV-3, OVCAR-3 and primary cells derived from CCNE1 amplified high grade serous ovarian cancer (HGSOC) patients. We then tested the combination in a SKOV-3 xenograft model and in a patient-derived xenograft (PDX) model. RESULTS: Entinostat potentiates the effect of olaparib in reducing cell viability and clonogenicity of HR-proficient ovarian cancer cells. The combination reduces peritoneal metastases in a SKOV-3 xenograft model and prolongs survival in a CCNE1 amplified HR-proficient PDX model. Entinostat also enhances olaparib-induced DNA damage. Further, entinostat decreases BRCA1, a key HR repair protein, associated with decreased Ki-67, a proliferation marker, and increased cleaved PARP, a marker of apoptosis. Finally, entinostat perturbs replication fork progression, which increases genome instability. CONCLUSION: Entinostat inhibits HR repair by reducing BRCA1 expression and stalling replication fork progression, leading to irreparable DNA damage and ultimate cell death. This work provides preclinical support for the clinical trial of the combination of olaparib and entinostat in HR-proficient ovarian cancer and suggests potential benefit even for CCNE1 amplified subtypes.

Unpacking the Drop in COVID-19 Case Fatality Rates: A Study of National and Florida Line-Level Data.

Since the COVID-19 pandemic began, the United States's case fatality rate (CFR) has plummeted. Using national and Florida data, we unpack the drop in CFR between April and December 2020, accounting for such confounders as expanded testing, age distribution shift, and detection-to-death lags. Guided by the insight that treatment improvements in this period should correspond to decreases in hospitalization fatality rate (HFR), and using a block-bootstrapping procedure to quantify uncertainty, we find that although treatment improvements do not follow the same trajectory in Florida and nationally (with Florida undergoing a comparatively severe second peak), by December, significant improvements are observed both in Florida and nationally (at least 17% and 55% respectively). These estimates paint a more realistic picture of improvements than the drop in aggregate CFR (70.8%-91.1%). We publish a website where users can apply our analyses to selected demographics, regions, and dates of interest.

A decision algorithm to promote outpatient antimicrobial stewardship for uncomplicated urinary tract infection.

Antibiotic resistance is a major cause of treatment failure and leads to increased use of broad-spectrum agents, which begets further resistance. This vicious cycle is epitomized by uncomplicated urinary tract infection (UTI), which affects one in two women during their life and is associated with increasing antibiotic resistance and high rates of prescription for broad-spectrum second-line agents. To address this, we developed machine learning models to predict antibiotic susceptibility using electronic health record data and built a decision algorithm for recommending the narrowest possible antibiotic to which a specimen is susceptible. When applied to a test cohort of 3629 patients presenting between 2014 and 2016, the algorithm achieved a 67% reduction in the use of second-line antibiotics relative to clinicians. At the same time, it reduced inappropriate antibiotic therapy, defined as the choice of a treatment to which a specimen is resistant, by 18% relative to clinicians. For specimens where clinicians chose a second-line drug but the algorithm chose a first-line drug, 92% (1066 of 1157) of decisions ended up being susceptible to the first-line drug. When clinicians chose an inappropriate first-line drug, the algorithm chose an appropriate first-line drug 47% (183 of 392) of the time. Our machine learning decision algorithm provides antibiotic stewardship for a common infectious syndrome by maximizing reductions in broad-spectrum antibiotic use while maintaining optimal treatment outcomes. Further work is necessary to improve generalizability by training models in more diverse populations.

Expression, Regulation, and Function of the Calmodulin Accessory Protein PCP4/PEP-19 in Myometrium.

OBJECTIVE: Calmodulin (CaM) plays a key role in the orchestration of Ca2+ signaling events, and its regulation is considered an important component of cellular homeostasis. The control of uterine smooth muscle function is largely dependent on the regulation of Ca2+ and CaM signaling. The objective of this study was to investigate the expression, function, and regulation of CaM regulatory proteins in myometrium during pregnancy. STUDY DESIGN: Myometrium was obtained from nonpregnant women and 4 groups of pregnant women at the time their primary cesarean delivery: (i) preterm not in labor, (ii) preterm in labor with clinical and/or histological diagnosis of chorioamnionitis, (3) term not in labor; and (4) term in labor. The effect of perinatal inflammation on pcp4/pep-19 expression was evaluated in a mouse model of Ureaplasma parvum-induced chorioamnionitis. Human myometrial cells stably expressing wild-type and mutant forms of PCP4/PEP-19 were used in the evaluation of agonist-induced intracellular Ca2+ mobilization. RESULTS: Compared to other CaM regulatory proteins, PCP4/PEP-19 transcripts were more abundant in human myometrium. The expression of PCP4/PEP-19 was lowest in myometrium of women with preterm pregnancy and chorioamnionitis. In the mouse uterus, pcp4/pep-19 expression was lower in late compared to mid-gestation and decreased in mice injected intra-amniotic with Ureaplasma parvum. In myometrial smooth muscle cells, tumor necrosis factor alpha and progesterone decreased and PCP4/PEP-19 promoter activity increased. Finally, the overexpression of PCP4/PEP-19 reduced agonist-induced intracellular Ca2+ levels in myometrial cells. CONCLUSION: The decreased expression of PCP4/PEP-19 in myometrium contributes to a loss of quiescence in response to infection-induced inflammation at preterm pregnancy.

Regulation of human placental drug transporters in HCV infection and their influence on direct acting antiviral medications.

INTRODUCTION: The objectives of this study were to determine how HCV infection affects placental drug transporters, and to determine the role of drug transporters on the cellular accumulation of direct-acting antiviral drugs in human trophoblasts. METHODS: Eighty-four ABC and SLC transporter genes were first screened in normal and HCV infected pregnant women using PCR profiler array. The changes in expression were confirmed by qPCR and Western blot. The impact of selected drug transporters on the cellular accumulation of radiolabeled antiviral drugs sofosbuvir, entecavir, and tenofovir was measured in primary human trophoblasts (PHT) and BeWo b30 cells in the presence or absence of transporter-specific inhibitors. PHT were then treated with CL097, ssRNA40, and imquimod to determine the impact of Toll-like receptor (TLR) 7/8 activation on drug transporter expression. RESULTS: The expression of the ABC efflux transporters ABCB1/P-gp and ABCG2/BCRP was increased in placenta of women with HCV, while the nucleoside transporters SLC29A1/ENT1 and SLC29A2/ENT2 remained unchanged. The accumulation of sofosbuvir and tenofovir was unaffected by inhibition of these transporters in trophoblast cells. Entecavir accumulation was decreased by the inhibition of ENT2. P-gp and BCRP inhibition enhanced entecavir accumulation in BeWo b30, but not PHT. Overall, there was little effect of TLR7/8 activation on these drug transporters, and the accumulation of entecavir in PHT. DISCUSSION: The data suggest that expression of placental drug transporters and selection of antiviral drug may impact fetal drug exposure in pregnancies complicated by HCV infections.