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Literature reports of adverse drug events can be replicated across multiple companies, resulting in extreme duplication (defined as a majority of reports being duplicates) in the FDA Adverse Event Reporting System (FAERS) database because they can escape legacy duplicate detection algorithms routinely deployed on that data source. Literature reference field, added to in 2014, could potentially be utilized to identify replicated reports. FAERS does not enforce adherence to the Vancouver referencing convention, thus the same article may be referenced differently leading to duplication. The objective of this analysis is to determine if variations of the same literature references observed in FAERS can be resolved with text normalization and fuzzy string matching.We normalized the literature references recorded in the FAERS database through the first quarter of 2021 with a rule-based algorithm so that they better conform to the Vancouver convention. Levenshtein distance was then utilized to merge sufficiently similar normalized literature references together.Normalization of literature references increases the percentage that can be parsed into author, title, and journal from 61.74% to 93.93%. We observe that about 98% of pairs within groups do have a Levenshtein similarity of the title above the threshold. The extreme duplication ranged from 66% to 87% with a median of 72% of reports being duplicates and often involved addictovigilance scenarios.We have shown that these normalized references can be merged via fuzzy string matching to improve enumeration of all the individual case safety reports that refer to the same article. Inclusion of the PubMed ID and adherence to the Vancouver convention could facilitate identification of duplicates in the FAERS dataset. Awareness of this phenomenon may improve disproportionality analysis, especially in areas such as addictovigilance.

Self-efficacy (SE) is recognized as a main determinant of successful performance and may mediate the relationship between psychological performance enhancement techniques and sports performance. Identifying the cognitive–motor processes of superior performance can provide crucial information not only for accelerating the motor learning process but also for enhancing motor performance. The frontal midline theta power (Fmθ) reflects the level of top–down attention allocated to achieve a desired cognitive–motor behavior. Thus, this study investigated the effect of SE on the performance and Fmθ of golf players and explored the association between the objective measures of cortical dynamics and SE. Thirty-four skilled golfers were recruited (within-subject design) to perform 60 putts, and their electroencephalographic activity was recorded during the task. The SE score was measured using a visual analog scale ranging from 0 to 10 before each putt. Paired t test results revealed that trials with higher SE scores were associated with a higher putting success rate than trials with lower SE scores (53.3% vs 46.7%). Moreover, trials with higher SE scores were preceded by lower Fmθ than trials with lower SE scores (4.49 vs. 5.18). These findings suggested that higher SE was followed by less top–down attentional control, a characteristic of automatic processing, leading to better putting performance. Our findings support Bandura’s SE theory and elucidate the intermediate processes of SE by investigating the effect of the anticipation of outcomes on sports performance and attentional control before putting.

Acetaminophen (APAP) is available over-the-counter and widely regarded as safe for use in pregnancy. APAP has been used to close a persistently patent ductus arteriosus. Fetal constriction/closure of the ductus arteriosus (FCCDA), of public health interest given the drug’s widespread use during pregnancy, is being monitored globally, including by the European Medicines Agency Pharmacovigilance Risk Assessment Committee. Our objective was to share a comprehensive signal evaluation of FCCDA with in utero APAP exposure to determine if the totality of evidence is sufficiently more consistent with one of the following two possibilities: (1) APAP never contributes to FCCDA (null hypothesis or HO) versus (2) APAP may in some cases be at least a contributory cause of in utero DA narrowing (alternative hypothesis or HA) to justify risk communication. To assess the relative support for HO versus HA, we synthesize and interpret within an Austin Bradford Hill criteria framework a comprehensive, cross-disciplinary set of published information and de novo analysis, including toxicology, epidemiology, clinical pharmacology, and clinical and quantitative pharmacovigilance analysis of spontaneous reports. While residual uncertainty remains, the totality of information is more compatible with HA than H0, to the extent that it is reasonably possible that APAP may sometimes be at least a contributory cause of FCCDA. It is reasonably possible that APAP may sometimes be at least a contributory cause of FCCDA, and this should therefore be communicated to stakeholders.

ObjectivesTofacitinib is a Janus kinase inhibitor for the treatment of rheumatoid arthritis (RA), psoriatic arthritis (PsA) and ulcerative colitis, and has been investigated in psoriasis (PsO). Routine pharmacovigilance of an ongoing, open-label, blinded-endpoint, tofacitinib RA trial (Study A3921133; NCT02092467) in patients aged ≥50 years and with ≥1 cardiovascular risk factor identified a higher frequency of pulmonary embolism (PE) and all-cause mortality for patients receiving tofacitinib 10 mg twice daily versus those receiving tumour necrosis factor inhibitors and resulted in identification of a safety signal for tofacitinib. Here, we report the incidence of deep vein thrombosis (DVT), PE, venous thromboembolism (VTE; DVT or PE) and arterial thromboembolism (ATE) from the tofacitinib RA (excluding Study A3921133), PsA and PsO development programmes and observational studies. Data from an ad hoc safety analysis of Study A3921133 are reported separately within.MethodsThis post-hoc analysis used data from separate tofacitinib RA, PsO and PsA programmes. Incidence rates (IRs; patients with events per 100 patient-years’ exposure) were calculated for DVT, PE, VTE and ATE, including for populations stratified by defined baseline cardiovascular or VTE risk factors. Observational data from the US Corrona registries (including cardiovascular risk factor stratification), IBM MarketScan research database and the US FDA Adverse Event Reporting System (FAERS) database were analysed.Results12 410 tofacitinib-treated patients from the development programmes (RA: n=7964; PsO: n=3663; PsA: n=783) were included. IRs (95% CI) of thromboembolic events among the all tofacitinib cohorts’ average tofacitinib 5 mg and 10 mg twice daily treated patients for RA, respectively, were: DVT (0.17 (0.09–0.27) and 0.15 (0.09–0.22)); PE (0.12 (0.06–0.22) and 0.13 (0.08–0.21)); ATE (0.32 (0.22–0.46) and 0.38 (0.28–0.49)). Among PsO patients, IRs were: DVT (0.06 (0.00–0.36) and 0.06 (0.02–0.15)); PE (0.13 (0.02–0.47) and 0.09 (0.04–0.19)); ATE (0.52 (0.22–1.02) and 0.22 (0.13–0.35)). Among PsA patients, IRs were: DVT (0.00 (0.00–0.28) and 0.13 (0.00–0.70)); PE (0.08 (0.00–0.43) and 0.00 (0.00–0.46)); ATE (0.31 (0.08–0.79) and 0.38 (0.08–1.11)). IRs were similar between tofacitinib doses and generally higher in patients with baseline cardiovascular or VTE risk factors. IRs from the overall Corrona populations and in Corrona RA patients (including tofacitinib-naïve/biologic disease-modifying antirheumatic drug-treated and tofacitinib-treated) with baseline cardiovascular risk factors were similar to IRs observed among the corresponding patients in the tofacitinib development programme. No signals of disproportionate reporting of DVT, PE or ATE with tofacitinib were identified in the FAERS database.ConclusionsDVT, PE and ATE IRs in the tofacitinib RA, PsO and PsA programmes were similar across tofacitinib doses, and generally consistent with observational data and published IRs of other treatments. As expected, IRs of thromboembolic events were elevated in patients with versus without baseline cardiovascular or VTE risk factors, and were broadly consistent with those observed in the Study A3921133 ad hoc safety analysis data, although the IR (95% CI) for PE was greater in patients treated with tofacitinib 10 mg twice daily in Study A3921133 (0.54 (0.32–0.87)), versus patients with baseline cardiovascular risk factors treated with tofacitinib 10 mg twice daily in the RA programme (0.24 (0.13–0.41)).

Acute myeloid leukemia (AML) is a highly aggressive disease with high relapse and mortality rates. Recent years have shown a surge in novel therapeutic development for AML, both in clinical and preclinical stages. These developments include targeted therapies based on AML-specific molecular signatures as well as more general immune modulation and vaccination studies. In this review, we will explore the evolving arena of AML therapy and suggest some intriguing connections between immune system modulation and targeted therapy. Improved understanding of the immune system involvement in various stages of the disease and the crosstalk between immune effectors, targeted therapy, and AML cells can provide a better framework for designing the next generation of AML therapies.

Breast cancer is the leading cause of cancer-related death for women. In breast cancer treatment, targeted therapy would be more effective and less harmful than radiotherapy or systemic chemotherapy. Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) has been shown to induce apoptosis in cancer cells but not in normal cells. Mesenchymal stem cells have shown great therapeutic potential in cancer therapy owing to their ability of homing to tumor sites and secreting many kinds of anti-tumor proteins including TRAIL. In this study, we found that IL-1β-stimulated human umbilical cord-derived mesenchymal stem cells (hUCMSCs) enhance the expression of membrane-bound and soluble TRAIL. Cellular FADD-like IL-1β-converting enzyme inhibitory protein (cFLIP) is an important regulator in TRAIL-mediated apoptosis and relates to TRAIL resistance in cancer cells. Previous studies have shown that embelin, which is extracted from Embelia ribes, can increase the TRAIL sensitivity of cancer cells by reducing cFLIP expression. Here we have demonstrated that cFLIPL is correlated with TRAIL-resistance and that embelin effectively downregulates cFLIPL in breast cancer cells. Moreover, co-culture of IL-1β-stimulated hUCMSCs with embelin-treated breast cancer cells could effectively induce apoptosis in breast cancer cells. The combined effects of embelin and IL-1β-stimulated hUCMSCs may provide a new therapeutic strategy for breast cancer therapy.

The 2019 guideline from the Anticoagulation Forum provides clear instructions on how to use 2 agents for reversing the effects of direct oral anticoagulants (DOACs): idarucizumab for dabigatran-associated bleeding and andexanet alfa for bleeding associated with rivaroxaban and apixaban. The guideline also discusses off-label use of andexanet alfa for bleeding associated with edoxaban and betrixaban and the use of hemostatic agents such as activated prothrombin complex concentrate and 4-factor prothrombin complex concentrate. Lastly, it offers approaches for building and managing stewardship programs at the health system level.

Purpose The COVID-19 pandemic was widely reported to present a stress to medical systems globally and disrupted the lives of patients and health care practitioners. Since spontaneous reporting heavily relies on both health care professionals and patients, an understandable question is whether the stress of the pandemic diminished spontaneous reporting. Herein we assess the hypothesis that the COVD-19 pandemic negatively impacted spontaneous reporting of adverse drug events. Methods We analyzed 119 weeks of spontaneous report counts from the Pfizer Safety database (January 1, 2018 to April 12, 2020). We fitted autoregressive integrated moving average models to aggregated and disaggregated time series and charted the model residuals on Individual value-moving range and exponentially weighted moving average charts to identify statistically unexpected changes associated with the pandemic. Results Overall reporting of serious adverse events showed no unexpected decline, Total global reporting declined, driven by health care professional reporting (both serious and non-serious), starting after week 8, 2020, exceeding model expectations by week 15, 2020, suggesting the pandemic as an assignable cause. However, reporting remained within longer term historic ranges. The Japan time series was the one individual country time series showing a significant decline, and unusual periodicity related to national holidays. A few countries, notably Taiwan, showed statistically unexpected reporting increases associated with the pandemic commencing as early as week 3, 2020. Literature reporting of adverse drug events was stable. Ancillary findings included prevalent year-end/beginning reporting minima, more with health professional than consumer reports. Implications In a large and diverse pharmaceutical company database we did detect a significant global decline in total reporting, driven by healthcare professionals, not consumers, and non-serious reports, consistent with the pandemic as an assignable cause, but the reporting remained within long term ranges. suggesting a relative durability. Importantly, our analyses found no unexpected decline in overall serious reporting. Future avenues for research include assessing whether these effects impaired signal detection, performing the same analysis on large public spontaneous reporting system data to assess generalizability of our findings, and follow-up analysis to assess if impacts on spontaneous reporting abate., Highlights • The COVID-19 pandemic is a historic event that presented a shock to health care systems. • Time series modelling and statistical process control charts were used to assess the impact of the pandemic on spontaneous adverse drug reaction reporting. • Spontaneous adverse drug reaction reporting significantly declined by week 15, 2020, suggesting the pandemic as an assignable cause.

Background: Severe cutaneous adverse reactions (SCARs) are prominent in pharmacovigilance (PhV). They have some commonalities such as nonimmediate nature and T-cell mediation and rare overlap syndromes have been documented, most commonly involving acute generalized exanthematous pustulosis (AGEP) and drug rash with eosinophilia and systemic symptoms (DRESS), and DRESS and toxic epidermal necrolysis (TEN). However, they display diverse clinical phenotypes and variations in specific T-cell immune response profiles, plus some specific genotype–phenotype associations. A question is whether causation of a given SCAR by a given drug supports causality of the same drug for other SCARs. If so, we might expect significant intercorrelations between SCARs with respect to overall drug-reporting patterns. SCARs with significant intercorrelations may reflect a unified underlying concept. Methods: We used exploratory factor analysis (EFA) on data from the United States Food and Drug Administration Adverse Event Reporting System (FAERS) to assess reporting intercorrelations between six SCARs [AGEP, DRESS, erythema multiforme (EM), Stevens–Johnson syndrome (SJS), TEN, exfoliative dermatitis (ExfolDerm)]. We screened the data using visual inspection of scatterplot matrices for problematic data patterns. We assessed factorability via Bartlett’s test of sphericity, Kaiser-Myer-Olkin (KMO) statistic, initial estimates of communality and the anti-image correlation matrix. We extracted factors via principle axis factoring (PAF). The number of factors was determined by scree plot/Kaiser’s rule. We also examined solutions with an additional factor. We applied various oblique rotations. We assessed the strength of the solution by percentage of variance explained, minimum number of factors loading per major factor, the magnitude of the communalities, loadings and crossloadings, and reproduced- and residual correlations. Results: The data were generally adequate for factor analysis but the amount of variance explained, shared variance, and communalities were low, suggesting caution in general against extrapolating causality between SCARs. SJS and TEN displayed most shared variance. AGEP and DRESS, the other SCAR pair most often observed in overlap syndromes, demonstrated modest shared variance, along with maculopapular rash (MPR). DRESS and TEN, another of the more commonly diagnosed pairs in overlap syndromes, did not. EM was uncorrelated with SJS and TEN. Conclusions: The notion that causality of a drug for one SCAR bolsters support for causality of the same drug with other SCARs was generally not supported.

Introduction: There is an interest in methodologies to expeditiously detect credible signals of drug-induced pancreatitis. An example is the reported signal of pancreatitis with rasburicase emerging from a study [the ‘index publication’ (IP)] combining quantitative signal detection findings from a spontaneous reporting system (SRS) and electronic health records (EHRs). The signal was reportedly supported by a clinical review with a case series manuscript in progress. The reported signal is noteworthy, being initially classified as a false-positive finding for the chosen reference standard, but reclassified as a ‘clinically supported’ signal. Objective: This paper has dual objectives: to revisit the signal of rasburicase and acute pancreatitis and extend the original analysis via reexamination of its findings, in light of more contemporary data; and to motivate discussions on key issues in signal detection and evaluation, including recent findings from a major international pharmacovigilance research initiative. Methodology: We used the same methodology as the IP, including the same disproportionality analysis software/dataset for calculating observed to expected reporting frequencies (O/Es), Medical Dictionary for Regulatory Activities Preferred Term, and O/E metric/threshold combination defining a signal of disproportionate reporting. Baseline analysis results prompted supplementary analyses using alternative analytical choices. We performed a comprehensive literature search to identify additional published case reports of rasburicase and pancreatitis. Results: We could not replicate positive findings (e.g. a signal or statistic of disproportionate reporting) from the SRS data using the same algorithm, software, dataset and vendor specified in the IP. The reporting association was statistically highlighted in default and supplemental analysis when more sensitive forms of disproportionality analysis were used. Two of three reports in the FAERS database were assessed as likely duplicate reports. We did not identify any additional reports in the FAERS corresponding to the three cases identified in the IP using EHRs. We did not identify additional published reports of pancreatitis associated with rasburicase. Discussion: Our exercise stimulated interesting discussions of key points in signal detection and evaluation, including causality assessment, signal detection algorithm performance, pharmacovigilance terminology, duplicate reporting, mechanisms for communicating signals, the structure of the FAERs database, and recent results from a major international pharmacovigilance research initiative.

Summary CKIα ablation induces p53 activation, and CKIα degradation underlies the therapeutic effect of lenalidomide in a pre-leukemia syndrome. Here we describe the development of CKIα inhibitors, which co-target the transcriptional kinases CDK7 and CDK9, thereby augmenting CKIα-induced p53 activation and its anti-leukemic activity. Oncogene-driving super-enhancers (SEs) are highly sensitive to CDK7/9 inhibition. We identified multiple newly gained SEs in primary mouse acute myeloid leukemia (AML) cells and demonstrate that the inhibitors abolish many SEs and preferentially suppress the transcription elongation of SE-driven oncogenes. We show that blocking CKIα together with CDK7 and/or CDK9 synergistically stabilize p53, deprive leukemia cells of survival and proliferation-maintaining SE-driven oncogenes, and induce apoptosis. Leukemia progenitors are selectively eliminated by the inhibitors, explaining their therapeutic efficacy with preserved hematopoiesis and leukemia cure potential; they eradicate leukemia in MLL-AF9 and Tet2−/−;Flt3ITD AML mouse models and in several patient-derived AML xenograft models, supporting their potential efficacy in curing human leukemia.

Drug resistance is a frequent cause of failure in cancer chemotherapy treatments. In this study, a pair of uterine sarcoma cancer lines, MES-SA, and doxorubicin-resistant partners, MES-SA/DxR-2μM cells and MES-SA/DxR-8μM cells, as a model system to investigate resistance-dependent proteome alterations and to identify potential therapeutic targets. We used two-dimensional differential gel electrophoresis (2D-DIGE) and matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) to perform this research and the results revealed that doxorubicin-resistance altered the expression of 208 proteins in which 129 identified proteins showed dose-dependent manners in response to the levels of resistance. Further studies have used RNA interference, H2A.X phosphorylation assay, cell viability analysis, and analysis of apoptosis against reticulocalbin-1 (RCN1) proteins, to prove its potency on the formation of doxorubicin resistance as well as the attenuation of doxorubicin-associated DNA double strand breakage. To sum up, our results provide useful diagnostic markers and therapeutic candidates such as RCN1 for the treatment of doxorubicin-resistant uterine cancer.

The nucleus is a key organelle in mammary cells, which is responsible for several cellular functions including cell proliferation, gene expression, and cell survival. In addition, the nucleus is the primary targets of doxorubicin treatment. In the current study, low-abundance nuclear proteins were enriched for proteomic analysis by using a state-of-the-art two-dimensional differential gel electrophoresis (2D-DIGE) and matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) strategy to compare and identify the nuclear protein profiling changes responsible for the development of doxorubicin resistance in human uterine cancer cells. The results of the nuclear proteomic analysis indicated that more than 2100 protein features were resolved from an equal pooled amount of three purified nuclear proteins and 117 differentially expressed spots were identified. Of these 117 identified proteins, 48 belonged to nuclear proteins and a positive correlation was observed between the expression levels of 32 of these nuclear proteins and an increase in drug resistance. According to our review of relevant research, nuclear proteins such as DNA repair protein XRCC3 (XRCC3) have not been reported to play roles in the formation of doxorubicin resistance. Previous studies have used RNA interference and cell viability analysis to evidence the essential roles of XRCC3 on its potency in the formation of doxorubicin resistance. To sum up, our nuclear proteomic approaches enabled us to identify numerous proteins, including XRCC3, involved in various drug-resistance-forming mechanisms. Our results provide potential diagnostic markers and therapeutic candidates for treating doxorubicin-resistant uterine cancer.

Background Masking is a statistical issue by which signals are hidden by the presence of other medicines in the database. In the absence algorithm, the impact of the masking effect has not been fully investigated. Objective Our study is aimed at assessing the extent and the impact of the masking effect on two large spontaneous reporting databases. Study design Cross sectional study using a set of terms of importance for public health in two spontaneous reporting databases. Setting The analyses were performed on EudraVigilance (EV) and the Pfizer spontaneous reporting database (PfDB). Main outcome measure Using the masking ratio, we have identified and removed the products inducing the highest masking effect. Results Studying a total of almost 50 000 drug-event combinations masking had an impact on approximately 60% of drug-event combinations were masked by another product with a masking ratio >1 in EV and 84% in PfDB. The prevalence of important masking was quite rare (0.003% of the DECs) and mainly affected events rarely reported in EV. The products involved in the highest masking effects are products known to induce the reaction. The removal of the masking effect of the highest masking product has revealed 974 signals of disproportionate reporting in EV including true signals. The study shows that the original ranking provided by the quantitative methods included in our study is marginally affected by the removal of the masking product. Conclusion Our study suggests that significant masking is rare in large spontaneous databases and mostly affects events rarely reported in EV. Copyright © 2013 John Wiley & Sons, Ltd.

Background Masking is a statistical issue by which true signals of disproportionate reporting are hidden by the presence of other products in the database. Masking is currently not perfectly understood. There is no algorithm to identify the potential masking drugs to remove them for subsequent analyses of disproportionality. Objective The primary objective of our study is to develop a mathematical framework for assessing the extent and impact of the masking effect of measures of disproportionality. Method We have developed a masking ratio that quantifies the masking effect of a given product. We have conducted a simulation study to validate our algorithm. Results The masking ratio is a measure of the strength of the masking effect whether the analysis is performed at the report or event level, and the manner in which reports are allocated to cells in the contingency table significantly impact the masking mechanisms. The reports containing both the product of interest and the masking product need to be handled appropriately. The proposed algorithm can use simplified masking provided that underlying assumptions (in particular the size of the database) are verified. For any event, the strongest masking effect is associated with the drug with the highest number of records (reports excluding the product of interest). Conclusion Our study provides significant insights with practical implications for real-world pharmacovigilance that are supported by both real and simulated data. The public health impact of masking is still unknown. Copyright © 2013 John Wiley & Sons, Ltd.

To investigate spontaneous reporting relationships between representative antifungal agents and congestive heart failure (CHF)-related adverse events (AE) we performed multiple disproportionality analyses of the US FDA AERS database. Specifically we performed analysis of drug-AE associations (2D) plus drug-drug-AE and drug-AE-AE-associations (3D), the latter two to explore the potential contribution of reported pharmacodynamic interactions, overexposure from pharmacokinetic interactions, and drug overdose. Itraconazole displayed a pattern of statistical reporting dependencies across multiple analyses (2D and 3D). Amphotericin B was the only other antifungal that demonstrated a 2D SDR with CHF-related events. Itraconazole demonstrated multiple SDRs with calcium channel blockers in suspect drug-only 3D analysis. There was one other SDR with fluconazole and propanolol and three SDRs involving valproate and fluconazole that may have been do at least in part to duplicate reporting. Less specific 3D analysis including both suspect plus concomitant medications showed a greater number and variety of SDRs with multiple antifungals. Statistical reporting dependencies with CHF-related events did not appear to be a consistent pharmacological (e.g., azole/triazole)/therapeutic (i.e., antifungal) class effect. Itraconzole was unique in the pattern of statistical reporting dependencies with CHF-related events which is consistent with findings from independent data sets.

Introduction: Pneumothorax is either primary or secondary. Secondary pneumothorax is usually due to trauma, including various non-pharmacologic iatrogenic triggers. Although not normally thought of as an adverse drug event (ADE) secondary pneumothorax is associated with numerous drugs, though it is often difficult to determine whether this association is causal in nature, or reflects an epiphenomenon of efficacy or inefficacy, or confounding by indication (CBI). Herein we explore this association in a large health authority drug safety surveillance database. Methods: A quantitative pharmacovigilance (PhV) methodology known as disproportionality analysis was applied to the United States Food and Drug Administration (US FDA) Adverse Event Reporting System (AERS) database to explore the quantitative reporting dependencies between drugs and the adverse event pneumothorax as well the corresponding reporting dependencies between drugs and reported indications that may be risk factors for pneumothorax themselves in order to explore the potential contribution of CBI. Results: We found 1. Multiple drugs are associated with pneumothorax; 2. Surfactants and oncology drugs account for most statistically distinctive associations with pneumothorax; 3. Pulmonary surfactants, pentamidine and nitric oxide have the largest statistical reporting associations 4. CBI may play a prominent role in reports of drug-associated pneumothorax. Conclusions: Disproportionality analysis (DA) can provide insights into the spontaneous reporting dependencies between drugs and pneumothorax. CBI assessment based on DA and Cornfield's inequality presents an additional novel option for the initial exploration of potential safety signals in PhV.

Background: The aim of this study was to investigate whether database restriction can improve oncology drug pharmacovigilance signal detection performance. Methods: We used spontaneous adverse event (AE) reports in the United States (US) Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) database. Positive control (PC) drug medical concept (DMC) pairs were selected from safety information not included in the product’s first label but subsequently added as label changes. These medical concepts (MCs) were mapped to the Medical Dictionary for Regulatory Activities (MedDRA) preferred terms (PTs) used in FAERS to code AEs. Negative controls (NC) were MCs with circumscribed PTs not included in the corresponding US package insert (USPI). We calculated shrinkage-adjusted observed-to-expected (O/E) reporting frequencies for the aforementioned drug–PT pairs. We also formulated an adjudication framework to calculate performance at the MC level. Performance metrics [sensitivity, specificity, positive and negative predictive value (PPV, NPV), signal/noise (S/N), F and Matthews correlation coefficient (MCC)] were calculated for each analysis and compared. Results: The PC reference set consisted of 11 drugs, 487 PTs, 27 MCs, 37 drug–MC combinations and 638 drug–event combinations (DECs). The NC reference set consisted of 11 drugs, 9 PTs, 5 MCs, 40 drug–MC combinations and 67 DECs. Most drug–event pairs were not highlighted by either analysis. A small percentage of signals of disproportionate reporting were lost, more noise than signal, with no gains. Specificity and PPV improved whereas sensitivity, NPV, F and MCC decreased, but all changes were small relative to the decrease in sensitivity. The overall S/N improved. Conclusion: This oncology drug restricted analysis improved the S/N ratio, removing proportionately more noise than signal, but with significant credible signal loss. Without broader experience and a calculus of costs and utilities of correct versus incorrect classifications in oncology pharmacovigilance such restricted analyses should be optional rather than a default analysis.

Over the past 4 decades, Asian American performers of Western classical mu sic have become a major force in the music industry. Among their ranks are A-list soloists, such as Sarah Chang and Yo-Yo Ma, members of world-renowned chamber groups, such as the siblings that make up the Ying Quartet, and concert masters of such major ensembles as the Chicago Symphony and the Philadelphia Orchestra. Arts administrators and admissions officers of music schools noticed the enormous influx of Asian Americans into classical music by the 1970s. Soon after, journalists began to write about it. In a 1980 New York Times article entitled "Oriental Musicians Come of Age," Leslie Rubinstein noted that 40 percent of the total enrollment (and two-thirds of the pianists) at Juilliard's precollege division was of Asian descent (Rubinstein 1980). Eight years later, John Rockwell wrote a fascinating article in which he argued that the influx of classical musicians of Asian descent was changing what he called the "New York sound." He asserts, "It might be argued that there hasn't been such a rewarding cultural synthesis in the classical performing arts as that currently taking place between Asian students and New York teachers and overall urban spirit since the blend of Russian pas sion and Jewish soul that characterized many of the great instrumentalists of earlier in the century" (Rockwell 1988). Despite Asian Americans' visibility in Western classical music, scholars of Asian American culture have until very recently ignored this phenomenon. There have been a few conference presentations on this topic by such scholars as Maiko Kawabata (2004), Roe-Min Kok (2006), and Mari Yoshihara (2006) over the past 5 years, but substantial publications have only arrived in the past year (Yang 2007; Yoshihara 2007). With this article, I aim to add to this growing literature by examining one Chinese American performer, Lang Lang, and his performances of "Chineseness." At 26, Lang Lang is one of the most sought-after pianists of our time. Born in Shenyang in northern China, Lang began studying piano when he was three and entered the Central Conservatory in Beijing when he was nine. After win ning the Tchaikovsky Young Musicians Competition in 1995, he enrolled at the

Cancer stem cells present a major therapeutic challenge - their effective eradication depends on therapeutic targeting of the relative vulnerabilities of the cancer stem cells vs. normal tissue stem cells. One feature that distinguishes cancer initiating and propagating cells from their normal counterparts is transcriptional addiction, providing opportunities for novel therapeutic interventions with the aim of curing cancer. CKIα ablation appears as a promising means of activating p53 and killing leukemia cells in MDS and AML (Elyada et al , doi:10.1038/nature09673; Kronke et al, doi: 10.1038/nature14610); yet, with no selective CKIα inhibitors for in vivo use, the therapeutic value of CKIα inhibition cannot be validated. We succeeded in developing two different classes of CKIα inhibitors, one inducing CKIα degradation, and another targeting the catalytic pocket of CKIα, with no degradation. Both inhibitor types activate p53, yet we found that CKIα ablation or degradation was not sufficient to selectively eliminate leukemia stem cells, due to robust expression of anti-apoptotic oncogenes driven by super-enhancer activation. Through extensive medicinal chemistry, we obtained CKIα catalytic inhibitors with profound killing capacity of primary mouse AML cells and human AML cell lines. We demonstrated a strong therapeutic effect in a mouse model of MLL-AF9-induced leukemia, with >40% cure rates evident by transplantation of bone marrow from treated leukemic mice to lethally irradiated normal mice. All transplanted mice regained normal blood counts, exclusively derived from the donor bone marrow. None showed any evidence of residual disease for 6 months, demonstrating a successful therapeutic window, distinguishing leukemia stem cells (LSCs) from HSPCs. Parallel in vitro experiments, show that the inhibitors did not affect normal hematopoietic progenitors in a CFU assay, but eliminated AML progenitors at an IC50 We found that CKIα inhibitors possessing potent anti-leukemia activity are distinguished by their capacity to co-target CDK9 and suppress the RNA Pol II elongation factor P-TEFb (CDK9-CyclinT1 complex), evident by blocking the phosphorylation of RNA Pol II C-terminal domain (pCTD2/5, see Figure). Co-crystallography studies elucidated the structural basis for co-targeting of CKIα and P-TEFb, the latter controls the rate limiting step of Poll-II-transcription and functions as a gatekeeper of super-enhancers. We found that both P-TEFb and super-enhancer activity are vigorously activated in AML cells. Therefore, the efficient P-TEFb-targeting activity of the inhibitors enables a selective blockade of leukemia super-enhancers (SE)-driven transcription, demonstrated by ChIP-seq analysis. As a result, SE-dependent transcription of major leukemia drivers including Myc and the anti-apoptotic oncogenes Bcl-2 and Mcl-1 was nearly abolished. Another remarkable feature of these dual CKIα-P-TEFb inhibitors is a rapid hit mechanism, by which, short drug exposure (10 mins in vitro and 2hrs in vivo) results in prolonged (24hrs) SE suppression and leukemia cell apoptosis. This unique property, which is at variance with the current occupancy-driven pharmacological paradigm, likely contributes to the dramatic therapeutic effect of co-targeting CKIα and P-TEFb in leukemia, whereby combination of rapid p53 induction with disruption of oncogenic super-enhancers eliminates leukemia stem cells without compromising normal HSPCs. The ability to disrupt super-enhancers and eliminate their associated oncogenes within minutes of drug exposure permits short intermittent therapy, which minimizes generalized toxicity. Indeed, at the therapeutic dose, we did not observe any significant adverse treatment effects even at daily treatment for 45 days in mice. To conclude, we developed a new class of small molecule inhibitors that co-targets CKIα and P-TEFb. These inhibitors have unique pharmacologic properties: short-term kinase inhibition results in long-term disruption of SE activity. Shutdown of leukemic super-enhancers in synergy with robust p53 activation compromises leukemic cells and stem cells addicted to SE-driven transcription. These features explain the powerful and specific anti-leukemic therapeutic effects of this new class of inhibitors in-vivo. Figure Figure. Disclosures Ben-Neriah: BioTheryX Inc.: Consultancy, Equity Ownership, Research Funding. Vacca: BioTheryX Inc.: Consultancy. Mercurio: BioTheryX: Employment, Equity Ownership.

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Masking is a statistical issue by which signals are hidden by the presence of other medicines in the database. In the absence algorithm, the impact of the masking effect has not been fully investigated.Our study is aimed at assessing the extent and the impact of the masking effect on two large spontaneous reporting databases.Cross sectional study using a set of terms of importance for public health in two spontaneous reporting databases.The analyses were performed on EudraVigilance (EV) and the Pfizer spontaneous reporting database (PfDB).Using the masking ratio, we have identified and removed the products inducing the highest masking effect.Studying a total of almost 50 000 drug-event combinations masking had an impact on approximately 60% of drug-event combinations were masked by another product with a masking ratio1 in EV and 84% in PfDB. The prevalence of important masking was quite rare (0.003% of the DECs) and mainly affected events rarely reported in EV. The products involved in the highest masking effects are products known to induce the reaction. The removal of the masking effect of the highest masking product has revealed 974 signals of disproportionate reporting in EV including true signals. The study shows that the original ranking provided by the quantitative methods included in our study is marginally affected by the removal of the masking product.Our study suggests that significant masking is rare in large spontaneous databases and mostly affects events rarely reported in EV.

Masking is a statistical issue by which true signals of disproportionate reporting are hidden by the presence of other products in the database. Masking is currently not perfectly understood. There is no algorithm to identify the potential masking drugs to remove them for subsequent analyses of disproportionality.The primary objective of our study is to develop a mathematical framework for assessing the extent and impact of the masking effect of measures of disproportionality.We have developed a masking ratio that quantifies the masking effect of a given product. We have conducted a simulation study to validate our algorithm.The masking ratio is a measure of the strength of the masking effect whether the analysis is performed at the report or event level, and the manner in which reports are allocated to cells in the contingency table significantly impact the masking mechanisms. The reports containing both the product of interest and the masking product need to be handled appropriately. The proposed algorithm can use simplified masking provided that underlying assumptions (in particular the size of the database) are verified. For any event, the strongest masking effect is associated with the drug with the highest number of records (reports excluding the product of interest).Our study provides significant insights with practical implications for real-world pharmacovigilance that are supported by both real and simulated data. The public health impact of masking is still unknown.

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