60 research outputs found

    Net clinical benefit of antiplatelet therapy was affected by patient preferences:A personalized benefit-risk assessment

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    Objectives: To assess the effect of patient preferences on the net clinical benefit (NCB) of an antiplatelet therapy for the secondary prevention of cardiovascular complications. Study Design and Setting: Risk equations were developed to estimate the individual predicted risk of key outcomes of antiplatelet treatment in patients with a prior myocardial infarction using the Clinical Practice Research Datalink linked to the Hospital Episode Statistics and UK Office of National Statistics databases. Patient preferences for outcomes of antiplatelet therapies were elicited in a separate discrete choice experiment survey. Trial hazard ratios, relative to placebo, were used to calculate the per-patient NCB using equal or preference weighting of outcomes. Results: Risk equations were estimated using 31,941 adults in the Clinical Practice Research Datalink population, of which 22,125 were included in the benefit-risk assessment. The mean NCB was lower in the preference-weighted than in the equal-weighted analysis (0.040 vs. 0.057; P < 0.0001), but the direction of effect was unchanged by the weighting. In analyses stratified by the presence of bleeding risk factors, including preference weighting altered the ranking of subgroups by NCB. Conclusion: Patient preference weighting may have a significant effect on NCB and should be included in personalized benefit-risk assessments

    Comparing Patient Preferences for Antithrombotic Treatment During the Acute and Chronic Phases of Myocardial Infarction:A Discrete-Choice Experiment

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    BACKGROUND: Antithrombotic drugs are used as preventive treatment in patients with a prior myocardial infarction (MI) in both the acute and chronic phases of the disease. To support patient-centered benefit–risk assessment, it is important to understand the influence of disease stage on patient preferences. OBJECTIVE: The aim of this study was to examine patient preferences for antithrombotic treatments and whether they differ by MI disease phase. METHODS: A discrete-choice experiment was used to elicit preferences of adults in the acute (≤ 365 days before enrolment) or chronic phase (> 365 days before enrolment) of MI for key ischemic events (risk of cardiovascular [CV] death, non-fatal MI, and non-fatal ischemic stroke) and bleeding events (risk of non-fatal intracranial hemorrhage and non-fatal other severe bleeding). Preference data were analyzed using the multinomial logit model. Trade-offs between attributes were calculated as the maximum acceptable increase in the risk of CV death for a decrease in the risk of the other outcomes. To assess the potential effect of sociodemographic and clinical characteristics on patient preferences, subgroups were introduced as interaction terms in logit models. RESULTS: The evaluable population included 155 patients with MI in the acute phase of disease and 180 in the chronic phase. The overall population was 82% male, mean age was 64.2 ± 9.6 years, and 93% had not experienced bleeding events or key ischemic events other than MI. Patients valued reduction in the risk of non-fatal intracranial hemorrhage more than CV death (p < 0.01) and CV death more than non-fatal ischemic events (p < 0.01). Preferences were similar in the acute and chronic populations (p = 0.17). However, older patients valued reduction in risk of MI more than younger patients (p = 0.04), and patients with bleeding risk factors valued reduction in the risk of CV death (p = 0.01) and MI (p = 0.01) less than patients without bleeding risk factors. Also, patients who were at high risk of future ischemic events valued reduction of the risk of CV death less than those at low risk (p = 0.01). CONCLUSION: Patient preferences for antithrombotic treatments were unaffected by disease stage but varied by bleeding risk and other factors. This heterogeneity in preferences is an important consideration because it can affect the benefit–risk balance and the acceptability of antithrombotic treatments to patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40271-021-00548-6

    How can patient preferences be used and communicated in the regulatory evaluation of medicinal products? Findings and recommendations from IMI PREFER and call to action

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    Objective: Patients have unique insights and are (in-)directly affected by each decision taken throughout the life cycle of medicinal products. Patient preference studies (PPS) assess what matters most to patients, how much, and what trade-offs patients are willing to make. IMI PREFER was a six-year European public-private partnership under the Innovative Medicines Initiative that developed recommendations on how to assess and use PPS in medical product decision-making, including in the regulatory evaluation of medicinal products. This paper aims to summarize findings and recommendations from IMI PREFER regarding i) PPS applications in regulatory evaluation, ii) when and how to consult with regulators on PPS, iii) how to reflect PPS in regulatory communication and iv) barriers and open questions for PPS in regulatory decision-making.Methods: PREFER performed six literature reviews, 143 interviews and eight focus group discussions with regulators, patient representatives, industry representatives, Health Technology Assessment bodies, payers, academics, and clincians between October 2016 and May 2022.Results: i) With respect to PPS applications, prior to the conduct of clinical trials of medicinal products, PPS could inform regulators’ understanding of patients’ unmet needs and relevant endpoints during horizon scanning activities and scientific advice. During the evaluation of a marketing authorization application, PPS could inform: a) the assessment of whether a product meets an unmet need, b) whether patient-relevant clinical trial endpoints and outcomes were studied, c) the understanding of patient-relevant effect sizes and acceptable trade-offs, and d) the identification of key (un-)favorable effects and uncertainties. ii) With respect to consulting with regulators on PPS, PPS researchers should ideally have early discussions with regulators (e.g., during scientific advice) on the PPS design and research questions. iii) Regarding external PPS communication, PPS could be reflected in the assessment report and product information (e.g., the European Public Assessment Report and the Summary of Product Characteristics). iv) Barriers relevant to the use of PPS in regulatory evaluation include a lack of PPS use cases and demonstrated impact on regulatory decision-making, and need for (financial) incentives, guidance and quality criteria for implementing PPS results in regulatory decision-making. Open questions concerning regulatory PPS use include: a) should a product independent broad approach to the design of PPS be taken and/or a product-specific one, b) who should optimally be financing, designing, conducting, and coordinating PPS, c) when (within and/or outside clinical trials) to perform PPS, and d) how can PPS use best be operationalized in regulatory decisions.Conclusion: PPS have high potential to inform regulators on key unmet needs, endpoints, benefits, and risks that matter most to patients and their acceptable trade-offs. Regulatory guidelines, templates and checklists, together with incentives are needed to foster structural and transparent PPS submission and evaluation in regulatory decision-making. More PPS case studies should be conducted and submitted for regulatory assessment to enable regulatory discussion and increase regulators’ experience with PPS implementation and communication in regulatory evaluations

    Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

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    Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

    The Eighth Data Release of the Sloan Digital Sky Survey: First Data from SDSS-III

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    The Sloan Digital Sky Survey (SDSS) started a new phase in August 2008, with new instrumentation and new surveys focused on Galactic structure and chemical evolution, measurements of the baryon oscillation feature in the clustering of galaxies and the quasar Ly alpha forest, and a radial velocity search for planets around ~8000 stars. This paper describes the first data release of SDSS-III (and the eighth counting from the beginning of the SDSS). The release includes five-band imaging of roughly 5200 deg^2 in the Southern Galactic Cap, bringing the total footprint of the SDSS imaging to 14,555 deg^2, or over a third of the Celestial Sphere. All the imaging data have been reprocessed with an improved sky-subtraction algorithm and a final, self-consistent photometric recalibration and flat-field determination. This release also includes all data from the second phase of the Sloan Extension for Galactic Understanding and Evolution (SEGUE-2), consisting of spectroscopy of approximately 118,000 stars at both high and low Galactic latitudes. All the more than half a million stellar spectra obtained with the SDSS spectrograph have been reprocessed through an improved stellar parameters pipeline, which has better determination of metallicity for high metallicity stars.Comment: Astrophysical Journal Supplements, in press (minor updates from submitted version

    Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

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    This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

    Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

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    Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

    The Cancer Genome Atlas Comprehensive Molecular Characterization of Renal Cell Carcinoma

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    SDSS-III: Massive Spectroscopic Surveys of the Distant Universe, the Milky Way Galaxy, and Extra-Solar Planetary Systems

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    Building on the legacy of the Sloan Digital Sky Survey (SDSS-I and II), SDSS-III is a program of four spectroscopic surveys on three scientific themes: dark energy and cosmological parameters, the history and structure of the Milky Way, and the population of giant planets around other stars. In keeping with SDSS tradition, SDSS-III will provide regular public releases of all its data, beginning with SDSS DR8 (which occurred in Jan 2011). This paper presents an overview of the four SDSS-III surveys. BOSS will measure redshifts of 1.5 million massive galaxies and Lya forest spectra of 150,000 quasars, using the BAO feature of large scale structure to obtain percent-level determinations of the distance scale and Hubble expansion rate at z<0.7 and at z~2.5. SEGUE-2, which is now completed, measured medium-resolution (R=1800) optical spectra of 118,000 stars in a variety of target categories, probing chemical evolution, stellar kinematics and substructure, and the mass profile of the dark matter halo from the solar neighborhood to distances of 100 kpc. APOGEE will obtain high-resolution (R~30,000), high signal-to-noise (S/N>100 per resolution element), H-band (1.51-1.70 micron) spectra of 10^5 evolved, late-type stars, measuring separate abundances for ~15 elements per star and creating the first high-precision spectroscopic survey of all Galactic stellar populations (bulge, bar, disks, halo) with a uniform set of stellar tracers and spectral diagnostics. MARVELS will monitor radial velocities of more than 8000 FGK stars with the sensitivity and cadence (10-40 m/s, ~24 visits per star) needed to detect giant planets with periods up to two years, providing an unprecedented data set for understanding the formation and dynamical evolution of giant planet systems. (Abridged)Comment: Revised to version published in The Astronomical Journa
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