22 research outputs found

    Quantifying the impact of novel metastatic cancer therapies on health inequalities in survival outcomes

    Get PDF
    Background: Novel therapies in metastatic cancers have contributed to improvements in survival outcomes, yet real-world data suggest that improvements may be mainly driven by those patient groups who already had the highest survival outcomes. This study aimed to develop and apply a framework for quantifying the impact of novel metastatic cancer therapies on health inequalities in survival outcomes based on published aggregate data.Methods: Nine (N = 9) novel therapies for metastatic breast cancer (mBC), metastatic colorectal cancer (mCRC), and metastatic non–small cell lung cancer (mNSCLC) were identified, 3 for each cancer type. Individual patient data (IPD) for overall survival (OS) and progression-free survival (PFS) were replicated from published Kaplan-Meier (KM) curves. For each cancer type, data were pooled for the novel therapies and comparators separately and weighted based on sample size to ensure equal contribution of each therapy in the analyses. Parametric (mixture) distributions were fitted to the weighted data to model and extrapolate survival. The inequality in survival was defined by the absolute difference between groups with the highest and lowest survival for 2 stratifications: one for which survival was stratified into 2 groups and one using 5 groups. Additionally, a linear regression model was fitted to survival estimates for the 5 groups, with the regression coefficient or slope considered as the inequality gradient (IG). The impact of the pooled novel therapies was subsequently defined as the change in survival inequality relative to the pooled comparator therapies. A probabilistic analysis was performed to quantify parameter uncertainty.Results: The analyses found that novel therapies were associated with significant increases in inequalities in survival outcomes relative to their comparators, except in terms of OS for mNSCLC. For mBC, the inequalities in OS increased by 13.9 (95% CI: 1.4; 26.6) months, or 25.0%, if OS was stratified in 5 groups. The IG for mBC increased by 3.2 (0.3; 6.1) months, or 24.7%. For mCRC, inequalities increased by 6.7 (3.0; 10.5) months, or 40.4%, for stratification based on 5 groups; the IG increased by 1.6 (0.7; 2.4) months, or 40.2%. For mNSCLC, inequalities decreased by 14.9 (−84.5; 19.0) months, or 12.2%, for the 5-group stratification; the IG decreased by 2.0 (−16.1; 5.1) months, or 5.5%. Results for the stratification based on 2 groups demonstrated significant increases in OS inequality for all cancer types. In terms of PFS, the increases in survival inequalities were larger in a relative sense compared with OS. For mBC, PFS inequalities increased by 8.7 (5.9; 11.6) months, or 71.7%, for stratification based on 5 groups; the IG increased by 2.0 (1.3; 2.6) months, or 67.6%. For mCRC, PFS inequalities increased by 5.4 (4.2; 6.6) months, or 147.6%, for the same stratification. The IG increased by 1.3 (1.1; 1.6) months, or 172.7%. For mNSCLC, inequalities increased by 18.2 (12.5; 24.4) months, or 93.8%, for the 5-group stratification; the IG increased by 4.0 (2.8; 5.4) months, or 88.1%. Results from the stratification based on 2 groups were similar.Conclusion: Novel therapies for mBC, mCRC, and mNSCLC are generally associated with significant increases in survival inequalities relative to their comparators in randomized controlled trials, though inequalities in OS for mNSCLC decreased nonsignificantly when stratified based on 5 groups. Although further research using real-world IPD is warranted to assess how, for example, social determinants of health affect the impact of therapies on health inequalities among patient groups, the proposed framework can provide important insights in the absence of such data

    Search for supersymmetry with a dominant R-parity violating LQDbar couplings in e+e- collisions at centre-of-mass energies of 130GeV to 172 GeV

    Full text link
    A search for pair-production of supersymmetric particles under the assumption that R-parity is violated via a dominant LQDbar coupling has been performed using the data collected by ALEPH at centre-of-mass energies of 130-172 GeV. The observed candidate events in the data are in agreement with the Standard Model expectation. This result is translated into lower limits on the masses of charginos, neutralinos, sleptons, sneutrinos and squarks. For instance, for m_0=500 GeV/c^2 and tan(beta)=sqrt(2) charginos with masses smaller than 81 GeV/c^2 and neutralinos with masses smaller than 29 GeV/c^2 are excluded at the 95% confidence level for any generation structure of the LQDbar coupling.Comment: 32 pages, 30 figure

    Search for Bs0B^{0}_{s} oscillations using inclusive lepton events

    Get PDF
    A search for Bs oscillations is performed using a sample of semileptonic b-hadron decays collected by the ALEPH experiment during 1991-1995. Compared to previous inclusive lepton analyses, the prop er time resolution and b-flavour mistag rate are significantly improved. Additional sensitivity to Bs mixing is obtained by identifying subsamples of events having a Bs purity which is higher than the average for the whole data sample. Unbinned maximum likelihood amplitude fits are performed to derive a lower limit of Dms>9.5 ps-1 at 95% CL. Combining with the ALEPH Ds based analyses yields Dms>9.6 ps-1 at 95% CL.A search for B0s oscillations is performed using a sample of semileptonic b-hadron decays collected by the ALEPH experiment during 1991-1995. Compared to previous inclusive lepton analyses, the proper time resolution and b-flavour mistag rate are significantly improved. Additional sensitivity to B0s mixing is obtained by identifying subsamples of events having a B0s purity which is higher than the average for the whole data sample. Unbinned maximum likelihood amplitude fits are performed to derive a lower limit of Deltam_s>9.5ps^-1 at 95% CL. Combining with the ALEPH D-s based analyses yields Deltam_s>9.6ps^-1 at 95% CL

    Genomic Relationships, Novel Loci, and Pleiotropic Mechanisms across Eight Psychiatric Disorders

    Get PDF
    Genetic influences on psychiatric disorders transcend diagnostic boundaries, suggesting substantial pleiotropy of contributing loci. However, the nature and mechanisms of these pleiotropic effects remain unclear. We performed analyses of 232,964 cases and 494,162 controls from genome-wide studies of anorexia nervosa, attention-deficit/hyper-activity disorder, autism spectrum disorder, bipolar disorder, major depression, obsessive-compulsive disorder, schizophrenia, and Tourette syndrome. Genetic correlation analyses revealed a meaningful structure within the eight disorders, identifying three groups of inter-related disorders. Meta-analysis across these eight disorders detected 109 loci associated with at least two psychiatric disorders, including 23 loci with pleiotropic effects on four or more disorders and 11 loci with antagonistic effects on multiple disorders. The pleiotropic loci are located within genes that show heightened expression in the brain throughout the lifespan, beginning prenatally in the second trimester, and play prominent roles in neurodevelopmental processes. These findings have important implications for psychiatric nosology, drug development, and risk prediction.Peer reviewe

    The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

    Get PDF
    INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

    Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

    Get PDF
    Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

    DataSheet1_Quantifying the impact of novel metastatic cancer therapies on health inequalities in survival outcomes.pdf

    No full text
    Background: Novel therapies in metastatic cancers have contributed to improvements in survival outcomes, yet real-world data suggest that improvements may be mainly driven by those patient groups who already had the highest survival outcomes. This study aimed to develop and apply a framework for quantifying the impact of novel metastatic cancer therapies on health inequalities in survival outcomes based on published aggregate data.Methods: Nine (N = 9) novel therapies for metastatic breast cancer (mBC), metastatic colorectal cancer (mCRC), and metastatic non–small cell lung cancer (mNSCLC) were identified, 3 for each cancer type. Individual patient data (IPD) for overall survival (OS) and progression-free survival (PFS) were replicated from published Kaplan-Meier (KM) curves. For each cancer type, data were pooled for the novel therapies and comparators separately and weighted based on sample size to ensure equal contribution of each therapy in the analyses. Parametric (mixture) distributions were fitted to the weighted data to model and extrapolate survival. The inequality in survival was defined by the absolute difference between groups with the highest and lowest survival for 2 stratifications: one for which survival was stratified into 2 groups and one using 5 groups. Additionally, a linear regression model was fitted to survival estimates for the 5 groups, with the regression coefficient or slope considered as the inequality gradient (IG). The impact of the pooled novel therapies was subsequently defined as the change in survival inequality relative to the pooled comparator therapies. A probabilistic analysis was performed to quantify parameter uncertainty.Results: The analyses found that novel therapies were associated with significant increases in inequalities in survival outcomes relative to their comparators, except in terms of OS for mNSCLC. For mBC, the inequalities in OS increased by 13.9 (95% CI: 1.4; 26.6) months, or 25.0%, if OS was stratified in 5 groups. The IG for mBC increased by 3.2 (0.3; 6.1) months, or 24.7%. For mCRC, inequalities increased by 6.7 (3.0; 10.5) months, or 40.4%, for stratification based on 5 groups; the IG increased by 1.6 (0.7; 2.4) months, or 40.2%. For mNSCLC, inequalities decreased by 14.9 (−84.5; 19.0) months, or 12.2%, for the 5-group stratification; the IG decreased by 2.0 (−16.1; 5.1) months, or 5.5%. Results for the stratification based on 2 groups demonstrated significant increases in OS inequality for all cancer types. In terms of PFS, the increases in survival inequalities were larger in a relative sense compared with OS. For mBC, PFS inequalities increased by 8.7 (5.9; 11.6) months, or 71.7%, for stratification based on 5 groups; the IG increased by 2.0 (1.3; 2.6) months, or 67.6%. For mCRC, PFS inequalities increased by 5.4 (4.2; 6.6) months, or 147.6%, for the same stratification. The IG increased by 1.3 (1.1; 1.6) months, or 172.7%. For mNSCLC, inequalities increased by 18.2 (12.5; 24.4) months, or 93.8%, for the 5-group stratification; the IG increased by 4.0 (2.8; 5.4) months, or 88.1%. Results from the stratification based on 2 groups were similar.Conclusion: Novel therapies for mBC, mCRC, and mNSCLC are generally associated with significant increases in survival inequalities relative to their comparators in randomized controlled trials, though inequalities in OS for mNSCLC decreased nonsignificantly when stratified based on 5 groups. Although further research using real-world IPD is warranted to assess how, for example, social determinants of health affect the impact of therapies on health inequalities among patient groups, the proposed framework can provide important insights in the absence of such data.</p

    Assessment of cardiovascular risk and prevention of cardiovascular disease in women with the polycystic ovary syndrome: A consensus statement by the Androgen Excess and Polycystic Ovary Syndrome (AE-PCOS) Society

    No full text
    Objective: Women with polycystic ovary syndrome (PCOS) often have cardiovascular disease (CVD) risk factors. The Androgen Excess and Polycystic Ovary Syndrome (AE-PCOS) Society created a panel to provide evidence-based reviews of studies assessing PCOS-CVD risk relationships and to develop guidelines for preventing CVD. Participants: An expert panel in PCOS and CVD reviewed literature and presented recommendations. Evidence: Only studies comparing PCOS with control patients were included. All electronic databases were searched; reviews included individual studies/databases, systematic reviews, abstracts, and expert data. Articles were excluded if other hyperandrogenic disorders were not excluded, PCOS diagnosis was unclear, controls were not described, or methodology precluded evaluation. Inclusion/exclusion criteria were confirmed by at least two reviewers and arbitrated by a third. Consensus Process: Systematic reviews of CVD risk factors were compiled and submitted for approval to the AE-PCOS Society Board. Conclusions: Women with PCOS with obesity, cigarette smoking, dyslipidemia, hypertension, impaired glucose tolerance, and subclinical vascular disease are at risk, whereas those with metabolic syndrome and/or type 2 diabetes mellitus are at high risk for CVD. Body mass index, waist circumference, serum lipid/glucose, and blood pressure determinations are recommended for all women with PCOS, as is oral glucose tolerance testing in those with obesity, advanced age, personal history of gestational diabetes, or family history of type 2 diabetes mellitus. Mood disorder assessment is suggested in all PCOS patients. Lifestyle management is recommended for primary CVD prevention, targeting low-density and non-high-density lipoprotein cholesterol and adding insulin-sensitizing and other drugs if dyslipidemia or other risk factors persist.Robert A. Wild, Enrico Carmina, Evanthia Diamanti-Kandarakis, Anuja Dokras, Hector F. Escobar-Morreale, Walter Futterweit, Rogerio Lobo, Robert J. Norman, Evelyn Talbott and Daniel A. Dumesi

    Delphinidin activates NFAT and induces IL-2 production through SOCE in T cells

    No full text
    Delphinidin is an anthocyanidin that possesses antioxidant and anti-inflammatory effects; however, some reports suggest that delphinidin has pro-inflammatory properties. For this reason, we assessed the effect of delphinidin on cytokine production in T cells. We demonstrated that delphinidin increased the cytosolic-free Ca2+ concentration by releasing Ca2+ from intracellular stores and increasing Ca2+ entry. The putative Ca2+ release activated Ca2+ (CRAC) channel inhibitors BTP2 and gadolinium reduced the calcium entry stimulated by the anthocyanidin. Delphinidin induced nuclear factor of activated T cells (NFAT) translocation and NFAT-Luc activity in Jurkat cells and was dependent on the CRAC channel and calcineurin pathway. Delphinidin increased the mRNA expression and production of IL-2 in Jurkat cells and was inhibited by BTP2 and cyclosporine A. Using peripheral blood lymphocytes, we demonstrated that delphinidin increased the production of IL-2 and IFN-¿ and was inhibited by BTP2. Taken together, our results suggest that delphinidin exerts immunostimulatory effects on T cells by increasing cytokine production through CRAC channel and NFAT activation. © 2013 Springer Science+Business Media New York.This work was supported by Grants from Consorcio de Tecnología e Innovación para la Salud CTI-Salud (CTE-06), Chile (CONICYT 21090900 and CONICYT T-24100037).Peer Reviewe
    corecore