Severe sepsis poses a major burden on the U.S. healthcare system. Previous epidemiologic studies have not differentiated community-acquired severe sepsis from healthcare-associated severe sepsis or ...hospital-acquired severe sepsis hospitalizations. We sought to compare and contrast community-acquired severe sepsis, healthcare-associated severe sepsis, and hospital-acquired severe sepsis hospitalizations in a national hospital sample.
Retrospective analysis of severe sepsis discharges from University HealthSystem Consortium hospitals in 2012.
United States.
We used the criteria from Angus et al (discharge diagnoses for both a serious infection and organ dysfunction) to identify severe sepsis hospitalizations. We defined healthcare-associated severe sepsis as severe sepsis hospitalizations with an infection present at admission, where the patient was a nursing home resident, was on hemodialysis, or was readmitted within 30 days of a prior hospitalization. We defined community-acquired severe sepsis as all other severe sepsis patients with an infection present at admission. We defined hospital-acquired severe sepsis as severe sepsis patients where the documented infection was not present at admission.
None.
Prevalence of community-acquired severe sepsis, healthcare-associated severe sepsis, and hospital-acquired severe sepsis, adjusted hospital mortality, length of hospitalization, length of stay in an ICU, and hospital costs. Among 3,355,753 hospital discharges, there were 307,491 with severe sepsis, including 193,081 (62.8%) community-acquired severe sepsis, 79,581 (25.9%) healthcare-associated severe sepsis, and 34,829 (11.3%) hospital-acquired severe sepsis. Hospital-acquired severe sepsis and healthcare-associated severe sepsis exhibited higher in-hospital mortality than community-acquired severe sepsis (hospital acquired 19.2% vs healthcare associated 12.8% vs community acquired 8.6%). Hospital-acquired severe sepsis had greater resource utilization than both healthcare-associated severe sepsis and community-acquired severe sepsis, with higher median length of hospital stay (hospital acquired 17 d vs healthcare associated 7 d vs community acquired 6 d), median length of ICU stay (hospital acquired 8 d vs healthcare associated 3 d vs community acquired 3 d), and median hospital costs (hospital acquired $38,369 vs healthcare associated $8,796 vs community acquired $7,024).
In this series, severe sepsis hospitalizations included community-acquired severe sepsis (62.8%), healthcare-associated severe sepsis (25.9%), and hospital-acquired severe sepsis (11.3%) cases. Hospital-acquired severe sepsis was associated with both higher mortality and resource utilization than community-acquired severe sepsis and healthcare-associated severe sepsis.
Ipilimumab is the prototypical immunomodulatory antibody, approved by the FDA in 2011 for advanced melanoma on the basis of survival benefit. Since that time, we have made significant strides in ...optimizing this therapy: we have characterized the spectrum of immune-related adverse events and learned how to mitigate them with treatment algorithms, discovered potential biomarkers of activity, and identified the potential synergy between checkpoint modulation and other therapeutic modalities. Recent phase I trials have established the efficacy and safety of next-generation checkpoint agents, including PD-1 and PD-L1 inhibitors, across multiple tumor types. Much work lies ahead in developing these next-generation checkpoint agents, testing them in combination, and determining how to integrate them into the treatment paradigms of various tumor types.
Mounting evidence supports a role for the immune system in breast cancer outcomes. The ability to distinguish highly immunogenic tumors susceptible to anti-tumor immunity from weakly immunogenic or ...inherently immune-resistant tumors would guide development of therapeutic strategies in breast cancer. Genomic, transcriptomic and clinical data from The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) breast cancer cohorts were used to examine statistical associations between tumor mutational burden (TMB) and the survival of patients whose tumors were assigned to previously-described prognostic immune subclasses reflecting favorable, weak or poor immune-infiltrate dispositions (FID, WID or PID, respectively). Tumor immune subclasses were associated with survival in patients with high TMB (TMB-Hi, P < 0.001) but not in those with low TMB (TMB-Lo, P = 0.44). This statistical relationship was confirmed in the METABRIC cohort (TMB-Hi, P = 0.047; TMB-Lo, P = 0.39), and also found to hold true in the more-indolent Luminal A tumor subtype (TMB-Hi, P = 0.011; TMB-Lo, P = 0.91). In TMB-Hi tumors, the FID subclass was associated with prolonged survival independent of tumor stage, molecular subtype, age and treatment. Copy number analysis revealed the reproducible, preferential amplification of chromosome 1q immune-regulatory genes in the PID immune subclass. These findings demonstrate a previously unappreciated role for TMB as a determinant of immune-mediated survival of breast cancer patients and identify candidate immune-regulatory mechanisms associated with immunologically cold tumors. Immune subtyping of breast cancers may offer opportunities for therapeutic stratification.
The H&E stromal tumor-infiltrating lymphocyte (sTIL) score and programmed death ligand 1 (PD-L1) SP142 immunohistochemistry assay are prognostic and predictive in early-stage breast cancer, but are ...operator-dependent and may have insufficient precision to characterize dynamic changes in sTILs/PD-L1 in the context of clinical research. We illustrate how multiplex immunofluorescence (mIF) combined with statistical modeling can be used to precisely estimate dynamic changes in sTIL score, PD-L1 expression, and other immune variables from a single paraffin-embedded slide, thus enabling comprehensive characterization of activity of novel immunotherapy agents.
Serial tissue was obtained from a recent clinical trial evaluating loco-regional cytokine delivery as a strategy to promote immune cell infiltration and activation in breast tumors. Pre-treatment biopsies and post-treatment tumor resections were analyzed by mIF (PerkinElmer Vectra) using an antibody panel that characterized tumor cells (cytokeratin-positive), immune cells (CD3, CD8, CD163, FoxP3), and PD-L1 expression. mIF estimates of sTIL score and PD-L1 expression were compared to the H&E/SP142 clinical assays. Hierarchical linear modeling was utilized to compare pre- and post-treatment immune cell expression, account for correlation of time-dependent measurement, variation across high-powered magnification views within each subject, and variation between subjects. Simulation methods (Monte Carlo, bootstrapping) were used to evaluate the impact of model and tissue sample size on statistical power.
mIF estimates of sTIL and PD-L1 expression were strongly correlated with their respective clinical assays (p < .001). Hierarchical linear modeling resulted in more precise estimates of treatment-related increases in sTIL, PD-L1, and other metrics such as CD8+ tumor nest infiltration. Statistical precision was dependent on adequate tissue sampling, with at least 15 high-powered fields recommended per specimen. Compared to conventional t-testing of means, hierarchical linear modeling was associated with substantial reductions in enrollment size required (n = 25➔n = 13) to detect the observed increases in sTIL/PD-L1.
mIF is useful for quantifying treatment-related dynamic changes in sTILs/PD-L1 and is concordant with clinical assays, but with greater precision. Hierarchical linear modeling can mitigate the effects of intratumoral heterogeneity on immune cell count estimations, allowing for more efficient detection of treatment-related pharmocodynamic effects in the context of clinical trials.
NCT02950259 .
In just a few years, microarrays have gone from obscurity to being almost ubiquitous in biological research. At the same time, the statistical methodology for microarray analysis has progressed from ...simple visual assessments of results to a weekly deluge of papers that describe purportedly novel algorithms for analysing changes in gene expression. Although the many procedures that are available might be bewildering to biologists who wish to apply them, statistical geneticists are recognizing commonalities among the different methods. Many are special cases of more general models, and points of consensus are emerging about the general approaches that warrant use and elaboration.
We consider modeling a dependent sequence of random partitions. It is well known in Bayesian nonparametrics that a random measure of discrete type induces a distribution over random partitions. The ...community has therefore assumed that the best approach to obtain a dependent sequence of random partitions is through modeling dependent random measures. We argue that this approach is problematic and show that the random partition model induced by dependent Bayesian nonparametric priors exhibits counter-intuitive dependence among partitions even though the dependence for the sequence of random probability measures is intuitive. Because of this, we suggest directly modeling the sequence of random partitions when clustering is of principal interest. To this end, we develop a class of dependent random partition models that explicitly models dependence in a sequence of partitions. We derive conditional and marginal properties of the joint partition model and devise computational strategies when employing the method in Bayesian modeling. In the case of temporal dependence, we demonstrate through simulation how the methodology produces partitions that evolve gently and naturally over time. We further illustrate the utility of the method by applying it to an environmental dataset that exhibits spatio-temporal dependence. Supplemental files for this article are available online.
The Human Tumor Atlas Network is a multi-institutional effort to generate genomic and histologic datasets spanning thousands of patients. Johnson et al., in this issue of Cell Reports Medicine, ...illustrate how disparate data types from a single case can be combined to discover novel therapeutic directions.
The Human Tumor Atlas Network is a multi-institutional effort to generate genomic and histologic datasets spanning thousands of patients. Johnson et al., in this issue of Cell Reports Medicine, illustrate how disparate data types from a single case can be combined to discover novel therapeutic directions.
Immune checkpoint blockade Naidoo, Jarushka; Page, David B; Wolchok, Jedd D
Hematology/oncology clinics of North America,
06/2014, Letnik:
28, Številka:
3
Journal Article
Recenzirano
Since the development and approval of Ipilimumab, the first immune checkpoint inhibitor licensed for the treatment of metastatic melanoma, clinicians have gained a better understanding of the mode of ...action, management of toxicities, and assessment of response to this class of drugs. Several antibodies are now in development, aimed at blocking novel immune checkpoint molecules, such as PD-1 and it's corresponding ligand PD-L1. This article summarizes the mechanism of action, preclinical development, and subsequent clinical studies of immune checkpoint antibodies in melanoma.
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