56 research outputs found
Predictive ability of a drug-based score in patients with advanced non–small-cell lung cancer receiving first-line immunotherapy
Differential influence of antibiotic therapy and other medications on oncological outcomes of patients with non-small cell lung cancer treated with first-line pembrolizumab versus cytotoxic chemotherapy
Prognostic impact of the cumulative dose and dose intensity of everolimus in patients with pancreatic neuroendocrine tumors
The aim of this work is to assess if cumulative dose (CD) and dose intensity (DI) of everolimus may affect survival of advanced pancreatic neuroendocrine tumors (PNETs) patients. One hundred and sixteen patients (62 males and 54 females, median age 55\ua0years) with advanced PNETs were treated with everolimus for 653\ua0months. According to a Receiver operating characteristics (ROC) analysis, patients were stratified into two groups, with CD\ua0 64\ua03000\ua0mg (Group A; n\ua0=\ua068) and CD\ua0>\ua03000\ua0mg (Group B; n\ua0=\ua048). The response rate and toxicity were comparable in the two groups. However, patients in group A experienced more dose modifications than patients in group B. Median OS was 24\ua0months in Group A while in Group B it was not reached (HR: 26.9; 95% CI: 11.0-76.7; P\ua0<\ua00.0001). Patients who maintained a DI higher than 9\ua0mg/day experienced a significantly longer OS and experienced a trend to higher response rate. Overall, our study results showed that both CD and DI of everolimus play a prognostic role for patients with advanced PNETs treated with everolimus. This should prompt efforts to continue everolimus administration in responsive patients up to at least 3000\ua0mg despite delays or temporary interruptions
Baseline BMI and BMI variation during first line pembrolizumab in NSCLC patients with a PD-L1 expression >= 50%: a multicenter study with external validation
Background The association between obesity and
outcomes in patients receiving programmed death-1/
programmed death ligand-1 (PD-L1) checkpoint inhibitors
has already been confirmed in pre-treated non-small cell
lung cancer (NSCLC) patients, regardless of PD-L1 tumor
expression.
Methods We present the outcomes analysis according
to baseline body mass index (BMI) and BMI variation in a
large cohort of metastatic NSCLC patients with a PD-L1
expression ≥50%, receiving first line pembrolizumab.
We also evaluated a control cohort of metastatic
NSCLC patients treated with first line platinum-based
chemotherapy. Normal weight was set as control group.
Results 962 patients and 426 patients were included
in the pembrolizumab and chemotherapy cohorts,
respectively. Obese patients had a significantly higher
objective response rate (ORR) (OR=1.61 (95% CI: 1.04–
2.50)) in the pembrolizumab cohort, while overweight
patients had a significantly lower ORR (OR=0.59 (95%
CI: 0.37–0.92)) within the chemotherapy cohort. Obese
patients had a significantly longer progression-free
survival (PFS) (HR=0.61 (95% CI: 0.45–0.82)) in the
pembrolizumab cohort. Conversely, they had a significantly
shorter PFS in the chemotherapy cohort (HR=1.27 (95%
CI: 1.01–1.60)). Obese patients had a significantly longer
overall survival (OS) within the pembrolizumab cohort
(HR=0.70 (95% CI: 0.49–0.99)), while no significant
differences according to baseline BMI were found in the
chemotherapy cohort. BMI variation significantly affected
ORR, PFS and OS in both the pembrolizumab and the
chemotherapy cohorts.
Conclusions Baseline obesity is associated to
significantly improved ORR, PFS and OS in metastatic
NSCLC patients with a PD-L1 expression of ≥50%,
receiving first line pembrolizumab, but not among
patients treated with chemotherapy. BMI variation is also
significantly related to clinical outcomes
The Ontology for Biomedical Investigations
The Ontology for Biomedical Investigations (OBI) is an ontology that provides terms with precisely defined meanings to describe all aspects of how investigations in the biological and medical domains are conducted. OBI re-uses ontologies that provide a representation of biomedical knowledge from the Open Biological and Biomedical Ontologies (OBO) project and adds the ability to describe how this knowledge was derived. We here describe the state of OBI and several applications that are using it, such as adding semantic expressivity to existing databases, building data entry forms, and enabling interoperability between knowledge resources. OBI covers all phases of the investigation process, such as planning, execution and reporting. It represents information and material entities that participate in these processes, as well as roles and functions. Prior to OBI, it was not possible to use a single internally consistent resource that could be applied to multiple types of experiments for these applications. OBI has made this possible by creating terms for entities involved in biological and medical investigations and by importing parts of other biomedical ontologies such as GO, Chemical Entities of Biological Interest (ChEBI) and Phenotype Attribute and Trait Ontology (PATO) without altering their meaning. OBI is being used in a wide range of projects covering genomics, multi-omics, immunology, and catalogs of services. OBI has also spawned other ontologies (Information Artifact Ontology) and methods for importing parts of ontologies (Minimum information to reference an external ontology term (MIREOT)). The OBI project is an open cross-disciplinary collaborative effort, encompassing multiple research communities from around the globe. To date, OBI has created 2366 classes and 40 relations along with textual and formal definitions. The OBI Consortium maintains a web resource (http://obi-ontology.org) providing details on the people, policies, and issues being addressed in association with OBI. The current release of OBI is available at http://purl.obolibrary.org/obo/obi.owl
Video Annotation with Pictorially Enriched Ontologies
Video annotation is typically performed by classifying video elements according to some pre-defined ontology of the video content domain. Ontologies are defined by establishing relationships between linguistic terms, that specify domain concepts at different abstraction levels. However, although linguistic terms are appropriate to distinguish event and object categories, they are inadequate when they must describe specific patterns of events or video entities. Instead, in these cases, pattern specifications are better expressed through visual prototypes that capture the essence of the event or entity. Pictorially enriched ontologies, that include visual concepts together with linguistic keywords, are therefore needed tosupport video annotation up to the level of detail of pattern specification. This paper presents pictorially enriched ontologies and provide a solution for their implementation in the soccer video domain. The pictorially enriched ontology is used both to directly assign multimedia objects to concepts, providing a more meaningful definition than the linguistics terms, and to extend the initial knowledge of the domain, adding subclasses of highlights or new highlight classes that were not defined in the linguistic ontology. Automatic annotation of soccer clips up to the pattern specification level using a pictorially enriched ontology is discussed
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