scholarly journals Panel Informativity Optimizer (PIO): an R package to improve cancer NGS panel informativity

2021 ◽  
Author(s):  
Vincent Alcazer ◽  
Pierre Sujobert
Keyword(s):  
Real Life ◽  
R Package ◽  
Cancer Type ◽  
Optimization Strategy ◽  
Panel Size ◽  
Number Of Patients ◽  
Exon Level ◽  
Definition Of ◽  
Private Datasets ◽  
Optimal Set

Mutation detection by next generation sequencing (NGS) is routinely used for cancer diagnosis. Selecting an optimal set of genes for a given cancer is not trivial as it has to optimize informativity (i.e. the number of patients with at least one mutation in the panel), while minimizing panel length in order to reduce sequencing costs and increase sensitivity. We propose herein Panel Informativity Optimizer (PIO), an open-source software developed as an R package with a user-friendly graphical interface to help optimize cancer NGS panel informativity. Using patient-level mutational data from either private datasets or preloaded dataset of 91 independent cohort from 31 different cancer type, PIO selects an optimal set of genomic intervals to maximize informativity and panel size in a given cancer type. Different options are offered such as the definition of genomic intervals at the gene or exon level, and the use of optimization strategy at the patient or patient per kilobase level. PIO can also propose an optimal set of genomic intervals to increase informativity of custom panels. A panel tester function is also available for panel benchmarking. Using public databases, as well as data from real-life settings, we demonstrate that PIO allows panel size reduction of up to 1000kb, and accurately predicts the performance of custom or commercial panels. PIO is available online at https://vincentalcazer.shinyapps.io/Panel_informativity_optimizer/ or can be set on a locale machine from https://github.com/VincentAlcazer/PIO.

Is Treat-to-target in Lupus Nephritis Realistic in Clinical Practice?

2018 ◽  
Vol 15 (1) ◽  
pp. 2-6 ◽  
Author(s):  
Chi Chiu Mok
Keyword(s):  
Lupus Nephritis ◽  
Disease Activity ◽  
Safety Concern ◽  
Real Life ◽  
Current Treatment ◽  
Treat To Target ◽  
Low Disease Activity ◽  
Activity State ◽  
Definition Of ◽  
Comparative Trials

The Treat-to-Target (T2T) principle has been advocated in a number of inflammatory and non-inflammatory medical illnesses. Tight control of disease activity has been shown to improve the outcome of rheumatoid arthritis and psoriatic arthritis as compared to the conventional approach. However, whether T2T can be applied to patients with lupus nephritis is still under emerging discussion. Treatment of lupus nephritis should target at inducing and maintaining remission of the kidney inflammation so as to preserve renal function and improve survival in the longterm. However, there is no universal agreement on the definition of remission or low disease activity state of nephritis, as well as the time points for switching of therapies. Moreover, despite the availability of objective parameters for monitoring such as proteinuria and urinary sediments, differentiation between ongoing activity and damage in some patients with persistent urinary abnormalities remains difficult without a renal biopsy. A large number of serum and urinary biomarkers have been tested in lupus nephritis but none of them have been validated for routine clinical use. In real life practice, therapeutic options for lupus nephritis are limited. As patients with lupus nephritis are more prone to infective complications, tight disease control with aggressive immunosuppressive therapies may have safety concern. Not until the feasibility, efficacy, safety and cost-effectiveness of T2T in lupus nephritis is confirmed by comparative trials, this approach should not be routinely recommended with the current treatment armamentarium and monitoring regimes.

scholarly journals Bayesian adaptive design of early-phase clinical trials for precision medicine based on cancer biomarkers

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Shinjo Yada
Keyword(s):  
Neural Network ◽  
Clinical Trials ◽  
Precision Medicine ◽  
Early Phase ◽  
Patient Specific ◽  
Specific Gene ◽  
Cancer Type ◽  
Background Characteristics ◽  
Number Of Patients ◽  
Early Phase Clinical Trials

Abstract Cancer tissue samples obtained via biopsy or surgery were examined for specific gene mutations by genetic testing to inform treatment. Precision medicine, which considers not only the cancer type and location, but also the genetic information, environment, and lifestyle of each patient, can be applied for disease prevention and treatment in individual patients. The number of patient-specific characteristics, including biomarkers, has been increasing with time; these characteristics are highly correlated with outcomes. The number of patients at the beginning of early-phase clinical trials is often limited. Moreover, it is challenging to estimate parameters of models that include baseline characteristics as covariates such as biomarkers. To overcome these issues and promote personalized medicine, we propose a dose-finding method that considers patient background characteristics, including biomarkers, using a model for phase I/II oncology trials. We built a Bayesian neural network with input variables of dose, biomarkers, and interactions between dose and biomarkers and output variables of efficacy outcomes for each patient. We trained the neural network to select the optimal dose based on all background characteristics of a patient. Simulation analysis showed that the probability of selecting the desirable dose was higher using the proposed method than that using the naïve method.

scholarly journals Management of Patients with Pancreatic Ductal Adenocarcinoma in the Real-Life Setting: Lessons from the French National Hospital Database

Cancers ◽  
2021 ◽  
Vol 13 (14) ◽  
pp. 3515
Author(s):  
Christelle de la Fouchardière ◽  
Mustapha Adham ◽  
Anne-Marie Marion-Audibert ◽  
Antoine Duclos ◽  
Claude Darcha ◽  
...  
Keyword(s):  
Pancreatic Ductal Adenocarcinoma ◽  
Real Life ◽  
Ductal Adenocarcinoma ◽  
University Hospitals ◽  
National Hospital ◽  
Curative Intent ◽  
The Real ◽  
Oncological Treatment ◽  
Real Life Setting ◽  
Number Of Patients

Pancreatic ductal adenocarcinoma (PDAC) remains a major public health challenge, and faces disparities and delays in the diagnosis and access to care. Our purposes were to describe the medical path of PDAC patients in the real-life setting and evaluate the overall survival at 1 year. We used the national hospital discharge summaries database system to analyze the management of patients with newly diagnosed PDAC over the year 2016 in Auvergne-Rhône-Alpes region (AuRA) (France). A total of 1872 patients met inclusion criteria corresponding to an incidence of 22.6 per 100,000 person-year. Within the follow-up period, 353 (18.9%) were operated with a curative intent, 743 (39.7%) underwent chemo- and/or radiotherapy, and 776 (41.4%) did not receive any of these treatments. Less than half of patients were operated in a high-volume center, defined by more than 20 PDAC resections performed annually, mainly university hospitals. The 1-year survival rate was 47% in the overall population. This study highlights that a significant number of patients with PDAC are still operated in low-volume centers or do not receive any specific oncological treatment. A detailed analysis of the medical pathways is necessary in order to identify the medical and territorial determinants and their impact on the patient’s outcome.

scholarly journals A Multi-Objective Optimization Method for Hospital Admission Problem—A Case Study on Covid-19 Patients

Algorithms ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 38
Author(s):  
Amr Mohamed AbdelAziz ◽  
Louai Alarabi ◽  
Saleh Basalamah ◽  
Abdeltawab Hendawi
Keyword(s):  
Medical Care ◽  
Real Life ◽  
Optimization Method ◽  
Multi Objective Optimization ◽  
Admission Process ◽  
Multi Objective ◽  
Admission Time ◽  
King Faisal Specialist Hospital ◽  
Number Of Patients ◽  
Massive Number

The wide spread of Covid-19 has led to infecting a huge number of patients, simultaneously. This resulted in a massive number of requests for medical care, at the same time. During the first wave of Covid-19, many people were not able to get admitted to appropriate hospitals because of the immense number of patients. Admitting patients to suitable hospitals can decrease the in-bed time of patients, which can lead to saving many lives. Also, optimizing the admission process can minimize the waiting time for medical care, which can save the lives of severe cases. The admission process needs to consider two main criteria: the admission time and the readiness of the hospital that will accept the patients. These two objectives convert the admission problem into a Multi-Objective Problem (MOP). Pareto Optimization (PO) is a common multi-objective optimization method that has been applied to different MOPs and showed its ability to solve them. In this paper, a PO-based algorithm is proposed to deal with admitting Covid-19 patients to hospitals. The method uses PO to vary among hospitals to choose the most suitable hospital for the patient with the least admission time. The method also considers patients with severe cases by admitting them to hospitals with the least admission time regardless of their readiness. The method has been tested over a real-life dataset that consisted of 254 patients obtained from King Faisal specialist hospital in Saudi Arabia. The method was compared with the lexicographic multi-objective optimization method regarding admission time and accuracy. The proposed method showed its superiority over the lexicographic method regarding the two criteria, which makes it a good candidate for real-life admission systems.

scholarly journals 247. Validation of the Use of Oral Vancomycin Following Positive Admission Screening Testing for C. difficile

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S123-S123
Author(s):  
Preethi Yeturu ◽  
Jorge P Parada ◽  
Maressa Santarossa ◽  
Laurie Labuszewski ◽  
Jenna Lopez ◽  
...  
Keyword(s):  
Clinical History ◽  
Inclusion Criteria ◽  
Infectious Colitis ◽  
First Line Therapy ◽  
Clostridioides Difficile ◽  
Admission Screening ◽  
Positive Stool ◽  
Number Of Patients ◽  
Polymerase Chain ◽  
Definition Of

Abstract Background Clostridioides difficile can cause a severe infectious colitis and is often associated with significant morbidity and mortality. C. difficile infection (CDI) is defined as the presence of diarrhea plus a positive stool test, whereas C. difficile colonization is defined as a positive stool test in the absence of diarrhea or the presence of diarrhea attributable to causes other than CDI. Widespread use of stool polymerase chain reaction (PCR) testing, especially within the first 3 days of admission, has become common at our institution and has been associated with increased number of positive C. difficile tests results. However, C. difficile colonization rates may be 15% or higher. Oral (PO) vancomycin (vanc) is first line therapy for the treatment of CDI. We sought to evaluate the appropriateness of use of PO vanc in patients who tested positive for C. difficile via stool PCR within 3 days of admission. Methods We reviewed the clinical history, presence of diarrhea, risk factors for diarrhea, treatment and use of an infectious disease (ID) consultation for all patients 18 years of age or older found to test positive for C. difficile by PCR on stool assays during the first 3 days of admission from 07/01/18 to 12/31/18. Results A total of 228 patients met inclusion criteria. 183 (80%) received PO vanc while 45 (20%) did not. 131 (71.6%) of patients who received PO vanc had diarrhea, 39 (21.3%) did not have diarrhea, 13 (7.1%) the presence of diarrhea was unknown. 41 of 143 (28.7%) of patients without ID consults received PO vanc despite not having diarrhea, while 11 of 40 (27.5%) patients seen by ID received PO vanc despite not having diarrhea (p=0.888). Conclusion Most patients who tested positive for C. difficile received PO vanc had documented diarrhea, meeting the definition of CDI. However, over 1 in 5 (21.3%) of patients who received PO vanc did not have diarrhea and may have been colonized rather than have true CDI. ID consultation did not decrease the number of patients without diarrhea who received PO vanc or prevent treatment of colonized patients. This work reveals there may be an opportunity for improvement regarding management of CDI vs. C. difficile colonization which may enhance antibiotic stewardship and the appropriate use of PO vanc. Disclosures All Authors: No reported disclosures

Is active sacroiliitis on MRI associated with radiographic damage in axial spondyloarthritis? Real-life data from the ASAS and DESIR cohorts

Rheumatology ◽  
2018 ◽  
Vol 58 (5) ◽  
pp. 798-802 ◽  
Author(s):  
Alexandre Sepriano ◽  
Sofia Ramiro ◽  
Robert Landewé ◽  
Maxime Dougados ◽  
Désirée van der Heijde ◽  
...  
Keyword(s):  
Bone Marrow ◽  
Odds Ratio ◽  
Structural Damage ◽  
Axial Spondyloarthritis ◽  
Multivariable Analysis ◽  
Real Life ◽  
Daily Practice ◽  
Bone Marrow Oedema ◽  
Number Of Patients ◽  
Structural Progression

Abstract Objective To assess any association between bone marrow oedema on MRI of the sacroiliac joints (MRI-SIJ) according to local readings in daily practice and the development of structural damage on radiographs of the SIJ (X-SIJ) in axial spondyloarthritis (axSpA). Methods Patients with axSpA from the Assessment of the SpondyloArthritis international Society (ASAS) and DEvenir des Spondylarthopathies Indifférenciées Récentes (DESIR) multicentre cohorts were included. MRI-SIJ and X-SIJ were obtained at baseline, and X-SIJ at follow-up after a mean 4.6 years (ASAS) and 5.1 years (DESIR). All images were scored by local readers. Structural damage in the X-SIJ was defined according to the modified New York criteria. The percentage of structural net progression (number of ‘progressors’ minus the number of ‘regressors’ divided by the total number of patients) was assessed and the effect of bone marrow oedema on MRI-SIJ on X-SIJ damage evaluated by multivariable logistic regression. Results In total, 125 (ASAS-cohort) and 415 (DESIR-cohort) patients had baseline MRI-SIJ and complete X-SIJ data available. According to local readings, progression and ‘improvement’ in X-SIJ was seen in both the ASAS- and DESIR-cohort, yielding a net progression that was higher in the former than in the latter (19.2% and 6.3%). In multivariable analysis, baseline bone marrow oedema on MRI-SIJ was strongly associated with X-SIJ structural progression in both ASAS (odds ratio = 3.2 [95% CI: 1.3; 7.9]), and DESIR (odds ratio = 7.6 [95% CI: 4.3; 13.2]). Conclusion Inflammation on MRI-SIJ is associated with future radiographic progression according to local readings despite an expected increased imprecision invoked by local readings.

scholarly journals Training of a future social professional for the formation of safe adolescent behavior in social networks

2021 ◽  
Keyword(s):  
Social Networks ◽  
Information Exchange ◽  
Professional Training ◽  
Social Groups ◽  
Real Life ◽  
Well Being ◽  
The Internet ◽  
Stage Of Development ◽  
Safe Behavior ◽  
Definition Of

The article analyzes different approaches to the definition of «social networks» as technological complexes of organization and management of electronic information exchange among the subjects of social relations, united by common interests, information needs and skills. Based on the analysis of the scientific literature the essential characteristics of social networks that affect the formation and development of the adolescent's personality are revealed. Role of social networks at the present stage of development of society, which is manifested in the representation of interests not only of social groups but also of entire social groups, is defined in the article. The negative impact of social networks on the personality of the adolescent, which is manifested in the expansion of adolescents in cyberspace, the desire for independence and adulthood, selfexperimentation, which leads to risky activities both on the Internet and in real life are revealed. Concept of safe behavior in social networks as a set of actions of the individual when using the Internet, helping to meet the needs and at the same time prevent the possibility of causing damage to physical, mental, social well-being and property of man and others is analyzed. The basic rules of safe behavior in social Internet communities are highlighted. The structural components of safe behavior of adolescents in social networks are singled out: cognitive, motivational and actionreflexive; the concept of «professional training of future social professionals for the formation of safe behavior of adolescents in social networks» is revealed. Readiness is revealed as a result of the process of training future social specialists for professional activity on the formation of safe behavior of adolescents in social networks; the author's definition of the concept «readiness of future social professionals to form safe behavior of adolescents in social networks» is given. Components of readiness of future social workers to form safe behavior of teenagers in social networks, such as cognitive, motivational-personal and activity, are described.

scholarly journals ISMAR-study presentation: in-hospital epidemiology and clinical management of respiratory and cardiac comorbidities in cardiac and respiratory disease units

2014 ◽  
Vol 9 ◽  
Author(s):  
Roberto Tramarin ◽  
Mario Polverino ◽  
Maurizio Volterrani ◽  
Bruna Girardi ◽  
Claudio Chimini ◽  
...  
Keyword(s):  
Clinical Practice ◽  
Clinical Management ◽  
Real Life ◽  
Length Of Hospital Stay ◽  
Relevant Information ◽  
Hospital Epidemiology ◽  
Discharge Data ◽  
Definition Of ◽  
Current Guidelines

Background: Cardiovascular and respiratory diseases are leading causes of morbidity and their co-occurrence has important implications in mortality and other outcomes. Even the most recent guidelines do not reliably address clinical, prognostic, and therapeutic concerns due to the overlap of respiratory and cardiac diseases. Study objectives and design: In order to evaluate in the reality of clinical practice the epidemiology and the reciprocal impact of cardio-pulmonary comorbidity on the clinical management, diagnostic workup and treatment, 1,500 cardiac and 1,500 respiratory inpatients, admitted in acute and rehabilitation units, will be enrolled in a multicenter, nationwide, prospective observational study. For this purpose, each center will enroll at least 50 consecutive patients. At discharge, data analysis will be aimed at the definition of cardiac and pulmonary inpatient comorbidity prevalence, demographic characteristics, length of hospital stay, and risk factors, taking into account also procedures, pharmacological and non-pharmacological treatment, and follow up in patients with cardio-respiratory comorbidity. Conclusions: The purely observational design of the study aims to give new relevant information on the assessment and management of overlapping patients in real life clinical practice, and new insight for improvement and implementation of current guidelines on the management of individual diseases.

scholarly journals Improving Transparency, Falsifiability, and Rigour by Making Hypothesis Tests Machine Readable

2020 ◽  
Author(s):  
Daniel Lakens ◽  
Lisa Marie DeBruine
Keyword(s):  
Peer Review ◽  
Hypothesis Test ◽  
Scientific Information ◽  
Real Life ◽  
R Package ◽  
Statistical Prediction ◽  
Hypothesis Tests ◽  
Research Questions ◽  
Meta Analyses ◽  
Machine Readable

Making scientific information machine-readable greatly facilitates its re-use. Many scientific articles have the goal to test a hypothesis, so making the tests of statistical predictions easier to find and access could be very beneficial. We propose an approach that can be used to make hypothesis tests machine readable. We believe there are two benefits to specifying a hypothesis test in a way that a computer can evaluate whether the statistical prediction is corroborated or not. First, hypothesis test will become more transparent, falsifiable, and rigorous. Second, scientists will benefit if information related to hypothesis tests in scientific articles is easily findable and re-usable, for example when performing meta-analyses, during peer review, and when examining meta-scientific research questions. We examine what a machine readable hypothesis test should look like, and demonstrate the feasibility of machine readable hypothesis tests in a real-life example using the fully operational prototype R package scienceverse.

scholarly journals Monitoring Robust Estimates for Compositional Data

2021 ◽  
Vol 50 (2) ◽  
pp. 16-37
Author(s):  
Valentin Todorov
Keyword(s):  
Compositional Data ◽  
Real Life ◽  
R Package ◽  
Diagnostic Tools ◽  
Data Set ◽  
Mahalanobis Distances ◽  
Robust Estimates ◽  
Real Life Data ◽  
Manufactured Exports ◽  
Parameter Values

In a number of recent articles Riani, Cerioli, Atkinson and others advocate the technique of monitoring robust estimates computed over a range of key parameter values. Through this approach the diagnostic tools of choice can be tuned in such a way that highly robust estimators which are as efficient as possible are obtained. This approach is applicable to various robust multivariate estimates like S- and MM-estimates, MVE and MCD as well as to the Forward Search in whichmonitoring is part of the robust method. Key tool for detection of multivariate outliers and for monitoring of robust estimates is the Mahalanobis distances and statistics related to these distances. However, the results obtained with thistool in case of compositional data might be unrealistic since compositional data contain relative rather than absolute information and need to be transformed to the usual Euclidean geometry before the standard statistical tools can be applied. Various data transformations of compositional data have been introduced in the literature and theoretical results on the equivalence of the additive, the centered, and the isometric logratio transformation in the context of outlier identification exist. To illustrate the problem of monitoring compositional data and to demonstrate the usefulness of monitoring in this case we start with a simple example and then analyze a real life data set presenting the technologicalstructure of manufactured exports. The analysis is conducted with the R package fsdaR, which makes the analytical and graphical tools provided in the MATLAB FSDA library available for R users.

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