scholarly journals Sensitivity analysis of regression models of physicochemical and rheological properties of kashk containing flaxseed extract

2021 ◽  
Vol 18 (117) ◽  
pp. 321-331
Author(s):  
hassan rashidi ◽  
Morteza Kashaninejad ◽  
Masoud Najaf Najafi ◽  
Fozhan Khorasaniyan ◽  
◽  
...  
2000 ◽  
Vol 86 (1) ◽  
pp. 175-199 ◽  
Author(s):  
R.B. Arellano-Valle ◽  
M. Galea-Rojas ◽  
P.Iglesias Zuazola

Author(s):  
Sönke Kraft ◽  
Daniel Lüdicke

For the reliable simulation-based fatigue design of railway vehicles, the operation conditions and resulting loads over the lifespan of the vehicle have to be considered. After introducing the relevant fatigue loads on the vehicle and the methods for modelling the fatigue damage, this work aims at analysing the influence of the operating conditions and loads on the damage using sensitivity analysis. Two approaches are studied: the variance-based sensitivity analysis of the loads acting on the car body and the influence of different operating conditions using statistical values per track section. The loads are obtained from multi-body simulations and the damage is estimated using both physical FE-models and meta-models. The performances of linear regression models and polynomial chaos models are evaluated. The proposed sensitivity analysis is applied to the highspeed train being developed in the Next Generation Train (NGT) project at DLR and will serve as a basis for the virtual design and reliability analysis.


Blood ◽  
2011 ◽  
Vol 118 (21) ◽  
pp. 2754-2754
Author(s):  
Annie Guerin ◽  
Vamsi K Bollu ◽  
Amy Guo ◽  
Michael Stepner ◽  
James D Griffin ◽  
...  

Abstract Abstract 2754 Background: According to the NCCN guidelines, the recommended treatment option for patients diagnosed with Philadelphia-positive (Ph+) chronic myeloid leukemia (CML) in chronic or accelerated phases who are resistant or develop intolerance to first-line imatinib is to switch to one of the two second-generation BCR-ABL tyrosine kinase inhibitors, nilotinib or dasatinib. There is limited information on their comparative adherence. Analysis of adherence may reveal whether these two drugs are being used as intended and how adherence issues may potentially affect clinical outcomes. Nonadherence to imatinib has been associated with loss of cytogenetic response, imatinib failure, and higher rates of inpatient visits. A prior study covering the period up to 6/2009 has revealed a better adherence profile for nilotinib versus dasatinib. Since dasatinib was approved for once daily use in addition to twice daily use in 05/2009, this study replicated the analysis using more recent data to compare adherence between nilotinib and dasatinib as second-line therapies in CML. Methods: Medical and pharmacy records from two databases from January 1997 to April 2010 were combined to identify adult patients diagnosed with CML (ICD-9 code 205.1x) with ≥1 prescription for either nilotinib or dasatinib. Patients were required to have continuous enrollment ≥1 month prior to and after the index date, defined as the first prescription for nilotinib or dasatinib, and to continue their treatment ≥1 month before discontinuing or switching to another TKI. Adherence over an up-to 180-day period was evaluated based on the proportion of days covered (PDC; sum of days of medication on hand for nilotinib or dasatinib divided by the number of calendar days in the study period). Medication possession ratio (MPR) was also evaluated in a sensitivity analysis. PDC and MPR were compared between cohorts using linear regression models. Discontinuation was defined as a treatment gap ≥30 days, and rates were compared between cohorts using Kaplan-Meier survival analyses and Cox proportional hazard regression models. In a sensitivity analysis, discontinuation was defined as a treatment gap ≥90 days. All multivariate regression models were controlled for age, gender, CML complexity, adverse events at baseline, number of inpatient days, emergency room (ER) visits and outpatient visits during baseline, medical costs during baseline, CML year of diagnosis, Charlson Comorbidity Index, and bone marrow or stem cell transplant before the index date. Results: Adherence and discontinuation were analyzed for a total of 558 CML patients receiving a second-line TKI (473 dasatinib and 85 nilotinib). Patient characteristics were generally similar. Patients in the dasatinib cohort had a longer mean follow-up period compared with those in the nilotinib cohort (162 days vs. 146 days; P = 0.0007) and greater utilization and costs associated with inpatient and ER services. The mean PDC over the study period for nilotinib was higher compared with dasatinib (0.81 vs 0.68). After adjusting for confounding factors, the nilotinib group had a 0.115 higher PDC (approximately 17% higher) compared to the dasatinib group (P = 0.0004). Additionally, patients in the nilotinib group had a significantly higher MPR compared to patients in the dasatinib group (0.90 vs. 0.77 P = 0.0043). Discontinuation rates (gap ≥30 days) were significantly higher for dasatinib users than for nilotinib users, with an adjusted hazard ratio of 2.15 (P = 0.0013). Dasatinib-treated patients had higher discontinuation rates than nilotinib-treated patients after 3 months (40% vs 22%) and 6 months (50% vs 28%). These unadjusted differences were robust in the sensitivity analysis with discontinuation defined as a treatment gap ≥90 days, but the difference between the cohorts was no longer significant after adjusting for confounding factors (HR 1.76, P = 0.1328). Conclusions: This retrospective study showed that CML patients treated with nilotinib for second-line treatment were significantly more adherent to therapy, based on PDC and MPR, and had a lower discontinuation rate than did patients receiving dasatinib in this analysis. Further studies are needed to better understand treatment-specific factors affecting adherence and persistence (e.g., treatment cost, tolerability profile, dosing convenience). Disclosures: Guerin: Novartis Pharmaceutical Corporation: Annie Guerin is an employee of Analysis Group, Inc, which has received research funds from Novartis Pharmaceuticals. Bollu:Novartis Pharmaceutical Corporation: Employment, Vamsi K. Bollu worked for the Novartis Pharmaceuticals Corporation while performing this analysis but is currently employed by Sunovion Pharmaceuticals Inc. Sunovion Pharmaceuticals Inc. was not in any way associated with this study. Guo:Novartis Pharmaceutical Corporation: Employment. Stepner:Novartis Pharmaceutical Corporation: Michael Stepner is an employee of Analysis Group, Inc, which has received research funds from Novartis Pharmaceuticals. Griffin:Novartis Pharmaceutical Corporation: James D. Griffin is an employee of the Dana Farber Institute which has received consultancy fees from Analysis Group, Inc, which has received research funds from Novartis Pharmaceuticals Corporation. Wu:Novartis Pharmaceutical Corporation: Eric Q. Wu is an employee of Analysis Group, Inc, which has received consultancy funds from Novartis Pharmaceutical Corporation.


Author(s):  
Anita Lindmark

AbstractCausal mediation analysis is used to decompose the total effect of an exposure on an outcome into an indirect effect, taking the path through an intermediate variable, and a direct effect. To estimate these effects, strong assumptions are made about unconfoundedness of the relationships between the exposure, mediator and outcome. These assumptions are difficult to verify in a given situation and therefore a mediation analysis should be complemented with a sensitivity analysis to assess the possible impact of violations. In this paper we present a method for sensitivity analysis to not only unobserved mediator-outcome confounding, which has largely been the focus of previous literature, but also unobserved confounding involving the exposure. The setting is estimation of natural direct and indirect effects based on parametric regression models. We present results for combinations of binary and continuous mediators and outcomes and extend the sensitivity analysis for mediator-outcome confounding to cases where the continuous outcome variable is censored or truncated. The proposed methods perform well also in the presence of interactions between the exposure, mediator and observed confounders, allowing for modeling flexibility as well as exploration of effect modification. The performance of the method is illustrated through simulations and an empirical example.


2018 ◽  
Vol 44 (2) ◽  
pp. 1119-1127 ◽  
Author(s):  
Naveed ur Rehman ◽  
Muhammad Uzair ◽  
Mubashir Ali Siddiqui ◽  
Mehrdad Khamooshi

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