Impact of pharmacy channel on prescription abandonment and adherence to oral oncolytics.

2013 ◽  
Vol 31 (15_suppl) ◽  
pp. 6546-6546
Author(s):  
Michael Edward Stokes ◽  
Hans-Peter Goertz ◽  
Veronica Alas ◽  
Carolina Reyes ◽  
Elyse Gatt ◽  
...  
Keyword(s):  
Regression Models ◽  
Health Plans ◽  
Chi Square ◽  
Logistic Regression Models ◽  
Cohort Design ◽  
Proportion Of Days Covered ◽  
Specialty Pharmacy ◽  
Baseline Characteristics ◽  
Oral Oncolytics ◽  
The Impact

6546 Background: Oral chemotherapy is increasingly prescribed to treat cancer. Despite benefits such as convenience of use, concerns have been raised regarding adherence to therapy. The objective was to compare and measure rates of adherence and abandonment in patients filling prescriptions in traditional retail versus specialty pharmacy channels. Methods: Using a retrospective cohort design, we selected patients aged ≥18 years with a prescription for erlotinib, capecitabine, or imatinib during 2007-2011 from a Medco population of both U.S. commercial and Medicare health plans. Patients were classified according to the initial oral oncolytic received and the pharmacy channel providing the medication. Abandonment was defined as a reversal following the initial approval of the prescription claim with no additional paid claims for the agent within 90 days of reversal. Adherence was defined as the proportion of days covered between the date of the first and last oral prescription. Patients were classified as adherent if the proportion of days covered was ≥80%. Unadjusted comparisons of adherence and abandonment measures were assessed using chi-square tests. Logistic regression models adjusted for baseline characteristics were used to examine the impact of pharmacy channel on abandonment and adherence. Results: Among patients treated with an oral oncolytic, 15,071 were prescribed erlotinib, 20,062 were prescribed capecitabine and 7,233 were prescribed imatinib. For all study cohorts, Medco specialty channel had the highest proportion of adherent patients compared with traditional retail (erlotinib 84% vs. 80%, capecitabine 63% vs. 35%, and imatinib 72% vs. 67%, P<.001 all comparisons). Abandonment of the initial prescription was low with overall rates of 1.9%, 1.6%, and 1.2% for erlotinib, capecitabine, and imatinib, respectively. In multivariate models, specialty channel was significantly associated with lower abandonment and increased adherence for each cohort. Conclusions: Pharmacy channel appears to be influential on abandonment and adherence. Lower rates of abandonment and higher rates of adherence were observed among specialty pharmacy patients compared with traditional retail.

Abstract P122: The Impact of Center Certification Status on Acute Stroke Care Within a Multi-Hospital System in Western United States

Stroke ◽  
2021 ◽  
Vol 52 (Suppl_1) ◽  
Author(s):  
Radoslav I Raychev ◽  
CrystalAnn Moreno ◽  
Leslie Corless ◽  
Jason W Tarpley ◽  
John F Zurasky ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Clinical Outcome ◽  
Regression Models ◽  
Process Of Care ◽  
Chi Square ◽  
Hospital System ◽  
Logistic Regression Models ◽  
Stroke Center ◽  
The Impact ◽  
Iv Tpa

Introduction: We aimed to investigate the impact of certification status on process of care metrics and clinical outcome in a large multi-center hospital system. Methods: We analyzed data obtained from the Providence Stroke Registry between January 2016 and December 2019. Key process of care metrics and clinical outcome were compared among patients with a discharge diagnosis of stroke and stratified based on site certification: comprehensive stroke center (CSC), thrombectomy-capable stroke center (TSC), primary stroke center (PSC) and no certification (NC). Donner’s adjusted chi-square tests were used to compare proportions for each metric grouped by certification. Generalized linear mixed effects logistic regression models were used to adjust for mode of patient arrival, age, sex, admit NIHSS, and medical history. Results: Data included 45,278 patients. Results from the analyses are summarized in the table. Donner’s adjusted chi-square analyses showed significant differences for metrics across certification groups. Results from the logistic regression models indicated significant differences in IV TPA and EVT treatment, as well as IV TPA treatment times across certification groups. There were no significant differences between TSC and CSC. Conclusions: Patients presenting with acute ischemic stroke at NC and PSC were significantly less likely to receive IV TPA or EVT with significantly less efficient IV tPA treatment times as compared to CSC. However, CSC and TSC sites performed similarly.

The impact of SPY angiography on intraoperative decision making and outcomes for post-mastectomy reconstruction

2019 ◽  
pp. 1-5
Keyword(s):  
Decision Making ◽  
Logistic Regression ◽  
Skin Necrosis ◽  
Regression Models ◽  
Multivariable Analysis ◽  
P Value ◽  
Flap Necrosis ◽  
Single Institution ◽  
Logistic Regression Models ◽  
The Impact

Objective: While the use of intraoperative laser angiography (SPY) is increasing in mastectomy patients, its impact in the operating room to change the type of reconstruction performed has not been well described. The purpose of this study is to investigate whether SPY angiography influences post-mastectomy reconstruction decisions and outcomes. Methods and materials: A retrospective analysis of mastectomy patients with reconstruction at a single institution was performed from 2015-2017.All patients underwent intraoperative SPY after mastectomy but prior to reconstruction. SPY results were defined as ‘good’, ‘questionable’, ‘bad’, or ‘had skin excised’. Complications within 60 days of surgery were compared between those whose SPY results did not change the type of reconstruction done versus those who did. Preoperative and intraoperative variables were entered into multivariable logistic regression models if significant at the univariate level. A p-value <0.05 was considered significant. Results: 267 mastectomies were identified, 42 underwent a change in the type of planned reconstruction due to intraoperative SPY results. Of the 42 breasts that underwent a change in reconstruction, 6 had a ‘good’ SPY result, 10 ‘questionable’, 25 ‘bad’, and 2 ‘had areas excised’ (p<0.01). After multivariable analysis, predictors of skin necrosis included patients with ‘questionable’ SPY results (p<0.01, OR: 8.1, 95%CI: 2.06 – 32.2) and smokers (p<0.01, OR:5.7, 95%CI: 1.5 – 21.2). Predictors of any complication included a change in reconstruction (p<0.05, OR:4.5, 95%CI: 1.4-14.9) and ‘questionable’ SPY result (p<0.01, OR: 4.4, 95%CI: 1.6-14.9). Conclusion: SPY angiography results strongly influence intraoperative surgical decisions regarding the type of reconstruction performed. Patients most at risk for flap necrosis and complication post-mastectomy are those with questionable SPY results.

scholarly journals High association of COVID-19 severity with poor gut health score in Lebanese patients

PLoS ONE ◽  
2021 ◽  
Vol 16 (10) ◽  
pp. e0258913
Author(s):  
Imad Al Kassaa ◽  
Sarah El Omari ◽  
Nada Abbas ◽  
Nicolas Papon ◽  
Djamel Drider ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Models ◽  
Equal Proportion ◽  
Gut Health ◽  
Kendall’S Tau ◽  
High Association ◽  
Kendall's Tau ◽  
Health Score ◽  
Logistic Regression Models ◽  
The Impact

Background Coronavirus disease 2019 (COVID-19) has affected millions of lives globally. However, the disease has presented more extreme challenges for developing countries that are experiencing economic crises. Studies on COVID-19 symptoms and gut health are scarce and have not fully analyzed possible associations between gut health and disease pathophysiology. Therefore, this study aimed to demonstrate a potential association between gut health and COVID-19 severity in the Lebanese community, which has been experiencing a severe economic crisis. Methods This cross-sectional study investigated SARS-CoV-2 PCR-positive Lebanese patients. Participants were interviewed and gut health, COVID-19 symptoms, and different metrics were analyzed using simple and multiple logistic regression models. Results Analysis of the data showed that 25% of participants were asymptomatic, while an equal proportion experienced severe symptoms, including dyspnea (22.7%), oxygen need (7.5%), and hospitalization (3.1%). The mean age of the participants was 38.3 ±0.8 years, and the majority were males (63.9%), married (68.2%), and currently employed (66.7%). A negative correlation was found between gut health score and COVID-19 symptoms (Kendall’s tau-b = -0.153, P = 0.004); indicating that low gut health was associated with more severe COVID-19 cases. Additionally, participants who reported unhealthy food intake were more likely to experience severe symptoms (Kendall’s tau-b = 0.118, P = 0.049). When all items were taken into consideration, multiple ordinal logistic regression models showed a significant association between COVID-19 symptoms and each of the following variables: working status, flu-like illness episodes, and gut health score. COVID-19 severe symptoms were more common among patients having poor gut health scores (OR:1.31, 95%CI:1.07–1.61; P = 0.008), experiencing more than one episode of flu-like illness per year (OR:2.85, 95%CI:1.58–5.15; P = 0.001), and owning a job (OR:2.00, 95%CI:1.1–3.65; P = 0.023). Conclusions To our knowledge, this is the first study that showed the impact of gut health and exposure to respiratory viruses on COVID-19 severity in Lebanon. These findings can facilitate combating the pandemic in Lebanon.

scholarly journals Do RATs save lives? A retrospective analysis of out-of-hospital cardiac arrest in an English Ambulance Service

2018 ◽  
Vol 3 (2) ◽  
Author(s):  
Richard Pilbery ◽  
M. Dawn Teare
Keyword(s):  
Retrospective Cohort ◽  
Regression Models ◽  
Spontaneous Circulation ◽  
Ambulance Service ◽  
Logistic Regression Models ◽  
Cad System ◽  
Routinely Collected Data ◽  
Collection Period ◽  
The Impact ◽  
Hospital Cardiac Arrest

<h3>Study aim</h3><p>This study aims to determine the impact of the red arrest teams (RATs) on survival to 30 days and return of spontaneous circulation (ROSC) at hospital.</p><h3>Methods</h3><p class="FirstParagraph">A retrospective cohort study analysing routinely collected data was undertaken. All adult (≥18 years) OHCAs entered onto the YAS computer aided dispatch (CAD) system between the 1st October, 2015 and 30th September, 2017 were included if the patient was resuscitated, and the cause of the arrest was considered to be medical in origin. Multivariable logistic regression models were created to enable adjustment for common predictors of survival and ROSC.</p><h3>Results</h3><p>During the 2-year data collection period, 15,151 cardiac arrests that were attended by Yorkshire Ambulance Service. After removing ineligible cases, 5,868 cardiac arrests remained. RATs attended 2,000/5,868 (34.1%) incidents, with each RAT attending a median of 13 cardiac arrests (IQR 7–23, minimum 1, maximum 78).</p><p class="FirstParagraph">The adjusted odds ratios suggest that a RAT on scene is associated with a slight increase in the odds of survival to 30 days (OR 1.01, 95%CI 0.74–1.38) and odds of ROSC on arrival at hospital (OR 1.13, 95%CI 0.99–1.29), compared to the odds of not having a RAT present, although neither results are statistically significant.</p><h3>Conclusion</h3><p class="FirstParagraph">The presence of a RAT paramedic was associated with a small increase in survival to 30 days and ROSC on arrival at hospital, although neither were statistically significant. Larger prospective studies are required to determine the effect of roles such as RAT on outcomes from OHCA</p>

Innovation in the aftermath of downsizing: evidence from the threat-rigidity perspective

2020 ◽  
Vol 49 (9) ◽  
pp. 1859-1877
Author(s):  
José Fernández-Menéndez ◽  
Óscar Rodríguez-Ruiz ◽  
José-Ignacio López-Sánchez ◽  
María Isabel Delgado-Piña
Keyword(s):  
Regression Models ◽  
Negative Impact ◽  
Content Type ◽  
Logistic Regression Models ◽  
Marketing Innovation ◽  
Different Types ◽  
Threat Rigidity ◽  
The Impact ◽  
Research Show ◽  
Innovation Outcomes

PurposeThe purpose of this paper is to study how job reductions affect product innovation and marketing innovation in a sample of 2,034 Spanish manufacturing firms in the period 2007–2014.Design/methodology/approachPoisson and logistic regression models with random effects were used to analyse the impact of downsizing on some innovation outcomes of firms.FindingsThe results of this research show that the stressful measure of job reductions may have unexpected consequences, stimulating innovation. However downsizing combined with radical organisational changes such as new equipment, techniques or processes seems to have a negative impact on product and marketing innovation.Originality/valueThis research has two original features. First, it explores the unconventional direction of causality from the planned elimination of jobs to innovation outputs. Secondly, the paper looks at the combined effect of downsizing and other restructuring measures on different types of innovation. Following the threat-rigidity theory, we assume that this combination represents a major threat for survivors that leads to lower levels of product and marketing innovation.

scholarly journals The impact of demographic, clinical, genetic, and imaging variables on tau PET status

2020 ◽  
Author(s):  
Rik Ossenkoppele ◽  
◽  
Antoine Leuzy ◽  
Hanna Cho ◽  
Carole H. Sudre ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Cortical Thickness ◽  
Regression Models ◽  
Neurodegenerative Disorder ◽  
Amyloid Β ◽  
Binary Logistic Regression ◽  
Clinical Genetic ◽  
Logistic Regression Models ◽  
Tau Pet ◽  
The Impact

Abstract Purpose A substantial proportion of amyloid-β (Aβ)+ patients with clinically diagnosed Alzheimer’s disease (AD) dementia and mild cognitive impairment (MCI) are tau PET–negative, while some clinically diagnosed non-AD neurodegenerative disorder (non-AD) patients or cognitively unimpaired (CU) subjects are tau PET–positive. We investigated which demographic, clinical, genetic, and imaging variables contributed to tau PET status. Methods We included 2338 participants (430 Aβ+ AD dementia, 381 Aβ+ MCI, 370 non-AD, and 1157 CU) who underwent [18F]flortaucipir (n = 1944) or [18F]RO948 (n = 719) PET. Tau PET positivity was determined in the entorhinal cortex, temporal meta-ROI, and Braak V-VI regions using previously established cutoffs. We performed bivariate binary logistic regression models with tau PET status (positive/negative) as dependent variable and age, sex, APOEε4, Aβ status (only in CU and non-AD analyses), MMSE, global white matter hyperintensities (WMH), and AD-signature cortical thickness as predictors. Additionally, we performed multivariable binary logistic regression models to account for all other predictors in the same model. Results Tau PET positivity in the temporal meta-ROI was 88.6% for AD dementia, 46.5% for MCI, 9.5% for non-AD, and 6.1% for CU. Among Aβ+ participants with AD dementia and MCI, lower age, MMSE score, and AD-signature cortical thickness showed the strongest associations with tau PET positivity. In non-AD and CU participants, presence of Aβ was the strongest predictor of a positive tau PET scan. Conclusion We identified several demographic, clinical, and neurobiological factors that are important to explain the variance in tau PET retention observed across the AD pathological continuum, non-AD neurodegenerative disorders, and cognitively unimpaired persons.

The impact of intellectual capital on start-up expectations

2016 ◽  
Vol 17 (4) ◽  
pp. 654-674 ◽  
Author(s):  
Diego Matricano
Keyword(s):  
Logistic Regression ◽  
Intellectual Capital ◽  
Regression Models ◽  
Empirical Studies ◽  
Binary Logistic Regression ◽  
Research Trend ◽  
Content Type ◽  
Logistic Regression Models ◽  
Start Up ◽  
The Impact

Purpose According to an emerging research trend, which seeks to apply the concept of intellectual capital (IC) to the field of entrepreneurship, the purpose of this paper is to test whether IC can affect the start-up expectations of aspiring entrepreneurs. Design/methodology/approach Binary logistic regression models, based on empirical data derived from the Global Entrepreneurship Monitor website and referring to Italy over the years 2005-2010, are used to test the influence of IC (comprising human, structural and relational capital) on start-up expectations. Findings Binary logistic regression models reveal robust results. Human, structural and relational capitals affect start-up expectations in Italy. Only in 2010 did structural capital fail to do so. Research limitations/implications This study has three main limitations. The first concerns the need for further research to confirm the influence of IC on start-up expectations. The second concerns in-depth, more exhaustive analyses that cannot be carried out due to the use of second- hand data. The third deals with the reference only to Italy, over a limited time-span (2005-2010). Originality/value To the best knowledge of the author, this is one of the first empirical studies that investigate whether IC can affect start-up expectations. Results revealed by the regression models might steer other scholars’ interest toward this research path (linking IC and entrepreneurship) that has not yet been properly considered.

scholarly journals One-year outcomes of early-crossover patients in a cohort receiving nonoperative care for lumbar disc herniation

2017 ◽  
Vol 27 (4) ◽  
pp. 391-396 ◽  
Author(s):  
Anurekha Ramakrishnan ◽  
K. Michael Webb ◽  
Matthew C. Cowperthwaite
Keyword(s):  
Lumbar Disc Herniation ◽  
Disc Herniation ◽  
Regression Models ◽  
Lumbar Disc ◽  
Recursive Partitioning ◽  
Chi Square ◽  
Logistic Regression Models ◽  
Spine Intervention ◽  
Euroqol 5D ◽  
One Year

OBJECTIVEThe authors comprehensively studied the recovery course and 1-year outcomes of early-crossover patients who were randomized to the nonoperative care arm of the Leiden–The Hague Spine Intervention Prognostic Study. The primary goal was to gain insight into the differences in the recovery patterns of early-crossover patients and those treated nonoperatively; secondary goals were to identify predictors of good 1-year outcomes, and to understand when and why patients were likely to cross over.METHODSIndividual EuroQol-5D scores were obtained at baseline and at 2, 4, 8, 12, 26, 38, and 52 weeks for 142 patients. Early-crossover patients were defined as those electing to undergo surgery during the first 12 weeks of treatment. Crossover and noncrossover groups were compared using Kruskal-Wallis, Wilcoxon-Mann-Whitney, and chi-square tests. Linear mixed-effects models were used to examine the growth trajectories of crossover and noncrossover groups. Recursive partitioning trees were used to model crossover events and the timing of crossover decisions. Multivariable logistic regression models were used to identify predictors of good 1-year outcomes.RESULTSOf the 142 patients randomized to receive prolonged nonoperative care, 136 were selected for the study. In this cohort, 43/136 (32%) opted for surgery, and 31/43 (72%) of crossover events occurred before the 12-week time point. Early-crossover patients had significantly greater functional impairment at Week 2 than noncrossover patients (p = 0.031), but experienced greater recovery by 26 weeks and better 1-year outcomes (p = 0.045). Patients who did not experience an improvement in their symptoms between 2 and 8 weeks were more likely to cross over (OR 3.5, 95% CI 1.2–10.1; p = 0.01). Recursive partitioning trees were able to identify crossover patients with 76% accuracy. Regression models suggested that better recovery at 26 weeks (p < 0.01) was predictive of good 1-year outcome; declining health status between Weeks 4 and 8 was negatively predictive of good outcome (p < 0.01).CONCLUSIONSThis study is the first to comprehensively analyze the recovery and outcomes of crossover patients, and compare them to nonoperatively treated patients. The results suggest that patients who have a low EuroQol-5D score during the early weeks of treatment and who do not respond to nonoperative care during the first few weeks of treatment are most likely to cross over. Early-crossover patients experience a greater rate of recovery and more frequently have a good 1-year outcome when compared with nonoperatively treated patients. The current results motivate a broader investigation into the timing of surgery and the identification of patient populations that will be most benefited by early surgical treatment for lumbar disc herniation.

scholarly journals Defensible inferences from a nested sequence of logistic regressions: a guide for the perplexed

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Gulsah Gurkan ◽  
Yoav Benjamini ◽  
Henry Braun
Keyword(s):  
Logistic Regression ◽  
Cognitive Skills ◽  
Regression Models ◽  
Large Scale ◽  
Family Background ◽  
National Income ◽  
Logistic Models ◽  
Logistic Regression Models ◽  
Logistic Regressions ◽  
The Impact

AbstractEmploying nested sequences of models is a common practice when exploring the extent to which one set of variables mediates the impact of another set. Such an analysis in the context of logistic regression models confronts two challenges: (i) direct comparisons of coefficients across models are generally biased due to the changes in scale that accompany the changes in the set of explanatory variables, (ii) conducting a large number of tests induces a problem of multiplicity that can lead to spurious findings of significance if not heeded. This article aims to illustrate a practical strategy for conducting analyses in the face of these challenges. The challenges—and how to address them—are illustrated using a subset of the findings reported by Braun (Large-scale Assess Educ 6(4):1–52, 2018. 10.1186/s40536-018-0058-x), drawn from the Programme for the International Assessment of Adult Competencies (PIAAC), an international, large-scale assessment of adults. For each country in the dataset, a nested pair of logistic regression models was fit in order to investigate the role of Educational Attainment and Cognitive Skills in mediating the impact of family background and demographic characteristics on the location of an individual’s annual income in the national income distribution. A modified version of the Karlson–Holm–Breen (KHB) method was employed to obtain an unbiased estimate of the true differences in the coefficients between nested logistic models. In order to address the issue of multiplicity, a recent generalization of the Benjamini–Hochberg (BH) False Discovery Rate (FDR)-controlling procedure to hierarchically structured hypotheses was employed and compared to two conventional methods. The differences between the changes in coefficients calculated conventionally and with the KHB adjustment varied from negligible to very substantial. When combined with the actual magnitudes of the coefficients, we concluded that the more proximal factors indeed act as strong mediators for the background factors, but less so for Age, and hardly at all for Gender. With respect to multiplicity, applying the FDR-controlling procedure yielded results very similar to those obtained by applying a standard per-comparison procedure, but quite a few more discoveries in comparison to the Bonferroni procedure. The KHB methodology illustrated here can be applied wherever there is interest in comparing nested logistic regressions. Modifications to account for probability sampling are practicable. The categorization of variables and the order of entry should be determined by substantive considerations. On the other hand, the BH procedure is perfectly general and can be implemented to address multiplicity issues in a broad range of settings.

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