scholarly journals Safety Profile of Immunotherapy Combined With Antiangiogenic Therapy in Patients With Melanoma: Analysis of Three Clinical Studies

2021 ◽  
Vol 12 ◽  
Author(s):  
Hui Tian ◽  
Xuan Wang ◽  
Bin Lian ◽  
Xieqiao Yan ◽  
Lu Si ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Adverse Event ◽  
Treatment Duration ◽  
Retrospective Cohort ◽  
Regression Models ◽  
Antiangiogenic Therapy ◽  
Risk Models ◽  
Clinical Trial Registration ◽  
Logistic Regression Models

Objective: To describe the frequency and spectrum of treatment-related adverse events (TRAEs) of immunotherapy combined with antiangiogenic therapy in patients with melanoma.Methods: This retrospective cohort study included three clinical trials on patients with stage III/IV melanoma treated with anti–PD 1 and antiangiogenic therapy.Results: We analyzed data from 72 patients with a median follow-up time of 25.9 months (95% CI, 9.1–42.7 m). The median treatment duration was 7.5 months (range, 0.7–42.8 m), and the median of treatment cycles was 11.0 (range, 1–90). Most patients (70 of 72 or 97.2%) experienced TRAEs (mostly grades 1 or 2). No drug-related deaths were reported. Most TRAEs were hepatic (75%), endocrine (72.2%), skin (65.3%), and gastrointestinal tract (59.7%) manifestations, followed by myelosuppression (55.6%), renal dysfunction (55.6%), and dyslipidaemia (54.2%). The adverse event (AE) spectra were similar between regimens. Using multivariate Cox proportional risk models showed that hypertension was associated with a long PFS. According to our multivariable logistic regression models, TRAEs were not associated with ORR.Conclusion: We found that the prevalence of AEs was higher than that of anti–PD-1 monotherapy. Most of the AEs were mild. The AE spectra were similar to those seen after anti–PD-1 or antiangiogenic therapy monotherapy, without unexpected AEs. Immunotherapy combined with antiangiogenic therapy was well tolerated.Clinical Trial Registration: ClinicalTrials.gov, identifier NCT03955354.

Sensor-based Fall Risk Assessment – an Expert ‘to go’

2011 ◽  
Vol 50 (05) ◽  
pp. 420-426 ◽  
Author(s):  
A. Rehwald ◽  
K. H. Wolf ◽  
M. Gietzelt ◽  
G. Nemitz ◽  
H. Meyer zu Schwabedissen ◽  
...  
Keyword(s):  
Physical Activity ◽  
Fall Risk ◽  
Regression Models ◽  
Sensor Data ◽  
Accelerometer Data ◽  
Risk Models ◽  
Logistic Regression Models ◽  
Follow Up Study ◽  
One Year

SummaryBackground: Falls are a predominant problem in our aging society, often leading to severe somatic and psychological consequences, and having an incidence of about 30% in the group of persons aged 65 years or above. In order to identify persons at risk, many assessment tools and tests have been developed, but most of these have to be conducted in a supervised setting and are dependent on an expert rater.Objectives: The overall aim of our research work is to develop an objective and unobtrusive method to determine individual fall risk based on the use of motion sensor data. The aims of our work for this paper are to derive a fall risk model based on sensor data that may potentially be measured during typical activities of daily life (aim #1), and to evaluate the resulting model with data from a one-year follow-up study (aim #2).Methods: A sample of n = 119 geriatric inpatients wore an accelerometer on the waist during a Timed ‘Up & Go’ test and a 20 m walk. Fifty patients were included in a one-year follow-up study, assessing fall events and scoring average physical activity at home in telephone interviews. The sensor data were processed to extract gait and dynamic balance parameters, from which four fall risk models – two classification trees and two logistic regression models – were computed: models CT#1 and SL#1 using accelerometer data only, models CT#2 and SL#2 including the physical activity score. The risk models were evaluated in a ten-times tenfold cross-validation procedure, calculating sensitivity (SENS), speci ficity (SPEC), positive and negative predictive values (PPV, NPV), classification accuracy, area under the curve (AUC) and the Brier score.Results: Both classification trees show a fair to good performance (models CT#1/ CT#2): SENS 74% / 58%, SPEC 96% / 82%, PPV 92% / 74%, NPV 77%/82%, accuracy 80% / 78%, AUC 0.83 / 0.87 and Brier scores 0.14 / 0.14. The logistic regression models (SL#1/ SL#2) perform worse: SENS 42% / 58%, SPEC 82% / 78%, PPV 62% / 65%, NPV 67% / 72%, accuracy 65% /70%, AUC 0.65 / 0.72 and Brier scores 0.23 / 0.21.Conclusions: Our results suggest that accelerometer data may be used to predict falls in an unsupervised setting. Furthermore, the parameters used for prediction are measurable with an unobtrusive sensor device during normal activities of daily living. These promising results have to be validated in a larger, long-term prospective trial.

Demographic factors associated with missed follow-up among solid tumor patients treated at a large multi-site academic institution

2020 ◽  
Vol 16 (32) ◽  
pp. 2635-2643
Author(s):  
Samantha L Freije ◽  
Jordan A Holmes ◽  
Saleh Rachidi ◽  
Susannah G Ellsworth ◽  
Richard C Zellars ◽  
...  
Keyword(s):  
Cancer Patients ◽  
Odds Ratio ◽  
Regression Models ◽  
Tumor Patients ◽  
Logistic Regression Models ◽  
Factors Associated ◽  
Follow Up Care ◽  
Risk Patients ◽  
African American Race

Aim: To identify demographic predictors of patients who miss oncology follow-up, considering that missed follow-up has not been well studies in cancer patients. Methods: Patients with solid tumors diagnosed from 2007 to 2016 were analyzed (n = 16,080). Univariate and multivariable logistic regression models were constructed to examine predictors of missed follow-up. Results: Our study revealed that 21.2% of patients missed ≥1 follow-up appointment. African–American race (odds ratio [OR] 1.33; 95% CI: 1.17–1.51), Medicaid insurance (OR 1.59; 1.36–1.87), no insurance (OR 1.66; 1.32–2.10) and rural residence (OR 1.78; 1.49–2.13) were associated with missed follow-up. Conclusion: Many cancer patients miss follow-up, and inadequate follow-up may influence cancer outcomes. Further research is needed on how to address disparities in follow-up care in high-risk patients.

scholarly journals Interim Estimates of COVID-19 Vaccine Effectiveness in a Mass Vaccination Setting: Data from an Italian Province

Vaccines ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 628
Author(s):  
Maria Elena Flacco ◽  
Graziella Soldato ◽  
Cecilia Acuti Martellucci ◽  
Roberto Carota ◽  
Rossano Di Luzio ◽  
...  
Keyword(s):  
Adverse Event ◽  
Retrospective Cohort ◽  
Cox Model ◽  
National Health System ◽  
Vaccine Dose ◽  
Vaccine Hesitancy ◽  
Serious Adverse Event ◽  
Italian Province ◽  
Official Data

This retrospective cohort study compared the rates of virologically-confirmed SARS-CoV-2 infections, symptomatic or lethal COVID-19 among the residents of the Italian province of Pescara who received one or two doses of COVID-19 vaccines, versus the unvaccinated. The official data of the National Health System were used, and a total of 69,539 vaccinated adults were compared with 175,687 unvaccinated. Among the subjects who received at least one vaccine dose, 85 infections (0.12%), 18 severe and 3 lethal COVID-19 cases were recorded after an average follow-up of 38 days. Among the unvaccinated, the numbers were 6948 (4.00%), 933 (0.53%) and 241 (0.14%), respectively. The serious adverse event reports—yet unconfirmed—were 24 out of 102,394 administered doses. In a Cox model, adjusting for age, gender, and selected comorbidities, the effectiveness of either BNT162b2, ChAdOx1 nCoV-19 or mRNA-1273 vaccines was higher than 95% in preventing infections (mostly due to B.1.1.7 variant), symptomatic or lethal COVID-19. No differences were observed across genders, and among the 691 subjects who received the second dose of vaccine later than the recommended date. Although preliminary, these findings support current immunization policies and may help reducing vaccine hesitancy.

scholarly journals Low HbA1c levels and all-cause or cardiovascular mortality among people without diabetes: the US National Health and Nutrition Examination Survey 1999–2015

2020 ◽  
Author(s):  
Kosuke Inoue ◽  
Roch Nianogo ◽  
Donatello Telesca ◽  
Atsushi Goto ◽  
Vahe Khachadourian ◽  
...  
Keyword(s):  
Cardiovascular Mortality ◽  
Regression Models ◽  
Machine Learning Algorithms ◽  
Logistic Regression Models ◽  
Health And Nutrition ◽  
Increased Risk ◽  
The Us ◽  
All Cause Mortality ◽  
Hba1c Levels

Abstract Objective It is unclear whether relatively low glycated haemoglobin (HbA1c) levels are beneficial or harmful for the long-term health outcomes among people without diabetes. We aimed to investigate the association between low HbA1c levels and mortality among the US general population. Methods This study includes a nationally representative sample of 39 453 US adults from the National Health and Nutrition Examination Surveys 1999–2014, linked to mortality data through 2015. We employed the parametric g-formula with pooled logistic regression models and the ensemble machine learning algorithms to estimate the time-varying risk of all-cause and cardiovascular mortality by HbA1c categories (low, 4.0 to <5.0%; mid-level, 5.0 to <5.7%; prediabetes, 5.7 to <6.5%; and diabetes, ≥6.5% or taking antidiabetic medication), adjusting for 72 potential confounders including demographic characteristics, lifestyle, biomarkers, comorbidities and medications. Results Over a median follow-up of 7.5 years, 5118 (13%) all-cause deaths, and 1116 (3%) cardiovascular deaths were observed. Logistic regression models and machine learning algorithms showed nearly identical predictive performance of death and risk estimates. Compared with mid-level HbA1c, low HbA1c was associated with a 30% (95% CI, 16 to 48) and a 12% (95% CI, 3 to 22) increased risk of all-cause mortality at 5 years and 10 years of follow-up, respectively. We found no evidence that low HbA1c levels were associated with cardiovascular mortality risk. The diabetes group, but not the prediabetes group, also showed an increased risk of all-cause mortality. Conclusions Using the US national database and adjusting for an extensive set of potential confounders with flexible modelling, we found that adults with low HbA1c were at increased risk of all-cause mortality. Further evaluation and careful monitoring of low HbA1c levels need to be considered.

scholarly journals SO093LONGITUDINAL DATA ON TREATMENT DURATION AND COMPLIANCE FROM AUTOSOMAL DOMINANT POLYCYSTIC KIDNEY DISEASE CLINICAL TRIALS WITH TOLVAPTAN

2020 ◽  
Vol 35 (Supplement_3) ◽  
Author(s):  
Xiaolei Zhou ◽  
Diana Garbinsky ◽  
John Ouyang ◽  
Eric Davenport ◽  
Indra Agarwal ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Treatment Duration ◽  
Treatment Time ◽  
Treatment Compliance ◽  
Kidney Volume ◽  
Total Kidney Volume ◽  
Treatment Gaps ◽  
Clinical Trial Program

Abstract Background and Aims : Observation of impactful clinical outcomes in a clinical trial setting for ADPKD is challenging due to the life-long progressive nature of ADPKD and longer-term associated outcomes of interest in this population (e.g., renal function decline, cardiovascular events, and mortality). Since 2004, the tolvaptan (TOL) clinical trial program enrolled subjects in multiple clinical studies with the opportunity to enroll in subsequent clinical trials for treatment and outcomes evaluation. Method : Data from 6 ADPKD studies (protocols 156-04-250, 156-04-251, 156-06-260, 156-09-284, 156-09-290, 156-08-271) were pooled and evaluated over time for overall treatment duration, treatment time, and treatment gaps. Treatment duration for the individual clinical trials ranged from 1 week to up to 3 years. Results : Overall, 1,437 subjects received TOL in these ADPKD clinical trials. For these subjects, the mean overall treatment duration was 4.1 years (3.8 years on treatment) with a maximum of 9.7 years (9.0 years on treatment). In this cohort, 513 subjects (35.7%) received TOL treatment for more than 5 years. Mean treatment compliance was 94.1%. Overall, 723 subjects (50.3%) received TOL treatment in ≥2 trials, with a median treatment gap duration between trials of 0.1 years (maximum, 5.6 years). At least 7 years of follow-up data are available for estimated glomerular filtration rate in 241 subjects (mean at baseline, 78.6 mL/min/1.73m2) and for total kidney volume in 130 subjects (mean at baseline, 1,816.9 mL). Conclusion : This analysis provides longitudinal follow-up over an extended timeframe in a large number of subjects treated with TOL, with the greatest number of subjects being enrolled in clinical trials enriched for rapidly progressing ADPKD. Treatment compliance over years was reasonably good despite treatment gaps.

scholarly journals Ethnic differences in the incidence of pterygium in a multi-ethnic Asian population: the Singapore Epidemiology of Eye Diseases Study

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Xiao Ling Fang ◽  
Crystal Chun Yuen Chong ◽  
Sahil Thakur ◽  
Zhi Da Soh ◽  
Zhen Ling Teo ◽  
...  
Keyword(s):  
Ethnic Differences ◽  
Regression Models ◽  
Multivariable Analysis ◽  
Anterior Segment ◽  
Asian Population ◽  
Eye Diseases ◽  
Logistic Regression Models ◽  
Income Status ◽  
Baseline Visit

AbstractWe evaluated the 6-year incidence and risk factors of pterygium in a multi-ethnic Asian population. Participants who attended the baseline visit of the Singapore Epidemiology of Eye Diseases Study (year 2004–2011) and returned six years later, were included in this study. Pterygium was diagnosed based on anterior segment photographs. Incident pterygium was defined as presence of pterygium at 6-year follow-up in either eye, among individuals without pterygium at baseline. Multivariable logistic regression models were used to determine factors associated with incident pterygium, adjusting for baseline age, gender, ethnicity, body mass index, occupation type, educational level, income status, smoking, alcohol consumption, presence of hypertension, diabetes and hyperlipidemia. The overall age-adjusted 6-year incidence of pterygium was 1.2% (95% confidence interval [CI] 1.0–1.6%); with Chinese (1.9%; 95% CI 1.4%-2.5%) having the highest incidence rate followed by Malays (1.4%; 95% CI 0.9%-2.1%) and Indians (0.3%; 95% CI 0.3–0.7%). In multivariable analysis, Chinese (compared with Indians; odds ratio [OR] = 4.21; 95% CI 2.12–9.35) and Malays (OR 3.22; 95% CI 1.52–7.45), male (OR 2.13; 95% CI 1.26–3.63), outdoor occupation (OR 2.33; 95% CI 1.16–4.38), and smoking (OR 0.41; 95% CI 0.16–0.87) were significantly associated with incident pterygium. Findings from this multi-ethnic Asian population provide useful information in identifying at-risk individuals for pterygium.

scholarly journals The prospective relationship between social cohesion and depressive symptoms among older adults from Central and Eastern Europe

2018 ◽  
Vol 73 (2) ◽  
pp. 117-122 ◽  
Author(s):  
Carla Bertossi Urzua ◽  
Milagros A Ruiz ◽  
Andrzej Pajak ◽  
Magdalena Kozela ◽  
Ruzena Kubinova ◽  
...  
Keyword(s):  
Depressive Symptoms ◽  
Eastern Europe ◽  
Social Cohesion ◽  
Regression Models ◽  
Central And Eastern Europe ◽  
The Czech Republic ◽  
Logistic Regression Models ◽  
Z Scores ◽  
Prospective Association

BackgroundSocial cohesion has a potential protective effect against depression, but evidence for Central and Eastern Europe is lacking. We investigated the prospective association between social cohesion and elevated depressive symptoms in the Czech Republic, Russia and Poland, and assessed whether alcohol drinking and smoking mediated this association.MethodsCohort data from 15 438 older urban participants from the Health, Alcohol and Psychosocial factors In Eastern Europe project were analysed. Baseline social cohesion was measured by five questions, and depressive symptoms were measured 3 years later by the 10-item Center for Epidemiological Depression (CES-D) Scale. Nested logistic regression models estimated ORs of elevated depressive symptoms (CES-D 10 score ≥4) by z-scores and tertiles of social cohesion.ResultsPer 1 SD decrease in social cohesion score, adjusted ORs of elevated depressive symptoms were 1.13 (95% CI 1.05 to 1.23) and 1.05 (95% CI 0.99 to 1.13) in men and women, respectively. Further adjustment for smoking and drinking did not attenuate these associations in either men (OR=1.13, 95% CI 1.05 to 1.22) or women (OR=1.05, 95% CI 0.99 to 1.13). Similarly, the fully adjusted ORs comparing the lowest versus highest social cohesion tertile were 1.33 (95% CI 1.10 to 1.62) in men and 1.18 (95% CI 1.01 to 1.39) in women.ConclusionsLower levels of social cohesion was associated with heightened depressive symptoms after a 3-year follow-up among older Czech, Russian and Polish adults. These effects appeared stronger in men, and alcohol and smoking played no appreciable role in this association.

scholarly journals Alcohol consumption and pregnancy in the Mexican national addiction survey

1997 ◽  
Vol 13 (2) ◽  
pp. 205-211 ◽  
Author(s):  
Guilherme Borges ◽  
Roberto Tapia-Conyer ◽  
Malaquías López-Cervantes ◽  
María Elena Medina-Mora ◽  
Blanca Pelcastre ◽  
...  
Keyword(s):  
Alcohol Consumption ◽  
Spontaneous Abortion ◽  
Regression Models ◽  
Congenital Abnormalities ◽  
Adverse Outcomes ◽  
Multiple Logistic Regression ◽  
National Data ◽  
Logistic Regression Models ◽  
Important Relationship

In 1988, the General Directorate of Epidemiology and the Mexican Institute of Psychiatry conducted the first National Addiction Survey (ENA), providing regional and national data on alcohol, tobacco, and drug use. The ENA providing a subsample of women who have been pregnant at some time in their lives. There were 5,234 affirmative responses. Women were asked if they had suffered any of three adverse outcomes during their last pregnancy: spontaneous abortion, stillbirth, and congenital abnormalities. Prevalence of spontaneous abortion was 3.8%, stillbirth 1.2%, and congenital abnormalities 1.1 %. Multiple logistic-regression models were used to analyze the effect of alcohol consumption on these problems. Consumption during pregnancy was related only with the prevalence of congenital abnormalities, with prevalence odds of 3.4. Among habitual users during the last 12 months, oniy women in the highest use category showed an important relationship with the three problems mentioned. Follow-up studies on the Mexican population are recommended in order to obtain more conclusive findings.

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>

scholarly journals Coffee Consumption, Genetic Polymorphisms, and the Risk of Type 2 Diabetes Mellitus: A Pooled Analysis of Four Prospective Cohort Studies

2020 ◽  
Vol 17 (15) ◽  
pp. 5379
Author(s):  
An Na Kim ◽  
Hyun Jeong Cho ◽  
Jiyoung Youn ◽  
Taiyue Jin ◽  
Moonil Kang ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Regression Models ◽  
Coffee Consumption ◽  
Pooled Analysis ◽  
Random Effects Model ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Logistic Regression Models

The association between coffee consumption and the risk of type 2 diabetes may vary by genetic variants. Our study addresses the question of whether the incidence of type 2 diabetes is related to the consumption of coffee and whether this relationship is modified by polymorphisms related to type 2 diabetes. We performed a pooled analysis of four Korean prospective studies that included 71,527 participants; median follow-up periods ranged between 2 and 13 years. All participants had completed a validated food-frequency questionnaire (FFQ) at baseline. The odds ratios (ORs) and 95% confidence intervals (CIs) for type 2 diabetes were calculated using logistic regression models. The ORs were combined using a fixed or random effects model depending on the heterogeneity across the studies. Compared with 0 to <0.5 cups/day of coffee consumption, the OR for type 2 diabetes was 0.89 (95% CI: 0.80–0.98, p for trend = 0.01) for ≥3 cups/day of coffee consumption. We did not observe significant interactions by five single nucleotide polymorphisms (SNPs) related to type 2 diabetes (CDKAL1 rs7756992, CDKN2A/B rs10811661, KCNJ11 rs5215, KCNQ1 rs163184, and PEPD rs3786897) in the association between coffee and the risk of type 2 diabetes. We found that coffee consumption was inversely associated with the risk of type 2 diabetes.

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