Fatigue in newly diagnosed acute myeloid leukaemia: general population comparison and predictive factors

2021 ◽  
pp. bmjspcare-2020-002312
Author(s):  
Laura B Oswald ◽  
Adriano Venditti ◽  
David Cella ◽  
Francesco Cottone ◽  
Anna Candoni ◽  
...  
Keyword(s):  
General Population ◽  
Linear Regression ◽  
Acute Myeloid Leukaemia ◽  
Regression Models ◽  
Disease Risk ◽  
Newly Diagnosed ◽  
Linear Regression Models ◽  
Mean Differences ◽  
Risk Categories ◽  
Acute Myeloid

ObjectivesThis study compared the burden of fatigue between treatment-naïve patients with newly diagnosed acute myeloid leukaemia (AML) and the general population and investigated patient factors associated with fatigue severity.MethodsPretreatment patient-reported fatigue was assessed with the Functional Assessment of Chronic Illness Therapy-Fatigue questionnaire in a sample of 463 newly diagnosed patients with AML who were enrolled in a clinical trial. Multivariable linear regression models were used to estimate the adjusted mean differences in fatigue between patients with AML and adults from the general population (n=847) by AML disease risk categories. A clinically meaningful difference in fatigue was defined as ≥3 points. Univariable and multivariable linear regression models were used to identify sociodemographic, clinical and molecular correlates of worse fatigue in patients with AML.ResultsPatients with AML reported adjusted mean fatigue scores that were 7.5 points worse than the general population (95% CI −8.6 to −6.4, p<0.001). Across AML disease risk categories, adjusted mean differences in fatigue compared with the general population ranged from 6.7 points worse (patients with favourable risk: 95% CI −8.6 to −4.8, p<0.001) to 8.9 points worse (patients with poor risk, 95% CI −10.5 to −7.2, p<0.001). Overall, 91% of patients with AML reported fatigue that was equal to or worse than the general population’s median fatigue score. Higher pretreatment fatigue was independently associated with female sex, WHO performance status ≥1 and lower platelet levels.ConclusionsPatients with newly diagnosed AML reported worse fatigue than the general population, and mean differences exceeded twice the threshold for clinical significance. Our findings may help to identify patients with AML most likely to benefit from supportive care interventions to reduce fatigue.

scholarly journals Physiological Aldosterone Concentrations Are Associated with Alterations of Lipid Metabolism: Observations from the General Population

2018 ◽  
Vol 2018 ◽  
pp. 1-6 ◽  
Author(s):  
M. Hannich ◽  
H. Wallaschofski ◽  
M. Nauck ◽  
M. Reincke ◽  
C. Adolf ◽  
...  
Keyword(s):  
Lipid Metabolism ◽  
General Population ◽  
Linear Regression ◽  
Standard Error ◽  
Regression Models ◽  
Adult Population ◽  
Density Lipoprotein ◽  
Lipoprotein Cholesterol ◽  
Inverse Association ◽  
Linear Regression Models

Objective. Aldosterone and high-density lipoprotein cholesterol (HDL-C) are involved in many pathophysiological processes that contribute to the development of cardiovascular diseases. Previously, associations between the concentrations of aldosterone and certain components of the lipid metabolism in the peripheral circulation were suggested, but data from the general population is sparse. We therefore aimed to assess the associations between aldosterone and HDL-C, low-density lipoprotein cholesterol (LDL-C), total cholesterol, triglycerides, or non-HDL-C in the general adult population. Methods. Data from 793 men and 938 women aged 25–85 years who participated in the first follow-up of the Study of Health in Pomerania were obtained. The associations of aldosterone with serum lipid concentrations were assessed in multivariable linear regression models adjusted for sex, age, body mass index (BMI), estimated glomerular filtration rate (eGFR), and HbA1c. Results. The linear regression models showed statistically significant positive associations of aldosterone with LDL-C (β-coefficient = 0.022, standard error = 0.010, p=0.03) and non-HDL-C (β-coefficient = 0.023, standard error = 0.009, p=0.01) as well as an inverse association of aldosterone with HDL-C (β-coefficient = −0.022, standard error = 0.011, p=0.04). Conclusions. The present data show that plasma aldosterone is positively associated with LDL-C and non-HDL-C and inversely associated with HDL-C in the general population. Our data thus suggests that aldosterone concentrations within the physiological range may be related to alterations of lipid metabolism.

scholarly journals Joint effects of fatty acid desaturase 1 polymorphisms and dietary polyunsaturated fatty acid intake on circulating fatty acid proportions

2018 ◽  
Vol 107 (5) ◽  
pp. 826-833 ◽  
Author(s):  
Juan Juan ◽  
Hongyan Huang ◽  
Xia Jiang ◽  
Andres V Ardisson Korat ◽  
Mingyang Song ◽  
...  
Keyword(s):  
Fatty Acid ◽  
Linear Regression ◽  
Regression Models ◽  
Disease Risk ◽  
Fatty Acid Desaturase ◽  
Gas Liquid Chromatography ◽  
Linear Regression Models ◽  
Dietary Pufa ◽  
Pufa Intake ◽  
Joint Effects

ABSTRACT Background Polyunsaturated fatty acids (PUFAs) are associated with a lower risk of multiple diseases. Fatty acid desaturase 1 gene (FADS1) polymorphisms and dietary PUFA intake are both established determinants of circulating PUFA proportions. Objective We explored the joint effects of FADS1 polymorphisms and dietary PUFA intake on circulating PUFA proportions. Design We studied 2288 participants from a nested case-control study of coronary artery disease among participants who provided blood samples in the Nurses’ Health Study and the Health Professionals Follow-Up Study. Dietary PUFA intake was obtained from semiquantitative food-frequency questionnaires. FADS1 rs174546 was genotyped by using the Affymetrix 6.0 platform, and circulating PUFA proportions were measured with gas-liquid chromatography. Linear regression models were used to examine the associations between rs174546 and circulating proportions of each fatty acid. Gene-diet interactions were tested by including a cross-product term of dietary intake of each PUFA by rs174546 genotype in the linear regression models. Results After adjustment for sex and ancestry, each copy of the C allele of rs174546 was associated with higher circulating proportions of arachidonic acid, eicosapentaenoic acid (EPA), and docosahexaenoic acid (DHA) and lower proportions of linoleic acid and α-linolenic acid. The magnitude of positive association between higher consumption of dietary EPA or DHA and circulating proportions of EPA increased with each copy of the rs174546_T allele (P-interaction = 0.01 and 0.007, respectively). Each 1-SD increment in EPA intake was associated with an average 3.7% increase in circulating EPA proportions among participants with the rs174546_CC genotype and an average 7.8% increase among participants with the TT genotype. Conclusions Carriers of the T allele at FADS1 rs174546 may need higher doses of dietary EPA and DHA to achieve the same circulating proportions of EPA as carriers of the C allele. The implications of these findings on disease risk and dietary guidelines require further study.

FAKTOR DETERMINAN PENYALURAN KREDIT BANK PERSERO

2018 ◽  
Vol 23 (1) ◽  
pp. 60-71
Author(s):  
Wigiyanti Masodah
Keyword(s):  
Interest Rate ◽  
Linear Regression ◽  
Interest Rates ◽  
Regression Models ◽  
Linear Regression Models ◽  
Negative Impacts ◽  
Main Activity ◽  
The Impact ◽  
The Given ◽  
Multiple Linear Regression Models

Offering credit is the main activity of a Bank. There are some considerations when a bank offers credit, that includes Interest Rates, Inflation, and NPL. This study aims to find out the impact of Variable Interest Rates, Inflation variables and NPL variables on credit disbursed. The object in this study is state-owned banks. The method of analysis in this study uses multiple linear regression models. The results of the study have shown that Interest Rates and NPL gave some negative impacts on the given credit. Meanwhile, Inflation variable does not have a significant effect on credit given. Keywords: Interest Rate, Inflation, NPL, offered Credit.

Linear Regression Models for Interval-Valued Data using Log-transformation

2020 ◽  
Author(s):  
Nykolas Mayko Maia Barbosa ◽  
João Paulo Pordeus Gomes ◽  
César Lincoln Cavalcante Mattos ◽  
Diêgo Farias Oliveira
Keyword(s):  
Linear Regression ◽  
Regression Models ◽  
Linear Regression Models ◽  
Log Transformation ◽  
Interval Valued

THE PREDICTIVE CONTENT OF DISAGGREGATED NORMAL INCOME: An Empirical Study in the JSX

2003 ◽  
Vol 5 (3) ◽  
pp. 363 ◽  
Author(s):  
Slamet Sugiri
Keyword(s):  
Linear Regression ◽  
Regression Models ◽  
Stock Exchange ◽  
Manufacturing Firms ◽  
Single Step ◽  
Model Parameters ◽  
Linear Regression Models ◽  
Operating Income ◽  
Predictive Content ◽  
Multiple Step

The main objective of this study is to examine a hypothesis that the predictive content of normal income disaggregated into operating income and nonoperating income outperforms that of aggregated normal income in predicting future cash flow. To test the hypothesis, linear regression models are developed. The model parameters are estimated based on fifty-five manufacturing firms listed in the Jakarta Stock Exchange (JSX) up to the end of 1997.This study finds that empirical evidence supports the hypothesis. This evidence supports arguments that, in reporting income from continuing operations, multiple-step approach is preferred to single-step one.

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