Ezr software

Manufactured by R Project for Statistical Computing

Sourced in Austria

EZR (Easy R) is a graphical user interface (GUI) for the R statistical computing environment. It provides a user-friendly interface for performing common statistical analyses and data visualization tasks using the R programming language. EZR's core function is to simplify the use of R for those who are not familiar with the command-line interface or programming. The software aims to make R more accessible to a wider audience by providing a point-and-click interface for data manipulation, analysis, and visualization.

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Lab products found in correlation

Plink version 1, by R Project for Statistical Computing (1 mentions) R commander, by R Project for Statistical Computing (1 mentions)

15 protocols using ezr software

Lymph Node Relapse Analysis

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A P-value ≤0.05 was considered statistically significant. EZR software (Saitama Medical Center, Jichi Medical University, Saitama, Japan) was used for all analyses. EZR software is a graphical user interface for R, a modified version of R commander (version 1.6–3; The R Foundation for Statistical Computing, Vienna, Austria, version 2.13.0) with statistical functions used in biostatistics (30 (link)).
The optimal cut-off values for lymph node relapse (maximizing the sum of sensitivity and specificity) were also analyzed by EZR software using receiver operating characteristic (ROC) curve analysis.

Kimura S., Noguchi H., Nanbu U, & Nakayama T. (2021). Macrophage CCL22 expression promotes lymphangiogenesis in patients with tongue squamous cell carcinoma via IL-4/STAT6 in the tumor microenvironment. Oncology Letters, 21(5), 383.

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Antimicrobial Prescriptions for Common Cold and Other Respiratory Tract Infections

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We stratified the eligible cases by the presence of clinical manifestations associated with ARTIs. Cases were grouped by the involvement of respiratory tract regions (nasal, pharyngo-laryngeal, and bronchial), with descriptions of three, two, and two or more regions involved. Categorical variables were shown in the numbers, percentages, and odds ratios (ORs) with their 95% confidence intervals (CIs), which were assessed with the chi-squared test or Fisher’s exact test, as appropriate. Continuous variables were summarized with median and interquartile range (IQR). The primary outcome was the proportion of antimicrobial prescriptions and the drugs prescribed for patients diagnosed with the common cold. The secondary outcomes were defined as the proportion of antimicrobial prescriptions and the drugs prescribed for patients diagnosed with respiratory tract infections other than the common cold. The data were analyzed using EZR software, a graphic user interface for the R 3.5.2 software (The R Foundation for Statistical Computing, Vienna, Austria). All reported p values less than 0.05 were considered statistically significant.

Ishida T., Hagiya H., Honda H., Nakano Y., Ogawa H., Obika M., Ueda K., Kataoka H., Hanayama Y, & Otsuka F. (2021). Antimicrobial prescription practices for outpatients with acute respiratory tract infections: A retrospective, multicenter, medical record-based study. PLoS ONE, 16(11), e0259633.

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Predictive Value of Arrhythmia Scores

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All categorical variables were presented as number and percentage in each group. Continuous variables were expressed as mean ± standard deviation (SD) or medians (25th, 75th, interquartile range range). Categorical variables were compared between the groups by chi-square or Fisher exact tests, as appropriate. Continuous variables between the groups were examined by an unpaired t test or Mann-Whitney U test. The predictive value of tested scores was calculated as the area under the curve (AUC) with 95% confidence interval under the receiver operating characteristic (ROC) curves. The comparison of AUC between each score was evaluated using DeLong test. The optimal cutoff values were determined using Youden’s index. The univariate Cox’s proportional hazards were analyzed separately for each factor of the validated scores. The mean arrhythmia-free survival curves were determined by Kaplan-Meier estimation and compared between the subgroups in the higher or lower MB-LATER score with the cutoff level using the log-rank test. A two-sided p value of < 0.05 was considered statistically significant. All statistical analyses were performed using EZR software, which is a graphical user interface for R (The R Foundation for Statistical Computing, Vienna, Austria).

Sano M., Heeger C.H., Sciacca V., Große N., Keelani A., Fahimi B.H., Phan H.L., Reincke S., Brüggemann B., Fink T., Liosis S., Vogler J., Eitel C, & Tilz R.R. (2020). Evaluation of predictive scores for late and very late recurrence after cryoballoon-based ablation of atrial fibrillation. Journal of Interventional Cardiac Electrophysiology, 61(2), 321-332.

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Comparison of Exercise and Inspiratory Muscle Training

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The clinical backgrounds of the exercise therapy and the IMT load + exercise therapy groups were compared using the χ² test and Student’s t-test. Variations in MIP and MBS ratings were examined using a two-way repeated-measures analysis of variance (ANOVA) to investigate the effects of IMT. Mauchly’s test of sphericity was used to test the assumption of sphericity; when it yielded statistically significant results, the Greenhouse–Geisser ε correction was used to adjust violations of sphericity. In addition, Bonferroni’s method was used for multiple comparisons. Statistical analysis was performed using EZR software (EZR Version 1.60., The R Foundation for Statistical Computing, Vienna, Austria) [23 (link)]. Descriptive data are expressed as the mean ± standard deviation or standard error values. The significance level was set at 5%.

Sakai Y., Yamaga T., Yamamoto S., Matsumori K., Ichiyama T., Hanaoka M., Ikegami S, & Horiuchi H. (2023). Effects and Usefulness of Inspiratory Muscle Training Load in Patients with Advanced Lung Cancer with Dyspnea. Journal of Clinical Medicine, 12(10), 3396.

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Multivariate Analysis of Categorical Data

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Categorical variables were shown in numbers, percentages, and odds ratios (OR) with their 95% confidential intervals (CIs), which were assessed with the Chi-square test or Fisher's exact test as appropriate. Continuous variables were summarized with median and interquartile range (IQR). For multivariate analysis, we applied a logistic regression model. The data were analyzed using EZR software, a graphic user interface for the R 4.0.3 software (The R Foundation for Statistical Computing, Vienna, Austria). All estimates were expressed as point estimates with 95% CI, and all reported p-values less than 0.05 were considered statistically significant.

Takahashi M., Hagiya H., Higashionna T., Nakano Y., Sato K., Haruki Y., Haruki M., Honda H., Ogawa H., Ueda K, & Otsuka F. (2022). Antimicrobial prescription practices for outpatients with uncomplicated cystitis in Japan. Scientific Reports, 12, 5921.

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Everyday vs. Occasional Drivers: Comparative Study

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“Everyday drivers” were defined as those who answered they drive almost every day, while the rest were defined as “occasional drivers”; the background of these groups of drivers was compared. During the study period, data was prospectively collected without sample size calculation. Categorical variables were expressed as numbers, percentages, and odds ratios (ORs) with their 95% confidence intervals (CIs), which were assessed using the chi-square test or Fisher’s exact test, as appropriate. Continuous variables were expressed as median and interquartile range (IQR) and were analyzed using the Mann–Whitney test. The data were analyzed using EZR software, a graphic user interface for the R 3.5.2 software (The R Foundation for Statistical Computing, Vienna, Austria) [16 (link)]. A P-value of < 0.05 was considered significant.

Hagiya H., Takase R., Honda H., Nakano Y., Otsuka Y., Kataoka H., Uno M., Ueda K., Takahashi M., Ogawa H., Hanayama Y, & Otsuka F. (2022). Prevalence of medical factors related to aging among older car drivers: a multicenter, cross-sectional, descriptive study. BMC Geriatrics, 22, 792.

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Survival Analysis of FCM Subtypes

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The data were expressed as mean ± SD. Statistical analysis was performed using Student's t-test (two-tailed) or Fisher's exact test. The Kaplan-Meier method was used to estimate the survival curves and median survival time, and the log-rank test was used to test for differences in survival between the FCM-C and FCM-D groups. A p-value of <0.05 was considered statistically significant. Statistical analysis was performed using EZR software, a graphical user interface for R (The R Foundation for Statistical Computing, Vienna, Austria).^{13 (link)}⁾

TAKEUCHI H., INABA T., SHISHIDO-HARA Y., TSUKAMOTO T., MIZUTANI S., OKAMOTO T., TANIGAWA S., YAMANAKA T., TAKAHASHI Y., KONISHI E., KURODA J, & HASHIMOTO N. (2023). Analysis of False-negative Findings of the Incomparable Accuracy and Swiftness of Flow Cytometric Diagnosis of Primary Central Nervous System Lymphoma. Neurologia medico-chirurgica, 63(11), 495-502.

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Cardiac MRI Measurements and Analysis

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All continuous data were expressed as the mean ± standard deviation or numbers (%). Comparisons among the groups were analyzed using a univariate analysis (one-way ANOVA, post-hoc test, and Fisher's exact test). Multivariable linear regression models were used to assess the relationship between each CMR parameter. The models included the age, types of cardiomyopathy, LVEF on echocardiography, and LA volume.
The intra-observer agreement for the LA measurements was determined for 20 randomly selected patients. One reader remeasured the same cases one month later after the first measurement for the intra-observer variability. Bland-Altman plots were computed to assess the intra-observer variability. The statistical analyses were performed using EZR software, a graphical user interface for R (The R Foundation for Statistical Computing, version 2.13.0). Statistical significance was determined at a p < 0.05.

Koike H., Kishi S., Hosoda N., Takemoto S., Tomii D., Ninomiya K., Tanaka T., Asami M., Yahagi K., Komiyama K., Tanaka J., Yuzawa H., Nakanishi R., Fujino T., Aoki J., Venkatesh B.A., Lima J.A., Tanabe K, & Ikeda T. (2020). The impact of tissue-tracking strain on the left atrial dysfunction in the patients with left ventricular dysfunction. International Journal of Cardiology. Heart & Vasculature, 26, 100453.

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Competing Risks Analysis of TKI Therapy Response

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Cumulative incidence of responses to IM therapy including CCyR, MMR, and DMR were calculated considering competing risks (i.e., switch to other TKI or death or progression). Gray’s test was used for comparison according to TCGAATAC haplotype. The Fine-Gray model was adopted for multivariate analysis. Student’s t test was used for independent samples, and the Wilcoxon rank sum or Kruskal–Wallis rank sum test was used to calculate difference in cell viability or for eQTL analysis. All statistical analyses were performed using PLINK Version 1.07 [41 ], R (R Foundation for Statistical Computing, Austria), and EZR software (https://www.jichi.ac.jp/saitama-sct/SaitamaHP.files/statmedEN.html) [18 (link)].

Park J.H., Woo Y.M., Youm E.M., Hamad N., Won H.H., Naka K., Park E.J., Park J.H., Kim H.J., Kim S.H., Kim H.J., Ahn J.S., Sohn S.K., Moon J.H., Jung C.W., Park S., Lipton J.H., Kimura S., Kim J.W, & Kim D.(. (2018). HMGCLL1 is a predictive biomarker for deep molecular response to imatinib therapy in chronic myeloid leukemia. Leukemia, 33(6), 1439-1450.

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Unpaired t-test and Correlation Analysis

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Intergroup differences were tested for significance with the unpaired Student’s t‐test. Correlation analysis was based on Pearson’s correlation coefficient. A P‐value of <0.05 was considered statistically significant. All statistical analysis was carried out with EZR software (The R Foundation for Statistical Computing, Vienna, Austria)24.

Sugawara K., Okada Y., Hirota Y., Sakaguchi K, & Ogawa W. (2020). Relationship between metformin use and vitamin B12 status in patients with type 2 diabetes in Japan. Journal of Diabetes Investigation, 11(4), 917-922.

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