Jmp pro version 11

Differences between measurements and groups were tested with the Mann–Whitney U, Kruskal–Wallis, or Steel–Dwass test. Paired t testing was used to determine the level of significance of change in LRG levels over time during the clinical course of disease. A receiver operated characteristic [ROC] curve was generated by plotting the false-positive fraction versus the true-positive fraction for every possible cutoff score,^{25 (link)} and area under the ROC curve [AUC] was calculated. Multivariable logistic regression analysis was performed to investigate factors associated with the increase in LRG; p- values < 0.05 were considered as statistically significant. All analyses were performed using JMP^® Pro version 11 software [SAS, Cary, NC].

Data regarding patient characteristics and various biomarker levels are given as percentage, mean±SD, or median (IQR). We used the chi-squared test to compare the proportion of categorical variables (e.g., complications) between the 2 groups. We used the Mann-Whitney U-test to compare the various biomarker levels between the groups. The Kaplan-Meier method was used to estimate pacing lead survival. We compared freedom from lead complications using log-rank test. Event-free survival in lead failure was calculated from the date of lead implantation to the date of lead failure. We used multivariate logistic regression analysis to analyze the risk factors associated with lead failure, including age <16 years at the time of lead placement, atrial lead, moderate to severe CHD, and ICD lead. Age <12 years and atrial leads were reported as risk factors for lead failure.⁴ (link)^,13 (link)^,14 (link)
Given that only a small number of patients were age <12 years (n=3), we used age <16 years as a variable on multivariate analysis. JMP Pro version 11 (SAS Institute, Cary, NC, USA) was used for all analyses. P<0.05 was considered significant.

Data were presented as mean, mean ± SD, n or n(%). The required sample size was calculated based on analyses of the mean ± SD age of patients treated with NAC, primary surgery and radiotherapy, and the proportion of patients with stage IIb cancer.
Differences in PFS and OS between the groups were compared using the log-rank test. Patient and tumour characteristics and adverse events were compared using Fisher’s exact test, apart from age and tumour size, which were compared using Student’s t-test.
A P-value < 0.05 was considered to be statistically significant. Statistical analyses were performed using STATA™ software, version 13 (StataCorp LP, College Station, TX, USA) and JMP Pro version 11 (SAS Institute Inc., Cary, NC, USA).

Overall survival (OS) was calculated from the date of the start of induction chemotherapy until the date of death of any cause or last documented follow-up. Disease free survival (DFS) was calculated from the delivery of induction chemotherapy until death of any cause or evidence of disease relapse. Baseline patient, disease and treatment related variables were reported using descriptive statistics (counts, medians and percentages). Categorical and continuous variables were compared using Pearson's chi-squared and Wilcoxon / Kruskal-Wallis, respectively. Probability of OS and DFS was computed using the Kaplan-Meier method. Group comparisons were made using the log-rank test. Statistical analyses were performed using JMP Pro-Version 11 (SAS Institute, Cary, NC, USA) software and EZR on R commander.

Baseline patient, disease and treatment related variables were reported using descriptive statistics (counts, medians and percentages). Categorical and continuous variables were compared using Pearson’s χ² and Wilcoxon/Kruskal-Wallis, respectively. Probability of OS was computed using the Kaplan-Meier method. Group comparisons were made using the log-rank test. Time to event was calculated from the date of transplant until the event of interest or point of last clinical encounter, in which case the event will be censored. Cumulative incidence was computed as competing events using Grey’s model, considering death as a competing event for relapse and relapse as a competing event for NRM. Univariable and multivariable analyses were performed using Cox proportional hazard regression modelling and expressed as HR with 95%CI and P value. Any variable with a P ≤ 0.1 was incorporated into the multivariable model in a stepwise selection process. Thresholds of ALC recovery post HCT as well as infused allograft characteristics, if present, were assessed using the ROC and AUC for the end point of relapse. Statistical analysis were performed using JMP Pro Version 11 (SAS Institute, Cary, NC, United States) software and EZR on R commander version 1.28[22 (link)].