Sentence examples for multiple validation cohorts from inspiring English sources

Multiple validation cohorts were independently studied to test whether target indices were related to pathological response to neoadjuvant chemotherapy (GSE21094 (T/FAC), GSE22513 (T), GSE25055 & GSE25065 (AT).

We used multiple imputation in the two validation cohorts to replace missing values for continuous variables and smoking status.

The prognostic performance of the HRneg/Tneg index was also compared with that of other well-validated multigene predictors; in addition, the multiple predictive indices were compared with one another across both the training and validation cohorts.

A non-parametric Mann-Whitney U test was used for comparison of two independent groups in the training cohort and a non-parametric Kruskal-Wallis test with Dunn's multiple comparison post hoc analysis was used for comparison of multiple groups in the validation cohort.

In the comparison between the MCI individuals and OCs, both the training and the validation cohorts demonstrated similar AUC values indicating the reliability of these measures across multiple independent cohorts.

Furthermore, our study benefits from the use of test and validation cohorts, the latter representing an independent, external validation subset on which protein markers were assessed by multiple independent pathologists, thus further confirming the reproducibility of the CD8/TIA-1 systemg system and effect on outcome.

In well-defined patients, we found multiple miRNAs, miR- 192-5p, -194-5p, 215-5p to have an excellent accuracy for BE diagnosis in the discovery and validation cohorts (91 100% sensitivity and >90% specificity).

Performance of models was tested in validation cohorts.

Furthermore, ventilator parameters were also comparable, with the exception of FiO2 (80%% in derivation and temporal validation cohorts, 60%% in spatial validation cohort).

The racial distribution was more heterogeneous in the geographic validation cohort, while the derivation and the temporal validation cohorts were almost entirely Caucasian.

Both validation cohorts contained fewer patients than the development cohort.