Due to uncertainty around the diagnostic accuracy of the NT-proBNP test, two scenario analyses were undertaken to assess the diagnostic accuracy data and from two other study populations included in the clinical review. A further limitation of the anlaysis is that when applying the ordinal logistic regression model to the Verdu data to enable the results to be run probabilistically, the mean sensitivity values were not consistent with the reported study values. Therefore the Verdu study was run both probabilistically (using the ordinal logistic regression model data) and deterministically (using the reported study data). The inconsistency in the mean values from the regression model and those reported in the study was thought to be due to the fact that the sensitivity of 280pg/ml and 125pg/ml threshold were both 100%. Ordinal logisitic regression was thought to be the most suitable method to fit a distribution to Chronic Heart Failure Diagnosing heart failure the diagnostic accuracy data to ensure that the sensitivity and specificity values maintained their order according to the threshold level for each run. Using this method one assumes that the model is predicting values that the data would show if you had a greater sample size. The probabilistic analysis for Verdu found 400pg/ml to be the most cost effective NT-proBNP threshold, however when run deterministically using the reported study values 280pg/ml was found to be the most cost-effective threshold. This is likely to be due to the fact that this threshold had both the highest sensitivity and highest specificity. The other scenario analyses (Zaphiriou) found 280pg/ml to be the most cost effective NT-proBNP threshold. 