Secondary Variables Sample Clauses

Secondary Variables. Exhibit 4.2-16 Secondary variables are those measurements not directly used in the calculation of test results. These variables will be measured to provide backup readings for the primary variables, to allow the Owner to establish complete heat balance calculations around the cycle and individual Plant components, and to provide assistance in pinpointing any improper test operating condition. Secondary variables will generally be permanent Plant instrumentation. However, the Owner may choose to install a number of temporary test instruments to achieve more accurate results in evaluating individual component performance.
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Secondary Variables. 4.2.3.1 Change in tumour size at 12 weeks The absolute values and percentage change in target lesion tumour size from baseline will be summarised using descriptive statistics and presented at each time point and by randomised treatment group. The number and percentage of subjects in each treatment group whose week 12 data is imputed will also be presented. At blind review, plots of the residuals from fitting an ANCOVA model (including covariates for baseline tumour size, time from randomisation to baseline assessment and PIK3CA mutation status) to the percentage change from baseline at week 12 will be produced. If the residuals appear to follow a normal distribution then the same model will be used in the final analysis with an additional term for treatment. The model will be repeated in each of the PIK3CA mutation subgroup (protocol definition) analyses. In each case, the results to be presented include: the adjusted least square means for each treatment, the difference in least square means between treatments, the adjusted geometric least square means for each treatment (back transformed to the original scale), the ratio of the geometric least square means, In each case, the results to be presented include: Should neither of the above parametric models produce normally distributed residuals, a non- parametric approach will be applied instead. The recommended method is an ANCOVA model on the ranked percentage change in tumour size, including a covariate for baseline tumour size, time from randomisation to baseline assessment, treatment and PIK3CA status. The ranking will be of the analysis data set following appropriate imputation. The subject with the greatest reduction in target lesion tumour size will be assigned the lowest rank, with smaller changes and increases in tumour sizes taking increasing ranks. Deaths will be assigned the highest rank. The model will be repeated in each of the PIK3CA mutation subgroup analyses. If a non-parametric analysis is performed, the p-value from the ANCOVA model will be presented together with the Xxxxxx Xxxxxxx estimate of the median difference and The median percentage change and range will be presented for each treatment group, together with the number of subjects and percentage of subjects in each treatment group whose 12 week data is imputed (imputation as described above or using a regression method) in the non-parametric analysis. Tumour size is also to be presented graphically using waterfall plots for each tr...
Secondary Variables. Secondary efficacy variables and endpoints are as follows: • proportion of patients achieving an SRI response at each visit during the treatment period • proportion of patients achieving a reduction of at least 4 points in the SLEDAI-2K total score at each visit during the treatment period • proportion of patients achieving a clinical SLEDAI-2K response at each visit during the treatment period, where the clinical response is defined as a reduction of at least 4 points in the SLEDAI-2K clinical score • proportion of patients achieving a BILAG-2004 response at each visit during the treatment period (no new BILAG A body system score and no more than 1 new BILAG B body system score from baseline) • proportion of patients achieving a BILAG-2004 clinical response at each visit during the treatment period (an improvement in at least 1 category from a B score to a C or D score, with no worsening in any other category) • proportion of patients showing no worsening on a PhGA scale at each visit during the treatment period • proportion of patients achieving a reduction of 5 points in the SLEDAI-2K total score at each visit during the treatment period • proportion of patients achieving a reduction of 6 points in the SLEDAI-2K total score at each visit during the treatment period • proportion of patients achieving an SRI-5 response at each visit during the treatment period • proportion of patients achieving an SRI-6 response at each visit during the treatment period • proportion of patients showing an improvement in tender and swollen joint counts using the 28-joint count examination for pain and tenderness at each visit during the treatment period • SFI at each visit during the treatment period — time to first mild to moderate flare — incidence of mild to moderate flare — time to severe flare (NOTE: A severe flare leads to early withdrawal) • changes in the SDI over time (assessed at screening and weeks 24 and 52 [or final assessment]) • absolute and relative changes in the SF-36 at weeks 12, 24, 36, and 52 (or final assessment) proportion of patients with changes in steroid dose over time throughout the study. The exploratory efficacy variables and endpoints for this study are as follows: • changes in the biomarkers anti-dsDNA Ab, C3, and C4 at each visit during the treatment period • changes in the following biomarkers at weeks 4, 12, 24, 36, and 52 (or final assessment): — ANA — anti–U1-70K snRNP Ab — anti-Sm Ab — CRP — IgG, IgM, IgA and IgE • absolute and relativ...

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