Objective response rate Sample Clauses

Objective response rate. (XXX) at week 12 XXX at week 12 is defined as the percentage of patients who have a week 12 visit response of CR or PR prior to any evidence of progression (as defined by RECIST 1.1) and regardless of whether the responses are confirmed or not. A visit response of CR is defined when all TL and NTL lesions present at baseline have disappeared (with the exception of lymph nodes which must be <10mm to be considered non- pathological) and no ne w lesions have developed since baseline. A visit response of PR is defined when the sum of diameters of the TLs has decreased by 30% or more compared to baseline (with no evidence of progression) and the NTLs are at least stable with no evidence of new lesions. The denominator for all response rate calculations will be based on Full analysis set.
Sample 1
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Objective response rate. (XXX) Objective response rate (XXX) as defined in section 3.2.2.1 will be reported and analyzed over the whole study and reported at week 12 in the ITT. A tabulation of response rate at 12 weeks and proportion progression free at 12 weeks will be presented for the overall population, PIK3CA detected and PIK3CA not detected. Best overall response will be presented by treatment group at time of PFS analysis. Frequencies and percentages will be presented for complete responses and partial response, stable disease, progressive disease and not evaluable. Summaries will be repeated based on the overall population, PIK3CA detected, PIK3CA not detected, PIK3CA detected (blood (ctDNA)) and PIK3CA not detected (blood (ctDNA)). Objective tumour response rates will be compared between the two treatment arms for scenarios i – iii outlined in the primary analysis above using a logistic regression model allowing for the effect of treatment and adjusted for PIK3CA mutation status in the overall population. The analysis will also be repeated based on PIK3CA mutation detected/not detected by blood (ctDNA) only. The objective tumour response rate will be estimated for each arm. If there is an imbalance in the covariates, adjusted response rates will also be presented. These are the counterparts of lsmeans from linear models and require conditioning on one arm’s observed response rate. An estimate statement would be used that weights log-odds in line with the prevalence of the covariates.
Sample 1

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