Primary Analysis of Efficacy Sample Clauses

Primary Analysis of Efficacy. ‌ The intent-to-treat (ITT) population, which includes all randomized patients who received at least one dose of study medication, will be used as the primary population for assessment of efficacy. Likelihood-based estimation with mixed-model repeated measures (MMRM) analysis will compare the treatment groups with respect to the primary endpoint. The dependent variable will be change from baseline in 6MWD. The model will include treatment, visit, and the treatment-by-visit interactions as fixed effects; stratification by number of background PAH therapies (0, 1, or 2); and visit as a repeated measure having an unstructured covariance structure. Covariates may be defined in the SAP as appropriate. Missing data will not be imputed for the primary analysis. To assess the assumption of missing at random (MAR), a tipping point approach for imputing missing data will be performed as a sensitivity analysis. Shift parameters will adjust the imputed values for observations in the treatment group, not the placebo group, until the p-value > 0.05. Multiple imputation will be used for missing data. Other sensitivity analyses may be performed as appropriate.
Sample 1
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Primary Analysis of Efficacy. The ITT population, which includes all patients randomized within each cohort, will be used as the population for assessment of the primary efficacy endpoint. Mixed-model repeated measures (MMRM) analyses will be used to analyze the Phase 2 and Phase 3 primary and key secondary efficacy endpoints. For the Phase 2 portion of the study, eGFR values for all scheduled visits collected through the Week 12 visit will contribute to the primary analysis. For the Phase 3 portion of the study, eGFR values for all scheduled visits collected through the Week 48 visit will contribute to the primary analysis. The dependent variable will be change from baseline in eGFR. The model will include change from baseline in eGFR as the dependent variable, protocol-scheduled nominal time point as a fixed effect, patient as a random effect, and the baseline eGFR and log-transformed baseline ACR as continuous covariates. Within-patient correlations will be modeled using an unstructured covariance structure. Time ordering is a repeated measure within patients. It is assumed that errors for different patients are independent with an unstructured covariance structure. The estimation method for the model will be restricted maximum likelihood (REML). For analysis of the Phase 3 primary endpoint at Week 48, missing data in the ITT population will be imputed using Jump to Reference (J2R) multiple imputation (Ratitch, 2013) based on available data collected from patients discontinuing from study treatment but continuing in the study. Appropriate sensitivity analyses will be performed. The primary analyses of efficacy using an unstructured covariance structure is expected to have approximately the same power as the analysis with compound symmetry used for study planning. The analysis of the Phase 3 key secondary endpoint will be based on available Week 52 data from the subset of patients who complete the 48-week treatment course.
Sample 1

Related to Primary Analysis of Efficacy

  • Data Analysis In the meeting, the analysis that has led the College President to conclude that a reduction- in-force in the FSA at that College may be necessary will be shared. The analysis will include but is not limited to the following: ● Relationship of the FSA to the mission, vision, values, and strategic plan of the College and district ● External requirement for the services provided by the FSA such as accreditation or intergovernmental agreements ● Annual instructional load (as applicable) ● Percentage of annual instructional load taught by Residential Faculty (as applicable) ● Fall 45th-day FTSE inclusive of dual enrollment ● Number of Residential Faculty teaching/working in the FSA ● Number of Residential Faculty whose primary FSA is the FSA being analyzed ● Revenue trends over five years for the FSA including but not limited to tuition and fees ● Expenditure trends over five years for the FSA including but not limited to personnel and capital ● Account balances for any fees accounts within the FSA ● Cost/benefit analysis of reducing all non-Residential Faculty plus one Residential Faculty within the FSA ● An explanation of the problem that reducing the number of faculty in the FSA would solve ● The list of potential Residential Faculty that are at risk of layoff as determined by the Vice Chancellor of Human Resources ● Other relevant information, as requested

  • Statistical Analysis 31 F-tests and t-tests will be used to analyze OV and Quality Acceptance data. The F-test is a 32 comparison of variances to determine if the OV and Quality Acceptance population variances 33 are equal. The t-test is a comparison of means to determine if the OV and Quality Acceptance 34 population means are equal. In addition to these two types of analyses, independent verification 35 and observation verification will also be used to validate the Quality Acceptance test results.

  • Drug Test Results Client certifies that it understands that various states impose requirements and/or restrictions on employers intending to obtain or use drug testing results.For example, Minnesota only allows employers to conduct drug testing in certain situations and further requires that certain notices be provided.Client certifies that it will comply with any and all legal requirements or restrictions pertaining to its acquisition or use of drug test results received fromSapphire Check.

  • Study An application for leave of absence for professional study must be supported by a written statement indicating what study or research is to be undertaken, or, if applicable, what subjects are to be studied and at what institutions.

  • Study Population The study was based at the San Francisco KPNC Anal Cancer Screening Clinic. We enrolled men who were identified as positive for HIV through the Kaiser HIV registry, who were aged ≥ 18 years, who were not diag- nosed with anal cancer before enrollment, and who pro- vided informed consent. In total, 363 men were enrolled between August 2009 and June 2010. The study was reviewed and approved by the institutional review boards at KPNC and at the National Cancer Institute. All partici- pants were asked to complete a self-administered ques- tionnaire to collect risk factor information. Additional information regarding HIV status and medication, sexu- ally transmitted diseases, and histopathology results were abstracted from the KPNC clinical database. For 87 of the 271 subjects without biopsy-proven AIN2 or AIN3 at the time of enrollment, follow-up infor- mation concerning outcomes from additional clinic visits up to December 2011 was available and included in the analysis to correct for the possible imperfect sensitivity of high-resolution anoscopy (HRA).13,15 Clinical Examination, Evaluation, and Results During the clinical examination, 2 specimens were col- lected by inserting a wet flocked nylon swab16 into the anal canal up to the distal rectal vault and withdrawing with rotation and lateral pressure. Both specimens were trans- ferred to PreservCyt medium (Hologic, Bedford, Mass). A third specimen was collected for routine testing for Chla- mydia trachomatis and Neisseria gonorrhea. After specimen collection, participants underwent a digital anorectal ex- amination followed by HRA. All lesions that appeared sus- picious on HRA were biopsied and sent for routine histopathological review by KPNC pathologists, and were subsequently graded as condyloma or AIN1 through AIN3. No cancers were observed in this study population. From the first specimen, a ThinPrep slide (Hologic) was prepared for routine Xxxxxxxxxxxx staining and xxxxx- xxxxx. Two pathologists (T.D. and D.T.) reviewed the slides independently. Cytology results were reported anal- ogous to the Bethesda classification17 for cervical cytology except when otherwise noted. The following categories were used: negative for intraepithelial lesion or malig- xxxxx (NILM); ASC-US; atypical squamous cells cannot rule out high-grade squamous intraepithelial lesion (HSIL) (ASC-H); low-grade squamous intraepithelial lesion (LSIL); HSIL, favor AIN2 (HSIL-AIN2); and HSIL-AIN3. ASC-H, HSIL-AIN2, and HSIL-AIN3 were combined into a single high-grade cytology category for the current analysis. Biomarker Testing Using the residual specimen from the first collection, mtm Laboratories AG (Heidelberg, Germany) performed the p16INK4a/Ki-67 dual immunostaining (‘‘p16/Ki-67 staining’’) using their CINtec Plus cytology kit according to their specifications. A ThinPrep 2000 processor (Holo- gic) was used to prepare a slide, which then was stained according to the manufacturer’s instructions. The CINtec Plus cytology kit was then applied to the unstained cytol- ogy slide for p16/Ki-67 staining. On the second collected specimen, Roche Molecular Systems (Pleasanton, Calif) tested for HR-HPV, includ- ing separate detection of HPV-16, and HPV-18 DNA, using their cobas 4800 HPV test. To prepare DNA for the cobas test, automated sample extraction was per- formed as follows: 500 lL of the PreservCyt specimen was pipetted into a secondary tube (Falcon 5-mL polypropyl- ene round-bottom tube, which measured 12-mm-by-75- mm and was nonpyrogenic and sterile). The tube was capped, mixed by vortexing, uncapped, placed on the x-480 specimen rack, and loaded onto the x-480 sample extraction module of the cobas 4800 system. The x-480 extraction module then inputs 400 lL of this material into the specimen preparation process. The extracted DNA was then tested as previously described.16 NorChip AS (Klokkarstua, Norway) also tested the second specimen for HPV-16, -18, -31, -33, and -45 HPV E6/E7 mRNA using their PreTect HPV-Proofer assay according to their specifications. All testing was per- formed masked to the results of the other assays, clinical outcomes, and patient characteristics.

  • SAMPLE 3.1 (If applicable and the project has specifications, insert the specifications into this section.)

  • DATA COLLECTION AND ANALYSIS The goal of this task is to collect operational data from the project, to analyze that data for economic and environmental impacts, and to include the data and analysis in the Final Report. Formulas will be provided for calculations. A Final Report data collection template will be provided by the Energy Commission. The Recipient shall: • Develop data collection test plan. • Troubleshoot any issues identified. • Collect data, information, and analysis and develop a Final Report which includes: o Total gross project costs. o Length of time from award of bus(es) to project completion. o Fuel usage before and after the project.

  • Protocol The attached Protocol shall be an integral part of this Agreement.

  • Statistical Sampling Documentation a. A copy of the printout of the random numbers generated by the “Random Numbers” function of the statistical sampling software used by the IRO.

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