In the subject data listing all available data, including partial data, will be presented as they are recorded on the case report forms (CRFs). Time to event or duration of event endpoints will be calculated based on the study day of the event date (or censoring da te) rather than visit number or visit label. Missing efficacy or safety data will not be imp uted unless otherwise specified. 7.2.1 Partial Dates for Adverse Events For adverse events (AEs) with partially missing start dates , it’s necessary to impute an AE start date to define TEAE . For the partial date of AE start date (missing day and/or month and/or year) , the following imputation rules will be applied: • If year of the AE start date is missing , no date imputation will be made and the AE will not be consi dered treatment -emergent unless the investigator has deemed it to be treatment -related. • If both day and month of the AE start date are missing but year is known, the day and month will be imputed with the day and month of the first study dose date if the year is equal to the year of first dose. Otherwise, the month and day is imputed as the first day of the year (01 Jan). • If only day is missing, and if the year and month are equal to the first dose date, the day will be imputed as day of the first dose date. Otherwise, the day will be imputed as “01.” Partial AE end dates will be imputed for non- ongoing AEs as follows: • If year of the AE end date is missing , no date imputation will be made. • If both day and month of the AE end date are missing but year is known, the date of the last dose of study drug will be used as the end date of the AE. Otherwise, December 31 will be used as the end of the AE. • If only day is missing, the date of last dose of study drug will be used as the end date of the AE. Otherwise, the last day of the month will be used as the end of the AE. 7.2.2 Partial Dates for Concomitant Medication For c oncomitant medications (CM) with incomplete dates, imputation will be used to convert to a complete date. Imputed dates will b e used to determine Study Day. Partial medication start dates will be imputed as follows: 05FPRF Immune Design Corp. I MDZ -04-1702 SAP Draft V1.0 for Protocol V2.0 Version Date: 2018- 05-25 Confidential 25 / 36 • If year of the CM start date is missing, no date imputation will be made. • If both day and month of the CM start date are missing but year is known, the day and month will be imputed with the day and month of the first study dose date if the year is equal to the year of first dose. Otherwise, the month and day is imputed as the first day of the year (01 Jan). • If only day is missing, and if the year and month are equal to the first dose date, the day will be imputed as day of the first dose date. Otherwise, the day will be imputed as “01.” Partial medication end dates will be imputed for non -ongoing medications as follows: • If year of the CM end date is missing, no date imputation will be made. • If both day and month of the CM end date are missing but year is known, the date of the last dose of study drug will be used as the end date of the medication. Otherwise, December 31 will be used as the end of the medication. • If only day is missing , the date of last dose of study drug will be used as the end date of the medication. Otherwise, the last day of the month will be used as the end of the medication. 7.3 Multiplicit y The study is to be conducted with PFS and OS as 2 primary endpoints with the goal of a regulatory approval based on either PFS or OS. The overall type I error probability is specified to be 1-sided 0.025 with success for either of the 2 primary endpoint s defining study success using the Bonferroni method to specify that each endpoint will be evaluated using a type I error probability of 1- sided 0.0125 in order to protect the overall type I error. In case both final PFS analysis and final OS analysis hav e 1-sided 0.0125≤ p<0.025, or one of the analyses has 1 -sided 0.0125≤p<0.025 w hile the other has 1-sided p<0.0125, the overall type I error will be controlled at 1-sided 0.025 with statistical significance applied to both PFS and OS analyses using the Hochberg method. 7.4 Interim Analyses and Data Monitoring A data monitoring committee will be established with the responsibility of safeguarding the interest of study subjects and maintaining the overall integrity of the study. The DMC will review safety dat a periodically during the study as described under Section 8.17 (Data Monitoring Committee) of the protocol and will evaluate the results of final PFS analysis and a planned interim OS analysis to assess futility with the possibility of a recommendation fo r stopping the study early because of futility. The OS non- binding futility boundary is set to be HR = 1.0. It will be conducted at 67% of information time (120th death event from the 179 required death events for final OS analysis). If deemed necessary by the DMC, unblinded data may be reviewed on a case- by-case basis. The sponsor will remain blinded to study treatment until either 05FPRF Immune Design Corp. I MDZ -04-1702 SAP Draft V1.0 for Protocol V2.0 Version Date: 2018- 05-25 Confidential 26 / 36 1 of the 2 primary endpoints is met or until the study has been stopped early. Details of DMC function will be governed by a D MC Charter developed by the sponsor and accepted by DMC members. 8 STATISTICAL ANALYSIS 8.1 Study Population 8.1.1 Subject Disposition Subject disposition and the incidence of study discontinuation (and reason for discontinuation) will be tabulated for all enrolled pa tients by treatment arm. The information will be summarized as follows for subject disposition per treatment arm and overall :  Subject Status ( Prime Phase [Day 1 to 92] , Boost Phase [Day 92 up to Day 365], Post Treatment Period [Last dose to PD] , and Long Term Follow -up [PD to end of study] )  Treatment Completed  Primary Reason f or Treatment Discontinuation (as reported on CRF)  Study Completed  Primary Reason f or Study Discontinuation (as reported on CRF) At the same time, the number and percentage of subjects in each analysis set and reason for excluding from the specified analysis set will also be tabulated . Listing s will be presented for data relevant to subject disposition. 8.1.2 Prot ocol Deviations The clinical study team will define CSR reportable protocol deviation and major protocol deviation to be excluded from efficacy evaluable set. They clinical team will have quarterly review of all potential CSR reportable and major protocol deviations during study conduct and prior to database lock. CSR reportable and major protocol deviations will be categorized by deviation type. The subject incidence of CSR reportable protocol deviation (IPD) will be summarized by deviatio n type based on safety set . A listing will be provided for all protocol deviations . 8.1.3 Demograph ic and Baseline Characteristics All demographics and baseline characteristic variables will be summarized by treatment arm and overall for ITT set. 05FPRF Immune Design Corp. I MDZ -04-1702 SAP Draft V1.0 for Protocol V2.0 Version Date: 2018- 05-25 Confidential 27 / 36  Demographic and baseline characteristics data, incl uding age (continuous and grouped as <65, or ≥65 years) , sex, childbearing potential , race, ethnicity, weight, height , BMI and ECOG will be summarized.  Disease history and characteristics wi ll be summarized and include: o Time from Initial Diagnosis (month) [(date of randomization – date of i nitial diagnosis + 1 )/30.4375] o TNM separated stage at initial diagnosis o AJCC stage at initial diagnosis o Grade (French or FNCLCC) at initial diagnosis o t(X;18) T ranslocation o BCOR 6 P resent o Tumor Monophasic or Biphasic o Any Prior Cancer Related Treatment (Yes, No) o Any Prior Cancer Related Surgery (Yes, No) o Type of prior therapy (adjuvant /neoadjuvant chemotherapy and surgery and/or radiotherapy ) o First-Line systemic anti- cancer therapy (regimen, number of cycles, type, best response, total dose) 8.2 Efficacy Analyses The efficacy analysis will be performed based on ITT set and supportive analysis will be performed based on EE set . For PFS and ORR, primary analyses will be performed for the scan results determined by the investigator assessment, scan results by independent radiological review (IRC) , if required, wi ll be the supportive analysis . 8.2.1 Analytic Standard 8.2.1.1 Data Cutoff Date Associated with each analysis is a data cutoff date. The key analyses will use the data cutoff date to censor event dates, and this may result in an event date turning into a censored date. Additional sensitivity analyses without data cutoff censoring will also be done when there has been data cutoff censoring, especially when data cutoff censoring results in loss of events. 05FPRF Immune Design Corp. I MDZ -04-1702 SAP Draft V1.0 for Protocol V2.0 Version Date: 2018- 05-25 Confidential 28 / 36 8.2.1.2 Assessing Clinical Site Homogeneity It is important to assess clinical site homogeneity with respect to the primary and secondary outcomes. Following is the method that will be used to obtain a descriptive assessment of clinical site homogeneity . Assume each clinical site is identified by a unique code. It i s often the case that one or more clinical sites will fail to have at least one subject assigned to each arm. All such clinical sites are to be pooled into a new pseudo clinical site with a new unique code. This new pseudo clinical site is to be used in the following analyses. A forest graph with sites or a grouping of sites will be created where the effect estimate will be displayed along with the 95% confidence interval. This graph is most effectively displayed if the estimates are sorted by estimate size . 8.2.2 Analysis of Primary Efficacy Variables 8.2.2.1 Primary Analys es The null hypothesis of no difference in PFS /OS between CMB305 and placebo, in the ITT set, will be tested using a stratified log -rank test stratified by randomized stratification factors : disease status at screening (locally advanced unresectable versus metastatic), tumor response during screening (PR/SD versus CR/ NED), and by baseline presence of anti -NY-ESO -1 antibody (yes versus no)). The null hypothesis will be rejected and it will be concluded that PFS /OS on CMB305 is superior to that on placebo if the 1 -sided p value at the final analysis for the stratified log -rank test is less than the pre -specified alpha as discussed in Multiplicity Se ction. Success for either of the 2 primary endpoints defines study success. The Kaplan -Meier curve will summarize PFS /OS graphically by treatment arm. Tabular summaries of the Kaplan -Meier curves, incl uding the median and 2- side 97.5% and 95% CI will be provided by treatment arm. The 4, 6, 8, and 10 month PFS rate and 12, 18 , 24, and 30 month OS rate will be provided by treatment arm . The associated HR and its 2 -sided 97.5% and 95% CI will be provided using the stratifie d Cox proportional hazard model for PFS /OS, comparing treatment arm, stratified by the randomized stratification factors . The final PFS analysis will be conducted when a total of 141 PFS events occur. The final OS analysis will be conducted when a total of 179 deaths occur. 8.2.2.2 Sensitive Analysis of Primary Endpoints (PFS/OS) The sensitive analys es of primary endpoints will include : • OS using the Safety set, according to the treated arm 05FPRF Immune Design Corp. I MDZ -04-1702 SAP Draft V1.0 for Protocol V2.0 Version Date: 2018- 05-25 Confidential 29 / 36 • PFS by investigator assessment and OS using the EE set • PFS by investigator assessment in the ITT set , with start of subsequent anti -cancer therapy as a PFS event • PFS based on the IRC response assessment , if required, for both ITT and EE set s as supportive analysis • Stratified Cox proportional hazard model for PFS or OS , in ITT set, with additional covariates of number of cycles in first line chemotherapy , and /or type o f prior therapy (adjuvant/ neoadjuvant chemotherapy and surgery and/or radiotherapy ) • PFS and OS by Fleming -Harrington weighted log -rank test with ρ =0, γ =1, for adjustment of delayed effects. • The Fleming -Harrington weight for late effects is defined as below Wn(t)= (S n(t))ρ(1- Sn(t))γ • PFS and OS by p iecewise Cox proportional model in presence of non- proportional hazard for time -varying treatment effect : () ()()() ( ) 1 12 22 1 32 1 | ( ) exp 1 1 1i o i i i ii i i i h t h t z z tc z c tc z tc αβ β β++Ζ= + ≤ + <≤ + > Where Z 1j is time -independent covariates such as stratification factors ; Ci and Ci+1 are cut point s (e.g. 4 and 8 months, respectively) for time period and 1(.) denotes the indicator function.