Statistical considerations
TTD
REGRESSION, EVENTS, EVENT
The primary endpoint is time to deterioration (TTD) of quality of life (QoL), based on the FACT-G instrument total score. This time is defined as the interval from registration until a DQoL (deterioration of quality of life) event, determined using the FACT-G scale (or censoring). Measurements are taken at day 1 of each 28-day treatment cycle in both arms. The event “deterioration of quality of life (DQoL)” is defined as any decrease of 10 or more points from baseline unless a recovery is achieved in the subsequent assessment. A recovery is defined as a QoL score no worse than 9 points below baseline. If data of the subsequent visit is missing, a decrease of 10 or more points will be considered as an event. The study tests the hypothesis of superiority of TTD in patients supported by eHealth therapy management in arm A compared to arm B.Sample size was estimated as follows: the superiority hypothesis test for DQoL is based on the stratified score function test of a Cox regression model with Breslow likelihood, including therapy line stratum as covariate. Assuming a (constant) hazard ratio of 0.8 for TTD in arm A vs. arm B, the study is designed to refute the null hypothesis of equal survivor functions between arm A and arm B at a two-sided 5% significance level [Patients in the strata defined above are referred to here as “first-line” and “later-line” patients. First-line patients are assumed to comprise about 5/8 (62.5%) of the entire trial population; the remaining patients (3/8, i.e., 37.5%) are assumed to be treated in later lines. In first-line patients, the proposed hazard ratio between CANKADO arms of 0.8 corresponds to about 4 months superior TTD for CANKADO active; in later-line patients, it corresponds to about 2 months superior TTD. Such an increase is assumed to have a clinically relevant benefit.To estimate a During the conduct of the study no interim analysis is planned.The primary analysis implements the intent-to-treat principle (ITT). Primary reporting is based on the ITT population of all randomized patients, including patients with protocol violations and intercurrent events, handled by a while-on-treatment strategy. An additional sensitivity analysis will be carried out based on a per-protocol population excluding patients with major protocol violations (to be determined during data review prior to database lock based on prospectively defined criteria). For the primary analysis, missing values are treated as missing-at-random by therapy line and treatment arm strata. Patient information entering the analysis will be either time of censoring (e.g., administrative censoring or intercurrent event) or the actual event time.The sample size was estimated using a validated Monte-Carlo simulation implemented in Python 3.5. In all 4 groups (2 arms with 2 strata each), exponential survival was used as parametric sampling distribution with hazard rate computed from median PFS estimates as indicated above. In addition, an independent exponential censoring process was used to simulate loss to follow-up with 48-month probability of censoring calibrated at 10%.If 960 patients are recruited (assuming 10% loss to follow-up), we can expect to reject the null-hypothesis with 80% power if a stratified two-sided test of equal hazards between (CANKADO active) and (CANKADO inform) is performed at alpha = 0.05. The corresponding expected number of events across groups is 693.For each stratum and arm, Kaplan–Meier product-limit estimators of the survivor functions together with Hall-Wellner confidence bands will be reported and visualized graphically. In addition, corresponding median TTD with log-transformed 95% confidence will be reported.Secondary endpoints include a definition of TTD of QoL as minimally important difference (5-point drop from baseline on FACT-G scale) to provide a sensitivity analysis with respect to the primary endpoint, progression-free survival and overall survival as clinical outcomes, as well as ePRO measurements of global health status and FACT-B scales. Translational research questions will focus on the influence of genetic and immune biomarker profiles on clinical outcome.