Statistical Methodology

Overtime, NJS has provided below expert statistical consulting for clients. 

Oncology Trial Design

  • Adaptive Group Sequential Design with application to seamless phase IIB and Phase III combination study
  • Adaptive Multi-stage Adaptive Design toxicity monitoring critical value
  • Adaptive Randomization
  • Sample size re-estimation
  • Bayesian Hierarchical Model
  • IPE Method, RPSFT and IPCW
  • Pick Winner Design (Biomarker Guided)
  • Oncology Trial Design Simulator (sample size/power calculation and simulation)
  • 3×3 Design Probabilities simulation and Bayesian CRM modeling/mTPI/BOIN
  • Comparing dose-response shapes, e.g., linear, logistic, Emax, sigmoid Emax, exponential, etc
  • Modified MSPRT for post-approval safety monitoring study

Trial Monitoring Tool

  • Event Trial duration Projection (parametric, non-parametric, bootstrapping)
  • Advanced Survival Analysis Models:
  • Multiple methods for estimating true OS effect from treatment crossover data (Robin’s RPSFT, 2-dimension RPSFT, IPCW, etc.)
  • Bootstrapping projecting Future Efficacy Distribution of P-values and Hazard ratios
  • Conditional and Predictive Power Calculation
  • Efficacy P-value vs. Time, hazard ratio vs. time (Landmark Analysis)
  • Survival Model Distribution Validation and Testing
  • Nonproportional hazard survival model
  • PFS and OS joint distribution modeling.

Quality of Life Analysis for Oncology trials

  • Fit pattern mixture model Qol data with non-ignoble missing (missing not at random, MNAR) due to dropout.
  • Use the worst rank method to handle missing QoL scores due to informed dropouts as an alternative to the pattern mixture model.

Other

  • Koch randomization based nonparametric methods for time to failure outcomes in multi-center trials
  • Multiplicity adjusted confidence intervals for many to one comparison
  • Overall multiplicity adjusted p-values
  • Bayesian Statistical Prediction for Accelerated Submission (Device)
  • Expectation–maximization (EM) algorithms
  • Bayesian Classification and regression tree methods
  • Statistical comparison using Virtual-Matched Historical Data
  • Control using Virtual-Matched Historical Data
  • Sequential Parallel Comparison Design (SPCD)
  • Randomized Withdrawal Design
  • Randomized Delayed Start Design