Oncology KB — Wiki Index
FDA Concept Articles
| Article | Description |
|---|---|
| Oncology Endpoint Overview | FDA recognizes two broad categories of endpoints for cancer drug approval: |
| Overall Survival (OS) | OS is a time-to-event endpoint. The event is all-cause death. Patients alive at the data cutoff are censored at their la… |
| Progression-Free Survival (PFS) | PFS is a time-to-event composite: the event is the earlier of documented objective disease progression per pre-specified… |
| Response-Based Endpoints (ORR, CR, DOR) | Objective Response Rate (ORR): |
| DFS and EFS Endpoints | Disease-Free Survival (DFS): |
| FDA Approval Pathways in Oncology | FDA offers four primary expedited programs and two standard approval routes for oncology drugs: |
| Multiple Endpoints and Alpha Allocation | Clinical trials often test effects on more than one endpoint. When multiple hypothesis tests are conducted and the trial… |
| Emerging Endpoints in Oncology Trials | Emerging endpoints are clinical trial endpoints that are under active regulatory evaluation but have not yet achieved th… |
| Novel Drug Combination Trial Design | The FDA July 2025 draft guidance on Development of Cancer Drugs for Use in Novel Combinations addresses the fundamenta… |
Estimand / ICH E9(R1)
| Article | Description |
|---|---|
| ICH E9(R1) Estimand Framework | The estimand framework was introduced to align trial planning, design, conduct, analysis, and interpretation. It require… |
| Intercurrent Events in Oncology Trials | Intercurrent events (IEs) differ fundamentally from missing data. The five ICH E9(R1) IE strategies answer different cl… |
| Principal Stratum and While-on-Treatment Strategies | A principal stratum is a subgroup of patients defined by their potential intercurrent event status — not their act… |
| Sensitivity Analyses for Estimands | Sensitivity analysis in the estimand framework serves a specific purpose: to verify that the primary estimator's conclus… |
Indication Articles
| Article | Description |
|---|---|
| NSCLC Indication Guide: FDA Regulatory Endpoints & Trial Design Patterns | Non-small cell lung cancer (NSCLC) encompasses squamous and non-squamous histologies, comprising approximately 85% of al… |
| Breast Cancer Trial Design Patterns: Indication-Specific Statistical Framework | Breast cancer encompasses multiple biologically distinct subtypes defined by hormone receptor (HR) status, HER2 status, … |
| Colorectal Cancer Trial Design Patterns | Colorectal cancer (CRC) encompasses colon and rectal cancers. Phase 3 CRC trial design is stratified by: treatment setti… |
| Melanoma Trial Design Patterns | Melanoma Phase 3 trials are stratified by: disease stage (unresectable/metastatic Stage IV vs. resected Stage III/IV adj… |
| AML Trial Design Patterns | Acute myeloid leukemia (AML) is a heterogeneous hematologic malignancy defined by clonal expansion of myeloid blasts (≥2… |
| Multiple Myeloma Trial Design Patterns | Multiple myeloma (MM) is a plasma cell malignancy characterized by clonal proliferation of plasma cells secreting monocl… |
| Lymphoma Trial Design Patterns | Lymphoma encompasses Hodgkin lymphoma (HL) and non-Hodgkin lymphoma (NHL). NHL is further divided by histology: diffuse … |
| Renal Cell Carcinoma Trial Design Patterns | Renal cell carcinoma (RCC) encompasses clear cell RCC (~75%), papillary RCC (~15%), chromophobe, and rare subtypes. Phas… |
| Ovarian Cancer Trial Design Patterns | Ovarian cancer encompasses epithelial ovarian cancer (EOC, ~90%), fallopian tube cancer, and primary peritoneal cancer —… |
RCT Design Methodologies
| Article | Description |
|---|---|
| RCT Design Fundamentals in Oncology | Foundational randomized controlled trial design principles tailored to oncology drug development, including stratification… |
| Group Sequential Designs (GSD) | Group sequential designs enable interim efficacy and futility analyses with controlled Type I error, allowing for early stop… |
| Adaptive Trial Designs in Oncology | Adaptive designs modify trial conduct during execution based on pre-specified interim data, enabling efficient dose-finding… |
| Master Protocols: Basket, Umbrella, and Platform Trials | Master protocol frameworks facilitate evaluation of multiple drugs, multiple biomarkers, and/or multiple indications under… |
| Biomarker-Enriched Trial Designs | Biomarker enrichment strategies stratify patient populations by genomic or molecular predictors, enabling precision medicin… |
| Non-Inferiority and Equivalence Trial Design | Non-inferiority designs test whether a new treatment preserves a pre-specified fraction of the active control's effect, b… |
| Phase 1/2 Dose-Finding Designs | Dose-finding designs identify the recommended dose through escalation based on toxicity (MTD) or integrated efficacy–toxici… |
Statistical Methods & Analysis
| Article | Description |
|---|---|
| Simulation-Based Power Analysis | Simulation-based power analysis computes operating characteristics (power, type I error, sample size) for complex trial desi… |
| Sample Size Re-estimation (SSR) | Sample size re-estimation permits unblinded review of interim data to recalculate sample size while controlling type I erro… |
| Interim Analysis and DSMB Operations | Interim analyses enable early stopping for efficacy or futility. Data Safety Monitoring Boards (DSMBs) evaluate safety and… |
| Multiplicity Control in Oncology Trials | Multiplicity adjustment methods control family-wise error rate when testing multiple hypotheses (primary, secondary endpoi… |
| Missing Data: Mechanisms, Methods, and Estimand-Driven Strategy | Missing data mechanisms (MCAR, MAR, MNAR) require distinct handling strategies. The estimand framework guides selection o… |
| Statistical Analysis Methods in Oncology Trials | Comprehensive overview of parametric, semiparametric, and nonparametric approaches for analysis of time-to-event (Cox, AFT… |
| Time-to-Event Assumptions and Nonproportional Hazards | Time-to-event analyses assume proportional hazards; violation leads to biased HR estimates and reduced power. Detection and… |
| Longitudinal, PRO, and Repeated-Measures Methods | Mixed-effects models, GEE, and repeated-measures ANOVA handle patient-reported outcomes (PROs) and longitudinal patient-c… |
| Response, Binary, and Disease-Control Endpoint Methods | Methods for binary endpoints (ORR, disease control rate, confirmed response) including logistic regression, risk difference… |
| Sensitivity Analysis Playbook for Oncology Trials | Sensitivity analyses test robustness of primary inferences to assumptions (missing data mechanism, intercurrent event stra… |