Clinical Trials
Everything on Aqrab tagged Clinical Trials — grouped into one landing page so readers can go deeper by problem family instead of bouncing around the archive blind.
The Hazard-Ratio Autopsy: When Delayed Effects Make One Number Misleading
A practical trial autopsy for non-proportional hazards. Read the curves, risk sets, landmarks, and restricted mean survival time before translating one hazard ratio into a constant treatment effect.
Hierarchical Testing in Clinical Trials: When a Significant Secondary Endpoint Is Still Descriptive
A practical hierarchical testing guide for clinical researchers. Reconstruct the prespecified testing path before treating a small p-value on a secondary endpoint as confirmatory evidence.
Randomized Withdrawal Trials: Why a Relapse-Prevention Win Is Not a New-Patient Effect
A practical randomized withdrawal trial guide for clinical researchers. Audit the run-in, responder enrichment, withdrawal contrast, safety, and target population before generalizing a maintenance-effect claim.
Allocation Concealment: The Randomized-Trial Safeguard That Works Before Assignment
A practical allocation concealment guide for clinical researchers and peer reviewers. Separate sequence generation, concealment, implementation, and blinding before trusting the word randomized.
Cluster-Trial Recruitment Bias: When the Clinic Knows the Assignment Before the Patient Enters
A practical guide to post-randomization recruitment bias in cluster trials. Audit timing, allocation awareness, eligibility, consent, patient denominators, and the limits of statistical adjustment.
Modified Intention-to-Treat: When Randomization Starts Losing Patients After the Fact
A practical guide to modified intention-to-treat analyses for clinical researchers. Learn how post-randomization exclusions weaken trial credibility, when exclusions may be defensible, and what reviewers should demand before trusting a modified analysis population.
Crossover Trials: When Every Patient Is Their Own Control—and Their Own Carryover Problem
A practical guide to crossover trials for clinical researchers. Audit treatment reversibility, washout, carryover, period effects, sequence, dropout, and paired analysis before trusting an efficient within-patient comparison.
Estimands in Meta-Analysis: When a Shared PICO Still Pools Different Questions
A practical guide to estimands in meta-analysis. Learn how treatment-policy and hypothetical strategies can make trials with the same PICO answer different questions, and how to audit the pool before combining effects.
Recurrent Events in Clinical Trials: When Time to First Event Hides Disease Burden
A practical guide to recurrent-event analysis in clinical trials. Learn when time to first event discards patient burden, how death changes the estimand, and what reviewers should demand.
Co-Intervention Bias: When the Treatment Arm Gets More Than the Treatment
A practical co-intervention bias guide for clinical trial reviewers. Learn when unequal concomitant care distorts a treatment claim, belongs to the strategy, or changes the estimand.
Multi-State Models: When One Time-to-Event Endpoint Hides the Clinical Path
A practical multi-state models guide for clinical researchers. Learn how state occupation, transition hazards, and time in state reveal clinical paths hidden by one survival endpoint.
Endpoint Adjudication: When a Blinded Committee Cannot Rescue Biased Event Capture
A practical endpoint adjudication guide for clinical researchers. Learn why blinded central review cannot repair unequal event capture, incomplete evidence dossiers, or post hoc endpoint rules.
Desirability of Outcome Ranking: When Benefit–Risk Depends on Who Ranks the Outcomes
A practical guide to desirability of outcome ranking (DOOR) in clinical trials. Learn how whole-patient outcome ranks encode benefit–risk judgments, how to interpret DOOR probability, and what reviewers should demand before trusting one summary number.
CONSORT 2025 for Reviewers: A Practical Checklist for Interpretable Trials
A practical CONSORT 2025 reviewer checklist for randomized trials. Find the reporting gaps that change what you can infer about allocation, treatment, outcomes, missing data, and analysis.
Small Number of Clusters: When 500 Patients Still Behave Like 10 Sites
A practical guide to inference with a small number of clusters in clinical research. Learn why patients inside the same site are not independent evidence, why default cluster-robust standard errors can be too optimistic, and what reviewers should demand before trusting a cluster-level result.
Bayesian Borrowing: When Historical Data Starts Spending Credibility It Did Not Earn
A practical guide to Bayesian borrowing for clinical researchers. Covers exchangeability, commensurate priors, historical controls, calendar-time drift, and what reviewers should demand before trusting extra certainty borrowed from earlier data.
Informative Cluster Size: When the Biggest Sites Start Writing the Result
A practical guide to informative cluster size for clinical researchers. Covers why larger centers can quietly dominate treatment effects, how weighting changes the estimand, and what reviewers should demand before trusting clustered results.
Baseline Adjustment in Randomized Trials: Why Change From Baseline Keeps Losing to ANCOVA
A practical guide to baseline adjustment in randomized trials. Covers ANCOVA versus change scores, percent change traps, responder thresholds, and what reviewers should demand before trusting a tidy efficacy claim.
Complete-Case Analysis: When Missing Data Quietly Changes the Study Population
A practical guide to complete-case analysis for clinical researchers. Covers when dropping incomplete records changes the study population, how endpoint missingness becomes selection bias, and what reviewers should demand before trusting the estimate.
Platform Trials: When a Shared Control Stops Being the Same Comparison
A practical guide to platform trials for clinical researchers. Covers nonconcurrent controls, changing standard of care, case-mix drift, and what reviewers should demand before trusting an adaptive-trial headline.
Nonproportional Hazards: When One Hazard Ratio Pretends the Treatment Effect Never Changes
A practical guide to nonproportional hazards for clinical researchers. Covers delayed effects, crossing curves, waning benefit, why one hazard ratio can mislead, and what reviewers should demand instead.
Futility Stopping in Clinical Trials: When “No Signal Yet” Starts Pretending the Question Is Answered
A practical guide to futility stopping in clinical trials. Covers conditional power, delayed effects, optimistic design assumptions, and what reviewers should demand before trusting a trial stopped for futility.
Noninferiority Margins: When “Not Much Worse” Starts Giving Away Too Much
A practical guide to noninferiority margins for clinical researchers. Covers margin justification, assay sensitivity, constancy, biocreep, and what reviewers should demand before trusting a noninferiority win.
Win Ratio: When a Hierarchical Composite Endpoint Sounds Harder Than It Really Is
A practical guide to win ratio for clinical researchers. Covers hierarchical composite endpoints, pairwise priorities, soft-tier distortion, and what reviewers should demand before trusting a prioritized endpoint headline.
Stepped-Wedge Cluster Trials: When Rollout Timing Starts Competing With the Intervention
A practical guide to stepped-wedge cluster trials for clinical researchers. Covers secular trends, rollout order, learning effects, contamination, and what reviewers should demand before trusting a tidy implementation-era benefit.
Response-Adaptive Randomization: When a Trial Starts Chasing Its Early Winners
A practical guide to response-adaptive randomization for clinical researchers. Covers delayed outcomes, temporal drift, instability, ethical claims, and what reviewers should demand before trusting an adaptive allocation design.
Adaptive Enrichment Trials: When Precision for One Subgroup Pretends to Be Evidence for Everyone
A practical guide to adaptive enrichment trials for clinical researchers. Covers predictive versus prognostic enrichment, assay timing, multiplicity, external validity, and what reviewers should demand before trusting a biomarker-selected win.
Surrogate Endpoints: When a Biomarker Improvement Pretends to Be Patient Benefit
A practical guide to surrogate endpoints for clinical researchers. Covers validated versus merely plausible surrogates, classic failure modes, and what reviewers should demand before trusting a biomarker-driven trial claim.
Jump-to-Reference Imputation: When Missing Outcomes Start Borrowing the Control Arm's Future
A practical guide to jump-to-reference imputation for clinical researchers. Covers what J2R assumes after treatment discontinuation, when it helps sensitivity analysis, and when it quietly answers the wrong estimand.
Fragility Index: When One or Two Events Carry More Confidence Than They Should
A practical guide to the fragility index for clinical researchers. Covers event-flip sensitivity, loss to follow-up, effect-size context, and what reviewers should demand before trusting a barely significant trial.
Multiple Testing in Clinical Trials: When One Positive Endpoint Is Just the Loudest Coin Flip
A practical guide to multiple testing in clinical trials for clinical researchers. Covers endpoint families, subgroup fishing, interim looks, alpha control, and what reviewers should demand before trusting a lone positive result.
Intercurrent Events in Clinical Trials: When Rescue Therapy and Death Are Not Missing Data
A practical guide to intercurrent events for clinical researchers. Covers rescue therapy, treatment switching, discontinuation, death, estimand strategy choices, and what reviewers should demand before trusting the headline effect.
Last Observation Carried Forward: When Yesterday's Outcome Pretends the Patient Stopped Changing
A practical guide to last observation carried forward for clinical researchers. Covers why LOCF fails as missing-data strategy, how it can exaggerate or dilute treatment effects, and what reviewers should demand instead.
Early Stopping for Benefit: When a Trial Quits While the Effect Is Still on Its Best Behavior
A practical guide to early stopping for benefit in clinical trials. Covers interim looks, alpha spending, exaggerated effect sizes, immature follow-up, and what reviewers should demand before trusting a triumphant stop.
External Control Arms: When a Comparison Group Arrives from Another Universe
A practical guide to external control arms for clinical researchers. Covers historical and real-world comparators, design drift, prognostic imbalance, endpoint mismatch, and what reviewers should demand before trusting single-arm success stories.
Treatment Switching in Oncology Trials: When Overall Survival Becomes a Rescue Protocol Audit
A practical guide to treatment switching in oncology trials for clinical researchers. Covers crossover, overall survival dilution, ITT versus hypothetical estimands, RPSFTM, IPCW, two-stage estimation, and what reviewers should demand before trusting an adjusted survival claim.
Run-In Periods: When Your Trial Randomizes the Easy Patients First
A practical guide to run-in periods for clinical researchers. Covers adherence enrichment, tolerability selection, estimand drift, external validity, and what reviewers should demand before trusting a polished randomized cohort.
Responder Analyses: When a Cutoff Turns a Clinical Gradient into a Headline
A practical guide to responder analyses for clinical researchers. Covers dichotomizing continuous outcomes, post hoc thresholds, baseline dependence, power loss, and what reviewers should demand before trusting "X% achieved response" claims.
Outcome Switching: When the Primary Endpoint Moves After the Results Get Interesting
A practical guide to outcome switching for clinical researchers. Covers endpoint shopping, selective reporting, protocol drift, and what reviewers should demand before trusting a late-breaking primary outcome.
Composite Endpoints: When One Trial Outcome Quietly Becomes Four Different Clinical Questions
A practical guide to composite endpoints for clinical researchers. Covers when endpoint bundles improve efficiency, when they distort clinical meaning, how soft components hijack results, and what reviewers should demand before trusting the headline.
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