Monday, December 29, 2025

FDA guidance "Sponsor Responsibilities - Safety Reporting Requirements and Safety Assessment for IND and Bioavailability/Bioequivalence Studies"

Earlier this month, FDA issued its guidance "Sponsor Responsibilities - Safety Reporting Requirements and Safety Assessment for IND and Bioavailability/Bioequivalence Studies". As an clinical trialist, the updated FDA guidance (or the 2025 guidance) represents a major step forward, primarily by refining the focus on safety assessment and introducing key operational elements.

The 2025 guidance is not a complete rewrite of the 2012 version ("Safety Reporting Requirements for INDs and BA/BE Studies"), but rather a merger of the 2012 guidance content with the principles from the 2015 draft guidance on safety assessment.

Here is a comparison highlighting the key new elements the sponsor must now consider:

Key New Elements in the 2025 Guidance

The most significant change is a shift from focusing solely on individual case safety reports (ICSRs) to a greater emphasis on proactive, systematic safety assessment and the analysis of aggregate data.

New ConceptDescription and Implication for TrialistsRelevant Section in New Guidance 
Focus on Sponsor Responsibilities OnlyThe new guidance is strictly limited to Sponsor Responsibilities for safety reporting. All recommendations for Investigator Responsibilities found in the 2012 guidance have been moved to a separate document, reflecting a clear split in regulatory oversight.Section I, II (Preamble)
Aggregate Data AssessmentThis is the central update. The guidance expands significantly on the requirement to perform regular, proactive aggregate analyses of all accumulating safety data. The goal is to identify new or increased risks that would trigger expedited reporting, rather than relying only on individual case reports.Section III (Definitions) and Section IV (Aggregate Analyses)
Mandatory Safety Surveillance Plan (SSP)The guidance introduces the term Safety Surveillance Plan (SSP) as a systematic and organized approach to safety monitoring. The plan should include: 1) Clearly defined roles and responsibilities; 2) A plan for the regular review and evaluation of Serious Adverse Events (SAEs); and 3) The process for performing aggregate safety reviews.Section IV.C (Safety Surveillance Plan)
Sole Sponsor Causality DeterminationThe guidance emphasizes that the final responsibility for determining whether an event meets the criteria for expedited reporting (i.e., a "Suspected Adverse Reaction," or SUSAR) lies solely with the sponsor. While the sponsor should consider the investigator's opinion, the sponsor is imputed with the ultimate responsibility for the causality judgment for regulatory submission purposes.Section III.B (Suspected Adverse Reaction)
Flexibility in Safety ReviewThe new guidance offers greater flexibility by allowing sponsors to choose which individual, group, or entity (e.g., Safety Monitoring Committee, Data Monitoring Committee) is responsible for reviewing, analyzing, and making decisions regarding IND safety reporting.Section IV.C.1 (Features and Composition of the Entity)

This shift aims to reduce the "noise" of over-reporting uninformative individual adverse events, which was a concern under the old paradigm. Instead, the focus is placed on the sponsor's expert medical review and comprehensive analysis of the overall safety data package.

Here is a side-by-side comparison table summarizing the main discussion points and key changes between the 2012 and 2025 FDA guidance documents on safety reporting.


Safety Reporting Guidance: 2012 vs. 2025 Comparison

Discussion Point2012 Final Guidance: Safety Reporting Requirements for INDs and BA/BE Studies2025 Final Guidance: Sponsor Responsibilities — Safety Reporting Requirements and Safety Assessment for IND and BA/BE Studies
Primary Scope and FocusFocused on procedural requirements for expedited reporting of individual Serious Adverse Events (SAEs).Mandatory emphasis on safety assessment and aggregate data analysis to identify new, significant risks. Merges content with principles from the 2015 draft guidance on safety assessment.
Division of ResponsibilitiesContained recommendations for both Sponsor and Investigator safety reporting responsibilities.Exclusively focuses on Sponsor responsibilities. Investigator reporting recommendations are placed in a separate, concurrently issued guidance document.
Safety Surveillance/PlanningImplicit in the sponsor's duties, but lacked a formalized planning requirement.Introduces the new term "Safety Surveillance Plan (SSP)" to describe a required systematic and organized approach.
Plan Components (SSP)Did not specify formal plan components.Requires the plan to include clearly defined roles and responsibilities, a process for regular review of SAEs, and a process for aggregate safety reviews.
Requirement for ReviewFocused primarily on individual case review to determine if the reporting criteria (Serious, Unexpected, Suspected Adverse Reaction - SUSAR) were met.Explicitly requires sponsors to review and evaluate all accumulating safety data at regular intervals (aggregate review) to update the overall safety profile.
Decision-Making BodyLacked specific recommendations for the structure of the internal safety review process.Offers greater flexibility by allowing the sponsor to choose the individual, group, or entity (e.g., Safety Assessment Committee) responsible for safety reporting and decision-making.
Source of Safety DataFocused mainly on reports from the clinical trial itself.Emphasizes that sponsors must review information from any source (e.g., animal studies, scientific literature, foreign reports, and commercial experience) to identify new significant risks to trial participants.
Expedited Reporting RationaleThe concern was the overreporting of uninformative individual Adverse Events (AEs), which hindered the IRB's ability to focus on true risks.Seeks to reduce overreporting by clarifying that the decision for a 7- or 15-day expedited report must be based on the sponsor's professional judgment of causality (i.e., a reasonable possibility).

Summary of the Shift

The 2025 guidance strongly emphasizes a shift in the regulatory burden from volume-based individual reporting (the 2012 paradigm) to quality-based, comprehensive safety analysis by the sponsor. The overall goal is to enhance patient protection by focusing the FDA, IRBs, and investigators on truly meaningful safety signals derived from cumulative data, rather than individual case reports.

Monday, December 01, 2025

Handling "Median Not Reached": A Guide to Analyzing and Presenting Low Event Rate Survival Data

In the era of highly effective therapies for may diseases, clinical researchers are increasingly encountering a "good" problem in the time to event analyses: the Kaplan-Meier survival curves are flattening out well above the 50% mark. While this represents a triumph for patient outcomes, it creates a headache for statistical reporting. When the event rate is low (below 50%), the Median Time to Event (e.g., Median Overall Survival) and its 95% Confidence Interval (CI) cannot be estimated (often reported as "NE" (not estimable), "NR" (not reached), or "NC" (not calculable)).

So, how do we robustly describe the efficacy of a treatment when the standard metric fails? This post outlines the best-practice alternatives for summarizing, analyzing, and visualizing survival data in low event settings.


1. The Limitation of the Median

The median survival time is simply the time point at which the survival probability drops to 0.50. If the Kaplan-Meier curve plateaus at 70% or 80% because fewer than half the patients experienced the event, the median is mathematically undefined. Reporting it merely as "Not Reached" (NR) is accurate but clinically uninformative—it tells us what the survival is not, but not what it is.

To provide a complete picture, we must pivot to alternative metrics that describe different parts of the survival distribution.

2. Primary Summary Measures

A. Landmark Survival Probabilities

When we cannot answer "When will half the patients die?", we should ask, "What proportion of patients are event-free at time ?"

Landmark analysis reports the Kaplan-Meier survival probability (with 95% CIs) at clinically relevant, fixed timepoints (e.g., 24 weeks, 12 months, 24 months, 5 years).

  • Best Practice: Pre-specify these timepoints in the Statistical Analysis Plan (SAP) to avoid data dredging.

  • Example Reporting: "Event free rate was 93% at week 24 in the treatment group", "The 3-year recurrence-free survival rate was 88.4% (95% CI: 85.1–91.0) in the treatment arm compared to 82.1% (95% CI: 78.4–85.2) in the placebo arm."

B. Lower-Percentile Survival Times (10th and 25th)

Just because the 50th percentile (median) is missing doesn't mean all percentiles are.

  • 25th Percentile: The time at which 25% of patients have experienced the event (or survival drops to 75%).

  • 10th Percentile: The time at which 10% of patients have experienced the event (or survival drops to 90%).

These metrics characterize the "early failures" or the worst-performing subset of the cohort. They are particularly useful for showing that a treatment delays early progression even if the long-term survival is high.

MetricTreatment GroupControl Group
Median (50th)NR (95% CI: NR, NR)NR (95% CI: 36.7, NR)
25th Percentile18.4 months (14.2, 22.1)12.1 months (9.8, 14.5)
10th Percentile5.4 months (4.1, 6.8)3.2 months (2.8, 3.9)

Note: In the table above, while the median is NR for both, the 25th percentile clearly demonstrates a 6-month delay in progression for the treatment group.


3. Robust Analytical Alternatives

A. The "Reverse Kaplan-Meier" Method for Follow-Up

In low event trials, it is critical to prove that the "NR" result is due to drug efficacy, not just because patients left the study early. The Reverse Kaplan-Meier method is the gold standard for calculating median follow-up.

  • How it works: You reverse the censoring indicator (Event = Censored; Censored = Event) and run a standard Kaplan-Meier analysis. The resulting median is the median potential follow-up time.

  • Why use it: Unlike the "median time on study," it is not biased by early deaths or events, providing a true measure of how long the trial centers monitored the patients.

B. Restricted Mean Survival Time (RMST)

RMST is rapidly becoming the preferred alternative to the Hazard Ratio (HR) in low event trials, especially when the Proportional Hazards assumption is violated (e.g., crossing curves).

  • Definition: RMST is the "area under the survival curve" up to a specific time point ($\tau$). It represents the average survival time a patient lives during that window.

  • Reporting: You can report the Difference in RMST (Treatment minus Control) or the Ratio.

  • Interpretation: "Over the 5-year follow-up period, patients on the new therapy lived, on average, 4.2 months longer than those on the control (RMST difference = 4.2 months, p=0.003)."


4. Visualization Best Practices

A. The Kaplan-Meier Plot: Handling the Y-Axis

In trials with very high survival (e.g., >90%), the survival curves may be squeezed into the top 10% of the graph, making it hard to see separation.

  • Line Break (Axis Break): It is acceptable to "break" the y-axis to focus on the relevant range (e.g., from 80% to 100%), provided this is clearly marked.

  • Inverted Plot (Failure Plot): Alternatively, plot the Cumulative Incidence of Events (1 - Survival) on a y-axis ranging from 0% to 20%. This often visualizes the difference in event rates more clearly than a survival curve stuck at the top of the chart.

B. The "Number at Risk" Table

Always include a table below the x-axis aligned with the tick marks. In low event trials, this table reveals whether the "flat tail" of the curve is based on hundreds of patients or just a few who haven't been followed long enough.


5. Optional Exploratory Methods

If pre-specified in the protocol, Parametric Modeling can be used to estimate the median survival even if it hasn't been reached observed data.

  • Weibull Distribution: By fitting a Weibull model to the observed data, you can extrapolate the curve to predict when the median would be reached, assuming the risk profile remains constant.

  • Caution: This is a prediction, not an observation. It should be labeled clearly as "Estimated Median (Parametric)" and treated as exploratory evidence.

Summary Checklist for Reporting Low Event Data

  1. State clearly that the median is NE/NR.

  2. Report Landmark Rates (e.g., 3-year survival) with CIs.

  3. Report Lower Percentiles (25th, 10th) to show early separation.

  4. Use RMST to quantify the average time gained.

  5. Calculate Follow-up using the Reverse Kaplan-Meier method.

  6. Adjust Plots (zoom/break y-axis) to make differences visible, but keep the full context clear.

                                                          Note: AI-assisted writing for this blog article.