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    Lost to Follow-up

    Subjects whose outcome data are missing because they did not complete planned visits.

    Reviewed by Christian Espinosa, Founder, Blue Goat CyberLast reviewed May 5, 2026

    Definition

    Loss to follow-up reduces power, biases estimates if non-random, and is a leading reason for clinical-trial credibility concerns. Sponsors should pre-specify thresholds, sensitivity analyses, and retention strategies.
    What the regulation says
    Regulators emphasize the importance of minimizing lost to follow-up (LTFU) in clinical trials, as outlined in documents like the FDA's guidance on "E10 Clinical Development for Drugs Attenuating Progressive Neurodegenerative Diseases" which discusses trial integrity. They expect sponsors to implement robust strategies to maximize participant retention and to transparently report on LTFU rates and their potential impact on study results, as described in ICH E9 (R1) statistical principles for clinical trials. The EU MDR also implicitly requires adequate follow-up in post-market clinical follow-up (PMCF) studies to ensure continued safety and performance assessment of Medical Devices.

    What this means in practice

    Long-term implant studies and digital therapeutic trials are particularly prone to LTFU; remote follow-up models can mitigate but introduce data-quality questions.

    Examples

    • A sponsor of a long-term orthopedic implant study develops a detailed patient retention plan, including regular communication, travel assistance, and flexible follow-up options, to minimize lost to follow-up over a 10-year period.
    • During a clinical trial for a novel digital therapeutic, the sponsor conducts an interim analysis and discovers a higher-than-expected lost to follow-up rate, prompting an immediate review and adjustment of patient engagement strategies.
    • A post-market clinical follow-up (PMCF) study for a cardiovascular device accounts for potential lost to follow-up by over-enrolling participants, ensuring sufficient data remain for robust analysis even with anticipated attrition.
    Common pitfalls
    • •Failing to document and justify the chosen LTFU thresholds can lead to regulatory scrutiny.
    • •Assuming LTFU is always missing completely at random (MCAR) without conducting appropriate sensitivity analyses is a common statistical error.
    • •Not having a pre-specified plan for handling missing data due to LTFU can result in biased study conclusions.
    • •Overlooking the impact of LTFU on the statistical power of the study can lead to underpowered trials.
    • •Neglecting to implement specific retention strategies tailored to the study population and device type increases the risk of high LTFU rates.

    Frequently asked questions

    The primary regulatory concern is the potential for LTFU to introduce bias into study results, compromise the statistical power of a trial, and ultimately affect the reliability and validity of evidence supporting a Medical Device's safety and effectiveness.
    Grouped by theme

    Primary references

    3 sources
    Link health: 3 verified· last checked 2026-06-20
    ICH·2ISO·1
    1. 1
      ICH E9(R1)
      Verified
      ICHich.org
    2. 2
      ICH Guidelines
      Verified
      ICHich.org
    3. 3
      ISO 14155 Standard Page
      Verified
      ISOiso.org

    Inline markers like [1] jump to the matching reference above.