Differentiate between attrition and loss to follow-up; how can attrition bias affect results?

• A. Attrition is dropout; loss to follow-up is missing outcome; both can bias results if related to exposure/outcome
• B. They are the same
• C. Attrition only occurs in cross-sectional studies
• D. Loss to follow-up always invalidates a study

Answer: (A)

When you follow people over time, attrition means participants drop out of the study before it finishes. Loss to follow-up is a specific type of missing outcome data that happens when you can’t obtain the outcome for those participants during the follow-up period. The reason this matters is that if the likelihood of dropping out or being lost is related to the exposure being studied or to the outcome itself, the remaining group may not be representative. This can distort the observed association or effect, sometimes exaggerating or masking the true relationship. For example, if higher-risk individuals are more likely to drop out, the remaining sample might underestimate the real risk. If those who develop the outcome are more likely to be lost, incidence or progression estimates may be biased downward. So both attrition and loss to follow-up threaten internal validity when missingness is not random. To address this, researchers compare characteristics of those lost versus those who stay, and use methods like sensitivity analyses, multiple imputation, or weighting, while also designing to minimize dropouts.