Lead Time Bias

TL;DR

• Apparent survival can be inflated when time to diagnosis confirmation varies between patients.
• Screening or different diagnostic methods can produce longer observed survival without changing the course of disease.
• Use appropriate statistical methods (e.g., survival analysis) to assess true benefits of earlier detection.

Definition

Lead time bias is a type of bias that occurs when the estimated survival time of a patient is affected by the length of time it takes for their diagnosis to be confirmed. This bias can result in an overestimation of the survival time for patients with longer lead times, as their diagnosis may be confirmed at a later stage of their disease.

Explanation

When the interval until a diagnosis is confirmed differs across patients or diagnostic methods, measured survival time from diagnosis can be misleading. Patients with longer lead times may appear to survive longer after diagnosis not because their prognosis is better, but because the timing of confirmation shifts the measured start point. This can create the false impression that earlier detection or a particular diagnostic method improves survival unless analyses account for the differing lead times.

Examples

Mammography and breast cancer

In a study of women with breast cancer, those who were diagnosed through mammography had a longer lead time than those who were diagnosed through other means, such as a clinical examination or self-detection. As a result, the estimated survival time for the women diagnosed through mammography was longer than the estimated survival time for the women diagnosed through other means.

PSA testing and prostate cancer

In a study of men with prostate cancer, those who were diagnosed through PSA testing had a longer lead time than those who were diagnosed through other means, such as a digital rectal examination or biopsy. As a result, the estimated survival time for the men diagnosed through PSA testing was longer than the estimated survival time for the men diagnosed through other means.

Use cases

• Evaluating impacts of screening or diagnostic methods on measured survival.
• Informing clinical decision making by distinguishing apparent survival improvements from true treatment or detection benefits.
• Applying statistical approaches, such as survival analysis, to estimate true survival times and assess the benefit of early detection.

Notes or pitfalls

• Lead time bias can cause overestimation of the benefits of early detection.
• This overestimation may contribute to unnecessary treatments and associated adverse effects if not identified and corrected.
• Avoiding lead time bias requires appropriate statistical methods (for example, survival analysis) to produce a more accurate assessment of survival and the value of earlier diagnosis.

Related terms

• Survival analysis
• Early detection
• Screening
• Diagnosis