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.

One example of lead time bias can be seen in the use of mammography for the early detection of 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.

Another example of lead time bias can be seen in the use of prostate-specific antigen (PSA) testing for the early detection of 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.

Lead time bias can have important implications for clinical decision making, as it can lead to an overestimation of the benefits of early detection and may result in unnecessary treatments and adverse effects. To avoid this bias, it is important to use appropriate statistical methods, such as survival analysis, to estimate the survival time of patients with a particular disease. This can provide a more accurate assessment of the benefits of early detection and help clinicians make informed decisions about the best course of treatment for their patients.