Immortal person-time in studies of cancer outcomes.

able to inclusion of immortal person-time using a hypothetic study of 5-year survival after treatment initiation among patients diagnosed at a single clinical center. Suppose investigators prospectively enrolled 350 patients per year for 2 years and observed these patients for 5 years. To bolster sample size, investigators augmented these prospective data with prevalent cases identified retrospectively in the center’s registry of current patients. Imagine that they included 350 patients per year for the 5 years before study onset. For each patient with cancer, the investigators knew the number of years from treatment initiation to study enrollment (if any), the number of years from treatment initiation to death, and whether the patient was identified prospectively or retrospectively. Suppose the 1,750 prospectively enrolled patients with cancer contributed 3,473 person-years at risk for death, during which 111 deaths occurred, yielding a rate of 3.2 deaths per 100 person-years. In addition, 1,750 retrospectively enrolled patients with cancer contributed 8,506 person-years between treatment initiation and end of study; 4,169 person-years (49%) were accrued after study enrollment, during which 136 deaths occurred. Note that retrospectively enrolled patients had to be current patients at the time the study began, so they had to have survived from diagnosis to study inception. Counting all person-time, both mortal and immortal, among retrospectively enrolled patients would yield an overall rate of 1.6 deaths per 100 person-years, which is approximately half the prospectively measured rate. However, counting only mortal persontime among retrospectively enrolled patients would yield the correct rate of 3.3 deaths per 100 person-years. In a given study, immortal person-time usually accrues between the first event required for study entry (eg, cancer diagnosis or inception of treatment) and the last event required for study entry (eg, provision of written informed consent or collection of a biologic specimen). Immortal person-time may also arise when a list of potential study patients is used to define a cohort, but the list is modified between the time of its creation and the time it reaches the hands of investigators. For example, if study patients were removed from a registry because of death or emigration, then the registry list would only include survivors at the time it reached investigators. For the survivors on the list, the time between their entry into the registry and delivery of the list to investigators would be immortal person-time. Accrual of person-time from the date of the last study or exposure-defining criterion thus provides a simple solution for avoiding immortal and immune person-time bias when estimating outcome rates, rate differences, and rate ratios. Allowing patients into risk sets only when person-time is not immortal or immune using methods for late entry or time-varying exposure provides the analogous solution when estimating survival curves or hazard ratios. This solution of restricting or reallocating counted person-time is not foolproof. Analogous to informative censoring, bias will persist if the timing of late entry is informative with respect to the outcome of interest, conditional on measured variables. In addition, this solution is not optimal if a study samples exposed and unexposed patients Immortal Person-Time in Studies of Cancer Outcomes