Evaluation of new technologies for cancer control based on population trends in disease incidence and mortality

Abstract

Cancer interventions often disseminate in the population before evidence of their effectiveness is available. Population disease trends provide a natural experiment for assessing the characteristics of the disease and the potential impact of the intervention. We review models for extracting information from population data for use in economic evaluations of cancer screening interventions. We focus particularly on prostate-specific antigen (PSA) screening for prostate cancer and describe approaches that can be used to project the likely costs and benefits of competing screening policies. Results indicate that the lifetime probability of biopsy-detectable prostate cancer is 33%, the chance of clinical diagnosis without screening is 13%, and the average time from onset to clinical diagnosis is 14 years. Less aggressive screening policies that screen less often and use more conservative criteria (e.g., higher PSA thresholds) for biopsy referral may dramatically reduce PSA screening costs with modest impact on benefit.

Figure 1.

A model of prostate cancer (PCA) natural history, diagnosis, and survival in the absence and presence of screening. Following disease onset, PSA is assumed to grow exponentially. The risks of metastasis and clinical diagnosis (dx) increase proportionally with the PSA level. Without screening, the cancer is diagnosed in distant stage, but with screening, detection occurs while disease is still localized. The figure shows how overdiagnosis depends on the date of other-cause (OC) death relative to the lead time, which is the time from screen diagnosis to clinical diagnosis.

Figure 2.

Modeled impact of changes in primary treatment and changes in primary treatment combined with screening on age-adjusted prostate cancer mortality in the United States. The figure shows mortality among men diagnosed after 1975 as observed and then as modeled given changes in treatment and screening. For comparison, the figure also shows total mortality due to prostate cancer in the United States. By 2005, treatment changes account for about one-third of the drop in disease-specific mortality (20), whereas the combination of screening and treatment changes accounts for about two-thirds of the drop in mortality.

Figure 3.

Three outcomes of harm (false positive and overdiagnosis) and benefit (years of life saved) corresponding to six candidate PSA screening policies, varying ages to start and stop screening, and interscreening intervals as well as the criterion or threshold for biopsy referral. Outcomes are numbers of false positives, overdiagnoses, and lives saved per 1 million men screened. The ages to start and stop screening are specified below the figure; upper and lower bounds are provided and the interscreening interval is given in parentheses. As an example, the policy 40, 45, 50, (2), 75 indicates that screens take place at ages 40, 45, 50, and thereafter every 2 years until stopping at age 75. The figure shows that less intensive screening strategies can yield dramatic reductions in screening harms with very modest differences in benefit.