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Keywords:

  • Additive models;
  • Cancer screening;
  • Convolution models;
  • Lead time distribution;
  • Penalized likelihood

Summary The introduction of the prostate-specific antigen (PSA) test has led to dramatic changes in the incidence of prostate cancer in the United States. In this article, we use information on the increase and subsequent decline in prostate cancer incidence following the adoption of PSA to estimate the lead time associated with PSA screening. The lead time is a key determinant of the likelihood of overdiagnosis, one of the main costs associated with the PSA test. Our approach conceptualizes observed incidence as the sum of the secular trend in incidence, which reflects incidence in the absence of PSA, and the excess incidence over and above the secular trend, which is a function of population screening patterns and the unknown lead time. We develop a likelihood model for the excess incidence given the secular trend and use it to estimate the mean lead time under specified distributional assumptions. We also develop a likelihood model for observed incidence and use it to simultaneously estimate the mean lead time together with a smooth secular trend. Variances and confidence intervals are estimated via a parametric bootstrap. Our results indicate an average lead time of approximately 4.59 years (95% confidence interval [3.24, 5.93]) for whites and 6.78 years [5.42, 8.20] for blacks with a corresponding secular trend estimate that is fairly flat after the introduction of PSA screening. These estimates correspond to overdiagnosis frequencies of approximately 22.7% and 34.4% for screen-detected whites and blacks, respectively. Our results provide the first glimpse of a plausible secular trend in prostate cancer incidence and suggest that, in the absence of PSA screening, disease incidence would not have continued its historic increase, rather it would have leveled off in accordance with changes in prostate patterns of care unrelated to PSA.