Empirical estimates of the lead time distribution for prostate cancer based on two independent representative cohorts of men not subject to prostate-specific antigen screening Journal Article


Authors: Savage, C. J.; Lilja, H.; Cronin, A. M.; Ulmert, D.; Vickers, A. J.
Article Title: Empirical estimates of the lead time distribution for prostate cancer based on two independent representative cohorts of men not subject to prostate-specific antigen screening
Abstract: Background: Lead time, the estimated time by which screening advances the date of diagnosis, is used to calculate the risk of overdiagnosis. We sought to describe empirically the distribution of lead times between an elevated prostate-specific antigen (PSA) and subsequent prostate cancer diagnosis. Methods: We linked the Swedish cancer registry to two independent cohorts: 60-year-olds sampled in 1981-1982 and 51- to 56-year-olds sampled in 1982-1985. We used univariate kernel density estimation to characterize the lead time distribution. Linear regression was used to model the lead time as a function of baseline PSA and logistic regression was used to test for an association between lead time and either stage or grade at diagnosis. Results: Of 1,167 older men, 132 were diagnosed with prostate cancer, of which 57 had PSA ≥3 ng/mL at baseline; 495 of 4,260 younger men were diagnosed with prostate cancer, of which 116 had PSA ≥3 ng/mL at baseline. The median lead time was slightly longer in the younger men (12.8 versus 11.8 years). In both cohorts, wide variation in lead times followed an approximately normal distribution. Longer lead times were significantly associated with a lower risk of high-grade disease in older and younger men [odds ratio, 0.82 (P = 0.023) and 0.77 (P < 0.001)]. Conclusion: Our findings suggest that early changes in the natural history of the disease are associated with high-grade cancer at diagnosis. Impact: The distinct differences between the observed distribution of lead times and those used in modeling studies illustrate the need to model overdiagnosis rates using empirical data. ©2010 AACR.
Keywords: adult; controlled study; middle aged; major clinical study; case-control studies; sensitivity and specificity; sensitivity analysis; prostate specific antigen; cohort studies; cancer screening; mass screening; groups by age; time; models, theoretical; prostate cancer; gleason score; sweden; prostate-specific antigen; prostatic neoplasms; registries; blood level; lead time
Journal Title: Cancer Epidemiology Biomarkers and Prevention
Volume: 19
Issue: 5
ISSN: 1055-9965
Publisher: American Association for Cancer Research  
Date Published: 2010-05-01
Start Page: 1201
End Page: 1207
Language: English
DOI: 10.1158/1055-9965.epi-09-1251
PUBMED: 20406957
PROVIDER: scopus
PMCID: PMC2866147
DOI/URL:
Notes: --- - "Cited By (since 1996): 1" - "Export Date: 20 April 2011" - "CODEN: CEBPE" - "Source: Scopus"
Altmetric Score
MSK Authors
  1. Caroline Savage
    80 Savage
  2. Hans Gosta Lilja
    286 Lilja
  3. Andrew J Vickers
    569 Vickers
  4. Angel M Cronin
    145 Cronin
  5. Hans David Staffan Ulmert
    50 Ulmert