E J Feuer1, R M Merrill, B F Hankey. 1. Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, MD 20892, USA.
Abstract
BACKGROUND: The rise and fall of prostate cancer mortality correspond closely to the rise and fall of newly diagnosed cases. To understand this phenomenon, we explored the role that screening, treatment, iatrogenic (i.e., treatment-induced) deaths, and attribution bias (incorrect labeling of death from other causes as death from prostate cancer) have played in recent mortality trends. METHODS: Join point regression is utilized to assess the recent rise and fall in mortality and the relationship of total U.S. trends to those areas served by the National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) Cancer Registry Program. Incidence-based mortality (IBM) is estimated with the use of prostate cancer data from the SEER Program to partition (from overall prostate cancer mortality trends) the contribution of cases diagnosed since the widespread use of prostate-specific antigen (PSA) testing starting in 1987. IBM is also used to examine the contribution of stage at diagnosis to the recent prostate cancer mortality trends. RESULTS: IBM for cases diagnosed since 1987 rose above the pre-1987 secular (i.e., background) trend, peaked in the early 1990s, and almost returned to the secular trend by 1994. This rise and fall of IBM track with the pool of prevalent cases diagnosed within the prior 2 years. IBM for cases diagnosed with metastatic disease fell starting in 1991, while IBM for those diagnosed with localized/regional disease was relatively flat. CONCLUSIONS: The rise and fall in prostate cancer mortality observed since the introduction of PSA testing in the general population are consistent with a hypothesis that a fixed percent of the rising and falling pool of recently diagnosed patients who die of other causes may be mislabeled as dying of prostate cancer. The decline in IBM for distant stage disease and flat IBM trends for localized/regional disease provide some evidence of improved prognosis for screen-detected cases, although alternative interpretations are possible.
BACKGROUND: The rise and fall of prostate cancer mortality correspond closely to the rise and fall of newly diagnosed cases. To understand this phenomenon, we explored the role that screening, treatment, iatrogenic (i.e., treatment-induced) deaths, and attribution bias (incorrect labeling of death from other causes as death from prostate cancer) have played in recent mortality trends. METHODS: Join point regression is utilized to assess the recent rise and fall in mortality and the relationship of total U.S. trends to those areas served by the National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) Cancer Registry Program. Incidence-based mortality (IBM) is estimated with the use of prostate cancer data from the SEER Program to partition (from overall prostate cancer mortality trends) the contribution of cases diagnosed since the widespread use of prostate-specific antigen (PSA) testing starting in 1987. IBM is also used to examine the contribution of stage at diagnosis to the recent prostate cancer mortality trends. RESULTS: IBM for cases diagnosed since 1987 rose above the pre-1987 secular (i.e., background) trend, peaked in the early 1990s, and almost returned to the secular trend by 1994. This rise and fall of IBM track with the pool of prevalent cases diagnosed within the prior 2 years. IBM for cases diagnosed with metastatic disease fell starting in 1991, while IBM for those diagnosed with localized/regional disease was relatively flat. CONCLUSIONS: The rise and fall in prostate cancer mortality observed since the introduction of PSA testing in the general population are consistent with a hypothesis that a fixed percent of the rising and falling pool of recently diagnosed patients who die of other causes may be mislabeled as dying of prostate cancer. The decline in IBM for distant stage disease and flat IBM trends for localized/regional disease provide some evidence of improved prognosis for screen-detected cases, although alternative interpretations are possible.
Authors: Grace Lu-Yao; Peter C Albertsen; Janet L Stanford; Therese A Stukel; Elizabeth S Walker-Corkery; Michael J Barry Journal: BMJ Date: 2002-10-05
Authors: Nadia Howlader; Lindsay M Morton; Eric J Feuer; Caroline Besson; Eric A Engels Journal: Cancer Epidemiol Biomarkers Prev Date: 2015-10-15 Impact factor: 4.254
Authors: Grace Lu-Yao; Peter C Albertsen; Janet L Stanford; Therese A Stukel; Elizabeth Walker-Corkery; Michael J Barry Journal: J Gen Intern Med Date: 2008-09-16 Impact factor: 5.128