Effects of study methods and biases on estimates of invasive breast cancer overdetection with mammography screening: a systematic review

Lancet Oncol. 2007 Dec;8(12):1129-1138. doi: 10.1016/S1470-2045(07)70380-7.

Abstract

Estimates of breast-cancer overdetection, the detection with screening of cancer that would not have presented clinically during the woman's lifetime (and therefore would not be diagnosed in the absence of screening), vary widely. We systematically reviewed estimates of overdetection to assess the extent to which these might be biased by study methods. Primary research papers and reviews that estimated overdetection of invasive breast cancer were eligible for inclusion. For each paper we appraised the study design and methods to identify the extent and effect of bias. Two reviews and six primary studies were included. We categorised studies as being based on cumulative-incidence or incidence-rate methods. The least biased overdetection estimates range from -4% to 7.1% for women aged 40-49 years, 1.7% to 54% for women aged 50-59 years, and 7% to 21% for women aged 60-69 years. Studies consistently show that cancer overdetection occurs in screening for breast cancer; however, reported estimates are biased. Sensitivity of mammography for both cancers that will progress and for overdetected cancers may be increasing with time. New studies are urgently needed to quantify the true extent of overdetection in current mammography screening programmes. These studies should be designed to avoid the multiple sources of bias identified in this review.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review
  • Systematic Review

MeSH terms

  • Adult
  • Age Distribution
  • Age Factors
  • Aged
  • Bias
  • Breast Neoplasms / diagnosis*
  • Breast Neoplasms / epidemiology
  • Breast Neoplasms / pathology
  • Epidemiologic Research Design
  • Female
  • Humans
  • Incidence
  • Mammography* / statistics & numerical data
  • Mass Screening / methods*
  • Mass Screening / statistics & numerical data
  • Middle Aged
  • Models, Statistical
  • Neoplasm Invasiveness
  • Predictive Value of Tests
  • Risk Assessment
  • Sensitivity and Specificity
  • Time Factors