External validation of a mammographic texture marker for breast cancer risk in a case-control study

  • Chao Wang
  • , Adam R. Brentnall
  • , James Mainprize
  • , Martin Yaffe
  • , Jack Cuzick
  • , Jennifer A. Harvey

    Research output: Contribution to journalArticlepeer-review

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    Abstract

    Purpose: The pattern of dense tissue on a mammogram appears to provide additional information than overall density for risk assessment, but there has been little consistency in measures of texture identified. The purpose of this study is thus to validate a mammographic texture feature developed from a previous study in a new setting. Approach: A case-control study (316 invasive cases and 1339 controls) of women in Virginia, USA was used to validate a mammographic texture feature (MMTEXT) derived in a independent previous study. Analysis of predictive ability was adjusted for age, demographic factors, questionnaire risk factors (combined through the Tyrer-Cuzick model), and optionally BI-RADS breast density. Odds ratios per interquartile range (IQ-OR) in controls were estimated. Subgroup analysis assessed heterogeneity by mode of cancer detection (94 not detected by mammography). Results: MMTEXT was not a significant risk factor at 0.05 level after adjusting for classical risk factors (IQ-OR = 1.16, 95%CI 0.92 to 1.46), nor after further adjustment for BI-RADS density (IQ-OR = 0.92, 95%CI 0.76 to 1.10). There was weak evidence that MMTEXT was more predictive for cancers that were not detected by mammography (unadjusted for density: IQ-OR = 1.46, 95%CI 0.99 to 2.15 versus 1.03, 95%CI 0.79 to 1.35, Phet 0.10; adjusted for density: IQ-OR = 1.11, 95%CI 0.70 to 1.77 versus 0.76, 95%CI 0.55 to 1.05, Phet 0.21). Conclusions: MMTEXT is unlikely to be a useful imaging marker for invasive breast cancer risk assessment in women attending mammography screening. Future studies may benefit from a larger sample size to confirm this as well as developing and validating other measures of risk. This negative finding demonstrates the importance of external validation.
    Original languageEnglish
    Article number014003
    JournalJournal of Medical Imaging
    Volume7
    Issue number1
    Early online date12 Feb 2020
    DOIs
    Publication statusPublished - 12 Feb 2020

    Bibliographical note

    Note: This work was supported by the the Congressionally Directed Medical Research Programs [grant number: BC100474] and Cancer Research UK [grant number: C569/A16891].

    Keywords

    • Health services research

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