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Related Concept Videos

Cancer Survival Analysis01:21

Cancer Survival Analysis

Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...

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Related Experiment Video

Updated: Jun 18, 2026

Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
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Biennial Mammography Performance in the Korean National Cancer Screening Program From 2009 to 2020.

Dong Jun Kim1,2, Nan-He Yoon3, Jae Kwan Jun4,5

  • 1Department of Preventive Medicine, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.

Korean Journal of Radiology
|February 27, 2025
PubMed
Summary

Mammography screening in Korea improved significantly from 2009-2020, with better cancer detection rates and fewer false positives. However, positive predictive value and sensitivity need further enhancement for optimal breast cancer screening outcomes.

Keywords:
Breast cancerMammographyOutcomePerformanceRegional variationResultTrend analysis

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Area of Science:

  • Public Health
  • Radiology
  • Oncology

Background:

  • Mammography is crucial for breast cancer mortality reduction but exhibits global performance variability.
  • Evaluating screening program outcomes and regional disparities is essential for quality improvement.

Purpose of the Study:

  • To assess mammography screening performance over 12 years in Korea.
  • To investigate regional variations in mammography screening outcomes within the Korean National Cancer Screening Program (KNCSP).

Main Methods:

  • Analysis of 42 million mammography screenings from Korean women aged 40+ (2009-2020).
  • Computation of key performance metrics: recall rate (RR), positive predictive value (PPV), sensitivity, specificity, false positive rate (FPR), cancer detection rate (CDR), interval cancer rate (ICR), and dense breast rate (DBR).
  • Joinpoint regression for trend analysis and examination of regional variations across 237 districts.

Main Results:

  • Screenings increased from 2.8M (2009) to 3.6M (2020).
  • RR decreased (-3.7% annually), while PPV (+10.7% annually), CDR (+7.3% annually), and ICR (+5.2% annually) increased.
  • Regional performance differences in RR, sensitivity, specificity, and FPR diminished over the study period.

Conclusions:

  • Mammography performance in Korea improved between 2009 and 2020.
  • Positive predictive value and sensitivity remain suboptimal, necessitating ongoing quality monitoring.
  • Reduced but persistent regional disparities highlight the need to address screening inequities.