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Combining two or more treatment methods increases the life span of cancer patients while reducing damage to vital organs or tissue from the overuse of a single treatment. Combination therapy also targets different cancer-inducing pathways, thus reducing the chances of developing resistance to treatment.
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Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
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A framework for personalized mammogram screening.

Dinesh Pal Mudaranthakam1,2, Michele Park2, Jeffrey Thompson1,2

  • 1Department of Biostatistics & Data Science, University of Kansas, Medical Center, Kansas City, KS, USA.

Preventive Medicine Reports
|June 25, 2021
PubMed
Summary
This summary is machine-generated.

Understanding breast cancer screening is vital. This study found that older age, marriage, college education, and family history decrease screening nonattendance, while family history and hormonal contraceptive use increase abnormal mammogram risk.

Keywords:
Breast cancer screeningCancer risk factorsMammogramPreventive task force

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Area of Science:

  • Oncology
  • Public Health
  • Biostatistics

Background:

  • Breast cancer screening guidelines are evidence-based but vary due to research evolution and interpretation differences.
  • This variability leads to delayed guideline adoption, inconsistent physician decisions, and unnecessary screenings for some patients.
  • Identifying key risk factors influencing screening behavior and outcomes is crucial for optimizing patient care.

Purpose of the Study:

  • To analyze patient risk factors associated with breast cancer screening behaviors and results.
  • To identify predictors of screening nonattendance and abnormal mammogram findings.
  • To inform the refinement of breast cancer screening protocols and risk stratification.

Main Methods:

  • Logistic regression analysis was employed to assess the relationship between various risk factors and screening outcomes.
  • Two outcome variables were analyzed: 1) whether a patient underwent screening, and 2) whether screening yielded abnormal results.
  • Risk factors included demographics (age, marital status, education, residence), family history, BMI, lifestyle (smoking, alcohol), reproductive history, and medication use.

Main Results:

  • Screening nonattendance was negatively associated with older age, being married, having a college education, and a family history of breast cancer.
  • Abnormal mammogram results were positively associated with a family history of breast cancer and hormonal contraceptive use.
  • The analysis identified significant associations, highlighting specific demographic and clinical factors influencing screening adherence and outcomes.

Conclusions:

  • Patient age, marital status, education, and family history significantly impact breast cancer screening attendance.
  • Family history and hormonal contraceptive use are key factors associated with abnormal mammogram findings.
  • Further development of this analytical procedure will incorporate additional risk factors to enhance screening precision and patient risk assessment.