Modeling risk assessment for breast cancer in symptomatic women: A Saudi Arabian study

Anwar E. Ahmed*, Donna K. McClish, Thamer Alghamdi, Abdulmajeed Alshehri, Yasser Aljahdali, Khalid Aburayah, Abdulrahman Almaymoni, Monirah Albaijan, Hamdan Al-Jahdali, Abdul Rahman Jazieh

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


Background: Despite the continuing increase in the breast cancer incidence rate among Saudi Arabian women, no breast cancer risk-prediction model is available in this population. The aim of this research was to develop a risk-assessment tool to distinguish between high risk and low risk of breast cancer in a sample of Saudi women who were screened for breast cancer. Methods: A retrospective chart review was conducted on symptomatic women who underwent breast mass biopsies between September 8, 2015 and November 8, 2017 at King Abdulaziz Medical City, Riyadh, Saudi Arabia. Results: A total of 404 (63.8%) malignant breast biopsies and 229 (36.2%) benign breast biopsies were analyzed. Women ≥40 years old (aOR: 6.202, CI 3.497-11.001, P=0.001), hormonereplacement therapy (aOR 24.365, 95% CI 8.606-68.987, P=0.001), postmenopausal (aOR 3.058, 95% CI 1.861-5.024, P=0.001), and with a family history of breast cancer (aOR 2.307, 95% CI 1.142-4.658, P=0.020) were independently associated with an increased risk of breast cancer. This model showed an acceptable fit and had area under the receiver-operating characteristic curve of 0.877 (95% CI 0.851-0.903), with optimism-corrected area under the curve of 0.865. Conclusion: The prediction model developed in this study has a high ability in predicting increased breast cancer risk in our facility. Combining information on age, use of hormone therapy, postmenopausal status, and family history of breast cancer improved the degree of discriminatory accuracy of breast cancer prediction. Our risk model may assist in initiating population-screening programs and prompt clinical decision making to manage cases and prevent unfavorable outcomes.

Original languageEnglish
Pages (from-to)1125-1132
Number of pages8
JournalCancer Management and Research
StatePublished - 2019
Externally publishedYes


  • Breast cancer management
  • Modeling
  • Patient stratification
  • Predictive tool
  • Risk assessment


Dive into the research topics of 'Modeling risk assessment for breast cancer in symptomatic women: A Saudi Arabian study'. Together they form a unique fingerprint.

Cite this