BACKGROUND AND PURPOSE:

• Estimated risk of occult uterine cancer unclear and often not based on subtypes
• Desai et al. (AJOG, 2019) sought to examine the prevalence of occult uterine cancer at hysterectomy for benign indications as well as related risk factors

METHODS:

• Retrospective Cohort Study
  • New York Statewide Planning and Research Cooperative System (SPARCS) database (2003-2013)
  • New York State Cancer Registry
• Participants
  • Inpatient or outpatient hysterectomy for benign indications
• Data analysis
  • Occult cancer definition: Newly diagnosed corpus uteri cancer within 28 days after the index hysterectomy
  • Prevalence of occult uterine cancer was estimated overall and by subtype
  • Developed and validated risk prediction models

RESULTS:

• 229,536 women were included
• Prevalence of occult cancer
  • Overall: 0.96% (95% CI, 0.92 to 1.00%)
  • Endometrial carcinoma: 0.75% (95% CI, 0.71 to 0.78%)
  • Uterine sarcoma: 0.22% (95% CI, 0.20 to 0.23%)
  • Leiomyosarcoma: 0.15% (95% CI, 0.13 to 0.17%)
• Stage
  • 71% of the endometrial carcinomas and 58.0% of the uterine sarcomas were at localized stage
• Risk for all occult uterine cancer
  • Varied across the age spectrum
    • 18-29 years: 0.10% | ≥75 years: 4.40% 
    • 1.03% prevalence reached in the 50 to 54 year cohort
  • Varied by indication
    • Endometriosis: 0.14% | Uterine fibroids: 0.62% | Postmenopausal bleeding: 8.43%
• Risk factors for occult uterine cancer included
  • Race/ethnicity
  • Obesity
  • Comorbidity
  • Personal history of malignancy
• Prediction models incorporating these risk factors had
  • High negative predictive values: 99.8% for endometrial carcinoma | 99.9% for uterine sarcoma
  • Relatively low positive predictive value

CONCLUSION:

• Overall, approximately 1% of women undergoing hysterectomy for benign indications had occult uterine cancer
• Prevalence higher than in some previous studies, however those tend to focus on myomectomy not hysterectomy and therefore may be skewed toward a younger, healthier patient population
• Patient characteristics may be useful and applied to algorithms
  • Risk algorithms in this study performed better for ruling out cancer rather than predicting the presence of an occult malignancy

Learn More – Primary Sources:

Prevalence, characteristics, and risk factors of occult uterine cancer in presumed benign hysterectomy

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