Asian Pacific Journal of Cancer Care (Sep 2021)

Prevalence, Predictive Factors and Nomogram of Residual Disease Following Cervical Conization for Adenocarcinoma in Situ

  • Boonyapipat Sathana,
  • Sukkasame Pichamon

DOI
https://doi.org/10.31557/apjcc.2021.6.3.317-322
Journal volume & issue
Vol. 6, no. 3
pp. 317 – 322

Abstract

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Objectives: To evaluate the prevalence of residual disease after conization in AIS women, and to develop a nomogram for predicting residual disease in such patients. Methods: Eighty-three cervical adenocarcinoma in situ (AIS) patients were retrospectively reviewed. Patient data concerning: demographic characteristics, colposcopic findings and diagnosis, type of conization, size of pathologic specimens, pathological characteristics, endocervical curettage (ECC) pathology and subsequent procedures, were collected. The rate of residual disease after conization and predictive factors for residual disease in subsequent hysterectomy were analyzed, and a predictive nomogram for residual disease was developed, based on the multivariate analysis results. The statistical significance was set at a p-value of <0.05. Results: The prevalence of residual disease in hysterectomy specimens following conization was 31.8%. Five (5.7%) women with AIS, who underwent subsequent hysterectomy, were found to have invasive adenocarcinoma. According to the multivariate analysis results, the predictive factors for residual disease were a positive endocervical margin status [OR 22.5 (95% CI 4.74, 106.79)] and a depth of specimen of < 8 mm [OR 8.11 (95% CI 1.12, 58.95)]. A nomogram for the prediction of residual disease in AIS women was developed, based on these predictive factors. After bootstrapping 1000 times, the bootstrap-corrected concordance index value for predicting residual disease was 0.852. Conclusion: The residual disease was found in 31.8% of hysterectomy specimens after conization for AIS. Residual disease was strongly associated with a positive endocervical margin and a depth of specimen of <8 mm. This study reports a feasible nomogram, with an acceptable level of accuracy for predicting the individual risk of residual disease; which may be beneficial in proper management decision-making.

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