A nomogram for estimating the probability of ovarian cancer

Jason A. Lachance, Asim Choudhri, Marc Sarti, Susan C. Modesitt, Amir A. Jazaeri, George J. Stukenborg

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

Objective: Accurate preoperative estimates of the probability of malignancy in women with adnexal masses are essential for ensuring optimal care. This study presents a new statistical model for combining predictive information and a graphic decision support tool for calculating risk of malignancy. Methods: The study included 153 women treated with definitive surgery for adnexal mass between 2001 and 2007 with preoperative ultrasound testing and a serum CA125. Multivariable logistic regression was used to develop a statistical model for estimating the probability of ovarian cancer as a function of age, ultrasound score, and CA125 value, with adjustments for nonlinear and interactive relationships. Results: A total of 20 cases of pathologically confirmed cancer (13 invasive malignancies, and 7 tumors of low malignant potential) were identified (20/153 = 13%). The model obtained excellent discrimination (ROC area = 0.87), explained nearly half of the observed variation in the risk of malignancy (R2 = 0.43), and was well calibrated across the full range of malignancy probabilities. The model equation is represented in the form of a nomogram, which can be used to calculate preoperative probability of malignancy. At a 5% risk of malignancy threshold, the model has a sensitivity of 90% and a specificity of 73%. Conclusions: Statistical models for estimating the probability of adnexal mass malignancy are substantially improved by including adjustments for non-linear relationships among key variables. A clinically relevant nomogram provides an objective tool to further aid clinicians in counseling patients and ensuring proper referral to surgical sub-specialists when indicated.

Original languageEnglish (US)
Pages (from-to)2-7
Number of pages6
JournalGynecologic Oncology
Volume121
Issue number1
DOIs
StatePublished - Apr 1 2011
Externally publishedYes

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Nomograms
Ovarian Neoplasms
Neoplasms
Statistical Models
Counseling
Referral and Consultation
Logistic Models

All Science Journal Classification (ASJC) codes

  • Obstetrics and Gynecology
  • Oncology

Cite this

Lachance, J. A., Choudhri, A., Sarti, M., Modesitt, S. C., Jazaeri, A. A., & Stukenborg, G. J. (2011). A nomogram for estimating the probability of ovarian cancer. Gynecologic Oncology, 121(1), 2-7. https://doi.org/10.1016/j.ygyno.2010.12.365

A nomogram for estimating the probability of ovarian cancer. / Lachance, Jason A.; Choudhri, Asim; Sarti, Marc; Modesitt, Susan C.; Jazaeri, Amir A.; Stukenborg, George J.

In: Gynecologic Oncology, Vol. 121, No. 1, 01.04.2011, p. 2-7.

Research output: Contribution to journalArticle

Lachance, JA, Choudhri, A, Sarti, M, Modesitt, SC, Jazaeri, AA & Stukenborg, GJ 2011, 'A nomogram for estimating the probability of ovarian cancer', Gynecologic Oncology, vol. 121, no. 1, pp. 2-7. https://doi.org/10.1016/j.ygyno.2010.12.365
Lachance, Jason A. ; Choudhri, Asim ; Sarti, Marc ; Modesitt, Susan C. ; Jazaeri, Amir A. ; Stukenborg, George J. / A nomogram for estimating the probability of ovarian cancer. In: Gynecologic Oncology. 2011 ; Vol. 121, No. 1. pp. 2-7.
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