Literature DB >> 17854238

Management of adnexal mass.

Evan R Myers, Lori A Bastian, Laura J Havrilesky, Shalini L Kulasingam, Mishka S Terplan, Kathryn E Cline, Rebecca N Gray, Douglas C McCrory.   

Abstract

OBJECTIVES: To assess diagnostic strategies for distinguishing benign from malignant adnexal masses. DATA SOURCES: MEDLINE(R) and reference lists of recent reviews; discharge data from the Nationwide Inpatient Sample. REVIEW
METHODS: The major diagnostic methods evaluated were bimanual pelvic examination, ultrasound (morphology and Doppler velocimetry), MRI, CT, FDG-PET, CA-125, and scoring systems that incorporated multiple clinical, laboratory, and radiologic findings. Meta-analysis using a random-effects model was used to estimate pooled sensitivity and specificity for discriminating benign from malignant. We reviewed evidence for followup strategies for masses considered benign, and for adverse outcomes of diagnostic surgery. We also reviewed published models of the natural history of ovarian cancer and compared the impact of assumptions about natural history on outcomes.
RESULTS: The majority of studies did not describe whether patients presented with asymptomatic masses detected through screening or with symptoms. Prevalence of malignant masses in a U.S. postmenopausal screening population was approximately 0.1 percent, while benign masses were found in 0.8 to 1.8 percent of women. Pooled (a) sensitivity and (b) specificity were: bimanual exam (a) 0.45, (b) 0.90; ultrasound morphology scores (a) 0.86 to 0.91, (b) 0.68 to 0.83; Doppler resistive index (a) 0.72, (b) 0.90; pulsatility index (a) 0.80, (b) 0.73; maximum systolic velocity (a) 0.74, (b) 0.81; presence of vessels (a) 0.88, (b) 0.78; combined morphology and Doppler (a) 0.86, (b) 0.91; MRI (a) 0.91, (b) 0.88; CT (a) 0.90, (b) 0.75; FDG-PET (a) 0.67, (b) 0.79; and CA-125 (a) 0.78, (b) 0.78. Both sensitivity and specificity of CA-125 were better in postmenopausal than in premenopausal women. In modeled outcomes, combinations of imaging and CA-125 were both more sensitive and more specific than either alone. Performance of scoring systems in validation studies was consistently worse than in development studies; the highest demonstrated specificity observed was 0.91, with a concurrent sensitivity of 0.74. Evidence on followup strategies was sparse, although one large study provided good evidence for safely following unilocular cysts less than 10 cm in diameter. Overall complication rates in studies of surgically managed adnexal masses were low, but important clinical information was not reported.
CONCLUSIONS: All diagnostic modalities showed trade-offs between sensitivity and specificity, but the available literature does not provide sufficient detail on relevant characteristics of study populations to allow confident estimation of the results of alternative diagnostic strategies. Although modeling studies may prove useful in evaluating diagnostic algorithms, further work is needed to explore the implications of uncertainty about the natural history of ovarian cancer.

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Mesh:

Year:  2006        PMID: 17854238      PMCID: PMC4781260     

Source DB:  PubMed          Journal:  Evid Rep Technol Assess (Full Rep)        ISSN: 1530-4396


  30 in total

1.  Intake of fruit, vegetables, and carotenoids in relation to risk of uterine leiomyomata.

Authors:  Lauren A Wise; Rose G Radin; Julie R Palmer; Shiriki K Kumanyika; Deborah A Boggs; Lynn Rosenberg
Journal:  Am J Clin Nutr       Date:  2011-11-09       Impact factor: 7.045

2.  An In Vitro Diagnostic Multivariate Index Assay (IVDMIA) for Ovarian Cancer: Harvesting the Power of Multiple Biomarkers.

Authors:  Zhen Zhang
Journal:  Rev Obstet Gynecol       Date:  2012

3.  Depressive symptoms and risk of uterine leiomyomata.

Authors:  Lauren A Wise; Se Li; Julie R Palmer; Lynn Rosenberg
Journal:  Am J Obstet Gynecol       Date:  2014-12-13       Impact factor: 8.661

4.  Accuracy of intraoperative frozen section in the evaluation of patients with adnexal mass: retrospective analysis of 748 cases with multivariate regression analysis.

Authors:  Derman Basaran; M Coskun Salman; Gokhan Boyraz; Ilker Selcuk; Alp Usubutun; Nejat Ozgul; Kunter Yuce
Journal:  Pathol Oncol Res       Date:  2014-05-22       Impact factor: 3.201

5.  Dietary glycemic index and load in relation to risk of uterine leiomyomata in the Black Women's Health Study.

Authors:  Rose G Radin; Julie R Palmer; Lynn Rosenberg; Shiriki K Kumanyika; Lauren A Wise
Journal:  Am J Clin Nutr       Date:  2010-03-03       Impact factor: 7.045

6.  Management of a suspicious adnexal mass: a clinical practice guideline.

Authors:  J E Dodge; A L Covens; C Lacchetti; L M Elit; T Le; M Devries-Aboud; M Fung-Kee-Fung
Journal:  Curr Oncol       Date:  2012-08       Impact factor: 3.677

7.  Hair relaxer use and risk of uterine leiomyomata in African-American women.

Authors:  Lauren A Wise; Julie R Palmer; David Reich; Yvette C Cozier; Lynn Rosenberg
Journal:  Am J Epidemiol       Date:  2012-01-10       Impact factor: 4.897

8.  A prospective study of dairy intake and risk of uterine leiomyomata.

Authors:  Lauren A Wise; Rose G Radin; Julie R Palmer; Shiriki K Kumanyika; Lynn Rosenberg
Journal:  Am J Epidemiol       Date:  2009-12-02       Impact factor: 4.897

9.  Assessing the risk of ovarian malignancy algorithm for the conservative management of women with a pelvic mass.

Authors:  Elizabeth Lokich; Marguerite Palisoul; Nicole Romano; M Craig Miller; Katina Robison; Ashley Stuckey; Paul DiSilvestro; Cara Mathews; C O Granai; Geralyn Lambert-Messerlian; Richard G Moore
Journal:  Gynecol Oncol       Date:  2015-09-11       Impact factor: 5.482

10.  Prospective study of dietary fat and risk of uterine leiomyomata.

Authors:  Lauren A Wise; Rose G Radin; Shiriki K Kumanyika; Edward A Ruiz-Narváez; Julie R Palmer; Lynn Rosenberg
Journal:  Am J Clin Nutr       Date:  2014-03-05       Impact factor: 7.045

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