Faculty Bibliography

BACKGROUND/PURPOSE/OBJECTIVE:Breast masses in the pediatric population cause patient and family concern, partially driven by public awareness of adult breast cancer. However, the spectrum of breast masses in children differs greatly from that in adults, and malignancy is exceedingly rare. The American College of Radiology Breast Imaging Reporting and Data System (BI-RADS) ultrasound-based classification system is the diagnostic standard, yet no study has validated BI-RADS in pediatric patients. This study compares BI-RADS classification with histologic diagnoses to evaluate BI-RADS validity in pediatric patients. METHODS:Multicenter retrospective evaluation of breast masses in patients under 21 years. Ultrasound reports were compared with histologic diagnoses. RESULTS:There were 283 patients with breast pathology results after excluding clinical diagnoses of gynecomastia. Mean age was 16.9 (SD 2.3), ranging 10-20 years. 227 had pre-operative ultrasounds, and 84% (191/227) were assigned a BI-RADS category. BI-RADS 4 was the most frequent category (55%, n = 124), by definition predicting 2 - 95% likelihood of malignancy. However, pathology was benign in all patients. CONCLUSIONS:The current BI-RADS categorization system overestimates cancer risk when applied to pediatric patients. BI-RADS scores should not be assigned to pediatric patients, and BIRADS-defined recommendations for biopsy should be disregarded. A pediatric-specific classification system could be useful.

OBJECTIVE:Implicit prejudice and stereotyping may exist in health care providers automatically without their awareness. These biases can correlate with outcomes that are consequential for the patient. This study examined gynecologic oncology care providers' implicit prejudice and stereotyping toward cervical cancer. METHODS:Members of professional gynecologic oncology organizations were asked to complete two Implicit Association Tests to determine if they implicitly associate cervical cancer with feelings of anger (prejudice) and beliefs about culpability for the disease (stereotypes), compared to ovarian cancer. Linear models and Student t-tests examined average levels of implicit bias and moderators of the implicit bias effects. RESULTS: = 10.59). Gynecologic oncology providers showed significant levels of implicit prejudice, X¯ = 0.17, SD = 0.47, 95% CI: (0.10, 0.25), toward cervical cancer patients. They also showed significant levels of implicit stereotyping of cervical cancer patients, X¯ = 0.15, SD = 0.42, 95% CI: (0.08, 0.21). Whereas physicians did not demonstrate significant levels of implicit bias, nurses demonstrated greater levels of implicit prejudice and implicit stereotyping. Providers without cultural competency/implicit bias training demonstrated greater bias than those who had completed such training (p < .05). CONCLUSIONS:This study provides the first evidence that gynecologic oncology providers hold implicit biases related to cervical cancer. Interventions may be designed to target specific groups in gynecologic oncology to improve interactions with patients.

BACKGROUND:Breast cancer has the highest incidence of cancers in women in the United States. Previous research has shown that screening mammography contributes to reduced breast cancer mortality. This study aimed to clarify why late screening might occur in an at-risk population. MATERIALS AND METHODS/METHODS:This study was a prospective cross-sectional study including 758 patients presenting to our radiology department for routine screening mammography who completed a 30-question survey regarding personal characteristics and mammography history. Univariate and multivariate logistic regression were performed to determine whether survey responses correlated with late screening. RESULTS:Of the 758 patients, 184 (24%) were noncompliant with screening mammography guidelines. Risk factors for late screening included younger age (P = 0.001), white race/ethnicity (P = 0.03), self-reported lack of financial means or health insurance (P = 0.005), lack of satisfaction with a previous mammogram experience (P = 0.001), inadequate mammography education by a physician (P = 0.001), and lack of awareness/comprehension of screening mammography guidelines (P = 0.002). CONCLUSION/CONCLUSIONS:Many factors contribute to late screening mammography. Although some are outside physician control, others can be influenced: patient education regarding screening mammography guidelines, and patient satisfaction with the mammography experience. This study highlights the importance of communication with and education of patients.