The role of chemoprevention in modifying the risk of breast cancer in women with atypical breast lesions.

Women with atypical ductal hyperplasia (ADH), atypical lobular hyperplasia (ALH), lobular carcinoma in situ (LCIS), and severe ADH are at increased risk of breast cancer, but a systematic quantification of this risk and the efficacy of chemoprevention in the clinical setting is still lacking. The objective of this study is to evaluate a woman's risk of breast cancer based on atypia type and to determine the effect of chemoprevention in decreasing this risk. Review of 76,333 breast pathology reports from three institutions within Partners Healthcare System, Boston, from 1987 to 2010 using natural language processing was carried out. This approach identified 2,938 women diagnosed with atypical breast lesions. The main outcome of this study is breast cancer occurrence. Of the 2,938 patients with atypical breast lesions, 1,658 were documented to have received no chemoprevention, and 184/1,658 (11.1 %) developed breast cancer at a mean follow-up of 68 months. Estimated 10-year cancer risks were 17.3 % with ADH, 20.7 % with ALH, 23.7 % with LCIS, and 26.0 % with severe ADH. In a subset of patients treated from 1999 on (the chemoprevention era), those who received no chemoprevention had an estimated 10-year breast cancer risk of 21.3 %, whereas those treated with chemoprevention had a 10-year risk of 7.5 % (p < 0.001). Chemoprevention use significantly reduced breast cancer risk for all atypia types (p < 0.05). The risk of breast cancer with atypical breast lesions is substantial. Physicians should counsel patients with ADH, ALH, LCIS, and severe ADH about the benefit of chemoprevention in decreasing their breast cancer risk.

The Necessity of Upper Extremity Neurologic Examination while Evaluating Breast Pain.

INTRODUCTION: Breast pain is one of the most frequent complaints and occurs in 45-69% of all women. Cervical disc herniation is a common cause of cervical radiculopathy with an incidence rate of 18.6 per 100,000, and it should be considered as a cause of breast pain. OBJECTIVE: To identify the extent to which upper extremity neurologic findings and cervical root disorders accompany breast pain. METHODS: We prospectively collected clinical features of patients with breast pain. An upper extremity neurologic examination was performed in patients and controls. Patients who had neurologic findings underwent cervical spine magnetic resonance imaging (MRI) to identify cervical root disorders. RESULTS: Out of the 554 participants, 233 had breast pain, and 321 were controls. Women with breast pain had more numbness (116 [49.8%] vs. 104 [32.4%], p < 0.001) and more dysesthesia (36 [15.5%] vs. 17 [5.3%], p < 0.001) than the controls, but they had similar upper extremity weakness (10 [4.3%] vs. 14 [4.4%], p > 0.05). The number of women with one neurologic finding was significantly greater in the group with breast pain (119 [51.1%] vs. 111 [34.6%], p < 0.001). Ninety (16.2%) patients underwent a cervical vertebra MRI, which showed that 86 (95.6%) patients had cervical root disorders including 21 (23.3%) cases of bulging, 9 (10%) of annular tear, and 56 (62.2%) of central disc protrusion; 4 (4.4%) patients had normal findings. The multivariate logistic regression analysis revealed that age was the only significant predictor of neurologic findings in patients with breast pain (p < 0.05, OR: 1.02, CI: 1.002-1.053). CONCLUSIONS: Cervical root disorders should be considered as a cause of extramammary breast pain.

Combination Technique Is Superior to Dye Alone in Identification of the Sentinel Lymph Node in Male Breast Cancer.

Sentinel lymph node (SLN) biopsy is the main method in staging the axilla. There are insufficient data available regarding the accuracy of an SLN biopsy in male breast cancer. The aim of this study is to evaluate whether the combination of dye and radiotracer would improve the detection rate of SLNs versus dye alone in male breast cancer patients. From February 2009 to January 2012, our SLN biopsy database was retrospectively reviewed to identify male breast cancer cases. Of the 890 SLN procedures contained in the database, 10 male breast cancer patients were identified. Patient age, body mass index, SLN biopsy technique, SLN identification, number of SLN excised, and pathology reports were reviewed. Mean age was 57.2 (34-85) years with a mean tumor size was 2.2 (1.0-4.0) cm. SLN detection ratios were two in four with blue dye and six in six with the combination technique. Overall, SLNs were identified in 8 of the 10 patients. SLN biopsy is applicable in male breast cancer cases. The addition of a radiotracer to the dye in SLN biopsy increases the detection rate of sentinel nodes in male breast cancer patients.

The feasibility of using natural language processing to extract clinical information from breast pathology reports.

OBJECTIVE: The opportunity to integrate clinical decision support systems into clinical practice is limited due to the lack of structured, machine readable data in the current format of the electronic health record. Natural language processing has been designed to convert free text into machine readable data. The aim of the current study was to ascertain the feasibility of using natural language processing to extract clinical information from >76,000 breast pathology reports. APPROACH AND PROCEDURE: Breast pathology reports from three institutions were analyzed using natural language processing software (Clearforest, Waltham, MA) to extract information on a variety of pathologic diagnoses of interest. Data tables were created from the extracted information according to date of surgery, side of surgery, and medical record number. The variety of ways in which each diagnosis could be represented was recorded, as a means of demonstrating the complexity of machine interpretation of free text. RESULTS: There was widespread variation in how pathologists reported common pathologic diagnoses. We report, for example, 124 ways of saying invasive ductal carcinoma and 95 ways of saying invasive lobular carcinoma. There were >4000 ways of saying invasive ductal carcinoma was not present. Natural language processor sensitivity and specificity were 99.1% and 96.5% when compared to expert human coders. CONCLUSION: We have demonstrated how a large body of free text medical information such as seen in breast pathology reports, can be converted to a machine readable format using natural language processing, and described the inherent complexities of the task.