Objective: A 31-gene expression profile (GEP) test that has been clinically validated identifies melanoma patients with low (Class 1) or high (Class 2) risk of metastasis based on primary tumor biology.  This study aimed to prospectively evaluate the test impact on clinical management of melanoma patients.Methods:  Physicians at 16 dermatology, surgical or medical oncology centers examined patients to assess clinical features of the primary melanoma.  Recommendations for clinical follow-up and surveillance were collected.  Following consent of the patient and performance of the GEP test, recommendations for management were again collected, and pre- and post-test recommendations were assessed to determine changes in management resulting from the addition of GEP testing to traditional clinicopathologic risk factors.   Results:  Post-test management plans changed for 49% (122 of 247) of cases in the study when compared to pre-test plans. Thirty-six percent (66 of 181) of Class 1 cases had a management change, compared to 85% (56 of 66) of Class 2 cases.  GEP class was a significant factor for change in care during the study (p<0.001), with Class 1 accounting for 91% (39 of 43) of cases with decreased management intensity, and Class 2 accounting for 72% (49 of 68) of cases with increases.Conclusions: The reported study show that the 31-gene GEP test improves net health outcomes in the management of cutaneous melanoma.  Physicians used test results to guide risk-appropriate changes that match the biological risk of the tumor, including directing more frequent and intense surveillance to high-risk, Class 2 patients.

PURPOSE National guidelines recommend sentinel lymph node biopsy (SLNB) be offered to patients with > 10% likelihood of sentinel lymph node (SLN) positivity. On the other hand, guidelines do not recommend SLNB for patients with T1a tumors without high-risk features who have < 5% likelihood of a positive SLN. However, the decision to perform SLNB is less certain for patients with higher-risk T1 melanomas in which a positive node is expected 5%-10% of the time. We hypothesized that integrating clinicopathologic features with the 31-gene expression profile (31-GEP) score using advanced artificial intelligence techniques would provide more precise SLN risk prediction. METHODS An integrated 31-GEP (i31-GEP) neural network algorithm incorporating clinicopathologic features with the continuous 31-GEP score was developed using a previously reported patient cohort (n = 1,398) and validated using an independent cohort (n = 1,674). RESULTS Compared with other covariates in the i31-GEP, the continuous 31-GEP score had the largest likelihood ratio (G2 = 91.3, P < .001) for predicting SLN positivity. The i31-GEP demonstrated high concordance between predicted and observed SLN positivity rates (linear regression slope = 0.999). The i31-GEP increased the percentage of patients with T1-T4 tumors predicted to have < 5% SLN-positive likelihood from 8.5% to 27.7% with a negative predictive value of 98%. Importantly, for patients with T1 tumors originally classified with a likelihood of SLN positivity of 5%-10%, the i31-GEP reclassified 63% of cases as having < 5% or > 10% likelihood of positive SLN, for a more precise, personalized, and clinically actionable SLN-positive likelihood estimate. CONCLUSION These data suggest the i31-GEP could reduce the number of SLNBs performed by identifying patients with likelihood under the 5% threshold for performance of SLNB and improve the yield of positive SLNBs by identifying patients more likely to have a positive SLNB.

OBJECTIVE.Fine-needle aspiration and stereotaxic needle core biopsy (SNCB) are techniques used in the workup of breast lesions suggestive of cancer. Many surgeons are reluctant to rely on fine needle results, and until now, SNCB could be done only with a dedicated biopsy

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In order to determine if intraoperative ultrasound (US)-guided excision is a feasible procedure, we prospectively studied 15 female patients between July 1996 and December 1998 for US-detected nonpalpable breast lesions. Intraoperative US was used by the operating surgeon to identify the lesion, guide its excision, and evaluate the specimen to document complete removal. A control group of 15 female patients with mammographically detected nonpalpable lesions was used for comparison. These patients underwent preoperative needle localization, excision of the lesions, and specimen radiographs. Age, size of the lesion, total excised tissue volume, and operative time were documented in all cases. Fifteen patients aged 20-83 years (mean 51) underwent US-guided excision, which adequately localized all lesions, and excision was successful in all patients. Specimen US documented the lesion in all cases. Lesion size ranged from 0.7 to 2 cm (mean 1.1) and the total excised tissue volume averaged 30 cc. Mean operative time was 53 minutes (range 30-75 minutes). The 15 patients of the control group ranged in age from 32 to 82 years (mean 61). Excision was successful in all cases. Lesion size ranged from 1 to 2.5 cm (average 1.5) and the average excised tissue volume was 35 cc. Mean operative time was 50 minutes (range 30-75 minutes). There were no statistically significant differences between the two groups with regard to age (p = 0.2), operative time (p = 0.5), and total excised tissue volume (p = 0.5). The size of the lesions did have a statistically significant difference (p = 0.01). There were no perioperative complications. In conclusion, US-guided excision of nonpalpable breast lesions is a feasible and effective technique. US documents results immediately, is of minimal discomfort to the patient, avoids the need for preoperative localization, allows the entire procedure to be performed in the operating room, does not require radiation, and provides the surgeon with a useful alternative in selected cases.