Citations

689 Background: The role of antiangiogenic agents in advanced RCC is well established. However, it is still not clear whether this benefit can be extrapolated to the adjuvant setting. In this meta-analysis of 3 randomized control trials (RCTs), we sought to determine the efficacy of these agents in RCC patients who underwent nephrectomy with high risk of relapse. Methods: We searched three databases, including Pubmed, Embase, and Cochrane Central Register of Controlled Trials to identify RCTs comparing antiangiogenic agents to placebo in post-nephrectomy RCC patients. We evaluated: 1) the effect of antiangiogenics in highest risk groups as defined by individual studies; 2) the role of each agent separately; and 3) the effect in clear-cell RCC population. Outcomes of interest included overall survival (OS) and disease-free survival (DFS). The overall effect was pooled using the DerSimonian and Laird random effects models Results: Three RCTs (N = 3693 patients) were identified. All studies were comparing placebo to antiangiogenics: sunitinib, sorafenib, and pazopanib. Overall, antiangiogenics did not improve DFS (HR 0.92, 95% CI 0.78 to 1.07) or OS (HR 0.99, 95% CI 0.79 to 1.25). These results persisted when restricting the analysis to patients with clear cell carcinoma and patients with highest risk of relapse. Similarly, sunitinib did not show any improvement in the entire studied group for either DFS (HR 0.89, 95% CI 0.67 to 1.19) or OS (HR 1.11, 95% CI 0.90 to 1.37). In addition, when restricting the analysis to the high risk group, sunitinib did not show any advantage in terms of DFS (HR 0.85, 95% CI 0.67 to 1.07) and OS (HR 1.04, 95% CI 0.83 to 1.31). Conclusions: Based on the available evidence, antiangiogenics do not seem to add an advantage over placebo in terms of OS and DFS in high risk RCC patients after nephrectomy. Further studies are needed to identify the patient population which might derive a benefit from antiangiogenics in the adjuvant setting.

Abstract OBJECTIVE: Currently, no study has assessed the performance of contrast-enhanced spectral mammography (CESM) in evaluating tumor response in breast cancer patients undergoing neoadjuvant systemic therapy (NST). This study aims to evaluate whether the accuracy of CESM is comparable to MRI in detection of residual breast cancer following NST. MATERIALS AND METHODS: Retrospective review of CESM cases at our institution between September 2014 and June 2016 identified patients who had both CESM and MRI pre- and post-NST with pathologic assessment after surgical management. Size of residual malignancy (if any) on post-neoadjuvant CESM and MRI was compared to surgical pathology (reference standard). Pathologic complete response (pCR) was documented and compared to Residual Cancer Burden (RCB) score for confirmation. Bland-Altman plots were used to visualize the differences between CESM/MRI and pathologic tumor size. RESULTS: Forty female patients met inclusion criteria. Mean age was 52.3 years (range 35-73). Type of NST included: 34 (85%) chemotherapy and 6 (15%) endocrine therapy. Histological analysis showed invasive ductal carcinoma in 38 (95%), the remaining cases consisted of one invasive lobular carcinoma, and one mixed invasive carcinoma. Mean tumor size after NST was 10.3 mm (range 0-75 mm) for CESM and 9.7 mm (range 0-60 mm) for MRI compared to 15.7 mm (range 0-100 mm) on final surgical pathology. Equivalence tests demonstrated that the mean tumor size measured by CESM or by MRI is equivalent to the mean tumor size measured by pathology within -1 and 1 cm range (p=0.0132 for CESM and p=0.0194 for MRI). Difference in Measurement Post-NST Compared to Pathology Path Tumor Size (mm)CESM Tumor Size (mm)MRI Tumor Size (mm)Mean (SD)15.7 (24.5)10.3 (18.9)9.7 (16.3)Difference Compared with Path (SD); P value -5.4 (12.6); 0.0132-6.0 (11.7); 0.0194 A complete radiologic response was seen in 25 CESM and 22 MRI cases which was confirmed by pathology in 17 and 14, respectively. Alternatively, CESM and MRI demonstrated residual disease in 15 patients and 18 patients respectively and this was confirmed on pathology in 15 and 15, respectively. Accuracy of CESM vs. MRIModalityResidual Disease by Pathology (N=23)Complete Response by Pathology (N=17)SensitivitySpecificityPPVNPVResidual Disease by CESM (N=15)150Complete Response by CESM (N=25)81765.2%100%100%68%Residual Disease by MRI (N=18)153Complete Response by MRI (N=22)81465.2%82.4%83.3%63.6% All patients who achieved a pCR had an RCB score of 0 indicating no residual cancer in lymph nodes. Among patients with residual disease, their mean RCB score was 2.6 (range 0.8-4.18). CONCLUSION: In this study, CESM was comparable to MRI in assessing residual malignancy after completion of NST, thereby offering a potentially faster and less expensive alternative to MRI for monitoring treatment response in the neoadjuvant setting. Citation Format: Hilal T, Covington M, Sugi M, Zhang N, Pockaj B, Northfelt D, Ocal IT, Patel BK. Contrast-enhanced spectral mammography is comparable to MRI in the assessment of residual breast cancer following neoadjuvant systemic therapy [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr PD2-11.

Abstract OBJECTIVE: Neoadjuvant endocrine therapy (NET) is increasingly used for the treatment of low and intermediate grade, hormone receptor positive, HER2 negative breast cancer. Several MRI phenotypes that may predict response to neoadjuvant chemotherapy (NAC) have been identified, but little data exists for phenotypes associated with response to NET. This study analyzed imaging phenotypes for all patients treated with NET with the aim to identify specific features that can be predictive of response to therapy. MATERIALS AND METHODS: The study was retrospective and included 21 patients with clinical stage I, II, and III breast cancer. The tumors were grade 1 or 2, estrogen receptor (ER) positive in >20% of cells, and HER2 non-amplified. MRI examinations were performed in all women before NET. MRI interpretation included mass shape, non-mass enhancement (NME) pattern, background parenchymal enhancement, and MRI phenotype (I well-defined unicentric mass; II well defined multilobulated mass; III area enhancement with nodularity; IV area enhancement without nodularity; V septal spreading). Type of neoadjuvant endocrine therapy included: tamoxifien alone, an aromatase inhibitor (AI) alone, AI + ovarian suppression, and AI + a non-chemotherapeutic agent. Patients received NET for a total duration ranging between 3 - 6 months, with one patient receiving therapy for 18 months. Clinically meaningful response was defined as stable or decreased tumor size by clinical exam and confirmed at resection by comparing final pathologic T stage with clinical T stage. RESULTS: Twenty-one patients were identified. Median age was 62 (range 36-84) years. Most were post-menopausal 17 (81%). Pre-neoadjuvant meadian tumor size on MRI was 3.9 (range 1.0-7.5) cm and comprised T1 3 (14.3%), T2 8 (38.1%), T3/4 10 (47.6%). Pre-treatment N stage was N0 14 (66.7%), N1 7 (33.3%) and pre-NET stage was I in 3 (14.3%), II in 8 (38.1%), and III in 10 (47.6%) patients. The majority 17 (81%) had some tumor reduction, and 4 (19%) had no response. No one achieved a complete response. Of the 17 responders, 7 (41%) had a good response defined as >25% decrease in tumor size. Median tumor size after NET was 3.1 (range 0.6-11) cm and the distribution of T stage was T1 7 (33.3%), T2 9 (42.9%), and T3/4 5 (23.8%). Eleven of 12 (92%) patients with well-defined phenotypes had a response as compared to 6 of 9 (67%) patients with non-well defined phenotypes. Phenotype was not predictive of a good response to therapy, 4 were in the well-defined phenotype and 3 were in the non-well defined phenotype groups. All 4 non-responders had moderate or marked background enhancement as compared to 5 of 17 responders (p = 0.02). CONCLUSION: A well-defined pre treatment MRI phenotype was significantly predictive of a positive response to NET, while a non well-defined MRI phenotype and higher degree of background enhancement was significantly predictive of negative response to NET. This warrants further prospective evaluation, especially in association with Ki-67 levels. If validated, pre treatment MRI phenotype can be applied in the clinical decision to either initiate NET or referral for upfront surgical resection. Citation Format: Hilal T, Covington M, Pockaj B, Northfelt D, Wu T, Zwart C, Li J, Patel BK. Pre-neoadjuavnt therapy MRI phenotype can predict response to neoadjuvant endocrine therapy [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P4-02-03.

Neuroendocrine tumors (NETs) are rare neoplasms that can arise from any tissue. They are classified based on embryonic gut derivative (i.e. foregut, midgut and hindgut) with midgut tumors being the most common (e.g. gastrointestinal NET). The second most common category of NETs is that which arises from the lung. In fact, 25% of primary lung cancers are NETs, including small cell lung cancer (SCLC), which comprises 20% of all lung cancers. The remaining 5% are large cell neuroendocrine cancer (LCNEC, 3%), typical carcinoids (TCs, 1.8%), and atypical carcinoids (ACs, 0.2%). The less common TCs/ACs are well differentiated lung NETs. Their incidence has been increasing in more recent years and although these tumors are slow growing, advanced disease is associated with poor survival. There have been advances in classification of lung NETs that have allowed for more appropriate management upfront. They are cured by surgical resection when disease is limited. However, advanced and metastatic disease requires medical therapy that is ever changing and expanding. In this review, the aim is to summarize the current understanding and classification of well differentiated lung NETs (i.e. TCs and ACs), and focus on recent updates in medical management of advanced disease, along with a brief discussion on potential future discoveries.