Bizarre parosteal osteocondromatous proliferation (BPOP) of the acromion with soft tissue recurrence.

Bizarre parosteal osteochondromatous proliferation (BPOP) is a benign but rare periosteal-originating chondrogenic tumor. It commonly arises from the hands and feet. It is slow-growing and often presents as a painless lump. On imaging, the mass is well-marginated and almost always remains contiguous with the cortical bone. Histologically, the lesion is composed of a disorganized admixture of fibrous tissue, bone, and cartilage with bizarre features. Treatment is surgical and local recurrence is common contiguous with bone. This case report demonstrates an uncommon acromial BPOP with the first reported recurrence not contiguous with the underlying cortex.

Increased tumor-infiltrating lymphocyte density is associated with favorable outcomes in a comparative study of canine histiocytic sarcoma.

Histiocytic sarcoma (HS) is a rare and aggressive tumor in humans with no universally agreed standard of care therapy. Spontaneous canine HS exhibits increased prevalence in specific breeds, shares key genetic and biologic similarities with the human disease, and occurs in an immunocompetent setting. Previous data allude to the immunogenicity of this disease in both species, highlighting the potential for their successful treatment with immunotherapy. Quantification of CD3 tumor-infiltrating lymphocytes (TIL) in five cases of human HS revealed variable intra-tumoral T cell infiltration. Due to the paucity of human cases and lack of current model systems in which to appraise associations between anti-tumor immunity and treatment-outcome in HS, we analyzed clinical data and quantified TIL in 18 dogs that were previously diagnosed with localized HS and treated with curative-intent tumor resection with or without adjuvant chemotherapy. As in humans, assessment of TIL in biopsy tissues taken at diagnosis reveal a spectrum of immunologically "cold" to "hot" tumors. Importantly, we show that increased CD3 and granzyme B TIL are positively associated with favorable outcomes in dogs following surgical resection. NanoString transcriptional analyses revealed increased T cell and antigen presentation transcripts associated with prolonged survival in canine pulmonary HS and a decreased tumor immunogenicity profile associated with shorter survivals in splenic HS. Based on these findings, we propose that spontaneous canine HS is an accessible and powerful novel model to study tumor immunology and will provide a unique platform to preclinically appraise the efficacy and tolerability of anti-cancer immunotherapies for HS.

COVID-19 mortality prediction in the intensive care unit with deep learning based on longitudinal chest X-rays and clinical data.

OBJECTIVES: We aimed to develop deep learning models using longitudinal chest X-rays (CXRs) and clinical data to predict in-hospital mortality of COVID-19 patients in the intensive care unit (ICU). METHODS: Six hundred fifty-four patients (212 deceased, 442 alive, 5645 total CXRs) were identified across two institutions. Imaging and clinical data from one institution were used to train five longitudinal transformer-based networks applying five-fold cross-validation. The models were tested on data from the other institution, and pairwise comparisons were used to determine the best-performing models. RESULTS: A higher proportion of deceased patients had elevated white blood cell count, decreased absolute lymphocyte count, elevated creatine concentration, and incidence of cardiovascular and chronic kidney disease. A model based on pre-ICU CXRs achieved an AUC of 0.632 and an accuracy of 0.593, and a model based on ICU CXRs achieved an AUC of 0.697 and an accuracy of 0.657. A model based on all longitudinal CXRs (both pre-ICU and ICU) achieved an AUC of 0.702 and an accuracy of 0.694. A model based on clinical data alone achieved an AUC of 0.653 and an accuracy of 0.657. The addition of longitudinal imaging to clinical data in a combined model significantly improved performance, reaching an AUC of 0.727 (p = 0.039) and an accuracy of 0.732. CONCLUSIONS: The addition of longitudinal CXRs to clinical data significantly improves mortality prediction with deep learning for COVID-19 patients in the ICU. KEY POINTS: • Deep learning was used to predict mortality in COVID-19 ICU patients. • Serial radiographs and clinical data were used. • The models could inform clinical decision-making and resource allocation.

Artificial intelligence for prediction of COVID-19 progression using CT imaging and clinical data.

OBJECTIVES: Early recognition of coronavirus disease 2019 (COVID-19) severity can guide patient management. However, it is challenging to predict when COVID-19 patients will progress to critical illness. This study aimed to develop an artificial intelligence system to predict future deterioration to critical illness in COVID-19 patients. METHODS: An artificial intelligence (AI) system in a time-to-event analysis framework was developed to integrate chest CT and clinical data for risk prediction of future deterioration to critical illness in patients with COVID-19. RESULTS: A multi-institutional international cohort of 1,051 patients with RT-PCR confirmed COVID-19 and chest CT was included in this study. Of them, 282 patients developed critical illness, which was defined as requiring ICU admission and/or mechanical ventilation and/or reaching death during their hospital stay. The AI system achieved a C-index of 0.80 for predicting individual COVID-19 patients' to critical illness. The AI system successfully stratified the patients into high-risk and low-risk groups with distinct progression risks (p < 0.0001). CONCLUSIONS: Using CT imaging and clinical data, the AI system successfully predicted time to critical illness for individual patients and identified patients with high risk. AI has the potential to accurately triage patients and facilitate personalized treatment. KEY POINT: • AI system can predict time to critical illness for patients with COVID-19 by using CT imaging and clinical data.

Neoadjuvant radiation for cutaneous and soft tissue angiosarcoma.

BACKGROUND AND OBJECTIVES: Neoadjuvant radiation (NRT) is frequently utilized in soft tissue sarcomas to increase local control. Its utility in cutaneous and soft tissue angiosarcoma remains poorly defined. METHODS: This retrospective cohort study was performed using the National Cancer Database (2004-2016) evaluating patients with clinically localized, surgically resected angiosarcomas. Factors associated with receipt of NRT in the overall cohort and margin positivity in treatment naïve patients were identified by univariate and multivariable logistic regression analyses. Survival was assessed using Kaplan-Meier analysis. RESULTS: Of 597 patients, 27 (4.5%) received NRT. Increasing age (odds ratio [OR] 0.95, p = 0.025), tumor size more than or equal to 5 cm (OR 3.16, p = 0.02), and extremity tumor location (OR 3.99, p = 0.04) were associated with receipt of NRT. All patients who received NRT achieved an R0 resection (p = 0.03) compared with 17.9% of patients without NRT. Factors associated with risk of margin positivity included tumor size more than or equal to 5 cm (OR 1.85, p = 0.01), and head/neck location (OR 2.24, p = 0.006). NRT was not significantly associated with improved survival (p = 0.21). CONCLUSIONS: NRT improves rates of R0 resection but is infrequently utilized in cutaneous and soft tissue angiosarcoma. Increased usage of NRT, particularly for patients with lesions more than or equal to 5 cm, or head and neck location, may help achieve complete resections.

Evaluation of a convolutional neural network for ovarian tumor differentiation based on magnetic resonance imaging.

OBJECTIVES: There currently lacks a noninvasive and accurate method to distinguish benign and malignant ovarian lesion prior to treatment. This study developed a deep learning algorithm that distinguishes benign from malignant ovarian lesion by applying a convolutional neural network on routine MR imaging. METHODS: Five hundred forty-five lesions (379 benign and 166 malignant) from 451 patients from a single institution were divided into training, validation, and testing set in a 7:2:1 ratio. Model performance was compared with four junior and three senior radiologists on the test set. RESULTS: Compared with junior radiologists averaged, the final ensemble model combining MR imaging and clinical variables had a higher test accuracy (0.87 vs 0.64, p < 0.001) and specificity (0.92 vs 0.64, p < 0.001) with comparable sensitivity (0.75 vs 0.63, p = 0.407). Against the senior radiologists averaged, the final ensemble model also had a higher test accuracy (0.87 vs 0.74, p = 0.033) and specificity (0.92 vs 0.70, p < 0.001) with comparable sensitivity (0.75 vs 0.83, p = 0.557). Assisted by the model's probabilities, the junior radiologists achieved a higher average test accuracy (0.77 vs 0.64, Δ = 0.13, p < 0.001) and specificity (0.81 vs 0.64, Δ = 0.17, p < 0.001) with unchanged sensitivity (0.69 vs 0.63, Δ = 0.06, p = 0.302). With the AI probabilities, the junior radiologists had higher specificity (0.81 vs 0.70, Δ = 0.11, p = 0.005) but similar accuracy (0.77 vs 0.74, Δ = 0.03, p = 0.409) and sensitivity (0.69 vs 0.83, Δ = -0.146, p = 0.097) when compared with the senior radiologists. CONCLUSIONS: These results demonstrate that artificial intelligence based on deep learning can assist radiologists in assessing the nature of ovarian lesions and improve their performance. KEY POINTS: • Artificial Intelligence based on deep learning can assess the nature of ovarian lesions on routine MRI with higher accuracy and specificity than radiologists. • Assisted by the deep learning model's probabilities, junior radiologists achieved better performance that matched those of senior radiologists.

Phase II Trial of Palbociclib in Patients with Advanced Esophageal or Gastric Cancer.

LESSONS LEARNED: Palbociclib monotherapy demonstrated minimal clinical activity in patients with previously treated gastroesophageal cancers. Further clinical evaluation of palbociclib monotherapy is not warranted in gastroesophageal cancers, but improved understanding of resistance mechanisms may permit rational combination approaches. BACKGROUND: Dysregulation of the cell cycle is a hallmark of cancer. Progression through the G1/S transition requires phosphorylation of retinoblastoma (RB) by cyclin-dependent kinases (CDKs) 4 and 6, which are regulated by cyclins D and E. Amplifications of cyclin D loci and activating mutations in CDKs are frequent molecular aberrations in gastroesophageal malignancies. We conducted a phase II trial of the CDK4/6 inhibitor palbociclib as an initial test of efficacy. METHODS: Patients with previously treated metastatic gastroesophageal cancers with intact RB nuclear expression by immunohistochemistry were treated with 125 mg daily of palbociclib for days 1-21 of 28-day cycles. The primary endpoint was overall response rate. RESULTS: We screened 29 patients and enrolled 21 patients: 5 with gastric adenocarcinoma, 3 with gastroesophageal junction adenocarcinoma, 8 with esophageal adenocarcinoma, and 5 with esophageal squamous cell carcinoma. All 29 tumors screened had intact nuclear RB expression, and four treated patients tested positive for CCND1 overexpression. No objective responses were seen. Median progression-free survival was 1.8 months, and median overall survival was 3.0 months. All recurrent grade 3 or 4 toxicities were hematologic, with neutropenia in eight patients (38%), anemia in four patients (19%), and thrombocytopenia in two patients (10%). CONCLUSION: Palbociclib has limited single-agent activity in gastroesophageal tumors.

CDH2/N-cadherin and early diagnosis of invasion in patients with ductal carcinoma in situ.

PURPOSE: This proof-of-concept study investigates gene expression in core needle biopsies (CNB) to predict whether individuals diagnosed with ductal carcinoma in situ (DCIS) on CNB were affected by invasion at the time of diagnosis. METHODS: Using a QuantiGene Plex 2.0 assay, 14 gene expression profiling was performed in 303 breast tissue samples. Preoperative diagnostic performance of a gene was measured by area under receiver-operating characteristic curve (AUC) with 95% confidence interval (CI). The gene mRNA positivity cutoff was computed using Gaussian mixture model (GMM); protein expression was measured by immunohistochemistry; DNA methylation was evaluated by targeted bisulfite sequencing. RESULTS: mRNA from 69% (34/49) mammoplasties, 72% (75/104) CNB DCIS, and 89% (133/150) invasive breast cancers (IBC) were analyzed. Based on pre-and post-surgery DCIS chart reviews, 21 cases were categorized as DCIS synchronous with invasion and 54 DCIS were pure DCIS without pathologic evidence of invasive disease. The ectopic expression of neuronal cadherin CDH2 was probable in 0% mammoplasties, 6% pure DCIS, 29% synchronous DCIS, and 26% IBC. The CDH2 mRNA positivity in preoperative biopsies showing pure DCIS was predictive of a final diagnosis of invasion (AUC = 0.67; 95% CI 0.53-0.80; P = 0.029). Site-specific methylation of the CDH2 promoter (AUC = 0.76; 95% CI 0.54-0.97; P = 0.04) and measurements of N-cadherin, a pro-invasive cell-cell adhesion receptor encoded by CDH2 (AUC = 0.8; 95% CI 0.66-0.99; P < 0.005) had a discriminating power allowing for discernment of CDH2-positive biopsy. CONCLUSIONS: Evidence of CDH2/N-cadherin expression, predictive of invasion synchronous with DCIS, may help to clarify a diagnosis and direct the course of therapy earlier in a patient's care.

Conjunctival 'mucoepidermoid carcinoma' revisited: a revision of terminology, based on morphologic, immunohistochemical and molecular findings of 14 cases, and the 2018 WHO Classification of Tumours of the Eye.

In 2018, the consensus meeting for the WHO Classification of Tumours of the Eye decided that conjunctival mucoepidermoid carcinoma should be reclassified as adenosquamous carcinoma, as this represented a better morphological fit. To examine the applicability of this terminology, we studied the clinical, histopathological, immunohistochemical and molecular pathology of 14 cases that were originally diagnosed as conjunctival mucoepidermoid carcinoma. There were 7 (50%) females and 7 (50%) males. The median age was 64 years. The left eye was affected in 8 and the right eye in 6 patients. In-situ carcinoma was present in 11/14 (79%) cases and comprised in-situ squamous cell carcinoma (SCC) and conjunctival intraepithelial neoplasia with mucinous differentiation (CIN-Muc). Invasive carcinoma was present in 11/14 (79%) cases. Group 1 (1/11 cases, 9%) comprised invasive SCC only. Group 2 (6/11 cases, 55%) comprised SCC with mucinous differentiation, manifesting as scattered intracellular mucin, occasionally together with intercellular mucin, with no evidence of true glandular differentiation. Group 3 (3/11 cases. 27%) comprised true adenosquamous carcinoma. Group 4 (1/11 cases, 9%) comprised pure adenocarcinoma. Thirteen of 14 cases (93%) underwent FISH for MAML2 translocation and none were rearranged. Two cases harboured high-risk HPV (type 16 and 18). The combined findings confirm that all lesions in our study were not mucoepidermoid carcinoma, but represented predominantly SCC with mucinous differentiation and adenosquamous carcinoma. We, therefore, recommend future revision of the WHO classification to include SCC with mucinous differentiation alongside adenosquamous carcinoma.

Deep Learning Based on MRI for Differentiation of Low- and High-Grade in Low-Stage Renal Cell Carcinoma.

Pretreatment determination of renal cell carcinoma aggressiveness may help to guide clinical decision-making. PURPOSE: To evaluate the efficacy of residual convolutional neural network using routine MRI in differentiating low-grade (grade I-II) from high-grade (grade III-IV) in stage I and II renal cell carcinoma. STUDY TYPE: Retrospective. POPULATION: In all, 376 patients with 430 renal cell carcinoma lesions from 2008-2019 in a multicenter cohort were acquired. The 353 Fuhrman-graded renal cell carcinomas were divided into a training, validation, and test set with a 7:2:1 split. The 77 WHO/ISUP graded renal cell carcinomas were used as a separate WHO/ISUP test set. FIELD STRENGTH/SEQUENCE: 1.5T and 3.0T/T2 -weighted and T1 contrast-enhanced sequences. ASSESSMENT: The accuracy, sensitivity, and specificity of the final model were assessed. The receiver operating characteristic (ROC) curve and precision-recall curve were plotted to measure the performance of the binary classifier. A confusion matrix was drawn to show the true positive, true negative, false positive, and false negative of the model. STATISTICAL TESTS: Mann-Whitney U-test for continuous data and the chi-square test or Fisher's exact test for categorical data were used to compare the difference of clinicopathologic characteristics between the low- and high-grade groups. The adjusted Wald method was used to calculate the 95% confidence interval (CI) of accuracy, sensitivity, and specificity. RESULTS: The final deep-learning model achieved a test accuracy of 0.88 (95% CI: 0.73-0.96), sensitivity of 0.89 (95% CI: 0.74-0.96), and specificity of 0.88 (95% CI: 0.73-0.96) in the Fuhrman test set and a test accuracy of 0.83 (95% CI: 0.73-0.90), sensitivity of 0.92 (95% CI: 0.84-0.97), and specificity of 0.78 (95% CI: 0.68-0.86) in the WHO/ISUP test set. DATA CONCLUSION: Deep learning can noninvasively predict the histological grade of stage I and II renal cell carcinoma using conventional MRI in a multiinstitutional dataset with high accuracy. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY STAGE: 2.

Ablation Therapy for Advanced Stage Non-Small Cell Lung Cancer: A National Cancer Database Study.

PURPOSE: To compare overall survival (OS) of ablation with no treatment for patients with advanced stage non-small cell lung cancer. METHODS: Patients with clinical stage IIIB (T1-4N3M0, T4N2M0) and stage IV (T1-4N0-3M1) non-small cell lung cancer, in accordance with the American Joint Committee on Cancer, 7th edition, who did not receive treatment or who received ablation as their sole primary treatment besides chemotherapy from 2004 to 2014, were identified from the National Cancer Data Base. OS was estimated using the Kaplan-Meier method and evaluated by log-rank test, univariate and multivariate Cox proportional hazard regression, and propensity score-matched analysis. Relative survival analyses comparing age- and sex-matched United States populations were performed. RESULTS: A total of 140,819 patients were included. The 1-, 2-, 3- and 5-year survival rates relative to age- and sex-matched United States population were 28%, 18%, 12%, and 10%, respectively, for ablation (n = 249); and 30%, 15%, 9%, and 5%, respectively for no treatment (n = 140,570). Propensity score matching resulted in 249 patients in the ablation group versus 498 patients in the no-treatment group. After matching, ablation was associated with longer OS than that in the no-treatment group (median, 5.9 vs 4.7 months, respectively; hazard ratio, 0.844; 95% confidence interval, 0.719-0.990; P = .037). These results persisted in patients with an initial tumor size of ≤3 cm. CONCLUSIONS: Preliminary results suggest ablation may be associated with longer OS in patients with late-stage non-small cell lung cancer than survival in those who received no treatment.

Machine learning reveals multimodal MRI patterns predictive of isocitrate dehydrogenase and 1p/19q status in diffuse low- and high-grade gliomas.

PURPOSE: Isocitrate dehydrogenase (IDH) and 1p19q codeletion status are importantin providing prognostic information as well as prediction of treatment response in gliomas. Accurate determination of the IDH mutation status and 1p19q co-deletion prior to surgery may complement invasive tissue sampling and guide treatment decisions. METHODS: Preoperative MRIs of 538 glioma patients from three institutions were used as a training cohort. Histogram, shape, and texture features were extracted from preoperative MRIs of T1 contrast enhanced and T2-FLAIR sequences. The extracted features were then integrated with age using a random forest algorithm to generate a model predictive of IDH mutation status and 1p19q codeletion. The model was then validated using MRIs from glioma patients in the Cancer Imaging Archive. RESULTS: Our model predictive of IDH achieved an area under the receiver operating characteristic curve (AUC) of 0.921 in the training cohort and 0.919 in the validation cohort. Age offered the highest predictive value, followed by shape features. Based on the top 15 features, the AUC was 0.917 and 0.916 for the training and validation cohort, respectively. The overall accuracy for 3 group prediction (IDH-wild type, IDH-mutant and 1p19q co-deletion, IDH-mutant and 1p19q non-codeletion) was 78.2% (155 correctly predicted out of 198). CONCLUSION: Using machine-learning algorithms, high accuracy was achieved in the prediction of IDH genotype in gliomas and moderate accuracy in a three-group prediction including IDH genotype and 1p19q codeletion.

A Comparison of Cryoablation with Heat-Based Thermal Ablation for Treatment of Clinical T1a Renal Cell Carcinoma: A National Cancer Database Study.

PURPOSE: To compare the overall survival (OS) of patients receiving cryoablation versus heat-based thermal ablation for clinical T1a renal cell carcinoma (RCC) in a large national cohort. MATERIALS AND METHODS: Patients with RCC from 2004 to 2014 who were treated with ablation were identified from the National Cancer Database. OS was estimated with the use of the Kaplan-Meier method and evaluated by means of log-rank test, univariate and multivariate Cox proportional hazard regression, and propensity score-matched analysis. RESULTS: A total of 3,936 patients who received cryoablation and 2,322 who received heat-based thermal ablation met the inclusion criteria. The mean age was 67 ± 12 year, and the mean size of tumors was 25 ± 8 mm. The 3-, 5-, and 10-year survival rates were, respectively, 91%, 82%, and 62% for cryoablation and 89%, 81%, and 55% for heat-based thermal ablation. After propensity score matching, cryoablation was associated with longer OS compared with heat-based thermal ablation (median 11.3 vs 10.4 years; hazard ratio 1.175, 95% CI 1.03-1.341; P = .016). For patients with tumors ≤2 cm, propensity score-matched analyses demonstrated no significant difference between the 2 treatment groups (P = .772). CONCLUSIONS: Overall, cryoablation may be associated with longer OS compared with heat-based thermal ablation in cT1a RCC. No significant difference in survival rates was observed between the 2 treatments for patients with tumor sizes ≤2 cm. Owing to the inherent limitations of this study, further study with details on technology, local outcome, and complications is needed.

Comparison of Mohs Surgery and Surgical Excision in the Treatment of Localized Sebaceous Carcinoma.

BACKGROUND: It remains controversial if Mohs surgery is superior to surgical excision in treating localized sebaceous carcinoma. OBJECTIVE: To compare Mohs surgery and surgical excision for treating patients with localized sebaceous carcinoma. MATERIALS AND METHODS: The US National Cancer Database was used to identify patients with histologically confirmed Stage 0 to 2 sebaceous carcinoma from 2004 to 2014. Clinicopathologic and socioeconomic factors were compared between treatment groups using the chi-square test. Overall survival (OS) was evaluated by log-rank test, multivariable Cox proportional hazard regression, and propensity score-matched analysis. Relative survival analyses compared with age- and sex-matched US population were performed. RESULTS: Of 1,265 patients, 234 received Mohs surgery and 1,031 received surgical excision. Mohs surgery had a higher rate of negative margin (p = .004). On multivariate Cox regression analysis, Mohs surgery was associated with longer OS than surgical excision (HR: 0.703, 95% CI: 0.496-0.995, p = .047). The survival benefit of Mohs surgery persisted on relative survival analysis and propensity score-matched analysis (p = .0385), after matching the 2 groups on patient and disease characteristics. CONCLUSION: Patients who received Mohs surgery had significantly longer OS when compared with those who received surgical excision. Prospective clinical trials comparing these treatment paradigms are warranted.

Orbital Atypical Lipomatous Tumor/Well-Differentiated Liposarcoma Masquerading as Pleomorphic Lipoma: A Diagnostic Challenge.

Atypical lipomatous tumor/well-differentiated liposarcoma is a common neoplasm of the superficial and deep soft tissues of the extremities, trunk, and retroperitoneum. Atypical lipomatous tumor/well-differentiated liposarcoma is very rare in the orbit, with only 19 previously reported cases. The authors describe a 22-year-old woman who presented with an 8-month history of diplopia and was found to have an orbital mass on MRI. The excised tumor initially was interpreted as spindle cell/pleomorphic lipoma based on its morphologic and immunohistochemical features. Nine years later, the patient returned with a recurrence that required surgical debulking. Histopathologic and molecular cytogenetic evaluation of both primary and recurrent lesions disclosed Atypical lipomatous tumor/well-differentiated liposarcoma. This case highlights the diagnostic challenges and the importance of molecular genetic studies in evaluation of fatty orbital tumors.

Disease site as a determinant of survival outcome in patients with systemic anaplastic lymphoma kinase positive anaplastic large cell lymphoma with extranodal involvement: an analysis of 1306 cases from the US National Cancer Database.

Systemic anaplastic lymphoma kinase positive (ALK+) anaplastic large cell lymphoma with extranodal involvement (ALCL-E) is a rare form of non-Hodgkin lymphoma. No large study in the literature has compared the survival outcomes among different primary extranodal sites of involvement in ALK+ ALCL-E. We identified 1306 patients with ALK+ ALCL-E diagnosed between 2004 and 2014 in the US National Cancer Database, among whom 387 had primary extranodal site in the chest/abdomen/pelvis, 103 in the bone, 62 in the central nervous system, 134 in the head and neck and 620 in the cutaneous/soft tissue. Younger age, lower Charlson-Deyo score, lower clinical stage, receipt of chemotherapy and receipt of radiotherapy were predictors of longer overall survival. Patients with extranodal involvement of central nervous system and chest/abdomen/pelvis had shorter overall survival than those with involvement of head and neck, bone, and cutaneous/subcutaneous tissue after adjusting for confounding variables. We recommend treating these patients upfront with more aggressive therapy.

Ethnic disparity in primary cutaneous CD30+ T-cell lymphoproliferative disorders: an analysis of 1496 cases from the US National Cancer Database.

Primary cutaneous CD30+ T cell lymphoproliferative disorders (PCLPD), the second most common type of primary cutaneous T cell lymphomas, accounts for approximately 25-30% of cutaneous T-cell lymphoma cases. However, only small retrospective studies have been reported. We aimed to identify prognostic factors and evaluate the overall survival (OS) of patients with PCLPD stratified by ethnicity. We identified 1496 patients diagnosed with PCLPD between 2004 and 2014 in the US National Cancer Database. Chi-square test and anova were used to evaluate differences in demographic and disease characteristics, socioeconomic factors and treatments received. OS was evaluated with the log-rank test, Cox proportional hazard regression analysis, and propensity score matching. The study included 1267 Caucasians, 153 African Americans (AA), 43 Asians, and 33 of other/unknown ethnicity. Older age, higher Charlson-Deyo score, higher clinical stage and receipt of chemotherapy were predictors of shorter OS. Primary disease site on a lower extremity was associated with shorter OS, while a head and neck location was associated with longer OS. AA patients had shorter OS when compared to Caucasian patients on multivariate analysis. This ethnic disparity persisted on propensity-score matched analysis and after matching Caucasian and AA patients on demographic and disease characteristics, socioeconomic factors and treatments received, and age and gender-matched relative survival analyses.

Impact of Neoadjuvant Chemotherapy on Breast Cancer Subtype: Does Subtype Change and, if so, How? : IHC Profile and Neoadjuvant Chemotherapy.

BACKGROUND: Breast cancer subtype, as determined by the expression of estrogen receptor (ER) and progesterone receptor (PR), together defined as hormone receptor (HR) status, and the HER2/neu receptor (HER2), is important in predicting prognosis and guiding therapy. Knowledge regarding how tumors evolve during treatment and whether subtype is influenced by neoadjuvant chemotherapy (nCT) is limited. The purpose of this study was to compare the HR and HER2 status between core needle biopsy and residual tumor after surgery of breast cancer patients treated with nCT and to evaluate the impact of status change on therapeutic management. METHODS: After institutional review board approval, we performed a retrospective review of all patients with a diagnosis of breast cancer who received nCT and had their initial biopsy and post-nCT surgical specimens evaluated for tumor subtype between January 2009 and December 2014 at our institution. Immunohistochemistry (IHC) of ER, PR, HER2, and fluorescence in situ hybridization for HER2 expression, when indicated, was performed using identical technique and measured by a single pathologist who specializes in breast pathology. Pre- and post-nCT subtype was cross-tabulated to assess change. Standard diagnostic metrics were computed. RESULTS: Fifty-two patients with 54 cancers were identified to have their initial biopsy and post-nCT surgical specimens evaluated for tumor subtype in identical fashion. There was a complete pathologic response after nCT in 23 cancers (42.6%). Residual disease was noted in 31 cancers (57.4%). Five of these (16.1%) had a change in tumor subtype, of which four changes were based on IHC. HR status changed from positive to negative in two cases and from negative to positive in one case. HER2 status changed from positive to negative in one case and from negative to positive in one case. Subtype change led to treatment change in all five cases, with either the addition or discontinuation of adjuvant therapies. CONCLUSIONS: Patients with breast cancer may experience alterations in their tumor subtype after nCT. At our institution, this led to a change in adjuvant treatment in 100% of such patients. This implies that retesting receptor status of residual tumors after nCT should be routinely performed to tailor adjuvant therapy after nCT.

Prediction of Residual Nodal Disease at Completion Dissection Following Positive Sentinel Lymph Node Biopsy for Melanoma.

INTRODUCTION: While recent trial data have demonstrated no survival benefit to immediate completion lymph node dissection (CLND) for positive sentinel lymph node (SLN) disease in melanoma, prediction of non-SLN disease may help risk-stratify patients for more intensive observation of the nodal basin. PATIENTS AND METHODS: A retrospective cohort of patients with positive SLN biopsy (SLNB) who underwent CLND was identified (1996-2016). A risk score for likelihood of CLND-positive disease was developed based on factors associated with presence of CLND metastases identified on logistic regression. Survival outcomes were analyzed. RESULTS: Among 312 patients with positive SLN, 192 underwent CLND and had complete pathologic data for evaluation. The median age of the study cohort was 53 years [interquartile range (IQR) 43-66 years], and 112 (58%) were male. Thirty-one (16%) had non-SLN metastatic disease on CLND. The four factors independently associated with CLND positivity and thus included in the risk score were Breslow thickness ≥ 3 mm [odds ratio (OR) 2.56, p = 0.047], presence of primary tumor-infiltrating lymphocytes (OR 0.33, p = 0.013), ≥ 2/3 positive-to-total SLN ratio (OR 4.35, p = 0.003), and combined subcapsular and parenchymal metastatic SLN location or metastatic deposit ≥ 1 mm (OR 4.45, p = 0.013). The four-point risk score predicted CLND positivity well with area under the curve of 0.82 (0.80-0.85). Increasing risk score was independently associated with increasingly worse melanoma-specific survival [hazard ratio (HR) = 1.54, p = 0.001]. CONCLUSIONS: Likelihood of residual nodal disease after positive SLNB and survival can be predicted from primary tumor and SLN characteristics. High-risk patients may warrant more intensive surveillance of the nodal basin to reduce risk of loss of regional control.

MYB rearrangement and immunohistochemical expression in adenomyoepithelioma of the breast: a comparison with adenoid cystic carcinoma.

AIMS: Adenomyoepithelioma (AME) and adenoid cystic carcinoma (ACC) of the breast have been noted to occur simultaneously, raising the possibility that AME may represent a related or precursor lesion to ACC. ACC frequently harbours genetic rearrangement of the MYB gene. We sought to clarify the relationship between AME and ACC by comparing their rates of MYB expression by IHC and MYB rearrangement by FISH. METHODS AND RESULTS: IHC and FISH for MYB rearrangement were performed on paraffin-embedded sections of 11 breast ACCs, 11 non-breast ACCs and 11 breast-AMEs. Using FISH, five of eight (63%) interpretable breast ACCs demonstrated MYB gene rearrangement. Nine of 11 (81%) breast ACCs demonstrated MYB expression (range = 20-95%). Of the three FISH-negative breast ACCs, two were solid variant and demonstrated strong MYB expression by IHC. Of the 10 interpretable non-breast ACCs, six showed MYB rearrangement, all of which were conventional type. Nine of these 11 (81%) cases showed MYB immunoexpression (range = 10-90%), including three solid-variant cases which were negative by FISH. No MYB rearrangements were detected by FISH in 10 interpretable AMEs. However, three of 11 cases (27%) showed weak to moderate MYB expression by IHC (range = 10-40%). CONCLUSIONS: Our results indicate that AMEs do not harbour MYB gene rearrangement. IHC for MYB may be helpful in diagnosing FISH-negative cases of ACC, particularly the diagnostically more difficult solid variants. However, weak to moderate MYB expression in a subset of AMEs highlights not only a potential diagnostic pitfall, but also shared pathophysiology with ACC worth investigating further at the genomic level.