Citations

AbstractEsthesioneuroblastoma is a rare malignancy originating from the olfactory epithelium. Treatment consists of surgical resection with strong consideration for adjuvant treatment in advanced Kadish stage and high Hyams grade. In the modern era, overall outcomes for esthesioneuroblastoma are favorable compared with many other sinonasal malignancies with 5-year overall survival estimated to be 80%. When selecting the optimal surgical approach, the surgeon must consider the approach that will allow for a negative margin resection and adequate reconstruction. In appropriately selected patients, endoscopic outcomes appear at least equivalent to open approaches and unilateral endoscopic approach may be used in select olfactory preservation cases.

OBJECTIVES To evaluate risk factors for postdischarge sequelae in children and adolescents hospitalized for acute coronavirus disease 2019 (COVID-19) or multisystem inflammatory syndrome in children (MIS-C). METHODS Multicenter prospective cohort study conducted in 25 United States pediatric hospitals. Patients <21-years-old, hospitalized May 2020 to May 2021 for acute COVID-19 or MIS-C with follow-up 2 to 4 months after admission. We assessed readmissions, persistent symptoms or activity impairment, and new morbidities. Multivariable regression was used to calculate adjusted risk ratios (aRR) and 95% confidence intervals (CI). RESULTS Of 358 eligible patients, 2 to 4 month survey data were available for 119 of 155 (76.8%) with acute COVID-19 and 160 of 203 (78.8%) with MIS-C. Thirteen (11%) patients with acute COVID-19 and 12 (8%) with MIS-C had a readmission. Thirty-two (26.9%) patients with acute COVID-19 had persistent symptoms (22.7%) or activity impairment (14.3%) and 48 (30.0%) with MIS-C had persistent symptoms (20.0%) or activity impairment (21.3%). For patients with acute COVID-19, persistent symptoms (aRR, 1.29 [95% CI, 1.04–1.59]) and activity impairment (aRR, 1.37 [95% CI, 1.06–1.78]) were associated with more organ systems involved. Patients with MIS-C and pre-existing respiratory conditions more frequently had persistent symptoms (aRR, 3.09 [95% CI, 1.55–6.14]) and those with obesity more frequently had activity impairment (aRR, 2.52 [95% CI, 1.35–4.69]). New morbidities were infrequent (9% COVID-19, 1% MIS-C). CONCLUSIONS Over 1 in 4 children hospitalized with acute COVID-19 or MIS-C experienced persistent symptoms or activity impairment for at least 2 months. Patients with MIS-C and respiratory conditions or obesity are at higher risk of prolonged recovery.

AbstractBackground/ObjectivesThe COVID‐19 pandemic prompted a rapid expansion in the use of telemedicine. This study aimed to assess the experiences of hemangioma specialists utilizing telemedicine during the COVID‐19 pandemic to evaluate and manage infantile hemangiomas (IH), including perceived effectiveness of different modalities and barriers to care delivery.MethodsMulticenter cross‐sectional study asking providers to describe their experiences using telemedicine for initial evaluation of IH from March to September 2020.ResultsThe study included 281 patients from 15 medical centers internationally. Median time from referral to evaluation was 17 days. Median physician confidence in performing evaluations via telemedicine was 95.0 (IQR 90.0–100.0). Most evaluations were performed via video communication with photographs or audio communication with photographs; when not initially available, photographs were requested in 51.4%. Providers preferred follow‐up modalities that included photographs.ConclusionsPhysicians with extensive expertise in managing IH are confident in their abilities to assess and manage IH via telemedicine including initiating treatment in patients without risk factors for beta‐blocker therapy. There was a preference for hybrid modalities that included photographs. The data suggest that telemedicine can be effective for managing IH and may decrease wait times and improve specialist reach to underserved areas.

As survival in breast cancer patients from newer therapies increases, concerns for chemotherapy-induced cardiotoxicity (CIC) have offset some of these benefits, manifesting as a decline in left ventricular ejection fraction (LVEF). Patients receiving anthracycline-based chemotherapy followed by trastuzumab are at risk for CIC. Previous research evaluating whether clinical biomarkers predict cardiotoxicity has been inconsistent. Recently, angiotensin II type 1 receptor (ATR1) and endothelin 1 (ET1) have been shown to play a role in breast tumor growth. We evaluated ATR1 and ET1 expression in breast cancer tissue and its association with CIC. A total of 33 paraffin-embedded breast tissue specimens from women with breast cancer treated with anthracycline-based chemotherapy and trastuzumab were analyzed by immunohistochemistry (IHC) and qRT-PCR. We found that ET1 expression was increased in patients with an LVEF ≤ 50% (p = 0.032) with a lower LVEF correlating with higher ET1 expression (r = 0.377, p = 0.031). In patients with a change in LVEF of greater than 10%, greater ET1 expression was noted compared to those without a change in LVEF (p = 0.017). Increased ET1 expression in breast tumor tissue is associated with reduced LVEF. Future studies need to examine whether ET1 may be a tissue biomarker that helps predict the risk of developing CIC in women with breast cancer.

Abstract Background Clinical differences between critical illness from influenza infection vs coronavirus disease 2019 (COVID-19) have not been well characterized in pediatric patients. Methods We compared demographics, clinical characteristics, and outcomes of US children (aged 8 months to 17 years) admitted to the intensive care or high-acuity unit with influenza or COVID-19. Using mixed-effects models, we assessed the odds of death or requiring life support for influenza vs COVID-19 after adjustment for age, sex, race and Hispanic origin, and underlying conditions including obesity. Results Children with influenza (n = 179) were younger than those with COVID-19 (n = 381; median, 5.2 years vs 13.8 years), less likely to be non-Hispanic Black (14.5% vs 27.6%) or Hispanic (24.0% vs 36.2%), and less likely to have ≥1 underlying condition (66.4% vs 78.5%) or be obese (21.4% vs 42.2%), and a shorter hospital stay (median, 5 days vs 7 days). They were similarly likely to require invasive mechanical ventilation (both 30.2%), vasopressor support (19.6% and 19.9%), or extracorporeal membrane oxygenation (2.2% and 2.9%). Four children with influenza (2.2%) and 11 children with COVID-19 (2.9%) died. The odds of death or requiring life support in children with influenza vs COVID-19 were similar (adjusted odds ratio, 1.30; 95% confidence interval, .78–2.15; P = .32). Conclusions Despite differences in demographics and clinical characteristics of children with influenza or COVID-19, the frequency of life-threatening complications was similar. Our findings highlight the importance of implementing prevention measures to reduce transmission and disease severity of influenza and COVID-19.

Abstract Background: Cemiplimab is the first treatment approved in the US (as cemiplimab-rwlc) for patients with metastatic basal cell carcinoma (mBCC) or locally advanced disease (laBCC) after hedgehog inhibitor (HHI) treatment or for whom an HHI is not appropriate. Cemiplimab provided substantial clinical benefit and an acceptable safety profile in patients with laBCC who discontinued HHI therapy due to progressive disease (PD), intolerance, or no better than stable disease (SD) after 9 months (NCT03132636). Here, we present the primary analysis of the mBCC cohort. Methods: Patients with mBCC (nodal or distant) post-HHI treatment received cemiplimab 350 mg intravenously every 3 weeks for up to 93 weeks or until PD. The primary endpoint was objective response rate (ORR) by independent central review (ICR). Key secondary endpoints included safety and tolerability, ORR per investigator (INV) assessment, duration of response (DOR), progression-free survival (PFS), overall survival (OS), and complete response (CR) rate (data cutoff date: May 20, 2021). Results: Fifty-four patients were enrolled (70.4% male; median age 63.5 years [range, 38−90]; Eastern Cooperative Oncology Group performance status 0 [66.7%] and 1 [33.3%]). Median duration of follow-up was 8.4 months (range 1.5-36.2). ORR per ICR was 24.1% (95% confidence interval [CI], 13.5-37.6); with 1 CR and 12 partial responses (PRs). ORR per INV was 25.9% (95% CI, 15.0-39.7), with 2 CRs and 12 PRs. Among responders, median time to response per ICR was 4.0 months (range, 2.0−10.5). Estimated median DOR per ICR was 16.7 months (95% CI, 9.8-not evaluable). Disease control rate was 63.0% (95% CI, 48.7-75.7) per ICR and 70.4% (95% CI, 56.4-82.0) per INV. Median OS was not reached. Median PFS per ICR was 8.3 months (95% CI, 4.2-15.9). The most common treatment-related adverse events were fatigue (37.0%), diarrhea (14.8%), pruritus (13.0%), hyperthyroidism (9.3%), and arthralgia (9.3%) as well as hypothyroidism, asthenia, constipation, and maculo-papular rash (7.4% each). There were no treatment-related deaths. Conclusions: Cemiplimab provided clinically meaningful antitumor activity, including durable responses, and an acceptable safety profile in patients with mBCC who had progressed on or were intolerant to HHI therapy. Citation Format: Karl Lewis, Ketty Peris, Aleksander Sekulic, Alexander J. Stratigos, Lara Dunn, Zeynep Eroglu, Anne Lynn S. Chang, Michael R. Migden, Suk-Young Yoo, Kosalai Mohan, Ebony Coates, Emmanuel Okoye, Timothy Bowler, Jean-François Baurain, Oliver Bechter, Axel Hauschild, Marcus O. Butler, Leonel Hernandez-Aya, Lisa Licitra, Rogerio I. Neves, Emily S. Ruiz, Frank Seebach, David M. Weinreich, George D. Yancopoulos, Israel Lowy, Priscila Goncalves, Matthew G. Fury. Primary analysis of phase 2 results for cemiplimab in patients with metastatic basal cell carcinoma who progressed on or were intolerant to hedgehog inhibitors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr CT165.

Abstract Background: It has been widely established that breast density is an independent breast cancer risk factor. With the increasing utilization of digital breast tomosynthesis (DBT) in breast cancer screening, there is an opportunity to estimate volumetric breast density (VBD) routinely. However, current available methods extrapolate VBD from 2D images acquired with DBT and/or depend on the existence of raw DBT data which is rarely archived by clinical centers due to cost and storage constraints. This study aims to harness deep learning to develop a computational tool for VBD assessment based solely on 3D reconstructed, “for presentation” DBT images. Methods: We retrospectively analyzed 1,080 negative DBT screening exams (09/20/2011 - 11/25/2016) from the Hospital of the University of Pennsylvania (mean age ± SD, 57 ± 11 years; mean BMI ± SD, 28.7 ± 7.1 kg/m2; racial makeup, 41.2% White, 54.2% Black, 4.6% Other), for which both 3D reconstructed and 2D raw DBT images (Selenia Dimensions, Hologic Inc) were available. All available standard views (left and right mediolateral-oblique and cranio-caudal views) were included for each exam, leading to 7,850 DBT views. Corresponding 3D reference-standard tissue segmentations were generated from a previously validated software that uses both 3D reconstructed slices and raw 2D DBT data to provide VBD metrics, shown to be strongly correlated with VBD measures from MRI image volumes. We based our deep learning algorithm on the U-Net architecture within the open-source Generally Nuanced Deep Learning Framework (GaNDLF) and created a 3-label image segmentation task (background, dense tissue, and fatty tissue). Our dataset was randomly split into training (70%), validation (15%) and test (15%) sets, while ensuring that all views of the same DBT exam were assigned to the same set. The performance of our deep learning algorithm against the corresponding reference-standard segmentations was measured in terms of Dice scores (DSC), with 0 signifying no overlap and 1 signifying perfect overlap, overall, as well as separately for each label. Results: After training was complete, our deep learning algorithm achieved a DSC of 0.78 on the validation, as well as on the test set. Our method accurately segmented background from breast tissue (DSC = 0.94) and demonstrated moderate to high performance in segmenting dense and fatty tissue, respectively (DSC = 0.49 and 0.89). Conclusion: Our preliminary analysis suggests that deep learning shows promise in the estimation of VBD using 3D DBT reconstructed, “for presentation” images. Future work involving transfer learning based on ground truth masks by clinical radiologists could further enhance this method’s performance. In view of rapid clinical conversion to DBT screening, such a tool has the potential to enable large retrospective epidemiologic and personalized risk assessment studies of breast density with DBT. Citation Format: Vinayak S. Ahluwalia, Walter Mankowski, Sarthak Pati, Spyridon Bakas, Ari Brooks, Celine M. Vachon, Emily F. Conant, Aimilia Gastounioti, Despina Kontos. Deep-learning-enabled volumetric breast density estimation with digital breast tomosynthesis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1929.