Citations

Abstract Purpose: Treatment options are limited beyond JAK inhibitors for patients with primary myelofibrosis (MF) or secondary MF. Preclinical studies have revealed that PI3Kδ inhibition cooperates with ruxolitinib, a JAK1/2 inhibitor, to reduce proliferation and induce apoptosis of JAK2V617F-mutant cell lines. Patients and Methods: In a phase I dose-escalation and -expansion study, we evaluated the safety and efficacy of a selective PI3Kδ inhibitor, umbralisib, in combination with ruxolitinib in patients with MF who had a suboptimal response or lost response to ruxolitinib. Enrolled subjects were required to be on a stable dose of ruxolitinib for ≥8 weeks and continue that MTD at study enrollment. The recommended dose of umbralisib in combination with ruxolitinib was determined using a modified 3+3 dose-escalation design. Safety, pharmacokinetics, and efficacy outcomes were evaluated, and spleen size was measured with a novel automated digital atlas. Results: Thirty-seven patients with MF (median age, 67 years) with prior exposure to ruxolitinib were enrolled. A total of 2 patients treated with 800 mg umbralisib experienced reversible grade 3 asymptomatic pancreatic enzyme elevation, but no dose-limiting toxicities were seen at lower umbralisib doses. Two patients (5%) achieved a durable complete response, and 12 patients (32%) met the International Working Group-Myeloproliferative Neoplasms Research and Treatment response criteria of clinical improvement. With a median follow-up of 50.3 months for censored patients, overall survival was greater than 70% after 3 years of follow-up. Conclusions: Adding umbralisib to ruxolitinib in patients was well tolerated and may resensitize patients with MF to ruxolitinib without unacceptable rates of adverse events seen with earlier generation PI3Kδ inhibitors. Randomized trials testing umbralisib in the treatment of MF should be pursued.

Background The use of low-titer group O whole blood is increasing. To reduce wastage, unused units can be converted to packed red blood cells. Supernatant is currently discarded post-conversion; however, it could be a valuable transfusable product. The aim of this study was to evaluate supernatant prepared from late-storage low-titer group O whole blood being converted to red blood cells, hypothesizing it will have higher hemostatic activity compared to fresh never-frozen liquid plasma. Methods Low-titer group O whole blood supernatant (n = 12) prepared on storage day 15 was tested on days 15, 21, and 26 and liquid plasma (n = 12) on 3, 15, 21, and 26. Same-day assays included cell counts, rotational thromboelastometry, and thrombin generation. Centrifuged plasma from units was banked for microparticle characterization, conventional coagulation, clot structure, hemoglobin, and additional thrombin generation assays. Results Low-titer group O whole blood supernatant contained more residual platelets and microparticles compared to liquid plasma. At day 15, low-titer group O whole blood supernatant elicited a faster intrinsic clotting time compared to liquid plasma (257 ± 41 vs . 299 ± 36 s, P = 0.044), and increased clot firmness (49 ± 9 vs . 28 ± 5 mm, P < 0.0001). Low-titer group O whole blood supernatant showed more significant thrombin generation compared to liquid plasma (day 15 endogenous thrombin potential 1,071 ± 315 vs . 285 ± 221 nM·min, P < 0.0001). Flow cytometry demonstrated low-titer group O whole blood supernatant contained significantly more phosphatidylserine and CD41 + microparticles. However, thrombin generation in isolated plasma suggested residual platelets in low-titer group O whole blood supernatant were a greater contributor than microparticles. Additionally, low-titer group O whole blood supernatant and liquid plasma showed no difference in clot structure, despite higher CD61 + microparticle presence. Conclusions Plasma supernatant produced from late-storage low-titer group O whole blood shows comparable, if not enhanced, in vitro hemostatic efficacy to liquid plasma. Editor’s Perspective What We Already Know about This Topic What This Article Tells Us That Is New

Abstract Background: Cancer is usually treated with a combination of drugs rather than a single agent. Treating cancer with a drug combination decreases the likelihood of the cancer acquiring resistance to therapy. It also allows for lower dosages of individual drugs, which reduces the occurrence and severity of side effects. Using public datasets, we investigated potential anti-cancer drug combinations using a novel framework, ReCorDE (Recurrent Correlation of Drugs with Enrichment), which identifies correlated drug response patterns for drugs with different primary mechanisms of action. Methods: 250 drugs from CTRPv2, GDSCv2, and PRISM datasets were examined using normalized logIC50 or AUC measurements. ReCorDE consists of a correlation and an enrichment step. For each dataset, we constructed pairwise drug-drug relationships using Spearman’s correlation. Combinations significant (p &lt; 0.05) in less than two datasets after Benjamini-Hochberg (BH) correction were pruned. To turn each drug combination into a drug class combination, all drugs were mapped to their corresponding fourth-level Anatomical Therapeutic Chemical (ATC) codes. Then, using a hypergeometric test, for each class combination in the subset of significant drug combinations (the “inside” set), we tested for enrichment of that class combination in the inside set compared to the class combination universe, the distribution of class combinations for all unique pairwise drug-drug associations (250 unique drugs; 31,125 distinct drug combinations mapped to 1596 distinct class combinations). Multiple testing during enrichment was corrected using the BH method with a significance cutoff of p&lt; 0.05. Results: We found 2764 pairs to be significant at a = 0.05 using the AUC measure. With a correlation coefficient of 0.77, vincristine and YK-4-279, an EWS-FLI1/RNA Helicase A inhibitor, had the lowest computed p-value of of 1.39 × 10−120 Adjusted p-values for &gt;15% of these combinations had p-values &lt; 5 × 10−6. Class combination enrichment on the same set showed 132 class pairs were enriched in the inside set compared to the class combination universe after BH correction. Taxanes/Plk1 inhibitors (OR = 69.5, adjusted p = 5.6 × 10−11); Aurora Kinase inhibitors/histone modifying agents (OR=9.2, adjusted p = 6.13 × 10−11); and pyrimidine analogues/CDK inhibitors (OR=3.43, adjusted p = 0.02) are a few notable enriched class combinations. The enrichment of these class combinations in the inside set suggests that combinations of drugs from these classes may be particularly effective in treating cancer compared to other drug combinations. Conclusions: Our framework, ReCorDE, demonstrates that finding potential drug combinations and characterizing novel, frequently perturbed pathways outside of a drug's primary mechanisms of action can be accomplished by identifying correlated drug-drug pairs from large, publicly accessible databases. Citation Format: Emily T. Ghose, August John, Huanyao Gao, Krishna R. Kalari, Liewei Wang. ReCorDE: A novel computational framework to discover potential combinations of anti-cancer drugs. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4290.

Abstract Purpose Albumin, the most abundant and arguably most important protein in the human body, plays a unique role in decompensated cirrhosis because its structure and function are quantitatively and qualitatively affected. A literature review was performed to provide insights into albumin use. The manuscript was developed using a multidisciplinary approach; 2 hepatologists, a nephrologist, a hospitalist, and a pharmacist, who are all members of or work closely with the Chronic Liver Disease Foundation, collaborated to write this expert perspective review. Summary Cirrhosis represents the potential end in the spectrum of all chronic liver diseases. Decompensated cirrhosis, defined by the overt manifestation of liver failure (eg, ascites, hepatic encephalopathy, variceal bleeding), is the inflection point associated with increased mortality. Human serum albumin (HSA) infusion serves an important role in the treatment of advanced liver disease. The benefits of HSA administration in patients with cirrhosis are widely accepted, and its use has been advocated by several professional societies. However, inappropriate HSA use can lead to significant adverse patient events. This paper discusses the rationale for the administration of HSA in the treatment of complications of cirrhosis, analyzes the data on the use of HSA in cirrhosis, and streamlines practical recommendations set forth in published guidance. Conclusion Use of HSA in clinical practice needs to be improved. The objective of this paper is to empower pharmacists to facilitate and improve the use of HSA in patients with cirrhosis at their practice sites.

Abstract Objective The purpose of this study is to assess the “real-world” impact of an artificial intelligence (AI) tool designed to detect breast cancer in digital breast tomosynthesis (DBT) screening exams following 12 months of utilization in a subspecialized academic breast center. Methods Following IRB approval, mammography audit reports, as specified in the BI-RADS atlas, were retrospectively generated for five radiologists reading at three locations during a 12-month time frame. One location had the AI tool (iCAD ProFound AI v2.0), and the other two locations did not. The co-primary endpoints were cancer detection rate (CDR) and abnormal interpretation rate (AIR). Secondary endpoints included positive predictive values (PPVs) for cancer among screenings with abnormal interpretations (PPV1) and for biopsies performed (PPV3). Odds ratios (OR) with two-sided 95% confidence intervals (CIs) summarized the impact of AI across radiologists using generalized estimating equations. Results Nonsignificant differences were observed in CDR, AIR, and PPVs. The CDR was 7.3 with AI and 5.9 without AI (OR 1.3, 95% CI: 0.9–1.7). The AIR was 11.7% with AI and 11.8% without AI (OR 1.0, 95% CI: 0.8–1.3). The PPV1 was 6.2% with AI and 5.0% without AI (OR 1.3, 95% CI: 0.97–1.7). The PPV3 was 33.3% with AI and 32.0% without AI (OR 1.1, 95% CI: 0.8–1.5). Conclusion Although we are unable to show statistically significant changes in CDR and AIR outcomes in the two groups, the results are consistent with prior reader studies. There is a nonsignificant trend toward improvement in CDR with AI, without significant increases in AIR.

AbstractReject rate analysis is considered an integral part of a diagnostic radiography quality control (QC) program. A rejected image is a patient radiograph that was not presented to a radiologist for diagnosis and that contributes unnecessary radiation dose to the patient. Reject rates that are either too high or too low may suggest systemic department shortcomings in QC mechanisms. Due to the lack of standardization, reject data often cannot be easily compared between radiography systems from different vendors. The purpose of this report is to provide guidance to help standardize data elements that are required for comprehensive reject analysis and to propose data reporting and workflows to enable an effective and comprehensive reject rate monitoring program. Essential data elements, a proposed schema for classifying reject reasons, and workflow implementation options are recommended in this task group report.

AbstractBackground and ObjectivesConvalescent COVID‐19 plasma (CCP) was developed and used worldwide as a treatment option by supplying passive immunity. Adult studies suggest administering high‐titer CCP early in the disease course of patients who are expected to be antibody‐negative; however, pediatric experience is limited. We created a multi‐institutional registry to characterize pediatric patients (<18 years) who received CCP and to assess the safety of this intervention.MethodsA REDCap survey was distributed. The registry collected de‐identified data including demographic information (age, gender, and underlying conditions), COVID‐19 disease features and concurrent treatments, CCP transfusion and safety events, and therapy response.ResultsNinety‐five children received CCP: 90 inpatients and 5 outpatients, with a median age of 10.2 years (range 0–17.9). They were predominantly Latino/Hispanic and White. The most frequent underlying medical conditions were chronic respiratory disease, immunosuppression, obesity, and genetic syndromes. CCP was primarily given as a treatment (95%) rather than prophylaxis (5%). Median total plasma dose administered and transfusion rates were 5.0 ml/kg and 2.6 ml/kg/h, respectively. The transfusions were well‐tolerated, with 3 in 115 transfusions reporting mild reactions. No serious adverse events were reported. Severity scores decreased significantly 7 days after CCP transfusion or at discharge. Eighty‐five patients (94.4%) survived to hospital discharge. All five outpatients survived to 60 days.ConclusionsCCP was found to be safe and well‐tolerated in children. CCP was frequently given concurrently with other COVID‐19‐directed treatments with improvement in clinical severity scores ≥7 days after CCP, but efficacy could not be evaluated in this study.

Background: Residual fragments (RFs) after percutaneous nephrolithotomy (PCNL) have a significant impact on patients' quality of life and clinical course. There is a paucity of studies that evaluate the natural history of RFs after PCNL. The objective of this study is to compare rates of reintervention, complications, stone growth, and passage in patients with RFs >4, ≤4, and ≤2 mm after PCNL. Methods: Sites from the Endourologic Disease Group for Excellence (EDGE) research consortium examined data of PCNL patients from 2015 to 2019 with at least 1-year follow-up. RF passage, regrowth, reintervention, and complications were recorded and RFs were stratified into >4 and ≤4 mm groups, as well as >2 and ≤2 mm groups. Potential predictors for stone-related events after PCNL were determined using multivariable logistic regression analysis. It was hypothesized that larger RF thresholds would result in lower passage rates, faster regrowth, and greater clinically significant events (complications and reinterventions) than smaller RF thresholds. Results: A total of 439 patients with RFs >1 mm on CT postoperative day 1 were included in this study. For RFs >4 mm, rates of reintervention were found to be significantly higher and Kaplan–Meier curve analysis showed significantly higher rates of stone-related events. Passage and RF regrowth were not found to be significantly different compared with RFs ≤4 mm. However, RFs ≤2 mm had significantly higher rates of passage, and significantly lower rates of fragment regrowth (>1 mm), complications, and reintervention compared with RFs >2 mm. On multivariable analysis, older age, body mass index, and RF size were found to be predictive of stone-related events. Conclusions: With the largest cohort to date, this study by the EDGE research consortium further confirms that clinically insignificant residual fragment is problematic for patients after PCNL, particularly in older more obese patients with larger RFs. Our study underscores the importance of complete stone clearance post-PCNL and challenges the use of Clinically insignificant residual fragment (CIFR).

PURPOSE Image-derived artificial intelligence–based short-term risk models for breast cancer have shown high discriminatory performance compared with traditional lifestyle/familial-based risk models. The long-term performance of image-derived risk models has not been investigated. METHODS We performed a case-cohort study of 8,604 randomly selected women within a mammography screening cohort initiated in 2010 in Sweden for women age 40-74 years. Mammograms, age, lifestyle, and familial risk factors were collected at study entry. In all, 2,028 incident breast cancers were identified through register matching in May 2022 (206 incident breast cancers were found in the subcohort). The image-based model extracted mammographic features (density, microcalcifications, masses, and left-right breast asymmetries of these features) and age from study entry mammograms. The Tyrer-Cuzick v8 risk model incorporates self-reported lifestyle and familial risk factors and mammographic density to estimate risk. Absolute risks were estimated, and age-adjusted AUC model performances (aAUCs) were compared across the 10-year period. RESULTS The aAUCs of the image-based risk model ranged from 0.74 (95% CI, 0.70 to 0.78) to 0.65 (95% CI, 0.63 to 0.66) for breast cancers developed 1-10 years after study entry; the corresponding Tyrer-Cuzick aAUCs were 0.62 (95% CI, 0.56 to 0.67) to 0.60 (95% CI, 0.58 to 0.61). For symptomatic cancers, the aAUCs for the image-based model were ≥0.75 during the first 3 years. Women with high and low mammographic density showed similar aAUCs. Throughout the 10-year follow-up, 20% of all women with breast cancers were deemed high-risk at study entry by the image-based risk model compared with 7.1% using the lifestyle familial-based model ( P < .01). CONCLUSION The image-based risk model outperformed the Tyrer-Cuzick v8 model for both short-term and long-term risk assessment and could be used to identify women who may benefit from supplemental screening and risk reduction strategies.