Citations

580 Background: Patients (pts) in Cohort A of the American College of Surgeons Oncology Group Z1031 (Alliance) trial of NET for cStage II-III breast cancer were randomized to anastrozole [ANA], letrozole [LET] or exemestane [EXE] for 16-18 weeks (wks). In Cohort B, pts chose between ANA and LET and switched to chemotherapy or surgery if a tumor biopsy after 2-4 wks of NET had Ki67 >10%. Treatments after surgery were not defined by the trial protocol. SET2,3 measures nonproliferation gene expression related to estrogen and progesterone receptors adjusting for a baseline prognostic index that combines clinical tumor and nodal stage and a 4-gene molecular subtype (RNA4) defined by ESR1, PGR, ERBB2 and AURKA. High SET2,3 in a pre-treatment biopsy using cStage information is defined as SET2,3 >1.77. Methods: 379 pts had gene expression data from a research tumor biopsy prior to NET (Agilent 44K microarrays). A bioinformatician blinded to pt treatment and clinical outcomes determined SET2,3. The trial statistician then examined the association between SET2,3 and pharmacodynamic response at 2-4 wks (N=141, Cohort B): Ki67 ≤10% and complete cell cycle arrest (CCCA Ki67 ≤2.7%); pathologic outcomes in pts who completed NET: ypStage 0/1 (N=329, Cohorts A&B), PEPI-0 rate (N=155, Cohort B); and event-free survival (EFS) post-registration (N=244, Cohorts A&B). We used Fisher’s exact tests to assess whether responses, and Cox modeling to evaluate whether EFS, differed with respect to SET2,3 status. Results: High SET2,3 in 48% of pts (183/379) was associated with older age (median: 66 vs 63 years; p=0.012); cStage II (95% vs 75%; p <0.001); and pre-NET Ki67 ≤10% (37% vs 20%; p< 0.001) in pts with low SET2,3. In Cohort B, pts with high SET2,3 had a higher rate of pharmacodynamic response in their tumor at wk 2-4 than pts with low SET2,3 (Table). In the subset of Cohort B pts with wk 2-4 Ki67 ≤10%, pre-treatment SET2,3 trended numerically higher in pts who achieved PEPI-0 score (p=0.049) but the proportion achieving PEPI-0 did not differ by SET2,3 high/low status (Table). EFS was significantly longer for pts with high SET2,3 than pts with low SET2,3 (HR[H/L]: 0.52; 95% CI: 0.34-0.80; p=0.003). Conclusions: An exploratory analysis of Z1031 data demonstrated that the rate of pharmacodynamic suppression of proliferation by NET at 2-4 wks was greater and EFS was longer for pts with breast cancer expressing high SET2,3 disease than pts with low SET2,3. Support: U10CA180821, U10CA180882, U24CA196171; https://acknowledgments.alliancefound.org ; Clinical trial information: NCT00265759. [Table: see text]

ObjectiveThe objective of this study was to describe differences in the clinical course of patients with rheumatoid arthritis (RA) who are antinuclear antibody (ANA)–positive compared with those who are ANA‐negative.MethodsThis was a retrospective population‐based cohort study of residents in Olmsted County, Minnesota, who first fulfilled 1987 American College of Rheumatology criteria for RA in 2009‐2014. Data were collected on first documentation of joint swelling. Data on rheumatoid factor or anti‐cyclic citrullinated peptide antibody testing and the ANA level were also collected. Comparisons between groups were performed by using χ2 and rank sum tests.ResultsIn this cohort, 64% of patients were tested for ANA within ±90 days of RA criteria fulfillment. In the161 patients with ANA testing, 25% were ANA‐positive. Patients who were ANA‐positive were younger, female, and less likely to be current smokers. ANA positivity did not differ between patients with RA who were seropositive and seronegative. In seropositive patients who were ANA‐positive, there was an increased time to fulfillment of RA criteria, increased time to treatment with disease‐modifying antirheumatic drugs (DMARDs), and increased likelihood of being treated with hydroxychloroquine as opposed to methotrexate. Other outcomes, including disease activity and mortality, did not differ significantly between groups.ConclusionIn patients with RA, important differences exist between those who are ANA‐positive and ANA‐negative in terms of time to fulfillment of RA criteria and time to DMARD initiation as well as choice of initial pharmacotherapy. These findings could indicate a difference in clinical presentation or perception of patients with RA who are ANA‐positive. Further research is needed to study the long‐term outcomes of patients with RA who are ANA‐positive.

Abstract BACKGROUND Clinicoradiologic differentiation between benign and malignant peripheral nerve sheath tumors (PNSTs) has important management implications. OBJECTIVE To develop and evaluate machine-learning approaches to differentiate benign from malignant PNSTs. METHODS We identified PNSTs treated at 3 institutions and extracted high-dimensional radiomics features from gadolinium-enhanced, T1-weighted magnetic resonance imaging (MRI) sequences. Training and test sets were selected randomly in a 70:30 ratio. A total of 900 image features were automatically extracted using the PyRadiomics package from Quantitative Imaging Feature Pipeline. Clinical data including age, sex, neurogenetic syndrome presence, spontaneous pain, and motor deficit were also incorporated. Features were selected using sparse regression analysis and retained features were further refined by gradient boost modeling to optimize the area under the curve (AUC) for diagnosis. We evaluated the performance of radiomics-based classifiers with and without clinical features and compared performance against human readers. RESULTS A total of 95 malignant and 171 benign PNSTs were included. The final classifier model included 21 imaging and clinical features. Sensitivity, specificity, and AUC of 0.676, 0.882, and 0.845, respectively, were achieved on the test set. Using imaging and clinical features, human experts collectively achieved sensitivity, specificity, and AUC of 0.786, 0.431, and 0.624, respectively. The AUC of the classifier was statistically better than expert humans ( P = .002). Expert humans were not statistically better than the no-information rate, whereas the classifier was ( P = .001). CONCLUSION Radiomics-based machine learning using routine MRI sequences and clinical features can aid in evaluation of PNSTs. Further improvement may be achieved by incorporating additional imaging sequences and clinical variables into future models.

Abstract Patients requiring chronic transfusion support are at risk of alloimmunization after red blood cell (RBC) transfusion because of a disparity between donor and recipient antigen profiles. This research explored the probability of obtaining an exact extended phenotype match between blood donors randomly selected from our institution and patients randomly selected from particular ethnic groups. Blood samples from 1,000 blood donors tested by molecular method were evaluated for the predicted phenotype distribution of Rh, Kell, Kidd, Duffy, and MNS. A random subsample of 800 donor phenotypes was then evaluated for the probability of obtaining an exact match with respect to phenotype with a randomly selected patient from a particular ethnic group. Overall, there was a greater than 80 percent probability of finding an exact donor-recipient match for the K/k alleles in the Kell system. The probability ranged from 3 percent to 38 percent, depending on the ethnicity and disparities in phenotypic profiles, for the Rh, Kidd, Duffy, and MNS systems. A significant donor-recipient phenotype mismatch ratio exists with certain blood group antigens such that, with current routine ABO and D matching practices, recipients of certain ethnic groups are predisposed to alloimmunization. Immunohematology 2011; 27:12–19.

PurposeMulti‐energy computed tomography (MECT) has a great potential to enable many novel clinical applications such as simultaneous multi‐contrast imaging. The purpose of this study was to implement triple‐beam MECT on a traditional energy‐integrating‐detector (EID) CT platform (EID‐MECT).MethodsThis was accomplished by mounting a z‐axis split‐filter (0.05 mm Au, 0.6 mm Sn) on Tube A of a dual‐source EID CT scanner. With the two split x‐ray beams from Tube A and the third beam from Tube B, three beams with different x‐ray spectra can be simultaneously acquired. With Tube B operated at 70 or 80 kV and Tube A at 120 or 140 kV, four different triple‐beam configurations were calibrated for MECT measurements: 70/Au120/Sn120, 80/Au120/Sn120, 70/Au140/Sn140, and 80/Au140/Sn140 kV. Iodine (I), gadolinium (Gd), bismuth (Bi) samples, and their mixtures were prepared for 2 three‐material‐decomposition tasks and 1 four‐material‐decomposition task. For each task, samples were placed in a water phantom and scanned using each of the four triple‐beam configurations. For comparison, the same phantom was also scanned using three other dual‐energy CT (DECT) or MECT technologies: twin‐beam DECT (TB‐DECT), dual‐source DECT (DS‐DECT), and photon‐counting‐detector CT (PCD‐CT), all with optimal x‐ray spectrum settings and at equal volume CT dose index (CTDIvol). The phantom for four‐material decomposition (I/Gd/Bi/Water imaging) was scanned using the PCD‐CT only (140 kV with 25, 50, 75, and 90 keV). Image‐based material decomposition was performed to acquire material‐specific images, on which the mean basis material concentrations and noise levels were measured and compared across all triple‐beam configurations in EID‐MECT and various DECT/MECT systems.ResultsThe optimal triple‐beam configuration was task‐dependent with 70/Au120/Sn120, 70/Au140/Sn140, and 70/Au120/Sn120 kV for I/Gd/Water, I/Bi/Water, and I/Gd/Bi/Water material decomposition tasks, respectively. At equal radiation dose level, EID‐MECT provided comparable or better quantification accuracy in material‐specific images for all three material decomposition tasks, compared to EID‐based DECT and PCD‐CT systems. In terms of noise level comparison, EID‐MECT‐derived material‐specific images showed lower noise levels than TB‐DECT and DS‐DECT, but slightly higher than that from PCD‐CT in I/Gd/Water imaging. For I/Bi/Water imaging, EID‐MECT showed a comparable noise level to DS‐DECT, and a much lower noise level than TB‐DECT and PCD‐CT in all material‐specific images. For the four‐material decomposition task involving I/Gd/Bi/Water, the bismuth‐specific image derived from EID‐MECT was slightly noisier, but both iodine‐ and gadolinium‐specific images showed much lower noise levels in comparison to PCD‐CT.ConclusionsFor the first time, an EID‐based MECT system that can simultaneously acquire three x‐ray spectra measurements was implemented on a clinical scanner, which demonstrated comparable or better imaging performance than existing DECT and MECT systems.

Encephalopathy, delirium, and agitation are documented symptoms of coronavirus disease (COVID-19) infection, but research into the management of agitation in the setting of COVID-19 and pre-existing neuropsychiatric disease is ongoing. We present a 55-year-old male patient with early-onset Alzheimer disease and deteriorating mental and functional status who presented to our institution with agitation and persistent COVID-19 positivity on polymerase chain reaction testing. His agitation was improved through pharmacologic optimization including the avoidance of benzodiazepines and initiation of clonidine and prazosin, which temporally coincided with the resolution of his nearly 2-month long COVID-19 positivity.

Abstract Background: Fibrodysplasia ossificans progressiva (FOP) is an ultra-rare, autosomal dominant disorder driven by mutations in ACVR1 that render it responsive to Activin A. FOP is characterized by progressive heterotopic ossification (HO) and distressing inflammatory events called “flare-ups.” Flare-ups can precede new HO; however, limited prospective data exists on this phenomenon. Garetosmab (GAR), an investigational human monoclonal antibody against Activin A, blocks formation of new HO in FOP. Methods: This is a post-hoc analysis of LUMINA-1 (NCT03188666) a phase 2, randomized, double-blind, placebo-controlled study, which evaluated the safety and efficacy of GAR (10 mg/kg/week IV) versus placebo (PBO) in adult patients with FOP over 28 weeks. Patient-reported flare-ups were collected via a patient diary and severity level was reported as mild, moderate or severe. Clinician-reported flare-ups were collected as adverse events in the trial. HO lesions were imaged by 18F-NaF positron emission tomography (PET) and whole-body low-dose X-ray computed tomography (CT). Results: There was a two-fold higher proportion of patients who reported one or more flare-ups on PBO 17/24 (71%) compared with GAR 7/20 (35%). Clinicians reported a four-fold higher proportion of patients experiencing one or more flare-ups on PBO 10/24 (42%) compared with GAR 2/20 (10%). Overall rates of flare-up events were two-fold higher on PBO vs. GAR (1.4 vs. 0.65 events/patient/28 weeks) for patient-reported events and eight-fold higher on PBO vs. GAR by clinician report (0.83 vs. 0.10 events/patient/28 weeks). Most flare-ups occurred on the extremities and back; pain was the most commonly reported symptom. Patient-reported flare-ups on PBO were more frequently reported as severe (29.4%) compared with GAR (7.7%). Among subjects with at least 12 weeks of follow-up from start of patient-reported flare-up, development of new HO near the site was 5/27 (18.5%) on PBO and (0%) on GAR. Of all new HO lesions, 41% on PBO and 0% on GAR occurred with spatial and temporal relation to flare-up. Conclusions: Approximately two-thirds of patients on PBO reported flare-ups over 28 weeks. GAR was associated with reductions in frequency and severity of flare-ups. Fewer than 20% of patient-reported flare-ups were associated with new HO, indicating frequent discordance of these phenomena, and compatible with previous reports. GAR’s ability to reduce patient- and clinician-reported flare-ups, as well as new HO lesions may provide an important therapeutic option.

AbstractBackgroundPrexasertib (LY2606368) is a novel, second‐generation, selective dual inhibitor of checkpoint kinase proteins 1 (CHK1) and 2 (CHK2). We conducted a phase 1 trial of prexasertib to estimate the maximum‐tolerated dose (MTD) and/or recommended phase 2 dose (RP2D), to define and describe the toxicities, and to characterize the pharmacokinetics (PK) of prexasertib in pediatric patients with recurrent or refractory solid and central nervous system (CNS) tumors.MethodsPrexasertib was administered intravenously (i.v.) on days 1 and 15 of a 28‐day cycle. Four dose levels, 80, 100, 125, and 150 mg/m2, were evaluated using a rolling‐six design. PK analysis was performed during cycle 1. Tumor tissue was examined for biomarkers (CHK1 and TP53) of prexasertib activity.ResultsThirty patients were enrolled; 25 were evaluable. The median age was 9.5 years (range: 2‐20) and 21 (70%) were male. Twelve patients (40%) had solid tumors and 18 patients (60%) had CNS tumors. There were no cycle 1 or later dose‐limiting toxicities. Common cycle 1, drug‐related grade 3/4 toxicities (> 10% of patients) included neutropenia (100%), leukopenia (68%), thrombocytopenia (24%), lymphopenia (24%), and anemia (12%). There were no objective responses; best overall response was stable disease in three patients for five cycles (hepatocellular carcinoma), three cycles (ependymoma), and five cycles (undifferentiated sarcoma). The PK appeared dose proportional across the 80‐150 mg/m2 dose range.ConclusionsAlthough the MTD of prexasertib was not defined by this study, 150 mg/m2 administered i.v. on days 1 and 15 of a 28‐day cycle was determined to be the RP2D.