Citations

Abstract Disclosure: B. Clarke: Advisory Board Member; Self; Ascendis Pharma, Takeda, Entera-Bio, Extend-Bio, Amolyt. Consulting Fee; Self; Ascendis Pharma, Takeda, Entera-Bio, Extend-Bio, Amolyt. Grant Recipient; Self; Ascendis Pharma, Takeda. Research Investigator; Self; Ascendis Pharma, Takeda. Other; Self; Ascendis Pharma, Takeda, Entera-Bio, Extend-Bio, Amolyt. A.A. Khan: Advisory Board Member; Self; Amgen Inc, Alexion Pharmaceuticals, Inc., Ascendis Pharma, Takeda, Ultragenyx. Consulting Fee; Self; Amgen Inc, Alexion Pharmaceuticals, Inc., Amolyt, Ascendis Pharma, Ultragenyx. Grant Recipient; Self; Amolyt. Research Investigator; Self; Radius Health, Inc, Takeda, Ultragenyx, Amolyt, Ascendis Pharma, Chugai. Speaker; Self; Amgen Inc. Other; Self; Amgen Inc, Alexion Pharmaceuticals, Inc., Ascendis Pharma, Takeda, Ultragenyx. M.R. Rubin: Research Investigator; Self; Chugai Pharma. P.E. Schwarz: Stock Owner; Self; Novo Nordisk, Genmab. T.J. Vokes: Consulting Fee; Self; Takeda, Ascendis Pharma. Research Investigator; Self; Ascendis Pharma, Radius Health, Inc. D.M. Shoback: Research Investigator; Self; Bone Health Tech. C. Gagnon: Advisory Board Member; Self; Novo Nordisk. Grant Recipient; Self; Shire, Takeda, Ascendis Pharma. Research Investigator; Self; Novo Nordisk. Other; Self; Amgen Inc. A. Palermo: Consulting Fee; Self; Theramex, Bruno, Farmaceutici, Amgen Inc. Grant Recipient; Self; Amgen Inc. Research Investigator; Self; Amgen Inc, Shire, Ascendis Pharma. Speaker; Self; UCB, Amgen Inc. L.G. Abbott: Advisory Board Member; Self; Ascendis. Research Investigator; Self; Takeda, Shire, Ascendis Pharma. Speaker; Self; Abbott Laboratories, Clarus. Other; Self; Ascendis. L.C. Hofbauer: Advisory Board Member; Self; Amgen Inc, UCB. Other; Self; Amgen Inc, UCB. L. Kohlmeier: Advisory Board Member; Self; Alexion Pharmaceuticals, Inc., Ascendis Pharma. Research Investigator; Self; Ascendis Pharma. Speaker; Self; Amgen Inc, Radius Health, Inc, Alexion Pharmaceuticals, Inc., Ascendis Pharma. Other; Self; Amgen Inc, Radius Health, Inc, Alexion Pharmaceuticals, Inc., Ascendis Pharma, MediMaps. F. Cetani: None. S. Phil: Employee; Self; Ascendis Pharma. X. An: Employee; Self; Ascendis Pharma. A.R. Smith: Employee; Self; Ascendis Pharma. B. Lai: Employee; Self; Ascendis Pharma. J. Le: Employee; Self; Ascendis Pharma. J. Ukena: Employee; Self; Ascendis Pharma. C. Sibley: Employee; Self; Ascendis Pharma. A. Shu: Employee; Self; Ascendis Pharma. L. Rejnmark: Advisory Board Member; Self; Takeda, Amolyt. Research Investigator; Self; Takeda, Kyowa Kirin International, Ascendis Pharma, Calcilytix Therapeutics. Other; Self; Calcilytix Therapeutics. Objective: Evaluate the long-term efficacy and safety of TransCon PTH as a potential hormone replacement therapy for hypoparathyroidism. Methods: PaTHway is a phase 3 trial of TransCon PTH with a placebo (PBO)-controlled 26-week blinded period and a 156-week open-label extension (OLE) period. Results through Week 52 (26 weeks blinded + 26 weeks OLE) are reported. Three-component efficacy endpoint: normal serum calcium (8.3-10.6 mg/dL) and independence from conventional therapy (≤600 mg/day of elemental calcium and no active vitamin D). Other endpoints: Hypoparathyroidism Patient Experience Scale (HPES); 36-Item Short Form Survey (SF-36); bone mineral density (BMD) by dual-energy X-ray absorptiometry (DXA); bone turnover markers (BTM) procollagen type 1 N-terminal propeptide (P1NP) and C-terminal telopeptide of type 1 collagen (CTx). Safety was assessed by 24-hour urine calcium and reported treatment-emergent adverse events (TEAEs). Results: Of the 82 participants given study drug, 79 completed blinded treatment and entered the OLE, and 78 (59 TransCon PTH/TransCon PTH, 19 PBO/TransCon PTH) completed Week 52. Overall at Week 52, 81% (63/78) met the efficacy endpoint, 95% (74/78) achieved independence from conventional therapy, and none required active vitamin D. Mean albumin-adjusted serum calcium was within the normal range at all time points in the OLE (8.9 mg/dL at Week 52). Mean Week 52 HPES scores showed sustained improvement from baseline in disease-related symptoms and the impact of hypoparathyroidism on physical functioning and daily life. Mean Week 52 SF-36 physical functioning scores also remained above baseline. In the TransCon PTH/TransCon PTH group, mean BMD corrected Z-scores trended toward norms from baseline to Weeks 26 and 52:1.5, 0.7, 0.7 at the lumbar spine (L1-L4); 0.8, 0.3, 0.3 at femoral neck; 0.9, 0.5, 0.4 at total hip; and 0.3, 0.3, 0.3 at distal 1/3 radius; P1NP peaked at Week 26 and CTx at Week 12. Smaller incremental changes were seen in BMD and BTM from Weeks 26 to 52 than baseline to Week 26. In the PBO/TransCon PTH group, changes in BMD and BTM from Week 26 to 52 resembled those in the TransCon PTH/TransCon PTH group from baseline to Week 26. Mean 24-hour urine calcium excretion decreased from 376 mg/day at baseline to 195 mg/day at Week 52. Most TEAEs were mild or moderate and none led to discontinuation of the study drug or trial. Conclusions: At Week 52 of the PaTHway trial, TransCon PTH showed a similar sustained efficacy, safety, and tolerability profile to that of Week 26, demonstrating its potential as a hormone replacement therapy for adults with hypoparathyroidism. Indices of skeletal dynamics trended toward age- and sex-matched norms in the TransCon/TransCon PTH group. TransCon PTH treatment in the PBO/TransCon PTH group showed rapid improvement in all outcomes in the first 26 weeks of the OLE consistent with the pattern in the TransCon PTH group during the blinded period. Presentation: Saturday, June 17, 2023

Abstract Disclosure: S. Bjornsdottir: None. W. Kamal: None. B.L. Langdahl: None. T. Spelman: None. B.L. Clarke: None. O. Kampe: None. Context: Previous studies have shown that patients with hypoparathyroidism (hypoPT) have reduced bone remodeling, with consequent increases in bone density, and abnormalities in microarchitecture and bone strength. It is still not clear whether there is an increased risk of fractures in patients with hypoPT. Objective: The aim of this study was to evaluate the risk of fractures in patients with hypoPT in Sweden. Patients: The Swedish National Patient Register, the Swedish Prescribed Drug Register and the Total Population Register were used to identify 1982 patients with chronic hypoPT (duration ≥ 12 months), and 19820 controls matched by age, sex and county of residency between 1997-2018. The 10th revision of the International Classification of Diseases (ICD) was used to identify fractures. Results: Patients with hypoPT did not have higher risk of any fracture compared to controls (HR 0.96; 95% CI 0.86-1.08). However, patients with hypoPT had a slightly higher risk of vertebral fractures (HR 1.33; 95% CI 1.01-1.75), p= 0.047 and a lower risk of femoral fractures (HR 0.60; 95% CI 0.45-0.82), p= 0.001. There was no significant difference in the risk of fractures of the forearm, p= 0.177, proximal humerus, p= 0.096 or pelvis, p= 0.446. There was no difference in the risk of any fracture between females and males with hypoPT (p for interaction= 0.511). Patients with surgical hypoPT had a significantly higher risk of any fracture compared with patients with non-surgical hypoPT (p for interaction= 0.006). Conclusion: The risk of any fracture was not increased in patients with hypoPT. However, the risk of vertebral fracture was increased, and the risk of femoral fracture was lower than for matched controls. No difference was found in fracture risk between females and males. Patients with surgical hypoPT had a higher fracture risk compared to patients with non-surgical hypoPT. Presentation: Saturday, June 17, 2023

Spinal subependymomas (SE) are rare, often indolent benign tumors presenting most frequently as intramedullary tumors in the cervical spine or cervicothoracic junction. When symptomatic, patients often present with years of sensory changes, weakness, paresthesias, or bowel and bladder dysfunction. Preoperatively, SE are difficult to distinguish radiographically from ependymomas or astrocytomas; however, it is important to make the distinction intraoperatively as complete resection can be curative. Here the authors present a rare case of recurrent, symptomatic cervical subependymoma which underwent gross-total resection and discussion of management strategies and outcomes of all SE at their institution.

Abstract Objectives To compare clinical characteristics, including the frequency of cutaneous, extramuscular manifestations and malignancy, between adults with anti-synthetase syndrome (ASyS) and DM. Methods Using data regarding adults from the MYONET registry, a cohort of DM patients with anti-Mi2/-TIF1γ/-NXP2/-SAE/-MDA5 autoantibodies, and a cohort of ASyS patients with anti-tRNA synthetase autoantibodies (anti-Jo1/-PL7/-PL12/-OJ/-EJ/-Zo/-KS) were identified. Patients with DM sine dermatitis or with discordant dual autoantibody specificities were excluded. Sub-cohorts of patients with ASyS with or without skin involvement were defined based on presence of DM-type rashes (heliotrope rash, Gottron’s papules/sign, violaceous rash, shawl sign, V-sign, erythroderma, and/or periorbital rash). Results In total 1054 patients were included (DM, n = 405; ASyS, n = 649). In the ASyS cohort, 31% (n = 203) had DM-type skin involvement (ASyS-DMskin). A higher frequency of extramuscular manifestations, including Mechanic’s hands, Raynaud’s phenomenon, arthritis, interstitial lung disease and cardiac involvement differentiated ASyS-DMskin from DM (all P < 0.001), whereas higher frequency of any of four DM-type rashes—heliotrope rash (n = 248, 61% vs n = 90, 44%), violaceous rash (n = 166, 41% vs n = 57, 9%), V-sign (n = 124, 31% vs n = 28, 4%), and shawl sign (n = 133, 33% vs n = 18, 3%)—differentiated DM from ASyS-DMskin (all P < 0.005). Cancer-associated myositis (CAM) was more frequent in DM (n = 67, 17%) compared with ASyS (n = 21, 3%) and ASyS-DMskin (n = 7, 3%) cohorts (both P < 0.001). Conclusion DM-type rashes are frequent in patients with ASyS; however, distinct clinical manifestations differentiate these patients from classical DM. Skin involvement in ASyS does not necessitate increased malignancy surveillance. These findings will inform future ASyS classification criteria and patient management.

Across multiancestry groups, we analyzed Human Leukocyte Antigen (HLA) associations in over 176,000 individuals with Parkinson’s disease (PD) and Alzheimer’s disease (AD) versus controls. We demonstrate that the two diseases share the same protective association at the HLA locus. HLA-specific fine-mapping showed that hierarchical protective effects of HLA-DRB1 *04 subtypes best accounted for the association, strongest with HLA-DRB1 *04:04 and HLA-DRB1 *04:07, and intermediary with HLA-DRB1 *04:01 and HLA-DRB1 *04:03. The same signal was associated with decreased neurofibrillary tangles in postmortem brains and was associated with reduced tau levels in cerebrospinal fluid and to a lower extent with increased Aβ42. Protective HLA-DRB1 *04 subtypes strongly bound the aggregation-prone tau PHF6 sequence, however only when acetylated at a lysine (K311), a common posttranslational modification central to tau aggregation. An HLA-DRB1 *04-mediated adaptive immune response decreases PD and AD risks, potentially by acting against tau, offering the possibility of therapeutic avenues.

Abstract Background Pharmacogenomics is an emerging and affordable tool that may improve postoperative pain control. One challenge to successful pain control is the large interindividual variability among analgesics in their efficacy and adverse drug events. Whether preoperative pharmacogenomic testing is worthwhile for patients undergoing TKA is unclear. Questions/purposes (1) Are the results of preoperative pharmacogenetic testing associated with lower postoperative pain scores as measured by the Overall Benefit of Analgesic Score (OBAS)? (2) Do the results of preoperative pharmacogenomic testing lead to less total opioids given? (3) Do the results of preoperative pharmacogenomic testing lead to changes in opioid prescribing patterns? Methods Participants of this randomized trial were enrolled from September 2018 through December 2021 if they were aged 18 to 80 years and were undergoing primary TKA under general anesthesia. Patients were excluded if they had chronic kidney disease, a history of chronic pain or narcotic use before surgery, or if they were undergoing robotic surgery. Preoperatively, patients completed pharmacogenomic testing (RightMed, OneOME) and a questionnaire and were randomly assigned to the experimental group or control group. Of 99 patients screened, 23 were excluded, one before randomization; 11 allocated patients in each group did not receive their allocated interventions for reasons such as surgery canceled, patients ultimately undergoing spinal anesthesia, and change in surgery plan. Another four patients in each group were excluded from the analysis because they were missing an OBAS report. This left 30 patients for analysis in the control group and 38 patients in the experimental group. The control and experimental groups were similar in age, gender, and race. Pharmacogenomic test results for patients in the experimental group were reviewed before surgery by a pharmacist, who recommended perioperative medications to the clinical team. A pharmacist also assessed for clinically relevant drug-gene interactions and recommended drug and dose selection according to guidelines from the Clinical Pharmacogenomics Implementation Consortium for each patient enrolled in the study. Patients were unaware of their pharmacogenomic results. Pharmacogenomic test results for patients in the control group were not reviewed before surgery; instead, standard perioperative medications were administered in adherence to our institutional care pathways. The OBAS (maximum 28 points) was the primary outcome measure, recorded 24 hours postoperatively. A two-sample t-test was used to compare the mean OBAS between groups. Secondary measures were the mean 24-hour pain score, total morphine milligram equivalent, and frequency of opioid use. Postoperatively, patients were assessed for pain with a VAS (range 0 to 10). Opioid use was recorded preoperatively, intraoperatively, in the postanesthesia care unit, and 24 hours after discharge from the postanesthesia care unit. Changes in perioperative opioid use based on pharmacogenomic testing were recorded, as were changes in prescription patterns for postoperative pain control. Preoperative characteristics were also compared between patients with and without various phenotypes ascertained from pharmacogenomic test results. Results The mean OBAS did not differ between groups (mean ± SD 4.7 ± 3.7 in the control group versus 4.2 ± 2.8 in the experimental group, mean difference 0.5 [95% CI -1.1 to 2.1]; p = 0.55). Total opioids given did not differ between groups or at any single perioperative timepoint (preoperative, intraoperative, or postoperative). We found no difference in opioid prescribing pattern. After adjusting for multiple comparisons, no difference was observed between the treatment and control groups in tramadol use (41% versus 71%, proportion difference 0.29 [95% CI 0.05 to 0.53]; nominal p = 0.02; adjusted p > 0.99). Conclusion Routine use of pharmacogenomic testing for patients undergoing TKA did not lead to better pain control or decreased opioid consumption. Future studies might focus on at-risk populations, such as patients with chronic pain or those undergoing complex, painful surgical procedures, to test whether pharmacogenomic results might be beneficial in certain circumstances. Level of Evidence Level I, therapeutic study.

ImportanceSystematic data on the association between anticancer therapies and thromboembolic events (TEEs) in patients with COVID-19 are lacking.ObjectiveTo assess the association between anticancer therapy exposure within 3 months prior to COVID-19 and TEEs following COVID-19 diagnosis in patients with cancer.Design, Setting, and ParticipantsThis registry-based retrospective cohort study included patients who were hospitalized and had active cancer and laboratory-confirmed SARS-CoV-2 infection. Data were accrued from March 2020 to December 2021 and analyzed from December 2021 to October 2022.ExposureTreatments of interest (TOIs) (endocrine therapy, vascular endothelial growth factor inhibitors/tyrosine kinase inhibitors [VEGFis/TKIs], immunomodulators [IMiDs], immune checkpoint inhibitors [ICIs], chemotherapy) vs reference (no systemic therapy) in 3 months prior to COVID-19.Main Outcomes and MeasuresMain outcomes were (1) venous thromboembolism (VTE) and (2) arterial thromboembolism (ATE). Secondary outcome was severity of COVID-19 (rates of intensive care unit admission, mechanical ventilation, 30-day all-cause mortality following TEEs in TOI vs reference group) at 30-day follow-up.ResultsOf 4988 hospitalized patients with cancer (median [IQR] age, 69 [59-78] years; 2608 [52%] male), 1869 had received 1 or more TOIs. Incidence of VTE was higher in all TOI groups: endocrine therapy, 7%; VEGFis/TKIs, 10%; IMiDs, 8%; ICIs, 12%; and chemotherapy, 10%, compared with patients not receiving systemic therapies (6%). In multivariable log-binomial regression analyses, relative risk of VTE (adjusted risk ratio [aRR], 1.33; 95% CI, 1.04-1.69) but not ATE (aRR, 0.81; 95% CI, 0.56-1.16) was significantly higher in those exposed to all TOIs pooled together vs those with no exposure. Among individual drugs, ICIs were significantly associated with VTE (aRR, 1.45; 95% CI, 1.01-2.07). Also noted were significant associations between VTE and active and progressing cancer (aRR, 1.43; 95% CI, 1.01-2.03), history of VTE (aRR, 3.10; 95% CI, 2.38-4.04), and high-risk site of cancer (aRR, 1.42; 95% CI, 1.14-1.75). Black patients had a higher risk of TEEs (aRR, 1.24; 95% CI, 1.03-1.50) than White patients. Patients with TEEs had high intensive care unit admission (46%) and mechanical ventilation (31%) rates. Relative risk of death in patients with TEEs was higher in those exposed to TOIs vs not (aRR, 1.12; 95% CI, 0.91-1.38) and was significantly associated with poor performance status (aRR, 1.77; 95% CI, 1.30-2.40) and active/progressing cancer (aRR, 1.55; 95% CI, 1.13-2.13).Conclusions and RelevanceIn this cohort study, relative risk of developing VTE was high among patients receiving TOIs and varied by the type of therapy, underlying risk factors, and demographics, such as race and ethnicity. These findings highlight the need for close monitoring and perhaps personalized thromboprophylaxis to prevent morbidity and mortality associated with COVID-19–related thromboembolism in patients with cancer.

OBJECTIVE Chordomas are slow-growing tumors derived from notochord remnants. Despite margin-negative excision and postoperative radiation therapy, spinal chordomas (SCs) often progress. The potential of immunohistochemical (IHC) markers, such as epithelial membrane antigen (EMA), combined with machine learning algorithms to predict long-term (≥ 12 months) postoperative tumor progression, has been understudied. The authors aimed to identify IHC markers using trained tree-based algorithms to predict long-term (≥ 12 months) postoperative tumor progression. METHODS The authors reviewed the records of patients who underwent resection of SCs between January 2017 and June 2021 across the Mayo Clinic enterprise. Demographics, type of treatment, histopathology, and other relevant clinical factors were abstracted from each patient’s record. Low tumor progression was defined as more than a 94.3-mm3 decrease in the tumor size at the latest radiographic follow-up. Decision trees and random forest classifiers were trained and tested to predict the long-term volumetric progression after an 80/20 data split. RESULTS Sixty-two patients diagnosed with and surgically treated for SC were identified, of whom 31 were found to have a more advanced tumor progression based on the tumor volume change cutoff of 94.3 mm3. The mean age was 54.3 ± 13.8 years, and most patients were male (62.9%) and White (98.4%). The most common treatment modality was subtotal resection with radiation therapy (35.5%), with proton beam therapy being the most common (71%). Most SCs were sacrococcygeal (41.9%), followed by cervical (32.3%). EMA-positive SCs had a postoperative progression risk of 67%. Pancytokeratin-positive SCs had a progression rate of 67%; however, patients with S100 protein–positive SCs had a 54% risk of progression. The accuracy of this model in predicting the progression of unseen test data was 66%. Pancytokeratin (mean minimal depth = 1.57), EMA (mean minimal depth = 1.58), cytokeratin A1/A3 (mean minimal depth = 1.59), and S100 protein (mean minimal depth = 1.6) predicted the long-term volumetric progression. Multiway variable importance plots show the relative importance of the top 10 variables based on three measures of varying significance and their predictive role. CONCLUSIONS These IHC variables with tree-based machine learning tools successfully demonstrate a high capacity to identify a patient’s tumor progression pattern with an accuracy of 66%. Pancytokeratin, EMA, cytokeratin A1/A3, and S100 protein were the IHC drivers of a low tumor progression. This shows the power of machine learning algorithms in analyzing and predicting outcomes of rare conditions in a small sample size.