Citations

Objective: To determine if gastrointestinal (GI) symptoms can predict deep endometriosis (DE) of the posterior pelvic compartment on magnetic resonance imaging (MRI). Methods: Patients with suspected endometriosis undergoing endometriosis protocol MRI at an academic center between 9/1/2015 and 7/31/2018 were identified. Presenting GI symptoms were collected via a standardized survey instrument prospectively at initial presentation. MRI and interdisciplinary conference notes were reviewed to identify posterior compartment DE (rectosigmoid, uterosacral ligaments, posterior cul de sac, and pelvic side walls). Associations between symptoms and DE were evaluated. Results: A total of 104 patients met inclusion criteria, and 89 (85.6%) presented with at least one GI symptom. Posterior compartment DE was identified on MRI in 47 patients (45.2%). The GI symptom that most strongly predicted DE was a bowel movement resulting in pain relief (OR 3.36, 95% CI 1.31–8.61, p = 0.012), with sensitivity, specificity, positive and negative predictive values 0.42, 0.82, 0.67, and 0.63, respectively. Other GI symptoms such as nausea, vomiting, rectal bleeding, change in frequency of bowel movements, and pain exacerbation by bowel movements did not significantly correlate to having DE. Of the 15 patients with no GI symptoms, 5 were found to have posterior compartment DE. Conclusion: In patients with suspected endometriosis, those who noted that bowel movements relieved their pain had more than three times the odds of having DE of the posterior compartment on MRI. Preoperative evaluation with MRI may be of value in these patients; however, lack of gastrointestinal symptoms does not exclude the possibility of posterior compartment DE.

Abstract Objective The Genomic Medicine Working Group of the National Advisory Council for Human Genome Research virtually hosted its 13th genomic medicine meeting titled “Developing a Clinical Genomic Informatics Research Agenda”. The meeting’s goal was to articulate a research strategy to develop Genomics-based Clinical Informatics Tools and Resources (GCIT) to improve the detection, treatment, and reporting of genetic disorders in clinical settings. Materials and Methods Experts from government agencies, the private sector, and academia in genomic medicine and clinical informatics were invited to address the meeting's goals. Invitees were also asked to complete a survey to assess important considerations needed to develop a genomic-based clinical informatics research strategy. Results Outcomes from the meeting included identifying short-term research needs, such as designing and implementing standards-based interfaces between laboratory information systems and electronic health records, as well as long-term projects, such as identifying and addressing barriers related to the establishment and implementation of genomic data exchange systems that, in turn, the research community could help address. Discussion Discussions centered on identifying gaps and barriers that impede the use of GCIT in genomic medicine. Emergent themes from the meeting included developing an implementation science framework, defining a value proposition for all stakeholders, fostering engagement with patients and partners to develop applications under patient control, promoting the use of relevant clinical workflows in research, and lowering related barriers to regulatory processes. Another key theme was recognizing pervasive biases in data and information systems, algorithms, access, value, and knowledge repositories and identifying ways to resolve them.

Abstract Objective Artificial intelligence (AI) models may propagate harmful biases in performance and hence negatively affect the underserved. We aimed to assess the degree to which data quality of electronic health records (EHRs) affected by inequities related to low socioeconomic status (SES), results in differential performance of AI models across SES. Materials and Methods This study utilized existing machine learning models for predicting asthma exacerbation in children with asthma. We compared balanced error rate (BER) against different SES levels measured by HOUsing-based SocioEconomic Status measure (HOUSES) index. As a possible mechanism for differential performance, we also compared incompleteness of EHR information relevant to asthma care by SES. Results Asthmatic children with lower SES had larger BER than those with higher SES (eg, ratio = 1.35 for HOUSES Q1 vs Q2–Q4) and had a higher proportion of missing information relevant to asthma care (eg, 41% vs 24% for missing asthma severity and 12% vs 9.8% for undiagnosed asthma despite meeting asthma criteria). Discussion Our study suggests that lower SES is associated with worse predictive model performance. It also highlights the potential role of incomplete EHR data in this differential performance and suggests a way to mitigate this bias. Conclusion The HOUSES index allows AI researchers to assess bias in predictive model performance by SES. Although our case study was based on a small sample size and a single-site study, the study results highlight a potential strategy for identifying bias by using an innovative SES measure.

Abstract Aims Mitral valve prolapse (MVP) is a common valvular heart disease with a prevalence of >2% in the general adult population. Despite this high incidence, there is a limited understanding of the molecular mechanism of this disease, and no medical therapy is available for this disease. We aimed to elucidate the genetic basis of MVP in order to better understand this complex disorder. Methods and results We performed a meta-analysis of six genome-wide association studies that included 4884 cases and 434 649 controls. We identified 14 loci associated with MVP in our primary analysis and 2 additional loci associated with a subset of the samples that additionally underwent mitral valve surgery. Integration of epigenetic, transcriptional, and proteomic data identified candidate MVP genes including LMCD1, SPTBN1, LTBP2, TGFB2, NMB, and ALPK3. We created a polygenic risk score (PRS) for MVP and showed an improved MVP risk prediction beyond age, sex, and clinical risk factors. Conclusion We identified 14 genetic loci that are associated with MVP. Multiple analyses identified candidate genes including two transforming growth factor-β signalling molecules and spectrin β. We present the first PRS for MVP that could eventually aid risk stratification of patients for MVP screening in a clinical setting. These findings advance our understanding of this common valvular heart disease and may reveal novel therapeutic targets for intervention.

Background: Sequencing Mendelian arrhythmia genes in individuals without an indication for arrhythmia genetic testing can identify carriers of pathogenic or likely pathogenic (P/LP) variants. However, the extent to which these variants are associated with clinically meaningful phenotypes before or after return of variant results is unclear. In addition, the majority of discovered variants are currently classified as variants of uncertain significance, limiting clinical actionability. Methods: The eMERGE-III study (Electronic Medical Records and Genomics Phase III) is a multicenter prospective cohort that included 21 846 participants without previous indication for cardiac genetic testing. Participants were sequenced for 109 Mendelian disease genes, including 10 linked to arrhythmia syndromes. Variant carriers were assessed with electronic health record–derived phenotypes and follow-up clinical examination. Selected variants of uncertain significance (n=50) were characterized in vitro with automated electrophysiology experiments in HEK293 cells. Results: As previously reported, 3.0% of participants had P/LP variants in the 109 genes. Herein, we report 120 participants (0.6%) with P/LP arrhythmia variants. Compared with noncarriers, arrhythmia P/LP carriers had a significantly higher burden of arrhythmia phenotypes in their electronic health records. Fifty-four participants had variant results returned. Nineteen of these 54 participants had inherited arrhythmia syndrome diagnoses (primarily long-QT syndrome), and 12 of these 19 diagnoses were made only after variant results were returned (0.05%). After in vitro functional evaluation of 50 variants of uncertain significance, we reclassified 11 variants: 3 to likely benign and 8 to P/LP. Conclusions: Genome sequencing in a large population without indication for arrhythmia genetic testing identified phenotype-positive carriers of variants in congenital arrhythmia syndrome disease genes. As the genomes of large numbers of people are sequenced, the disease risk from rare variants in arrhythmia genes can be assessed by integrating genomic screening, electronic health record phenotypes, and in vitro functional studies. Registration: URL: https://www.clinicaltrials.gov ; Unique identifier; NCT03394859.

Abstract Background: MGTA-145, a CXCR2 agonist, has shown promising activity for hematopoietic stem cell (HSC) mobilization with plerixafor in pre-clinical models and healthy volunteers. It has the potential to become the first GCSF free regimen for HSC mobilization/apheresis in preparation for transplant, with fewer side effects, better patient experience and optimal resource utilization. Methods: We conducted a single center phase 2 trial of MGTA-145 + plerixafor for HSC mobilization in patients with multiple myeloma (MM), NCT04552743. Primary endpoint was collection of ≥2 x 10 6 CD34+ cells/kg in up to 2 days of mobilization/apheresis. Secondary endpoints were collection of 4 and 6 x 10 6 CD34+ cells/kg, safety and engraftment. Patients with MM, 18-70 years of age, within 1 year of starting treatment & CrCl > 30 ml/min were eligible. Patients received plerixafor 0.24 mg/kg (0.16 mg/kg if renal dysfunction) SQ, followed 2 hours later by MGTA-145 (0.03 mg/kg) IV over 3-10 minutes and apheresis within 30 minutes. Mobilization and collection were repeated for a second consecutive day if day 1 yield was < 6 x 10 6 CD34+ cells/kg. The study was open-label single arm trial of 15 patients. If 13 or more patients met primary endpoint, an expansion cohort of 10 patients was planned. The trial has 85% power at a 5% one-sided type I error rate. Our analysis is based on aggregated results from total cohort of 25 patients. Results: Median age was 62 years, 52% were female, 24% had ISS stage 3, 57% had high-risk FISH (primarily gain1q). Induction therapy was VRD in 68% (17), daratumumab VRD in 24% (6), CyBorD in 8% (2) patients. Median duration of induction was 4 months (3-6) and median lenalidomide exposure was 5 cycles (1-8), with > VGPR in 88% of patients. (Table 1) Plerixafor 0.24 mg/kg was given in 24 (96%) patients. Median pre-apheresis CD34 count was day 1, 24/uL (3-99) & day 2, 15/uL (5-46). Median total HSC cell yield (CD34+ cells/kg x 10 6) was 5.0 (1.1-16.2), day 1 yield was 3.4 (0.3-16.2) and day 2 yield was 1.9 (0.5-4.6) (Fig1). 88% (n=22) of patients met the primary endpoint of collecting sufficient HSCs in < 2 days of mobilization + apheresis to proceed to transplant, 68% (17) in 1 day (2 x 10 6 CD34+ cells/kg). 3 patients who did not meet primary endpoint successfully collected HSCs with standard GCSF + plerixafor dosing & 2-3 apheresis sessions. Secondary endpoints of 4 and 6 x 10 6 CD34+ cells/kg in < 2 days were met in 68% (17) and 40% (10) patients. MGTA-145+plerixafor was well tolerated. At least 1 treatment emergent AE (TEAE) with MGTA-145 was seen in 60% of patients (grade 1, n= 14, grade 2, n=1). Pain (all grade 1) was most common, seen in 44% (11), with 38% (9) patients experiencing acute onset transient bone pain with MGTA-145 (duration: 7 minutes, range: 3-28). Using the validated Brief Pain Inventory, 56% (14) patients self-reported pain with mobilization vs 40% (10) at baseline. 7/15 patients without baseline pain reported pain with mobilization. An increase for worst pain was seen on mobilization day 1, that returned to the baseline, but no difference for aggregate score of pain severity/interference (linear mixed effects model). At last follow-up, 18 patients have completed transplant with MGTA-145 mobilized graft, with melphalan 200 mg/m 2 in 15 (83%) patients. Median of 3.5 (2.2-8.1) x 10 6 CD34+ cells/kg were infused. All patients have engrafted. Median time to neutrophil engraftment of 12 days (range: 11-15) & platelet engraftment (platelets > 20,000, no transfusion in 7 days) of 17.5 days (15-33) are comparable to historical data (DiPersio et al. 2009). RBC transfusion was needed in 3 (17%) patients. 14 patients have day 100 follow-up, all with durable engraftment. MGTA-145 + plerixafor mobilized grafts had a favorable graft composition. We observed high enrichment for CD90+CD45RA- among CD34+ cells, a CD34 subset of long term engrafting HSCs (median: 36% of CD34+ cells, range 10-66%, N=25). 74% (17 of 23) grafts were minimal residual disease negative with next generation flow cytometry. Conclusions: This is the first study to evaluate the novel G-CSF-free regimen of MGTA-145 + plerixafor for HSC cell mobilization & collection for hematologic malignancies. The study cohort was representative of transplant eligible patients with MM, with 88% patients meeting the primary endpoint. The regimen was well tolerated. Patients achieved timely & durable engraftment. Our data support further development of this regimen for rapid HSC mobilization. Figure 1 Figure 1. Disclosures Sidana: Janssen: Consultancy, Research Funding; Allogene: Research Funding; Magenta Therapeutics: Consultancy, Research Funding; BMS: Consultancy. Kumar: Bluebird Bio: Consultancy; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Carsgen: Research Funding; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Research Funding; Oncopeptides: Consultancy; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Tenebio: Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Beigene: Consultancy; Antengene: Consultancy, Honoraria; Amgen: Consultancy, Research Funding; Roche-Genentech: Consultancy, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Research Funding; BMS: Consultancy, Research Funding; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Research Funding. Muffly: Pfizer, Amgen, Jazz, Medexus, Pfizer: Consultancy; Astellas, Jasper, Adaptive, Baxalta: Research Funding; Adaptive: Honoraria, Other: fees for non-CME/CE services: , Research Funding. Arai: Magenta Therapeutics: Research Funding. Meyer: Indee, Jura: Consultancy; Orca Biosystems: Research Funding; GigaImmune: Current holder of stock options in a privately-held company; Triursus Therapeutics: Current holder of stock options in a privately-held company. Rezvani: US Department of Justice: Consultancy; Kaleido: Other: One-time scientific advisory board; Nohla Therapeutics: Other: One-time scientific advisory board; Pharmacyclics-Abbvie: Research Funding. Weng: Kite Pharma: Research Funding. Frank: Kite-Gilead: Membership on an entity's Board of Directors or advisory committees; Allogene Therapeutics: Research Funding; Adaptive Biotechnologies: Research Funding. Shiraz: Kite Pharma-Gilead: Research Funding. Girgenti: Magenta Therapeutics: Current Employment. Goncalves: Magenta Therapeutics: Current Employment, Current equity holder in publicly-traded company, Patents & Royalties. Schmelmer: Magenta Therapeutics: Current Employment, Current equity holder in publicly-traded company, Patents & Royalties. Davis: Magenta Therapeutics: Current equity holder in publicly-traded company, Ended employment in the past 24 months. Shizuru: Jasper Therapeutics, Inc.: Current holder of stock options in a privately-held company, Membership on an entity's Board of Directors or advisory committees, Other: Chair of scientific advisory board; Forty seven Inc: Other: Inventor on a patent licenses by Forty Seven. Forty seven was acquired by Gilead in 2020. Miklos: Pharmacyclics: Patents & Royalties; Kite, a Gilead Company, Amgen, Atara, Wugen, Celgene, Novartis, Juno-Celgene-Bristol Myers Squibb, Allogene, Precision Bioscience, Adicet, Pharmacyclics, Janssen, Takeda, Adaptive Biotechnologies and Miltenyi Biotechnologies: Consultancy; Pharmacyclics, Amgen, Kite, a Gilead Company, Novartis, Roche, Genentech, Becton Dickinson, Isoplexis, Miltenyi, Juno-Celgene-Bristol Myers Squibb, Allogene, Precision Biosciences, Adicet, Adaptive Biotechnologies: Research Funding; Adaptive Biotechnologies, Novartis, Juno/Celgene-BMS, Kite, a Gilead Company, Pharmacyclics-AbbVie, Janssen, Pharmacyclics, AlloGene, Precision Bioscience, Miltenyi Biotech, Adicet, Takeda: Membership on an entity's Board of Directors or advisory committees.

Objective: To determine the clinical characteristics and prior medical and surgical treatments in women undergoing surgical excision of endometriosis for pelvic pain at a single institution. Methods: In this retrospective cohort study we identified 140 women with pathology-proven endometriosis who completed a preoperative standardized pain form and underwent surgery at an endometriosis center. Women were stratified into three groups for analysis: no prior surgery, 1 prior surgery, and 2+ prior surgeries. Results: The most common treatments used prior to seeking care were hormonal contraceptives (51.6%) and surgery (46.1%). More than half of women were diagnosed with pelvic floor dysfunction at time of presentation or prior to consultation. There was a significant relationship between an increasing number of surgeries (none vs 1 vs 2+) and gonadotropin-releasing hormone (GnRH) agonist use (19.0% vs 27.5% vs 56.0%, p = 0.003). Though not significant, a trend was noted between increasing surgeries and opioid use (20.6% vs 30.0% vs 40.0%, p = 0.17). There was a statistically significant relationship between multiple surgeries and illicit drug use ( p < 0.001). Conclusion: Patients with pelvic pain and endometriosis who have undergone multiple surgeries are more likely to have used GnRH agonists and report illicit drug use prior to presenting to specialized care.

Abstract IntroductionCurrently, one of the commonly used methods for disseminating electronic health record (EHR)-based phenotype algorithms is providing a narrative description of the algorithm logic, often accompanied by flowcharts. A challenge with this mode of dissemination is the potential for under-specification in the algorithm definition, which leads to ambiguity and vagueness. MethodsThis study examines incidents of under-specification that occurred during the implementation of 34 narrative phenotyping algorithms in the electronic Medical Record and Genomics (eMERGE) network. We reviewed the online communication history between algorithm developers and implementers within the Phenotype Knowledge Base (PheKB) platform, where questions could be raised and answered regarding the intended implementation of a phenotype algorithm. ResultsWe developed a taxonomy of under-specification categories via an iterative review process between two groups of annotators. Under-specifications that lead to ambiguity and vagueness were consistently found across narrative phenotype algorithms developed by all involved eMERGE sites. Discussion & ConclusionOur findings highlight that under-specification is an impediment to the accuracy and efficiency of the implementation of current narrative phenotyping algorithms, and we propose approaches for mitigating these issues and improved methods for disseminating EHR phenotyping algorithms.