ABSTRACT
The UCL Huntington's Disease Centre Multidisciplinary clinic sees over 1,000 patients who from across the country. During the SARS-Covid19 pandemic, the clinic shifted to 100% remote consultation, using the video platform Circuit by Unify (https://eu.yourcircuit.com). The introduction of video platform enabled the clinic to operate throughout the pandemic. After the relaxation of local guidelines, most appointments have returned to in-person appointments, however, some patients, especially distant and care-home residents, continue to request video appointments. Given it is likely that video appointments will be a permanent addition to the service, we set out to evaluate the user experience from our patients to assess whether the video appointments are meeting their needs. To this end, we designed our electronic form specific to our centre, and sent to 100 patients and their carers who used the platform in the preceding 6 months. The survey addresses aspects of patient satisfaction such as convenience of location, technical issues of using the video platform, and waiting times, as well as overall clinical experience. The results will be analysed in two groups. Group 1 will be those without acute psychiatric illnesses, and Group 2 will be those with acute psychiatric illnesses. I will present the results our audit with these groups to evaluate the patient experience of virtual clinic appointments.
ABSTRACT
Ireland had one of the highest levels of COVID-19 in Europe and the numbers of cases and deaths were high especially in residential care settings. Since the onset of the pandemic, entire healthcare and research operations had to be reset, to prevent and manage COVID-19 in a Huntington's Disease (HD) residential care facility in Ireland. Lean Management principles were successfully used initially to manage the clinical caseload and eventually research during the pandemic. The strategy was to cut out the eight areas of 'wastes' as per the Lean Methodology. Initially these principles were applied in HD clinical care and eventually in research when it could be resumed during the pandemic. The first waste 'Waiting' was dealt with by creating of COVID-19 specific ward and buffer zone, 'Inventory' was managed by optimising the procurement and management of Personal protective equipment(PPE), the third waste 'defects' were minimized by continuous in-house training of personnel relevant to minimizing errors and optimizing care for COVID-19, the fourth waste 'transportation' was managed by transitioning the clinical and research visits to remote mode by deploying technology, the waste 'motion' was managed with segregated staff accommodation rosters and technology, 'Overproduction' was managed by optimizing clinical operations using emergency clinical governance initiatives, 'Overprocessing' was managed by eliminating repetitive, redundant, or less than valuable processes and finally 'untapped human potential' was tapped into by retraining and redeployment of staff in transdisciplinary roles. Research operations were completely optimised so that pandemic related restrictions had little effect on achieving research deliverables successfully.
ABSTRACT
Background: Psychiatric symptoms, particularly depression, are common in Huntington’s Disease (HD) patients. Catatonia is relatively rare in this population, and there is no current standardized treatment for catatonic HD patients (Merida-Puga et al., 2011). ECT is not generally used for treatment of psychiatric disorders in HD patients;however, there is evidence that it should be considered for some catatonic HD patients (Mowafi and Millard, 2021). Here, we present the case of a HD patient with catatonia rapidly responsive to ECT and conduct a literature review, adding further evidence of its efficacy in this population. Case: Mr. S is a 60-year-old male with a history of HD, MDD, and anxiety who presented to the ED with suicidal ideation and a plan to overdose due to his disease progression, significant anxiety, and paranoia surrounding the COVID-19 pandemic. He was previously admitted to another psychiatric hospital without clinical benefit. His psychotropic regimen at admission included buspirone, citalopram, deutetrabenazine, paliperidone, propranolol, and tiagabine. Four days into his admission, he was nonresponsive on interview. Given concern for catatonia (Bush-Francis Rating Scale, BFRS, 24), a successful lorazepam challenge was administered. Paliperidone was held and lorazepam was scheduled. In the subsequent days, multiple medication changes were made, including discontinuation of deutetrabenazine given concern for depression exacerbation. ECT was started due to continuation of catatonia symptoms despite scheduled lorazepam (BFRS fluctuating from 1 to 23). Following his first two treatments, he resumed oral intake, and his BFRS reduced to 0. By ECT #3, he was speaking fluently with improvement in his mood and suicidal ideation. Following an initial series of eight ECT, treatments were tapered with maintained improvement. Discussion: Our patient had complete resolution of his catatonia and remission of depression with a short course of ECT, experiencing profound improvement even two treatments into the course. Prior case reports indicated the need for longer ECT courses before resolution with the minimum being five treatments and the maximum being 42 (Mowafi and Millard, 2021). However, our patient has had sustained improvement in mood and catatonia symptoms allowing for minimization of polypharmacy. Implications: Given the neuropsychiatric burden in HD patients, it is important for C-L psychiatrists to be aware of ECT's efficacy for both depression and catatonia in this population. References: 1. Merida-Puga, J., Ramirez-Bermudez, J., Aguilar-Venegas, L. C., Fricchione, G. L., & Espinola-Nadurille, M. (2011). Westphal variant Huntington disease and refractory catatonia: a case report. Cognitive and behavioral neurology: official journal of the Society for Behavioral and Cognitive Neurology, 24(4), 204–208. 2. Mowafi, W., & Millard, J. (2021). Electroconvulsive therapy for severe depression, psychosis and chorea in a patient with Huntington's disease: case report and review of the literature. BJPsych bulletin, 45(2), 97–104.
ABSTRACT
Objective: To evaluate the feasibility of using telemedicine for predictive genetic testing in Huntington's disease (HD). Background: While a specific protocol for genetic testing in HD exists, evidence regarding its applicability via telemedicine is lacking. The implementation of social distancing guidelines during the COVID-19 pandemic led us to utilize telehealth visits in our clinic for predictive testing. Methods: From May 2020 to Sep 2021, eligible patients seen at the UTHealth Houston, HDSA Center of Excellence multidisciplinary clinic were offered predictive genetic testing via telemedicine. The 2016 HDSA recommendations for predictive testing were adapted and implemented via telemedicine. Visits were conducted by a team consisting of a movement disorder specialist, genetic counselor, psychiatrist, neuropsychologist, and social worker utilizing institute-approved telemedicine platforms. Patient satisfaction and telehealth quality were assessed with Telehealth Usability Questionnaire (TUQ), which included the components of usefulness, ease of use, interface quality, interaction quality, reliability, and satisfaction [1]. Results: 50 individuals expressed interest in predictive testing via telemedicine. Of these, 11 did not continue after initial inquiry and three had already prior testing [Fig. 1]. Of the remaining 36 individuals (mean age: 37.17 ± 13.23 years), 21 completed the consent and sample collection with an in-person visit. For 15 elected to use telemedicine consent was obtained via telemedicine, and sample collection was coordinated remotely. 21 individuals had results disclosure via telemedicine, 13 of whom used telemedicine for both visits. Seven out of 21 completed the TUQ and rated the visit usability as 92.5% usefulness, 75.5% ease of use, 78.6% interface quality, 86.7% interaction quality, 64.1% reliability, and 89.3% satisfaction and future use. Conclusion: Delivering the predictive testing protocol via telemedicine depends on various patient and clinician-related factors including ease of use, comfort with the type of visit and technology used. In our experience, a majority of patients who underwent telemedicine for genetic counseling and result disclosure were satisfied and would use this service in the future. Despite the convenience and patient satisfaction, it is imperative that caution is applied prior to determining patient readiness and result disclosure given the sensitive nature of HD gene testing.
ABSTRACT
Objective: To identify the educational needs of students during their Neurology clerkship as COVID-19 altered clinical exposure to Movement Disorders patients at the University of Alabama at Birmingham (UAB). Background: In the pandemic, programs promoted a flipped classroom and an increase in telehealth opportunities for students [1]. To our knowledge, there has not been a comparison of clinical neurology exposure prior to and after the start of the pandemic. Methods: A survey was distributed to all current UAB third- and fourth-year medical students via email. The questionnaire inquired about clinical exposure, recognition of movement disorders, and preferred study materials. Students were divided into pre-COVID (5/2019-3/2020) and post-COVID (6/2020-1/2021) cohorts. Categorical variables were compared with a chi-squared test. Statistical analyses were performed using SPSS version 27.0.1.0 (IBM Corp., Armonk, NY) with significance defined as p < 0.05. Results: We received 63 responses, and 54 students qualified for inclusion. Overall, students in the post-COVID cohort had less exposure to movement disorders patients (p = 0.018). No students were exposed to telehealth, nor did they report interest in this experience. The post- COVID cohort was less likely to experience Huntington's disease (p = 0.003), dystonia (p = 0.028), or functional movement disorders (p = 0.012). Despite the varied experiences, both groups expressed similar capability diagnosing and treating movement disorders, with the exception of diagnosing Huntington's disease (p = 0.051, which approached significance). Conclusion: In this pilot survey, students who completed their Neurology clerkship during the pandemic reported less overall exposure to movement disorders, and specifically with uncommon disorders. This is not surprising, given the restrictions that went into effect as the pandemic began (limited learners in clinic, less inpatient experience, etc.). Regardless, both groups felt capable diagnosing and treating movement disorders, highlighting the importance of supplemental materials. There were several limitations to this study, including a small sample size, recall bias, and varying experiences across branch campuses. Future studies could evaluate the usefulness of incorporating educational materials (such as online modules) into curriculums.
ABSTRACT
Background: Early during the COVID-19 pandemic patient and provider anxiety concerning in-person visits and travel restrictions may have delayed cancer diagnosis and altered treatment. We evaluated changes in clinical presentation and treatment patterns in multiple myeloma (MM) during the early COVID-19 period compared to historical pre-COVID periods. Methods: Using the nationwide Flatiron Health EHR-derived de-identified database, we compared clinical presentation and treatment patterns in the immediate post-COVID period (2020) to a comparable pre-COVID period (2018 and 2019). We focused on two separate clinical settings: 1) patients newly diagnosed with MM during February-June in the years of interest (NEWPT) with evidence of management within 90 days and follow-up for 7 months;and 2) patients diagnosed with MM during 2014-2019 receiving active treatment as of February (2018, 2019, 2020, ACTIVE) and follow-up for 11 months. Delayed clinical presentation was assessed using baseline (90 days before diagnosis/index date) measures of ISS stage, ECOG performance status, anemia, and kidney function. We examined treatment patterns (choice of regimen) of both cohorts in the two time periods. We compared clinical features of initial presentation in pre-COVID and COVID period using Pearson's χ 2 test. For NEWPT, we also utilized Kaplan-Meier curves and log-rank test to compare time to treatment initiation between the two periods. Multivariable Cox proportional hazards regression model with death as a competing risk was used to determine impact of COVID on treatment initiation by adjusting sex, age at diagnosis, race, insurance, stage, baseline ECOG, and hospital setting. All analyses were conducted in SAS (Version 9.4, SAS Institute, Cary, North Carolina) with 2 sided tests and a type I error of 5%. Results: Our study included 1319 NEWPT (964 pre-COVID and 355 COVID) and 2206 ACTIVE (1014 pre-COVID and 1192 COVID) patients. In the NEWPT cohort, we observed no differences between the pre-COVID and COVID periods in terms of baseline characteristics, including clinical features like stage, ECOG performance status, anemia or kidney function (Table A). Patients in the pre-COVID period were more likely to initiate any treatment (91.1% vs 86.2%, p<.01). Median time to treatment initiation was 30 days pre-Covid and 32 days during the Covid period (log-rank test p=0.04, Figure A). After adjusting for patient demographic, clinical features (extent of anemia, hypercalcemia, kidney dysfunction), and hospital variables (US region, practice type academic vs community), the difference between the two periods was not significant (COVID vs pre-COVID hazard ratio=0.88, 95% confidence interval 0.78-1.10, p=0.07). In NEWPT cohort, compared with their pre-COVID counterparts, patients in COVID period were more likely to receive monoclonal antibody (mAb) (14.4% vs 4.8%, p<.01, Figure B) and used IMID-based regimen as their first line of therapy (80.4% vs 74.3%, p<.01). In ACTIVE cohort, more patients in the pre-COVID period were anemic (Hemoglobin <10 g/L, 14.9% vs 9.7%, p<.01) at baseline than those in the COVID period. As in NEWPT cohort, ACTIVE patients in the COVID period used mAb-based regimen more commonly (28.9% vs 16.9%, p<.01) (Figure C). In addition, fewer ACTIVE treatment patients in the COVID period received cyclophosphamide regimens (7.9% vs 15.1% p<.01). Conclusions: During early COVID-19 pandemic we did not observe evidence of delayed diagnosis or more advanced stage, anemia or kidney disease for NEWPT with MM. MM treatment patterns were notable for higher utilization of mAb, IMID-based therapies and decreased use of cyclophosphamide regimens, without significant change in time to treatment initiation. Reassuringly, changes in treatment-patterns during COVID pandemic were modest, some likely reflecting changes in MM treatment landscape (advances in mAb regimens) rather than direct impact of COVID. Further studies are needed to understand how these changes evolve and affect clinical outcomes over time beyond 2020. [Formula presen ed] Disclosures: Neparidze: GlaxoSmithKline: Research Funding;Eidos Therapeutics: Membership on an entity's Board of Directors or advisory committees;Janssen: Research Funding. Zeidan: Jasper: Consultancy;AstraZeneca: Consultancy;Aprea: Consultancy, Research Funding;Gilead: Consultancy, Other: Clinical Trial Committees;Loxo Oncology: Consultancy, Other: Clinical Trial Committees;Astellas: Consultancy;Agios: Consultancy;Kura: Consultancy, Other: Clinical Trial Committees;Jazz: Consultancy;Pfizer: Other: Travel support, Research Funding;Genentech: Consultancy;Geron: Other: Clinical Trial Committees;BMS: Consultancy, Other: Clinical Trial Committees, Research Funding;ADC Therapeutics: Research Funding;Novartis: Consultancy, Other: Clinical Trial Committees, Travel support, Research Funding;Boehringer Ingelheim: Consultancy, Research Funding;Astex: Research Funding;BeyondSpring: Consultancy;Incyte: Consultancy, Research Funding;Daiichi Sankyo: Consultancy;Epizyme: Consultancy;BioCryst: Other: Clinical Trial Committees;Cardiff Oncology: Consultancy, Other: Travel support, Research Funding;Janssen: Consultancy;Ionis: Consultancy;Amgen: Consultancy, Research Funding;Acceleron: Consultancy, Research Funding;AbbVie: Consultancy, Other: Clinical Trial Committees, Research Funding. Podoltsev: Pfizer: Honoraria;PharmaEssentia: Honoraria;Blueprint Medicines: Honoraria;Incyte: Honoraria;Novartis: Honoraria;CTI BioPharma: Honoraria;Bristol-Myers Squib: Honoraria;Celgene: Honoraria. Shallis: Curis: Divested equity in a private or publicly-traded company in the past 24 months. Ma: Celgene/Bristol Myers Squibb: Consultancy, Research Funding. Davidoff: Amgen: Consultancy;AbbVie: Other: Family member consultancy. Huntington: AstraZeneca: Consultancy, Honoraria;TG Therapeutics: Research Funding;Thyme Inc: Consultancy;Flatiron Health Inc.: Consultancy;Genentech: Consultancy;SeaGen: Consultancy;Novartis: Consultancy;Pharmacyclics: Consultancy, Honoraria;Servier: Consultancy;Bayer: Honoraria;DTRM Biopharm: Research Funding;AbbVie: Consultancy;Celgene: Consultancy, Research Funding.
ABSTRACT
Background/objectives: The COVID-19 pandemic led to a dramatic reduction of in-person medical care in the general population;however, impacts have not been well-characterized for patients with hematologic malignancies. This study assessed the impact of COVID-19 on healthcare delivery for patients with hematologic malignancies with documented active treatment. Methods: Patients from the nationwide Flatiron Health electronic health record (EHR)-derived de-identified database with confirmed diagnosis of AML, DLBCL, FL, MCL, CLL or MM, and age ≥ 18 years at initial diagnosis were included. To be included in the study, documented receipt of at least one systemic, non-maintenance line of therapy between March 1, 2016 - February 28, 2021 was required. Patients were categorized into treatment types within lines of therapy: Oral therapy (OralTx);outpatient infusions (OutPtTx);and inpatient infusions, including hematopoietic transplants and CAR-T cell therapy (InPtTx). Monthly visit rates were calculated as the number of visits (telemedicine or in-person [in-clinic treatment administration, vitals, and/or labs]) per active patient per 30-day standardized month. Only visits occurring within a line of therapy were included (i.e. during active therapy, excluding surveillance). Telemedicine was only available for ion during the pandemic period. We used time-series forecasting methods on pre-pandemic monthly visit rate data (March 2016 - February 2020) to estimate projected counterfactual visit rates between March 2020 - February 2021 (expected in-person visit rates if the pandemic had not occurred) for all diseases combined, each disease, and each treatment type. Differences between projected and actual monthly visit rates during the pandemic period were considered statistically significant and related to the pandemic if the actual visit rate was outside of the 95% prediction interval (PI) surrounding the projected estimate. Results: A total of 22,559 patients were included in this analysis (6,241 OralTx, 14,501 OutPtTx, 7,675 InPtTx): 4,069 AML, 3,641 DLBCL, 2,004 FL, 1,899 MCL, 4,574 CLL and 6,701 MM. There was a gradual downward trend in in-person visit rates across all diseases over the study period (March 2016 - February 2021, Figure) and general visit frequencies were lower for OralTx and higher for OutPtTx and InPtTx overall. For all diseases combined, early pandemic months (March - May 2020) saw an 18% (95% PI 8.9% - 25%) reduction in in-person visit rates averaged across OralTx and OutPtTx, with the projected rate being 1.5 (95% PI 1.3 - 1.6) visits per patient per month, compared to an actual rate of 1.2. Reductions in the in-person visit rates were significant for all 3 treatment types for MM, for OralTx for CLL, and for OutPtTx for MCL and CLL. Telemedicine visit rates were greatest for patients who received OralTx, followed by OutPtTx, then InPtTx, with greater use in the early pandemic months and subsequent decrease in later months. All in-person visit rates increased close to predicted rates in the later half of the pandemic period. Conclusions: In treatment of hematologic malignancies, overall documented in-person visit rates for patients on OralTx and OutPtTx significantly decreased during early pandemic months, but returned close to the projected rates later in the pandemic. There were no significant reductions in the overall in-person visit rate for patients on InPtTx. Variability in these trends by disease type was observed, with significant reductions in in-person visits impacting MM, CLL, and MCL. Figure. Visit rates over time according to treatment category [Formula presented] Disclosures: Lau: Roche: Current equity holder in publicly-traded company;Flatiron Health Inc: Current Employment. Wang: Roche: Current equity holder in publicly-traded company;Flatiron Health: Current Employment. Davidoff: AbbVie: Other: Family member consultancy;Amgen: Consultancy. Huntington: Bayer: Honoraria;Thyme Inc: Consultancy;Novartis: Consultancy;Flatiron Health Inc.: Consultancy;Genentech: Consultancy;eaGen: Consultancy;Servier: Consultancy;AstraZeneca: Consultancy, Honoraria;TG Therapeutics: Research Funding;DTRM Biopharm: Research Funding;AbbVie: Consultancy;Pharmacyclics: Consultancy, Honoraria;Celgene: Consultancy, Research Funding. Calip: Pfizer: Research Funding;Roche: Current equity holder in publicly-traded company;Flatiron Health Inc: Current Employment. Shah: AstraZeneca: Research Funding;Seattle Genetics: Research Funding;Epizyme: Research Funding. Stephens: CSL Behring: Consultancy;TG Therapeutics: Membership on an entity's Board of Directors or advisory committees;AstraZeneca: Consultancy;Celgene: Consultancy;JUNO: Research Funding;Mingsight: Research Funding;Abbvie: Consultancy;Arqule: Research Funding;Adaptive: Membership on an entity's Board of Directors or advisory committees;Novartis: Research Funding;Epizyme: Membership on an entity's Board of Directors or advisory committees;Beigene: Membership on an entity's Board of Directors or advisory committees;Innate Pharma: Membership on an entity's Board of Directors or advisory committees;Karyopharm: Membership on an entity's Board of Directors or advisory committees, Research Funding. Miksad: Flatiron Health Inc: Current Employment, Current holder of individual stocks in a privately-held company;Roche: Current equity holder in publicly-traded company. Parikh: GNS Healthcare: Current holder of individual stocks in a privately-held company;Onc.AI: Current holder of individual stocks in a privately-held company;Humana: Honoraria, Research Funding;Nanology: Honoraria;Thyme Care: Honoraria;Flatiron Health Inc: Honoraria. Takvorian: Pfizer: Research Funding;Genentech: Consultancy. Neparidze: GlaxoSmithKline: Research Funding;Janssen: Research Funding;Eidos Therapeutics: Membership on an entity's Board of Directors or advisory committees. Seymour: Flatiron Health Inc: Current Employment;Janssen: Membership on an entity's Board of Directors or advisory committees;Roche: Current equity holder in publicly-traded company;Karyopharm: Honoraria, Membership on an entity's Board of Directors or advisory committees;Pharmacyclics: Membership on an entity's Board of Directors or advisory committees.
ABSTRACT
Background/objectives: The COVID-19 pandemic impacted healthcare visit trends, propelling healthcare systems to reduce in-person visits and hospital admissions and increasingly rely on telemedicine;whether there are differences in these trends across racial groups is unknown. This study investigated potential racial disparities in visits during the pandemic for patients with documented active treatment for hematologic malignancies. Methods: We used the nationwide Flatiron Health electronic health record (EHR)-derived de-identified database to select patients with confirmed diagnosis of AML, DLBCL, FL, MCL, CLL or MM, at least 18 years old at initial diagnosis, and documented race in the EHR as Black/African American or White were included. Patients were categorized into treatment types within lines of therapy: Orals (orals + outpatient infusions with orals) vs. Inpatient treatments (chemotherapy, hematopoietic transplants & CAR-T cell therapy). Monthly visit rates were calculated as the number of visits (telemedicine or in-person [in-clinic treatment administration, vitals, and/or labs]) per active patient per 30-day standardized month, except for months in which the patient was considered not active (e.g. no documented therapy, surveillance). We used time-series forecasting methods on pre-pandemic monthly visit rate data (March 2016 - February 2020) to estimate projected counterfactual monthly visit rates (expected rates if the pandemic did not occur) between March 2020 - February 2021 for all diseases combined, for each disease, each treatment type, and each race. Differences between projected and actual monthly visit rates during the pandemic period were considered significant and related due to the pandemic if the actual visit rate was outside of the 95% prediction interval (PI) surrounding the projected estimate. We used cross-correlation analysis to test for significant differences in visit rates between Black and White patients. Results: The analysis included 17,621 patients (2,225 Black, 15,396 White): 3,041 AML, 2,715 DLBCL, 1,558 FL, 1,511 MCL, 3,813 CLL and 5,244 MM (1,166 Black, 4078 White). Across all diseases and treatment categories, Black patients had no significant reductions in in-person visit rates throughout the pandemic period compared to the projected rates. There was, however, an 18% statistically significant reduction (95% PI 9.9% - 25%) in in-person visit rates for White patients on orals during early pandemic months (March - May 2020) from a projected visit rate of 2.0 (95% PI 1.8 - 2.2) visits per patient per month to an actual visit rate of 1.61. There was no significant reduction in in-person visit rates for White patients on inpatient treatments. Telemedicine uptake was significantly higher for White patients compared with Black patients for all diseases combined across all treatment categories (Figure A & B) (t = 9.5, p < 0.01), AML inpatient treatments (t = 2.4, p = 0.04), MM orals (Figure C) (t = 6.0, p < 0.01) and MM inpatient treatments (Figure D) (t = 2.3, p = 0.04). Conclusions: A tradeoff in reductions in in-person visits and uptake of telemedicine use was observed overall. White patients had significantly higher telemedicine uptake compared with Black patients for both oral and inpatient treatments. In-person visit rates for Black patients were unchanged regardless of treatment category. These in-person visit rates reflect documented telemedicine use disparities, which requires further study into possible compound causes, including economic and societal factors. Figure. Trends over time in telemedicine visit rates for White patients (blue line) and Black patients (black line) [Formula presented] Disclosures: Neparidze: Eidos Therapeutics: Membership on an entity's Board of Directors or advisory committees;GlaxoSmithKline: Research Funding;Janssen: Research Funding. Lau: Flatiron Health Inc: Current Employment;Roche: Current equity holder in publicly-traded company. Wang: Flatiron Health: Current Employment;Roche: Current equity holder in publicly-traded company. Davidoff: Amgen: Consultancy;AbbVie: Other: Family member consultancy. Huntington: Bayer: Honoraria;Servier: Consultancy;Pharmacyclics: Consultancy, Honoraria;Thyme Inc: Consultancy;Genentech: Consultancy;AbbVie: Consultancy;SeaGen: Consultancy;Celgene: Consultancy, Research Funding;Flatiron Health Inc.: Consultancy;DTRM Biopharm: Research Funding;TG Therapeutics: Research Funding;AstraZeneca: Consultancy, Honoraria;Novartis: Consultancy. Calip: Flatiron Health Inc: Current Employment;Roche: Current equity holder in publicly-traded company;Pfizer: Research Funding. Shah: AstraZeneca: Research Funding;Seattle Genetics: Research Funding;Epizyme: Research Funding. Stephens: Adaptive: Membership on an entity's Board of Directors or advisory committees;Celgene: Consultancy;Abbvie: Consultancy;CSL Behring: Consultancy;Novartis: Research Funding;Karyopharm: Membership on an entity's Board of Directors or advisory committees, Research Funding;JUNO: Research Funding;Mingsight: Research Funding;AstraZeneca: Consultancy;Innate Pharma: Membership on an entity's Board of Directors or advisory committees;Beigene: Membership on an entity's Board of Directors or advisory committees;TG Therapeutics: Membership on an entity's Board of Directors or advisory committees;Epizyme: Membership on an entity's Board of Directors or advisory committees;Arqule: Research Funding. Miksad: Flatiron Health Inc: Current Employment, Current holder of individual stocks in a privately-held company;Roche: Current equity holder in publicly-traded company. Parikh: Onc.AI: Current holder of individual stocks in a privately-held company;Humana: Honoraria, Research Funding;Flatiron Health Inc: Honoraria;Thyme Care: Honoraria;Nanology: Honoraria;GNS Healthcare: Current holder of individual stocks in a privately-held company. Takvorian: Genentech: Consultancy;Pfizer: Research Funding. Seymour: Janssen: Membership on an entity's Board of Directors or advisory committees;Roche: Current equity holder in publicly-traded company;Pharmacyclics: Membership on an entity's Board of Directors or advisory committees;Flatiron Health Inc: Current Employment;Karyopharm: Honoraria, Membership on an entity's Board of Directors or advisory committees.