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The impact of the COVID-19 pandemic meant that online teaching in higher education became the default. Educators were, and often now continue to be, required to pivot to online teaching, necessitating them to adapt their teaching delivery, effectively engage students online, and apply existing skills to new and unfamiliar pedagogical contexts. This paper presents a small international case study, investigating the experiences of a diverse group of educators who wanted to learn about engaging students because their higher education institutions were pivoting to online teaching. Following the educators' involvement in professional learning about a particular online engagement framework, the educators used their learning in their planning and online teaching. Data extracted from a deductive coding exercise augmented by qualitative data gleaned from semi-structured interviews was used to explore how the educators enhanced the engagement strategies they implemented in their courses. The findings indicate the types of learning processes used by the educators and how they applied their learning to online teaching. The deductive analysis suggests that the strategies the participants revealed worked well in their online practice correspond with the strategies delineated in the framework.
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INTRODUCTION An increasing body of evidence demonstrates that the COVID-19 pandemic of 2020 saw large reductions in the number of US patients being diagnosed with a variety of conditions, including cancer. A previous real world evidence study based upon analysis of CMS claims data showed a large drop in cancer diagnoses across multiple solid tumor diseases and evidence suggesting changes in testing behaviors for these patients over the period of maximal lockdown measures to mitigate spread of infection. Further, the drop in patient numbers had not returned to normal once these measures were relaxed by the end of June. Therefore, we decided to examine CMS data for the entire year of 2020 and focus on a single sub-group in breast cancer, TNBC. These patients have poor prognosis and are relatively intensively managed;it was reasoned that changes in management, especially testing behavior, might be more apparent in this group than in breast cancer patients as a whole. METHODS CMS data for 2019-20 were queried using a proprietary business rule for identifying TNBC cases and then subdivided into 2 groups: those who received a treatment under a "J" HCPCS code and those who had not. Office visits, Level IV surgical pathology (SP) and immunohistochemistry (IHC) were defined by appropriate HCPCS codes. Since all PD-L1 testing is covered by HCPCS code 88360, a claim for 88360 was considered indicative of a PD-L1 test. A decrease in the number of patients during the COVID-19 pandemic Swas defined as a ≥ 10% drop for the value in a given month in 2020 compared to the same month in 2019, as a percentage of the 2019 median value. This is termed the "COVID-Dip". RESULTS Data were gathered from a total of 68, 018 patients, 8, 131 with a J code treatment and 59, 887 without. Results of COVID dip analysis are presented in Table 1. Trastuzumab administration showed an overall decline across the entire study period. While IHC for 88360 showed a COVID dip, administration of atezolizumab and pembrolizumab increased across the study period with administration of nivolumab (collectively immuno-oncology, IO, drugs) remaining relatively constant. 47% of patients receiving IO therapy received a presumed PD-L1 test. There was longitudinal variation in the use of chemotherapy agents but no apparent COVID dip in their use. DISCUSSION There were declines both in patient presentation to doctors' offices, as well as diagnostic testing among TNBC patients during the COVID-19 pandemic of 2020 with differences between those receiving chemotherapy under J codes and those not. There was no evidence of decline in use of chemotherapy under J codes. Increased IO use but declines in IHC testing suggest a greater use of off-label prescribing of these drugs during the pandemic. The decline in presentation to doctors' offices and in testing of patients not receiving J code drugs suggests that these patients may experience significant delays in management of their condition with concomitant increases in morbidity and mortality.
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The anti-CD38 monoclonal antibody Daratumumab has shown impressive activity in combination with other agents for the treatment of multiple myeloma (MM), improving progression free survival and overall survival in several phase 3 studies. We conducted a phase 1b study of intravenous Daratumumab (16 mg/kg) with weekly subcutaneous bortezomib (1.3-1.5 mg/m 2 ), cyclophosphamide (150-300 mg/m 2), and dexamethasone (40 mg) (CyBorD-DARA) as induction before autologous stem cell transplantation (ASCT), followed by CyBorD-DARA consolidation (2 cycles) and monthly DARA +/- bortezomib (in high-risk disease) maintenance for 24 months. We hypothesized that the addition of cyclophosphamide could lead to enhanced antibody dependent cellular phagocytosis (ADCP). This trial was registered at www.clinicaltrials.gov as NCT02955810. We previously reported the initial results of this study. 1. In addition to a favourable safety profile we observed promising anti-MM activity with 10 of 13 patients (77%) in whom assessment was possible achieving measurable residual disease (MRD) negativity at a sensitivity of 10 -5 by next generation sequencing (NGS) after ASCT. We now report the results at EOT, with a focus on MRD. Eligible patients were ≤70 years of age with untreated transplant-eligible MM. 18 patients were enrolled. Median age was 56.5 years (range, 32-66 years), 61% were male and 94% of patients had Eastern Cooperative Oncology Group performance status ≤1. The International Staging System stages were I, II, and III in 78%, 17%, and 6% of patients, respectively. 29% of patients had high-risk genetic features by fluorescent in situ hybridisation (FISH) or gene expression profiling, including 17p deletion in 12% and t(4;14) and t(14;16) in 6% each. On an ITT basis, the rates of very good partial remission or better (≥VGPR) after ASCT, consolidation and at end of treatment (EOT) (after completion of 24 months of DARA) were 94%, 94% and 81% respectively, and rates of complete response or better (≥CR) were 50%, 63% and 63% respectively. Measurable residual disease (MRD) assessment was possible in 13 patients after induction, ASCT and consolidation, and 10 at EOT. Sustained MRD negativity (ie. MRD negativity after ASCT, consolidation and at EOT) to a level of 10 -5 by NGS was achieved in 33% (ITT). Of 13 patients who remained on study at EOT in VGPR or better, 54% were MRD negative (MRD was unavailable in 23%). 7 patients were MRD negative after both ASCT and consolidation. Of these patients, all evaluable at EOT(6/7) remained MRD negative, with 1 patient unable to undergo MRD assessment due to the COVID-19 pandemic, but remaining in CR. Nausea and diarrhoea occurred in 89% of patients, but were mostly grade 1-2 (Grade ≥3 nausea 17%;diarrhoea 6%). Neutropenia occurred in 44% (Grade ≥3 17%), anaemia in 39% (Grade ≥3 22%), and thrombocytopenia in 33% (Grade ≥3 22%). The rate of neutropenic sepsis was 11%. Infusion-related reactions occurred in 50% (Grade ≥3 6%) and peripheral neuropathy occurred in 33% (Grade ≥3 0%) The most commonly reported serious adverse event (SAE) was sepsis in 22%. One patient developed abnormal liver function tests leading to discontinuation from the trial. CyBorD-DARA induction, consolidation and DARA-maintenance is an effective and well-tolerated IMiD free regimen in transplant-eligible patients with MM. MRD negativity at a level of > 10 -5 after ASCT and consolidation may be predictive of sustained MRD negativity at EOT. References: 1. Naicker SD, et al. Cyclophosphamide alters the tumor cell secretome to potentiate the anti-myeloma activity of daratumumab through augmentation of macrophage-mediated antibody dependent cellular phagocytosis. Oncoimmunology. 2021 Jan 25;10(1):1859263. doi: 10.1080/2162402X.2020.1859263. PMID: 33552684;PMCID: PMC7849715. 2. O'Dwyer M, et al. CyBorD-DARA is potent initial induction for MM and enhances ADCP: initial results of the 16-BCNI-001/CTRIAL-IE 16-02 study. Blood Adv. 2019 Jun 25;3(12):1815-1825. doi: 10.1182/bloodadvances.2019000010. PMID: 31201169;PMCI : PMC6595251. Disclosures: O'Dwyer: ONK Therapeutics: Current Employment, Current equity holder in publicly-traded company, Membership on an entity's Board of Directors or advisory committees;Janssen: Consultancy;Bristol Myers Squibb: Research Funding. Quinn: Takeda: Honoraria. Szegezdi: ONK Therapeutics: Research Funding.
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Background Although the median age of patients with newly diagnosed multiple myeloma (MM) is 70-74 years, recruitment of frail older patients to clinical trials is poor. The International Myeloma Working Group (IMWG) frailty score predicts survival, adverse events and treatment tolerability using age, the Katz Activity of Daily Living, the Lawton Instrumental Activity of Daily Living, and the Charlson Comorbidity Index, rather than age alone. Despite IMWG score prognostic biomarker capability, to date no evidence exists of its predictive biomarker potential. The UK-MRA Myeloma Risk Profile (MRP) has also been shown in both clinical trial and real-world populations to be a prognostic biomarker in transplant ineligible patients but prospective comparisons of the two scores have not been previously conducted. Study Design/Methods The FiTNEss trial (Myeloma XIV, NCT03720041, Figure 1A) is a UK-MRA phase III, multi-centre, randomised controlled trial for newly diagnosed MM patients not suitable for stem cell transplant. The primary objectives are 1) to compare early treatment cessation (<60 days from randomisation) between patients randomised to standard (reactive) and frailty-adjusted (adaptive, based on IMWG score) induction therapy delivery with the triplet ixazomib, lenalidomide and dexamethasone (IRd) 2) to compare progression free survival for maintenance lenalidomide plus placebo (R) and lenalidomide plus ixazomib (IR). The FiTNEss trial is designed as an all-comers study with few exclusion criteria other than necessary for safety including some haematological and biochemical parameters, but there is no exclusion based on renal function. Patients with grade 2 or greater baseline peripheral neuropathy, current systemic infection or recent surgery or other cancer are excluded. Here we report the demographics for the first patients recruited, including IMWG frailty assessments and MRP to demonstrate the feasibility of recruiting frail patients to randomised phase III clinical trials. Results The FiTNEss trial opened on 04/08/2020 during the second wave of the COVID-19 pandemic in the UK. At the time of data cut off (14/07/2021) recruitment is active at 84 sites, with 180 patients randomised. Baseline characteristics for the randomised patients are shown in Figure 1B. The median age of patients is 77 years (range 64, 93) with 36.1% aged 76-80 and 26.1% over 80. In keeping with the older patient population 26.6% have an ECOG performance status of 2 or 3 and 31.7% ISS stage III. The IMWG frailty classification at baseline is FIT 43/180 (23.9%), UNFIT 53/180 (29.4%) and FRAIL 84/180 (46.7%). The effect of using age groups on the definition of patient frailty was explored. The IMWG frailty score defines all patients over 80 as FRAIL whilst an age of 76-80 contributes one point to the score. An analysis of patients' frailty was repeated with the contribution of age removed. For those aged over 80 years (n=47, 100% FRAIL) we found that 20 (42.6%) would have been re-classified as FIT and 18 (38.3%) as UNFIT, with only 9 (19.2%) retaining the FRAIL category. For those aged 76-80 (n=65, 53.8% UNFIT, 46.2% FRAIL) all 35 patients previously classified as UNFIT became FIT (53.8%) whilst 19 (29.2%) classed as FRAIL became UNFIT with 11 (16.9%) remaining FRAIL. The MRP classification, using age as a continuous variable, was Low-risk 45/180 (25.0%), Medium-risk 46/180 (25.6%), High-risk 75/180 (41.7%) and not available for 14/180 (7.8%) patients. Concordance between the IMWG frailty score and the MRP occurred in 48.9% of patients (88/180). 37.2% of FIT patients were classified as MRP Low-risk, 32.1% of UNFIT patients as MRP Medium-risk and 65.5% of FRAIL patients as MRP High-risk. Discussion The FiTNEss trial demonstrates the feasibility of recruiting older, less fit patients to clinical trials. Recruitment of patients classified as FRAIL was very high despite the COVID pandemic, likely due to the all-oral nature of the regimen under investigation enabling patients to avoid attendance at hospital day units for treatment and associa ed exposure risk. In the population recruited to date we found age to be a key contributor to the FRAIL category of the IMWG frailty score. Concordance between IMWG frailty score and MRP was highest in FRAIL/High-risk patients. The first interim analysis of the primary objectives is planned when 50% of required participants for R1 have reached 60 days post R1, which is anticipated in Q2 of 2022. [Formula presented] Disclosures: Cook: Amgen: Consultancy, Honoraria, Research Funding;BMS: Consultancy, Honoraria, Research Funding;Sanofi: Consultancy, Honoraria;Karyopharm: Consultancy, Honoraria;Roche: Consultancy, Honoraria;Pfizer: Consultancy, Honoraria;Oncopeptides: Consultancy, Honoraria;Takeda: Consultancy, Honoraria, Research Funding;Janssen: Consultancy, Honoraria, Research Funding. Pawlyn: Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees;Celgene / BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees;Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees;Amgen: Honoraria. Royle: BMS: Research Funding;Merck Sharpe and Dohme: Research Funding;Amgen: Research Funding;Takeda: Research Funding. Coulson: BMS / Celgene: Honoraria;Merck Sharpe and Dohme: Research Funding;Amgen: Research Funding;Takeda: Research Funding. Jenner: BMS/Celgene: Consultancy, Honoraria, Speakers Bureau;Janssen: Consultancy, Honoraria, Speakers Bureau;Pfizer: Consultancy;Takeda: Consultancy. Kishore: Sanofi: Other: Attending fees;Celgene: Other: Attending fees;Takeda: Other: Attending fees;Jannsen: Other: Attending fees. Rabin: BMS / Celgene: Consultancy, Honoraria, Other: Travel support for meetings;Takeda: Consultancy, Honoraria, Other: Travel support for meetings;Janssen: Consultancy, Honoraria, Other: Travel support for meetings. Best: BMS/Celgene: Research Funding;Merck Sharpe and Dohme: Research Funding;Amgen: Research Funding;Takeda: Research Funding. Gillson: BMS / Celgene: Research Funding;Meck Sharpe and Dohme: Research Funding;Amgen: Research Funding;Takeda: Research Funding. Henderson: Takeda: Research Funding;Amgen: Research Funding;Merck Sharpe and Dohme: Research Funding;BMS / Celgene: Research Funding. Olivier: Merck Sharpe and Dohme: Research Funding;Takeda: Research Funding;Amgen: Research Funding;Celgene / BMS: Research Funding. Kaiser: AbbVie: Consultancy;GSK: Consultancy;Karyopharm: Consultancy, Research Funding;Pfizer: Consultancy;Amgen: Honoraria;Seattle Genetics: Consultancy;Takeda: Consultancy, Other: Educational support;Janssen: Consultancy, Other: Educational support, Research Funding;BMS/Celgene: Consultancy, Other: Travel support, Research Funding. Drayson: Abingdon Health: Current holder of individual stocks in a privately-held company. Jones: Janssen: Honoraria;BMS/Celgene: Other: Conference fees. Cairns: Merck Sharpe and Dohme: Research Funding;Amgen: Research Funding;Takeda: Research Funding;Celgene / BMS: Other: travel support, Research Funding. Jackson: celgene BMS: Consultancy, Honoraria, Research Funding, Speakers Bureau;amgen: Consultancy, Honoraria, Speakers Bureau;takeda: Consultancy, Honoraria, Research Funding, Speakers Bureau;GSK: Consultancy, Honoraria, Speakers Bureau;J and J: Consultancy, Honoraria, Speakers Bureau;oncopeptides: Consultancy;Sanofi: Honoraria, Speakers Bureau. OffLabel Disclosure: Frailty-score adapted dosing strategies
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Introduction Measures taken to mitigate infection spread during the 2020 COVID-19 pandemic are considered to have caused significant unintended consequences on other diseases. Large decreases in the numbers of symptomatic and asymptomatic people presenting for diagnosis of heart disease, diabetes and cancer have been observed. A recent analysis of solid tumors showed up to 70% reduction in the number of patients presenting for diagnosis. The potential exists for significantly increased morbidity and mortality for these missed or delayed presenting patients. Further, it is important to determine whether infection spread mitigation measures affected the diagnostic testing and treatment decisions for these patients. This study aimed to determine whether pandemic control measures affected presentation, testing and treatment of patients across eight different hematologic cancers. Methods CMS claims data were analyzed for the presence of diagnostic (DX) ICD 10 codes indicative of hematologic cancer. Patients with a DX code first appearing in 2019 or in 2020 were selected to provide newly diagnosed pre-COVID-19 and during COVID-19 cohorts for comparison, with unique patient counts being calculated for each month. A “COVID-19 dip” i.e. a decrease in the number of patients was calculated as the change in number of patients diagnosed in a given month relative to the number for JAN2020. Dip duration was calculated only when the decrease was >10% of the JAN2020 figure. Patients who received treatment via a “J” code Healthcare Common Procedure Coding System (HCPCS) code were extracted from the cohorts and the time taken from initial diagnosis to first treatment calculated. Results Eight hematologic cancers: AML, CLL, CML, HEME (a group of different hematologic cancers), Hodgkins (HOG), Myelodysplasia (MDS), Non-Follicular Lymphomas (NFL), and Non-Hodgkins Lymphoma (NHL) showed a decrease in the number of patients being diagnosed during the early part of 2020 (Fig.1) Fig.1. Change in new patient diagnoses for selected hematologic cancers as a proportion of their JAN2020 value There was some variation in the depth and duration of the COVID-19 dip (Table 1) with MDS having both the longest and deepest dip. Median depth and duration of the dip was 33% and 3.5 months, respectively, with all dips starting either in FEB or MAR2020. Table 1. Duration and depth of COVID-19 dips for selected hematological cancers The proportions of patients receiving therapy via J HCPCS code (JRX) are shown in Table 2 Table 2. Proportions of patients receiving J code therapy Conclusions The decline in new patient diagnoses for heme cancers during the period when COVID-19 control measures were implemented is similar to that seen with solid tumors, although the depth of the COVID-19 dip was generally larger in the latter. There is no evidence of “catch up” diagnosis occurring i.e. patients missing from Q2 2020 are not reappearing en masse in subsequent quarters. The decline for MDS patients has, except for SEP to OCT2020, remained. Collectively, (depending on the calculation method), the COVID-19 dip for these eight heme cancers represents 16,584-33,671 patients who will likely have significantly increased rates of morbidity and mortality due to delayed diagnosis. Analysis of J code treatments show little difference between the proportions of patients receiving these treatments in 2020 compared to 2019 suggesting that at least some aspects of treatment e.g. infused chemotherapy, IO drugs for these patients was relatively unchanged by pandemic control measures. It also suggests that the main cause for decreased patient numbers treated is due to decreased testing for diagnosis, rather than not being treated once diagnosed. This aligns with findings from studies in the US and UK. The results of this study indicate that there may be a “backlog” of tens of thousands of people with cancer whose diagnosis has been significantly delayed and who urgently need to be identified in order to get on proper treatment to lessen the impact of that delay. [F rmula presented] Disclosures: No relevant conflicts of interest to declare.