ABSTRACT
Background: The COVID-19 pandemic impacted the delivery of cancer care and outcomes in the United States (US). We examined the association between time-varying state-level weekly COVID19 mortality and progression-free survival (rwPFS), time to progression (rwTTP), and survival (rwOS) among pts with advanced non-small cell lung cancer (advNSCLC). Method(s): This retrospective study used the nationwide Flatiron Health electronic health recordderived de-identified database. The cohort included community oncology pts diagnosed with advNSCLC between March 1, 2020 and December 31, 2021 (follow-up through March 30, 2022). We extracted US data on COVID-19 deaths from the COVID-19 Data Repository by the Center for Systems Science and Engineering at Johns Hopkins University. We calculated state-level weekly COVID-19 death rates as weekly COVID-19 deaths per state population size from the 2019 American Community Survey. We categorized rates into quintiles based on all weekly rates during the observation period. Analyses were restricted to treated pts and indexed to start of first-line therapy. For rwPFS analyses, first occurrence of progression or death was considered an event, and pts were censored at last clinic note date. For rwTTP, only progression (not death) was considered an event, and pts with no event were censored at last clinic note date. For rwOS analyses, pts who did not die were censored at last structured activity. We used Cox proportional hazards models to estimate hazard ratios (HR) and 95% confidence intervals (CI) for associations between weekly time-varying state-level COVID-19 mortality rates and outcomes of rwPFS, rwTTP, and rwOS, adjusted for age at diagnosis, race/ethnicity, and state. Result(s): Among 7,813 advNSCLC pts, the median age at diagnosis was 70 years, the majority of the cohort was non-Hispanic White (59%), had non-squamous cell histology (68%) and a history of smoking (87%). Compared to pts living in states with the lowest quintile of COVID-19 mortality rates (Q1), pts living in states with the highest COVID-19 mortality (Q5) had worse rwOS (Q5 vs. Q1: HR 1.46, 95% CI 1.26-1.69) and rwPFS (Q5 vs. Q1: HR 1.18, 95% CI 1.05-1.33). No association was observed with rwTTP (Q5 vs. Q1: HR 1.05, 95% CI 0.90-1.22). Conclusion(s): In this study of real-world oncology data, we demonstrated the use of publicly-available COVID-19 mortality data to measure the time-varying impact of COVID-19 severity on outcomes in pts with advNSCLC. Higher state-level COVID-19 mortality rates were associated with worse rwOS and rwPFS among advNSCLC pts. The association with increased mortality among pts with advNSCLC may be related to COVID-19-related mortality or other factors such as pre-existing comorbidities which were not explored in this study.
ABSTRACT
Background: The COVID-19 pandemic was associated with declines in in-person clinical visits. While telemedicine visits have increased, uptake has varied. Here we assess demographic and socioeconomic factors associated with telemedicine use among patients initiating treatment for 21 common cancers at community oncology clinics. Methods: This retrospective study uses the nationwide Flatiron Health electronic health record-derived de-identified database of patients with cancer. Patient characteristics were determined using structured and unstructured data curated via technology-enabled ion. We included patients (≥ 18 years) who initiated first-line cancer treatment between March 2020 and September 2021 (follow-up through December 2021). We focused on differences in telemedicine use (≥ 1 telemedicine visit within 90 days after treatment initiation) across race/ethnicity, insurance coverage, rurality (per Rural-Urban Commuting Areas), and socioeconomic status (SES). SES was defined using census block group data from the American Community Survey (2015-2019) (quintiles representing least to most affluent areas) based on patient addresses and measured using the Yost Index (incorporating income, home values, rental costs, poverty, blue-collar employment, unemployment, and education information). We used logistic regression models adjusted for clinical characteristics (i.e., age, sex, performance status, and stage) to examine differences in telemedicine use. Results: This study included 24,164 patients (48.1% women, median age: 69 [interquartile range: 61-77] years), of whom 15.9% used telemedicine services. Black patients were less likely to use telemedicine services than White patients (11.4% vs. 15.6%, odds ratio [OR] 0.69 [95% confidence interval [CI]: 0.59-0.79], p<0.01). Telemedicine use was also lower among patients without documented insurance than well-insured (commercial and Medicare payers) patients (10.7% vs. 15.9%, OR 0.62 [95% CI: 0.54-0.72], p<0.01). Those in rural (9.8%, OR 0.51 [95% CI: 0.45- 0.58], p<0.01) and suburban areas (13.1%, OR 0.71 [95%: 0.64-0.79], p<0.01) were less likely to use telemedicine services than patients in urban areas (17.6%). Finally, patients in the least affluent areas had lower telemedicine use than those in the most affluent areas (10.2% vs. 24.3%, OR 0.35 [95% CI: 0.31-0.40], p<0.01). Conclusions: During the COVID-19 pandemic, nearly one-fifth of patients initiating cancer treatment used telemedicine services. However, there were substantial disparities: Black, uninsured, non-urban, and less affluent patients are less likely to use telemedicine services. While telemedicine may expand access to specialty care, the proliferation of these services may widen cancer care disparities if vulnerable populations do not have equitable access.
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.
ABSTRACT
Background:AML is predominantly a disease of the elderly, yet outcomes remain dismal, particularly for relapsed/refractory (R/R) AML patients (pts). Gemtuzumab Ozogamicin (GO) is a monoclonal antibody targeting CD33-commonly expressed on AML blasts, and, critically, AML stem cells (LSC)-linked to the cytotoxin calicheamicin. GO resistance mechanisms include (i) decreased/aberrant blast CD33 expression, (ii) p-glycoprotein export of calicheamicin, and (iii) apoptosis resistance due to deficient activation of mitochondrial outer membrane permeabilization, a process highly dependent on BCL-2 expression. GO-induced apoptosis depends on the pro-apoptotic proteins Bax and Bak and is inhibited by overexpression of the anti-apoptotic proteins BCL-2 or BCL-XL. Venetoclax (VEN) is a BH3 mimetic, binding BCL-2, dislodging its binding to Bak/Bax, and thus facilitating apoptosis. LSC overexpress BCL-2, however VEN monotherapy is not effective in AML, as resistance develops rapidly. Hypothesis: VEN targeting of BCL-2 proteins that protect LSC from GO-induced apoptosis will synergistically increase GO efficacy. Correlative studies include pre-treatment AML blast BH3 profiling, CD33 expression (including sequencing for isoforms), and BCL-2, BCL-XL, and MCL-1 protein levels;MRD measurement at post-therapy time points using digital drop PCR technology;and quality of life assessments (EORTC QLQ-C30, FACT-Fatigue) MethodsThis is a single arm, open-label, multi-center (BTCRC), dose-escalation phase Ib study of combination of VEN and GO in R/R AML pts (18-75y), using a 3+3 design. Major eligibility: ECOG 0-2, adequate organ function, CD33+ in ≥ 20% AML blasts, ≤ 3 lines of prior therapy, and no prior use of GO or VEN, previous VOD, BMT within 2 months, CNS disease, or history of HIV. Induction: 3-day VEN ramp-up to the target dose of 200 (cohort i), 400 (ii), or 600 (iii) mg daily x 28 d, with GO 3mg/m2 infused days 1, 4, and 7. If CR/CRi achieved, pts proceed to BMT if applicable, otherwise, if in CR/CRi (provided ANC > 1000, plts > 100K) or PR (regardless of counts), they are consolidated with VEN at the prescribed dose x 28d and GO 3mg/m2 on days 1 and 4 (Cycle 2). If BMT not applicable, and pt remaining in CR/CRi or PR (as above), then proceed to VEN alone as Maintenance in cycles 3+ until progression or toxicity. The primary endpoint is MTD of VEN with GO. Secondary endpoints include ORR, antileukemic activity, characterization of AEs, and estimates of RFS, EFS, and OS. Progress: This study is currently open to its second dosing cohort and has enrolled 5 pts to date. No dose-limiting toxicities have been encountered. However, the COVID-19 pandemic has had a negative impact on enrollment, which is expected to improve as vaccinations expand. ClinicalTrials.gov NCT04070768.