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Cytogenetics in Essential Thrombocythemia: Phenotype and Molecular Correlates and Prognostic Relevance in 818 Informative Cases
Gangat, Naseema , Kittur, Jaya, Jadoon, Yamna, Hanson, Curtis A. , Wolanskyj, Alexandra P., Tefferi, Ayalew , Szuber, Natasha , Ketterling, Rhett P.

Blood | November 23, 2021 | Volume: 138 | Issue: Supplement 1 | Pages: 3629-3629

10.1182/blood-2021-152549 Get It

Abstract Background Cytogenetic abnormalities at diagnosis are relatively uncommon in essential thrombocythemia (ET). In the current study of 818 consecutive patients with ET who were fully annotated for karyotype, we describe the spectrum and prevalence of cytogenetic abnormalities at diagnosis, followed by a comprehensive assessment of phenotypic and molecular correlates and prognostic relevance. Methods The study cohort consisted of 818 consecutive patients with ET that were diagnosed according to the World health Organization 2016 criteria and underwent evaluation between 1967-2021. In order to minimize the inadvertent inclusion of patients with masked polycythemia vera, JAK2 mutated cases with hemoglobin (Hb) level >16 g/dL in women and 16.5 g/dL in men were excluded; similarly, cases with anemia defined by sex adjusted Hb level of <11 g/dL in women and <12.5 g/dL in men were also excluded, in order to avoid inadvertent inclusion of patients with prefibrotic myelofibrosis. Cytogenetic studies were performed either at or within one year of diagnosis and reported according to the International System for Human Cytogenetic Nomenclature. Disease status and survival information was updated in May 2021. JMP Pro 16.0.0 software package, SAS Institute, Cary, NC was utilized for all analyses. Results Prevalence and spectrum of cytogenetic abnormalities Karyotype was normal in 755 patients (92%), showed loss of Y chromosome (-Y) in 16 (2%), and showed abnormalities other than -Y in 47 (5.7%); most common abnormalities included del(20q) (n=10, 21%), trisomy 9 (n=8, 17%), trisomy 8 (n=2, 4%), del(5q) (n=2, 4%), and del(3p) (n=2, 4%). Other sole cytogenetic abnormalities were identified in 18 (38%) patients. Phenotypic and molecular correlates Abnormal karyotype, other than -Y, in comparison with normal karyotype was associated with older age (median age; 63 vs 58 years, p=0.02), lower hemoglobin level (p=0.003), and a higher incidence of arterial thrombosis prior to/at diagnosis (25% vs 13%; p=0.03). 603 patients were annotated for driver mutations; abnormal/normal/-Y frequencies were 78%/60%/71% for JAK2, 22%/26%/14% CALR, 0%/3%/0% MPL and 0%/10% /14% triple negative (p=0.31). NGS information was available in 226 patients and showed absence of ASXL1 mutation in all patients with abnormal karyotype vs 8/211 (4%) with normal karyotype vs 2/4 (50%) with -Y (p<0.0001). Disease transformation and overall-survival. At a median follow-up of 9.6 years (range; 0.01-49.4 years), a total of 96 patients (12%) underwent fibrotic transformation: 6 (13%) with abnormal karyotype, 89 (12%) with normal karyotype and 1 (6%) with -Y (p=0.77). Leukemic transformation rates were also similar with respective frequencies of 4%, 3% and 0% (p=0.71). Abnormal karyotype and -Y were associated with inferior survival with median of 12 years (range; 0.1-34) and 9 years (range; 0.01- 19.9), respectively, compared to 21 years (range; 0.01-49.4) for normal karyotype (p<0.0001) (Figure). In univariate analysis, risk factors for overall survival included abnormal karyotype (p=0.001), - Y (p=0.004), age >60 years (p<0.0001), leukocytosis >11 x10 9/L (p<0.0001), male gender (p=0.0003), and history of thrombosis (p=0.001). During multivariable analysis, abnormal karyotype other than -Y (p=0.003), age >60 years (p<0.0001), leukocytosis >11 x10 9/L (p=0.001), and male gender (p=0.01) remained significant. Additional analysis suggested individual prognostic impact for del(20q) (p=0.04) and also for trisomy 9 (p=0.09) and other abnormalities (p=0.07), with borderline significance. Conclusion The current study confirms the association of abnormal karyotype in ET with older age, lower hemoglobin level, and history of arterial thrombosis, and its mutual exclusivity with ASXL1 mutations. Our observation regarding the independent adverse impact of abnormal karyotype other than -Y, on overall survival, in the absence of association with fibrotic or leukemic transformation, requires clarification from additional studies, which should also investigate the effect of specific abnormalities. Figure 1 Figure 1. Disclosures Szuber: Novartis: Honoraria.
Deciphering the Individual Contribution of Absolute Neutrophil, Lymphocyte and Monocyte Counts to Thrombosis Risk in Patients with Myeloproliferative Neoplasms
Farrukh, Faiqa, Pardanani, Animesh , Hanson, Curtis A. , Barbui, Tiziano , Gangat, Naseema , Tefferi, Ayalew , Guglielmelli, Paola , Loscocco, Giuseppe Gaetano , Stefano, Valerio De , Vannucchi, Alessandro M.

Blood | November 23, 2021 | Volume: 138 | Issue: Supplement 1 | Pages: 3651-3651

10.1182/blood-2021-149207 Get It

Abstract Background In addition to its influence on survival, leukocytosis in myeloproliferative neoplasms (MPN) has also been implicated as a risk factor for thrombosis, including venous thrombosis in PV (Blood Cancer J, 2017;7:662) and arterial thrombosis in ET (Blood. 2011;117:5857). In the current study, we sought to clarify the individual prognostic contribution of absolute neutrophil (ANC), lymphocyte (ALC) and monocyte (AMC) counts, for arterial and venous thrombotic events in essential thrombocythemia (ET) and polycythemia vera (PV). Methods The current study included 487 patients with ET (n=349) or PV (n=138), recruited from the Mayo Clinic MPN database, based on availability of information on ANC, ALC and AMC. Conventional criteria were used for diagnosis (Blood 2016;127:2391) and definitions of major vascular events (Blood Cancer J. 2018;8:25). Conventional statistical models were applied using JMP Pro 14.0.0 software package, SAS Institute, Cary, NC. Multivariable analyses included previously established risk factors for arterial or venous thrombosis. Results Essential thrombocythemia patients: 349 patients (median age 57 years, range 18-89; females 61%) with ET were included in the study: 46% JAK2, 34% CALR, 16% triple-negative and 4% MPL mutated; IPSET risk category high 24%, intermediate 41%, and low 35%; presenting median (range) values were 13.8 g/dL (11.1-16.4) for hemoglobin, 8.2 x 10(9)/L (3.2-52) for leukocyte count, and 859 x 10(9)/L (451-3460) for platelet count; palpable splenomegaly was present in 48 (14%) patients and cardiovascular risk factors in 56%; median follow-up was 10 years (range 0-47). There were 38 (11%) documented venous events at diagnosis and 31 (9%) after diagnosis and 42 (12%) arterial events at diagnosis and 64 (18%) after diagnosis. Polycythemia vera patients: 138 patients (median age 62 years, range 20-94; females 50%) with PV were included in the study; presenting median (range) values were 17.9 g/dL (16.1-24) for hemoglobin, 11.8 x 10(9)/L (2.7-65.8) for leukocyte count, and 434 x 10(9)/L (44-1679) for platelet count; 57% of patients presented with leukocytosis >11 x 10(9)/L; palpable splenomegaly was present in 37 (27%) patients; abnormal karyotype was documented in 17% of patients. Median follow-up was 11 years (range 0.03-36.7). There were 22 (16%) documented venous events at diagnosis and 21 (16%) after diagnosis and 28 (20%) arterial events at diagnosis and 15 (11%) after diagnosis. ANC/ALC/AMC associations with thrombosis in ET and PV: In both ET and PV, ANC/ALC/AMC did not correlate with arterial thrombosis at/prior to diagnosis (p>0.1 in all instances). By contrast, in both ET and PV, higher ANC (p=0.05 and 0.04, respectively) and higher AMC (p=0.005 and 0.07), but not ALC (p=0.6 and 0.7), were correlated with venous thrombosis at/prior to diagnosis. Arterial thrombosis-free survival was not affected by ANC/ALC/AMC in either ET or PV (p>0.1 in all instances). By contrast, venous thrombosis-free survival in both ET and PV was compromised by higher ANC (p=0.05 and 0.003, respectively), but not ALC or AMC. The significant association between higher ANC and inferior venous thrombosis-free survival in both ET (p=0.01) and PV (p=0.007) was sustained during multivariable analysis that included history of venous thrombosis, age and sex; the only other variable of significance was older age in ET (p<0.001). The significant association between ANC and venous thrombosis-free survival was also noted in an external cohort of PV patients from the University of Florence (n=576). Conclusions: The current study identifies ANC as having a direct correlation with venous thrombosis in both ET and PV, independent of currently known risk factors. An additional risk contribution from AMC was apparent for events occuring at or prior to but not after diagnosis. Taken together, these observations flag both neutrophils and monocytes as potential contributors to venous but not arterial thrombosis in MPN, at least not by themselves. Additional collaborative studies are ongoing in order to integrate and reconcile our observations in the context of neutrophil/lymphocyte ratio (Carobbio et al) and JAK2V617F allele burden (Loscocco et al), on venous thrombosis-free survival in PV, reported in concomitantly submitted ASH 2021 abstracts, especially in light of the relatively small number of events in the current study. Disclosures Barbui: Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding; AOP Orphan: Membership on an entity's Board of Directors or advisory committees, Research Funding. Vannucchi: AbbVie: Membership on an entity's Board of Directors or advisory committees; Incyte Corporation: Honoraria, Membership on an entity's Board of Directors or advisory committees; Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees.
The 1.5 Million Platelet Count Threshold in Essential Thrombocythemia: Phenotype and Genotype Correlates and Relevance to Vascular Events
Gangat, Naseema , Jadoon, Yamna, Farrukh, Faiqa, Rossi, Elena, Ramundo, Francesco , Hanson, Curtis A. , Wolanskyj, Alexandra P., Pardanani, Animesh , Barbui, Tiziano , Tefferi, Ayalew , Szuber, Natasha , Stefano, Valerio De , Vannucchi, Alessandro M.

Blood | November 23, 2021 | Volume: 138 | Issue: Supplement 1 | Pages: 3630-3630

10.1182/blood-2021-149223 Get It

Abstract Background Current NCCN and ELN guidelines lack supporting evidence in regards to initiation of cytoreductive therapy in essential thrombocythemia (ET) with extreme thrombocytosis (ExT) ≥1500 x 10 9/L (NCCN guidelines: myeloproliferative neoplasms, version 2. 2019, Barbui, Leukemia, 2018).; we sought to determine prevalence and establish phenotype and genotype correlates for ET with ExT and assess its impact on thrombotic and bleeding events, in the context of aspirin therapy or cytoreduction. Methods 1,249 WHO-defined ET patients evaluated over five decades (1967-2021) were retrospectively recruited from the Mayo Clinic. Conventional criteria were used to define major arterial and venous thrombosis and major hemorrhage. Conventional statistical methods were applied using JMP Pro 14.0.0 software package, SAS Institute, Cary, NC. Results i) Phenotype and genotype correlates Among 1,249 consecutive patients with ET, 104 (8%) displayed Ext ≥1500 x 10 9/L, at time of initial diagnosis; these patients were characterized by younger age (median 47 vs 59 years; p<0.001) female gender (80% vs 62%; p<0.001), CALR mutation (39% vs 25%; p=0.004), lower hemoglobin (median 13.1 vs 13.7 g/dl; p<0.0001), leukocytosis ≥11 x 10 9/l (42% vs 23%; p<0.0001), and palpable splenomegaly (22% vs 14%; 0.03); multivariable analysis confirmed associations with age, anemia, leukocytosis, and CALR mutation. Acquired von Willebrand syndrome was reported in 4/9 (44%) vs 27/78 (35%) tested patients, with or without Ext ≥1500 x 10 9/L, respectively (p=0.57); however, comparison using platelet ≥1000 x 10 9/L resulted in near-signficant difference (46% vs 29%; p=0.11). NGS was performed in 297 patients and showed a non-sigificant association with U2AF1 mutations (5% vs 0.4%; p=0.11). ExT ≥1500 x 10 9/L was present in 25/986 (3%), 42/891 (5%), and 15/558 (3%) in the validation cohort; the limited number of cases precluded comparative analyses. ii )Correlation with vascular events at/prior to diagnosis Arterial or venous thrombosis at/prior to diagnosis occurred in 190 (15%) and 111 (9%) patients, respectively, and major hemorrage in 50 (4%). Ext ≥1500 x 10 9/L was associated with major hemorrhage (HR 2.9; 1.3-6.3), but not with arterial (p=0.15) or venous (p=0.41) thrombotic events, at/prior to diagnosis. Instead, multivariable analysis for events at/prior to diagnosis identified male gender (p=0.02), JAK2 mutation (p=0.01), and cardiovascular risk factors (p=0.001) as risk factors for arterial thrombosis and JAK2 mutation (HR 2.8; 1.4-5.7) as a risk factor for venous thrombosis. iii ) Correlation with vascular events after diagnosis At median follow-up of 10 years, arterial or venous thrombosis occurred in 222 (18%) and 97 (8%) patients, respectively, and major hemorrage in 128 (11%). Ext ≥1500 x 10 9/L at diagnosis was not associated with arterial (p=0.35) or venous (p=0.23) thrombosis-free survival or hemorrhage-free survival (p=0.24). Instead, multivariable analysis identified age >60 years, presence of cardiovascular risk factors, and history of arterial thrombosis, as risk factors for arterial thrombosis-free survival; and male gender and history of venous thrombosis as risk factors for venous thrombosis-free survival; and age >60 years and leukocytosis of ≥11 x 10 9/L as risk factors for hemorrhage-free survival. In addition, aspirin therapy was idependently protective of venous thrombosis (HR 0.5; 0.2-0.9), and also of arterial thrombosis, in univariate analysis (HR 0.6; 0.3-0.9), without being associated with an increased risk of major hemorrhage (p=0.64); by contrast, beneficial effect from cytoreductive therapy was not evident for either arterial (p=0.37) or venous (p=0.77) thrombosis. In low-risk patients with Ext ≥1500 x 10 9/L, both aspirin and cytoreductive therapy were protective of venous events (Figure 1), without affecting hemorrhage-free survival. Conclusion ExT ≥1500 x 10 9/L in ET was associated with major hemorrhage at diagnosis but did not affect thrombosis-free or hemorrhage-free survival. Initial therapy with aspirin and/or cytoreductive therapy was protective of venous events in ET patients with ExT ≥1500 x 10 9/L, including those with low-risk disease, without enhancing the risk of hemorrhage. The limited number of informative cases with ExT in the validation cohort, underscore the foreseeable challenges associated with controlled studies. Figure 1 Figure 1. Disclosures Szuber: Novartis: Honoraria. Vannucchi: AbbVie: Membership on an entity's Board of Directors or advisory committees; Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; Incyte Corporation: Honoraria, Membership on an entity's Board of Directors or advisory committees; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees. Barbui: AOP Orphan: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding.
Relationship and Susceptibility to Serious Infections Among Monoclonal B-Cell Lymphocytosis (MBL), Monoclonal Gammopathy of Undetermined Significance (MGUS), and Clonal Hematopoiesis (CH) Premalignant Conditions
Kleinstern, Geffen , Call, Timothy G. , Murray, David , Kumar, Shaji , Hanson, Curtis A. , Shanafelt, Tait D. , Vachon, Celine M. , Shanafelt, Tait D , Boddicker, Nicholas , Parikh, Sameer A. , Norman, Aaron D. , Rabe, Kari G. , Olson, Janet E. , Dispenzieri, Angela , Rajkumar, S. Vincent , Cerhan, James R. , Kay, Neil E. , Braggio, Esteban , Vachon, Celine M. , Slager, Susan L.

Blood | November 23, 2021 | Volume: 138 | Issue: Supplement 1 | Pages: 3739-3739

10.1182/blood-2021-151929 Get It

Abstract Introduction Monoclonal B-cell lymphocytosis (MBL), monoclonal gammopathy of undetermined significance (MGUS), and clonal hematopoiesis (CH) are three common premalignant hematological conditions. MBL is a precursor to chronic lymphocytic leukemia (CLL), MGUS is a precursor to both multiple myeloma (MM) and Waldenström macroglobulinemia (WM), and CH is a possible precursor to myeloid disease. All three conditions are independently associated with aging. Furthermore, there is evidence that all three conditions are associated with increased risk of infection. The relationship among these conditions, the prevalence with which they co-exist, and the association between the number of premalignant conditions and risk of infection is unknown. Methods Study participants from the Mayo Clinic Biobank, a large-scale biorepository of adult patients, provided a peripheral blood sample between 7/14/2009 to 06/18/2015. Individuals were screened for MBL using eight-color flow cytometry capable of detecting clonal B-cells to the 0.005% level. MGUS was screened using a matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) assay. CH was screened using a targeted sequencing panel of 42 CH-associated genes with at least 1000x read depth and the ability to detect variant allele fractions down to 1%. All study participants resided in Olmsted County, Minnesota, the county that includes Mayo Clinic. Serious infection, defined as hospitalization due to infection, was abstracted from medical records from the time of sample collection through 12/31/2020 or date of death. The medical record abstractor collecting data was blinded to condition. Logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI) for the association between each of the conditions. Cox regression was used to estimate hazard ratios (HR) and 95% CI to assess the association between number of premalignant conditions with risk of infection. All analyses were adjusted for age at sample collection and sex. Results A total of 407 individuals (55% male, median age 68 years) were screened for all three conditions. The prevalence was 19.9% (n=81) for MBL, 14.5% (n=59) for MGUS, and 25.6% (n=104) for CH. When we evaluated the association between each of the conditions, we found no evidence of an association between the prevalence of CH and risk of MBL (OR=0.79, 95% CI: 0.43-1.42), CH and risk of MGUS (OR=1.24, 95% CI: 0.66-2.27), or MGUS and risk of MBL (OR=1.32, 95% CI:0.66-2.52). The prevalence of co-existence of these conditions was assessed by grouping individuals based on their condition or conditions (Figure 1A). We found that 197 (48.4%) study participants had at least one premalignant condition and 10.6% had two or more. Individuals with 2 or more conditions were the oldest (median age 74 years), followed by 1 condition (median 69 years) and 0 conditions (median 67 years, P-trend <0.001). Sex was not significantly different across the groups, with 55%, 58%, and 47% male for 0, 1, and 2 conditions, respectively. Medical record abstraction identified 97 serious infection events in 80 individuals. Medical records were not available on 7 individuals. The most common infections were urinary tract (20 events), pneumonia (14 events), and cellulitis (14 events). Median follow-up time was 10.6 years (range 0.1-11.5 years). Compared to individuals with no condition, MBL (HR=1.75, 95% CI: 1.06-2.88) and MGUS (HR=1.75, 95% CI: 1.04-2.93) were associated with increased risk of serious infection. We found no evidence of an association with CH (HR=1.15, 95% CI: 0.71-1.87). When grouped by the number of conditions, we observed a significant trend (P-trend <0.01, Figure 1B) in risk of serious infections by the number of conditions: individuals with 1 condition had a 35% increased risk of infections (HR=1.35, 95% CI:0.83-2.20) and individuals with 2 or more conditions had a 2.6-fold increased risk (HR=2.58, 95% CI: 1.37-4.84). Discussion At least one premalignant condition was present in nearly 50% of the study population, with CH being the most prevalent. No evidence of a relationship between any of the three conditions was observed. However, we found increased susceptibility to serious infections as the number of conditions increased with individuals with at least two conditions had 2.6-fold increased risk of infections. Figure 1 Figure 1. Disclosures Parikh: Pharmacyclics, AstraZeneca, Genentech, Gilead, GlaxoSmithKline, Verastem Oncology, and AbbVie: Membership on an entity's Board of Directors or advisory committees; Pharmacyclics, MorphoSys, Janssen, AstraZeneca, TG Therapeutics, Bristol Myers Squibb, Merck, AbbVie, and Ascentage Pharma: Research Funding. Dispenzieri: Takeda: Research Funding; Alnylam: Research Funding; Pfizer: Research Funding; Oncopeptides: Consultancy; Sorrento Therapeutics: Consultancy; Janssen: Consultancy, Research Funding. Murray: Mayo Clinic: Other: Has received patents for the Mass-Fix technology which has been licensed to the Binding Site with potential royalties.. Kumar: Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Merck: Research Funding; Oncopeptides: Consultancy; Beigene: Consultancy; Novartis: Research Funding; KITE: Consultancy, 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; Antengene: Consultancy, Honoraria; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Tenebio: Research Funding; Roche-Genentech: Consultancy, Research Funding; Bluebird Bio: Consultancy; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Carsgen: Research Funding; Amgen: Consultancy, Research Funding; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Consultancy, Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Research Funding. Cerhan: Regeneron Genetics Center: Other: Research Collaboration; Genentech: Research Funding; Celgene/BMS: Other: Connect Lymphoma Scientific Steering Committee, Research Funding; NanoString: Research Funding. Kay: TG Therapeutics: Research Funding; Morpho-sys: Membership on an entity's Board of Directors or advisory committees; Agios Pharm: Membership on an entity's Board of Directors or advisory committees; Targeted Oncology: Membership on an entity's Board of Directors or advisory committees; AstraZeneca: Membership on an entity's Board of Directors or advisory committees; Abbvie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncotracker: Membership on an entity's Board of Directors or advisory committees; Sunesis: Research Funding; MEI Pharma: Research Funding; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol Meyer Squib: Membership on an entity's Board of Directors or advisory committees, Research Funding; Acerta Pharma: Research Funding; Rigel: Membership on an entity's Board of Directors or advisory committees; Tolero Pharmaceuticals: Research Funding; Genentech: Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Behring: Membership on an entity's Board of Directors or advisory committees; CytomX Therapeutics: Membership on an entity's Board of Directors or advisory committees; Dava Oncology: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Juno Therapeutics: Membership on an entity's Board of Directors or advisory committees. Shanafelt: Genentech, Pharmacyclics: Research Funding.
Quality of Life in Patients
Wang, Victoria , Hanson, Curtis A. , Thomas, Mary L., Paietta, Elisabeth , Leis, José F., Zhang, Cong Christine, Steven, Coutre, Cashen, Amanda F. , Mato, Anthony R. , Singh, Avina K., Little, Richard F. , Stone, Richard M. , Litzow, Mark R. , Tallman, Martin S. , Shanafelt, Tait, Shanafelt, Tait D. , Shanafelt, Tait D , Pophali, Priyanka A. , Zhao, Fengmin , Kay, Neil E. , Thomas, Mary L., O’Brien, Susan , Barrientos, Jacqueline C. , Barr, Paul M. , Erba, Harry Paul , Wagner, Lynne I.

Blood | November 23, 2021 | Volume: 138 | Issue: Supplement 1 | Pages: 1562-1562

10.1182/blood-2021-150462 Get It

Abstract Background: The ECOG-ACRIN randomized phase 3 clinical trial E1912 established ibrutinib-rituximab (IR) as the standard of care for CLL patients <= 70 years in the frontline setting by improving the progression free (PFS) and overall survival (OS) compared to previous standard chemo-immunotherapy with fludarabine, cyclophosphamide and rituximab (FCR) (Shanafelt et al. NEJM 2019). Quality of life (QOL) was an important secondary endpoint on this trial comparing continuous (IR) vs time-limited (FCR) therapy due to the differing profile of treatment-related toxicities over the short and long-term. E1912 patient-reported outcomes (PROs) results are presented here. Methods: Patients enrolled on E1912 completed the Functional Assessment of Cancer Therapy-General (FACT-G) and Leukemia subscale at randomization (baseline), 3, 6, and 12 months post-randomization, and every 6 months for 2 years regardless of disease status. The primary outcome was the 31-item FACT-Leukemia Trial Outcome Index (FACT-Leu TOI), calculated by summing items from the FACT-G physical wellbeing (PWB), functional well-being (FWB), and leukemia subscales (score range: 0-124). The primary endpoint was defined as the difference in FACT-Leu TOI change scores from randomization to 12 months (at response evaluation) between patients treated with continuous therapy Arm A (IR) vs time-limited therapy Arm B (FCR). Mean change scores from baseline to each time point were calculated using all cases with data at baseline and the corresponding time point. Comparisons between treatment arms were performed using two-sample t tests. Linear mixed effects models were used to estimate the trajectories of PRO scores. Results: PRO data was extracted on 3/8/2021. PRO data was provided at baseline and 12 months for 233/354 (65.8%) patients on the IR arm and 118/175 (67.4%) patients on the FCR arm. At enrollment, there were no significant differences in the baseline FACT-Leu TOI scores (mean ± SE) between the two arms: IR (93.27 ± 1.03) vs FCR (92.68 ± 1.38; p=0.73). The FACT-Leu TOI score improved from baseline to 12 months in both arms (Table 1 and Figure 1). The change scores from baseline to 12 months, the primary outcome, were not significantly different between IR (7.59 ± 1.09) vs FCR (8.22 ± 1.44; p=0.73). Change in FACT-Leu TOI from baseline to 3 months was 5.77 ± 0.77 and 4.06 ± 1.18 (p=0.22); and from baseline to 6 months was 6.87 ± 0.87 and 8.01 ± 1.44 (p=0.50) in the IR and FCR arms, respectively. After the first 6 months of treatment, the improvement in FACT-Leu TOI scores was maintained in both treatment arms. There was no significant difference in total FACT-Leu TOI score in the continuous therapy (IR) vs time-limited therapy (FCR) arms over the first 36 months post registration. Analysis of FACT subscales showed PWB improved in the IR arm (0.37 ± 0.22) and declined in the FCR arm (-0.92 ± 0.39) from baseline to 3 months (p=0.004 for difference in PWB change between arms) but there was no significant difference between the two arms for change in PWB scores from baseline to 6 and 12 months. There were no significant differences between the two arms for change in FWB and FACT-Leu subscales from baseline to 3, 6 and 12 months. Conclusions: QOL improves in CLL patients age 70 and younger when treated in the frontline setting with IR or FCR. The improvement in QOL is maintained during continuous therapy with ibrutinib and there is no significant decline in QOL over time. Given the improvement in PFS and OS with IR over FCR seen in E1912, the results of this QOL analysis support the use of frontline ibrutinib in previously untreated younger CLL patients. Acknowledgement: This study was conducted by the ECOG-ACRIN Cancer Research Group (Peter J. O'Dwyer, MD and Mitchell D. Schnall, MD, PhD, Group Co-Chairs) and supported by the National Cancer Institute of the National Institutes of Health under award numbers: U10CA180794, U10CA180820, UG1CA189863, UG1CA190140, UG1CA232760, UG1CA233180, UG1CA233230, UG1CA233253, UG1CA233277, UG1CA233290, UG1CA233339, UG1CA189859, UG1CA233332. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Figure 1 Figure 1. Disclosures Kay: Oncotracker: Membership on an entity's Board of Directors or advisory committees; CytomX Therapeutics: Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Tolero Pharmaceuticals: Research Funding; Acerta Pharma: Research Funding; Behring: Membership on an entity's Board of Directors or advisory committees; Abbvie: Membership on an entity's Board of Directors or advisory committees, Research Funding; TG Therapeutics: Research Funding; AstraZeneca: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Juno Therapeutics: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Agios Pharm: Membership on an entity's Board of Directors or advisory committees; Rigel: Membership on an entity's Board of Directors or advisory committees; Dava Oncology: Membership on an entity's Board of Directors or advisory committees; Morpho-sys: Membership on an entity's Board of Directors or advisory committees; Targeted Oncology: Membership on an entity's Board of Directors or advisory committees; MEI Pharma: Research Funding; Sunesis: Research Funding; Genentech: Research Funding; Bristol Meyer Squib: Membership on an entity's Board of Directors or advisory committees, Research Funding. O'Brien: Amgen, Astellas, Celgene, GlaxoSmithKline, Janssen Oncology, Aptose Biosciences Inc., Vaniam Group LLC, AbbVie, Alexion, Verastem, Juno Therapeutics, Vida Ventures, Autolus, Johnson and Johnson, Merck, Bristol Myers Squibb, NOVA Research Company, Eli Lill: Consultancy; Kite, Regeneron, Acerta, Caribou, Gilead, Pharmacyclics, TG Therapeutics, Pfizer, Sunesis: Research Funding. Coutre: Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pharmacyclics: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; AstraZeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees; Beigene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other: Data Safety Monitoring Committee, Research Funding; Genentech: Consultancy, Membership on an entity's Board of Directors or advisory committees; Acerta: Other: Data Safety Monitoring Committee, Research Funding. Barr: AstraZeneca: Consultancy; Gilead: Consultancy; Janssen: Consultancy; Genentech: Consultancy; Beigene: Consultancy; Bristol Meyers Squibb: Consultancy; Seattle Genetics: Consultancy; TG Therapeutics: Consultancy; Morphosys: Consultancy; Abbvie/Pharmacyclics: Consultancy. Cashen: Secura Bio, ADC Therapeutics: Consultancy. Mato: Adaptive Biotechnologies: Consultancy, Research Funding; DTRM BioPharma: Consultancy, Research Funding; Johnson and Johnson: Consultancy, Research Funding; Acerta/AstraZeneca: Consultancy, Research Funding; Sunesis: Consultancy, Research Funding; AstraZeneca: Consultancy; BeiGene: Consultancy, Research Funding; Genentech: Consultancy, Research Funding; AbbVie: Consultancy, Research Funding; LOXO: Consultancy, Research Funding; MSKCC: Current Employment; Pharmacyclics LLC, an AbbVie Company: Consultancy, Research Funding; TG Therapeutics: Consultancy, Other: DSMB, Research Funding; Nurix: Research Funding; Janssen: Consultancy, Research Funding; Genmab: Research Funding. Erba: AbbVie Inc; Agios Pharmaceuticals Inc; Astellas; Bristol Myers Squibb; Celgene, a Bristol Myers Squibb company; Daiichi Sankyo Inc; Genentech, a member of the Roche Group; GlycoMimetics Inc; Incyte Corporation; Jazz Pharmaceuticals Inc; Kura Oncology; Nov: Other: Advisory Committee; AbbVie Inc: Other: Independent review committee; AbbVie Inc; Agios Pharmaceuticals Inc; ALX Oncology; Amgen Inc; Daiichi Sankyo Inc; FORMA Therapeutics; Forty Seven Inc; Gilead Sciences Inc; GlycoMimetics Inc; ImmunoGen Inc; Jazz Pharmaceuticals Inc; MacroGenics Inc; Novartis; PTC Therapeutics: Research Funding; AbbVie Inc; Agios Pharmaceuticals Inc; Bristol Myers Squibb; Celgene, a Bristol Myers Squibb company; Incyte Corporation; Jazz Pharmaceuticals Inc; Novartis: Speakers Bureau. Stone: Onconova: Consultancy; AbbVie: Consultancy; Boston Pharmaceuticals: Consultancy; Bristol Myers Squibb: Consultancy; Gemoab: Membership on an entity's Board of Directors or advisory committees; Elevate Bio: Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Research Funding; Jazz: Consultancy; Syros: Membership on an entity's Board of Directors or advisory committees; Syndax: Membership on an entity's Board of Directors or advisory committees; Agios: Consultancy, Research Funding; Takeda: Consultancy; BerGen Bio: Membership on an entity's Board of Directors or advisory committees; Astellas: Membership on an entity's Board of Directors or advisory committees; Foghorn Therapeutics: Consultancy; Innate: Consultancy; Janssen: Consultancy; GlaxoSmithKline: Consultancy; Amgen: Membership on an entity's Board of Directors or advisory committees; Arog: Consultancy, Research Funding; Actinium: Membership on an entity's Board of Directors or advisory committees; Syntrix/ACI: Membership on an entity's Board of Directors or advisory committees; Aprea: Consultancy; Celgene: Consultancy; Macrogenics: Consultancy. Litzow: Actinium: Research Funding; Amgen: Research Funding; AbbVie: Research Funding; Pluristem: Research Funding; Jazz: Other: Advisory Board; Omeros: Other: Advisory Board; Astellas: Research Funding; Biosight: Other: Data monitoring committee. Tallman: NYU Grand Rounds: Honoraria; Kura: Membership on an entity's Board of Directors or advisory committees; Syros: Membership on an entity's Board of Directors or advisory committees; Innate Pharma: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees; Biosight: Membership on an entity's Board of Directors or advisory committees; Roche: Membership on an entity's Board of Directors or advisory committees; Jazz Pharma: Membership on an entity's Board of Directors or advisory committees; Oncolyze: Membership on an entity's Board of Directors or advisory committees; KAHR: Membership on an entity's Board of Directors or advisory committees; Orsenix: Membership on an entity's Board of Directors or advisory committees; Daiichi-Sankyo: Membership on an entity's Board of Directors or advisory committees; Abbvie: Membership on an entity's Board of Directors or advisory committees; Amgen: Research Funding; Rafael Pharmaceuticals: Research Funding; Glycomimetics: Research Funding; Biosight: Research Funding; Orsenix: Research Funding; Abbvie: Research Funding; Mayo Clinic: Honoraria; UC DAVIS: Honoraria; Northwell Grand Rounds: Honoraria; NYU Grand Rounds: Honoraria; Danbury Hospital Tumor Board: Honoraria; Acute Leukemia Forum: Honoraria; Miami Leukemia Symposium: Honoraria; New Orleans Cancer Symposium: Honoraria; ASH: Honoraria; NCCN: Honoraria. Shanafelt: Genentech, Pharmacyclics: Research Funding. Wagner: Eli Lilly, Johnson & Johnson: Other: Spouse, previously held individual stocks;; Celgene-BMS: Consultancy, Membership on an entity's Board of Directors or advisory committees; Athenex Inc: Consultancy.
Outcomes of Patients with Chronic Lymphocytic Leukemia (CLL) Treated with the Combination of Ibrutinib (I) and Venetoclax (V; I+V) after Progression on I Alone (V-naïve) or after Progression on Sequential I and V (Double-Refractory)
Hampel, Paul J. , Call, Timothy G. , Leis, José F., Chanan‐Khan, Asher , Koehler, Amber B. , Schwager, Susan M., Sher, Taimur , Hanson, Curtis A. , Dyke, Daniel L. Van , Rabe, Kari G. , Ding, Wei , Kenderian, Saad S. , Muchtar, Eli , Wang, Yucai , Ailawadhi, Sikander , Shi, Min , Braggio, Esteban , Slager, Susan L. , Kay, Neil E. , Parikh, Sameer A.

Blood | November 23, 2021 | Volume: 138 | Issue: Supplement 1 | Pages: 1560-1560

10.1182/blood-2021-151668 Get It

Abstract INTRODUCTION Sparse data exist regarding I+V in an off-trial setting, particularly in patients (pts) with progression of disease on either I or V as single agent treatment. The 1-year overall survival (OS) rates with V monotherapy following I range from 75%-91% (Eyre et al, BJH 2019; Jones et al, Lancet Oncol 2018); however, longer-term follow-up of these or other patient cohorts treated with V after I has not yet been reported. Effective options in double-refractory pts are lacking when a clinical trial is not feasible. Here, we report our experience with I+V in these patient groups. METHODS After IRB approval, we reviewed the records of pts seen at Mayo Clinic (between 4/2012-1/2021) who received I+V therapy off-trial for CLL progression. Pts treated with I+V for Richter's transformation were excluded. Time to next treatment (TTNT) was measured from I+V treatment start date to the date of next treatment start or last known treatment status with death as a competing risk. OS was measured from I+V start date until date of death or when the patient was last known alive; OS was analyzed using the Kaplan-Meier method and Cox proportional hazards model. RESULTS Thirty-three pts with progressive CLL were treated with I+V (median duration 13.3 months [95% CI: 7.1 months-not estimable (NE)]). The median age was 70 years (range 47-86), 6 (18%) were women, and 20 (65%) had del(17p) or TP53 mutation. The median number of prior lines of therapy was 3 (range 1-15). Additional characteristics at the time of I+V start are shown in Table 1. Median follow-up from start of I+V was 23.8 months. Among 22 pts with prior progression on I only (V-naïve), the median duration of I+V was 14.8 months (95% CI 7.6 months-NE). The median duration on either I or V from the start of combination was 20.3 months (95% CI 8.3 months-NE). The median TTNT was 25.1 months (Figure 1A). Four pts proceeded to cellular therapy (alloSCT [n=3], CAR-T [n=1]) while on I+V. Next therapy (n=9) consisted of Richter transformation treatment (n=2), chemotherapy plus continued I+V (n=1), anti-CD20 plus continued I+V (n=1), duvelisib + I (n=1), TP-0903 + I (n=1), reintroduction of I at disease progression after previously stopping I during I+V therapy (n=1), and reintroduction of I (n=1) or V (n=1) at disease progression after previously stopping I+V. Of 9 pts who did not receive subsequent therapy, 4 pts remain on I+V (median duration 16.4 months), 4 pts continued V after discontinuing I (median duration on V from start of I+V was 21.5 months), and 1 pt discontinued I+V following a second cancer diagnosis and died without receiving additional CLL-directed treatment. Eleven pts received I+V in the double-refractory setting; 9 pts had prior disease progression on sequential I then V and 2 pts had prior disease progression on sequential V then I. The median duration of I+V was 7.5 months (95% CI 4.3 months-NE), and the median duration of either agent from I+V start was 10.8 months (95% CI 7.1 months-NE). The median TTNT was 14.0 months (Figure 1A). Eight pts required additional treatment, consisting of PI3K inhibitor (n=2), anti-CD20 added to I+V (n=1), CAR-T (n=1), anti-CD20 with (n=1) or without (n=1) bendamustine added to continued I, and Richter transformation treatment (n=2). One pt continues I+V (17.4 months ongoing) without further treatment. Two pts died from disease progression without receiving additional treatment. The median OS of all 33 pts was 27.4 months (95% CI 25.9 months-NE; Figure 1B). The median OS of the 22 pts with prior progression on I (V-naïve) was 47.1 months (95% CI 27.7 months-NE), and the median OS of the 11 pts with prior progression on I and V separately was 27.0 months (95% CI 15.5 months-NE). In univariate analyses, prior progression on V was a predictor of shorter OS (HR=3.9; 95% CI 1.4-11.2; p=0.01). CONCLUSIONS Combination I+V therapy in heavily pre-treated CLL pts who have disease progression after I provides durable benefit with a median OS approaching 4 years. In the double-refractory setting, repurposing both drugs as combination I+V therapy can be a useful strategy, despite the short-term disease control, for pts where clinical trial options are limited or not available. Further examination of these approaches in larger cohorts and understanding the operative resistance mechanisms in pts with double-refractory disease are key next studies. Figure 1 Figure 1. Disclosures Ding: Octapharma: Membership on an entity's Board of Directors or advisory committees; DTRM: Research Funding; Merck: Membership on an entity's Board of Directors or advisory committees, Research Funding. Chanan-Khan: BeiGene, Jansen, Ascentage: Honoraria; Ascentage, Starton, Cellectar, NonoDev, Alpha2 Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; Alpha2 Pharmaceuticals: Patents & Royalties: Tabi; Ascentage: Research Funding; Cellectar: Current equity holder in publicly-traded company; Alpha2 Pharmaceuticals, NonoDev, Starton: Current holder of stock options in a privately-held company; BieGene, Jansen, Ascentage: Consultancy. Kenderian: Humanigen, Inc.: Consultancy, Honoraria, Research Funding. Wang: TG Therapeutics: Membership on an entity's Board of Directors or advisory committees; MorphoSys: Research Funding; Novartis: Research Funding; LOXO Oncology: Membership on an entity's Board of Directors or advisory committees, Research Funding; Genentech: Research Funding; Incyte: Membership on an entity's Board of Directors or advisory committees, Research Funding; InnoCare: Research Funding; Eli Lilly: Membership on an entity's Board of Directors or advisory committees. Ailawadhi: Pharmacyclics: Consultancy, Research Funding; Xencor: Research Funding; Janssen: Consultancy, Research Funding; Cellectar: Research Funding; Sanofi: Consultancy; BMS: Consultancy, Research Funding; GSK: Consultancy, Research Funding; Ascentage: Research Funding; Medimmune: Research Funding; Karyopharm: Consultancy; Amgen: Consultancy, Research Funding; Beigene: Consultancy; AbbVie: Consultancy; Takeda: Consultancy; Genentech: Consultancy. Koehler: AbbVie: Membership on an entity's Board of Directors or advisory committees; TG Therapeutics: Membership on an entity's Board of Directors or advisory committees. Kay: AstraZeneca: Membership on an entity's Board of Directors or advisory committees; Dava Oncology: Membership on an entity's Board of Directors or advisory committees; Targeted Oncology: Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Juno Therapeutics: Membership on an entity's Board of Directors or advisory committees; Genentech: Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol Meyer Squib: Membership on an entity's Board of Directors or advisory committees, Research Funding; TG Therapeutics: Research Funding; Agios Pharm: Membership on an entity's Board of Directors or advisory committees; Sunesis: Research Funding; Rigel: Membership on an entity's Board of Directors or advisory committees; Acerta Pharma: Research Funding; CytomX Therapeutics: Membership on an entity's Board of Directors or advisory committees; Abbvie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Morpho-sys: Membership on an entity's Board of Directors or advisory committees; Oncotracker: Membership on an entity's Board of Directors or advisory committees; MEI Pharma: Research Funding; Behring: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Tolero Pharmaceuticals: Research Funding. Parikh: Pharmacyclics, MorphoSys, Janssen, AstraZeneca, TG Therapeutics, Bristol Myers Squibb, Merck, AbbVie, and Ascentage Pharma: Research Funding; Pharmacyclics, AstraZeneca, Genentech, Gilead, GlaxoSmithKline, Verastem Oncology, and AbbVie: Membership on an entity's Board of Directors or advisory committees. OffLabel Disclosure: Combination ibrutinib and venetoclax in patients with relapsed CLL.
Effect of COVID-19 Pandemic Control Measures on Diagnoses of Hematologic Cancer Among CMS Population in 2020
Smart, Dave, Moore, Wendy C. , Hjort, Karina, Keating, Karen , Holt, Bob, Henderson, Raymond , Riccelli, Peter V., Magliocco, Anthony M., Hanson, Curtis A. , Moore, Wendy, Bloom, Kenneth

Blood | November 23, 2021 | Volume: 138 | Issue: Supplement 1 | Pages: 5017-5017

10.1182/blood-2021-153005 Get It

Abstract 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. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.
Sensitivity analysis in classification using Bayesian smoothing spline ANOVA probit regression
Zhang, Chunzhe, Storlie, Curtis B. , Lee, Thomas C. M.

Canadian Journal of Statistics | November 20, 2021 | Volume: 50 | Issue: 3 | Pages: 928-950

10.1002/cjs.11669 Get It

For many classification problems, in addition to providing accurate classification results, very often it is equally important to determine which predictors are contributing to the results, and by how much. This motivates this article, where a new sensitivity analysis framework is developed for classification problems to address this issue. The effectiveness of this framework is illustrated through simulation studies and application to real data. Notice that this framework can be coupled with different classification methods. However, in practice it is recommended to pair it with a classification method called Bayesian smoothing spline ANOVA probit regression (BSSANOVA). When compared with other existing methods through numerical experiments, BSSANOVA performs extremely well for both classification and sensitivity analysis.
Lay understandings of drug‐gene interactions: The right medication, the right dose, at the right time, but what are the right words?
Meagher, Karen M. , Finn, Kelsey Stuttgen , Curtis, Susan , Borucki, Jack, Beck, Annika T., Cheema, Amal , Sharp, Richard R. , Stuttgen Finn, Kelsey, Curtis, Susan H , Cheema, Amal W, Sharp, Richard R , Meagher, Karen M , Stuttgen, Kelsey

Clinical and Translational Science | November 10, 2021 | Volume: 15 | Issue: 3 | Pages: 721-731

10.1111/cts.13193 | PMID 34755460 Get It

AbstractAs pharmacogenomic (PGx) testing increases in popularity, lay concepts of drug‐gene interactions set the stage for shared decision making in precision medicine. Few studies explore what recipients of PGx results think is happening in their bodies when a drug‐gene interaction is discovered. To characterize biobank participants’ understanding of PGx research results, we conducted a focus group study, which took place after PGx variants conferring increased risk of dihydropyrimidine dehydrogenase (DPD) deficiency were disclosed to biobank contributors. DPD deficiency confers an increased risk of adverse reaction to commonly used cancer chemotherapeutics. Ten focus groups were conducted, ranging from two to eight participants. Fifty‐four individuals participated in focus groups. A framework approach was used for descriptive and explanatory analysis. Descriptive themes included participants’ efforts to make sense of PGx findings as they related to: (1) health implications, (2) drugs, and (3) genetics. Explanatory analysis supplied a functional framework of how participant word choices can perform different purposes in PGx communication. Results bear three main implications for PGx research‐related disclosure. First, participants’ use of various terms suggest participants generally understanding their PGx results, including how positive PGx results differ from positive disease susceptibility genetic results. Second, PGx disclosure in biobanking can involve participant conflation of drug‐gene interactions with allergies or other types of medical reactions. Third, the functional framework suggests a need to move beyond a deficit model of genetic literacy in PGx communication. Together, findings provide an initial evidence base for supporting bidirectional expert‐recipient PGx results communication.
Comparison of pulse‐dose and high‐dose corticosteroids with no corticosteroid treatment for COVID‐19 pneumonia in the intensive care unit
Yaqoob, Hamid , Greenberg, Daniel J. , Lee, Curtis , Vernik, David, Manglani, Ravi , Murad, Mohammed , Chandy, Dipak , Epelbaum, Oleg , Hwang, Frank, Wang, Zhen

Journal of Medical Virology | September 20, 2021 | Volume: 94 | Issue: 1 | Pages: 349-356

10.1002/jmv.27351 | PMID 34542192 Get It

AbstractCorticosteroid dosing in the range of 0.5–2 mg/kg/day of methylprednisolone equivalents has become a standard part of the management of intensive care unit (ICU) patients with COVID‐19 pneumonia based on positive results of randomized trials and a meta‐analysis. Alongside such conventional dosing, administration of 1 gm of methylprednisolone daily (pulse dosing) has also been reported in the literature with claims of favorable outcomes. Comparisons between such disparate approaches to corticosteroids for Coronavirus disease 2019 (COVID‐19) pneumonia are lacking. In this retrospective study of patients admitted to the ICU with COVID‐19 pneumonia, we compared patients treated with 0.5–2 mg/kg/day in methylprednisolone equivalents (high‐dose corticosteroids) and patients treated with 1 gm of methylprednisolone (pulse‐dose corticosteroids) to those who did not receive any corticosteroids. The endpoints of interest were hospital mortality, ICU‐free days at Day 28, and complications potentially attributable to corticosteroids. Pulse‐dose corticosteroid therapy was associated with a significant increase in ICU‐free days at Day 28 compared to no receipt: adjusted relative risk (aRR): 1.45 (95% confidence interval [CI]: 1.05–2.02; p = 0.03) and compared with high‐dose corticosteroid administration (p = 0.003). Nonetheless, receipt of high‐dose corticosteroids—but not of pulse‐dose corticosteroids—significantly reduced the odds of hospital mortality compared to no receipt: adjusted Odds ratio (aOR) 0.31 (95% CI: 0.12–0.77; p = 0.01). High‐dose corticosteroids reduced mortality compared to pulse‐dose corticosteroids (p = 0.04). Pulse‐dose corticosteroids—but not high‐dose corticosteroids—significantly increased the odds of acute kidney injury requiring renal replacement therapy compared to no receipt: aOR 3.53 (95% CI: 1.27–9.82; p = 0.02). The odds of this complication were also significantly higher in the pulse‐dose group when compared to the high‐dose group (p = 0.05 for the comparison). In this single‐center study, pulse‐dose corticosteroid therapy for COVID‐19 pneumonia in the ICU was associated with an increase in ICU‐free days but failed to impact hospital mortality, perhaps because of its association with development of severe renal failure. In line with existing trial data, the effect of high‐dose corticosteroids on mortality was favorable.