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Purpose: Patients with Waldenström macroglobulinemia (WM) have disparate outcomes. Newer therapies have emerged since the development of International Prognostic Scoring System, and MYD88 L265P mutation is now frequently assessed at diagnosis, warranting reexamination of the prognostic parameters., Patients and Methods: We reviewed records of 889 treatment-naïve patients with active WM, consecutively seen between January 01, 1996, and December 31, 2017, to identify clinical predictors of overall survival (OS) in univariate analyses. Patients with complete data for the parameters significant on the univariate analyses (n = 341) were included in a multivariable analysis to derive a prognostic model, subsequently validated in a multi-institutional cohort., Results: In the derivation cohort (n = 341), age (hazard ratio [HR], 1.9 [95% CI, 1.2 to 2.1]; P = .0009), serum lactate dehydrogenase (LDH) above upper limit of normal (HR, 2.3 [95% CI, 1.3 to 4.5]; P = .007), and serum albumin <3.5 g/dL (HR, 1.5 [95% CI, 0.99 to 2.3]; P = .056) were independently prognostic. By assigning a score of 1 point each to albumin <3.5 g/dL (HR, 1.5) and age 66-75 years (HR 1.4) and 2 points for age >75 years (HR, 2.6) or elevated LDH (HR, 2.3), four groups with distinct outcomes were observed on the basis of the composite scores. Five-year OS was 93% for the low-risk (score 0), 82% for low-intermediate risk (score 1), 69% for intermediate-risk (score 2), and 55% for the high-risk (score ≥3; P < .0001) groups. In the validation cohort (N = 335), the model maintained its prognostic value, with a 5-year OS of 93%, 90%, 75%, and 57% for the four groups, respectively ( P < .0001)., Conclusion: Modified Staging System for WM (MSS-WM), utilizing age, albumin, and LDH is a simple, clinically useful, and externally validated prognostic model that reliably risk-stratifies patients with symptomatic WM into four groups with distinct prognosis.

Several landmark therapeutic advances in multiple myeloma (MM) have led to an unprecedented number of options available to patients and their physicians as shared decision making is attempted. A myriad of factors need to be considered to ensure that patient-, disease-, and treatment-related factors are addressed to arrive at the most appropriate choice for patients at that time in their journey with myeloma. Some of these factors have traditionally remained underaddressed but have a clear association with patient outcomes, leading to underrepresented groups of patients with MM, including the elderly patients, racial-ethnic minorities, and those with specific advanced comorbidities, for example, renal insufficiency. Some of these factors may not be modifiable, but data suggest that they may give rise to implicit or explicit bias and affect treatment decisions. A growing body of literature is bringing these factors to light. However, their incorporation in day-to-day decision making for patients needs to be universal. It is imperative that prospective data are generated for all these and other underrepresented groups such that evidence-based medicine is applicable universally to all patients with MM, irrespective of clinical and sociodemographic factors.

Purpose: Financial hardship (FH) in cancer care is a growing challenge for patients, their caregivers, and health care providers with impact on morbidity and mortality. In this study, we report on a standardized approach to describe the prevalence and predictors for FH as part of routine clinical workflow. We also report on the association of FH with survival in our cancer patient population., Methods: This study includes patients who completed a FH screen at least once between 2018 and 2020. Demographics, disease state, and mortality data were extracted from the medical records. Multivariable logistic regression models were used to examine association of sociodemographic and disease variables with FH. By using propensity score weighting to account for differences in demographic and clinical factors between patients with and without FH, we then fit Cox proportional hazards models to examine the relationship between FH and survival., Results: The study cohort included 31,154 patients. FH was reported by 14% (n = 4,250) of the patients. A significantly higher likelihood of having FH ( P < .001 for all) was reported by racial/ethnic minority patients; those who were unemployed/disabled, single, or divorced; patients from disadvantaged neighborhoods; and those who were self-pay or had government insurance. Older age, being retired, and living farther from the cancer center were associated with significantly less likelihood of endorsing FH. Patients who endorsed FH had a lower survival (hazard ratio for mortality 1.46)., Conclusion: Our study identified key groups more likely to report FH in a relatively affluent population at a large cancer center and showed an adverse association between FH and survival. Further research is needed to develop clinical care pathways for patients at high risk for worse financial and clinical outcomes.

Purpose: The benefit of routine pre-emptive screening for severe acute respiratory syndrome coronavirus 2 infections in patients with cancer before cancer-directed therapies is unclear. Herein, we characterize the outcomes of a cohort of patients with cancer who were diagnosed with COVID-19 by routine screening (RS) in comparison with those diagnosed on the basis of clinical suspicion or exposure history (nonroutine screening [NRS])., Methods: A multisite prospective observational study was conducted at three major and five satellite campuses of the Mayo Clinic Cancer Center between March 18 and July 31, 2020. The primary outcome was COVID-19-related hospital admission. Secondary outcomes included intensive care unit admissions and all-cause mortality., Results: Five thousand four hundred fifty-two patients underwent RS in the outpatient setting only, and 44 (0.81%) were diagnosed with COVID-19. RS detected 19 additional patients from the scheduled inpatient admissions for surgical or interventional procedures or inpatient chemotherapy. One hundred sixty-one patients were diagnosed with COVID-19 on the basis of NRS. COVID-19-related hospitalization rate (17.5% v 26.7%; P = .14), intensive care unit admission (1.6% v 5.6%; P = .19), and mortality (4.8% v 3.7%; P = .72) were not significantly different between the RS and NRS groups. In the multivariable analysis, age ≥ 60 years (odds ratio, 4.4; P = .023) and an absolute lymphocyte count ≤ 1.4 × 10 9 /L (odds ratio, 9.2; P = .002) were independent predictors of COVID-19-related hospital admission., Conclusion: The COVID-19 positivity rate was low on the basis of RS. Comparing the hospital admission and mortality outcomes with the NRS cohort, there were no significant differences. The value of routine pre-emptive screening of asymptomatic patients with cancer for COVID-19 remains low., Competing Interests: Joshua PritchettPatents, Royalties, Other Intellectual Property: Novel discovery with intellectual property interests in ongoing development with Mayo Clinic Ventures, patent pending, US Patent Application No. 63/109625Uncompensated Relationships: Biofourmis Andrew BadleyEmployment: Mayo ClinicLeadership: Splissen, NferenceStock and Other Ownership Interests: ZentalisConsulting or Advisory Role: AbbVie, Flambeau Diagnostics, Corvus Pharmaceuticals, Pinetree, EquiliumSpeakers' Bureau: Medscape, ReachMDPatents, Royalties, Other Intellectual Property: Patents on Casp8p41, and TRAILshort Rami ManochakianConsulting or Advisory Role: Takeda, Guardant Health, AstraZeneca, Novocure Sikander AilawadhiHonoraria: AstraZeneca, Bristol Myers Squibb, Amgen, JanssenConsulting or Advisory Role: Takeda, Celgene, Beigene, Oncopeptides, GlaxoSmithKline, SanofiResearch Funding: Pharmacyclics, Janssen Biotech, Cellectar, Phosplatin Therapeutics, Bristol Myers Squibb, Amgen, MedImmune, Xencor Alan H. BryceHonoraria: Astellas Pharma, BayerTravel, Accommodations, Expenses: Clovis Oncology, Phosplatin Therapeutics Joleen M. HubbardConsulting or Advisory Role: Bayer, Taiho OncologyResearch Funding: Boston Biomedical, Senhwa Biosciences, Bayer, Merck, Taiho Pharmaceutical, Treos Bio, eFFECTOR Therapeutics, Hutchison MediPharma, Seattle Genetics, Trovagene, Translational Research in Oncology, Incyte Thomas E. WitzigHonoraria: Curio ScienceConsulting or Advisory Role: Karyopharm Therapeutics, Celgene, Epizyme, Cellectar, Tessa Therapeutics, Portola Pharmaceuticals, ADC TherapeuticsResearch Funding: Celgene, Acerta Pharma, Kura Oncology, Acrotech Biopharma, Karyopharm TherapeuticsPatents, Royalties, Other Intellectual Property: I am coinventor on a patent application filed by Mayo Clinic and pending on the combination of CRM1 inhibitors with salicylates. Please note—simply filed—not even close to being granted Robert R. McWilliamsStock and Other Ownership Interests: ZentalisConsulting or Advisory Role: Merrimack, Newlink Genetics, ZentalisResearch Funding: Newlink Genetics, Merck, Bristol Myers Squibb, GlaxoSmithKline/Tesaro Konstantinos LeventakosConsulting or Advisory Role: AstraZeneca, Boehringer Ingelheim, Targeted Oncology, OncLive, TakedaResearch Funding: AstraZeneca, Mirati Therapeutics Thorvardur R. HalfdanarsonConsulting or Advisory Role: Lexicon, Ipsen, Advanced Accelerator Applications, Curium Pharma, ScioScientific, TerumoResearch Funding: Ipsen, Agios, Thermo Fisher Scientific, Basilea, Turnstone Bio, Advanced Accelerator Applications, NovartisNo other potential conflicts of interest were reported.

Purpose: Multiple myeloma (MM) treatment has changed tremendously, with significant improvement in patient out-comes. One group with a suboptimal benefit is patients with high-risk cytogenetics, as tested by conventional karyotyping or fluorescence in situ hybridization (FISH). Methodology for these tests has been published, but not necessarily standardized., Methods: We address variability in the testing and reporting methodology for MM cytogenetics in the United States using the ongoing African American Multiple Myeloma Study (AAMMS). We evaluated clinical and cytogenetic data from 1,221 patients (1,161 with conventional karyotyping and 976 with FISH) tested between 1998 and 2016 across 58 laboratories nationwide., Results: Interlab and intralab variability was noted for the number of cells analyzed for karyotyping, with a significantly higher number of cells analyzed in patients in whom cytogenetics were normal (P 5.0025). For FISH testing, CD138-positive cell enrichment was used in 29.7% of patients and no enrichment in 50% of patients, whereas the remainder had unknown status. A significantly smaller number of cells was analyzed for patients in which CD138 cell enrichment was used compared with those without such enrichment (median, 50 v 200; P, .0001). A median of 7 loci probes (range, 1-16) were used for FISH testing across all laboratories, with variability in the loci probed even within a given laboratory. Chromosome 13-related abnormalities were the most frequently tested abnormality (n5956; 97.9%), and t(14;16) was the least frequently tested abnormality (n 5 119; 12.2%)., Conclusions: We report significant variability in cytogenetic testing across the United States for MM, potentially leading to variability in risk stratification, with possible clinical implications and personalized treatment approaches.

Multiple myeloma (MM) treatment has advanced significantly over the last 2 decades. In most patients, the disease course has been altered from early fatality to chronic morbidity with multiple lines of treatment. The MM treatment paradigm has shifted toward treating patients before end-organ damage occurs. Thus, timeliness of treatment initiation in this era might improve patient outcomes. This is the first report to our knowledge analyzing disparities and trends in treatment timeliness of patients with MM using the National Cancer Database. Multiple factors affected the timing of treatment initiation in MM and disparities were found. We noted that initiation of treatment was delayed in women (odds ratio [OR], 1.15; 95% CI, 1.1 to 1.2) and blacks (OR, 1.21; 95% CI, 1.14 to 1.28; reference, whites) and in patients diagnosed in more recent years (2012-2015; OR, 1.15; 95% CI, 1.1 to 1.22; reference, 2004-2007). Patients were likely to start treatment earlier if they were age ≥ 80 years (OR, 0.83; 95% CI, 0.76 to 0.9; reference, age < 60 years), were uninsured (OR, 0.81; 95% CI, 0.72 to 0.91; reference, private insurance), had Medicaid (OR, 0.87; 95% CI, 0.79 to 0.95; reference, private insurance), were treated in a comprehensive community cancer program (OR, 0.7; 95% CI, 0.65 to 0.77; reference, community cancer program), lived in a location other than the US Northeast, or had a higher Charlson comorbidity score. Patient education and income levels did not affect time to treatment initiation. Particular aspects of these disparities could be explained by our current health care system and insurance rules, whereas others need to be investigated more deeply.

Despite the evolution of the therapeutic arsenal for the treatment of multiple myeloma (MM) over the past decade, autologous stem-cell transplantation (ASCT) remains an integral part of the treatment of patients with both newly diagnosed and relapsed MM. The advent of novel therapies, such as immunomodulatory agents, proteasome inhibitors, and monoclonal antibodies, has led to unprecedented levels of deep hematologic responses. Nonetheless, studies show that ASCT has an additive effect leading to additional deepening of responses. As the therapeutic agents for MM continue to evolve, the timing, duration, and sequence of their use in combination with ASCT will be crucial to understand to obtain the deepest response and survival benefit for patients with MM. This review aims to discuss the role of ASCT for the management of MM, with a particular focus on the role of ASCT in the context of novel therapies and minimal residual disease.

Treatment of multiple myeloma (MM) has notably evolved with improved patient outcomes over the past few years. Several new drugs have become available, and large national and international clinical trials have set the stage for evidence-based medicine guidelines for the treatment of patients with MM. Although patient outcomes have undoubtedly improved, data increasingly show that several disparities exist at varying levels of health care and that these disparities make the care of patients heterogenous and potentially result in inferior outcomes. These disparities have been described with regard to patient age, race/ethnicity, rural-urban residence, socioeconomic status, and insurance type, among other factors. Looking at the global picture of MM care, there is substantial variation among different countries, primarily depending on the disparate availability of anti-MM drugs and access to quality health care across the world, limiting the delivery of innovative therapeutic approaches at the individual patient level. The causes of these national and international disparities could be multifactorial, intricate, and difficult to isolate. Yet the ongoing research in this field is encouraging, and there seems to be growing momentum to understand such disparities and their causes. It is hoped that this research will lead to solutions that can be implemented in the near future. This review focuses on certain aspects of disparities in MM care, highlighting disparities among different racial/ethnic subgroups, rural-urban differences in America, and global disparities at an international level.

Introduction: Optimal scheduling and calendar management in an outpatient chemotherapy unit is a complex process that is driven by a need to focus on safety while accommodating a high degree of variability. Primary constraints are infusion times, staffing resources, chair availability, and unit hours., Methods: We undertook a process to analyze our existing management models across multiple practice settings in our health care system, then developed a model to optimize safety and efficiency. The model was tested in one of the community chemotherapy units. We assessed staffing violations as measured by nurse-to-patient ratios throughout the workday and at key points during treatment. Staffing violations were tracked before and after the implementation of the new model., Results: The new model reduced staffing violations by nearly 50% and required fewer chairs to treat the same number of patients for the selected clinic day. Actual implementation results indicated that the new model leveled the distribution of patients across the workday with an 18% reduction in maximum chair utilization and a 27% reduction in staffing violations. Subsequently, a positive impact on peak pharmacy workload reduced delays by as much as 35 minutes. Nursing staff satisfaction with the new model was positive., Conclusion: We conclude that the proposed optimization approach with regard to nursing resource assignment and workload balance throughout a day effectively improves patient service quality and staff satisfaction.

Purpose: Genomic testing has increased the quantity of information available to oncologists. Unfortunately, many identified sequence alterations are variants of unknown significance (VUSs), which thus limit the clinician's ability to use these findings to inform treatment. We applied a combination of in silico prediction and molecular modeling tools and laboratory techniques to rapidly define actionable VUSs., Materials and Methods: Exome sequencing was conducted on 308 tumors from various origins. Most single nucleotide alterations within gene coding regions were VUSs. These VUSs were filtered to identify a subset of therapeutically targetable genes that were predicted with in silico tools to be altered in function by their variant sequence. A subset of receptor tyrosine kinase VUSs was characterized by laboratory comparison of each VUS versus its wild-type counterpart in terms of expression and signaling activity., Results: The study identified 4,327 point mutations of which 3,833 were VUSs. Filtering for mutations in genes that were therapeutically targetable and predicted to affect protein function reduced these to 522VUSs of interest, including a large number of kinases. Ten receptortyrosine kinase VUSs were selected to explore in the laboratory. Of these, seven were found to be functionally altered. Three VUSs (FGFR2 F276C, FGFR4 R78H, and KDR G539R) showed increased basal or ligand-stimulated ERK phosphorylation compared with their wild-type counterparts, which suggests that they support transformation. Treatment of a patient who carried FGFR2 F276C with an FGFR inhibitor resulted in significant and sustained tumor response with clinical benefit., Conclusion: The findings demonstrate the feasibility of rapid identification of the biologic relevance of somatic mutations, which thus advances clinicians' ability to make informed treatment decisions., Competing Interests: AUTHORS’ DISCLOSURES OF POTENTIAL CONFLICTS OF INTEREST The following represents disclosure information provided by authors of this manuscript. All relationships are considered compensated. Relationships are self-held unless noted. I = Immediate Family Member, Inst = My Institution. Relation-ships may not relate to the subject matter of this manuscript. For more information about ASCO’s conflict of interest policy, please refer to www.asco.org/rwc or po.ascopubs.org/site/ifc. Jan B. Egan No relationship to disclose David L. Marks Stock and Other Ownership Interests: WebMD, Cardinal Health (I), Prothena (I), Perrigo (I) Tara L. Hogenson No relationship to disclose Anne M. Vrabel No relationship to disclose Ashley N. Sigafoos No relationship to disclose Ezequiel J. Tolosa No relationship to disclose Ryan M. Carr No relationship to disclose Stephanie L. Safgren No relationship to disclose Elisa Enriquez Hesles No relationship to disclose Luciana L. Almada No relationship to disclose Paola A. Romecin-Duran No relationship to disclose Eriko Iguchi No relationship to disclose Aryan Ala’Aldeen No relationship to disclose Jean-Pierre A. Kocher No relationship to disclose Gavin R. Oliver No relationship to disclose Naresh Prodduturi No relationship to disclose David W. Mead No relationship to disclose Asif Hossain No relationship to disclose Norine E. Huneke No relationship to disclose Colleen M. Tagtow No relationship to disclose Sikander Ailawadhi Consulting or Advisory Role: Amgen, Takeda Pharmaceuticals, Novartis Research Funding: Pharmacyclics (Inst) Travel, Accommodations, Expenses: Amgen, Takeda Pharmaceuticals, Novartis Stephen M. Ansell Honoraria: WebMD, Research To Practice Research Funding: Bristol-Myers Squibb (Inst), Celldex Therapeutics (Inst), Seattle Genetics (Inst), Merck (Inst), Affimed (Inst), Trillium Therapeutics (Inst) Michaela S. Banck No relationship to disclose Alan H. BryceNo relationship to disclose Estrella M. Carballido No relationship to disclose Asher A. Chanan-Khan No relationship to disclose Kelly K. Curtis Employment: INC Research Stock and Other Ownership Interests: INC Research Travel, Accommodations, Expenses: INC Research Ernesto ResnikNo relationship to disclose Chelsea D. Gawryletz No relationship to disclose Ronald S. Go Speakers’ Bureau: OnLive, Takeda Pharmaceuticals Thorvardur R. Halfdanarson Consulting or Advisory Role: Lexicon (Inst), Ipsen (Inst), Merrimack (Inst) Research Funding: Esanex (Inst), Ipsen (Inst), Boston Biomedical (Inst) Thai H. Ho No relationship to disclose Richard W. Joseph Consulting or Advisory Role: Bristol-Myers Squibb, Nektar, Genoptix, Eisai, Bristol-Myers Squibb Research Funding: Merck, Bristol-Meyers Squibb, Roche (Inst), Genentech (Inst), X4P Pharmaceuticals (Inst), Amgen (Inst) Prashant Kapoor Consulting or Advisory Role: Sanofi (Inst) Research Funding: Amgen (Inst), Takeda Pharmaceuticals (Inst) Aaron S. Mansfield Consulting or Advisory Role: TrovaGene (Inst), Genentech (Inst), Bristol-Myers Squibb (Inst) Travel, Accommodations, Expenses: Bristol-Myers Squibb Nathalie Meurice No relationship to disclose Amulya A. Nageswara Rao No relationship to disclose Grzegorz S. Nowakowski Consulting or Advisory Role: Celgene (Inst), MorphoSys (Inst), Genentech (Inst) Research Funding: Celgene (Inst) Animesh Pardanani No relationship to disclose Sameer A. Parikh Research Funding: Pharmacyclics (Inst) John C. Cheville No relationship to disclose Andrew L. Feldman Consulting or Advisory Role: Infinity Pharmaceuticals Patents, Royalties, Other Intellectual Property: Inventor of technology for which the Mayo Clinic holds an unlicensed patent or has submitted a patent application (Inst) Ramesh K. Ramanathan Honoraria: Taiho Pharmaceutical, Cerulean Pharma, Pharmacyclics, Insys Therapeutics, Novocure Consulting or Advisory Role: Cerulean Pharma, Novocure, INSYS Therapeutics, Pharmacyclics Research Funding: AbbVie (Inst), Celgene (Inst), Merck (Inst), Schering Plough (Inst), Merrimack (Inst), Boston Biomedical (Inst), BERG (Inst), Superlab Far East (Inst) Steven I. Robinson Travel, Accommodations, Expenses: Tricon Pharmaceuticals Raoul Tibes Research Funding: Novartis (Inst), Merck (Inst), Seattle Genetics (Inst), Boehringer Ingelheim (Inst), Astellas Pharma (Inst), Astex Pharmaceuticals (Inst)Heidi D. Finnes Jennifer B. McCormick No relationship to disclose Robert R. McWilliams Consulting or Advisory Role: Merrimack (Inst) Research Funding: PRISM BioLab (Inst), Genentech (Inst), Novartis (Inst), NewLink Genetics (Inst), Eli Lilly (Inst), Aduro Biotech (Inst), Pfizer (Inst), Sanofi (Inst) Travel, Accommodations, Expenses: AstraZeneca Aminah Jatoi Research Funding: Entera Health, Boston Biologics Mrinal M. Patnaik No relationship to disclose Alvin C. Silva No relationship to disclose Eric D. Wieben Patents, Royalties, Other Intellectual Property: Champions Oncology–licensed IP-targeted therapy with abiraterone acetate ($0 received), WuXi AppTec–licensed IP-breast cancer xenografts ($12,737 to Mayo Clinic; Inst), Affymetrix-licensed IP on several variants in drug processing enzymes ($0 in past 2 years), Life Technologies–licensed IP on several variants in drug processing enzymes ($0 in past 2 years) Tammy M. McAllister No relationship to disclose Kandelaria M. Rumilla No relationship to disclose Sarah E. Kerr Research Funding: Abbott Molecular Konstantinos N. Lazaridis No relationship to disclose Gianrico Farrugia No relationship to disclose A. Keith Stewart Consulting or Advisory Role: Celgene, Bristol-Myers Squibb, Janssen Pharmaceuticals, Roche, Amgen Karl J. Clark Patents, Royalties, Other Intellectual Property: Inventor on patents associated with the Sleeping Beauty transposon system Eileen J. Kennedy Patents, Royalties, Other Intellectual Property: Patent on unrelated work (US patent 9,458,189) for “ligation of stapled polypeptides” issued October 4, 2016 Eric W. Klee Patents, Royalties, Other Intellectual Property: Royalties on software development Mitesh J. Borad Stock and Other Ownership Interests: GlaxoSmithKline, Gilead Sciences Consulting or Advisory Role: G1 Therapeutics, TD2, Fujifilm (Inst), Agios (Inst), INSYS Therapeutics (Inst), Novartis (Inst), ArQule (Inst), Celegene (Inst), Inspyr Therapeutics, Halozyme Therapeutics (Inst) Research Funding: Boston Biomedical (Inst), miRNA Therapeutics (Inst), Senhwa Biosciences (Inst), Medimmune (Inst), Bioline (Inst), Agios (Inst), Halozyme Therapeutics (Inst), Celgene (Inst), Threshold Pharmaceuticals (Inst), Toray (Inst), Dicerna Pharmaceuticals (Inst), Sillajen (Inst), Eisai (Inst), Taiho Pharmaceuticals (Inst), EMD Serono (Inst), Isis Pharmaceuticals (Inst), Incyte (Inst), Sun BioPharma (Inst), ARIAD Pharmaceuticals (Inst), ImClone Systems (Inst) Travel, Accommodations, Expenses: ArQule, Celgene, AstraZeneca Martin E. Fernandez-Zapico No relationship to disclose