Trial of Electronic Medical Record Integrated Next-Generation Sequencing Ordering in Veterans Affairs Cancer Care.

PURPOSE: Previous studies document underuse of next-generation sequencing (NGS). We examined the impact to oncology care for veterans of incorporating NGS ordering into the Veterans Affairs (VA) electronic medical record (EMR) at two New York City VA Medical Centers. METHODS: We identified patients with non-small cell lung cancer and prostate cancer with oncology clinic visits and NGS testing indications between January and December 2021. Patients were divided into external ordering (EO) with visits before we implemented an EMR ordering system for NGS in July 2021, and internal ordering (IO) with visits after this date. The primary outcome was proportion of NGS testing performed in EO versus IO groups. Secondary outcomes were time between metastatic disease diagnosis to receipt of test by vendor, time of metastatic diagnosis to result, and proportion of testing by race. RESULTS: A total of 168 patients were identified, 116 EO and 52 IO patients. Between IO and EO periods, testing significantly increased from 52% to 87% (P ≤ .01); it was conducted more quickly, with time from metastatic diagnosis to sample receipt by the NGS vendor improving to median 37 days from 299 days (P = .03); and the time from documented metastatic disease to a test result improved to median 56 days from 309 days (P = .03). The proportion of tissue received by the vendor was not significantly different between the two groups. There were no significant differences in testing according to self-reported race. CONCLUSION: Integration of NGS ordering in the EMR led to increased proportion and speed of testing for a vulnerable patient population served by the country's largest health system.

Multiomic Mapping of Acquired Chromosome 1 Copy-Number and Structural Variants to Identify Therapeutic Vulnerabilities in Multiple Myeloma.

PURPOSE: Chromosome 1 (chr1) copy-number abnormalities (CNA) and structural variants (SV) are frequent in newly diagnosed multiple myeloma (NDMM) and are associated with a heterogeneous impact on outcomes, the drivers of which are largely unknown. EXPERIMENTAL DESIGN: A multiomic approach comprising CRISPR, gene mapping of CNAs and SVs, methylation, expression, and mutational analysis was used to document the extent of chr1 molecular variants and their impact on pathway utilization. RESULTS: We identified two distinct groups of gain(1q): focal gains associated with limited gene-expression changes and a neutral prognosis, and whole-arm gains, which are associated with substantial gene-expression changes, complex genetics, and an adverse prognosis. CRISPR identified a number of dependencies on chr1 but only limited variants associated with acquired CNAs. We identified seven regions of deletion, nine of gain, three of chromothripsis (CT), and two of templated insertion (TI), which contain a number of potential drivers. An additional mechanism involving hypomethylation of genes at 1q may contribute to the aberrant gene expression of a number of genes. Expression changes associated with whole-arm gains were substantial and gene set enrichment analysis identified metabolic processes, apoptotic resistance, signaling via the MAPK pathway, and upregulation of transcription factors as being key drivers of the adverse prognosis associated with these variants. CONCLUSIONS: Multiple layers of genetic complexity impact the phenotype associated with CNAs on chr1 to generate its associated clinical phenotype. Whole-arm gains of 1q are the critically important prognostic group that deregulate multiple pathways, which may offer therapeutic vulnerabilities.

COVID-19 outcomes in hospitalized patients with active cancer: Experiences from a major New York City health care system.

BACKGROUND: The authors sought to study the risk factors associated with severe outcomes in hospitalized coronavirus disease 2019 (COVID-19) patients with cancer. METHODS: The authors queried the New York University Langone Medical Center's records for hospitalized patients who were polymerase chain reaction-positive for severe acute respiratory syndrome coronavirus 2 (SARS CoV-2) and performed chart reviews on patients with cancer diagnoses to identify patients with active cancer and patients with a history of cancer. Descriptive statistics were calculated and multivariable logistic regression was used to determine associations between clinical, demographic, and laboratory characteristics with outcomes, including death and admission to the intensive care unit. RESULTS: A total of 4184 hospitalized SARS CoV-2+ patients, including 233 with active cancer, were identified. Patients with active cancer were more likely to die than those with a history of cancer and those without any cancer history (34.3% vs 27.6% vs 20%, respectively; P < .01). In multivariable regression among all patients, active cancer (odds ratio [OR], 1.89; CI, 1.34-2.67; P < .01), older age (OR, 1.06; CI, 1.05-1.06; P < .01), male sex (OR for female vs male, 0.70; CI, 0.58-0.84; P < .01), diabetes (OR, 1.26; CI, 1.04-1.53; P = .02), morbidly obese body mass index (OR, 1.87; CI, 1.24-2.81; P < .01), and elevated D-dimer (OR, 6.41 for value >2300; CI, 4.75-8.66; P < .01) were associated with increased mortality. Recent cancer-directed medical therapy was not associated with death in multivariable analysis. Among patients with active cancer, those with a hematologic malignancy had the highest mortality rate in comparison with other cancer types (47.83% vs 28.66%; P < .01). CONCLUSIONS: The authors found that patients with an active cancer diagnosis were more likely to die from COVID-19. Those with hematologic malignancies were at the highest risk of death. Patients receiving cancer-directed therapy within 3 months before hospitalization had no overall increased risk of death. LAY SUMMARY: Our investigators found that hospitalized patients with active cancer were more likely to die from coronavirus disease 2019 (COVID-19) than those with a history of cancer and those without any cancer history. Patients with hematologic cancers were the most likely among patients with cancer to die from COVID-19. Patients who received cancer therapy within 3 months before hospitalization did not have an increased risk of death.

The evolving role and utility of off-label drug use in multiple myeloma.

The treatment landscape for multiple myeloma (MM) has dramatically changed over the last three decades, moving from no US Food and Drug Administration approvals and two active drug classes to over 19 drug approvals and at least eight different active classes. The advances seen in MM therapy have relied on both a structured approach to obtaining new labels and cautious off-label drug use. Although there are country and regional differences in drug approval processes, many of the basic principles behind off-label drug use in MM can be summarized into four main categories: 1) use of a therapy prior to the current approval regulations; 2) widespread use of a therapy following the release of promising clinical trial results but prior to drug approval; 3) use of a cheap therapy supported by clinical safety and efficacy data but without commercial backing; and 4) niche therapies for small well-defined patient populations where large clinical trials with sufficient power may be difficult to perform. This review takes a historical approach to discuss how off-label drug use has helped to shape the current treatment approach for MM.