Background Data on patients with COVID-19 who have cancer are lacking. Here we characterise the outcomes of a cohort of patients with cancer and COVID-19 and identify potential prognostic factors for mortality and severe illness.Methods In this cohort study, we collected de-identified data on patients with active or previous malignancy, aged 18 years and older, with confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection from the USA, Canada, and Spain from the COVID-19 and Cancer Consortium (CCC19) database for whom baseline data were added between March 17 and April 16, 2020. We collected data on baseline clinical conditions, medications, cancer diagnosis and treatment, and COVID-19 disease course. The primary endpoint was all-cause mortality within 30 days of diagnosis of COVID-19. We assessed the association between the outcome and potential prognostic variables using logistic regression analyses, partially adjusted for age, sex, smoking status, and obesity. This study is registered with ClinicalTrials.gov, NCT04354701, and is ongoing. FindingsOf 1035 records entered into the CCC19 database during the study period, 928 patients met inclusion criteria for our analysis. Median age was 66 years (IQR 57-76), 279 (30%) were aged 75 years or older, and 468 (50%) patients were male. The most prevalent malignancies were breast (191 [21%]) and prostate (152 [16%]). 366 (39%) patients were on active anticancer treatment, and 396 (43%) had active (measurable) cancer. At analysis (May 7, 2020), 121 (13%) patients had died. In logistic regression analysis, independent factors associated with increased 30-day mortality, after partial adjustment, were: increased age (per 10 years; partially adjusted odds ratio 1•84, 95% CI 1•53-2•21), male sex (1•63, 1•07-2•48), smoking status (former smoker vs never smoked: 1•60, 1•03-2•47), number of comorbidities (two vs none: 4•50, 1•33-15•28), Eastern Cooperative Oncology Group performance status of 2 or higher (status of 2 vs 0 or 1: 3•89, 2•11-7•18), active cancer (progressing vs remission: 5•20, 2•77-9•77), and receipt of azithromycin plus hydroxychloroquine (vs treatment with neither: 2•93, 1•79-4•79; confounding by indication cannot be excluded). Compared with residence in the US-Northeast, residence in Canada (0•24, 0•07-0•84) or the US-Midwest (0•50, 0•28-0•90) were associated with decreased 30-day all-cause mortality. Race and ethnicity, obesity status, cancer type, type of anticancer therapy, and recent surgery were not associated with mortality. Interpretation Among patients with cancer and COVID-19, 30-day all-cause mortality was high and associated with general risk factors and risk factors unique to patients with cancer. Longer follow-up is needed to better understand the effect of COVID-19 on outcomes in patients with cancer, including the ability to continue specific cancer treatments.

IMPORTANCE COVID-19 is a life-threatening illness for many patients. Prior studies have established hematologic cancers as a risk factor associated with particularly poor outcomes from COVID-19. To our knowledge, no studies have established a beneficial role for anti-COVID-19 interventions in this at-risk population. Convalescent plasma therapy may benefit immunocompromised individuals with COVID-19, including those with hematologic cancers.OBJECTIVE To evaluate the association of convalescent plasma treatment with 30-day mortality in hospitalized adults with hematologic cancers and COVID-19 from a multi-institutional cohort. DESIGN, SETTING, AND PARTICIPANTSThis retrospective cohort study using data from the COVID-19 and Cancer Consortium registry with propensity score matching evaluated patients with hematologic cancers who were hospitalized for COVID-19. Data were collected between

Purpose: Liquid biopsy provides a real-time assessment of metastatic breast cancer (MBC). We evaluated the utility of combining circulating tumor cells (CTC) and circulating tumor DNA (ctDNA) to predict prognosis in MBC.Experimental Design: We conducted a retrospective study of 91 patients with locally advanced breast cancer and MBC. CTCs were enumerated by CellSearch; the plasma-based assay was performed utilizing Guardant360 and the survival analysis using Kaplan-Meier curves.Results: Eighty-four patients had stage IV cancer, and 7 patients had no metastases. Eighty patients had CTC analysis: median number 2 (0-5,612). Blood samples [232 of 277 (84%)] had mutations. The average ctDNA fraction was 4.5% (0-88.2%) and number of alterations 3 (0-27); the most commonly mutated genes were TP53 (52%), PIK3CA (40%), and ERBB2 (20%). At the time of analysis, 36 patients (39.6%) were dead. The median follow-up for CTCs was 9 months; for ctDNA, it was 9.9 months. For CTCs and ctDNA, respectively, progression-free survival (PFS) was 4.2 and 5.2 months and overall survival (OS) was 18.7 and 21.5 months. There was a statistically significant difference in PFS and OS for baseline CTCs < 5 versus CTCs ! 5 (P ¼ 0.021 and P ¼ 0.0004, respectively); %ctDNA < 0.5 versus ! 0.5 (P ¼ 0.003 and P ¼ 0.012); number of alterations < 2 versus ! 2 (P ¼ 0.059 borderline and P ¼ 0.0015). A significant association by Fisher exact test was found between the number of alterations and the %ctDNA in the baseline sample (P < 0.0001).Conclusions: The study demonstrated that liquid biopsy is an effective prognostic tool. Clin Cancer Res; 24(3); 560-8. Ó2017 AACR.

Background Electronic health records (EHRs) are increasingly used for clinical and translational research through the creation of phenotype algorithms. Currently, phenotype algorithms are most commonly represented as noncomputable descriptive documents and knowledge artifacts that detail the protocols for querying diagnoses, symptoms, procedures, medications, and/or text-driven medical concepts, and are primarily meant for human comprehension. We present desiderata for developing a computable phenotype representation model (PheRM).Methods A team of clinicians and informaticians reviewed common features for multisite phenotype algorithms published in PheKB.org and existing phenotype representation platforms. We also evaluated well-known diagnostic criteria and clinical decision-making guidelines to encompass a broader category of algorithms.Results We propose 10 desired characteristics for a flexible, computable PheRM: (1) structure clinical data into queryable forms; (2) recommend use of a common data model, but also support customization for the variability and availability of EHR data among sites; (3) support both human-readable and computable representations of phenotype algorithms; (4) implement set operations and relational algebra for modeling phenotype algorithms; (5) represent phenotype criteria with structured rules; (6) support defining temporal relations between events; (7) use standardized terminologies and ontologies, and facilitate reuse of value sets; (8) define representations for text searching and natural language processing; (9) provide interfaces for external software algorithms; and (10) maintain backward compatibility.Conclusion A computable PheRM is needed for true phenotype portability and reliability across different EHR products and healthcare systems. These desiderata are a guide to inform the establishment and evolution of EHR phenotype algorithm authoring platforms and languages.

BackgroundStarting HAART in a very advanced stage of disease is assumed to be the most prevalent form of initiation in HIV-infected subjects in developing countries. Data from Latin America and the Caribbean is still lacking. Our main objective was to determine the frequency, risk factors and trends in time for being late HAART initiator (LHI) in this region.MethodologyCross-sectional analysis from 9817 HIV-infected treatment-naïve patients initiating HAART at 6 sites (Argentina, Chile, Haiti, Honduras, Peru and Mexico) from October 1999 to July 2010. LHI had CD4+ count ≤200cells/mm3 prior to HAART. Late testers (LT) were those LHI who initiated HAART within 6 months of HIV diagnosis. Late presenters (LP) initiated after 6 months of diagnosis. Prevalence, risk factors and trends over time were analyzed.Principal FindingsAmong subjects starting HAART (n = 9817) who had baseline CD4+ available (n = 8515), 76% were LHI: Argentina (56%[95%CI:52–59]), Chile (80%[95%CI:77–82]), Haiti (76%[95%CI:74–77]), Honduras (91%[95%CI:87–94]), Mexico (79%[95%CI:75–83]), Peru (86%[95%CI:84–88]). The proportion of LHI statistically changed over time (except in Honduras) (p≤0.02; Honduras p = 0.7), with a tendency towards lower rates in recent years. Males had increased risk of LHI in Chile, Haiti, Peru, and in the combined site analyses (CSA). Older patients were more likely LHI in Argentina and Peru (OR 1.21 per +10-year of age, 95%CI:1.02–1.45; OR 1.20, 95%CI:1.02–1.43; respectively), but not in CSA (OR 1.07, 95%CI:0.94–1.21). Higher education was associated with decreased risk for LHI in Chile (OR 0.92 per +1-year of education, 95%CI:0.87–0.98) (similar trends in Mexico, Peru, and CSA). LHI with date of HIV-diagnosis available, 55% were LT and 45% LP.ConclusionLHI was highly prevalent in CCASAnet sites, mostly due to LT; the main risk factors associated were being male and older age. Earlier HIV-diagnosis and earlier treatment initiation are needed to maximize benefits from HAART in the region.