COVID-19 vaccination and breakthrough infections in patients with cancer

BACKGROUND

Vaccination is an important preventive health measure to protect against symptomatic and severe COVID-19. Impaired immunity secondary to an underlying malignancy or recent receipt of antineoplastic systemic therapies can result in less robust antibody titers following vaccination and possible risk of breakthrough infection. As clinical trials evaluating COVID-19 vaccines largely excluded patients with a history of cancer and those on active immunosuppression (including chemotherapy), limited evidence is available to inform the clinical efficacy of COVID-19 vaccination across the spectrum of patients with cancer.

PATIENTS AND METHODS

We describe the clinical features of patients with cancer who developed symptomatic COVID-19 following vaccination and compare weighted outcomes with those of contemporary unvaccinated patients, after adjustment for confounders, using data from the multi-institutional COVID-19 and Cancer Consortium (CCC19).

RESULTS

Patients with cancer who develop COVID-19 following vaccination have substantial comorbidities and can present with severe and even lethal infection. Patients harboring hematologic malignancies are over-represented among vaccinated patients with cancer who develop symptomatic COVID-19.

CONCLUSIONS

Vaccination against COVID-19 remains an essential strategy in protecting vulnerable populations, including patients with cancer. Patients with cancer who develop breakthrough infection despite full vaccination, however, remain at risk of severe outcomes. A multilayered public health mitigation approach that includes vaccination of close contacts, boosters, social distancing, and mask-wearing should be continued for the foreseeable future.

Association of clinical factors and recent anticancer therapy with COVID-19 severity among patients with cancer: a report from the COVID-19 and Cancer Consortium

BACKGROUND

Patients with cancer may be at high risk of adverse outcomes from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. We analyzed a cohort of patients with cancer and coronavirus 2019 (COVID-19) reported to the COVID-19 and Cancer Consortium (CCC19) to identify prognostic clinical factors, including laboratory measurements and anticancer therapies.

PATIENTS AND METHODS

Patients with active or historical cancer and a laboratory-confirmed SARS-CoV-2 diagnosis recorded between 17 March and 18 November 2020 were included. The primary outcome was COVID-19 severity measured on an ordinal scale (uncomplicated, hospitalized, admitted to intensive care unit, mechanically ventilated, died within 30 days). Multivariable regression models included demographics, cancer status, anticancer therapy and timing, COVID-19-directed therapies, and laboratory measurements (among hospitalized patients).

RESULTS

A total of 4966 patients were included (median age 66 years, 51% female, 50% non-Hispanic white); 2872 (58%) were hospitalized and 695 (14%) died; 61% had cancer that was present, diagnosed, or treated within the year prior to COVID-19 diagnosis. Older age, male sex, obesity, cardiovascular and pulmonary comorbidities, renal disease, diabetes mellitus, non-Hispanic black race, Hispanic ethnicity, worse Eastern Cooperative Oncology Group performance status, recent cytotoxic chemotherapy, and hematologic malignancy were associated with higher COVID-19 severity. Among hospitalized patients, low or high absolute lymphocyte count; high absolute neutrophil count; low platelet count; abnormal creatinine; troponin; lactate dehydrogenase; and C-reactive protein were associated with higher COVID-19 severity. Patients diagnosed early in the COVID-19 pandemic (January-April 2020) had worse outcomes than those diagnosed later. Specific anticancer therapies (e.g. R-CHOP, platinum combined with etoposide, and DNA methyltransferase inhibitors) were associated with high 30-day all-cause mortality.

CONCLUSIONS

Clinical factors (e.g. older age, hematological malignancy, recent chemotherapy) and laboratory measurements were associated with poor outcomes among patients with cancer and COVID-19. Although further studies are needed, caution may be required in utilizing particular anticancer therapies.

CLINICAL TRIAL IDENTIFIER

NCT04354701.

Hourly movement decisions indicate how a large carnivore inhabits developed landscapes

The ecology of wildlife living in proximity to humans often differs from that in more natural places. Animals may perceive anthropogenic features and people as threats, exhibiting avoidance behavior, or may acclimate to human activities. As development expands globally, changes in the ecology of species in response to human phenomena may determine whether animals persist in these changing environments. We hypothesize that American black bears (Ursus americanus) persist within developed areas by effectively avoiding risky landscape features. We test this by quantifying changes in the movements of adult females from a population living within exurban and suburban development. We collected hourly GPS data from 23 individuals from 2012 to 2014 and used step-selection functions to estimate selection for anthropogenic features. Females were more avoidant of roads and highways when with cubs than without and were more responsive to increased traffic volume. As bears occupied greater housing densities, selection for housing increased, while avoidance of roads and responsiveness to traffic increased. Behavioral flexibility allowed bears in highly developed areas to alter selection and avoidance for anthropogenic features seasonally. These findings support the hypothesis that black bears perceive human activity as risky, and effectively avoid these risks while inhabiting developed areas. We document a high amount of individual variation in selection of anthropogenic features within the study population. Our findings suggest that initially, wildlife can successfully inhabit developed landscapes by effectively avoiding human activity. However, variation among individuals provides the capacity for population-level shifts in behavior over time.

Spatial genetic patterns indicate mechanism and consequences of large carnivore cohabitation within development

Patterns of human development are shifting from concentrated housing toward sprawled housing intermixed with natural land cover, and wildlife species increasingly persist in close proximity to housing, roads, and other anthropogenic features. These associations can alter population dynamics and evolutionary trajectories. Large carnivores increasingly occupy urban peripheries, yet the ecological consequences for populations established entirely within urban and exurban landscapes are largely unknown. We applied a spatial and landscape genetics approach, using noninvasively collected genetic data, to identify differences in black bear spatial genetic patterns across a rural‐to‐urban gradient and quantify how development affects spatial genetic processes. We quantified differences in black bear dispersal, spatial genetic structure, and migration between differing levels of development within a population primarily occupying areas with >6 houses/km² in western Connecticut. Increased development disrupted spatial genetic structure, and we found an association between increased housing densities and longer dispersal. We also found evidence that roads limited gene flow among bears in more rural areas, yet had no effect among bears in more developed ones. These results suggest dispersal behavior is condition‐dependent and indicate the potential for landscapes intermixing development and natural land cover to facilitate shifts toward increased dispersal. These changes can affect patterns of range expansion and the phenotypic and genetic composition of surrounding populations. We found evidence that subpopulations occupying more developed landscapes may be sustained by male‐biased immigration, creating potentially detrimental demographic shifts.