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1.
EBioMedicine ; 80: 104077, 2022 Jun.
Article in English | MEDLINE | ID: covidwho-1867076

ABSTRACT

BACKGROUND: Severe COVID-19 is associated with a high circulating level of calprotectin, the S100A8/S100A9 alarmin heterodimer. Baseline calprotectin amount measured in peripheral blood at diagnosis correlates with disease severity. The optimal use of this biomarker along COVID-19 course remains to be delineated. METHODS: We focused on patients with a WHO-defined moderate COVID-19 requiring hospitalization in a medical ward. We collected plasma and serum from three independent cohorts (N = 626 patients) and measured calprotectin amount at admission. We performed longitudinal measures of calprotectin in 457 of these patients (1461 samples) and used a joint latent class mixture model in which classes were defined by age, body mass index and comorbidities to identify calprotectin trajectories predicting the risk of transfer into an intensive care unit or death. FINDINGS: After adjustment for age, sex, body mass index and comorbidities, the predictive value of baseline calprotectin in patients with moderate COVID19 could be refined by serial monitoring of the biomarker. We discriminated three calprotectin trajectories associated with low, moderate, and high risk of poor outcome, and we designed an algorithm available as online software (https://calpla.gustaveroussy.fr:8443/) to monitor the probability of a poor outcome in individual patients with moderate COVID-19. INTERPRETATION: These results emphasize the clinical interest of serial monitoring of calprotectin amount in the peripheral blood to anticipate the risk of poor outcomes in patients with moderate COVID-19 hospitalized in a standard care unit. FUNDING: The study received support (research grants) from ThermoFisher immunodiagnostics (France) and Gustave Roussy Foundation.


Subject(s)
COVID-19 , Leukocyte L1 Antigen Complex , Biomarkers/blood , COVID-19/blood , COVID-19/diagnosis , Humans , Leukocyte L1 Antigen Complex/blood , Severity of Illness Index
2.
JCO Clin Cancer Inform ; 6: e2100177, 2022 05.
Article in English | MEDLINE | ID: covidwho-1862196

ABSTRACT

PURPOSE: Patients with cancer are at increased risk of severe COVID-19 disease, but have heterogeneous presentations and outcomes. Decision-making tools for hospital admission, severity prediction, and increased monitoring for early intervention are critical. We sought to identify features of COVID-19 disease in patients with cancer predicting severe disease and build a decision support online tool, COVID-19 Risk in Oncology Evaluation Tool (CORONET). METHODS: Patients with active cancer (stage I-IV) and laboratory-confirmed COVID-19 disease presenting to hospitals worldwide were included. Discharge (within 24 hours), admission (≥ 24 hours inpatient), oxygen (O2) requirement, and death were combined in a 0-3 point severity scale. Association of features with outcomes were investigated using Lasso regression and Random Forest combined with Shapley Additive Explanations. The CORONET model was then examined in the entire cohort to build an online CORONET decision support tool. Admission and severe disease thresholds were established through pragmatically defined cost functions. Finally, the CORONET model was validated on an external cohort. RESULTS: The model development data set comprised 920 patients, with median age 70 (range 5-99) years, 56% males, 44% females, and 81% solid versus 19% hematologic cancers. In derivation, Random Forest demonstrated superior performance over Lasso with lower mean squared error (0.801 v 0.807) and was selected for development. During validation (n = 282 patients), the performance of CORONET varied depending on the country cohort. CORONET cutoffs for admission and mortality of 1.0 and 2.3 were established. The CORONET decision support tool recommended admission for 95% of patients eventually requiring oxygen and 97% of those who died (94% and 98% in validation, respectively). The specificity for mortality prediction was 92% and 83% in derivation and validation, respectively. Shapley Additive Explanations revealed that National Early Warning Score 2, C-reactive protein, and albumin were the most important features contributing to COVID-19 severity prediction in patients with cancer at time of hospital presentation. CONCLUSION: CORONET, a decision support tool validated in health care systems worldwide, can aid admission decisions and predict COVID-19 severity in patients with cancer.


Subject(s)
COVID-19 , Neoplasms , Adolescent , Adult , Aged , Aged, 80 and over , COVID-19/complications , COVID-19/diagnosis , Child , Child, Preschool , Female , Hospitals , Humans , Male , Middle Aged , Neoplasms/complications , Neoplasms/diagnosis , Neoplasms/therapy , Oxygen , SARS-CoV-2 , Young Adult
3.
Open forum infectious diseases ; 8(Suppl 1):S254-S254, 2021.
Article in English | EuropePMC | ID: covidwho-1601836

ABSTRACT

Background Several studies have shown that underlying cancer is a risk factor for progression of COVID-19 to severe illness and fatal outcome but there is very little data that specifies which underlying cancer puts this patient population at the highest risk. Methods We retrospectively collected de-identified data on 1115 cancer patients diagnosed with COVID-19 between January and November 2020, at 12 centers in Asia, Australia, Europe, North America, and South America. Patient characteristics including age, type of malignancy (hematologic malignancy [HM], lung cancer, and non-lung cancer were determined in association with severe illness as well as all-cause mortality within 30 days after COVID-19 diagnosis. Results By multivariable logistic regression analysis, independent risk factors for 30-day mortality in cancer patients included age > 65 (OR 6.64;95% CI 3.351to 12.55;p< 0.0001), ALC < 0.5 K/microliter (OR 2.10;95% CI 1.16 to 3.79;p=0.014), and anemia at < 10g/dl (OR 2.41;95% CI 1.30 to 4.44;p=0.005). Among cancer patients, the 30-day mortality rate was significantly higher in patients with lung cancer than in patients with non-lung cancer solid tumors, including those with lung metastases (22% vs 9%;p=0.001). Patients with HM tended to have higher 30-day mortality than patients with non-lung cancer solid tumors (13% vs 9% p=0.07) and tended to have a lower mortality rate than patients with lung cancer (p=0.07). Furthermore, HM patients were more likely to be lymphopenic and anemic at diagnosis as well as progress to LRTI and be placed on ventilatory support compared to non-lung cancer solid tumor patients ( p= or < 0.01). In addition, lung cancer and HM patients were more likely to develop hypoxia and require hospital admission than non-lung cancer solid tumor patients ( p=0.01). Conclusion Lung cancer and HM patients are associated with the highest risk of progressing to severe disease and mortality in cancer patients with COVID-19. Hence, cancer patient population should be given the highest priority as far as prevention [vaccination with boosters if needed] as well as preemptive early therapy with monoclonal antibodies right after the onset of COVID-19. Disclosures Monica Slavin, MBBS,MD, F2G (Advisor or Review Panel member)Merck (Advisor or Review Panel member)Pfizer (Advisor or Review Panel member)

5.
Open forum infectious diseases ; 8(Suppl 1):S15-S15, 2021.
Article in English | EuropePMC | ID: covidwho-1564213

ABSTRACT

Background Given the limited collaborative international studies that evaluated COVID-19 in patients with cancer in comparison to patients without cancer, we aimed to determine the independent risk factors associated with increased 30-day mortality and the impact of novel treatment modalities in a large group of cancer and non-cancer patients with COVID-19 from multiple countries. Methods We retrospectively collected de-identified data on cancer and non-cancer patients diagnosed with COVID-19 between January and November 2020, at 16 centers in Asia, Australia, Europe, North America, and South America. A logistic regression model was used to identify independent predictors of all-cause mortality within 30 days after COVID-19 diagnosis. Results Of the total 4015 COVID-19 confirmed patients entered, we analyzed 3966 patients, 1115 cancer and 2851 non-cancer patients. Cancer patients were older than non-cancer patients (median age, 61 vs 50 years;p< 0.0001);more likely to be pancytopenic , had pulmonary disorders, hypertension, diabetes mellitus. In addition, they were more likely to present with higher inflammatory biomarkers (D-dimer, ferritin and procalcitonin), but were less likely to present with clinical symptoms. By multivariable logistic regression analysis, cancer was an independent risk factor for 30-day mortality (OR 1.46;95% CI 1.03 to 2.07;p=0.035). Older age (≥65 years) was the strongest predictor of 30-day mortality in all patients (OR 4.55;95% CI 3.34 to 6.20;p< 0.0001). Remdesivir was the only therapeutic agent independently associated with decreased 30-day mortality (OR 0.58;CI 0.39-0.88;p=0.009). Among patients on low-flow oxygen at admission, patients who received remdesivir had a lower 30-day mortality rate than those who were on high flow oxygen (5.9% vs 17.6%;p=0.03). Patients transfused with convalescent plasma within 1 day of diagnosis had a lower 30-day mortality rate than those transfused later (1% vs 7%, p=0.04). Conclusion Cancer is an independent risk factor for increased 30-day all-cause mortality from COVID-19. Remdesivir, particularly in patients receiving low-flow oxygen, can reduce 30-day all-cause mortality, as well as convalescent plasma given early after COVID-19 diagnosis. Disclosures Roy F. Chemaly, MD, MPH, FACP, FIDSA, AiCuris (Grant/Research Support)Ansun Biopharma (Consultant, Grant/Research Support)Chimerix (Consultant, Grant/Research Support)Clinigen (Consultant)Genentech (Consultant, Grant/Research Support)Janssen (Consultant, Grant/Research Support)Karius (Grant/Research Support)Merck (Consultant, Grant/Research Support)Molecular Partners (Consultant, Advisor or Review Panel member)Novartis (Grant/Research Support)Oxford Immunotec (Consultant, Grant/Research Support)Partner Therapeutics (Consultant)Pulmotec (Consultant, Grant/Research Support)Shire/Takeda (Consultant, Grant/Research Support)Viracor (Grant/Research Support)Xenex (Grant/Research Support) Fareed Khawaja, MBBS, Eurofins Viracor (Research Grant or Support) Monica Slavin, MBBS,MD, F2G (Advisor or Review Panel member)Merck (Advisor or Review Panel member)Pfizer (Advisor or Review Panel member) Dimitrios P. Kontoyiannis, MD, Astellas (Consultant)Cidara Therapeutics (Advisor or Review Panel member)Gilead Sciences (Consultant, Grant/Research Support, Other Financial or Material Support, Honoraria)

7.
Int J Radiat Oncol Biol Phys ; 110(4): 947-956, 2021 07 15.
Article in English | MEDLINE | ID: covidwho-1144733

ABSTRACT

PURPOSE: Patients with cancer are presumed to be more vulnerable to COVID-19. We evaluated a screening strategy combining chest computed tomography (CT) and reverse-transcription polymerase chain reaction (RT-PCR) for patients treated with radiation therapy at our cancer center located in a COVID-19 French hotspot during the first wave of the pandemic. METHODS AND MATERIALS: Chest CT images were proposed during radiation therapy CT simulation. Images were reviewed by an expert radiologist according to the COVID-19 Reporting and Data System classification. Nasal swabs with RT-PCR assay were initially proposed in cases of suspicious imaging or clinical context and were eventually integrated into the systematic screening. A dedicated radiation therapy workflow was proposed for COVID-19 patients to limit the risk of contamination. RESULTS: From March 18, 2020 to May 1, 2020, 480 patients were screened by chest CT, and 313 patients had both chest CT and RT-PCR (65%). The cumulative incidence of COVID-19 was 5.4% (95% confidence interval [CI], 3.6-7.8; 26 of 480 patients). Diagnosis of COVID-19 was made before radiation therapy for 22 patients (84.6%) and during RT for 4 patients (15.3%). Chest CT directly aided the diagnosis of 7 cases in which the initial RT-PCR was negative or not feasible, out of a total of 480 patients (1.5%) and 517 chest CT acquisitions. Four patients with COVID-19 at the time of the chest CT screening had a false negative CT. Sensitivity and specificity of chest CT screening in patients with both RT-PCR and chest CT testing were estimated at 0.82 (95% CI, 0.60-0.95) and 0.98 (95% CI, 0.96-0.99), respectively. Adaptation of the radiation therapy treatment was made for all patients, with 7 postponed treatments (median: 5 days; interquartile range, 1.5-14.8). CONCLUSIONS: The benefit of systematic use of chest CT screening during CT simulation for patients undergoing radiation therapy during the COVID-19 pandemic seemed limited.


Subject(s)
COVID-19 Nucleic Acid Testing , COVID-19/diagnosis , Multidetector Computed Tomography , Neoplasms/radiotherapy , Adolescent , Adult , Aged , COVID-19/complications , COVID-19/diagnostic imaging , COVID-19/epidemiology , Cancer Care Facilities , Child , Confidence Intervals , Female , France/epidemiology , Humans , Incidence , Male , Middle Aged , Neoplasms/complications , Radiography, Thoracic/methods , Retrospective Studies , Sensitivity and Specificity , Tomography, Spiral Computed , Young Adult
11.
Nat Cancer ; 1(10): 965-975, 2020 10.
Article in English | MEDLINE | ID: covidwho-798872

ABSTRACT

Patients with cancer are presumed to be at increased risk of severe COVID-19 outcomes due to underlying malignancy and treatment-induced immunosuppression. Of the first 178 patients managed for COVID-19 at the Gustave Roussy Cancer Centre, 125 (70.2%) were hospitalized, 47 (26.4%) developed clinical worsening and 31 (17.4%) died. An age of over 70 years, smoking status, metastatic disease, cytotoxic chemotherapy and an Eastern Cooperative Oncology Group score of ≥2 at the last visit were the strongest determinants of increased risk of death. In multivariable analysis, the Eastern Cooperative Oncology Group score remained the only predictor of death. In contrast, immunotherapy, hormone therapy and targeted therapy did not increase clinical worsening or death risk. Biomarker studies found that C-reactive protein and lactate dehydrogenase levels were significantly associated with an increased risk of clinical worsening, while C-reactive protein and D-dimer levels were associated with an increased risk of death. COVID-19 management impacted the oncological treatment strategy, inducing a median 20 d delay in 41% of patients and adaptation of the therapeutic strategy in 30% of patients.


Subject(s)
COVID-19/epidemiology , SARS-CoV-2/pathogenicity , Aged , Cohort Studies , Female , Humans , Male , Middle Aged
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