Validation of the CoVID-TE model as a tool to predict thrombosis, bleeding, and mortality in the oncology patient with Sars-Cov-2 infection: a study by the SEOM cancer and thrombosis group

Purpose The CoVID-TE model was developed with the aim of predicting venous thrombotic events (VTE) in cancer patients with Sars-Cov-2 infection. Moreover, it was capable of predicting hemorrhage and mortality 30 days following infection diagnosis. The model is pending validation. Methods/patients Multicenter retrospective study (10 centers). Adult patients with active oncologic disease/ antineoplastic therapy with Sars-Cov-2 infection hospitalized between March 1, 2020 and March 1. 2022 were recruited. The primary endpoint was to study the association between the risk categories of the CoVID-TE model and the occurrence of thrombosis using the Chi-Square test. Secondary endpoints were to demonstrate the association between these categories and the occurrence of post-diagnostic Sars-Cov-2 bleeding/ death events. The Kaplan–Meier method was also used to compare mortality by stratification. Results 263 patients were enrolled. 59.3% were men with a median age of 67 years. 73.8% had stage IV disease and lung cancer was the most prevalent tumor (24%). A total of 86.7% had an ECOG 0–2 and 77.9% were receiving active antineoplastic therapy. After a median follow-up of 6.83 months, the incidence of VTE, bleeding, and death 90 days after Sars-Cov-2 diagnosis in the low-risk group was 3.9% (95% CI 1.9–7.9), 4.5% (95% CI 2.3–8.6), and 52.5% (95% CI 45.2–59.7), respectively. For the high-risk group it was 6% (95% CI 2.6–13.2), 9.6% (95% CI 5.0–17.9), and 58.0% (95% CI 45.3–66.1). The Chi-square test for trends detected no statistically significant association between these variables (p > 0.05). Median survival in the low-risk group was 10.15 months (95% CI 3.84–16.46), while in the high-risk group it was 3.68 months (95% CI 0.0–7.79). The differences detected were not statistically significant (p = 0.375) (AU)

Validation of the CoVID-TE model as a tool to predict thrombosis, bleeding, and mortality in the oncology patient with Sars-Cov-2 infection: a study by the SEOM cancer and thrombosis group.

PURPOSE: The CoVID-TE model was developed with the aim of predicting venous thrombotic events (VTE) in cancer patients with Sars-Cov-2 infection. Moreover, it was capable of predicting hemorrhage and mortality 30 days following infection diagnosis. The model is pending validation. METHODS/PATIENTS: Multicenter retrospective study (10 centers). Adult patients with active oncologic disease/ antineoplastic therapy with Sars-Cov-2 infection hospitalized between March 1, 2020 and March 1. 2022 were recruited. The primary endpoint was to study the association between the risk categories of the CoVID-TE model and the occurrence of thrombosis using the Chi-Square test. Secondary endpoints were to demonstrate the association between these categories and the occurrence of post-diagnostic Sars-Cov-2 bleeding/ death events. The Kaplan-Meier method was also used to compare mortality by stratification. RESULTS: 263 patients were enrolled. 59.3% were men with a median age of 67 years. 73.8% had stage IV disease and lung cancer was the most prevalent tumor (24%). A total of 86.7% had an ECOG 0-2 and 77.9% were receiving active antineoplastic therapy. After a median follow-up of 6.83 months, the incidence of VTE, bleeding, and death 90 days after Sars-Cov-2 diagnosis in the low-risk group was 3.9% (95% CI 1.9-7.9), 4.5% (95% CI 2.3-8.6), and 52.5% (95% CI 45.2-59.7), respectively. For the high-risk group it was 6% (95% CI 2.6-13.2), 9.6% (95% CI 5.0-17.9), and 58.0% (95% CI 45.3-66.1). The Chi-square test for trends detected no statistically significant association between these variables (p > 0.05). Median survival in the low-risk group was 10.15 months (95% CI 3.84-16.46), while in the high-risk group it was 3.68 months (95% CI 0.0-7.79). The differences detected were not statistically significant (p = 0.375). CONCLUSIONS: The data from our series does not validate of the CoVID-TE as a model to predict thrombosis, hemorrhage, or mortality in cancer patients with Sars-Cov-2 infection.

Signalling in auctions for risk-averse bidders.

We study risk-averse equilibrium bidding in first-price and second-price sealed-bid auctions where bidders have signalling concerns, i.e., they care about how the auction outcome is interpreted by an outside observer. We find that when the winner's identity and her payment are revealed to the outside observer, risk aversion yields less aggressive bidding behaviour in the second-price sealed-bid auction than in the risk-neutral case. Our analysis explains various revenue ranking reversals relative to the risk-neutral equilibrium observed in a recent experiment by Bos (2021).