Objectives: To systematically evaluate the performance of COVID-19 prognostic models and scores for mortality risk in older populations across three health-care settings: hospitals, primary care,... Show moreObjectives: To systematically evaluate the performance of COVID-19 prognostic models and scores for mortality risk in older populations across three health-care settings: hospitals, primary care, and nursing homes.Study Design and Setting: This retrospective external validation study included 14,092 older individuals of >=70 years of age with a clinical or polymerase chain reaction-confirmed COVID-19 diagnosis from March 2020 to December 2020. The six validation cohorts include three hospital-based (CliniCo, COVID-OLD, COVID-PREDICT), two primary care-based (Julius General Practitioners Network/Academisch network huisartsgeneeskunde/Network of Academic general Practitioners, PHARMO), and one nursing home cohort (YSIS) in the Netherlands. Based on a living systematic review of COVID-19 prediction models using Prediction model Risk Of Bias ASsessment Tool for quality and risk of bias assessment and considering predictor availability in validation cohorts, we selected six prognostic models predicting mortality risk in adults with COVID-19 infection (GAL-COVID-19 mortality, 4C Mortality Score, National Early Warning Score 2-extended model, Xie model, Wang clinical model, and CURB65 score). All six prognostic models were validated in the hospital cohorts and the GAL-COVID-19 mortality model was validated in all three healthcare settings. The primary outcome was in-hospital mortality for hospitals and 28-day mortality for primary care and nursing home settings. Model performance was evaluated in each validation cohort separately in terms of discrimination, calibration, and decision curves. An intercept update was performed in models indicating miscalibration followed by predictive performance re-evaluation. Main Outcome Measure: In-hospital mortality for hospitals and 28-day mortality for primary care and nursing home setting. Results: All six prognostic models performed poorly and showed miscalibration in the older population cohorts. In the hospital settings, model performance ranged from calibration-in-the-large 1.45 to 7.46, calibration slopes 0.24e0.81, and C-statistic 0.55e0.71 with 4C Mortality Score performing as the most discriminative and well-calibrated model. Performance across health-care settings was similar for the GAL-COVID-19 model, with a calibration-in-the-large in the range of 2.35 to 0.15 indicating overestimation, calibration slopes of 0.24e0.81 indicating signs of overfitting, and C-statistic of 0.55e0.71. Conclusion: Our results show that most prognostic models for predicting mortality risk performed poorly in the older population with COVID-19, in each health-care setting: hospital, primary care, and nursing home settings. Insights into factors influencing predictive model performance in the older population are needed for pandemic preparedness and reliable prognostication of health-related outcomes in this demographic Show less
Popping, S.; Nichols, B.E.; Appelman, B.; Biemond, J.J.; Vergouwe, M.; Rosendaal, F.R.; ... ; Turn-Covid Study Grp 2023
IMPORTANCE Pre-exposure prophylaxis with neutralizing SARS-CoV-2 monoclonal antibodies (mAbs PrEP) prevents infection and reduces hospitalizations and the duration thereof for COVID-19 and death... Show moreIMPORTANCE Pre-exposure prophylaxis with neutralizing SARS-CoV-2 monoclonal antibodies (mAbs PrEP) prevents infection and reduces hospitalizations and the duration thereof for COVID-19 and death among high-risk individuals. However, reduced effectiveness due to a changing SARS-CoV-2 viral landscape and high drug prices remain substantial implementation barriers.OBJECTIVE To assess the cost-effectiveness of mAbs PrEP as COVID-19 PrEP.DESIGN, SETTING, AND PARTICIPANTS For this economic evaluation, a decision analytic model was developed and parameterized with health care outcome and utilization data from individuals with high risk for COVID-19. The SARS-CoV-2 infection probability, mAbs PrEP effectiveness, and drug pricing were varied. All costs were collected from a third-party payer perspective. Data were analyzed from September 2021 to December 2022.MAIN OUTCOMES AND MEASURES Health care outcomes including new SARS-CoV-2 infections, hospitalization, and deaths. The cost per death averted and cost-effectiveness ratios using a threshold for prevention interventions of $22000 or less per quality-adjusted life year (QALY) gained.RESULTS The clinical cohort consisted of 636 individuals with COVID-19 (mean [SD] age 63 [18] years; 341 [54%] male). Most individuals were at high risk for severe COVID-19, including 137 (21%) with a body mass index of 30 or higher, 60 (9.4%) with hematological malignant neoplasm, 108 (17%) post-transplantation, and 152 (23.9%) who used immunosuppressive medication before COVID-19. Within the context of a high (18%) SARS-CoV-2 infection probability and low (25%) effectiveness the model calculated a short-term reduction of 42% ward admissions, 31% intensive care unit (ICU) admissions, and 34% deaths. Cost-saving scenarios were obtained with drug prices of $275 and 75% or higher effectiveness. With a 100% effectiveness mAbs PrEP can reduce ward admissions by 70%, ICU admissions by 97%, and deaths by 92%. Drug prices, however, need to reduce to $550 for cost-effectiveness ratios less than $22000 per QALY gained per death averted and to $2200 for ratios between $22000 and $88000.CONCLUSIONS AND RELEVANCE In this study, use of mAbs PrEP for preventing SARS-CoV-2 infections was cost-saving at the beginning of an epidemic wave (high infection probability) with 75% or higher effectiveness and drug price of $275. These results are timely and relevant for decision-makers involved in mAbs PrEP implementation. When newer mAbs PrEP combinations become available, guidance on implementation should be formulated ensuring a fast rollout. Nevertheless, advocacy for mAbs PrEP use and critical discussion on drug prices are necessary to ensuring cost-effectiveness for different epidemic settings. Show less
Background Large clinical trials on drugs for hospitalized coronavirus disease 2019 (COVID-19) patients have shown significant effects on mortality. There may be a discrepancy with the observed... Show moreBackground Large clinical trials on drugs for hospitalized coronavirus disease 2019 (COVID-19) patients have shown significant effects on mortality. There may be a discrepancy with the observed real-world effect. We describe the clinical characteristics and outcomes of hospitalized COVID-19 patients in the Netherlands during 4 pandemic waves and analyze the association of the newly introduced treatments with mortality, intensive care unit (ICU) admission, and discharge alive. Methods We conducted a nationwide retrospective analysis of hospitalized COVID-19 patients between February 27, 2020, and December 31, 2021. Patients were categorized into waves and into treatment groups (hydroxychloroquine, remdesivir, neutralizing severe acute respiratory syndrome coronavirus 2 monoclonal antibodies, corticosteroids, and interleukin [IL]-6 antagonists). Four types of Cox regression analyses were used: unadjusted, adjusted, propensity matched, and propensity weighted. Results Among 5643 patients from 11 hospitals, we observed a changing epidemiology during 4 pandemic waves, with a decrease in median age (67-64 years; P < .001), in in-hospital mortality on the ward (21%-15%; P < .001), and a trend in the ICU (24%-16%; P = .148). In ward patients, hydroxychloroquine was associated with increased mortality (1.54; 95% CI, 1.22-1.96), and remdesivir was associated with a higher rate of discharge alive within 29 days (1.16; 95% CI, 1.03-1.31). Corticosteroids were associated with a decrease in mortality (0.82; 95% CI, 0.69-0.96); the results of IL-6 antagonists were inconclusive. In patients directly admitted to the ICU, hydroxychloroquine, corticosteroids, and IL-6 antagonists were not associated with decreased mortality. Conclusions Both remdesivir and corticosteroids were associated with better outcomes in ward patients with COVID-19. Continuous evaluation of real-world treatment effects is needed. Show less
