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- Bruggmann, P., et al.
(författare)
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Historical epidemiology of hepatitis C virus (HCV) in selected countries
- 2014
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Ingår i: Journal of Viral Hepatitis. - Hoboken : Wiley-Blackwell. - 1352-0504 .- 1365-2893. ; 21, s. 5-33
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Tidskriftsartikel (refereegranskat)abstract
- Chronic infection with hepatitis C virus (HCV) is a leading indicator for liver disease. New treatment options are becoming available, and there is a need to characterize the epidemiology and disease burden of HCV. Data for prevalence, viremia, genotype, diagnosis and treatment were obtained through literature searches and expert consensus for 16 countries. For some countries, data from centralized registries were used to estimate diagnosis and treatment rates. Data for the number of liver transplants and the proportion attributable to HCV were obtained from centralized databases. Viremic prevalence estimates varied widely between countries, ranging from 0.3% in Austria, England and Germany to 8.5% in Egypt. The largest viremic populations were in Egypt, with 6358000 cases in 2008 and Brazil with 2106000 cases in 2007. The age distribution of cases differed between countries. In most countries, prevalence rates were higher among males, reflecting higher rates of injection drug use. Diagnosis, treatment and transplant levels also differed considerably between countries. Reliable estimates characterizing HCV-infected populations are critical for addressing HCV-related morbidity and mortality. There is a need to quantify the burden of chronic HCV infection at the national level.
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- Burn, E., et al.
(författare)
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Deep phenotyping of 34,128 adult patients hospitalised with COVID-19 in an international network study
- 2020
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Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 11:1
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Tidskriftsartikel (refereegranskat)abstract
- Comorbid conditions appear to be common among individuals hospitalised with coronavirus disease 2019 (COVID-19) but estimates of prevalence vary and little is known about the prior medication use of patients. Here, we describe the characteristics of adults hospitalised with COVID-19 and compare them with influenza patients. We include 34,128 (US: 8362, South Korea: 7341, Spain: 18,425) COVID-19 patients, summarising between 4811 and 11,643 unique aggregate characteristics. COVID-19 patients have been majority male in the US and Spain, but predominantly female in South Korea. Age profiles vary across data sources. Compared to 84,585 individuals hospitalised with influenza in 2014-19, COVID-19 patients have more typically been male, younger, and with fewer comorbidities and lower medication use. While protecting groups vulnerable to influenza is likely a useful starting point in the response to COVID-19, strategies will likely need to be broadened to reflect the particular characteristics of individuals being hospitalised with COVID-19. Detailed knowledge of the characteristics of COVID-19 patients helps with public health planning. Here, the authors use routinely-collected data from seven databases in three countries to describe the characteristics of >30,000 patients admitted with COVID-19 and compare them with those admitted for influenza in previous years.
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- Cremers, Ruben G., et al.
(författare)
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The role of the prostate cancer gene 3 urine test in addition to serum prostate-specific antigen level in prostate cancer screening among breast cancer, early-onset gene mutation carriers
- 2015
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Ingår i: Urologic Oncology: Seminars and Original Investigations. - : Elsevier BV. - 1078-1439. ; 33:5, s. 19-202
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Tidskriftsartikel (refereegranskat)abstract
- Objective: To evaluate the additive value of the prostate cancer gene 3 (PCA3) urine test to serum prostate-specific antigen (PSA) in prostate cancer (PC) screening among breast cancer, early-onset gene (BRCA) mutation carriers. This study was performed among the Dutch participants of IMPACT, a large international study on the effectiveness of PSA screening among BRCA mutation carriers. Materials and methods: Urinary PCA3 was measured in 191 BRCA1 mutation carriers, 75 BRCA2 mutation carriers, and 308 noncarriers. The physicians and participants were blinded for the results. Serum PSA level≥3.0. ng/ml was used to indicate prostate biopsies. PCA3 was evaluated (1) as an independent indicator for prostate biopsies and (2) as an indicator for prostate biopsies among men with an elevated PSA level. PC detected up to the 2-year screening was used as gold standard as end-of-study biopsies were not performed. Results: Overall, 23 PCs were diagnosed, 20 of which were in men who had an elevated PSA level in the initial screening round. (1) PCA3, successfully determined in 552 participants, was elevated in 188 (cutoff≥25; 34%) or 134 (cutoff≥35; 24%) participants, including 2 of the 3 PCs missed by PSA. PCA3 would have added 157 (≥25; 28%) or 109 (≥35; 20%) biopsy sessions to screening with PSA only. (2) Elevated PCA3 as a requirement for biopsies in addition to PSA would have saved 37 (cutoff≥25) or 43 (cutoff≥35) of the 68 biopsy sessions, and 7 or 11 PCs would have been missed, respectively, including multiple high-risk PCs. So far, PCA3 performed best among BRCA2 mutation carriers, but the numbers are still small. Because PCA3 was not used to indicate prostate biopsies, its true diagnostic value cannot be calculated. Conclusions: The results do not provide evidence for PCA3 as a useful additional indicator of prostate biopsies in BRCA mutation carriers, as many participants had an elevated PCA3 in the absence of PC. This must be interpreted with caution because PCA3 was not used to indicate biopsies. Many participants diagnosed with PC had low PCA3, making it invalid as a restrictive marker for prostate biopsies in men with elevated PSA levels.
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- Razavi, H., et al.
(författare)
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The present and future disease burden of hepatitis C virus (HCV) infection with today's treatment paradigm
- 2014
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Ingår i: Journal of Viral Hepatitis. - Hoboken : Wiley-Blackwell. - 1352-0504 .- 1365-2893. ; 21:Suppl. 1, s. 34-59
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Tidskriftsartikel (refereegranskat)abstract
- The disease burden of hepatitis C virus (HCV) is expected to increase as the infected population ages. A modelling approach was used to estimate the total number of viremic infections, diagnosed, treated and new infections in 2013. In addition, the model was used to estimate the change in the total number of HCV infections, the disease progression and mortality in 2013-2030. Finally, expert panel consensus was used to capture current treatment practices in each country. Using today's treatment paradigm, the total number of HCV infections is projected to decline or remain flat in all countries studied. However, in the same time period, the number of individuals with late-stage liver disease is projected to increase. This study concluded that the current treatment rate and efficacy are not sufficient to manage the disease burden of HCV. Thus, alternative strategies are required to keep the number of HCV individuals with advanced liver disease and liver-related deaths from increasing.
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- Wedemeyer, H., et al.
(författare)
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Strategies to manage hepatitis C virus (HCV) disease burden
- 2014
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Ingår i: Journal of Viral Hepatitis. - Hoboken : Wiley-Blackwell. - 1352-0504 .- 1365-2893. ; 21, s. 60-89
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Tidskriftsartikel (refereegranskat)abstract
- The number of hepatitis C virus (HCV) infections is projected to decline while those with advanced liver disease will increase. A modeling approach was used to forecast two treatment scenarios: (i) the impact of increased treatment efficacy while keeping the number of treated patients constant and (ii) increasing efficacy and treatment rate. This analysis suggests that successful diagnosis and treatment of a small proportion of patients can contribute significantly to the reduction of disease burden in the countries studied. The largest reduction in HCV-related morbidity and mortality occurs when increased treatment is combined with higher efficacy therapies, generally in combination with increased diagnosis. With a treatment rate of approximately 10%, this analysis suggests it is possible to achieve elimination of HCV (defined as a >90% decline in total infections by 2030). However, for most countries presented, this will require a 3-5 fold increase in diagnosis and/or treatment. Thus, building the public health and clinical provider capacity for improved diagnosis and treatment will be critical.
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- Razavi, H., et al.
(författare)
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Hepatitis C virus prevalence and level of intervention required to achieve the WHO targets for elimination in the European Union by 2030: a modelling study
- 2017
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Ingår i: Lancet Gastroenterology & Hepatology. - : Elsevier BV. - 2468-1253. ; 2:5, s. 325-336
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Tidskriftsartikel (refereegranskat)abstract
- Background Hepatitis C virus (HCV) is a leading cause of liver-related morbidity and mortality worldwide. In the European Union (EU), treatment and cure of HCV with direct-acting antiviral therapies began in 2014. WHO targets are to achieve a 65% reduction in liver-related deaths, a 90% reduction of new viral hepatitis infections, and 90% of patients with viral hepatitis infections being diagnosed by 2030. This study assessed the prevalence of HCV in the EU and the level of intervention required to achieve WHO targets for HCV elimination. Methods We populated country Markov models for the 28 EU countries through a literature search of PubMed and Embase between Jan 1, 2000, and March 31, 2016, and a Delphi process to gain expert consensus and validate inputs. We aggregated country models to create a regional EU model. We used the EU model to forecast HCV disease progression (considering the effect of immigration) and developed a strategy to acehive WHO targets. We used weighted average sustained viral response rates and fibrosis restrictions to model the effect of current therapeutic guidelines. We used the EU model to forecast HCV disease progression (considering the effect of immigration) under current screening and therapeutic guidelines. Additionally, we back-calculated the total number of patients needing to be screened and treated to achieve WHO targets. Findings We estimated the number of viraemic HCV infections in 2015 to be 3 238 000 (95% uncertainty interval [UI] 2 106 000-3 795 000) of a total population of 509 868 000 in the EU, equating to a prevalence of viraemic HCV of 0.64% (95% UI 0.41-0.74). We estimated that 1 180 000 (95% UI 1 003 000-1 357 000) people were diagnosed with viraemia (36.4%), 150 000 (12 000-180 000) were treated (4.6% of the total infected population or 12.7% of the diagnosed population), 133 000 (106 000-160 000) were cured (4.1%), and 57 900 (43 900-67 300) were newly infected (1.8%) in 2015. Additionally, 30 400 (26 600-42 500) HCV-positive immigrants entered the EU. To achieve WHO targets, unrestricted treatment needs to increase from 150 000 patients in 2015 to 187 000 patients in 2025 and diagnosis needs to increase from 88 800 new cases annually in 2015 to 180 000 in 2025. Interpretation Given its advanced health-care infrastructure, the EU is uniquely poised to eliminate HCV; however, expansion of screening programmes is essential to increase treatment to achieve the WHO targets. A united effort, grounded in sound epidemiological evidence, will also be necessary.
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| 20. |
- Reps, J. M., et al.
(författare)
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Implementation of the COVID-19 Vulnerability Index Across an International Network of Health Care Data Sets: Collaborative External Validation Study
- 2021
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Ingår i: JMIR Medical Informatics. - : JMIR Publications Inc.. - 2291-9694. ; 9:4
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Tidskriftsartikel (refereegranskat)abstract
- Background: SARS-CoV-2 is straining health care systems globally. The burden on hospitals during the pandemic could be reduced by implementing prediction models that can discriminate patients who require hospitalization from those who do not. The COVID-19 vulnerability (C-19) index, a model that predicts which patients will be admitted to hospital for treatment of pneumonia or pneumonia proxies, has been developed and proposed as a valuable tool for decision-making during the pandemic. However, the model is at high risk of bias according to the "prediction model risk of bias assessment" criteria, and it has not been externally validated. Objective: The aim of this study was to externally validate the C-19 index across a range of health care settings to determine how well it broadly predicts hospitalization due to pneumonia in COVID-19 cases. Methods: We followed the Observational Health Data Sciences and Informatics (OHDSI) framework for external validation to assess the reliability of the C-19 index. We evaluated the model on two different target populations, 41,381 patients who presented with SARS-CoV-2 at an outpatient or emergency department visit and 9,429,285 patients who presented with influenza or related symptoms during an outpatient or emergency department visit, to predict their risk of hospitalization with pneumonia during the following 0-30 days. In total, we validated the model across a network of 14 databases spanning the United States, Europe, Australia, and Asia. Results: The internal validation performance of the C-19 index had a C statistic of 0.73, and the calibration was not reported by the authors. When we externally validated it by transporting it to SARS-CoV-2 data, the model obtained C statistics of 0.36, 0.53 (0.473-0.584) and 0.56 (0.488-0.636) on Spanish, US, and South Korean data sets, respectively. The calibration was poor, with the model underestimating risk. When validated on 12 data sets containing influenza patients across the OHDSI network, the C statistics ranged between 0.40 and 0.68. Conclusions: Our results show that the discriminative performance of the C-19 index model is low for influenza cohorts and even worse among patients with COVID-19 in the United States, Spain, and South Korea. These results suggest that C-19 should not be used to aid decision-making during the COVID-19 pandemic. Our findings highlight the importance of performing external validation across a range of settings, especially when a prediction model is being extrapolated to a different population. In the field of prediction, extensive validation is required to create appropriate trust in a model.
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| 21. |
- Williams, R. D., et al.
(författare)
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Seek COVER: using a disease proxy to rapidly develop and validate a personalized risk calculator for COVID-19 outcomes in an international network
- 2022
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Ingår i: BMC Medical Research Methodology. - : Springer Science and Business Media LLC. - 1471-2288. ; 22:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: We investigated whether we could use influenza data to develop prediction models for COVID-19 to increase the speed at which prediction models can reliably be developed and validated early in a pandemic. We developed COVID-19 Estimated Risk (COVER) scores that quantify a patient’s risk of hospital admission with pneumonia (COVER-H), hospitalization with pneumonia requiring intensive services or death (COVER-I), or fatality (COVER-F) in the 30-days following COVID-19 diagnosis using historical data from patients with influenza or flu-like symptoms and tested this in COVID-19 patients. Methods: We analyzed a federated network of electronic medical records and administrative claims data from 14 data sources and 6 countries containing data collected on or before 4/27/2020. We used a 2-step process to develop 3 scores using historical data from patients with influenza or flu-like symptoms any time prior to 2020. The first step was to create a data-driven model using LASSO regularized logistic regression, the covariates of which were used to develop aggregate covariates for the second step where the COVER scores were developed using a smaller set of features. These 3 COVER scores were then externally validated on patients with 1) influenza or flu-like symptoms and 2) confirmed or suspected COVID-19 diagnosis across 5 databases from South Korea, Spain, and the United States. Outcomes included i) hospitalization with pneumonia, ii) hospitalization with pneumonia requiring intensive services or death, and iii) death in the 30 days after index date. Results: Overall, 44,507 COVID-19 patients were included for model validation. We identified 7 predictors (history of cancer, chronic obstructive pulmonary disease, diabetes, heart disease, hypertension, hyperlipidemia, kidney disease) which combined with age and sex discriminated which patients would experience any of our three outcomes. The models achieved good performance in influenza and COVID-19 cohorts. For COVID-19 the AUC ranges were, COVER-H: 0.69–0.81, COVER-I: 0.73–0.91, and COVER-F: 0.72–0.90. Calibration varied across the validations with some of the COVID-19 validations being less well calibrated than the influenza validations. Conclusions: This research demonstrated the utility of using a proxy disease to develop a prediction model. The 3 COVER models with 9-predictors that were developed using influenza data perform well for COVID-19 patients for predicting hospitalization, intensive services, and fatality. The scores showed good discriminatory performance which transferred well to the COVID-19 population. There was some miscalibration in the COVID-19 validations, which is potentially due to the difference in symptom severity between the two diseases. A possible solution for this is to recalibrate the models in each location before use. © 2022, The Author(s).
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- Recalde, M., et al.
(författare)
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Characteristics and outcomes of 627 044 COVID-19 patients living with and without obesity in the United States, Spain, and the United Kingdom
- 2021
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Ingår i: International Journal of Obesity. - : Springer Science and Business Media LLC. - 0307-0565 .- 1476-5497. ; 45:11, s. 2347-2357
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Tidskriftsartikel (refereegranskat)abstract
- Background A detailed characterization of patients with COVID-19 living with obesity has not yet been undertaken. We aimed to describe and compare the demographics, medical conditions, and outcomes of COVID-19 patients living with obesity (PLWO) to those of patients living without obesity. Methods We conducted a cohort study based on outpatient/inpatient care and claims data from January to June 2020 from Spain, the UK, and the US. We used six databases standardized to the OMOP common data model. We defined two non-mutually exclusive cohorts of patients diagnosed and/or hospitalized with COVID-19; patients were followed from index date to 30 days or death. We report the frequency of demographics, prior medical conditions, and 30-days outcomes (hospitalization, events, and death) by obesity status. Results We included 627 044 (Spain: 122 058, UK: 2336, and US: 502 650) diagnosed and 160 013 (Spain: 18 197, US: 141 816) hospitalized patients with COVID-19. The prevalence of obesity was higher among patients hospitalized (39.9%, 95%CI: 39.8-40.0) than among those diagnosed with COVID-19 (33.1%; 95%CI: 33.0-33.2). In both cohorts, PLWO were more often female. Hospitalized PLWO were younger than patients without obesity. Overall, COVID-19 PLWO were more likely to have prior medical conditions, present with cardiovascular and respiratory events during hospitalization, or require intensive services compared to COVID-19 patients without obesity. Conclusion We show that PLWO differ from patients without obesity in a wide range of medical conditions and present with more severe forms of COVID-19, with higher hospitalization rates and intensive services requirements. These findings can help guiding preventive strategies of COVID-19 infection and complications and generating hypotheses for causal inference studies.
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