PREDICT-GTN 1: Can we improve the FIGO scoring system in gestational trophoblastic neoplasia?

Gestational trophoblastic neoplasia (GTN) patients are treated according to the eight-variable International Federation of Gynaecology and Obstetrics (FIGO) scoring system, that aims to predict first-line single-agent chemotherapy resistance. FIGO is imperfect with one-third of low-risk patients developing disease resistance to first-line single-agent chemotherapy. We aimed to generate simplified models that improve upon FIGO. Logistic regression (LR) and multilayer perceptron (MLP) modelling (n = 4191) generated six models (M1-6). M1, all eight FIGO variables (scored data); M2, all eight FIGO variables (scored and raw data); M3, nonimaging variables (scored data); M4, nonimaging variables (scored and raw data); M5, imaging variables (scored data); and M6, pretreatment hCG (raw data) + imaging variables (scored data). Performance was compared to FIGO using true and false positive rates, positive and negative predictive values, diagnostic odds ratio, receiver operating characteristic (ROC) curves, Bland-Altman calibration plots, decision curve analysis and contingency tables. M1-6 were calibrated and outperformed FIGO on true positive rate and positive predictive value. Using LR and MLP, M1, M2 and M4 generated small improvements to the ROC curve and decision curve analysis. M3, M5 and M6 matched FIGO or performed less well. Compared to FIGO, most (excluding LR M4 and MLP M5) had significant discordance in patient classification (McNemar's test P < .05); 55-112 undertreated, 46-206 overtreated. Statistical modelling yielded only small gains over FIGO performance, arising through recategorisation of treatment-resistant patients, with a significant proportion of under/overtreatment as the available data have been used a priori to allocate primary chemotherapy. Streamlining FIGO should now be the focus.     

Skin regeneration,repair, and reconstruction: present and future

European Surgery - Large skin defects caused by trauma (e.g., burns) or due to other reasons (e.g., tumor-related skin resections) require sufficient skin replacement. The constant improvement of...     

Praxis der perioperativen Prävention von Phantomschmerz: eine deutschlandweite Umfrage

Die Anaesthesiologie - Phantomschmerzen haben eine hohe Prävalenz nach Majoramputationen und sind mit einer zusätzlichen Einschränkung der Lebensqualität verbunden....     

Patient Blood Management in der Geburtsvorbereitung,Geburtshilfe und postpartalen Phase

Die Anaesthesiologie - Die Implementierung eines Patient Blood Management (PBM) wird zunehmender Standard in der operativen Medizin. Seit einiger Zeit gilt das Interesse auch den vulnerablen...     

Adherence to Chronic Kidney Disease Screening Guidelines Among Patients With Type 2 Diabetes in a US Administrative Claims Database

ObjectiveTo examine the screening rates for kidney damage and function among patients with type 2 diabetes (T2D) and chronic kidney disease stage at diabetes diagnosis using a US administrative claims database.Patients and MethodsThis cohort study used a claims database enriched with laboratory results data. Patients with T2D (defined as 1 inpatient or 2 outpatient claims for diabetes), aged 18 years or older, and with at least 1 year of follow-up enrollment were identified. Patients with type 1 diabetes, kidney disease, or other related conditions at baseline were excluded. We estimated screening rates using laboratory orders for serum creatinine and estimated glomerular filtration rate (eGFR) measurement and urine albumin to creatinine ratio (UACR). Chronic kidney disease severity was reported using the Kidney Disease: Improving Global Outcomes classification based on laboratory results.ResultsA total of 1,881,447 patients with T2D were eligible for analysis. Mean ± SD age was 63.1±13.1 years; 947,150 patients (50.3%) were male. Serum creatinine tests were ordered within 14 days of the index date among 290,722 patients of 622,915 (46.7%) patients with newly-recognized T2D. Overall, 1,595,964 patients (84.8%) had at least one serum creatinine test ordered during the 1-year follow-up period. Fewer patients received a UACR test during follow-up (814,897 [43.3%]). Less than half of all patients with T2D received a laboratory test order for both serum creatinine and urine albumin measurements during the follow-up period.ConclusionPhysicians treating patients with diabetes are selectively adhering to chronic kidney disease screening guidelines, as indicated by high rates of eGFR testing, but less frequent UACR testing. Despite recommendations to monitor both eGFR and UACR, less than half of patients were screened for albuminuria during the 1-year follow-up.     

The potential public health and economic value of a hypothetical COVID-19 vaccine in the United States: Use of cost-effectiveness modeling to inform vaccination prioritization

BackgroundResearchers are working at unprecedented speed to develop a SARS-CoV-2 vaccine. We aimed to assess the value of a hypothetical vaccine and its potential public health impact when prioritization is required due to supply constraints.MethodsA Markov cohort model was used to estimate COVID-19 related direct medical costs and deaths in the United States (US), with and without implementation of a 60% efficacious vaccine. To prioritize the vaccine under constrained supply, the population was divided into tiers based on age; risk and age; and occupation and age; and outcomes were compared across one year under various supply assumptions. The incremental cost per quality-adjusted life-year (QALY) gained versus no vaccine was calculated for the entire adult population and for each tier in the three prioritization schemes.ResultsThe incremental cost per QALY gained for the US adult population was $8,200 versus no vaccination. For the tiers at highest risk of complications from COVID-19, such as those ages 65 years and older, vaccination was cost-saving compared to no vaccination. The cost per QALY gained increased to over $94,000 for those with a low risk of hospitalization and death following infection. Results were most sensitive to infection incidence, vaccine price, the cost of treating COVID-19, and vaccine efficacy. Under the most optimistic supply scenario, the hypothetical vaccine may prevent 31% of expected deaths. As supply becomes more constrained, only 23% of deaths may be prevented. In lower supply scenarios, prioritization becomes more important to maximize the number of deaths prevented.ConclusionsA COVID-19 vaccine is predicted to be good value for money (cost per QALY gained <$50,000). The speed at which an effective vaccine can be made available will determine how much morbidity and mortality may be prevented in the US.