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OBJECTIVES: Classifying radiologic pulmonary lesions as malignant is challenging. Scoring systems like the Mayo model lack precision in predicting the probability of malignancy. We developed the logistic scoring system 'LIONS PREY' (Lung lesION Score PREdicts malignancY), which is superior to existing models in its precision in determining the likelihood of malignancy. METHODS: We evaluated all patients that were presented to our multidisciplinary team between January 2013 and December 2020. Availability of pathological results after resection or CT-/EBUS-guided sampling was mandatory for study inclusion. Two groups were formed: Group A (malignant nodule; n = 238) and Group B (benign nodule; n = 148). Initially, 22 potential score parameters were derived from the patients' medical histories. RESULTS: After uni- and multivariate analysis, we identified the following eight parameters that were integrated into a scoring system: (1) age (Group A: 64.5 ± 10.2 years vs. Group B: 61.6 ± 13.8 years; multivariate p-value: 0.054); (2) nodule size (21.8 ± 7.5 mm vs. 18.3 ± 7.9 mm; p = 0.051); (3) spiculation (73.1% vs. 41.9%; p = 0.024); (4) solidity (84.9% vs. 62.8%; p = 0.004); (5) size dynamics (6.4 ± 7.7 mm/3 months vs. 0.2 ± 0.9 mm/3 months; p < 0.0001); (6) smoking history (92.0% vs. 43.9%; p < 0.0001); (7) pack years (35.1 ± 19.1 vs. 21.3 ± 18.8; p = 0.079); and (8) cancer history (34.9% vs. 24.3%; p = 0.052). Our model demonstrated superior precision to that of the Mayo score (p = 0.013) with an overall correct classification of 96.0%, a calibration (observed/expected-ratio) of 1.1, and a discrimination (ROC analysis) of AUC (95% CI) 0.94 (0.92-0.97). CONCLUSIONS: Focusing on essential parameters, LIONS PREY can be easily and reproducibly applied based on computed tomography (CT) scans. Multidisciplinary team members could use it to facilitate decision making. Patients may find it easier to consent to surgery knowing the likelihood of pulmonary malignancy. The LIONS PREY app is available for free on Android and iOS devices.
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The National Reference Center (NRC) for hepatitis B viruses (HBV) and hepatitis D viruses (HDV) has been located at the Institute of Medical Virology of the Justus Liebig University (JLU) in Giessen, Germany, since its establishment in 2011. This paper describes the NRC's areas of activity and related experience.The NRC offers comprehensive consulting services on all diagnostic and clinical aspects of acute and chronic HBV and HDV infections for the Public Health Service (ÖGD), diagnostic laboratories, clinics, research institutes, and physicians in private practice. Uncertain diagnostic findings can be analyzed and interpreted and epidemiological correlations clarified with the HBV/HDV special diagnostics established at the NRC using state-of-the-art molecular, biochemical, and genetic laboratory tools. The NRC has access to a strain collection of many well-characterized and cloned HBV/HDV isolates, allowing comparative analysis and evaluation of antiviral resistance mutations and immune escape variants. Together with its national and international partner institutions, the NRC initiates and supervises, among other things, interlaboratory studies for the diagnosis of HBV resistance and immune escape for the establishment and validation of international World Health Organization (WHO) standards and for the improvement of quantitative HDV genome determination. The NRC actively participates in current recommendations and guidelines on HBV and HDV and the recommendations of medical societies. It also highlights current HBV/HDV-relevant aspects with contributions in the form of national and international lectures as well as original articles and comments in national and international journals.
Assuntos
Hepatite B , Hepatite D , Alemanha , Hepatite B/diagnóstico , Hepatite B/epidemiologia , Vírus da Hepatite B , Hepatite D/diagnóstico , Hepatite D/epidemiologia , Vírus Delta da Hepatite/genética , HumanosRESUMO
BACKGROUND & AIMS: Currently available HDV PCR assays are characterized by considerable run-to-run and inter-laboratory variability. Hence, we established a quantitative reverse transcription real-time PCR (RT-qPCR) assay on the open channel of a fully automated PCR platform (cobas6800, Roche) offering improved consistency and reliability. METHODS: A primer/probe-set targeting a highly conserved region upstream of the HDV antigen was adapted for use on the cobas6800. The lower limit of detection (LLOD) was determined using a dilution panel of the HDV WHO standard (n = 21/dilution). Linearity and inclusivity were tested by preparing 10-fold dilution series of cell culture-derived virus (genotype [GT]1-8; n = 5/dilution). Patient samples containing a variety of bloodborne viral pathogens were tested to confirm exclusivity (n = 60). RESULTS: The LLOD of the HDV utility-channel (HDV_UTC) assay was determined as 3.86 IU/ml (95% CI 2.95-5.05 IU/ml) with a linear range from 10-10Ë8 IU/ml (GT1). Linear relationships were observed for all HDV GTs with slopes ranging from -3.481 to -4.134 cycles/log and R2 from 0.918 to 0.994. Inter-run and intra-run variability were 0.3 and 0.6 Ct (3xLLOD), respectively. No false-positive results were observed. To evaluate clinical performance, 110 serum samples of anti-HDV-Ab+ patients were analyzed using the HDV_UTC and CE-IVD RoboGene assays. 58/110 and 49/110 samples were concordant positive or negative, respectively (overall agreement 97.3%). Quantitative comparison demonstrated a strong correlation (R2 0.8733; 95% CI 0.8914-0.9609; p value <0.0001). CONCLUSION: The use of highly automated, sample-to-result solutions for molecular diagnostics holds many inherent benefits over manual workflows, including improved reliability, reproducibility and dynamic scaling of testing capacity. The assay we established showed excellent analytical and clinical performance, with inclusivity for all HDV GTs and a limit of quantification of 10 IU/ml, making it a sensitive new tool for HDV screening and viral load monitoring. LAY SUMMARY: The hepatitis delta virus (HDV) causes a severe form of inflammation in the liver. We developed a tool for molecular diagnostics, a polymerase chain reaction HDV assay that showed great performance. It can be used to improve diagnosis of HDV, as well as for monitoring treatment responses. The assay allows for quantification of the virus in the tested samples and is performed on a fully automated platform (cobas6800), which provides various benefits including less hands-on time and excellent comparability of test results.