623 research outputs found
Patterns and frequency of recurrences of squamous cell carcinoma of the vulva
Get PDFJorien M. Woolderink, Geertruida H. de Bock, Joanne A. de Hullu, Margaret J. Davy, Ate G.J. van der Zee, Marian J.E. Mourit
Additional file 3: of Digital breast tomosynthesis for breast cancer screening and diagnosis in women with dense breasts â a systematic review and meta-analysis
Get PDFSubgroup analysis - Recall rate of DBT and DM in screening studies using two study groups by outcome definition. (DOCX 30 kb
"Timed Up & Go": a screening tool for predicting 30-day morbidity in onco-geriatric surgical patients? A multicenter cohort study.
Get PDFTo determine the predictive value of the "Timed Up & Go" (TUG), a validated assessment tool, on a prospective cohort study and to compare these findings to the ASA classification, an instrument commonly used for quantifying patients' physical status and anesthetic risk.In the onco-geriatric surgical population it is important to identify patients at increased risk of adverse post-operative outcome to minimize the risk of over- and under-treatment and improve outcome in this population.280 patients ≥70 years undergoing elective surgery for solid tumors were prospectively recruited. Primary endpoint was 30-day morbidity. Pre-operatively TUG was administered and ASA-classification was registered. Data were analyzed using multivariable logistic regression analyses to estimate odds ratios (OR) and 95% confidence intervals (95%-CI). Absolute risks and area under the receiver operating characteristic curves (AUC's) were calculated.180 (64.3%) patients (median age: 76) underwent major surgery. 55 (20.1%) patients experienced major complications. 50.0% of patients with high TUG and 25.6% of patients with ASA≥3 experienced major complications (absolute risks). TUG and ASA were independent predictors of the occurrence of major complications (TUG:OR 3.43; 95%-CI = 1.14-10.35. ASA1 vs. 2:OR 5.91; 95%-CI = 0.93-37.77. ASA1 vs. 3&4:OR 12.77; 95%-CI = 1.84-88.74). AUCTUG was 0.64 (95%-CI = 0.55-0.73, p = 0.001) and AUCASA was 0.59 (95%-CI = 0.51-0.67, p = 0.04).Twice as many onco-geriatric patients at risk of post-operative complications, who might benefit from pre-operative interventions, are identified using TUG than when using ASA
Comparison of analysis methods and design choices for treatment-by-period interaction in unidirectional switch designs:a simulation study
Get PDFBackground: Due to identifiability problems, statistical inference about treatment-by-period interactions has not been discussed for stepped wedge designs in the literature thus far. Unidirectional switch designs (USDs) generalize the stepped wedge designs and allow for estimation and testing of treatment-by-period interaction in its many flexible design forms. Methods: Under different forms of the USDs, we simulated binary data at both aggregated and individual levels and studied the performances of the generalized linear mixed model (GLMM) and the marginal model with generalized estimation equations (GEE) for estimating and testing treatment-by-period interactions. Results: The parallel group design had the highest power for detecting the treatment-by-period interactions. While there was no substantial difference between aggregated-level and individual-level analysis, the GLMM had better point estimates than the marginal model with GEE. Furthermore, the optimal USD for estimating the average treatment effect was not efficient for treatment-by-period interaction and the marginal model with GEE required a substantial number of clusters to yield unbiased estimates of the interaction parameters when the correlation structure is autoregressive of order 1 (AR1). On the other hand, marginal model with GEE had better coverages than GLMM under the AR1 correlation structure. Conclusion: From the designs and methods evaluated, in general, parallel group design with a GLMM is, preferred for estimation and testing of treatment-by-period interaction in a clustered randomized controlled trial for a binary outcome.</p
Outstanding negative prediction performance of solid pulmonary nodule volume AI for ultra-LDCT baseline lung cancer screening risk stratification
Get PDFOBJECTIVE: To evaluate performance of AI as a standalone reader in ultra-low-dose CT lung cancer baseline screening, and compare it to that of experienced radiologists.METHODS: 283 participants who underwent a baseline ultra-LDCT scan in Moscow Lung Cancer Screening, between February 2017-2018, and had at least one solid lung nodule, were included. Volumetric nodule measurements were performed by five experienced blinded radiologists, and independently assessed using an AI lung cancer screening prototype (AVIEW LCS, v1.0.34, Coreline Soft, Co. ltd, Seoul, Korea) to automatically detect, measure, and classify solid nodules. Discrepancies were stratified into two groups: positive-misclassification (PM); nodule classified by the reader as a NELSON-plus /EUPS-indeterminate/positive nodule, which at the reference consensus read was < 100 mm3, and negative-misclassification (NM); nodule classified as a NELSON-plus /EUPS-negative nodule, which at consensus read was ≥ 100 mm3.RESULTS: 1149 nodules with a solid-component were detected, of which 878 were classified as solid nodules. For the largest solid nodule per participant (n = 283); 61 [21.6 %; 53 PM, 8 NM] discrepancies were reported for AI as a standalone reader, compared to 43 [15.1 %; 22 PM, 21 NM], 36 [12.7 %; 25 PM, 11 NM], 29 [10.2 %; 25 PM, 4 NM], 28 [9.9 %; 6 PM, 22 NM], and 50 [17.7 %; 15 PM, 35 NM] discrepancies for readers 1, 2, 3, 4, and 5 respectively.CONCLUSION: Our results suggest that through the use of AI as an impartial reader in baseline lung cancer screening, negative-misclassification results could exceed that of four out of five experienced radiologists, and radiologists' workload could be drastically diminished by up to 86.7%.</p
Optimal unidirectional switch designs
Get PDFStepped wedge designs and delayed start designs can all be considered as special cases of the so-called unidirectional switch design. This paper provides optimal proportions of clusters that are allocated to switch patterns in a unidirectional switch design to minimize the asymptotic variance of the treatment effect estimator. This unique optimal design applies to certain cross-sectional and longitudinal variance component models. When the intraclass correlation coefficient is zero, the optimal unidirectional switch design coincides with the classic (cluster) parallel group design. The optimal unidirectional switch design is more efficient than the optimal stepped wedge design and delayed start designs. Compared with the uniform unidirectional switch design, the efficiency gain of the optimal unidirectional switch design can be substantial, but it depends on the intraclass correlation and the cluster size. We also showed that augmenting the optimal stepped wedge design with pure control pattern is more efficient than the optimal stepped wedge design. In addition, robust minimax design for unidirectional switch design, delayed start design, and stepped wedge design are provided
Community Use of Repurposed Drugs Before and During COVID-19 Pandemic in the Netherlands: An Interrupted Time-Series Analysis
No full textGuiling Zhou,1 Stijn de Vos,1 Catharina CM Schuiling-Veninga,1 Jens Bos,1 Katrien Oude Rengerink,2 Anna Maria Gerdina Pasmooij,2 Peter GM Mol,2,3 Geertruida H de Bock,4 Eelko Hak1 1Unit of Pharmaco-Therapy, -Epidemiology and -Economics (PTEE), Department of Pharmacy, University of Groningen, Groningen, the Netherlands; 2Medicines Evaluation Board, Utrecht, the Netherlands; 3Department of Clinical Pharmacy and Pharmacology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands; 4Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, the NetherlandsCorrespondence: Guiling Zhou, Unit of Pharmaco-Therapy, -Epidemiology and -Economics (PTEE), Department of Pharmacy, University of Groningen, Antonius Deusinglaan 1, Groningen, 9713 AV, the Netherlands, Tel +31 503638707, Fax +31 503632772, Email [email protected]: Repurposing registered drugs could reduce coronavirus disease (COVID-19) burden before novel drugs are authorized. Little is known about how the pandemic and imposed restrictions changed their dispensing. We aimed to investigate the impact of COVID-19 pandemic on repurposed drugs dispensing in the Netherlands.Methods: We performed interrupted time-series study using University of Groningen prescription database IADB.nl to evaluate dispensing trends of 24 repurposed drugs before (2017-February 2020) and after (March 2020– 2021) the pandemic’ start. Primary outcomes were monthly prevalence and incidence rates. An autoregressive integrated moving average model assessed the effect of pandemic and stringency index (measuring strictness of government’s restriction policies).Results: Annual number of IADB.nl population ranged from 919,697 to 952,400. Generally, dispensing of common long-term-used drugs was not significantly affected by pandemic. The prevalence of antibacterials (− 4.20 users per 1000 people), antivirals (− 0.04), corticosteroids (− 1.29), prednisolone (− 1.32), calcium channel blocker (− 0.41), and diuretics (− 1.29) was lower than expected after the pandemic’s start, while the prevalence of ivermectin (0.07), sulfonylureas (0.15), sodium-glucose co-transporter-2 (SGLT2) inhibitor (0.17), and anticoagulants (1.95) was higher than expected. The pandemic was associated with statistically significant decreases in the incidence of antibacterials (− 1.21), corticosteroids (− 0.60), prednisolone (− 0.64) and anticoagulants (− 0.02), and increases in ivermectin (0.02), aggregated antidiabetic drugs (0.13), and SGLT2 inhibitors (0.06). These trends were positively associated with pandemic and negatively associated with stringency index.Conclusion: Dispensing of most drugs was not significantly associated with pandemic and government’s response. Despite some statistically significant disruptions, these were not necessarily clinically relevant due to small absolute differences observed.Keywords: COVID-19, drug utilization, repurposed drug, stringency inde
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