In treatment of metastatic epidural spinal cord compression (MESCC), hybrid therapy, consisting of separation surgery, followed by stereotactic body radiation therapy, has become the mainstay of ...treatment for radioresistant pathologies, such as non-small-cell lung cancer (NSCLC).
To evaluate clinical outcomes of MESCC secondary to NSCLC treated with hybrid therapy and to identify clinical and molecular prognostic predictors.
This is a single-center, retrospective study. Adult patients (≥18 years old) with pathologically confirmed NSCLC and spinal metastasis who were treated with hybrid therapy for high-grade MESCC or nerve root compression from 2012 to 2019 are included. Outcome variables evaluated included overall survival (OS) and progression-free survival, local tumor control in the competing risks setting, surgical and radiation complications, and clinical-genomic correlations.
One hundred and three patients met inclusion criteria. The median OS for this cohort was 6.5 months, with progression of disease noted in 5 (5%) patients at the index tumor level requiring reoperation and/or reirradiation at a mean of 802 days after postoperative stereotactic body radiation therapy. The 2-year local control rate was 94.6% (95% CI: 89.8-99.3). Epidermal growth factor receptor (EGFR) treatment-naïve patients who initiated EGFR-targeted therapy after hybrid therapy had significantly longer OS (hazard ratio 0.47, 95% CI 0.23-0.95, P = .04) even after adjusting for smoking status. The presence of EGFR exon 21 mutation was predictive of improved progression-free survival.
Hybrid therapy in NSCLC resulted in 95% local control at 2 years after surgery. EGFR treatment-naïve patients initiating therapy after hybrid therapy had significantly improved survival advantage. EGFR-targeted therapy initiated before hybrid therapy did not confer survival benefit.
Data envelopment analysis (DEA) is a methodology for measuring the relative efficiencies of a set of decision making units (DMUs) that use multiple inputs to produce multiple outputs. Crisp input and ...output data are fundamentally indispensable in conventional DEA. However, the observed values of the input and output data in real-world problems are sometimes imprecise or vague. Many researchers have proposed various fuzzy methods for dealing with the imprecise and ambiguous data in DEA. In this study, we provide a taxonomy and review of the fuzzy DEA methods. We present a classification scheme with four primary categories, namely, the tolerance approach, the α-level based approach, the fuzzy ranking approach and the possibility approach. We discuss each classification scheme and group the fuzzy DEA papers published in the literature over the past 20 years. To the best of our knowledge, this paper appears to be the only review and complete source of references on fuzzy DEA.
Total hip arthroplasty (THA) has become one of the most reliable and patient-requested surgical interventions in all medicine. The procedure can be performed using a variety of surgical approaches, ...but the posterior approach, direct lateral approach, and direct anterior approach are by far the most common across the globe. This article highlights the history and technique for each of these common approaches. A review of outcomes and complications for each approach are also provided. Each approach has its own unique advantages and disadvantages, but all can be safely and successful utilized for THA. Strong, convincing, high-quality studies comparing the different approaches are lacking at this time. Surgeons are therefore recommended to choose whichever approach they are most comfortable and experienced using. Though not described here, THA can also be done using the anterolateral approach (also known as the Watson Jones approach) as well as the two-incision approach. In addition, recently, some surgeons are utilizing the so-called direct superior approach for THA. While these approaches are far less commonly utilized, they are recognized as viable alternatives to traditional approaches.
There are several landmarks to safely identify the limits of the retrosigmoid approach and its intradural variations; however, there has been little discussion about how those landmarks may vary ...among patients.
Patient positions; surface landmarks for the retrosigmoid craniotomy; and structures to recognize for transmeatal, suprameatal, suprajugular, and transtentorial extensions were reviewed.
The position of the dural sinuses in relation to the zygomatic-inion line and digastric notch line is readily identified on magnetic resonance imaging. For transmeatal drilling, the position of the semicircular canals, vestibular aqueduct, and jugular bulb is best evaluated on computed tomography. For suprameatal drilling, the labyrinth and the position and integrity of the carotid canal are relevant for planning the anterior extension of the approach. For transtentorial extension, it is desirable to identify incisural structures. For suprajugular drilling, the position of the jugular bulb, invasion of venous structures, and integrity of the roof of the jugular foramen must be checked preoperatively.
The retrosigmoid approach is the workhorse of posterior skull base surgery. By recognizing patient-specific variations in known landmarks, the approach may be tailored prevent complications.
The evidence‐based medicine allows the physician to evaluate the risk–benefit ratio of a treatment through setting and data. Risk‐based choices can be done by the doctor using different information. ...With the emergence of new technologies, a large amount of data is recorded offering interesting perspectives with machine learning for predictive data analytics. Machine learning is an ensemble of methods that process data to model a learning problem. Supervised machine learning algorithms consist in using annotated data to construct the model. This category allows to solve prediction data analytics problems. In this paper, we detail the use of supervised machine learning algorithms for predictive data analytics problems in medicine. In the medical field, data can be split into two categories: medical images and other data. For brevity, our review deals with any kind of medical data excluding images. In this article, we offer a discussion around four supervised machine learning approaches: information‐based, similarity‐based, probability‐based and error‐based approaches. Each method is illustrated with detailed cardiovascular and nuclear medicine examples. Our review shows that model ensemble (ME) and support vector machine (SVM) methods are the most popular. SVM, ME and artificial neural networks often lead to better results than those given by other algorithms. In the coming years, more studies, more data, more tools and more methods will, for sure, be proposed.
This review details the use of supervised machine learning algorithms for predictive data analytics problems in medicine. Machine learning algorithms were split into four approaches: information‐based, similarity‐based, error‐based, and probability‐based approaches.
The ever increasing size of wind turbines and the move to build them offshore have accelerated the need for optimised maintenance strategies in order to reduce operating costs. Predictive maintenance ...requires detailed information on the condition of turbines. Due to the high costs of dedicated condition monitoring systems based on mainly vibration measurements, the use of data from the turbine supervisory control and data acquisition (SCADA) system is appealing. This review discusses recent research using SCADA data for failure detection and condition monitoring (CM), focussing on approaches which have already proved their ability to detect anomalies in data from real turbines. Approaches are categorised as (i) trending, (ii) clustering, (iii) normal behaviour modelling, (iv) damage modelling and (v) assessment of alarms and expert systems. Potential for future research on the use of SCADA data for advanced turbine CM is discussed.
Several misconceptions about the design‐based approach for sampling and statistical inference, based on classical sampling theory, seem to be quite persistent. These misconceptions are the result of ...confusion about basic statistical concepts such as independence, expectation, and bias and variance of estimators or predictors. These concepts have a different meaning in the design‐based and model‐based approach, because they consider different sources of randomness. Also, a population mean is still often confused with a model mean, and a population variance with a model‐variance, leading to invalid formulas for the variance of an estimator of the population mean. In this paper the fundamental differences between these two approaches are illustrated with simulations, so that hopefully more pedometricians get a better understanding of this subject. An overview is presented of how in the design‐based approach we can make use of knowledge of the spatial structure of the study variable. In the second part, new developments in both the design‐based and model‐based approach are described that try to combine the strengths of the two approaches.
Highlights
Ignorance of fundamental differences between design‐based and model‐based approaches still cause errors in statistical inference.
Basic statistical concepts such as independence, variance and bias of an estimator have a different meaning in the two approaches.
In estimating and testing it is important to distinguish population parameters from model parameters.
Hybrid methods that combine the strengths of the two approaches are reviewed.
Pilon or tibial plafond fractures usually result from high-energy injuries with rotation and/or axial compression. They occur in an area of relatively poor soft tissue coverage and frequently present ...a surgical challenge in deciding which incisions will be best for performing open reduction internal fixation. A variety of anterior and posterior approaches have been described based on the ease of fracture reduction and internal fixation with plates. Some of the incisions are fracture specific, that is, planned for a limited approach to the pilon. But in more complex cases, a wider exposure is indicated and thus more extensile approaches, both anterior and posterior, can be valuable. This review article will describe the different surgical approaches, focusing on their indication and technique.
With the reformation of Ukrainian criminal procedural legislation and the conviction of individual scholars in the necessity of applying a methodological approach to scientific research, new ideas on ...the nature and procedure of criminal procedural evidence have started to emerge in the domestic scientific literature. The purpose of the paper is to distinguish scientific concepts to criminal procedural proof and substantiation of the expediency of isolation and use of the complex and systemic approach. This study of criminal procedural proof was performed using a methodological approach, the essence of which is to change the attention of the researcher from the object as such to the means and methods of their own thought. The application of an activity-based methodological approach in scientific research allows us to further develop other conceptual ideas about criminal procedural proof, which will contribute to a deeper and more complete study of this legal phenomenon.
Correlated binary data arise in many ophthalmological and otolaryngological clinical trials. To test the homogeneity of prevalences among different groups is an important issue when conducting these ...trials. The equal correlation coefficients model proposed by Donner in 1989 is a popular model handling correlated binary data. The asymptotic chi-square test works well when the sample size is large. However, it would fail to maintain the type I error rate when the sample size is relatively small. In this paper, we propose several exact methods to deal with small sample scenarios. Their performances are compared with respect to type I error rate and power. The 'M approach' and the 'E + M approach' seem to outperform the others. A real work example is given to further explain how these approaches work. Finally, the computational efficiency of the exact methods is discussed as a pressing issue of future work.
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