Is age an additional factor in the treatment of elderly patients with glioblastoma? A new stratification model: an Italian Multicenter Study.

OBJECTIVE: Approximately half of glioblastoma (GBM) cases develop in geriatric patients, and this trend is destined to increase with the aging of the population. The optimal strategy for management of GBM in elderly patients remains controversial. The aim of this study was to assess the role of surgery in the elderly (≥ 65 years old) based on clinical, molecular, and imaging data routinely available in neurosurgical departments and to assess a prognostic survival score that could be helpful in stratifying the prognosis for elderly GBM patients. METHODS: Clinical, radiological, surgical, and molecular data were retrospectively analyzed in 322 patients with GBM from 9 neurosurgical centers. Univariate and multivariate analyses were performed to identify predictors of survival. A random forest approach (classification and regression tree [CART] analysis) was utilized to create the prognostic survival score. RESULTS: Survival analysis showed that overall survival (OS) was influenced by age as a continuous variable (p = 0.018), MGMT (p = 0.012), extent of resection (EOR; p = 0.002), and preoperative tumor growth pattern (evaluated with the preoperative T1/T2 MRI index; p = 0.002). CART analysis was used to create the prognostic survival score, forming six different survival groups on the basis of tumor volumetric, surgical, and molecular features. Terminal nodes with similar hazard ratios were grouped together to form a final diagram composed of five classes with different OSs (p < 0.0001). EOR was the most robust influencing factor in the algorithm hierarchy, while age appeared at the third node of the CART algorithm. The ability of the prognostic survival score to predict death was determined by a Harrell's c-index of 0.75 (95% CI 0.76-0.81). CONCLUSIONS: The CART algorithm provided a promising, thorough, and new clinical prognostic survival score for elderly surgical patients with GBM. The prognostic survival score can be useful to stratify survival risk in elderly GBM patients with different surgical, radiological, and molecular profiles, thus assisting physicians in daily clinical management. The preliminary model, however, requires validation with future prospective investigations. Practical recommendations for clinicians/surgeons would strengthen the quality of the study; e.g., surgery can be considered as a first therapeutic option in the workflow of elderly patients with GBM, especially when the preoperative estimated EOR is greater than 80%.

Trees, Coral, and Seaweed: An Interpretation of Sketches Found in Darwin's Papers.

The sole diagram in On the Origin of Species is generally considered to be merely an illustration of Darwin's ideas, but such an interpretation ignores the fact that Darwin himself expressly stated that the diagram helped him to discover and express his ideas. This article demonstrates that developing the so-called "tree diagram" substantially aided Darwin's heuristics. This demonstration is based on an interpretation of the diagram and of 17 sketches found in Darwin's scientific papers. The key to this interpretation is the meaning that Darwin assigned to the graphic elements (points, lines, and spaces) he used to construct the preliminary sketches and the diagram. I argue that each of the sketches contributed to the shaping of Darwin's ideas and that, in their succession, each added new elements that ultimately resulted in the fully developed published diagram.

An Eye-Tracking Study of Statistical Reasoning With Tree Diagrams and 2 × 2 Tables.

Changing the information format from probabilities into frequencies as well as employing appropriate visualizations such as tree diagrams or 2 × 2 tables are important tools that can facilitate people's statistical reasoning. Previous studies have shown that despite their widespread use in statistical textbooks, both of those visualization types are only of restricted help when they are provided with probabilities, but that they can foster insight when presented with frequencies instead. In the present study, we attempt to replicate this effect and also examine, by the method of eye tracking, why probabilistic 2 × 2 tables and tree diagrams do not facilitate reasoning with regard to Bayesian inferences (i.e., determining what errors occur and whether they can be explained by scan paths), and why the same visualizations are of great help to an individual when they are combined with frequencies. All ten inferences of N = 24 participants were based solely on tree diagrams or 2 × 2 tables that presented either the famous "mammography context" or an "economics context" (without additional textual wording). We first asked participants for marginal, conjoint, and (non-inverted) conditional probabilities (or frequencies), followed by related Bayesian tasks. While solution rates were higher for natural frequency questions as compared to probability versions, eye-tracking analyses indeed yielded noticeable differences regarding eye movements between correct and incorrect solutions. For instance, heat maps (aggregated scan paths) of distinct results differed remarkably, thereby making correct and faulty strategies visible in the line of theoretical classifications. Moreover, the inherent structure of 2 × 2 tables seems to help participants avoid certain Bayesian mistakes (e.g., "Fisherian" error) while tree diagrams seem to help steer them away from others (e.g., "joint occurrence"). We will discuss resulting educational consequences at the end of the paper.

Why Can Only 24% Solve Bayesian Reasoning Problems in Natural Frequencies: Frequency Phobia in Spite of Probability Blindness.

For more than 20 years, research has proven the beneficial effect of natural frequencies when it comes to solving Bayesian reasoning tasks (Gigerenzer and Hoffrage, 1995). In a recent meta-analysis, McDowell and Jacobs (2017) showed that presenting a task in natural frequency format increases performance rates to 24% compared to only 4% when the same task is presented in probability format. Nevertheless, on average three quarters of participants in their meta-analysis failed to obtain the correct solution for such a task in frequency format. In this paper, we present an empirical study on what participants typically do wrong when confronted with natural frequencies. We found that many of them did not actually use natural frequencies for their calculations, but translated them back into complicated probabilities instead. This switch from the intuitive presentation format to a less intuitive calculation format will be discussed within the framework of psychological theories (e.g., the Einstellung effect).

Breed comparison for heat adaptation in rams using multivariate analysis / Comparação entre raças para adaptação ao calor em carneiros usando análise multivariada

In this study, a multivariate analysis of morphological and physiological characteristics was performed on clinically healthy rams from six breeds (Santa Ines, Bergamasca, Dorper, Texel, Ile de France and Hampshire Down) to determine if these characteristics were able to separate and determine the most important variables in the differentiation of breeds for heat adaptation. To characterize the thermal environment, mean temperature was 23°C and relative humidity ranged between 30.6-55.6%. Morphological and physiological data were subjected to multivariate statistical tests including principal components (PRINCOMP), clustering (CLUSTER), discriminant (DISCRIM), step-bystep (STEPDISC) and canonical (CANDISC) analyses, using the Statistical Analysis System (SAS®). A multiple analysis of variance (MANOVA) was carried out with the variables defined as important by the discriminant analysis. The principal components analysis for biometric characteristics and scrotum-testicle, for physiological characteristics and body temperature as well as the characteristics of the skin and hair explained 60, 70 and 67 % of the total variation, respectively. The dendrogram showed a clear separation between the breeds studied and the existence of two distinct groups, one formed by the Texel and the other by the other breeds, considering all the characteristics used in the study. The most useful morphological parameters to explain heat tolerance were diameter of hair, layer thickness of hair at withers, 12th thoracic vertebra and rump, withers height, thoracic and scrotal circumferences, body weight, anterior and posterior shin perimeters, hair and epidermis brightness as well as the content of red and yellow in the epidermis. Among physiological characteristics, respiratory rate was better than rectal temperature and heart rate to explain changes caused by thermal stress. From the multivariate and variance analyzes it can be concluded that the Santa Ines breed was the most tolerant to heat stress as it presented a highly pigmented epidermis, a shorter hair of larger diameter, the lower layer thickness of hair at withers, 12th thoracic vertebra and rump, the lower temperatures in the testicle and at the 12th thoracic vertebra as well as the lower respiratory rate and rectal temperature value.

Neste estudo, foram realizadas análises multivariadas das características fisiológicas e morfológicas em carneiros clinicamente saudáveis de seis raças (Santa Inês, Bergamácia, Dorper, Texel, Ile de France e Hampshire Down) para determinar se essas características foram capazes de separar as raças e determinar as variáveis mais importantes na diferenciação das raças na adaptação ao calor. Os dados foram submetidos a testes estatísticos multivariados, incluindo as análises de componentes principais (PINCOMP), agrupamento (CLUSTER), discriminante (DISCRIM), step-by-step (STEPDISC) e canônica (CANDISC), utilizando o pacote estatístico SAS®. A análise variância de múltipla (MANOVA) foi realizada com as variáveis definidas como importante pela análise discriminante. A análise dos componentes principais para características biométricas e escroto-testiculares, para as características fisiológicas e de temperatura corporal e para as características da pele e pelo explicaram 60, 70 e 67% da variação total, respectivamente. O dendrograma mostrou uma clara separação entre as raças estudadas e a existência de dois grupos distintos, um formado pela raça Texel e o outro pelas raças Dorper, Hampshire Down, Ile de France, Santa Inês e Bergamácia, considerando todas as características avaliadas. As características morfológicas mais importantes para explicar a tolerância ao calor foram o diâmetro do pelo, as espessuras das camadas de pelo na cernelha, na décima segunda vértebra torácica e na garupa, a altura da cernelha, as circunferências torácica e escrotal, o peso corporal, os perímetros das canelas anterior e posterior, as luminosidades da pele e do pelo, bem como os teores de pigmentação vermelho e amarelo na epiderme. Entre as características fisiológicas a frequência respiratória foi melhor que a temperatura retal e a frequência cardíaca para explicar as mudanças causadas pelo estresse térmico. A partir das análises multivariada e de variância pode-se concluir que a raça Santa Inês foi a mais tolerante ao estresse térmico, uma vez que apresentou epiderme altamente pigmentada, pelo mais curto e de diâmetro maior, menores espessuras das camadas de pelo na cernelha, na décima segunda vértebra torácica e na garupa, menores temperaturas no testículo e na décima segunda vértebra torácica, bem como as menores frequência respiratória e temperatura retal.

The Impact of Visualizing Nested Sets. An Empirical Study on Tree Diagrams and Unit Squares.

It is an ongoing debate, what properties of visualizations increase people's performance when solving Bayesian reasoning tasks. In the discussion of the properties of two visualizations, i.e., the tree diagram and the unit square, we emphasize how both visualizations make relevant subset relations transparent. Actually, the unit square with natural frequencies reveals the subset relation that is essential for the Bayes' rule in a numerical and geometrical way whereas the tree diagram with natural frequencies does it only in a numerical way. Accordingly, in a first experiment with 148 university students, the unit square outperformed the tree diagram when referring to the students' ability to quantify the subset relation that must be applied in Bayes' rule. As hypothesized, in a second experiment with 143 students, the unit square was significantly more effective when the students' performance in tasks based on Bayes' rule was regarded. Our results could inform the debate referring to Bayesian reasoning since we found that the graphical transparency of nested sets could explain these visualizations' effect.

Using tree diagrams without numerical values in addition to relative numbers improves students' numeracy skills: a randomized study in medical education.

BACKGROUND: Physicians and medical students may lack sufficient numeracy skills to make treatment decisions, interpret test results, and practice evidence-based medicine. We evaluated whether the use of a tree diagram without numerical values as an aid for numerical processing might improve students' test results when dealing with percentages. METHODS: A prospective randomized study was carried out with 102 third-year students. Participants received 3 diagnostic test problems and were asked to determine positive predictive values. The information in these tests was expressed either in (1) natural frequencies, (2) conditional probabilities, or (3) conditional probabilities with a tree diagram without numbers. RESULTS: Ninety-eight (96.1%) complete data sets could be obtained. The group working with natural frequencies achieved significantly higher test results (n = 29, mean score: 1.1, P = 0.045) than the group working with conditional probabilities (n = 34, mean score: 0.56). The students who were given a tree diagram in addition to conditional probabilities (n = 35, mean score: 1.26) also achieved significantly better scores than the group with conditional probabilities alone (P = 0.008). The difference between the group who had received natural frequencies and the group working with conditional probabilities and the tree diagram was not significant. CONCLUSIONS: We suggest the use of a tree diagram as a visual aid when dealing with diagnostic tests expressed in conditional probabilities.