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Track: Track 3
Non Clinical Statistics I
Chairs: Hannes-Friedrich Ulbrich and Frank Konietschke
Can statistics save preclinical research?
Ulrich Dirnagl
Charité / Berlin Institute of Health, Deutschland
IDENTIFYING OPTIMIZED DECISION CRITERIA AND EXPERIMENTAL DESIGNS BY SIMULATING PRECLINICAL EXPERIMENTS IN SILICO
Meggie Danziger1,2, Ulrich Dirnagl1,2, Ulf Toelch2
1Charité – Universitätsmedizin Berlin, Germany; 2BIH QUEST Center for Transforming Biomedical Research
Low statistical power in preclinical experiments has been repeatedly pointed out as a roadblock to successful replication and translation. To increase reproducibility of preclinical experiments under ethical and budget constraints, it is necessary to devise strategies that improve the efficiency of confirmatory studies.
To this end, we simulate two preclinical research trajectories from the exploratory stage to the results of a within-lab replication study based on empirical pre-study odds. In a first step, a decision is made based on exploratory data whether to continue to a replication. One trajectory (T1) employs the conventional significance threshold for this decision. The second trajectory (T2) uses a more lenient threshold based on an a priori determined smallest effect size of interest (SESOI). The sample size of a potential replication study is calculated via a standard power analysis using the initial exploratory effect size (T1) or using a SESOI (T2). The two trajectories are compared regarding the number of experiments proceeding to replication, number of animals tested, and positive predictive value (PPV).
Our simulations show that under the conventional significance threshold, only 32 percent of the initial exploratory experiments progress to the replication stage. Using the decision criterion based on a SESOI, 65 percent of initial studies proceed to replication. T1 results in the lowest number of animals needed for replication (n = 7 per group) but yields a PPV that is below pre-study odds. T2 increases PPV above pre-study odds while keeping sample size at a reasonably low number (n = 23 per group).
Our results reveal that current practice, represented by T1, impedes efforts to replicate preclinical experiments. Optimizing decision criteria and experimental design by employing easily applicable variations as shown in T2 keeps tested animal numbers low while generating more robust preclinical evidence that may ultimately benefit translation.
Information sharing across genes for improved parameter estimation in concentration-response curves
Franziska Kappenberg, Jörg Rahnenführer
TU Dortmund University, Germany
Technologies for measuring high-dimensional gene expression values for tens of thousands of genes simultaneously are well established. In toxicology, for estimating concentration-response curves, such data can be used to understand the biological processes initiated at different concentrations. Increasing the number of concentrations or the number of replicates per concentration can improve the accuracy of the fit, but causes critical additional costs. A statistical approach to obtain higher-quality fits is to exploit similarities between high-dimensional concentration-gene expression data. This idea can also be called information sharing across genes. Parameters of the concentration-response curves can be linked, according to a priori assumptions or estimates of the distributions of the parameters, in a Bayesian framework.
Here, we consider the special case of the sigmoidal 4pLL model for estimating the curves associated with single genes, and we are interested in the EC50 value of the curve, i.e. the concentration at which the half-maximal effect is reached. This value is a parameter of the 4pLL model and can be considered a reasonable indicator for a relevant expression effect of the corresponding gene. We introduce an empirical Bayes method for information sharing across genes in this situation, by modelling the distribution of the EC50 values across all genes. Based on this distribution, for each gene a weighted mean of the individually estimated parameter and the overall mean of the estimated parameters of all genes is calculated. In other words, parameters are shrunk towards an overall mean. We evaluate our approach using several simulation studies that differ with respect to their degree of assumptions made for the distribution of the EC50 values. Finally, the method is also applied to a real gene expression dataset to demonstrate the influence of the analysis strategy on the results.
An intuitive time-dose-response model for cytotoxicity data with varying exposure times
Julia Christin Duda, Jörg Rahnenführer
Modeling approaches for dose-response or concentration-response analyses are slowly becoming more popular in toxicological applications. For cytotoxicity assays, not only the concentration but also the exposure or incubation time of the compound administered to cells can be varied and might have influence on the response. A popular concentration-response model is the four-parameter log-logistic (4pLL) or, more specific and tailored to cytotoxicity data, the two-parameter log-logistic (2pLL) model. Both models, however, model the response based on the concentration only.
We propose a two-step procedure and a new time-concentration-response model for cytotoxicity data in which both concentration and exposure time are varied. The parameter of interest for the estimation is the EC50 value, i.e. the concentration at which half of the maximal effect is reached. The procedure consists of a testing step and a modeling step. In the testing step, a nested ANOVA test is performed to decide if the exposure time has an effect on the shape of the concentration-response curve. If no effect is identified then a classical 2pLL model is fitted. Otherwise, a new time-concentration-response model called td2pLL is fitted. In this model, we incorporate exposure time information into the 2pLL model by making the EC50 parameter dependent on the exposure time.
In simulation studies inspired by and based on a real data set, we compare the proposed procedure against various alternatives with respect to the precision of the estimation of the EC50 value. In all simulations, the new procedure provides estimates with higher or comparable precision, which demonstrates its universal applicability in corresponding toxicological experiments. In addition, we show that the use of optimal designs for cytotoxicity experiments further improves the EC50 estimates throughout all considered scenarios while reducing numerical problems. In order to facilitate the application in toxicological practice, the developed methods will be made available to practitioners via the R package td2pLL and a corresponding vignette that demonstrates the application on an example dataset.
Nonparametric Statistics and Multivariate Analysis
Chairs: Frank Konietschke and Markus Pauly
Marginalized Frailty-Based Illness-Death Model: Application to the UK-Biobank Survival Data
Malka Gorfine
The UK Biobank is a large-scale health resource comprising genetic, environmental, and medical information on approximately 500,000 volunteer participants in the United Kingdom, recruited at ages 40–69 during the years 2006–2010. The project monitors the health and well-being of its participants. This work demonstrates how these data can be used to yield the building blocks for an interpretable risk-prediction model, in a semiparametric fashion, based on known genetic and environmental risk factors of various chronic diseases, such as colorectal cancer. An illness-death model is adopted, which inherently is a semi-competing risks model, since death can censor the disease, but not vice versa. Using a shared-frailty approach to account for the dependence between time to disease diagnosis and time to death, we provide a new illness-death model that assumes Cox models for the marginal hazard functions. The recruitment procedure used in this study introduces delayed entry to the data. An additional challenge arising from the recruitment procedure is that information coming from both prevalent and incident cases must be aggregated. Lastly, we do not observe any deaths prior to the minimal recruitment age, 40. In this work, we provide an estimation procedure for our new illness-death model that overcomes all the above challenges.
Distribution-free estimation of the partial AUC in diagnostic studies
Maximilian Wechsung
Charité – Universitätsmedizin Berlin, Germany
The problem of partial area under the curve (pAUC) estimation arises in diagnostic studies in which not the whole receiver operating characteristic (ROC) curve of a diagnostic test with continuous outcome can be evaluated. Typically, the investigator is bound by economical as well as ethical considerations to analyze only that part of the ROC curve which includes true positive rates and false positive rates above and below certain thresholds, respectively. The pAUC is the area under this partial ROC curve. It can be used to evaluate the performance of a diagnostic test with continuous outcome. In our talk, we consider a distribution-free estimator of the pAUC and establish its asymptotic distribution. The results can be used to construct statistical tests to compare the performance of different diagnostic tests.
Ranking Procedures for the Factorial Repeated Measures Design with Missing Data – Estimation, Testing and Asymptotic Theory
Kerstin Rubarth, Frank Konietschke
Charité Berlin, Germany
A commonly used design in health, medical and biomedical research is the repeated measures design. Often, a parametric model is used for the analysis of such data. However, if sample size is rather small or if data is skewed or is on an ordinal scale, a nonparametric approach would fit the data better than a classic parametric approach, e.g. linear mixed models. Another issue, that naturally arises when dealing with clinical or pre-clinical data, is the occurrence of missing data. Most methods can only use a complete data set, if no imputation technique is applied. The newly developed ranking procedure is a flexible method for general non-normal, ordinal, ordered categorical and even binary data and uses in case of missing data all available information instead of only the information obtained from complete cases. The hypotheses are defined in terms of the nonparametric relative effect and can be tested by using quadratic test procedures as well as the multiple contrast test procedure. Additionally, the framework allows for the incorporation of clustered data within the repeated measurements. An example for clustered data are animal studies, where several animals share the same cage and are therefore clustered within a cage. Simulation studies indicate a good performance in terms of the type-I error rate and the power under different alternatives with a missing rate up to 30%, also under non-normal data. A real data example illustrates the application of the proposed methodology.
A cautionary tale on using imputation methods for inference in a matched pairs design.
Burim Ramosaj, Lubna Amro, Markus Pauly
Imputation procedures in biomedical fields have turned into statistical practice, since further analyses can be conducted ignoring the former presence of missing values. In particular, non-parametric imputationschemes like the random forest or a combination with the stochastic gradient boosting have shown favorable imputation performance compared to the more traditionally used MICE procedure. However, their effect on valid statistical inference has not been analyzed so far. This gap is closed by investigating their validity for inferring mean differences in incompletely observed pairs while opposing them to a recent approach that only works with the given observations at hand. Our findings indicate that machine learning schemes for (multiply) imputing missing values heavily inflate type-I-error in small to moderate matched pairs, even after modifying the test statistics using Rubin's multiple imputation rule. In addition to an extensive simulation study, an illustrative data example from a breast cancer gene study has been considered.
Chairs: Michael Altenbuchinger and Klaus Jung
AI Models for Multi-Modal Data Integration
Holger Fröhlich
Fraunhofer Gesellschaft e.V.
Precision medicine aims for the delivery of the right treatment for the right patients. One important goal is therefore to identify molecular sub-types of diseases, which opens the opportunity for a better targeted therapy of disease in the future. In that context high throughput omics data has been extensively used. However, analysis of one type of omics data alone provides only a very limited view on a complex and systemic disease such as cancer. Correspondingly, parallel analysis of multiple omics data types is needed and employed more and more routinely. However, leveraging the full potential of multi-omics data requires statistical data fusion, which comes along with a number of unique challenges, including differences in data types (e.g. numerical vs discrete), scale, data quality and dimension (e.g. hundreds of thousands of SNPs vs few hundred miRNAs).
In the first part of my talk I will focus on Pathway based Multi-modal AutoEncoders (PathME) as one possible approach for multi-omics data integration. PathME relies on a multi-modal sparse denoising autoencoder architecture to embed multiple omics types that can be mapped to the same biological pathway. We show that sparse non-negative matrix factorization applied to such embeddings result into well discriminated disease subtypes in several cancer types, which show clinically distinct features. Moreover, each of these subtypes can be associated to subtype-specific pathways, and for each of these pathways it is possible to disentangle the influence of individual omics features, hence providing a rich interpretation.
Going one step further in the second part of my talk I will focus on Variational Autoencoder Modular Bayesian Networks (VAMBN) as merger of Bayesian Networks and Variational Autoencoders to model multiple data modalities (including clinical assessment scores), also in a longitudinal manner. I will specifically demonstrate the application of VAMBN for modeling entire clinical studies in Parkinson's Disease (PD). Since VAMBN is generative the model can be used to simulate synthetic patients, also under counterfactual scenarios (e.g. age shift by 20 years, modification of disease severity at baseline), which could facilitate the design of clinical studies, sharing of data under probabilistic privacy guarantees and eventually allowing for finding "patients-like-me" within a broader, virtually merged meta-cohort.
NetCoMi: Network Construction and Comparison for Microbiome Data in R
Stefanie Peschel1, Christian L. Müller2,3,4, Erika von Mutius1,5,6, Anne-Laure Boulesteix7, Martin Depner1
1Institute of Asthma and Allergy Prevention, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany; 2Department of Statistics, Ludwig-Maximilians-Universität München, Munich, Germany; 3Institute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany; 4Center for Computational Mathematics, Flatiron Institute, New York, USA; 5Dr von Hauner Children's Hospital, Ludwig-Maximilians-Universität München, Munich, Germany; 6Comprehensive Pneumology Center Munich (CPC-M), Member of the German Center for Lung Research, Munich, Germany; 7Institute for Medical Information Processing, Biometry and Epidemiology, Ludwig-Maximilians-Universität München, Munich, Germany
Network analysis methods are suitable for investigating the microbial interplay within a habitat. Since microbial associations may change between conditions, e.g. between health and disease state, comparing microbial association networks between groups might be useful. For this purpose, the two networks are constructed separately, and either the resulting associations themselves or the network's properties are compared between the two groups.
Estimating associations for sequencing data is challenging due to their special characteristics – that is, sparsity with a high number of zeros, high dimensionality, and compositionality. Several association measures taking these features into account have been published during the last decade. Furthermore, several network analysis tools, methods for comparing network properties among two or more groups as well as approaches for constructing differential networks are available in the literature. However, no unifying tool for the whole process of constructing, analyzing and comparing microbial association networks between groups is available so far.
We provide the R package "NetCoMi" implementing this whole workflow starting with a read count matrix originating from a sequencing process, to network construction, up to a statement whether single associations, local network characteristics, the determined clusters, or even the overall network structure differs between the groups. For each of the aforementioned steps, a selection of existing methods suitable for the application on microbiome data is included. Especially the function for network construction contains many different approaches including methods for treating zeros in the data, normalization, computing microbial associations, and sparsifying the resulting association matrix. NetCoMi can either be used for constructing, analyzing and visualizing a single network, or for comparing two networks in a graphical as well as a quantitative manner, including statistical tests.
We illustrate the application of our package using a real data set from GABRIELA study [1] to compare microbial associations in settled dust from children's rooms between samples from two study centers. The examples demonstrate how our proposed graphical methods uncover genera with different characteristics (e.g. a different centrality) between the groups, similarities and differences between the clusterings, as well as differences among the associations themselfes. These descriptive findings are confirmed by a quantitative output including a statement whether the results are statistically significant.
[1] Jon Genuneit, Gisela Büchele, Marco Waser, Katalin Kovacs, Anna Debinska, AndrzejBoznanski, Christine Strunz-Lehner, Elisabeth Horak, Paul Cullinan, Dick Heederik, et al.The gabriel advanced surveys: study design, participation and evaluation of bias.Paediatric and Perinatal Epidemiology, 25(5):436–447, 2011.
Evaluation of augmentation techniques for high-dimensional gene expression data for the purpose of fitting artificial neural networks
Magdalena Kircher, Jessica Krepel, Babak Saremi, Klaus Jung
University of Veterinary Medicine Hannover, Foundation, Germany
High-throughput transcriptome expression data from DNA microarrays or RNA-seq are regularly checked for their ability to classify samples. However, with further densification of transcriptomic data and a low number of observations – due to a lack of available biosamples, prohibitive costs and ethical reasons – the ratio between the number of variables and available observations is usually very large. As a consequence, classifier performance estimated from training data often tends to be overrated and little robust. It has been demonstrated in many applications that data augmentation can improve the robustness of artificial neural networks. Data augmentation on high-dimensional gene expression data has, however, been very little studied so far.
We investigate the applicability and capacity of two data augmentation approaches including generative adversarial networks (GAN), which have been widely used for augmenting image datasets. Comparison of augmentation methods is carried out in public example data sets from infection research. Besides neural networks, we evaluate the augmentation techniques on the performance of linear discriminant analysis and support vector machines.
Results and Outlook:
First results of a 10-fold cross validation show increased accuracy, sensitivity, specificity and predictive values when using augmented data sets compared to classifier models based on the original data only. A simple augmentation approach by mixed observations shows a similar performance as the computational more expensive approach with GANs. Further evaluations are currently running to better understand the detailed performance of the augmentation techniques.
Comparison of merging strategies for building machine learning models on multiple independent gene expression data sets
Jessica Krepel, Magdalena Kircher, Moritz Kohls, Klaus Jung
Microarray experiments and RNA-seq experiments allow the simultaneous collection of gene expression data from several thousand genes which can be used in a wide range of biological questions. Nowadays, there are gene expression data available in public databases for many biological and medical research questions. Oftentimes, several independent studies are performed on the same or similar research question. There are several benefits of combining these studies compared to individual analyses. Several approaches for combining independent data sets of gene expression data have been proposed already in the context of differential gene expression analysis and gene set enrichment analysis. Here, we want to compare different strategies for combining independent data sets for the purpose of classification analysis.
We only considered the two-group design, e.g. with class labels diseased and healthy. At different stages of the analysis, the information of the individual studies can be aggregated. We examined three different merging pipelines with regard to the stage of the analysis at which merging is conducted, namely the direct merging of the data sets (strategy A), the merging of the trained classification models (strategy B), and the merging of the classification results (strategy C). We combined the merging pipelines with different methods for classification, linear discriminant analysis (LDA), support vector machines (SVM), and artificial neural networks (ANN). Within each merging strategy, we performed a differential gene expression analysis for dimension reduction to select a set of genes that we then used as feature subset in the classification. We trained and evaluated the classification model on several data subsets in form of a 10-fold cross validation. We first performed a simulation study with pure artificial data, and secondly a study based on a real world data set from the public data repository ArrayExpress that we artificially split into two studies.
With respect to classification accuracy, we found that the strategy of data merging outperformed the strategy of results merging in most of our simulation scenarios with artificial data. Especially when the number of studies is high and the differentiability between the groups is low, strategy A appears as the best performing one. Strategy A performed particularly better than the other two merging approaches when four independent studies were aggregated compared to scenarios with only two independent studies.
Evaluating the quality of synthetic SNP data from deep generative models under sample size constraints
Jens Nußberger, Frederic Boesel, Stefan Lenz, Harald Binder, Moritz Hess
Universitätsklinikum Freiburg, Germany
Synthetic data such as generated by deep generative models are increasingly considered for exchanging biomedical data, such as single nucleotide polymorphism (SNP) data, under privacy constraints. This requires that the employed model did sufficiently well learn the joint distribution of the data. A major limiting factor here is the number of available empirical observations which can be used for training. Until now, there is little evidence of how well the predominant generative approaches, namely variational autoencoders (VAEs), deep Boltzmann machines (DBMs) and generative adversarial networks (GANs) learn the joint distribution of the objective data under sample size constraints. Using simulated SNP data and data from the 1000 genomes project, we here provide results from an in-depth evaluation of VAEs, DBMs and GANs. Specifically, we investigate, how well pair-wise co-occurrences of variables in the investigated SNP data, quantified as odds ratios (ORs), are recovered in the synthetic data generated by the approaches. For simulated as well as the 1000 genomes SNP data, we observe that DBMs generally can recover structure for up to 300 SNPs. However, we also observe a tendency of over-estimating ORs when the DBMs are not carefully tuned. VAEs generally get the direction and relative strength of pairwise ORs right but generally under-estimate their magnitude. GANs perform well only when larger sample sizes are employed and when there are strong pairwise associations in the data. In conclusion, DBMs are well suited for generating synthetic observations for binary omics data, such as SNP data, under sample size constraints. VAEs perform superior at smaller sample sizes but are limited with respect to learning the absolute magnitude of pairwise associations between variables. GANs require large amounts of training data and likely require a careful selection of hyperparameters.
AG-Sitzungen
Die AG-Sitzungen finden im virtuellen Konferenzgebäude statt. Die Raumbezeichnungen beziehen sich auf die freien Gather-Räume G1-G4 (siehe auch Karte des virtuellen Konferenzgebäudes).
Zeit: 14:50-15:30
Bayes-Methodik (Raum G1)
Lehre und Didaktik der Biometrie (Raum G2)
Statistische Methoden in der Epidemiologie (Raum G3)
Statistische Methoden in der Medizin (Raum G3)
Ethik und Verantwortung (Raum G1)
Landwirtschaftliches Versuchswesen (über Webex: https://bitbw.webex.com/bitbw/j.php?MTID=m6e618dfa5cc087fe3dc526fea9b9362; Meeting-Kennnummer (Zugriffscode): 181 245 7489; Meeting Passwort: uuM7pbH2gS3)
Nichtparametrische Methoden (Raum G3)
Non-Clinical Statistics (Raum G4)
Die AG-Nachwuchs hält ihre AG-Sitzung am 18.03 von 17:00-18:00 per Zoom ab. Für nähere Informationen kontaktieren Sie bitte Stefanie Peschel (stefanie.peschel@helmholtz-muenchen.de).
Survival and Event History Analysis II
Chairs: Annika Hoyer and Oliver Kuß
Assessment of methods to deal with delayed treatment effects in immunooncology trials with time-to-event endpoints
Rouven Behnisch, Johannes Krisam, Meinhard Kieser
In cancer drug research and development, immunotherapy plays an ever more important role. A common feature of immunotherapies is a delayed treatment effect which is quite challenging when dealing with time-to-event endpoints [1]. In case of time-to-event endpoints, regulatory authorities often require a log-rank test, which is the standard statistical method. The log-rank test is known to be most powerful under proportional-hazards alternatives but suffers a substantial loss in power if this assumption is violated. Hence, a rather long follow-up period is required to detect a significant effect in immunooncology trials. For that reason, the question arises whether methods exist that are more susceptible to delayed treatment effects and that can be applied early on to generate evidence anticipating the final decision of the log-rank test to reduce the trial duration without inflation of the type I error. Alternative methods include, for example, weighted log-rank statistics with weights that can either be fixed at the design stage of the trial [2] or chosen based on the observed data [3] or tests based on the restricted mean survival time [4], survival proportions, accelerated failure time (AFT) models or additive hazard models.
We evaluate and compare these different methods systematically with regard to type I error control and power in the presence of delayed treatment effects. Our simulation study includes aspects such as different censoring rates and types, different times of delay, and different failure time distributions. First results show that most methods achieve type I error rate control and that, by construction, the weighted log-rank tests which place more weight on late time points have a greater power to detect differences when the treatment effect is delayed. It is furthermore investigated whether and to what extent these methods can be applied at an early stage of the trial to predict the decision of the log-rank test later on.
[1] T. Chen (2013): Statistical issues and challenges in immuno-oncology. Journal for ImmunoTherapy of Cancer 1:18
[2] T.R. Fleming and D.P. Harrington (1991): Counting Processes and Survival Analysis. New York [u.a.]: Wiley-Interscience Publ.
[3] D. Magirr and C. Burman (2019): Modestly weighted logrank tests. Statistics in Medicine 38(20):3782-3790.
[4] P. Royston and M.K.B. Parmar (2013): Restricted mean survival time: an alternative to the hazard ratio for the design and analysis of randomized trials with a time-to-event outcome. BMC Medical Research Methodology 13(1):152.
Sampling designs for rare time-dependent exposures – A comparison of the nested exposure case-control design and exposure density sampling
Jan Feifel1, Maja von Cube2, Martin Wolkewitz2, Jan Beyersmann1, Martin Schumacher2
1Institute of Statistics, Ulm University, Germany; 2Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center University of Freiburg, Germany
Hospital-acquired infections increase both morbidity and mortality of hospitalized patients. Researchers interested in the effect of these time-dependent infections on the length-of-hospital stay, as a measure of disease burden, face large cohorts with possibly rare exposures.
For large cohort studies with rare outcomes nested case-control designs are favorable due to the efficient use of limited resources. Here, nested case-control designs apply but do not lead to reduced sample sizes, because the outcome is not necessarily rare, but the exposure is. Recently, exposure density sampling (EDS)[1] and nested exposure case-control design (NECC) [2] have been proposed to sample for a rare time-dependent exposure in cohorts with a survival endpoint. The two designs differ in the time point of sampling.
Both designs enable efficient hazard ratio estimation by sampling all exposed individuals but only a small fraction of the unexposed ones. Moreover, they account for time-dependent exposure to avoid immortal time bias. We investigate and compare their performance using data of patients hospitalized in the neuro-intensive care unit at the Burdenko Neurosurgery Institute (NSI) in Moscow, Russia. The impact of different types of hospital-acquired infections with different prevalence on length-of-stay is considered. Additionally, inflation factors, a primary performance measure, are discussed. All presented methods will be compared to the gold-standard Cox model on the full cohort. We enhance both designs to allow for a competitive analysis of combined and competing endpoints. Additionally, these designs substantially reduce the amount of necessary information compared to the full cohort approach.
Both EDS and NECC are capable of analyzing time-to-event data by simultaneously accounting for rare time-dependent exposure and result in affordable sample sizes. EDS outperforms the NECC concerning efficiency and accuracy in most considered settings for combined endpoints. For competing risks, however, a tailored NECC shows more appealing results.
[1] K. Ohneberg, J. Beyersmann and M. Schumacher (2019): Exposure density sampling: Dynamic matching with respect to a time-dependent exposure. Statistics in Medicine, 38(22):4390-4403.
[2] J. Feifel, M. Gebauer, M. Schumacher and J. Beyersmann (2020): Nested exposure case-control sampling: a sampling scheme to analyze rare time-dependent exposures. Lifetime Data Analysis, 26:21-44.
Tumour-growth models improve progression-free survival estimation in the presence of high censoring-rates
Gabriele Bleckert, Hannes Buchner
Staburo GmbH, Germany
In oncology, reliable estimates of progression-free survival (PFS) are of highest importance because of high failure rates of phase III trials (around 60%). However, PFS estimations on early readouts with less than 50% of events observed do not use all available information from tumour measurements over time.
We project the PFS-event of each censored patient by using a mixed model [2] describing the tumour burden over time. RECIST-criteria are applied on estimated patient-specific non-linear tumour-trajectories to calculate the projected time-to-progression.
PFS is compared between test and reference by hazard ratios (HR). Several phase III and II simulations with 1000 runs each with 2000 or 80 patients, 6 months accrual and 2 (scenario-1) or 6 months (scenario-2) follow-up were performed. All simulations are based on a published optimal parameterisation [1] of tumour-growth in non-small-cell lung cancer (NSCLC) which implies a time-dependent HR.
The classical PFS estimation resulted in a HR of 0.34 (95%-percentiles: 0.29-0.40) for scenario-1 and 0.52 (0.47-0.58) for scenario-2 compared to a predicted HR of 0.77 for both scenarios (0.69-0.85 and 0.69-0.84), while the overall true HR (over ten years) was 0.78 (0.69-0.85). For 6, 12 and 120 months the time varying HRs were 0.41 (0.36-0.47), 0.60 (0.54-0.66) and 0.77 (0.69-0.85). The classical PFS estimation for phase II showed HRs from 0.52 to 0.61 compared to predicted HRs between 0.71 and 0.77.
Tumour-growth models improve PFS estimations in the presence of high censoring-rates as they consistently provide far better estimates of the overall true HR in phase III and II trials.
[1] M. Reck, A. Mellemgaard, S. Novello, PE. Postmus, B. Gaschler-Markefski, R. Kaiser, H. Buchner: Change in non-small-cell lung cancer tumor size in patients treated with nintedanib plus docetaxel: analyses from the Phase III LUME-Lung 1 study, OncoTargets and Therapy 2018:11 4573–4582
[2] Laird NM, Ware JH. Random-effects models for longitudinal data. Biometrics. 1982 Dec;38(4):963-74. PMID: 7168798.
Evaluation of event rate differences using stratified Kaplan-Meier difference estimates with Mantel-Haenszel weights
Hannes Buchner1, Stephan Bischofberger1, Rainer-Georg Goeldner2
1Staburo, Germany; 2Boehringer Ingelheim, Germany
The assessment of differences in event rates is a common endeavor in the evaluation of the efficacy of new treatments in clinical trials. We investigate the performance of different hypothesis tests for cumulative hospitalization or death rates of Covid-19 in order to reliably determine the efficacy of a novel treatment. The focus of the evaluation was on the comparison of event rates via Kaplan-Meier estimates for a pre-specified day and the aim to reduce sampling error, hence we examine different stratum weights for a stratified Z-test for Kaplan-Meier differences. The simulated data is calibrated from recent research on neutralizing antibodies treatment for Covid-19 with 2, 4, and 6 strata of different size and prevalence, and we investigate the effects of overall event rates ranging from 2% to 20%. We simulate 1000 patients and compare the results of 1000 simulation runs. Our simulation study shows superior performance of Mantel-Haenszel-type weights [Greenland & Robins (1985), Biometrics 41, 55-68] over inverse variance weights – in particular for unequal stratum sizes and very low event rates in some strata as common in COVID-19 treatment studies. The advantage of this approach is a larger power of the test (e.g. 79% instead of 64% for an average event rate 7%). The results are compared with those of a Cochran-Mantel-Haenszel (CMH) test, which yields lower power than the inverse variance weights for low event rates (under 62% for average event rate 7%) and consistently lower power than the Z-test with the Mantel-Haenszel stratum weights. Moreover, the CMH test breaks down (power reduction by 30%) in presence of loss-to-follow-up with as little as 5% of the patients due to its nature of not being designed for time-to-event data. The performance of the Z-test for Kaplan-Meier differences on the other hand is hardly suffering from the latter (power reduction by 4%). All investigated tests satisfy the set significance level for type-I errors in our simulation study.
Survival and Event History Analysis I
Chairs: Jan Beyersmann and Georg Zimmermann
CASANOVA: Permutation inference in factorial survival designs
Marc Ditzhaus1, Arnold Janssen2, Markus Pauly1
1TU Dortmund, Germany; 2Heinrich-Heine-University Duesseldorf
In this talk, inference procedures for general factorial designs with time-to-event endpoints are presented. Similar to additive Aalen models, null hypotheses are formulated in terms of cumulative hazards. Deviations are measured in terms of quadratic forms in Nelson–Aalen-type integrals. Different to existing approaches, this allows to work without restrictive model assumptions as proportional hazards. In particular, crossing survival or hazard curves can be detected without a significant loss of power. For a distribution-free application of the method, a permutation strategy is suggested. The theoretical findings are complemented by an extensive simulation study and the discussion of a real data example.
Statistical MODEling of Additive Time Effects in Survival Analysis
Annika Hoyer1, Oliver Kuss2
1Department of Statistics, Ludwig-Maximilians-University Munich, Germany; 2Institute for Biometrics and Epidemiology, German Diabetes Center, Leibniz Institute for Diabetes Research at Heinrich-Heine-University Duesseldorf, Germany
In survival analysis, there have been various efforts to model intervention or exposure effects on an additive rather than on a hazard, odds or accelerated life scale. Though it might be intuitively clear that additive effects can be easier understood, there is also evidence from randomized trials that this is indeed the case: treatment benefits are easier understood if communicated as postponement of an adverse event [1]. In clinical practice, physicians and patients tend to interpret an additive effect on the time scale as a gain in life expectancy which is added as additional time to the end of life [2]. However, as the gain in life expectancy is, from a statistical point of view, an integral, this is not a precise interpretation. As an easier interpretable alternative we propose to model the increasing "life span" [3] and to examine the corresponding densities instead of the survival functions. Focussing on the respective modes, the difference of them describes a change in life span, especially the shifting of the most probable event time. Therefore, it seems reasonable to model differences in life time in terms of mode differences instead of differences in expected times. To this task, we propose mode regression models (which we write "Statistical MODEls" to emphasize that the modes are modelled) based on parametric distributions (Gompertz, Weibull and log-normal). We illustrate our MODEls by an example from a randomized controlled trial on efficacy of a new glucose-lowering drug for the treatment of type 2 diabetes.
[1] Dahl R, Gyrd-Hansen D, Kristiansen IS, et al. Can postponement of an adverse outcome be used to present risk reductions to a lay audience? A population survey. BMC Med Inform Decis Mak 2007; 7:8
[2] Detsky AS, Redelmeier DA. Measuring health outcomes-putting gains into perspective. N Engl J Med 1998; 339:402-404 [3] Naimark D, Naglie G, Detsky AS. The meaning of life expectancy: what is a clinically significant gain? J Gen Intern Med 1994; 9:702-707
Assessment of additional benefit for time-to-event endpoints after significant phase III trials – investigation of ESMO and IQWiG approaches
Christopher Alexander Büsch, Johannes Krisam, Meinhard Kieser
New cancer treatments are often promoted as major advances after a significant phase III trial. Therefore, a clear and unbiased knowledge about the magnitude of the clinical benefit of newly approved treatments is important to assess the amount of reimbursement from public health insurance of new treatments. To perform these evaluations, two distinct "additional benefit assessment" methods are currently used in Europe.
The European Society for Medical Oncology (ESMO) developed the Magnitude of Clinical Benefit Scale Version 1.1 (ESMO-MCBSv1.1) classifying new treatments into 5 categories using a dual rule considering the relative and absolute benefit assessed by the lower limit of the 95% HR confidence interval or the observed absolute difference in median treatment outcomes, respectively[1,2]. As an alternative, the German IQWiG compares the upper limit of the 95% HR confidence interval to specific relative risk scaled thresholds classifying new treatments into 6 categories[4]. Until now, these methods have only been compared empirically[3].
We evaluate and compare the two methods in a simulation study with focus on time-to-event outcomes. The simulation includes aspects such as different censoring rates and types, incorrect HRs assumed for sample size calculation, informative censoring, and different failure time distributions. Since no "placebo" method reflecting a true (deserved) maximal score is available, different thresholds of the simulated treatment effects were used as alternatives. The methods' performance is assessed via ROC curves, sensitivity / specificity, and the methods' percentage of achieved maximal scores. Our results indicate that IQWiGs method is usually more conservative than ESMOs. Moreover, in some scenarios such as quick disease progression or incorrect assumed HR IQWiGs method is too liberal compared to ESMO. Nevertheless, further research is required, e.g. methods' performance under non-proportional hazards.
[1] N.I. Cherny, U. Dafni et al. (2017): ESMO-Magnitude of Clinical Benefit Scale version 1.1. Annals of Oncology, 28:2340-2366
[2] N.I. Cherny, R. Sullivan et al. (2015): A standardised, generic, validated approach to stratify the magnitude of clinical benefit that can be anticipated from anti-cancer therapies: the European Society for Medical Oncology Magnitude of Clinical Benefit Scale (ESMO-MCBS). Annals of Oncology, 26:1547-1573
[3] U. Dafni, D. Karlis et al. (2017): Detailed statistical assessment of the characteristics of the ESMO Magnitude of Clinical Benefit Scale (ESMO-MCBS) threshold rules. ESMO Open, 2:e000216
[4] G. Skipka, B. Wieseler et al. (2016): Methodological approach to determine minor, considerable, and major treatment effects in the early benefit assessment of new drugs. Biometrical Journal, 58:43-58
Independent Censoring in Event-Driven Trials with Staggered Entry
Jasmin Rühl
Universitätsmedizin Göttingen, Germany
In the pharmaceutical field, randomised clinical trials with time-to-event endpoints are frequently stopped after a pre-specified number of events has been observed. This practice leads to dependent data and non-random censoring, though, which can generally not be solved by conditioning on the underlying baseline information.
If the observation period starts at the same time for all of the subjects, the assumption of independent censoring in the counting process sense is valid (cf. Andersen et al., 1993, p. 139), and the common methods for analysing time-to-event data can be applied. The situation is not as clear in case that staggered study entry is considered, though. We demonstrate that the study design at hand indeed entails general independent censoring in the sense of Andersen et al.
By means of simulations, we further investigate possible consequences of employing techniques such as the non-parametric bootstrap that make the more restrictive assumption of random censoring. The results indicate that the dependence in event-driven data with staggered entry is generally too weak to affect the outcomes; however, in settings where only few occurrences of the regarded event are observed, the implications become clearer.
Chairs: Tim Friede and Cynthia Huber
Learning about personalised effects: transporting anonymized information from individuals to (meta-) analysis and back
Els Goetghebeur
Ghent University, Belgium
Evidence on `personalized' or stratified medicine draws information from subject-specific records on prognostic factors, (point) treatment and outcome from relevant population samples. A focus on treatment by covariate interactions makes such studies more data hungry than a typical trial focusing on a population average effect. Nationwide disease registers or individual patient meta-analysis may overcome sample size issues, but encounter new challenges, especially when targeting a risk or survival outcome. Between study heterogeneity comes as a curse and a blessing when aiming to transport treatment effects to new patient populations. It reveals sources of variation with specific roles in the transportation. For survival analysis special attention must be given to calendar time and internal time. A core set of covariates is needed for the stratified analysis, ideally measured with similar precision. A shared minimum follow-up time, and well understood censoring mechanisms are expected. Variation in baseline hazards under standard of care may reflect between study variation in diagnostic criteria, in populations, in unmeasured baseline covariates, in standard of care delivery and its impact.
When core set covariates are lacking for some studies or over certain stretches of time, a range of solutions may be considered. Different assumptions on missing covariates of survival models will affect treatment balancing IPW and direct standardization methods differentially. Alternatively, one may seek to link data from different sources to fill the gaps. It then pays to consider models with estimators that can be calculated from (iteratively) constructed summary statistics involving weighted averages over functions of the missing covariates. By thus avoiding the need for additional individually linked measures, one may open access to a range of existing covariates or biomarkers that can be merged while circumventing (time)consuming lengthy confidentiality agreements.
In light of the above we discuss pros and cons of various methods of standardizing effects to obtain transportable answers that are meaningfully compared between studies. We thus aim to provide relevant evidence on stratified interventions referring to several case studies.
Precision medicine in action – the FIRE3 NGS study
Laura Schlieker1, Nicole Krämer1, Volker Heinemann2,3, Arndt Stahler4, Sebastian Stintzing3,4
1Staburo GmbH, Germany; 2Department of Medicine III, University Hospital, University of Munich, Germany; 3DKTK, German Cancer Consortium, German Cancer Research Centre (DKFZ); 4Medical Department, Division of Hematology, Oncology and Tumor Immunology (CCM), Charité Universitaetsmedizin Berlin
The choice of the right treatment for patients based on their individual genetic profile is of utmost importance in precision medicine. To identify potential signals within the large number of biomarkers it is mandatory to define criteria for signal detection beforehand and apply appropriate statistical models in the setting of high dimensional data.
For the identification of predictive and prognostic genetic variants as well as tumor mutational burden (TMB) in patients with metastatic colorectal cancer, we derived the following pre-defined and hierarchical criteria for signal detection.
a) All biomarkers identified via a multivariate variable selection procedure
b) If a) reveals no signal, all biomarkers with adjusted p-value ≤ 0.157
c) If neither a) nor b) reveals signals, the top 5 biomarkers according to sorted, adjusted p-value
Regularized regression models were used for variable selection, and the stability of the selection process was quantified and visualized. Selected biomarkers were analyzed in terms of their predictive potential on a continuous scale.
With our analyses we confirmed the predictive potential of several already known biomarkers and identified additional promising candidate variants. Furthermore, we identified TMB as a potential prognostic biomarker with a trend towards prolonged survival for patients with high TMB.
Our analyses were supported by power simulations for the variable selection method, assuming different prevalences of biomarkers, numbers of truly predictive biomarkers and effect sizes.
Tree-based Identification of Predictive Factors in Randomized Trials using Weibull Regression
Wiebke Werft1, Julia Krzykalla2, Dominic Edelmann2, Axel Benner2
1Hochschule Mannheim University of Applied Sciences, Germany; 2German Cancer Research Center (DKFZ), Heidelberg, Germany
Keywords: Predictive biomarkers, Effect modification, Random forest, Time-to-event endpoint, Weibull regression
Novel high-throughput technology provides detailed information on the biomedical characteristics of each patient's disease. These biomarkers may qualify as predictive factors that distinguish patients who benefit from a particular treatment from patients who do not. Hence, large numbers of biomarkers need to be tested in order to gain evidence for tailored treatment decisions ("personalized medicine"). Tree-based methods divide patients into subgroups with differential treatment effects in an automated and data-driven way without requiring extensive pre-specification. Most of these methods mainly aim for a precise prediction of the individual treatment effect, thereby ignoring interpretability of the tree/random forest.
We propose a modification of the model-based recursive partitioning (MOB) approach for subgroup analyses (Seibold, Zeileis et al. 2016), the so-called predMOB, that is able to specifically identify predictive factors (Krzykalla, Benner et al. 2020) from a potentially large number of candidate biomarkers. The original predMOB is developed for normally distributed endpoints only. To widen the field of application, particularly for time-to-event endpoints, we enhanced the predMOB to these situations. More specifically, we use Weibull regression for the base model in the nodes of the tree since MOB and predMOB require fully parametrized models. However, the Weibull model includes the shape parameter as a nuisance parameter which has to be fixed to focus on predictive biomarkers only.
The performance of this extension of the predMOB is assessed concerning identification of the predictive factors as well as prediction accuracy of the individual treatment effect and the predictive effects. Using simulation studies, we are able to show that predMOB provides a targeted approach to predictive factors by reducing the erroneous selection of biomarkers that are only prognostic.
Furthermore, we apply our method to a data set of primary biliary cirrhosis (PBC) patients treated with D-penicillamine or placebo in order to compare our results to those obtained by Su et al. 2008. The aim is to identify predictive factors with respect to overall survival. On the whole, similar variables are identified, but the ranking differs.
Krzykalla, J., et al. (2020). "Exploratory identification of predictive biomarkers in randomized trials with normal endpoints." Statistics in Medicine 39(7): 923-939.
Seibold, H., et al. (2016). "Model-based recursive partitioning for subgroup analyses." The International Journal of Biostatistics 12(1): 45-63.
Su. X., et al. (2008). "Interaction trees with censored survival data." The International Journal of Biostatistics 4(1).


text:
How Points Party's Dan Frommer Earns and Spends Credit Card Points
Shep McAllister
Welcome back to Good Points, a weekly Q&A about credit card points, the people who collect them, and where they take us. This week's guest is Dan Frommer, a Brooklyn-based journalist and the creator of Points Party, a newsletter about travel points, credit card rewards and loyalty programs. Sign up here for free, and follow him on Twitter and Instagram at @FromeDome.
My Cat Loves This 30-Pack of Sparkly Balls More Than She Loves Me
Today's Best Deals: WeMo Switches, Garbage Disposal, Eneloops, and More
If you know anyone who just won't shut up about their points strategy, have them send an email to shep@gizmodomedia.com with the subject line "Good Points" for a chance to be featured. We want to talk to everyone from professional travelers who spend their lives on the road, to people who save all their points on one trip per year, so don't be shy!
What first got you hooked on collecting points?
I love to travel and I love a great deal, so collecting points has been an obvious pursuit of mine basically forever.
I filled out my first frequent-flyer application in the back of a stinky, cigarette-smoke-filled Air France 747 in the mid-1990s and haven't stopped since. Back then — I was in middle school — I was more excited about the actual physical membership card than the value of the points. But once I started using credit cards and traveling more on my own, I quickly got into the points hobby.
Now it's something I think about every day! And I found myself talking about points with friends often enough that I started Points Party, a newsletter of my best tricks, lessons I'm learning, analysis, and favorite ways to earn and spend points.
What are you trying to accomplish by collecting points? Pay for all of your small trips? Splurge on vacations that you wouldn't otherwise take? Somewhere in between?
I want to have great travel experiences and feel like I'm getting a good deal when I use my points. My travel style is more creative and comfortable than flashy luxury. I'm not an overwater-beach-villa-type — or at least not yet!
Sometimes that means trading in a year's worth of Hyatt points for a week in Japan, including a few days at the Andaz Tokyo, one of my favorite hotels in the world. Sometimes it means booking a utilitarian coach flight to Los Angeles or Chicago that will still earn credit towards airline status and where I might get upgraded anyway.
Once a year or so I'll do something like fly international first class instead of business, as a "free" splurge of indulgence and curiosity. But mostly I see points as a tool to help me get to interesting places.
What credit cards do you currently hold, and why'd you get them?
I'm going to focus most of my spending on Chase cards this year again, because I have a system that works and has been very lucrative over the past few years, which involves the Chase Sapphire Reserve, Chase Freedom and Chase Freedom Unlimited.
The Ultimate Guide to Chase Ultimate Rewards
Now that we've explored each of the cards in Chase's Ultimate Rewards ecosystem individually and in
Zooming out, the key to all of this is to both earn the most posts and to get the most value when you spend them. In my experience, and supported by frequent research, Chase's Ultimate Rewards program is still the best for this. It's possible this will change — points typically lose value over time, and programs change frequently — but this is my current strategy.
I generally use the Chase Sapphire Reserve for all travel and dining purchases — 3 points per dollar — which is a big percentage of my spending. And for international purchases, because it has no foreign transaction fees. But that's all I use it for.
For Frequent Travelers, The Chase Sapphire Reserve Is A Core Holding
The Chase Sapphire Reserve is the step up version of our readers' favorite travel rewards credit…
I use the Chase Freedom for its quarterly rotating bonus categories. This quarter, that means I'm earning 5 points per dollar at drugstores, gas stations and tolls. So I'll buy a year's worth of contact lenses from Walgreens online this quarter (starting at the Chase shopping portal, which will earn me even more points). And I'll buy Whole Foods gift cards at a drugstore to use for grocery shopping, and probably max out that category, which means spending $1,500 before the end of March.
Collect Ultimate Rewards Points Even Faster With Chase Freedom
We've already covered Chase's flagship credit cards, which bring huge benefits to frequent…
I use the Chase Freedom Unlimited — 1.5 points per dollar — for almost everything else when I'm following this system.
Chase's Freedom Unlimited is Your Rewards Credit Card For Everything Else
When Chase's flagship travel cards and the rotating bonuses of Chase's Freedom don't apply, the…
Then I can transfer all the Freedom and Freedom Unlimited points over to my Sapphire Reserve account, and use them to book flights, transfer to travel partners like Hyatt and British Airways, etc.
I consider Chase points to be worth 2 cents each, so that means I'm earning about 3% "back" in points value on every Freedom Unlimited purchase, 6% back on Sapphire Reserve purchases, and up to 10% back on those Freedom bonus categories. Plus whatever other bonus points or loyalty schemes those purchases include. It's a good system!
I just got the new American Express Gold Card, and I'm testing it as a competitor to my Chase system. It earns 4 points per dollar at restaurants and U.S. grocery stores (for the first $25,000 in purchases per year, after which it's 1x point per dollar), and I do a lot of grocery shopping. But Amex points are generally worth less than Chase points when you redeem them, and it takes longer for them to become available, so I'm not sure how much I'll use it over the long run. We'll see.
My favorite new card is the Cash card from Square, which I just wrote about on Points Party. It's not a credit card and it doesn't earn points — it's a prepaid card that links to your Cash App balance. But for now, at least, it has these amazing benefits called "Boosts." One of the "Boosts" gets you $1 back every time you use the card at a coffee shop, which generally ends up covering my tip, saving me about 20%. I'm on track to save about $150 a year that way. That's a much better deal than any points I'd earn on those purchases. You can also get 10% back on Whole Foods purchases, up to $7.50 — also a good deal. Having more cash is often better than having more points!
I also have some airline and hotel cards, such as the Citibank American Airlines card, which was one of my first points cards a long time ago. I keep it because it gets me 10% back on my first 100,000 American miles I redeem every year, which basically pays for its annual fee. And a few other benefits. I also have had the Barclaycard Aviator Silver, another American Airlines card, for the past two years, because spending on it helped me earn elite status on American faster. So I was putting a lot of spend on it, including my rent many months. But this year, they gutted that benefit, so I'll probably get rid of the card or downgrade to a free card to keep that credit line open.
I have the Hyatt Visa card because it earns me a free night every year, which covers its annual fee. And I have a Starwood Amex that I'll probably get rid of — I don't really care for Starwood hotels or Marriott, which it merged with. I'm more interested in the Amex Platinum, but not right away.
What point redemption are you most proud of?
One of my favorite things about using points to pay for flights is that the tickets are often more flexible than cash tickets. So if you're crafty, or get lucky, you can sometimes change them at the last minute for a much better seat and/or routing.
Several years back, my wife and I were scheduled to fly home to New York from Vancouver, in coach, all day, through Dallas, on American 737s. Ugh. I think our tickets were 25,000 points each, which wasn't even a very good deal.
But the day before our flight I remembered that Cathay Pacific has a nonstop redeye flight from Vancouver to JFK on a 777. So I called American, and sure enough, we could fly home on that Cathay flight — in international business class! — for the same number of points. I generally avoid redeyes, but if it's in business class with lie-flat seats, sure. And we got a whole extra day to enjoy Vancouver, too.
Last year, I flew the same route in reverse, in first class, and it was totally worth the one-time points splurge. Pajamas!
What point redemption are you least proud of?
Nothing super bad. Some hotels — usually cheaper, chain spots — haven't been as clean or as comfortable as I'd have hoped. But I've also slept in my share of grimy backpacker hostels over the years by choice. Nothing that was enough of a mistake to warn people about.
Just remember that points are a currency. Don't let them decide where you go or how you spend your time. Take the trip you want, and figure out the best way to pay for it, whether it's points or cash. This is supposed to be fun!
Do you chase status at a specific airline or hotel chain, or do you just shop around for the best deals, locations, and flights?
If you travel a lot, both airline and hotel status can be game-changers. Especially airline status.
I have been very loyal to American Airlines for the past dozen or so years, and it has served me well. The past few years I've flown enough to earn Executive Platinum status, which is their highest level that mere mortals can achieve. (There's "Concierge Key" status, too, but you generally have to spend a LOT of money to get it.) This comes with four worldwide upgrades, which are worth several hundred dollars each, and always feel great to redeem on long flights to Europe or Asia.
If you fly a lot, and you can't pay for business class on your own, airline status is a huge benefit — beyond upgrades, preferred seating, flexibility, and earning more miles — they just take better care of you. American has been making its frequent-flyer program less valuable each year, so as a New Yorker, I always have an eye on Delta. But for now, I'll happily pay more to fly American or one of its partners in most cases — unless it's a situation where the routing or flight times just don't make sense.
I'm less concerned with hotel status, but I tend to favor Hyatt hotels among the chains when I have a choice. The points are useful to me — especially for my annual Japan trips, where they have a few great hotels — and I think Hyatt has good taste. But I won't overpay.
And I try to stay in interesting, boutique hotels or Airbnbs on a lot of trips. I try to stay at the Ace in London and Chicago, or the Line in LA, if I'm not Airbnbing.
What's the first card you recommend to people who are interested in getting into points, and why?
If you want to earn points for travel, have good credit, and spend more than $1,000 a month on credit cards, I think the Chase Sapphire Reserve — and my Chase system, which earns me thousands of dollars a year in free travel — is what I'd choose.
If you are nervous about a card with a $450 annual fee — even though it can pay for itself in the rewards you earn — the Sapphire Preferred, which is $95, is also solid, because you can still transfer points to travel partners and from the various Freedom cards.
An airline or hotel card can also be a good way to get started, especially if you're going to be spending money with that company anyway. But you'll probably earn fewer points that way, with less flexibility on spending them.
What's one piece of advice you wish you'd known before you got into points collecting?
I knew this ahead of time, but it's worth repeating, and I include it in my "Guide to Life" at Points Party: Don't overextend yourself. Don't spend more than you can afford. Aim to pay your balance in full every month. No judgment here on debt — I've been there, for good and bad reasons. But never do it for the points. No amount is worth the cost of interest payments and the stress of falling behind.
How do you keep track of things like points, bonus categories, free nights, and annual fee dates?
I only really obsess over my progress toward airline status, which I built a spreadsheet to keep track of. Everything else I peek at once or twice a month, but don't really think much about until I'm planning a big trip.
Let's finish off with a few rapid fire questions. I give you enough points to take three flights anywhere in the world in economy, or one flight anywhere in the world in first class. What do you choose?
Right now, I'll take the three flights in coach. There's a decent chance I'll be able to work the system for an upgrade, or at least find the exit-row seat with unlimited legroom. (I once wrote an entire article about faking your own business-class upgrade!) But I am still more interested in seeing the world than sitting in the fanciest chair.
Top three items on your travel bucket list?
I want to spend more time in Japan, visit Vietnam and go back to China. And maybe Italy? Or Wyoming?
Favorite city you've ever visited?
Tokyo and Paris are my top two. I'll go any time I have an excuse. Or back to my hometown, Chicago, which is weirdly now a place I "visit."
Favorite airport?
I love airports! For feelings, JFK, because it means I'm about to go on an adventure or am coming home, both of which are exciting. SFO has the best food and amenities in America, at least among my regular stops. The traffic at LAX is a national embarrassment, but it's hard to beat landing in LA and walking out of the terminal on a warm evening. Madrid's Barajas is the prettiest terminal building. The Pier lounge in Hong Kong is the only one I ever think about. And I'm weirdly fond of Heathrow in London, even though a lot of things about it are terrible.
Worst airport?
Vegas. Bye!
Favorite hotel you've ever stayed in?
The Park Hyatt in Tokyo is a predictable answer, but it really is special — especially if you're staying there for free, using points — including incredible attention to detail. When my wife and I went to the pool and spa one afternoon, we left our wedding rings on the console in our room. When we returned a couple hours later, the staff had fetched a leather ring holder and tucked ours in. And yes, the pool is amazing.
Airplane drink of choice?
Sparkling water. Gotta stay hydrated! I bring at least one liter of water, too, if not two or three on long flights. Once a year or so I'll have a wine or scotch, but it's never worth it.
Can you sleep on a plane?
Yes, most of the time. Especially if I'm in biz or premium economy. Reading or a movie usually does the trick. I bring Bose QC35 headphones, and that helps.
Bose QuietComfort 35 II Wireless Bluetooth Headphones, Noise-...
Buy for $354 at Amazon
Window seat or aisle seat?
Depends on the airplane, route, and whether I'm alone or with my wife and/or dog. But mostly aisle, because I like to get up about once an hour to stretch my legs or visit the lav, and I don't like bothering others to get up.
Gizmodo Media Commerce has partnered with The Points Guy Affiliate Network for our coverage of credit products. Gizmodo Media Group and The Points Guy may receive a commission from card issuers.

redpajama_set_name: RedPajamaCommonCrawl


text:
Avocado shortage fuels crime wave in New Zealand
Thieves capitalise on booming black market for the fruit amid soaring demand
Avocados are selling for between NZ$4-6 each across the country, after a poor season last year and increasing local demand. Photograph: FotografiaBasica/Getty Images
Surging local and international demand for avocados is fuelling a crime wave inNew Zealand.
Since January there have been close to 40 large-scale thefts from avocado orchards in the north island of New Zealand, with as many as 350 fruit stolen at a time.
It is suspected many more thefts have gone unreported.
Avocados are selling for between NZ$4-6 each (£2-3) across the country, after a poor season last year and increasing local demand.
According to New Zealand Avocado in 2015 an additional 96,000 New Zealand households began purchasing avocados, and local growers – largely geared towards the lucrative export market – have been unable to keep up with the surge in demand.
The recent thefts have taken place in the middle of the night, with the crop either "raked" from the tree and collected in blankets or sheets on the ground, or hand-picked and driven away to pop-up road-side stalls, grocery stores or small-scale sushi, fruit and sandwich shops in Auckland.
Sergeant Aaron Fraser of Waihi said there had been "spates" of avocado thefts during his time in the police but nothing as sustained as the current activity.
"These stolen avocados can carry risks," he said.
"They are unripe, some have been sprayed recently and they may still carry toxins on the skin. But with the prices so high at the moment, the potential for profit is a strong inducement for certain individuals."
Jen Scoular, New Zealand Avocado CEO, said the recent thefts were concerning, but a bumper season of locally-grown avocados should flood the New Zealand market in coming weeks, reducing the incentive for thieves.
"It's an easy way to make a quick buck, but I don't think we are dealing with a sophisticated or highly organised operation here, more opportunistic," she said.
"This stolen fruit will only have made it to the local markets, it would never reach our export markets."
Scoular said avocado farms in New Zealand were getting increasingly savvy about protecting their crop, and many had installed automatic lights and alarm systems.
Source: https://www.theguardian.com/world/2016/jun/15/avocado-thieves-shortage-crime-fruit-black-market-new-zealand
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text:
Q: Ionic DeepLinker for lazy loaded page I am trying to implement ionic deeplinker in my app. I am trying to make it work with pages that are in it's own module i.e, lazy loaded page.
Here is what I have in app.module.ts
IonicModule.forRoot(MyApp,{},{
  links:[
    { component: HomePage, name: 'Home', segment: 'home' },
    { component: DemoPage, name: 'Demo', segment: 'demo/:postId' ,defaultHistory: [HomePage]  },
    { component: 'OtherPage', name: 'Other', segment: 'Other' ,defaultHistory: [HomePage]  },
]

Note that otherPage is in quotes. I want to lazy load it.
The other.module.ts is as follows.
import { NgModule } from '@angular/core';
import { IonicPageModule } from 'ionic-angular';
import { OtherPage } from './other';

@NgModule({
  declarations: [
    OtherPage,
  ],
  imports: [
    IonicPageModule.forChild(OtherPage),
  ],
})
export class OtherPageModule {}

How to I achive lazy loading and deeplinking.
Note here that I am using the tabs template.Here is an issue on github on tabs not working with deeplinking
Thanks

A: You can try to set in IonicPage. Deeplinking in Ionicpages is achieved by setting the segment and URL information in the page.
@IonicPage({
  name: 'Other',
  segment: 'Other',
  defaultHistory: ['HomePage']
})

redpajama_set_name: RedPajamaStackExchange


text:
Wasp spray being used as alternative to meth, police say
'Started spreading up my leg': Woman gets flesh-eating bacteria after swimming at Virginia beach
Documents link teen to Boone High School student's murder investigation
'A special ring': Man who found 64-year-old wedding band on Florida beach is in search of its owner
'Together in Heaven': Husband and wife married for 71 years die on same day, just 12 hours apart
Olympic gold-medalist, former Cal rower champions 'Fair Pay to Play'
Police:Suspect in Florida Amber Alert murder case found in relative's basement in Connecticut
Posted Jun 26 2019 11:10PM EDT
Video Posted Jun 27 2019 06:13AM EDT
Updated Jun 27 2019 06:14AM EDT
Bruce Hagans Sr. says justice needs to be served for the man accused of killing his son.
Authorities said Luis Rivera Jr., 20, fatally shot Bruce Hagans Jr., 16, following a kidnapping which prompted the issuance of an Amber Alert.
"I can't hear his voice no more, and it hurts," Hagans Sr. says. "I couldn't even have an open casket or good burial, because they way they treated him like an animal. hHs body was just messed up."
Winter Garden Police said Hagans Jr. was shot inside a car during a marijuana drug deal. His body was discovered on June 7, a few miles away from the Rivera home. Police said the father of the shooter, who was arrested last week and charged with destroying evidence, helped bury the west orange high school student's body the next day. Investigators said Rivera Sr. then put his son on a plane to Connecticut.
Rivera Jr. was found hiding in the basement of a relative's home in New Britain, Conn. The accused shooter was extradited back to Orange County on Tuesday night.
"Thank god, there is a god in heaven and justice will have been served because they have found him."
Rivera Jr. and his father may not be the last of the arrests. Police are looking for more people whom they say helped destroy evidence
"I pray for you, because you're going to be gone a long time hopefully, and just like my son suffered, I hope you suffer the same way."
New details have been revealed in the case of a Boone High School student who was shot and killed while on his way to school.
Court documents show prosecutors believe 19-year-old Deandre Florence is responsible for the death of 15-year-old Alejandro Vargas Martinez, fatally shot while walking to school in December of 2018. The new information was part of discovery documentation released by the State Attorney's Office.
Florence is already behind bars, charged with another murder.
Orlando hosts self-driving vehicle conference
The world's leaders in autonomous vehicle research and development have descended on Orlando, putting Central Florida in the spotlight.
Orlando is hosting the automated vehicle symposium while vying to be a hub for the technology that autonomous vehicles use.
"Getting the word out, helping people understand why Orlando is the best destination for testing, manufacturing and finding their new talents that apply for the automated vehicle industry," said Sheena Fowler, vice president of innovation of the Orlando Economic Partnership. "We're looking to really expand peoples' perceptions of Orlando and help them understand the other half of what we have to offer."
Deputies in northern Florida search for missing and endangered teen
The Santa Rosa County Sheriff's Office says that 16-year-old Kyla Jade Shannon is missing and endangered.
Deputies say that Kyla was last seen in the area of Pebble Brook Drive in Milton on June 28th. It was initially believed that she ran away from home, but recent information revealed that she may be endangered.
She may be in the Pensacola or Panama City area, deputies say. She may also be with a white 40-year-old female who has brown hair and hazel eyes.
Florida Democrats complain of Trump 'ballot bias' in 2020
Police: Worker loading ATMs with cash pocketed $100K instead


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The one week free trial is a fab idea as it allows you to see if the app is actually right for you before you sign up to the monthly payment.


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Detroit's Ex-(and Future?) Felon Mayor, Kwame Kilpatrick, is Living Large in Texas, with No Visible Income (but with a Secret Loan), Has Committed Tax
Evasion, is Not Paying Back His Court-Ordered Restitution, and being Represented on the (White) Taxpayer's Dime (And Trying to Forget Tamara Greene!)
[Previously, at WEJB/NSU, on Kwame Kilpatrick:
"Detroit's Gangster Mayor Reportedly to Accept Plea Today: Kilpatrick Era Over … for Now";
"(Kwame) Kilpatrick Enterprise" in Detroit: Most Corrupt Municipal Administration Anyone Had Ever Seen";
"Carlita Kilpatrick, Wife of Convicted Former Detroit Mayor Kwame Kilpatrick, Fights Paying One Dime of the $1 Million Restitution He Agreed to, as Part of His Plea-Bargain";
"Feds Declare War on Detroit's Gangster Mayor, Kwame Kilpatrick, Charge Him with Everything but the Murder of Tamara Greene";
"In Detroit, to Find the Biggest Crooks, Look to the Highest Offices: Judge Carlos Powell Charged with Being City's Drug Kingpin."]
Detroit's convicted felon ex-Mayor Kwame Kilpatrick says he'll file his taxes going back to 2009 this year. That's called tax evasion. He says he was in prison during 2009 and 2010 (but wasn't inside during all of that time), but that doesn't matter, as he had secret income at the time from a loan that he refuses to divulge, and about which says he will "take the Fifth."
So, his criminal ways haven't changed in the least.
Tamara "Strawberry" Greene was the voluptuous, high-priced, stripper-prostitute who reportedly performed at a secret party for Mayor Kilpatrick and friends at the mayor of Detroit's official residence, Manoogian Mansion, in the late fall of 2002. The mayor's wife, Carlita, was supposed to be away, but reportedly showed up unexpectedly, and brutally beat Greene with a blunt object. Several first-responders who were at a hospital emergency room that night have reported that a black woman was brought in who supposedly had been beaten up by Mrs. Kilpatrick. Greene was shot three times and killed on April 30, 2003, by a member of the Detroit PD; whose murder's files weren't all stolen from a locked file at DPD headquarters.
Greene's son sued the city over his mother's death, but Michigan's white attorney general, Mike Cox, a judge, and the Detroit newspapers all struck down or lambasted the son's suit, insisting that there was no evidence of official misconduct.
The Kilpatricks have denied that any party was ever held at Manoogian, in which Tamara Greene performed, was beaten, etc. You know what? Forget that I even mentioned Tamara "Strawberry" Greene. She never existed.
* * *Texas to Kwame Kilpatrick: Get a job
Emails ex-mayor wrote to say he's broke also reveal he hasn't filed taxes since 2008
By Robert Snell
February 20, 2012 at 1:27 a.m.
Detroit— Texas parole officials have a message for former Mayor Kwame Kilpatrick: Get a job.
The message was revealed in Kilpatrick's personal emails to Texas and Michigan prison officials, which were obtained by The Detroit News. Kilpatrick said he is so broke he had to borrow money to pay his $160 restitution to the city last month and hasn't repaid $240,000 in loans from Compuware co-founder Peter Karmanos Jr. and businessmen Roger Penske, Dan Gilbert and James Nicholson.
"The money is gone," Kilpatrick said, adding he has not made a single loan payment.
The emails — along with news that Kilpatrick has not filed his tax return since 2008 — are surfacing as officials in Michigan are poised to increase his court-ordered restitution to about $500 a month. The review was prompted by concerns he is hiding assets and living beyond his means.
Michigan Corrections officials have made a decision on the restitution and instituted new parole conditions and are mailing them to him Tuesday. They won't announce what they are until he gets the letter in the mail, said Corrections spokesman Russ Marlan. Kilpatrick owes $860,222.
In a Feb. 3 email to a Texas parole official, sent from his personal account "The Real KMK!" Kilpatrick complained about being told to look for a job. He said Texas officials have rejected appearances and trips to New York and Cleveland and that he earned no money in January.
"I understand that I am a 'high-profile' parolee, but I am incredibly confused as to why I'm being treated differently than ANYONE else," he wrote. "I have never asked for any special treatment, nor do I want to be treated especially bad."
The emails were obtained by The Detroit News from the Michigan Department of Corrections through the Freedom of Information Act.
The ex-con, who resigned in disgrace in 2008 amid a text message scandal and who faces racketeering conspiracy charges in federal court, complained the Corrections crackdown and canceled appearances are hurting his reputation.
"This has not only hurt my ability to earn income, but has begun a conversation in this industry that I am unable to commit in a timely fashion," Kilpatrick wrote.
He said he was confused about being ordered to report to the Texas Workforce Commission earlier this month to register for a job. Kilpatrick insists he has a job giving speeches and making public appearances.
"We would not consider occasional speaking engagements to be steady employment," Texas Criminal Justice Department spokesman Jason Clark told The News.
Kilpatrick was making $120,000 a year as a salesman for a division of Detroit computer software giant Compuware until 2010. He was fired after Wayne County Judge David Groner put him back behind bars for violating probation by hiding assets that could have been applied to the $1 million restitution he agreed to pay the city.
"He had a job," Kilpatrick attorney James C. Thomas said Friday. "They took it away from him."
The emails also shed light on Kilpatrick's controversial move last year to Grand Prairie, Texas.
In a Feb. 3 email, Kilpatrick said his wife, Carlita, is leasing the $372,000 home.
The 5,000-square-foot home is larger and more expensive than the family's last rental, but Kilpatrick is claiming poverty to qualify for taxpayer-funded criminal defense lawyers and low restitution payments.
"I HAVE NOTHING TO HIDE," he wrote.
Wayne County prosecutors disagree. Prosecutor Kym Worthy wants Kilpatrick to pay at least $1,000 a month toward the $860,000 restitution balance.
The job demand is appropriate, Assistant Wayne County Prosecutor Maria Miller said Sunday.
"Although long overdue, requiring Kilpatrick to seek gainful employment to pay his restitution obligation is certainly a step in the right direction," she said.
Worthy had asked Michigan Corrections officials to review and modify his restitution payments after a November report in The News about Kilpatrick's move into the larger home.
Following media reports, Texas parole officials made "abrupt sweeping changes," Kilpatrick complained in an email.
Those changes include increasing the number of times he has to check in with parole officials.
"This has caused severe harm, in my ability to earn income, pay my court ordered restitution and even the overall scheduling of my professional, personal and family obligations," he wrote.
Kilpatrick's parole conditions have not changed, Clark said.
In the Feb. 3 email, Kilpatrick said the travel restrictions are a concern because he has $11,000 worth of appearances and book signings lined up this winter, including stops in Chicago, Detroit and a cruise to Jamaica and the Bahamas.
Kilpatrick was offered $1,500 to appear at a six-day Caribbean cruise and sign books during the Tom Joyner Foundation Fantastic Voyage in late March.
Along with his appearance fee, Kilpatrick gets a free cabin and can sell copies of his autobiography during the nationally syndicated radio host's cruise.
Kilpatrick also was offered $5,000 to participate in an "ethics workshop" in April at a forum in Virginia for black public administrators.
"I don't believe that there are ANY jobs at the Texas Work Commission, where I could earn as much income as I could from what I am doing now," Kilpatrick wrote. Clark denied that Texas officials rejected Kilpatrick's request earlier this month to travel to Cleveland.
The emails reveal new demands placed on Kilpatrick by Michigan prison officials.
They recently requested copies of tax returns for 2008-10.
Kilpatrick submitted his 2008 tax return but said he didn't file in 2009 or 2010 because he was incarcerated for violating probation on felony charges from the text message scandal.
He said he will file for those years and 2011 by April 15.
Michigan prison officials also wanted a list of all bank and credit union accounts he accessed last year. They also demanded an update on the personal loans he received from Karmanos and the other businessmen in February 2009.
He was supposed to start repaying those loans in November 2010. As of last month, he hadn't made a single payment.
Michigan prison officials didn't ask about a second mysterious loan, however.
During a November 2009 court hearing, Kilpatrick testified he received a $150,000 loan after being released from jail. He refused to talk about the loan during the hearing.
"I'm going to take the Fifth," he said.
rsnell@detnews.com
[Thanks to reader-researcher RC for this article.
From WEJB/NSU's Detroit File:
"White Detroit News Columnist (Almost) Tells the Truth about Former Motor City's Decline!"
"Justice, Detroit-Style: Is Black Judge Vanessa Bradley a Racist? Do Cows Fart?";
"Detroit: No-Name Clearances of No-Name Murders";
"Detroit's Convicted "Hip-Hop Mayor," Kwame Kilpatrick, is Livin' Large While Pleading Poverty";
"Detroit: New Crime Stats Fail Smell Test; How Could Crime Go Down 7% Overall Last Quarter, While Homicides Went Up 31%?";
"Are White Gangs Making It Impossible to Drive City Buses in Detroit? Inquiring Minds Want to Know";
"Detroit: Buses are So Dangerous and Unreliable That Disabled Mom of 6 Traded Her House for a Minivan";
"Detroit: Three Men in Their 20s Allegedly Kidnapped and Gang-Raped Girl, 13, for at Least Three Days";
"Mysterious, Anonymous Detroit News Story About Arrest of Triple Shooting Suspect, Nasir Banks";
"Happy New Year, Detroit-Style: Club Manager was Killed, Trying to Break Up a Fight; FREEP Writer Knows Facts, but Refuses to Report Them";
"Detroit: Serial Killer is Murdering Prostitutes Who Advertised Online in Pairs, and Stuffing Them in Car Trunks";
"Blackberry: Detroit's Murder Bar—Demesha Hunt, Renisha Landers, and Now, Claudia Benson Last Seen Alive There";
"Detroit: Family of Murder Defendant Jacob Wells, Threatens to Murder Family of Murder Victim, Claudia Benson—on Camera!";
"Detroit: Murder Up 12%, but 'Serious' Crime is Down; Broken Windows Policing is on the Way";
"The Onion: Detroit Has One of America's Top 10 Downtowns"; and
Our Man in Seattle Reports an Explosion in Crime i...
Kristopher Kime, James Paroline, and Edward Scott ...
"Journalist" Piers Morgan is as Fraudulent as Opin...
White Meth-Head Josh Blake Murders Washington Stat...
The New York Times: Hollywood is Insufficiently PC!
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Documentary on Genocide in South Africa: The Murde...
Baloo: Honesty's (Sort of) the Best Policy
Tulsa Murder Suspects in Court Today
What Would It Take for Black Voters to Vote Republ...
Read This Hard-Hitting Exposé on the Corrupt Refug...
New York City: DeWayne Smith is a Murder Waiting t...
Baloo: The Shame and Humiliation of Not Getting .....
New York Times' Maureen Dowd: Why Can't Republican...
The Kitty Genovese Hoax
The Original New York Times Story on the Kitty Gen...
Baloo: Do You Support Nuclear Non-Proliferation?
Pat Buchanan Talks with Juan Williams about Gettin...
Detroit: Was Delric Miller IV Murdered Over a Seat...
Priceless Michelle Obama "Mastercard Ad"
Baloo: The New Civility
The Last Picture of Whitney Houston
Orlando: Hasidim Riot, Yet Again, over Nike Sneake...
Jared Taylor's White Identity: A Review
George S. Schuyler, All-American
Whitney Houston Family Source: Daughter Bobbi Kris...
Baloo: Before Saving the World, Get the Basics Right!
Immigrant Mass Murder Syndrome in Gwinnett County,...
John Hayward: The Real Unemployment Rate is 36%!
Tracey Biletnikoff's Killer Cries in Court
Classic Baloo: Bloomenkraft Thanks for the, er,...
Book Burning in Berlin: National Socialists Then; ...
The Perils of Multicultural Adventurism: White Gre...
Outing a Lefty Hack: "Reporter" Who Supports "Outi...
No First Amendment for You: Two White Girls Make V...
Baloo: Everyone's a Critic!
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Whitney Houston: N.J. Town's Mayor Just Says No to...
No to Same-Sex "Marriage": N.J. Gov. Chris Christi...
Chicago: 8 Shot, 2 Dead, in 7.3 Hours Saturday Nig...
Detroit: Washington's Birthday AK-47 Gang Shooting...
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Whitney Houston and That Ragged Old Flag: Fallen W...
Jayna Murray Murder on ID Channel Sunday Night
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Baloo: The Politics of Incrementalism
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Happy Valentine's Day, from WEJB/NSU!
Jamie Satterfield Live Chat on the Baumgartner Aff...
Whitney Houston Dead at 48: Racist Singer Found Su...
The Baumgartner Affair and the Knoxville Horror: I...
Baloo: Working for the Man
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Baloo on Voting: Same Difference!
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Keepin' It Real in NOLA: 4 Men Arrested So Far in ...
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Q: Is there support for transactions in SQLite for android? Is there support for transactions in SQLite for android ? I need to insert some data in two tables or to inform user if it fails. I need transaction for that. How to do this ?

A: SQLiteDatabase has functions beginTransaction, setTransactionSuccessfull and endTransaction. Use them.

A: Here is documentation about possible transactions and correct using


Pre-Natal Massage is safe. Yes, you read that right, and at all stages of pregnancy. So now that we're past that, let's talk about why it's so great! Pre-Natal Massage helps with stress, pain, tension, and overall feels really good. And for expecting mothers, we know that is highly sought after!
Make sure your therapist has been trained to work with expecting women.
This is a biggy. Being pregnant is a huge life change, and you want to KNOW that your therapist knows how to safely work on you, all while keeping you comfortable.
I have been trained in Pre-Natal Massage. Not only did we learn how in the class room, but we also had volunteers come in to receive pre-natal massage with instructors on hand for questions. We learned a lot about how to position a pregnant woman, what is not safe to do during pregnancy, and how to keep her as comfortable as possible. Of course, it's always a good idea to check with your doctor and your massage therapist to ensure that you don't have any pregnancy related conditions that would contraindicate massage therapy for you. Most women experiencing a healthy pregnancy can and should enjoy regular massage sessions.
Not only have I been trained in to work with pregnant women, I have been around them my whole life. (I'm the oldest of 16 kids in my family.) Not only that, but I have two kids of my own and received massage for the entirety of both pregnancies.
Pregnant women can greatly benefit from massage therapy! If you have been, or are pregnant, you know that you can often experience a lot of aches and pains as your pregnancy progresses. Many women suffer from back pain, hip & sciatic pain, headaches, and tired legs & feet.
Going to your massage therapist once or twice a month can help with the symptoms caused by pregnancy, and it can even help you sleep better.
In my own experience, I was a lot happier after having body work done. Yes, it felt great, but I also was less sore, my legs ached less, I had less calf cramps, I slept better. Who wouldn't want those things?!
For the most part, your massage will be the same as when you weren't pregnant. There are a few different changes though. The biggest one will be positioning once you aren't comfortable on your stomach. At that point, I will have you lay on your side and give you lots of pillows for support. This will most likely be in the second trimester and beyond. The second thing is I won't go as deep. I can still use quite a bit of pressure, but not as much. My most important concern is that you are comfortable.
For what you're going through, you totally deserve to come in and relax. You deserve to have an awesome pregnancy. Give your body a break, get a massage. You will wonder why you didn't get one sooner!


We had ourselves a little festive fall cookout at headquarters this week! Enjoy your last weekend before Halloween!
Fun photos from our Annual Picnic last month! We had Funny Faces on site to create balloon sculptures and apply glitter tattoos for kids of all ages! We love our KL Family!
Photos of KL Engineering's Jacob Joyal and WisDOT's Ahmet Demirbilek during their presentation at the ASCE Annual Meeting last month. They discussed how the WisDOT Statewide LED Retrofit Implementation Plan is modernizing and upgrading the State's roadway lighting systems. Learn more in the WisDOT's October issue of The Connector and in our previous post.
We welcome Justin Staudt to the KL Family! He is our new Surveyor at our Madison office. Justin graduated from Northern Illinois University last December with a BS in Geology and Environmental Geosciences. We're glad to have you on our team!


Select one of two options that will appear, Simple DNS Zone Editor and/or Advanced DNS Zone Editor.
In the Name field, enter the prefix/first part of your custom domain (cdn, StackPath, or whatever you choose… do NOT enter cdn.mydomain.com, cPanel will auto-complete that for you.
In the CNAME box, add your temporary StackPath CDN domain site.company.stackpathdns.com, do NOT suffix it with a period/dot.
Click the Add CNAME Record button.
In the Name field, enter the prefix/first part of your custom domain (cdn, StackPath, or whatever you choose… do NOT enter cdn.mydomain.com, cPanel will auto-complete that for you.
n the TTL box, add 14400 (4 hours).
In the CNAME box, add your temporary CDN domain sitecompany.stackpathdns.com, do NOT suffix it with a period/dot.
Click the Add Record Button.
In the last box, add your temporary CDN domain site.company.stackpathdns.com, you MUST suffix it with a period/dot.
Scroll down to the Add Domain Records button.
In the box saying anything.com. replace that with your temporary StackPath CDN domain site.company.stackpathdns.com, you MUST suffix it with a period/dot.
Under the Public Network menu, Click Domain Name System then click Manage DNS.
Points to: Enter your Temporary StackPath CDN URL suffixed by a dot/period.
Log into your account at aws.amazon.com, click on My Account/Console, then Management Console.
Click on the Amazon Route53 tab.
Tick the checkbox next to your domain and from the top menu, click on Go To Record Sets.
From the top menu, click on Create Record Sets.
Value: Enter your Temporary StackPath CND URL suffixed by a dot/period.
Hover over the Products tab then click on List All Orders.
Log into your account at DNS Park.
Log into your MyDomain.com account.
Under Name, enter only the part of your website address that you designated for your StackPath CDN Site. For example, if you picked www.mydomain.com as your address, just enter CDN as the entry underName.
Enter the prefix of the address for your CDN Site, and click OK. Example: if you chose cdn.example.com you should enter cdn.
From the Add… drop-down menu of the HOST NAME table, choose Host Alias, and click theAdd button next to it.
Log into your Media Temple account at ac.mediatemple.net.
Enter your "Primary Domain", "Primary Email" and "Password" then click the "Login" button.
Log into your CloudFlare account at www.cloudflare.com.