Bayesian statistics in oncology: a guide for the clinical investigator

The rise of evidence-based medicine as well as important progress in statistical methods and computational power have led to a second birth of the >200-year-old Bayesian framework. The use of Bayesian techniques, in particular in the design and interpretation of clinical trials, offers several substantial advantages over the classical statistical approach. First, in contrast to classical statistics, Bayesian analysis allows a direct statement regarding the probability that a treatment was beneficial. Second, Bayesian statistics allow the researcher to incorporate any prior information in the analysis of the experimental results. Third, Bayesian methods can efficiently handle complex statistical models, which are suited for advanced clinical trial designs. Finally, Bayesian statistics encourage a thorough consideration and presentation of the assumptions underlying an analysis, which enables the reader to fully appraise the authors' conclusions. Both Bayesian and classical statistics have their respective strengths and limitations and should be viewed as being complementary to each other; we do not attempt to make a head-to-head comparison, as this is beyond the scope of the present review. Rather, the objective of the present article is to provide a nonmathematical, reader-friendly overview of the current practice of Bayesian statistics coupled with numerous intuitive examples from the field of oncology. It is hoped that this educational review will be a useful resource to the oncologist and result in a better understanding of the scope, strengths, and limitations of the Bayesian approach.

Accounting for baseline differences and measurement error in the analysis of change over time

If change over time is compared in several groups, it is important to take into account baseline values so that the comparison is carried out under the same preconditions. As the observed baseline measurements are distorted by measurement error, it may not be sufficient to include them as covariate. By fitting a longitudinal mixed-effects model to all data including the baseline observations and subsequently calculating the expected change conditional on the underlying baseline value, a solution to this problem has been provided recently so that groups with the same baseline characteristics can be compared. In this article, we present an extended approach where a broader set of models can be used. Specifically, it is possible to include any desired set of interactions between the time variable and the other covariates, and also, time-dependent covariates can be included. Additionally, we extend the method to adjust for baseline measurement error of other time-varying covariates. We apply the methodology to data from the Swiss HIV Cohort Study to address the question if a joint infection with HIV-1 and hepatitis C virus leads to a slower increase of CD4 lymphocyte counts over time after the start of antiretroviral therapy.

Assessing the Potential of Multiple Imputation in Sequence Analysis

Sequence analysis and optimal matching are useful heuristic tools for the descriptive analysis of heterogeneous individual pathways such as educational careers, job sequences or patterns of family formation. However, to date it remains unclear how to handle the inevitable problems caused by missing values with regard to such analysis. Multiple Imputation (MI) offers a possible solution for this problem but it has not been tested in the context of sequence analysis. Against this background, we contribute to the literature by assessing the potential of MI in the context of sequence analyses using an empirical example. Methodologically, we draw upon the work of Brendan Halpin and extend it to additional types of missing value patterns. Our empirical case is a sequence analysis of panel data with substantial attrition that examines the typical patterns and the persistence of sex segregation in school-to-work transitions in Switzerland. The preliminary results indicate that MI is a valuable methodology for handling missing values due to panel mortality in the context of sequence analysis. MI is especially useful in facilitating a sound interpretation of the resulting sequence types.

Flexibility Properties in Complex Analysis and Affine Algebraic Geometry

In the last decades affine algebraic varieties and Stein manifolds with big (infinite-dimensional) automorphism groups have been intensively studied. Several notions expressing that the automorphisms group is big have been proposed. All of them imply that the manifold in question is an Oka–Forstnerič manifold. This important notion has also recently merged from the intensive studies around the homotopy principle in Complex Analysis. This homotopy principle, which goes back to the 1930s, has had an enormous impact on the development of the area of Several Complex Variables and the number of its applications is constantly growing. In this overview chapter we present three classes of properties: (1) density property, (2) flexibility, and (3) Oka–Forstnerič. For each class we give the relevant definitions, its most significant features and explain the known implications between all these properties. Many difficult mathematical problems could be solved by applying the developed theory, we indicate some of the most spectacular ones.

In vivo analysis of uropod function during physiological T cell trafficking

Migrating lymphocytes acquire a polarized phenotype with a leading and a trailing edge, or uropod. Although in vitro experiments in cell lines or activated primary cell cultures have established that Rho-p160 coiled-coil kinase (ROCK)-myosin II-mediated uropod contractility is required for integrin de-adhesion on two-dimensional surfaces and nuclear propulsion through narrow pores in three-dimensional matrices, less is known about the role of these two events during the recirculation of primary, nonactivated lymphocytes. Using pharmacological antagonists of ROCK and myosin II, we report that inhibition of uropod contractility blocked integrin-independent mouse T cell migration through narrow, but not large, pores in vitro. T cell crawling on chemokine-coated endothelial cells under shear was severely impaired by ROCK inhibition, whereas transendothelial migration was only reduced through endothelial cells with high, but not low, barrier properties. Using three-dimensional thick-tissue imaging and dynamic two-photon microscopy of T cell motility in lymphoid tissue, we demonstrated a significant role for uropod contractility in intraluminal crawling and transendothelial migration through lymph node, but not bone marrow, endothelial cells. Finally, we demonstrated that ICAM-1, but not anatomical constraints or integrin-independent interactions, reduced parenchymal motility of inhibitor-treated T cells within the dense lymphoid microenvironment, thus assigning context-dependent roles for uropod contraction during lymphocyte recirculation.

Ultrasound-guided needle positioning in sensory nerve conduction study of the sural nerve

OBJECTIVES: To evaluate the usefulness of ultrasound imaging to improve the positioning of the recording needle for nerve conduction studies (NCS) of the sural nerve. METHODS: Orthodromic NCS of the sural nerve was performed in 44 consecutive patients evaluated for polyneuropathy. Ultrasound-guided needle positioning (USNP) was compared to conventional "blind" needle positioning (BNP), electrically guided needle positioning (EGNP), and to recordings with surface electrodes (SFN). RESULTS: The mean distance between the needle tip and the nerve was 1.1 mm with USNP compared to 5.1 mm with BNP (p<0.0001). The mean amplitude of the sensory nerve action potential (SNAP) was 21 microV with USNP and 11 microV with BNP (p<0.0001). Compared to BNP, nerve-needle distances and SNAP amplitudes did not improve with EGNP. SNAP amplitudes recorded with SFN were significantly smaller than with BNP, EGNP and USNP. CONCLUSION: Ultrasound increases the precision of needle positioning markedly, compared to conventional methods. The amplitude of the recorded SNAP is usually clearly greater using USNP. In addition, USNP is faster, less painful and less dependent on the patient. SIGNIFICANCE: USNP is superior to BNP, EGNP, and SFN in accurate measurement of SNAP amplitude. It has a potential use in the routine near-nerve needle sensory NCS of pure sensory nerves.

A case-control study of sporadic Creutzfeldt-Jakob disease in Switzerland: analysis of potential risk factors with regard to an increased CJD incidence in the years 2001-2004

BACKGROUND: In 2001, the observed annual mortality from Creutzfeldt-Jakob disease (CJD) in Switzerland increased from less than 1.5 to 2.6 per million inhabitants. An underlying cause could not be identified. METHODS: To analyse potential risk factors for sCJD in Switzerland, close relatives of 69 sCJD-patients and 224 frequency age-matched controls were interviewed in a case-control study using a standardised questionnaire. 135 potential risk factors including socio-demographics, medical history, occupation and diet were analysed by logistic regression adjusting for age, sex and education. RESULTS: sCJD patients were more likely to have travelled abroad, worked at an animal laboratory, undergone invasive dental treatment, orthopaedic surgery, ophthalmologic surgery after 1980, regular GP visits, taken medication regularly, and consumed kidney. No differences between patients and controls were found for residency, family history, and exposure to environmental and other dietary factors. CONCLUSION: Although some factors were significantly more frequent among sCJD-cases, this study did not reveal specific explanations for the increased incidence of deaths due to sporadic CJD observed in Switzerland since 2001. Results have to be interpreted with caution due to multiple testing and possible recall bias in association with a long incubation period. The most plausible reason for the increase in Swiss sCJD cases after 2000 is an improved case ascertainment. Therefore, underreporting of cases might well have occurred before the year 2001, and the "real" yearly incidence of sCJD might not be lower than, but rather above 2 per million inhabitants.

In vivo analysis of efavirenz metabolism in individuals with impaired CYP2A6 function

INTRODUCTION: The antiretroviral drug efavirenz (EFV) is extensively metabolized into three primary metabolites: 8-hydroxy-EFV, 7-hydroxy-EFV and N-glucuronide-EFV. There is a wide interindividual variability in EFV plasma exposure, explained to a great extent by cytochrome P450 2B6 (CYP2B6), the main isoenzyme responsible for EFV metabolism and involved in the major metabolic pathway (8-hydroxylation) and to a lesser extent in 7-hydroxylation. When CYP2B6 function is impaired, the relevance of CYP2A6, the main isoenzyme responsible for 7-hydroxylation may increase. We hypothesize that genetic variability in this gene may contribute to the particularly high, unexplained variability in EFV exposure in individuals with limited CYP2B6 function. METHODS: This study characterized CYP2A6 variation (14 alleles) in individuals (N=169) previously characterized for functional variants in CYP2B6 (18 alleles). Plasma concentrations of EFV and its primary metabolites (8-hydroxy-EFV, 7-hydroxy-EFV and N-glucuronide-EFV) were measured in different genetic backgrounds in vivo. RESULTS: The accessory metabolic pathway CYP2A6 has a critical role in limiting drug accumulation in individuals characterized as CYP2B6 slow metabolizers. CONCLUSION: Dual CYP2B6 and CYP2A6 slow metabolism occurs at significant frequency in various human populations, leading to extremely high EFV exposure.

Are clustering effects accounted for in statistical analysis in leading dental specialty journals?

OBJECTIVES In dental research multiple site observations within patients or taken at various time intervals are commonplace. These clustered observations are not independent; statistical analysis should be amended accordingly. This study aimed to assess whether adjustment for clustering effects during statistical analysis was undertaken in five specialty dental journals. METHODS Thirty recent consecutive issues of Orthodontics (OJ), Periodontology (PJ), Endodontology (EJ), Maxillofacial (MJ) and Paediatric Dentristry (PDJ) journals were hand searched. Articles requiring adjustment accounting for clustering effects were identified and statistical techniques used were scrutinized. RESULTS Of 559 studies considered to have inherent clustering effects, adjustment for this was made in the statistical analysis in 223 (39.1%). Studies published in the Periodontology specialty accounted for clustering effects in the statistical analysis more often than articles published in other journals (OJ vs. PJ: OR=0.21, 95% CI: 0.12, 0.37, p<0.001; MJ vs. PJ: OR=0.02, 95% CI: 0.00, 0.07, p<0.001; PDJ vs. PJ: OR=0.14, 95% CI: 0.07, 0.28, p<0.001; EJ vs. PJ: OR=0.11, 95% CI: 0.06, 0.22, p<0.001). A positive correlation was found between increasing prevalence of clustering effects in individual specialty journals and correct statistical handling of clustering (r=0.89). CONCLUSIONS The majority of studies in 5 dental specialty journals (60.9%) examined failed to account for clustering effects in statistical analysis where indicated, raising the possibility of inappropriate decreases in p-values and the risk of inappropriate inferences.