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When treating patients with advanced non-small cell lung cancer (NSCLC) with tyrosine kinase inhibitors and chemotherapy, intercalated schedule with time separation between the two classes of drugs should avoid their mutual antagonism. In a survey of published trials, we focus on relation between eligibility criteria and effectiveness of intercalated treatment.

In population-based cancer studies, net survival is a crucial measure for population comparison purposes. However, alternative measures, namely the crude probability of death (CPr) and the number of life years lost (LYL) due to death according to different causes, are useful as complementary measures for reflecting different dimensions in terms of prognosis, treatment choice, or development of a control strategy. When the cause of death (COD) information is available, both measures can be estimated in competing risks setting using either cause-specific or subdistribution hazard regression models or with the pseudo-observation approach through direct modeling. We extended the pseudo-observation approach in order to model the CPr and the LYL due to different causes when information on COD is unavailable or unreliable (i.e., in relative survival setting). In a simulation study, we assessed the performance of the proposed approach in estimating regression parameters and examined models with different link functions that can provide an easier interpretation of the parameters. We showed that the pseudo-observation approach performs well for both measures and we illustrated their use on cervical cancer data from the England population-based cancer registry. A tutorial showing how to implement the method in R software is also provided. [ABSTRACT FROM AUTHOR]

The Mann-Whitney test is a commonly used non-parametric alternative of the two-sample t-test. Despite its frequent use, it is only rarely accompanied with confidence intervals of an effect size. If reported, the effect size is usually measured with the difference of medians or the shift of the two distribution locations. Neither of these two measures directly coincides with the test statistic of the Mann-Whitney test, so the interpretation of the test results and the confidence intervals may be importantly different. In this paper, we focus on the probability that random variable X is lower than random variable Y. This measure is often referred to as the degree of overlap or the probabilistic index; it is in one-to-one relationship with the Mann-Whitney test statistic. The measure equals the area under the ROC curve. Several methods have been proposed for the construction of the confidence interval for this measure, and we review the most promising ones and explain their ideas. We study the properties of different variance estimators and small sample problems of confidence intervals construction. We identify scenarios in which the existing approaches yield inadequate coverage probabilities. We conclude that the DeLong variance estimator is a reliable option regardless of the scenario, but confidence intervals should be constructed using the logit scale to avoid values above 1 or below 0 and the poor coverage probability that follows. A correction is needed for the case when all values from one sample are smaller than the values of the other. We propose a method that improves the coverage probability also in these cases. [ABSTRACT FROM AUTHOR]

A common goal in the analysis of the long-term survival related to a specific disease is to estimate a measure that is comparable between populations with different general population mortality. When cause of death is unavailable or unreliable, as for example in cancer registry studies, relative survival methodology is used-in addition to the mortality data of the patients, we use the data on the mortality of the general population. In this article, we focus on the marginal relative survival measure that summarizes the information about the disease-specific hazard. Under additional assumptions about latent times to death of each cause, this measure equals net survival. We propose a new approach to estimation based on pseudo-observations and derive two estimators of its variance. The properties of the new approach are assessed both theoretically and with simulations, showing practically no bias and a close to nominal coverage of the confidence intervals with the precise formula for the variance. The approximate formula for the variance has sufficiently good performance in large samples where the precise formula calculation becomes computationally intensive. Using bladder cancer data and simulations, we show that the behavior of the new approach is very close to that of the Pohar Perme estimator but has the important advantage of a simpler formula that does not require numerical integration and therefore lends itself more naturally to further extensions. [ABSTRACT FROM AUTHOR]

Different immunohistochemical algorithms for the classification of the activated B-cell (ABC) and germinal center B-cell (GCB) subtypes of diffuse large B-cell lymphoma (DLBCL) are applied in different laboratories. In the present study, 127 patients with DLCBL were investigated, all treated with rituximab and cyclophosphamide, hydroxydaunorubicin, oncovin and prednisone (CHOP) or CHOP-like regimens between April 2004 and December 2010. Multi-tumor tissue microarrays were prepared and were tested according to 4 algorithms: Hans; modified Hans; Choi; and modified Choi. For 39 patients, the flow cytometric quantification of CD19 and CD20 antigen expression was performed and the level of expression presented as molecules of equivalent soluble fluorochrome units. The Choi algorithm was demonstrated to be prognostic for OS and classified patients into the GCB subgroup with an HR of 0.91. No difference in the expression of the CD19 antigen between the ABC and GCB groups was observed, but the ABC subtype exhibited a decreased expression of the CD20 antigen compared with the GCB subtype. [ABSTRACT FROM AUTHOR]

Epigenetic dysregulation has been shown to limit functional capacity of aging hematopoietic stem cells, which may contribute to impaired outcome of hematopoietic stem cell-based therapies. The aim of our study was to gain better insight into the epigenetic profile of CD34+-enriched cell products intended for autologous CD34+ cell transplantation in patients with cardiomyopathy. We found global DNA methylation content significantly higher in immunoselected CD34+ cells compared to leukocytes in leukapheresis products (2.33 - 1.03% vs. 1.84 - 0.86%, p = 0.04). Global DNA hydroxymethylation content did not differ between CD34+ cells and leukocytes (p = 0.30). By measuring methylation levels of 94 stem cell transcription factors on a ready-to-use array, we identified 15 factors in which average promoter methylation was significantly different between leukocytes and CD34+ cells. The difference was highest for HOXC12 (58.18 - 6.47% vs. 13.34 - 24.18%, p = 0.0009) and NR2F2 (51.65 - 25.89% vs. 7.66 - 21.43%, p = 0.0045) genes. Our findings suggest that global DNA methylation and hydroxymethylation patterns as well as target methylation profile of selected genes in CD34+-enriched cell products do not differ significantly compared to leukapheresis products and, thus, can tell us little about the functional capacity and regenerative properties of CD34+ cells. Future studies should examine other CD34+ cell graft characteristics, which may serve as prognostic tools for autologous CD34+ cell transplantation. [ABSTRACT FROM AUTHOR]

Background: The relative survival field has seen a lot of development in the last decade, resulting in many different and even opposing suggestions on how to approach the analysis. Methods: We carefully define and explain the differences between the various measures of survival (overall survival, crude mortality, net survival and relative survival ratio) and study their differences using colon and prostate cancer data extracted from the national population-based cancer registry of Slovenia as well as simulated data. Results: The colon and prostate cancer data demonstrate clearly that when analysing population-based data, it is useful to split the overall mortality in crude probabilities of dying from cancer and from other causes. Complemented by net survival, it provides a complete picture of cancer survival in a given population. But when comparisons of different populations as defined for example by place or time are of interest, our simulated data demonstrate that net survival is the only measure to be used. Conclusions: The choice of the method should be done in two steps: first, one should determine the measure of interest and second, one should choose among the methods that estimate that measure consistently. [ABSTRACT FROM AUTHOR]

When analyzing time to disease recurrence, we sometimes need to work with data where all the recurrences are recorded, but no information is available on the possible deaths. This may occur when studying diseases of benign nature where patients are only seen at disease recurrences or in poorly-designed registries of benign diseases or medical device implantations without sufficient patient identifiers to obtain their dead/alive status at a later date. When the average time to disease recurrence is long enough in comparison with the expected survival of the patients, statistical analysis of such data can be significantly biased. Under the assumption that the expected survival of an individual is not influenced by the disease itself, general population mortality tables may be used to remove this bias. We show why the intuitive solution of simply imputing the patient's expected survival time does not give unbiased estimates of the usual quantities of interest in survival analysis and further explain that cumulative incidence function analysis does not require additional assumptions on general population mortality. We provide an alternative framework that allows unbiased estimation and introduce two new approaches: an iterative imputation method and a mortality adjusted at risk function. Their properties are carefully studied, with the results supported by simulations and illustrated on a real-world example. [ABSTRACT FROM AUTHOR]

The aim of the present case–control study was to evaluate the incidence of the (CAG)n AR polymorphism in Slovene polycystic ovary syndrome (PCOS) patients. The polymorphism was not found to be a major risk factor for the presence of PCOS and for hyperandrogenemia in PCOS. [Copyright &y& Elsevier]

Background: We performed a review of a large incident peritoneal dialysis cohort to establish the impact of current practice and that of switching to hemodialysis., Methods: Patients starting peritoneal dialysis between 2004 and 2010 were included and clinical data at start of dialysis recorded. Competing risk analysis and Cox proportional hazards model with time-varying covariate (technique failure) were used., Results: Of 286 patients (median age 57 years) followed for a median of 24.2 months, 76 were transplanted and 102 died. Outcome probabilities at 3 and 5 years respectively were 0.69 and 0.53 for patient survival (or transplantation) and 0.33 and 0.42 for technique failure. Peritonitis caused technique failure in 42%, but ultrafiltration failure accounted only for 6.3%. Davies comorbidity grade, creatinine and obesity (but not residual renal function or age) predicted technique failure. Due to peritonitis deaths, technique failure was an independent predictor of death hazard. When successful switch to hemodialysis (surviving more than 60 days after technique failure) and its timing were analyzed, no adverse impact on survival in adjusted analysis was found. However, hemodialysis via central venous line was associated with an elevated death hazard as compared to staying on peritoneal dialysis, or hemodialysis through a fistula (adjusted analysis hazard ratio 1.97 (1.02 - 3.80))., Conclusions: Once the patients survive the first 60 days after technique failure, the switch to hemodialysis does not adversely affect patient outcomes. The nature of vascular access has a significant impact on outcome after peritoneal dialysis failure., (Copyright © 2014 International Society for Peritoneal Dialysis.)

We review recent work on the application of pseudo-observations in survival and event history analysis. This includes regression models for parameters like the survival function in a single point, the restricted mean survival time and transition or state occupation probabilities in multi-state models, e.g. the competing risks cumulative incidence function. Graphical and numerical methods for assessing goodness-of-fit for hazard regression models and for the Fine-Gray model in competing risks studies based on pseudo-observations are also reviewed. Sensitivity to covariate-dependent censoring is studied. The methods are illustrated using a data set from bone marrow transplantation.

The purpose of this study was to evaluate whether any of the following factors are related to knee anterior laxity in healthy sportswomen: anthropometric characteristics, lower limb alignment characteristics, hormone-related factors and sport history. Six hundred and sixteen sportswomen were tested in the pre-season. The data have been analysed using linear regression for possible association of knee anterior laxity with other variables. Univariate linear regression indicated a positive association of knee anterior laxity with knee extension and navicular drop and a negative association with body height. Multivariate linear regression analysis showed statistically significant associations between knee anterior laxity and the combination of passive knee extension and the chosen sport (R(2)=0.089; p<0.05). The combination of passive knee extension and sport type was found to be related to the amount of knee anterior laxity, although the association was weak with this combination of factors able to explain only about 9% of the variability in laxity. Knowing which factors influence the amount of knee anterior laxity will help us to better interpret the results of knee anterior laxity testing and help us to understand the possible role of knee anterior laxity as a risk factor for knee injury.