202 research outputs found
The nuclear membrane in multidrug resistance: microinjection of epirubicin into bladder cancer cell lines
No full textObjevtive: to assess whether microinjecting epirubicin into cells showing multidrug resistance (MDR, common to many cancers, including bladder cancer, with resistance to, e.g. anthracyclines and mitomycin C) spares the nucleus, as when these drugs accumulate, distribution in MDR cells characteristically spares the nucleus, suggesting that the nuclear membrane is responsible for excluding cytotoxic drugs from MDR nuclei.Materials and methods: nuclear exclusion of drugs is an important feature of resistance in MDR cells, as many MDR-susceptible drugs have cytotoxic actions within the nucleus. Drug accumulation in 'classical' P-glycoprotein-mediated MDR cells is greatly reduced by efflux. Microinjection of epirubicin into the cytoplasm of MDR cells bypasses the P-glycoprotein efflux pump on the plasma membrane. Nuclear sparing would directly implicate the nuclear membrane in this phenomenon. Because of their fluorescence properties, which allow study by confocal microscopy and flow cytometry, anthracyclines have also been used extensively to investigate MDR. Thus sensitive (MGH-U1 and RT112) and MDR (MGH-U1R and MGH-U1-MMC) bladder cancer cell lines were used. Adherent cells from each cell line were individually microinjected with epirubicin (0.5 mg/mL) and a 77 kDa fluorescein isothiocyanate (FITC)-dextran (0.5 mg/mL). The pattern of nuclear epirubicin uptake in injected cells was then evaluated by confocal microscopy. The 77 kDa FITC-dextran allowed easier identification of injected cells and was also excluded from their nuclei.Results: sensitive bladder cancer cell lines all showed a nuclear accumulation pattern of epirubicin, consistent with their normal uptake after exposure to epirubicin. The MDR cell lines showed the characteristic nuclear-sparing pattern of epirubicin uptake, similar to the normal uptake pattern after epirubicin exposure. The 77 kDa FITC-dextran showed clearly which cells had been microinjected, and was excluded from the nuclei of all injected cells. Cell viability was confirmed by acridine-orange staining after initial visualization of injected cells.Conclusion: the nuclear membrane is responsible for the nuclear exclusion of epirubicin in MDR cells. Further work is necessary to determine the mechanisms involved
A statistical framework for quantifying clinical equipoise for individual cases during randomized controlled surgical trials
No full textBackground
Randomised controlled trials are being increasingly used to evaluate new surgical interventions. There are a number of problematic methodological issues specific to surgical trials, the most important being identifying whether patients are eligible for recruitment into the trial. This is in part due to the diversity in practice patterns across institutions and the enormous range of available interventions that often leads to a low level of agreement between clinicians about both the value and the appropriate choice of intervention. We argue that a clinician should offer patients the option of recruitment into a trial, even if the clinician is not individually in a position of equipoise, if there is collective (clinical) equipoise amongst the wider clinical community about the effectiveness of a proposed intervention (the clinical equipoise principle). We show how this process can work using data collected from an ongoing trial of a surgical intervention.
Results
We describe a statistical framework for the assessment of uncertainty prior to patient recruitment to a clinical trial using a panel of expert clinical assessors and techniques for eliciting, pooling and modelling of expert opinions. The methodology is illustrated using example data from the UK Heel Fracture Trial. The statistical modelling provided results that were clear and simple to present to clinicians and showed how decisions regarding recruitment were influenced by both the collective opinion of the expert panel and the type of decision rule selected.
Conclusions
The statistical framework presented has potential to identify eligible patients and assist in the simplification of eligibility criteria which might encourage greater participation in clinical trials evaluating surgical interventions
Design issues and extensions of multi-arm multi-stage clinical trials
No full textThe increasing cost of randomised controlled trials is hindering the rate at which new, effective therapies reach patients. To accelerate drug development, more efficient clinical trial designs are needed. One such design which has had success in speeding up the evaluation of therapies in cancer is the multi-arm multi-stage (MAMS) design. This particular design compares multiple new treatments against a control in a single trial, obviating the need for multiple two-arm studies, and ceases recruitment to poorly performing arms during the study. To further increase efficiency, interim assessments can be based on an intermediate outcome which is on the causal pathway to the primary outcome of the trial, thus allowing phases 2 and 3 of evaluation to be incorporated into a single, seamless design. The MAMS design was initially developed for trials in cancer where time to event outcomes are commonly used. To make it more widely applicable to other disease areas, we first extend the design to other types of outcome measure such as binary. The new designs are then applied to trials in tuberculosis --- a disease area with many new treatments currently in the clinical pipeline and which may therefore benefit from using more efficient trial designs. We then consider more general design issues such as familywise error rate and expected sample size and present calculations of both measures using simulation. Methods are developed for finding designs which have the desired overall operating characteristics and which are the most efficient under particular optimality criteria, known as admissible designs. Guidance is provided for choosing the number of stages and allocation ratio for a particular number of arms and we apply the methods developed in the thesis to existing and hypothetical MAMS trials. Throughout, Stata programs are created and updated to accommodate the use of the methods in practice
Waar is blokchain toepasbaar in de logistiek en wat doet dat met de waardepropositie?: Een basis voor een business-scan voor het mkb
No full textNieuwe digitale technieken bieden kansen om slimmer samen te werken en gegevens uit te wisselen voor het mkb. Blockchain technologie wordt daarbij genoemd als een van de meest kansrijke opkomende technologieën. Vanuit de Hogeschool Rotterdam en de Hogeschool Windesheim wordt onderzoek gedaan naar de kansen voor het mkb in het toepassen van de blockchain technologie. Het onderzoek richt zich met name op het mkb in de logistieke, agro-food en farma-sector. De mogelijkheden die blockchain-oplossingen bieden zijn veelbelovend. In het onderzoek zijn de belangrijkste vragen hierover: Welke invloed heeft de toepassing van blockchain op de toegevoegde waarde van de organisatie en op de machtsverhoudingen in de logistieke keten? Welke invloed heeft het op de stroom van goederen, informatie en transport? Het doel van het onderzoek is het komen tot een business-scan op basis waarvan een organisatie kan inschatten welke toegevoegde waarde de blockchain technologie kan hebben. Dit moet uiteindelijk leiden tot een stimulans voor deze branche ten behoeve van een betere concurrentiepositie.Transport and Logistic
A simulation study comparing the power of nine tests of the treatment effect in randomized controlled trials with a time-to-event outcome
No full textBackground: The logrank test is routinely applied to design and analyse randomized controlled trials (RCTs) with time-to-event outcomes. Sample size and power calculations assume the treatment effect follows proportional hazards (PH). If the PH assumption is false, power is reduced and interpretation of the hazard ratio (HR) as the estimated treatment effect is compromised. Using statistical simulation, we investigated the type 1 error and power of the logrank (LR)test and eight alternatives. We aimed to identify test(s) that improve power with three types of non-proportional hazards (non-PH): early, late or near-PH treatment effects. /
Methods: We investigated weighted logrank tests (early, LRE; late, LRL), the supremum logrank test (SupLR) and composite tests (joint, J; combined, C; weighted combined, WC; versatile and modified versatile weighted logrank, VWLR, VWLR2) with two or more components. Weighted logrank tests are intended to be sensitive to particular non-PH patterns. Composite tests attempt to improve power across a wider range of non-PH patterns. Using extensive simulations based on real trials, we studied test size and power under PH and under simple departures from PH comprising pointwise constant HRs with a single change point at various follow-up times. We systematically investigated the influence of high or low control-arm event rates on power. /
Results: With no preconceived type of treatment effect, the preferred test is VWLR2. Expecting an early effect, tests with acceptable power are SupLR, C, VWLR2, J, LRE and WC. Expecting a late effect, acceptable tests are LRL, VWLR, VWLR2, WC and J. Under near-PH, acceptable tests are LR, LRE, VWLR, C, VWLR2 and SupLR. Type 1 error was well controlled for all tests, showing only minor deviations from the nominal 5%. The location of the HR change point relative to the cumulative proportion of control-arm events considerably affected power. /
Conclusions: Assuming ignorance of the likely treatment effect, the best choice is VWLR2. Several non-standard tests performed well when the correct type of treatment effect was assumed. A low control-arm event rate reduced the power of weighted logrank tests targeting early effects. Test size was generally well controlled. Further investigation of test characteristics with different types of non-proportional hazards of the treatment effect is warranted
Waar is blokchain toepasbaar in de logistiek en wat doet dat met de waardepropositie?: Een basis voor een business scan voor het mkb
No full textNieuwe digitale technieken bieden kansen om slimmer samen te werken en gegevens uit te wisselen voor de mkb. Blockchaintechnologie wordt daarbij genoemd als een van de meest kansrijke opkomende technologieën. Vanuit de Hogeschool Rotterdam en de Hogeschool Windesheim wordt onderzoek gedaan naar de kansen voor het mkb in het toepassen van de blockchaintechnologie. Het onderzoek richt zich met name op het mkb in de logistieke, agro-food en farmasector. De mogelijkheden die blockchainoplossingen bieden zijn veelbelovend. In het onderzoek zijn de belangrijkste vragen hierover: Welke invloed heeft de toepassing van blockchain op de toegevoegde waarde van de organisatie en op de machtsverhoudingen in de logistieke keten? Welke invloed heeft het op de stroom van goederen, informatie en transport? Het doel van het onderzoek is het komen tot een business scan op basis waarvan een organisatie kan inschatten welke toegevoegde waarde de blockchaintechnologie kan hebben. Dit moet uiteindelijk leiden tot een stimulans voor deze branche ten behoeve van een betere concurrentiepositie. In de uitvoering van het onderzoek is behoefte aan een theoretische basis voor zo een business scan. Hiertoe is een literatuurstudie verricht op basis waarvan een eerste selectie is gedaan voor modellen en methoden in deze business scan. In deze literatuurstudie is gekozen voor een top-downbenadering. Eerst wordt vanuit strategisch perspectief gekeken naar de toegevoegde waarde om vervolgens vast te kunnen stellen welke machtsverhoudingen en kritische processen aanwezig zijn. Deze kritische processen kunnen dan nader bevraagd worden omwille van de toepasbaarheid van blockchain. Ten eerste zijn begrippen, zoals toegevoegde waarde, machtsverhoudingen en invloed op goederen-, geld- en informatiestromen gedefinieerd. Bij de definities wordt rekening gehouden met de strategische, tactische en operationele doelen van bedrijven. Het begrippenkader levert aanvullende vragen op waarmee richting gegeven wordt aan een selectie van methoden en modellen voor de business scan. Ten tweede zijn passende modellen en methoden geselecteerd. De aanvullende vragen die de literatuurstudie heeft opgeleverd, leggen een basis voor het effectief toepassen van de modellen en methoden in de business scan. Deze versie van de business scan is gericht op de genoemde mkb-organisaties die nog onvoldoende kennis hebben van mogelijke toepassingen van blockchaintechnologie. Op basis van de scan kunnen deze organisaties beoordelen of deze technologie toegevoegde waarde heeft voor hun processen.Transport and Logistic
Construction and validation of a prognostic model across several studies, with an application in superficial bladder cancer
No full textMany models for clinical prediction (prognosis or diagnosis) are published in the medical literature every year but few such models find their way into clinical practice. The reason may be that since in most cases models have not been validated in independent data, they lack generality and/or credibility. In this paper we consider the situation in which several compatible, independent data sets relating to a given disease with a time-to-event endpoint are available for analysis. The aim is to construct and evaluate a single prognostic model. Building a multivariable model from the available prognostic factors is accomplished within the Cox proportional hazards framework, stratifying by study. Non-linear relationships with continuous predictors are modelled by using fractional polynomials. To assess the discrimination or separation of a survival model, we use the D statistic of Royston and Sauerbrei. D may be interpreted as the separation (log hazard ratio) between the survival distributions for two independent prognostic groups. To evaluate the generality of a prognostic model across the data sets, we propose 'internal-external cross-validation' on D: each study is omitted in turn, the model parameters are estimated from the remaining studies and D is evaluated in the omitted study. Because the linear predictor of a survival model tells only part of the story, we also suggest a method for investigating heterogeneity in the baseline distribution function across studies which involves fitting completely specified, flexible parametric survival models (Royston and Parmar). Our final models combine the prognostic index (obtained with stratification by study) with the pooled baseline survival distribution (estimated parametrically). By applying this methodology, we construct two prognostic scores in superficial bladder cancer. The simpler of the two scores is more suited to clinical application. We show that a three-group prognostic classification scheme based on either score produces well-separated survival curves for each of the data sets, despite identifiable heterogeneity among the baseline distribution functions and to a lesser extent among the prognostic indexes for the individual studies. Copyright (C) 2004 John Wiley Sons, Ltd
Augmenting the logrank test in the design of clinical trials in which non-proportional hazards of the treatment effect may be anticipated
No full text© 2016 Royston and Parmar. Background: Most randomized controlled trials with a time-to-event outcome are designed assuming proportional hazards (PH) of the treatment effect. The sample size calculation is based on a logrank test. However, non-proportional hazards are increasingly common. At analysis, the estimated hazards ratio with a confidence interval is usually presented. The estimate is often obtained from a Cox PH model with treatment as a covariate. If non-proportional hazards are present, the logrank and equivalent Cox tests may lose power. To safeguard power, we previously suggested a 'joint test' combining the Cox test with a test of non-proportional hazards. Unfortunately, a larger sample size is needed to preserve power under PH. Here, we describe a novel test that unites the Cox test with a permutation test based on restricted mean survival time. Methods: We propose a combined hypothesis test based on a permutation test of the difference in restricted mean survival time across time. The test involves the minimum of the Cox and permutation test P-values. We approximate its null distribution and correct it for correlation between the two P-values. Using extensive simulations, we assess the type 1 error and power of the combined test under several scenarios and compare with other tests. We investigate powering a trial using the combined test. Results: The type 1 error of the combined test is close to nominal. Power under proportional hazards is slightly lower than for the Cox test. Enhanced power is available when the treatment difference shows an 'early effect', an initial separation of survival curves which diminishes over time. The power is reduced under a 'late effect', when little or no difference in survival curves is seen for an initial period and then a late separation occurs. We propose a method of powering a trial using the combined test. The 'insurance premium' offered by the combined test to safeguard power under non-PH represents about a single-digit percentage increase in sample size. Conclusions: The combined test increases trial power under an early treatment effect and protects power under other scenarios. Use of restricted mean survival time facilitates testing and displaying a generalized treatment effect
An approach to trial design and analysis in the era of non-proportional hazards of the treatment effect
No full textBackground: Most randomized controlled trials with a time-to-event outcome are designed and analysed under the proportional hazards assumption, with a target hazard ratio for the treatment effect in mind. However, the hazards may be non-proportional. We address how to design a trial under such conditions, and how to analyse the results. Methods: We propose to extend the usual approach, a logrank test, to also include the Grambsch-Therneau test of proportional hazards. We test the resulting composite null hypothesis using a joint test for the hazard ratio and for time-dependent behaviour of the hazard ratio. We compute the power and sample size for the logrank test under proportional hazards, and from that we compute the power of the joint test. For the estimation of relevant quantities from the trial data, various models could be used; we advocate adopting a pre-specified flexible parametric survival model that supports time-dependent behaviour of the hazard ratio. Results: We present the mathematics for calculating the power and sample size for the joint test. We illustrate the methodology in real data from two randomized trials, one in ovarian cancer and the other in treating cellulitis. We show selected estimates and their uncertainty derived from the advocated flexible parametric model. We demonstrate in a small simulation study that when a treatment effect either increases or decreases over time, the joint test can outperform the logrank test in the presence of both patterns of non-proportional hazards. Conclusions: Those designing and analysing trials in the era of non-proportional hazards need to acknowledge that a more complex type of treatment effect is becoming more common. Our method for the design of the trial retains the tools familiar in the standard methodology based on the logrank test, and extends it to incorporate a joint test of the null hypothesis with power against non-proportional hazards. For the analysis of trial data, we propose the use of a pre-specified flexible parametric model that can represent a time-dependent hazard ratio if one is present
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