Effectiveness of adjuvant radiotherapy in patients with oropharyngeal and floor of mouth squamous cell carcinoma and concomitant histological verification of singular ipsilateral cervical lymph node metastasis (pN1-state) - A prospective multicenter randomized controlled clinical trial using a comprehensive cohort design

<p>Abstract</p> <p>Background</p> <p>Modern radiotherapy plays an important role in therapy of advanced head and neck carcinomas. However, no clinical studies have been published addressing the effectiveness of postoperative radiotherapy in patients with small tumor (pT1, pT2) and concomitant ipsilateral metastasis of a single lymph node (pN1), which would provide a basis for a general treatment recommendation.</p> <p>Methods/Design</p> <p>The present study is a non-blinded, prospective, multi-center randomized controlled trial (RCT). As the primary clinical endpoint, overall-survival in patients receiving postoperative radiation therapy vs. patients without adjuvant therapy following curative intended surgery is compared. The aim of the study is to enroll 560 adult males and females for 1:1 randomization to one of the two treatment arms (irradiation/no irradiation). Since patients with small tumor (T1/T2) but singular lymph node metastasis are rare and the amount of patients consenting to randomization is not predictable in advance, all patients rejecting randomization will be treated as preferred and enrolled in a prospective observational study (comprehensive cohort design) after giving informed consent. This observational part of the trial will be performed with maximum consistency to the treatment and observation protocol of the RCT. Because the impact of patient preference for a certain treatment option is not calculable, parallel design of RCT and observational study may provide a maximum of evidence and efficacy for evaluation of treatment outcome. Secondary clinical endpoints are as follows: incidence and time to tumor relapse (locoregional relapse, lymph node involvement and distant metastatic spread), Quality of life as reported by EORTC (QLQ-C30 with H&N 35 module), and time from operation to orofacial rehabilitation. All tumors represent a homogeneous clinical state and therefore additional investigation of protein expression levels within resection specimen may serve for establishment of surrogate parameters of patient outcome.</p> <p>Conclusion</p> <p>The inherent challenges of a rare clinical condition (pN1) and two substantially different therapy arms would limit the practicality of a classical randomized study. The concept of a Comprehensive Cohort Design combines the preference of a randomized study, with the option of careful data interpretation within an observational study.</p> <p>Trial registration</p> <p>ClinicalTrials.gov: NCT00964977</p

Comparison of the Andersen-Gill model with poisson and negative binomial regression on recurrent event data

Many generalizations of the Cox proportional hazard method have been elaborated to analyse recurrent event data. The Andersen-Gill model was proposed to handle event data following Poisson processes. This method is compared with non-survival approaches, such as Poisson and negative binomial regression. The comparison is performed on data simulated according to various event-generating processes and differing in subject heterogeneity. When robust standard error estimates are applied, for Poisson processes the Andersen-Gill approach is comparable to a negative binomial regression, whereas the poisson regression has comparable coverage probabilities of confidence intervals, but increased type I error rates; however, none of the methods can generate unbiased parameter estimates with data violating the independent increment assumption. These findings are illustrated by data from a clinical trial of the efficacy of a new pneumococcal vaccine for prevention of otitis media.

Exploring the variable importance in random forests under correlations: a general concept applied to donor organ quality in post-transplant survival

Abstract Random Forests are a powerful and frequently applied Machine Learning tool. The permutation variable importance (VIMP) has been proposed to improve the explainability of such a pure prediction model. It describes the expected increase in prediction error after randomly permuting a variable and disturbing its association with the outcome. However, VIMPs measure a variable’s marginal influence only, that can make its interpretation difficult or even misleading. In the present work we address the general need for improving the explainability of prediction models by exploring VIMPs in the presence of correlated variables. In particular, we propose to use a variable’s residual information for investigating if its permutation importance partially or totally originates from correlated predictors. Hypotheses tests are derived by a resampling algorithm that can further support results by providing test decisions and p-values. In simulation studies we show that the proposed test controls type I error rates. When applying the methods to a Random Forest analysis of post-transplant survival after kidney transplantation, the importance of kidney donor quality for predicting post-transplant survival is shown to be high. However, the transplant allocation policy introduces correlations with other well-known predictors, which raises the concern that the importance of kidney donor quality may simply originate from these predictors. By using the proposed method, this concern is addressed and it is demonstrated that kidney donor quality plays an important role in post-transplant survival, regardless of correlations with other predictors

A DAG-based comparison of interventional effect underestimation between composite endpoint and multi-state analysis in cardiovascular trials

Abstract Background Composite endpoints comprising hospital admissions and death are the primary outcome in many cardiovascular clinical trials. For statistical analysis, a Cox proportional hazards model for the time to first event is commonly applied. There is an ongoing debate on whether multiple episodes per individual should be incorporated into the primary analysis. While the advantages in terms of power are readily apparent, potential biases have been mostly overlooked so far. Methods Motivated by a randomized controlled clinical trial in heart failure patients, we use directed acyclic graphs (DAG) to investigate potential sources of bias in treatment effect estimates, depending on whether only the first or multiple episodes are considered. The biases first are explained in simplified examples and then more thoroughly investigated in simulation studies that mimic realistic patterns. Results Particularly the Cox model is prone to potentially severe selection bias and direct effect bias, resulting in underestimation when restricting the analysis to first events. We find that both kinds of bias can simultaneously be reduced by adequately incorporating recurrent events into the analysis model. Correspondingly, we point out appropriate proportional hazards-based multi-state models for decreasing bias and increasing power when analyzing multiple-episode composite endpoints in randomized clinical trials. Conclusions Incorporating multiple episodes per individual into the primary analysis can reduce the bias of a treatment’s total effect estimate. Our findings will help to move beyond the paradigm of considering first events only for approaches that use more information from the trial and augment interpretability, as has been called for in cardiovascular research

Bonfils intubation fibrescope : use in simulation-based intubation training for medical students in comparison to MacIntosh laryngoscope

BACKGROUND: A variety of instruments are used to perform airway management by tracheal intubation. In this study, we compared the MacIntosh balde (MB) laryngoscope with the Bonfils intubation fibrescope as intubation techniques. The aim of this study was to identify the technique (MB or Bonfils) that would allow students in their last year of medical school to perform tracheal intubation faster and with a higher success probability. Data were collected from 150 participants using an airway simulator [‘Laerdal Airway Management Trainer’ (Laerdal Medical AS, Stavanger, Norway)]. The participants were randomly assigned to a sequence of techniques to use. Four consecutive intubation ‘trials’ were performed with each technique. These trials were evaluated for differences in the following categories: the ‘time to successful ventilation‘, ‘success probability’ within 90 s,’time to visualisation’ of the vocal cords (glottis), and ‘quality of visualisation’ according to the Cormack and Lehane score (C&L, grade 1–4). The primary endpoint was the ‘time to successful ventilation‘in the fourth and final trial. RESULTS: There was no statistically significant difference in the ‘time to successful ventilation’ between the two techniques in trial 4 (‘time to successful ventilation’: median: MB: 16 s, Bonfils: 14 s, p = 0.244). However, the ‘success probability’ within 90 s was higher when using a Macintosh blade than when using a Bonfils (95 vs. 87 %). The glottis could be better visualised when using a Bonfils (C&L score of 1 (best view): MB: 41 %, Bonfils: 93 %), but visualisation was achieved more rapidly when using a Macintosh blade (median: ‘time to visualisation’: MB: 6 s, Bonfils: 8 s, p = 0.003). CONCLUSIONS: The time to ventilation using the MacIntosh blade and Bonfils mainly did to differ, however success probabilities and time to visualisation primary favoured the MacIntosh blade as intubation technique, although the Bonfils seem to have a steeper learning curve. The Bonfils is still a promising intubation technique and might be easier to learn as the MB, at least in a manikin

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Additional file 2. ‘Success probabilities’ of the female and male participants

Endexpiratory lung volume measurement correlates with the ventilation/perfusion mismatch in lung injured pigs

Abstract Background In acute respiratory respiratory distress syndrome (ARDS) a sustained mismatch of alveolar ventilation and perfusion (VA/Q) impairs the pulmonary gas exchange. Measurement of endexpiratory lung volume (EELV) by multiple breath-nitrogen washout/washin is a non-invasive, bedside technology to assess pulmonary function in mechanically ventilated patients. The present study examines the association between EELV changes and VA/Q distribution and the possibility to predict VA/Q normalization by means of EELV in a porcine model. Methods After approval of the state and institutional animal care committee 12 anesthetized pigs were randomized to ARDS either by bronchoalveolar lavage (n = 6) or oleic acid injection (n = 6). EELV, VA/Q ratios by multiple inert gas elimination and ventilation distribution by electrical impedance tomography were assessed at healthy state and at five different positive endexpiratory pressure (PEEP) steps in ARDS (0, 20, 15, 10, 5 cmH2O; each maintained for 30 min). Results VA/Q, EELV and tidal volume distribution all displayed the PEEP-induced recruitment in ARDS. We found a close correlation between VA/Q < 0.1 (representing shunt and low VA/Q units) and changes in EELV (spearman correlation coefficient −0.79). Logistic regression reveals the potential to predict VA/Q normalization (VA/Q < 0.1 less than 5%) from changes in EELV with an area under the curve of 0.89 with a 95%-CI of 0.81–0.96 in the receiver operating characteristic. Different lung injury models and recruitment characteristics did not influence these findings. Conclusion In a porcine ARDS model EELV measurement depicts PEEP-induced lung recruitment and is strongly associated with normalization of the VA/Q distribution in a model-independent fashion. Determination of EELV could be an intriguing addition in the context of lung protection strategies