440 research outputs found
Combining estimates of interest in prognostic modelling studies after multiple imputation: current practice and guidelines
Background: Multiple imputation (MI) provides an effective approach to handle missing covariate
data within prognostic modelling studies, as it can properly account for the missing data
uncertainty. The multiply imputed datasets are each analysed using standard prognostic modelling
techniques to obtain the estimates of interest. The estimates from each imputed dataset are then
combined into one overall estimate and variance, incorporating both the within and between
imputation variability. Rubin's rules for combining these multiply imputed estimates are based on
asymptotic theory. The resulting combined estimates may be more accurate if the posterior
distribution of the population parameter of interest is better approximated by the normal
distribution. However, the normality assumption may not be appropriate for all the parameters of
interest when analysing prognostic modelling studies, such as predicted survival probabilities and
model performance measures.
Methods: Guidelines for combining the estimates of interest when analysing prognostic modelling
studies are provided. A literature review is performed to identify current practice for combining
such estimates in prognostic modelling studies.
Results: Methods for combining all reported estimates after MI were not well reported in the
current literature. Rubin's rules without applying any transformations were the standard approach
used, when any method was stated.
Conclusion: The proposed simple guidelines for combining estimates after MI may lead to a wider
and more appropriate use of MI in future prognostic modelling studies
Using ordinal logistic regression to evaluate the performance of laser-Doppler predictions of burn-healing time
Background
Laser-Doppler imaging (LDI) of cutaneous blood flow is beginning to be used by burn surgeons to predict the healing time of burn wounds; predicted healing time is used to determine wound treatment as either dressings or surgery. In this paper, we do a statistical analysis of the performance of the technique.
Methods
We used data from a study carried out by five burn centers: LDI was done once between days 2 to 5 post burn, and healing was assessed at both 14 days and 21 days post burn. Random-effects ordinal logistic regression and other models such as the continuation ratio model were used to model healing-time as a function of the LDI data, and of demographic and wound history variables. Statistical methods were also used to study the false-color palette, which enables the laser-Doppler imager to be used by clinicians as a decision-support tool.
Results
Overall performance is that diagnoses are over 90% correct. Related questions addressed were what was the best blood flow summary statistic and whether, given the blood flow measurements, demographic and observational variables had any additional predictive power (age, sex, race, % total body surface area burned (%TBSA), site and cause of burn, day of LDI scan, burn center). It was found that mean laser-Doppler flux over a wound area was the best statistic, and that, given the same mean flux, women recover slightly more slowly than men. Further, the likely degradation in predictive performance on moving to a patient group with larger %TBSA than those in the data sample was studied, and shown to be small.
Conclusion
Modeling healing time is a complex statistical problem, with random effects due to multiple burn areas per individual, and censoring caused by patients missing hospital visits and undergoing surgery. This analysis applies state-of-the art statistical methods such as the bootstrap and permutation tests to a medical problem of topical interest. New medical findings are that age and %TBSA are not important predictors of healing time when the LDI results are known, whereas gender does influence recovery time, even when blood flow is controlled for.
The conclusion regarding the palette is that an optimum three-color palette can be chosen 'automatically', but the optimum choice of a 5-color palette cannot be made solely by optimizing the percentage of correct diagnoses
Perioperative provider safety in the pandemic : Development, implementation and evaluation of an adjunct COVID-19 Surgical Patient Checklist
We would like to acknowledge Eliana Lillevik, Luciano Barbosa, Daniela Farchi, Dr Laila Woc-Colburn, Dr Gustavo Moraes, Suko Dwi Nugroho, Nguyen Tri Dung, Dr Rong Hu, Priya Desai and Senait Bitew for their contributions to language translations, survey distribution and data collection. Funding The authors disclosed receipt of the following financial support for the research, authorship, and publication of this article: NS received salary support during the conduct of this study from NIH Fogarty International Center (Global Health Equity Scholars NIH FIC D43TW010540).Peer reviewedPublisher PD
Suitability of PSA-detected localised prostate cancers for focal therapy: Experience from the ProtecT study
This article is available through a Creative Commons Attribution-NonCommercial-Share Alike 3.0 Unported License. Copyright @ 2011 Cancer Research UK.Background: Contemporary screening for prostate cancer frequently identifies small volume, low-grade lesions. Some clinicians have advocated focal prostatic ablation as an alternative to more aggressive interventions to manage these lesions. To identify which patients might benefit from focal ablative techniques, we analysed the surgical specimens of a large sample of population-detected men undergoing radical prostatectomy as part of a randomised clinical trial. Methods: Surgical specimens from 525 men who underwent prostatectomy within the ProtecT study were analysed to determine tumour volume, location and grade. These findings were compared with information available in the biopsy specimen to examine whether focal therapy could be provided appropriately. Results: Solitary cancers were found in prostatectomy specimens from 19% (100 out of 525) of men. In addition, 73 out of 425 (17%) men had multiple cancers with a solitary significant tumour focus. Thus, 173 out of 525 (33%) men had tumours potentially suitable for focal therapy. The majority of these were small, well-differentiated lesions that appeared to be pathologically insignificant (38–66%). Criteria used to select patients for focal prostatic ablation underestimated the cancer's significance in 26% (34 out of 130) of men and resulted in overtreatment in more than half. Only 18% (24 out of 130) of men presumed eligible for focal therapy, actually had significant solitary lesions. Conclusion: Focal therapy appears inappropriate for the majority of men presenting with prostate-specific antigen-detected localised prostate cancer. Unifocal prostate cancers suitable for focal ablation are difficult to identify pre-operatively using biopsy alone. Most lesions meeting criteria for focal ablation were either more aggressive than expected or posed little threat of progression.National Institute for Health Researc
Electrical behavior of MIS devices based on Si nanoclusters embedded in SiOxNy and SiO2 films
We examined and compared the electrical properties of silica (SiO2) and silicon oxynitride (SiOxNy) layers embedding silicon nanoclusters (Sinc) integrated in metal-insulator-semiconductor (MIS) devices. The technique used for the deposition of such layers is the reactive magnetron sputtering of a pure SiO2 target under a mixture of hydrogen/argon plasma in which nitrogen is incorporated in the case of SiOxNy layer. Al/SiOxNy-Sinc/p-Si and Al/SiO2-Sinc/p-Si devices were fabricated and electrically characterized. Results showed a high rectification ratio (>104) for the SiOxNy-based device and a resistive behavior when nitrogen was not incorporating (SiO2-based device). For rectifier devices, the ideality factor depends on the SiOxNy layer thickness. The conduction mechanisms of both MIS diode structures were studied by analyzing thermal and bias dependences of the carriers transport in relation with the nitrogen content
A computational approach to compare regression modelling strategies in prediction research
Minimum sample size for external validation of a clinical prediction model with a binary outcome
In prediction model research, external validation is needed to examine an existing model's performance using data independent to that for model development. Current external validation studies often suffer from small sample sizes and consequently imprecise predictive performance estimates. To address this, we propose how to determine the minimum sample size needed for a new external validation study of a prediction model for a binary outcome. Our calculations aim to precisely estimate calibration (Observed/Expected and calibration slope), discrimination (C-statistic), and clinical utility (net benefit). For each measure, we propose closed-form and iterative solutions for calculating the minimum sample size required. These require specifying: (i) target SEs (confidence interval widths) for each estimate of interest, (ii) the anticipated outcome event proportion in the validation population, (iii) the prediction model's anticipated (mis)calibration and variance of linear predictor values in the validation population, and (iv) potential risk thresholds for clinical decision-making. The calculations can also be used to inform whether the sample size of an existing (already collected) dataset is adequate for external validation. We illustrate our proposal for external validation of a prediction model for mechanical heart valve failure with an expected outcome event proportion of 0.018. Calculations suggest at least 9835 participants (177 events) are required to precisely estimate the calibration and discrimination measures, with this number driven by the calibration slope criterion, which we anticipate will often be the case. Also, 6443 participants (116 events) are required to precisely estimate net benefit at a risk threshold of 8%. Software code is provided.</p
CD4+ T Cell Effects on CD8+ T Cell Location Defined Using Bioluminescence
T lymphocytes of the CD8+ class are critical in delivering cytotoxic function and in controlling viral and intracellular infections. These cells are “helped” by T lymphocytes of the CD4+ class, which facilitate their activation, clonal expansion, full differentiation and the persistence of memory. In this study we investigated the impact of CD4+ T cells on the location of CD8+ T cells, using antibody-mediated CD4+ T cell depletion and imaging the antigen-driven redistribution of bioluminescent CD8+ T cells in living mice. We documented that CD4+ T cells influence the biodistribution of CD8+ T cells, favoring their localization to abdominal lymph nodes. Flow cytometric analysis revealed that this was associated with an increase in the expression of specific integrins. The presence of CD4+ T cells at the time of initial CD8+ T cell activation also influences their biodistribution in the memory phase. Based on these results, we propose the model that one of the functions of CD4+ T cell “help” is to program the homing potential of CD8+ T cells
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