Background: To date, little is known about treatment preferences for depression concerning new media. This study aims to (1) investigate treatment preferences for depression including internet-based interventions and (2) examine subgroup differences concerning age, gender and severity of depression as well as patient-related factors associated with treatment preferences.Methods: Data were derived from the baseline assessment of the @ktiv-trial. Depression treatment preferences were assessed from n = 641 primary care patients with mild to moderate depression regarding the following treatments: medication, psychotherapy, combined treatment, alternative treatment, talking to friends and family, exercise, self-help literature, and internet-based interventions. Depression severity was specified by GPs according to ICD-10 criteria. Ordinal logistic regression models were conducted to identify associated factors of treatment preferences.Results: Patients had a mean age of 43.9 years (SD = 13.8) and more than two thirds (68.6%) were female. About 43% of patients had mild depression while 57% were diagnosed with moderate depression. The majority of patients reported strong preferences for psychotherapy, talking to friends and family, and exercise. About one in five patients was very likely to consider internet-based interventions in case of depression. Younger patients expressed significantly stronger treatment preferences for psychotherapy and internet-based interventions than older patients. The most salient factors associated with treatment preferences were the patients' education and perceived self-efficacy.Conclusions: Patients with depression report individually different treatment preferences.Our results underline the importance of shared decision-making within primary care. Future studies should investigate treatment preferences for different types of internet-based interventions. Depression is a common, but often unrecognized and under-treated condition in primary care . AccordiPatients' preferences regarding a specific depression treatment may not only influence patients' treatment satisfaction, but may also have major implications for treatment adherence and outcome , 8. ThusNevertheless, studies regarding treatment preferences for depression as well as associated factors in primary care settings are rare and so far have mainly focused on comparing psychotherapy and pharmacotherapy as preferred treatments , 12. ThiThe present study therefore aims to investigate the following research questions:What are treatment preferences for depression in primary care patients?Are there subgroup differences in treatment preferences concerning gender, age and severity of depression?Which sociodemographic, work-related and illness-related variables are associated with different treatment preferences for depression in primary care patients?To what extent are internet-based interventions for depression preferred by primary care patients and which variables are associated with preferences for new media based approaches?Data were derived from the @ktiv-trial . The trial was approved by the institutional review boards (Ethics Committees) of the University of Leipzig (reference number 222/14ff) and of the Australian National University (reference number 2013/342). The @ktiv-trial consists of a baseline assessment followed by a 6 week and a 6 month follow-up. The present study focuses on the analysis of cross-sectional data from the baseline assessment.Patients were recruited from 112 primary care practices in Central Germany and had to fulfill the following criteria: (1) age of 18 years and above, (2) positive screening for mild to moderately severe depressive symptoms according to the 9 item version of the Patient Health Questionnaire (PHQ-9) with a total score between 5 and 19 points, (3) mild or moderate depression according to the GP's diagnosis based on ICD-10 criteria , (4) German as first language, and (5) home internet access and regular use of the Internet. Patients were excluded in case of (1) severe or persistent depression , (2) organic mental disorders (ICD-10: F00-F09), (3) alcohol or drug dependence , (4) schizophrenia and schizoaffective disorders (F20-F29), (5) bipolar disorders (F31), (6) suicidality, (7) fatal somatic disease , (8) current grief (due to recent loss of a beloved person), and/or (9) receiving psychotherapy at the time of recruitment.N = 647 patients filled in a written self-report questionnaire in the primary care practice for baseline assessment. Recruitment of patients was conducted between February 1, 2014 and August 31, 2015.After giving written consent The patient self-report questionnaire comprised a wide-ranging set of structured scales and variables.Treatment preferences were assessed using an adapted 8-item rating scale based on previous research , 17 withSociodemographic data included the patients' age, gender, marital status  and educational level according to the new CASMIN educational classification system . For worAs part of the recruitment process GPs were asked to specify the severity of depression, i.e., whether patients had mild or moderate depression according to ICD-10 criteria.Other illness-related variables were collected from the patients' self-report. Patients were asked to indicate whether they had ever received treatment due to emotional stress  before . Comorbid panic disorder  and/or generalized anxiety disorder  according to ICD-10 criteria were assessed with the Patient Health Questionnaire  to 7.8% (comorbid PD) and were replaced using multiple imputation by chained equations  to reduce multicollinearity. The proportionality of odds assumption was fulfilled in all ordinal regression models as suggested by approximate likelihood ratio tests of proportionality of odds (Descriptive data are presented as mean with standard deviation (SD) or absolute frequencies and percentages. Subgroup analyses were performed for gender, age, and severity of depression. Age was divided into three groups  to indicate age-related differences. Subgroup comparisons were evaluated using Wilcoxon two-sample tests or Cuzick's  trend te of odds .p-value below 0.01.All statistical analyses were performed using the Statistical Package for the Social Sciences 24.0 for Windows  or Stata 13.1 SE . Given the total number of eight models tested, all analyses are based on a more stringent level of significance with a SD = 13.8) with the following distribution of age groups: 21.5% (18–30 years), 43.8% (31–50 years) and 34.6% (51–82 years). Regarding older patients, n = 35 (5.5%) individuals in our sample were 65+ years of age and n = 9 (1.5%) were older than 75 years. More than two thirds (68.6%) of the patients were female. The majority of patients were either married (42.8%) or single (41.2%), had medium education (55.9%) and completed an apprenticeship (57.9%). 43.4% of patients had mild and 56.6% had moderate depression according to their GP. Two in three (67%) patients reported that they had been treated for emotional stress before, about one out of four patients had a comorbid panic disorder (27.0%) and 22.9% had a comorbid generalized anxiety disorder. Mean values for self-efficacy (EPAS) and HRQOL (EQ-5D-5L) were 11.9 (SD = 4.5) and 74.4 (SD = 13.4), respectively.Table Figure SD = 1.4) for psychotherapy, 3.6 (SD = 1.4) for talking to friends and family, 3.5 (SD = 1.3) for exercise, 3.1 (SD = 1.4) for combined treatment, 3.0 (SD = 1.5) for medication, 2.9 for self-help literature (SD = 1.4), alternative treatment (SD = 1.4) and internet-based interventions (SD = 1.5).The mean preference strengths were 3.7  and self-help literature  with females showing stronger preferences for these treatment options than men. Regarding age-related differences younger patients preferred psychotherapy to a greater extent than older patients . Patients with moderate depression showed higher preference for medication as a treatment option than patients with mild depression .Table Whereas several sociodemographic and illness-related variables were associated with treatment preferences for depression, work-related variables, i.e., the patients' vocational qualification did not show significant impact on any treatment option Table .The patients' educational level was significantly associated with treatment preferences for psychotherapy, exercise and self-help literature. Hence, patients with a higher academic education were more likely to prefer these treatment options. For example, patients with a high educational level had 2.27  higher odds for preferring psychotherapy than patients with a low educational level, given that all other variables in the model are held constant. Gender was associated with alternative treatment and self-help literature. Thus, women had 1/0.63 = 1.59 higher odds  for expressing stronger preference toward alternative treatment and 1/0.66 = 1.52 higher odds  for preferring self-help literature. The patients' marital status emerged as a factor that was significantly associated with a higher preference for psychotherapy as singles were more likely to favor psychotherapy than married patients .Patients scoring higher on the EPAS hope and self-efficacy subscale were less likely to prefer medication  or combined treatment , but had higher odds for exercise  or talking to friends and family . Having a comorbid general anxiety disorder increased the willingness to seek alternative treatment  and internet-based interventions . Finally, patients who had not received treatment due to emotional stress in the past were more likely to score high on medication  or combined treatment  than patients who did receive help due to psychological problems before. The following illness-related factors were not significantly associated with any treatment preference: severity of depression, comorbid panic disorder and HRQOL.z = −4.30, p < 0.001). Patients with moderate depression were more likely to prefer internet-based interventions than patients with mild depression , even though this was not significant given the significance level of p < 0.01. Associated factors for internet-based interventions were the patients' age, educational level and having a comorbid anxiety disorder. Thus, younger patients were significantly more likely to express stronger acceptance toward internet-based interventions than older patients . In addition, patients with a high educational level had 3.10  higher odds of scoring higher on internet-based interventions than patients with a low educational level. Finally, those with a comorbid general anxiety disorder had higher preferences for internet-based interventions .About 38% of the patients were likely or very likely to consider internet-based interventions in case of depression. In contrast, 42% of the patients were unlikely or very unlikely to prefer internet-based interventions for the treatment of depression. Subgroup differences were found for age, as younger patients expressed a stronger treatment preference for internet-based interventions than older patients . Our observed mean values for psychotherapy and medication are in line with Raue et al.  who founn = 417 participants who had sought help for depression from family or friends filled in a questionnaire about advantages and disadvantages of informal support. The most frequently reported benefit was social support with emotional support being the most commonly cited type of support, followed by informational, companionship and instrumental support. On the other hand, the most salient barriers in seeking help from a confidant were seen in issues of stigma, such as stigmatizing responses or anticipated stigma, as well as inappropriate support and lack of knowledge, training and expertise.Our finding for highly favorable preferences toward other treatment options such as talking to friends and family is supported by previous research reporting that individuals prefer informal help from a confidant to formal sources of help , 38, 39.Regarding physical exercise, a Cochrane review  includinWe found no gender-related differences regarding treatment preferences for psychotherapy which is in contrast with many previous studies indicating that women are more likely than men to favor psychotherapy , 45, 46.Our finding that younger age groups were more likely than older patients to prefer psychotherapy is supported by Boehlen et al.  showing Regarding severity of depression, we found that more severe depression was associated with stronger preferences for the intake of medication. This may be due to higher psychological strain in stronger affected patients. In line with this finding, Berner et al.  found thThe patients' educational level was the most salient sociodemographic factor associated with treatment preferences for depression. Accordingly, a higher educational level was associated with stronger treatment preferences. Likewise, patients with higher education have been found to use face-to-face psychotherapy more frequently than patients with lower education . This maIn accordance with subgroup analyses within the present study, female gender was associated with increased preferences for alternative therapy and self-help literature. Another sociodemographic factor influencing treatment preference was the patients' marital status. The finding that singles were more likely to express more preferences for psychotherapy than married patients may be explained by lacking emotional support from the spouse in patients without a partner, leading to a stronger wish to talk to a psychotherapist and receive professional support . FurtherConcerning illness-related factors for treatment preferences of depression, the patients' self-efficacy, signifying the patients' beliefs to be able to change something about their situation, seems to be of particular importance. Hence, higher self-efficacy was associated with less favorable preferences toward medication and combined treatment, which involve a passive component of dealing with the disease, but with higher preferences for active treatment options, i.e., doing sports and talking to friends and family. These findings may be associated with patient beliefs about depression etiology . AccordiMoreover, having a treatment history of depression was associated with reduced preference for medication or combined treatment. This may be caused by negative experiences with previous intake of medication as patients with positive experience of a certain treatment method are more likely to seek the same treatment in the future .During the last decade e-mental health interventions have been a rapidly developing field of research. Christensen et al.  define eWithin the present study, more than a third of the patients were likely or very likely to consider internet-based interventions in case of depression. In contrast, a slightly higher number of patients reported the opposite. Hence, internet-based interventions seem to evoke opposing reactions in primary care patients with mild to moderate depression. Nevertheless, these findings indicate that there is a considerable amount of patients showing interest in using e-mental health interventions for the treatment of depression. A previous study  investigAs an illness-related factor, comorbid general anxiety disorder was found to be associated with stronger treatment preferences for internet-based interventions. A possible reason may be increased psychological stress in patients with comorbid anxiety resulting in greater perceived need for help . AnotherStrengths of this study are the large sample, the naturalistic setting in primary care and the extended assessment of treatment preferences for depression including analyses on new media based approaches. However, this study also has some limitations. First, since we recruited primary care patients with mild or moderate depression, our findings may not apply to patients with severe depression and cannot be generalized to settings other than primary care. Treatment preferences reported by primary care patients may differ from those seen in specialized care settings. Moreover, we cannot ensure generalizability of our results for the whole population of primary care patients since the proportion of older patients in our study is not representative for this population. However, we were able to recruit a sufficient number of individuals in old age and we had enough power to obtain reliable results in this age range. Second, data were collected between 2014 and 2015, when internet-based interventions were hardly disseminated in public mental health care in Germany. Despite slow implementation, patients' perspectives on internet-based interventions might have changed since that time due to increasing public relations work. Third, patients were asked to indicate their treatment preferences for internet-based interventions in case of depression. However, the term internet-based interventions comprises many different aspects and may refer to guided or unguided self-management programs, mobile self-help apps, e-mail therapy, videoconference-based counseling or chat groups. In this regard, a scoping review  investigTo our knowledge, this is the first study investigating preferences for a broad range of treatment options including internet-based interventions for depression in primary care patients. Our results underline the importance of active patient involvement in order to find the perfect match between individual patient preferences and existing treatment options for depression. Since the patients' education and self-efficacy seemed to influence preferences for a variety of different treatment options, these factors may be particularly considered by GPs within the process of shared decision-making. In this regard, GPs may point out the positive effects of self-efficacy and empowerment on treatment success and recovery to their patients. To increase the patients' health literacy, patients should be informed thoroughly about the effectiveness and clinical evidence of treatment options for depression, e.g., with the help of information brochures. These should include information about internet-based interventions as patients may only have little knowledge about these new approaches.Future research may investigate how treatment preferences for innovative treatment options such as internet-based self-management programs affect the adherence to and effectiveness of interventions based on new media.The raw data supporting the conclusions of this manuscript will be made available by the authors upon request.MD, ML, and SR-H: conceptualized the paper; AP: conducted the statistical analyses; MD: wrote the paper; ML, JS, AP, and SR-H: revised it critically for important intellectual content.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


N = 2003 healthy individuals (aged 16–90 years) we trained support vector machines to (i) distinguish between young (<22 years) and old (>50 years) brains (classification) and (ii) predict chronological age (regression). We also evaluated generalisability of the age-regression model to an independent dataset . Bayesian optimization was used to identify optimal voxel size and smoothing kernel size for each task. This procedure adaptively samples the parameter space to evaluate accuracy across a range of possible parameters, using independent sub-samples to iteratively assess different parameter combinations to arrive at optimal values. When distinguishing between young and old brains a classification accuracy of 88.1% was achieved, . For predicting chronological age, a mean absolute error (MAE) of 5.08 years was achieved, . This was compared to performance using default values of 1.5 mm3 and 4mm respectively, resulting in MAE = 5.48 years, though this 7.3% improvement was not statistically significant. When assessing generalisability, best performance was achieved when applying the entire Bayesian optimization framework to the new dataset, out-performing the parameters optimized for the initial training dataset. Our study outlines the proof-of-principle that neuroimaging models for brain-age prediction can use Bayesian optimization to derive case-specific pre-processing parameters. Our results suggest that different pre-processing parameters are selected when optimization is conducted in specific contexts. This potentially motivates use of optimization techniques at many different points during the experimental process, which may improve statistical sensitivity and reduce opportunities for experimenter-led bias.Neuroimaging-based age prediction using machine learning is proposed as a biomarker of brain aging, relating to cognitive performance, health outcomes and progression of neurodegenerative disease. However, even leading age-prediction algorithms contain measurement error, motivating efforts to improve experimental pipelines. T1-weighted MRI is commonly used for age prediction, and the pre-processing of these scans involves normalization to a common template and resampling to a common voxel size, followed by spatial smoothing. Resampling parameters are often selected arbitrarily. Here, we sought to improve brain-age prediction accuracy by optimizing resampling parameters using Bayesian optimization. Using data on  The aging process affects the structure and function of the human brain in a characteristic manner that can be measured using neuroimaging. This quantifiable relationship was key to the early demonstrations of voxel-based morphometry (VBM)  and to tThe extent to which brain-predicted age is greater than an individual’s chronological age has been associated with accentuated age-associated physical and cognitive decline . SpecifiDespite promising results to-date, models for generating brain-predicted age still continue to contain measurement error, and efforts to improve accuracy and particularly, generalisability, to data from different MRI scanners are warranted. Training on large cohorts of healthy adults is one approach to reduce error, with the lowest mean absolute error (MAE) rates between 4 and 5 years . NotablyA key issue in brain-age prediction, along with many other neuroimaging approaches, is the choice of methods for extracting features or summary measures from raw data for further analysis . For exaBayesian optimization is an efficient and unbiased approach to parameter selection, which avoids both the failure to adequately search a large parameter space and the drawbacks of an exhaustive search. Instead, it utilizes a guided sampling strategy, assessing a subgroup of points from within the possible parameter space and testing these values on subsets of the total sample . This daThe current work used Bayesian optimization to attempt to optimize image pre-processing parameters for: (i) distinguishing the brains of young and old adults (classification), (ii) predicting chronological age (regression), and (iii) evaluating the generalisability of the resulting optima for the regression task to an independent dataset. The classification task was included to allow evaluation of Bayesian Optimization hyper-parameters and to show the applicability of Bayesian optimization to different contexts. We hypothesized that by using Bayesian optimization we would improve model accuracy compared to previously used ‘non-optimized’ values. The study was designed to show proof-of-principle of the applicability of Bayesian optimization to help improve neuroimaging pre-processing in a principled and unbiased fashion.Table 1), and as per our previous research . Ethical approval and informed consent were obtained locally for each study covering both participation and subsequent data sharing.This study used data compiled from 14 public sources  from 648 participants aged 18–88 years . This study used similar exclusion criteria, including only healthy individuals. Ethical approval for CamCAN was obtained locally, including the permission to subsequently make anonymised versions of the data publicly available.Additionally, the Cambridge Centre for Aging Neuroscience (CamCAN) neuroimaging cohort was used as an independent validation dataset . These dFigure 1. The details of each stage are as follows.An outline of the analysis pipeline for the study has been included as Normalized brain volume maps were created following a standard VBM protocol, described previously . This inAfter pre-processing, gray matter volume images were converted to vectors of ASCII-format intensity values. These were used as the input features for subsequent classification or regression analysis. This was performed in MATLAB using the support vector machine (SVM) program. For the binary classification problem of distinguishing young and old participants, SVMs were used. For predicting age as a continuous variable, SVM regression (SVR) was used. Both SVM and SVR procedures used a linear kernel to map the input data into a computationally efficient feature space.Bayesian optimization was used to identify optimal pre-processing parameters, based on the accuracy of the subsequent model predictions (either classification or regression). Hence, the Bayesian optimization procedure can be seen as an additional outer layer of analysis, that surrounds the standard pipeline . The Bayesian optimization process runs multiple iterations of this internal pipeline using different sub-samples of the dataset, exploring the parameter space to select varying image pre-processing options based on their influence on the objective function .2 implementation, which internally defines a number of optimization parameters, including selecting the covariance kernel and tuning the hyper-parameters of the process.A key advantage of Bayesian optimization derives from its ‘surrogate’ model that represents the relationship between an algorithm and the initially unknown objective function. This surrogate model is progressively refined in a closed-loop manner, by automatically selecting points in the parameter space. This provides an informed coverage of that space, based on the performance of previously sampled points. This aspect makes Bayesian optimization highly efficient, reducing the number of iterations necessary to identify optima of complex objective functions . We used3 and either 4 or 8 mm FWHM, respectively for VBM studies conducted using SPM. In our previous work on brain-age prediction we used 1.5 mm3 voxel dimensions and a 4 mm smoothing kernel . The time taken for the optimization procedure was approximately 30 s per image for the resampling step, running on a desktop computer with 16GB RAM. A full optimization cycle thus took approximately 8 h to complete 12 iterations (see below).In this study, we aimed to optimize the final normalized voxel size and the full-width half-maximum (FWHM) of the spatial smoothing kernel used during final resampling. Conventionally, these are set between 1 and 2 mmg kernel , which wN = 1000), to test a combination of pre-processing parameter values. Participants were divided into subsets of size n stratified by age, such that each subset contained an approximately representative distribution of participants from across the age range, resulting in a total of N/n iterations. We used n = 80 total (40 participants from each group) as a sample for each iteration, giving 1000/80 = 12 iterations of Bayesian optimization. This included a burn-in phase  of 5 randomly sampled points from within the parameter ranges to begin characterization of the search space, followed by 7 iterations of ‘guided’ active sampling. In each iteration, a voxel size and smoothing kernel size combination was selected and used for resampling during DARTEL normalization of each subject’s images. Normalized images were then converted to feature vectors and a binary SVM classifier was trained and assessed using 10-fold cross-validation. SVM hyper-parameters were left at default values. Classifier error was the objective function to be minimized. Bayesian optimization used the Expected Improvement Plus (EI+) acquisition function, with the default exploration-exploitation ratio of 0.5.We categorized the 500 oldest individuals (aged 51–90 years) and the 500 youngest (aged 16–22 years) as the “old” and “young” groups for classification. Each iteration of Bayesian optimization used a sub-sample of the total dataset  and the same Bayesian optimization hyper-parameters as above. The MAE in age prediction across 10-fold cross-validation using SVM regression  was the objective function to be minimized. SVR hyper-parameters were left at default values. To enable both the optimization search and make use of the full sample size available for training a generalisable regression model, the dataset was divided into a training set and a held-out test set. Bayesian optimization was first carried out using 1803 of the 2003 total participants to determine the optimal voxel size and smoothing kernel size values . A regression model was then trained on these 1803 images pre-processed using the identified optimal values, and tested on the 200 held-out participants in the test set (pre-processed using the same optimized parameters) to give an unbiased out-of-sample measure of age prediction performance.Next, we used Bayesian optimization in the context of regression models which predict chronological age in healthy individuals using brain volume images. This was done by first identifying optimal pre-processing parameters through Bayesian optimization, then applying them to the full training dataset and comparing the resulting prediction accuracy to that achieved in using ‘un-optimized’ values. The regression analysis used full model). This allowed us to evaluate how well the optimized pre-processing parameters generalized to the independent CamCAN dataset. We compared three possible approaches for this independent validation step: (1) application of the BAHC-derived full model to age prediction on CamCAN data, (2) application of the entire Bayesian optimization framework to the CamCAN dataset followed by regression training, (3) using the BAHC-derived pre-processing parameters to process the CamCAN dataset, but training a new regression model for age prediction. In case #1 the optimized voxel size and smoothing kernel size from the BAHC dataset were applied to the CamCAN dataset. In case #2, the pre-processing parameters were optimized afresh, using only the CamCAN dataset. Case #3 is something of an intermediate iteration, generalizing the optimized pre-processing parameters, but not the trained regression model.A final regression model was trained on all 2003 participants . This was done to allow inference regarding which image pre-processing parameters had the greatest impact on prediction accuracy, and to establish robustness of the model. We tested the consistency of model solutions across repetitions and participant sets, using different random seeds to create shuffled groups and burn-in points. We also varied the acquisition function of the Bayesian approach. This included comparing the results using six different acquisition functions: Expected Improvement (EI), EI per second, EI+, EI per second +, Lower Confidence Bound, and Probability of Improvement. Finally, model solutions were compared across differing values for the exploration-exploitation ratio, ranging from 10 to 90% exploration. These tests were conducted in context of voxel size and smoothing kernel size, using ranges of 1–15 mmTable 2). The optimized voxel size was 11.5 mm3 and smoothing kernel size was 2.3 mm. The performance using un-optimized values (1.5 mm3 voxels and 4 mm smoothing kernel) was 80.3%. The optimized model performance was significantly better than the un-optimized case . The parameter space exploring the expanded range of voxel size and smoothing kernel size values yielded by the model is shown in Figure 2.Model performance accuracy from ten-fold cross-validation was 88.1% for correct classification of neuroimaging data as either young or old  across 10 repetitions of the final classification protocol, (b) produced by the use of each of six different acquisition functions, and (c) using 5 different exploration-exploitation ratios ranging between 90% exploration and 90% exploitation. In all three cases, model solutions showed high cross-correlation across replications, as well as across varying settings of the optimization process. The choice of acquisition function for Bayesian sampling and the choice of exploration-exploitation ratio of this function had little impact on final model performance. Similar models were reproducible across repetitions and in randomly shuffled participant sub-sets. This behavior implied that a stable model exists in the outlined parameter space. These observations supported our use of the default acquisition function options for the classification analysis: Expected Improvement Plus (EI+), with an exploration ratio of 0.5. We thus adopted these parameters for the regression task.Stability and reproducibility of model solutions were explored in the classification problem. Correlation of models in different scenarios are shown in Figure 4 shows the objective function model created during regression, when varying smoothing kernel and voxel size , and minimizing the MAE in SVR age prediction. The lowest MAE observed for an individual sample (N = 80) was 7.17 years and the objective model function estimated a minimum error of 8.52 years . The estimated optimal voxel size and smoothing kernel size values were 3.73 mm3 and 3.68 mm respectively. Following optimization these values were used to pre-process the full dataset and train a regression model for subsequent application to other datasets.Figure 5A). This was compared to MAE = 5.48 years when using the un-optimized pre-processing values, though this value was not significantly different from the optimized case (Steiger test p > 0.1). The absolute error observed ranged from 0 to 22.78 years. In the hold-out set the Pearson’s correlation between predicted and true age was r = 0.941, with R2 = 0.89 using optimized pre-processing. Using un-optimized pre-processing parameters, we found r = 0.927, R2 = 0.86.The final resulting model was applied to predict ages for the remaining 200 holdouts and achieved a MAE of 5.08 years . This was an improvement compared to the performance when using un-optimized pre-processing values  which resulted in MAE = 6.76 years. (2) The CamCAN data was analyzed entirely independently; the full Bayesian optimization framework was instead applied to the CamCAN data to discover new, CamCAN-specific pre-processing optima, and a new regression model was trained with 588 participants and tested on 60 participants (giving a similar training-testing ratio as used in the BAHC dataset). This resulted in optimal values of 8.41 mm3 for voxel size and 3.54 mm for smoothing kernel size and yielded MAE = 5.46 years, r = 0.91, R2 = 0.83. (3) The CamCAN cohort was pre-processed using the BAHC-informed optimum values but a new regression model was trained and tested within the CamCAN participants. This model resulted in MAE = 6.21 years, r = 0.89, R2 = 0.79. The model from case #2 was significantly more accurate than the model from case #3 .The relevance of this approach for an independent dataset  was considered in three different ways. (1) The BAHC-trained model was applied to the CamCAN data pre-processed with the BAHC-informed optimum voxel size and smoothing kernel size values. Here the CamCAN participants were included in the test set only. This achieved a MAE of 6.08 years, Using Bayesian optimization, we present a conceptual improvement to conventional pipelines for distinguishing young and old brains or predicting age using neuroimaging data. The Bayesian optimization-derived optima for voxel size and smoothing kernel size showed improved performance over ‘un-optimized’ defaults for the classification of young and old brains, though performance in brain-age prediction was similar to un-optimized values. Potentially, the values previously used are relatively near the optimum thanks to the testing and experience of the researchers involved. In fact, the derived optimal smoothing kernel was very near the un-optimized value (3.68 mm vs. 4 mm). It is also important to note optima derived from the Bayesian optimization process should not be regarded as definitive, as a completely exhaustive search of the parameter space is not conducted (nor desirable due to time constraints). Our results are important as they suggest that the same pre-processing parameters are not optimal for different prediction tasks  or for different datasets (BAHC vs. CamCAN). Often, researchers will apply parameters used in one context to another. This may not necessarily be best practice, and our work shows proof-of-principle that Bayesian optimization can be used to improve image pre-processing in a principled and unbiased fashion.Figures 1, 2). This suggests that in future neuroimaging pre-processing pipeline design, there is more to be gained from optimizing voxel size, rather than smoothing kernel size. The target voxel size for normalization is often not considered, though has an important impact on the degree of partial volume effects, number of simultaneous statistical tests undertaken, spatial resolution and subsequent inferences made about anatomical specificity. Our findings suggest that more weight needs to be placed on this important parameter when relating volumetric MRI data to age.Beyond optimizing model performance, our Bayesian optimization approach also allows for relative comparison of the influence of different parameters. This potentially provides novel information regarding the prediction problem at hand. For example, here we found that varying voxel size had a much greater impact on overall performance than did smoothing kernel size. This was seen in all experiments; the change in performance across the full range of values was much smaller for smoothing kernel size than voxel size, and is clearly seen in the surface plots (3) compared to regression (3.73 mm3). Potentially, the more gross distinction between young and old brains benefits from a coarser resolution which increases signal-to-noise ratio, while the subtler patterns underlying gradual age-associated changes in brain structure requires finer-grained representation. Alternatively, the much larger voxel size identified here could result in better classification by reducing data dimensionality, with this size representing the optimal trade-off between representing the information and simplifying a high-dimensional feature space for more effective classification. Either way, the discrepancy in optimal voxel size between classification and regression reinforces the point that systematic evaluation of parameter specifications should be conducted case-by-case. Commonly, ‘one-size-fits-all’ is the prevailing heuristic for setting pre-processing parameters in neuroimaging analysis, where the defaults are assumed to be adequate. Our findings show that this is not necessarily the case, supporting the use of optimization techniques to improve experimental precision.Importantly, the conclusions regarding specific optimal values are related to the particular application in which they are tested. Within this study, we observed a notable difference in the optimal voxel size for classification (11.5 mmThe age-prediction accuracy achieved in the BAHC dataset (MAE = 5.08 years) is comparable to the current performance seen in similar research . In thes3 vs. 8.41 mm3). Speculatively, this could be due to the specific acquisition parameters at this site, or as a result of latent sample characteristics, as truly random sampling is hard to achieve. This suggests that there is unlikely to be ground-truth optimum for a given parameter, highlighting the importance of defining such optima in a given context. This relates to another potential limitation of the approach; sufficiently large datasets are necessary for the optimization to work effectively. While this is increasingly possible due to the drive to share data and the availability of large, publicly accessible cohorts , this may not be possible in certain clinical contexts, particularly regarding rarer diseases. Nevertheless, the ‘generalized’ performance of the model was still reasonable in this case, which suggests that it is incumbent on researchers to decide what constitutes sufficient prediction accuracy in each context.We explored the generalisability of the model and the general framework. The resulting MAE in the CamCAN dataset of 6.08 years (BAHC-defined model and parameters), 5.18 years (CamCAN defined model and parameters) and 6.38 years  provides some interesting insights. Though the BAHC-derived model produced reasonable performance, the highest accuracy was achieved when re-optimizing and re-training within the independent cohort, using the full Bayesian optimization framework. Interestingly, the optimal smoothing kernel size was similar between the two datasets (3.68 mm vs. 3.54 mm), while there was a marked difference in optimal voxel size (3.73 mmBayesian optimization is a robust and elegant way to tune pre-processing pipelines in an efficient and automated manner. In addition to the parameter optima, an additional strict, unbiased estimate for performance and generalisability is generated. The objective function model created provides detailed information on model performance and new insights can be gained from mapping the entire parameter space by enabling visualization of relationships between key components of the analysis and performance. This could allow for informed decision-making in experimental design, such as allowing for cost-benefit analysis in the case where optimal parameters only lead to marginal improvement in performance over other values which are easier, quicker, or less costly to enact. This could be critical in applications where the varied inputs represent expensive or invasive procedures, such as MRI scanning or obtaining CSF samples from lumbar punctures.a priori unbiased parameter optimization could be highly beneficial.Though our analysis focused on neuroimaging pre-processing to illustrate the strengths of Bayesian optimization methods, the potential applications are far-reaching. Optimization could be applied anywhere in the experimental pipeline: in questions of experimental design, stimuli choice, data acquisition, statistical method or algorithm selection, prediction methods or final model selection. The current literature on Bayesian optimization topics applies mainly to tuning of machine learning algorithms  and thouOur study shows the potential of Bayesian optimization to improve neuroimaging pre-processing by reducing prior assumptions, in the context of classification and regression in the context of brain aging. Future research into brain aging and other neuroscientific areas could benefit from applying principled optimization approaches to improve study sensitivity and reduce bias.All study data were obtained from repositories of publicly available data. These data were originally acquired with written informed consent of all study participants.RLe and JC conceived and designed the study. RLo, RLe, and JC developed the methods. JL, RLe, and JC analyzed and interpreted the data. JL, RLo, RLe, and JC drafted and revised the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The handling editor is currently co-organizing a Research Topic with one of the authors JC, and confirms the absence of any other collaboration.


Supplemental Digital Content is available in the text Despite that pelvic and para-aortic lymphadenectomy (PPaLND) is recommended as part of accurate surgical staging by International Federation of Gynecology and Obstetrics (FIGO) in endometrial cancer, the impact of para-aortic lymphadenectomy on survival remains controversial. The aim of this work is to evaluate the survival benefits or risks in endometrial cancer patients who underwent surgical staging with or without para-aortic lymphadenectomy using meta-analysis.Literature search was undertaken using PubMed, Embase, and Cochrane Library databases for relevant articles published between January 1, 1990, and January 1, 2017, without language restriction. The primary outcome was overall survival (OS); progression-free survival (PFS)/recurrence-free survival (RFS)/disease-free survival (DFS)/disease-related survival (DRS) was also analyzed. Subgroup analysis and sensitivity analysis were conducted to investigate the source of heterogeneity. Quality assessments were performed by Newcastle–Ottawa Quality Assessment Scale (NOS). Publication bias was evaluated by using Begg and Egger tests. The hazard ratio (HR) was pooled with random-effects or fixed-effects model as appropriate.P < .001, I2 = 12.2%]. Subgroup analysis by recurrence risk explored the same association in patients at intermediate- or high-risk , but not for low-risk patients . PPaLND with systematic resection of all para-aortic nodes up to renal vein also improved PFS/RFS/DFS/DRS, compared with PLND . No publication bias was observed among included studies.Eight studies with a total of 2793 patients were included. OS was significantly longer in PPaLND group than in pelvic lymphadenectomy (PLND) group for patients with endometrial cancer [HR 0.68; 95% confidence interval (CI) 0.55–0.84, PPaLND is associated with favorable survival outcomes in endometrial cancer patients with intermediate- or high-risk of recurrence compared with PLND, particularly with regards to OS. PPaLND with systematic resection of all para-aortic nodes up to renal vein also improve PFS compared with PLND. Further large-scale randomized clinical trials are required to validate our findings. The World Health Organization reported in 2012 that 319,605 cases of uterine corpus cancers have newly increased and led to 76,160 deaths worldwide. The management of endometrial cancer has significantly changed over the past 25 years.,5 In primary surgery, surgical assessment of lymph nodes for staging remains one of the most varied practices worldwide, ranging from no nodal assessment, to sentinel lymph node (SLN) mapping, to complete pelvic and para-aortic lymphadenectomy up to the renal vessels.Endometrial carcinoma is the most common gynecological malignancy in developed countries. approximately 10% of women with presumed early-stage endometrial cancer suffered lymph node metastasis. SLN mapping and biopsy is increasingly used in many gynecological centers, but the technique is still under investigation in order to improve the accuracy of SLN detection. Extensive lymphadenectomy may have therapeutic benefit due to the removal of occult metastasis that remains undiagnosed by the pathologist. However, the prognostic significance of routine dissection of the retroperitoneal para-aortic lymph node is still debated.–12 Notably, retroperitoneal para-aortic lymph node dissection could increase the surgical morbidity. Compared with patients undergoing pelvic lymphadenectomy (PLND) alone, patients undergoing pelvic and para-aortic lymphadenectomy (PPaLND) suffered increased blood loss, transfusion rates, hospital stay, and anesthesia time. The prognostic information provided by para-aortic lymphadenectomy is useful; however, the tangible costs for gathering this information should also be considered. We aimed to perform an analysis of a total evidence of relevant studies evaluating the survival benefits or risks in endometrial cancer patients who underwent surgical staging with or without para-aortic lymphadenectomy.Retroperitoneal lymph node metastasis is a critical prognostic factor for patients with endometrial cancer,22.1Literature search was undertaken using PubMed, Embase, and Cochrane Library databases for relevant articles published between January 1, 1990, and January 1, 2017, without language restriction. This study was prepared according to the recommendations of the Cochrane Collaboration and is reported following the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) Statement. The searching terms were (para-aortic) AND (pelvic) AND (“lymph node excision” [Mesh] OR “lymphadenectomy”[All Fields]) AND  without limiting publication language. Reference lists of all available clinical studies were manually searched and reviewed.2.2We designed the meta-analysis to compare PLND and PPaLND surgical procedures for patients with EC. Inclusion criteria were as follows: studies exploring endometrial cancer; studies comparing 2 treatment modalities and reporting overall survival (OS)/progression-free survival (PFS)/recurrence-free survival (RFS)/disease-free survival (DFS)/disease-related survival (DRS); studies providing hazard ratio (HR) directly or key information to calculate HR indirectly, such as Kaplan-curves and original survival data. The following studies that met one of the criteria would be excluded: abstracts of meetings, duplicate publication, review articles, and case reports; studies explored new surgical techniques or evaluated operation outcomes without comparison of survival effects; and full text or valid data not accessed. To avoid overlapping patient data in publications on the same cohort, we included articles with the latest data.2.3–17 For prognostic studies, when both multivariate and univariate analyses of the OS/PFS/RFS/DFS/DRS results were performed, HRs and their corresponding 95% confidence intervals (95% CIs) were extracted preferentially from the multivariate analyses. For the articles in which prognosis was plotted only as the Kaplan–Meier curves, the Engauge Digitizer 9.5  was then used to extract survival data, and the estimates of the HRs and 95% CIs were calculated by Tierney method.Two reviewers (W.N.G. and J.C.) individually screened the electronic database according to the prespecified strategies. Disagreement was resolved through independently extracting data from the original article by the corresponding author, and consensus was reached by discussions. Several essential information was extracted, including first author, publication year, country of origin, number of patients analyzed, mean age, International Federation of Gynecology and Obstetrics stage (FIGO), median lymph nodes removed, follow-up time, outcome, recurrence risk categories and its criteria, extracting method of HR, and whether multiple analysis or not. The main features of these eligible studies are summarized in Table 2.4 which contains 3 aspects: selection, comparability, and outcome. The highest quality studies are awarded up to 9 stars. Studies with more than 6 stars were considered as of high quality. Otherwise, studies were excluded from the final meta-analysis.Quality assessments were performed according to the Newcastle–Ottawa Quality Assessment Scale (NOS),2.5I2 estimates. Fixed effects model was conducted to aggregate data if there were no statistical heterogeneity (I2 < 50%); otherwise, a random effects model would be considered. Sensitivity analysis was performed to identify the origin of any heterogeneity by sequentially eliminating individual studies. Publication bias was examined using Begg funnel plot and Egger linear regression test. Two-sided P < .05 was considered statistically significant.Statistical analysis was performed using STATA version 14.0 software . The HR with 95% CI for data of survival analysis. Forest plots were generated for graphical presentations, and heterogeneity among different studies was appraised by Q statistics and 2.6The ethical approval was not necessary in this study because of the meta-analysis study design.33.1–13,15–17 A total of 2793 patients were included, 1456 patients received PLND alone, whereas 1337 patients received PPaLND. Characteristics of the 8 eligible studies are listed in Table ,10,16 3 in Korea,,17 1 in Turkey, 1 in Germany, 1 in USA. The average of follow-up duration was 46 months. We adopted NOS to assess the quality of included papers . The quality score ranged from 7 to 9 with a median score of 8 for all cohort studies, which suggested the relatively high quality of the studies included in the meta-analysis , so the fixed-effect model was used in this analysis. The pooled HR  suggested that PPaLND improved OS, compared with PLND, in all stages of endometrial cancer. The similar pooled HR 0.67 with 95% CI 0.56 to 0.86 was detected in the random-effect model.Seven studies involved 2730 endometrial patients and reported OS with PPaLND and compared with PLND These prognostic factors are aggregated to define patients with high recurrence risk and therefore are included in the risk stratification systems of European Society for Medical Oncology (ESMO), Gynecologic Oncology Group (GOG), Survival Effect of Para-Aortic Lymphadenectomy in endometrial cancer (SEPAL), and Post-Operative Radiation Therapy in Endometrial Carcinoma (PORTEC 1) in varies combination. Therefore, we defined patients with endometrial cancer of FIGO stage IA, grade 1 to 2, endometrioid histology, and negative lymphovascular space invasion (LVSI) as the low-risk group and the remaining patients as the intermediate- or high-risk group. Six studies involved 1729 intermediate- or high-risk endometrial cancer patients and compared PPaLND versus PLND.–13,15,16 There was no heterogeneity among the included studies  and a fixed-effect model was used. As listed in Fig. P < .001, I2 = 41.4% Fig. P = .077, I2 = 0 Fig. S1).On the basis of the recurrent risk evaluated intra- or postoperatively, we analyzed 2 recurrence rate groups  between PPaLND and PLND. Recurrent risk is related to the depth of myometrial invasion, tumor grade, histological subtype, and lymph-vascular space invasion in clinically proven early-stage endometrial cancer.3.2.2I2 = 74.8%, P = .001) was detected when 6 studies were adopted to pool HRs for PFS/RFS/DFS/DRS.,13,16,17 To make a conservative estimate, a random-effect model was used to account for the highly significant inter-study heterogeneity. Despite the lack of significant difference, PPaLND had a tendency to improve PFS in all stage endometrial cancer  or in low-risk group .Moreover, there was no significant difference in PFS between PPaLND and PLND either in intermediate- or high-risk group  trial and the study by Benedetti Panici et al, did not show any significant survival benefit of PLND in women with early endometrial cancer. However, less than 10 lymph nodes were removed in 35% of the patients in the lymphadenectomy group and neither study included para-aortic lymphadenectomy, which may contribute to the discrepancy between their and our present results. The survival benefit of para-aortic lymphadenectomy remains unclear. In this study, we calculated the pooled HRs for both OS and PFS, respectively, to obtain convincing results. On the whole, we identified that PPaLND was efficient for improving OS in all stage endometrial cancer patients compared with PLND. Exploratory analysis also suggested that the efficacy of PPaLND is limited in low-risk endometrial cancer, whereas it is efficient to increase OS in patients with intermediate- or high-risk endometrial cancer. For PFS, there was no significant difference between PPaLND and PLND. However, on the basis of the outcome of subgroup analysis, systematic PPaLND, namely systematic resection of all para-aortic node up to renal vein, improved PFS in all stage of endometrial cancer, compared with PLND. The result indicated that the extent of para-aortic lymphadenectomy may impose a great impact on PFS. It is worth mentioning that 1 study found that para-aortic lymphadenectomy yielding less than 10 nodes was associated with decreased PFS. This was a striking resemblance to our findings—3 studies undergoing systematic PPaLND yielded more than 10 para-aortic lymph nodes. The number of lymph node harvested would be an index of the degree of thoroughness in removal. But there were not enough studies to quantify the relationship between the number of para-aortic lymph node removed and the prognosis. Although using a cutoff at the median number of nodes is relatively arbitrary, the results illustrated that, besides the anatomy range of the operation, the number of para-aortic lymph node removed may be another important factor to measure the thoroughness of surgery.To the best of our knowledge, this is the first meta-analysis focused on the comparison of PPaLND versus PLND in endometrial cancer. Previously, a meta-analysis compared OS between systematic lymphadenectomy and unsystematic lymphadenectomy and concluded that systematic lymphadenectomy significantly improved OS of the endometrial cancer patients with intermediate- and high-risk of recurrence, but it did not focus on the para-aortic lymph node. However, a study found that intraoperative and postoperative complication rates were equivalent between PPaLND and PLND. SLN mapping is considered as an alternative. Studies revealed that SLN mapping provided similar detection rates of lymph node metastases in advanced stage of endometrial cancer and did not decrease DFS in patients with limited myometrial invasion. Therefore, future studies comparing SLN mapping versus systematic lymphadenectomy regarding the OS and DFS in patients with endometrial cancer should be taken into account.In general, PPaLND could increase the risk of operative complications.The results of our study have some guiding significance for the grouping of patients with endometrial cancer and the selecting of corresponding surgical scope. However, there are some hidden biases in the retrospective cohort analysis. Perhaps patients who undergo PPaLND are more likely to be operated in tertiary medical centers by more accomplished gynecologic oncologists and received standard treatment. Moreover, the patients’ health and size may affect the decision of surgical approach. These biases may affect the analysis. Our findings in this review should be further verified in larger clinical trials with more extensive comparable data.5The present systematic review of retrospective cohort studies reveals that PPaLND is associated with favorable survival outcomes in endometrial cancer patients with intermediate- or high-risk of recurrence compared with PLND, particularly with regards to OS. PPaLND with systematic resection of all para-aortic node up to renal vein may also improve PFS compared with PLND. In summary, this study provides some guidance for choosing the appropriate surgical scope in the different groups of endometrial cancer patients. Due to the limitations inherent with retrospective studies, further large-scale randomized clinical trials are required to validate our findings.


The specificity of nucleic acid amplification tests (NAATs) used for early infant diagnosis (EID) of HIV infection is <100%, leading some HIV-uninfected infants to be incorrectly identified as HIV-infected. The World Health Organization recommends that infants undergo a second NAAT to confirm any positive test result, but implementation is limited. Our objective was to determine the impact and cost-effectiveness of confirmatory HIV testing for EID programmes in South Africa.Using the Cost-effectiveness of Preventing AIDS Complications (CEPAC)–Pediatric model, we simulated EID testing at age 6 weeks for HIV-exposed infants without and with confirmatory testing. We assumed a NAAT cost of US$25, NAAT specificity of 99.6%, NAAT sensitivity of 100% for infants infected in pregnancy or at least 4 weeks prior to testing, and a mother-to-child transmission (MTCT) rate at 12 months of 4.9%; we simulated guideline-concordant rates of testing uptake, result return, and antiretroviral therapy (ART) initiation (100%). After diagnosis, infants were linked to and retained in care for 10 years  or lifelong (true-positive). All parameters were varied widely in sensitivity analyses. Outcomes included number of infants with false-positive diagnoses linked to ART per 1,000 ART initiations, life expectancy  and per-person lifetime HIV-related healthcare costs. Both without and with confirmatory testing, LE was 26.2 years for HIV-infected infants and 61.4 years for all HIV-exposed infants; clinical outcomes for truly infected infants did not differ by strategy. Without confirmatory testing, 128/1,000 ART initiations were false-positive diagnoses; with confirmatory testing, 1/1,000 ART initiations were false-positive diagnoses. Because confirmatory testing averted costly HIV care and ART in truly HIV-uninfected infants, it was cost-saving: total cost US$1,790/infant tested, compared to US$1,830/infant tested without confirmatory testing. Confirmatory testing remained cost-saving unless NAAT cost exceeded US$400 or the HIV-uninfected status of infants incorrectly identified as infected was ascertained and ART stopped within 3 months of starting. Limitations include uncertainty in the data used in the model, which we examined with sensitivity and uncertainty analyses. We also excluded clinical harms to HIV-uninfected infants incorrectly treated with ART after false-positive diagnosis ; including these outcomes would further increase the value of confirmatory testing.Without confirmatory testing, in settings with MTCT rates similar to that of South Africa, more than 10% of infants who initiate ART may reflect false-positive diagnoses. Confirmatory testing prevents inappropriate HIV diagnosis, is cost-saving, and should be adopted in all EID programmes. Lorna Dunning examine the cost-effectiveness of confirmatory testing in early infant HIV diagnosis programmes in South Africa. Paediatric HIV remains a substantial burden in many low-resource countries, with 170,000 infants infected with HIV in 2015. The World Health Organization (WHO) recommends virological testing of HIV-exposed infants by 6 weeks of life, with immediate referral of those who test positive for initiation of HIV care to reduce infant mortality associated with HIV.Despite reported specificities greater than 99%, virological assays still have the possibility for false-positive diagnoses. The use of confirmatory testing is therefore strongly recommended in early infant diagnosis (EID) programmes.A recent policy survey by WHO demonstrated that implementation of confirmatory testing in EID programmes is limited, with 38% (8/21) of high-burden countries not including confirmatory testing for infants in their guidelines.Cost is often cited as a key barrier; many low-resource countries struggle to implement EID programmes due to the high costs of virological tests.Our study was designed to estimate the clinical and economic value of confirmatory testing in EID programmes.We used a computer simulation model of paediatric HIV infection, diagnosis, and treatment to examine the clinical and economic outcomes of EID programmes without and with confirmatory testing in South Africa.We found there was no clinical difference in the life expectancy or 1-year survival of HIV-infected infants between the 2 strategies, but without confirmatory testing, in settings with a mother-to-child transmission (MTCT) rate similar to that of South Africa, over 10% of infants initiating antiretroviral therapy (ART) would do so inappropriately as a result of a false-positive diagnosis.Confirmatory testing averted costly HIV care and ART in truly HIV-uninfected infants, leading the confirmatory testing strategy to be cost-saving compared to without confirmatory testing in all reasonable scenarios.ART should be initiated after the first positive test result; when ART was not initiated until the return of the confirmatory result, mortality during the delay to ART initiation substantially reduced survival for HIV-infected infants.Use of confirmatory testing in EID programmes, with ART initiation after the first positive result, substantially reduces the proportion of infants incorrectly diagnosed as HIV-infected and initiated on ART.Confirmatory testing is cost-saving under a wide range of scenarios.Confirmatory testing should be implemented in settings using virological assays for EID. Despite the success of programmes to prevent mother-to-child transmission (MTCT) of HIV, paediatric HIV remains a substantial burden in sub-Saharan Africa, with 170,000 infants infected with HIV in 2015 .Inexpensive serological antibody assays routinely used for diagnosis in adults cannot be easily interpreted for HIV-exposed infants (those born to HIV-infected women), because transplacental transfer of maternal antibodies leads infants to be seropositive for as long as 18 months ,8. InfanCurrent WHO and South African guidelines strongly recommend the use of confirmatory NAAT testing with ART initiation at the first positive result as part of early infant diagnosis (EID) programmes ,14. Howehttp://web2.research.partners.org/cepac/model.html.We used the Cost-Effectiveness of Preventing AIDS Complications (CEPAC)–Pediatric model to simulate a cohort of HIV-exposed infants in South Africa undergoing 2 EID algorithms: 6-week EID testing without confirmatory testing and 6-week EID testing with confirmatory testing. The CEPAC–Pediatric model is a first-order Monte Carlo simulation model of paediatric HIV infection, disease progression, diagnosis, and treatment –21. For This work was approved by the Partners Human Research Committee, Boston, MA, US.In the base-case analysis, we simulated HIV-exposed South African children presenting to care at 6 weeks of age. EID in South Africa is currently directed at infants with known HIV exposure ; we therThe model records true infection status for all infants, as well as the results of each administered assay, allowing the direct reporting of true-positive, true-negative, false-positive, and false-negative diagnoses. The primary model outcomes were the number of infants with false-positive diagnoses linked to care as a proportion of total ART initiations, PPV (defined as the proportion of positive test results due to truly HIV-infected infants), life expectancy , and average per-person lifetime HIV-related healthcare costs, from the perspective of the healthcare provider. We projected survival, LE, and costs separately for HIV-infected infants and for the complete birth cohort of HIV-exposed infants, which included both HIV-infected and HIV-uninfected infants. Costs are presented in 2013 US dollars; costs and life expectancies were modelled both undiscounted and discounted at a rate of 3%/year . We firsThe strategy ‘without confirmatory testing’ simulated all HIV-exposed infants receiving a NAAT at 6 weeks of age; in this strategy, all infants who received positive results initiated ART upon result return (mean turnaround time: 1 month). The strategy ‘with confirmatory testing’ simulated all HIV-exposed infants receiving a NAAT at 6 weeks of age; all infants who received positive results on the first test initiated ART at result return, but a second blood sample was drawn before ART initiation and sent for a confirmatory NAAT . We assuWe modelled cohort characteristics, PMTCT coverage and MTCT risks, disease progression, and ART outcomes using data from published trials and cohort studies in sub-Saharan Africa  28–32].–32.28–32We incorporated published South African healthcare costs for HIV-infected children less than 5 years of age. Costs associated with OI care for children 5 years of age and older were calculated from South African adult resource utilisation  multiplied by South African unit costs ,39. RoutFollowing ISPOR–SMDM Good Research Practices Task Force  guidelinWe conducted 3 scenario analyses to examine important issues in EID implementation . Third, The univariate sensitivity analyses described above reveal the sensitivity of policy conclusions to variations in key parameters through a wide range of plausible values. To reflect the uncertainty in the primary data estimates, we also varied key parameters through reported 95% confidence intervals , with 95.1% of the cohort HIV-exposed but uninfected . In bothLifetime costs of HIV-exposed infants were US$1,830/infant without confirmatory testing and US$1,790/infant with confirmatory testing ; Fig 1. The use of confirmatory testing remained cost-saving even with wide variations in model parameters, including the cost, specificity, and sensitivity of the NAAT; the probability of presentation at each step in the EID cascade; and the costs of routine care and OI care. Robustness of model results to these key parameters is shown in We repeated the base-case analysis using a NAAT specificity of 98.8%, as reported by WHO in a previous meta-analysis . The cosSeveral variations in model parameters changed the proportion of ART initiations due to false-positive diagnosis , as depicted in Incorporating input parameters from current testing and treatment cascades reduced the LE of HIV-infected infants, but the number of infants with a false-positive diagnosis initiating ART remained 128/1,000 ART initiations . For proThe impact of varying key parameters through the confidence intervals around base-case estimates is shown in We simulated EID strategies without and with confirmatory testing for HIV-exposed infants in South Africa. The primary finding was that, when confirmatory testing was not used in the model, more than 10% of infants who initiated ART reflected false-positive diagnoses. These model results are comparable to empirical data from Africa: when records of infants receiving positive EID results and/or initiating ART were reviewed in detail, the proportion found to be truly HIV-uninfected was 2.5% in Kenya, 6.3% in South Africa, 14.6% in Malawi, and 16% in Côte d’Ivoire and Burkina Faso –75. HIV-False-positive results occur for a variety of reasons but are likely the result of stretched human resources compromising test specificity and sensitivity via specimen handling errors such as mislabelling of specimens, incorrect specimen placement in the device, or inadequate quality control resulting in contamination between specimens during PCR amplification ,76. WHO The second key finding from this analysis is that including confirmatory testing in EID programmes is cost-saving. We found that confirmatory testing reduced the cost per HIV-exposed infant tested from US$1,830 to US$1,790. Although concerns have been raised about the capacity of laboratories to conduct the additional assays needed for confirmatory testing, we found that the number of additional tests was relatively small, as they are required by only 3% of HIV-exposed infants [A third key finding of this analysis is that when confirmatory testing is done, ART should be initiated after the first positive result, as WHO recommends. If ART was delayed until the result of the confirmatory assay was available, short-term survival and LE were markedly reduced. Waiting even 1 month to initiate ART until the return of the confirmatory result can reduce 1-year survival for HIV-infected infants substantially (from 75.8% to 74.5%) and overall LE for HIV-infected infants (from 26.2 years to 25.9 years). Novel POC EID assays, which offer in-clinic testing and same-day result return, have been proposed as an approach to improving timely ART initiation. Based on preliminary published values for POC NAAT sensitivity (95.5%), specificity (99.8%), and cost (US$30), our analyses suggest that confirmatory testing would likely remain cost-saving in EID programmes using POC assays in place of traditional laboratory assays ,66.In South Africa, access to ART during pregnancy has steadily increased, leading to a 76% reduction in new HIV infections among children . If PMTCThere were 3 main limitations of the analysis. First, uncertainty exists in all long-term projections; although our model was calibrated to ensure results match current survival and OI data, developments in treatment and technology will undoubtedly occur in the coming years ,20. Our In summary, we find that use of a second NAAT for confirmatory testing in EID programmes substantially reduces the proportion of infants incorrectly diagnosed as HIV-infected and initiated on ART. While projected cost differences are small, confirmatory testing is cost-saving under a wide range of scenarios in South Africa. Confirmatory testing with ART initiation at the first positive result, as recommended by WHO for EID, should be implemented in settings using NAAT for EID.S1 Checklist(DOCX)Click here for additional data file.S1 TableImplementation of the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) and Society for Medical Decision Making (SMDM) good research practices within our analysis.(DOCX)Click here for additional data file.S2 TableExtensive table containing all input parameters used in the CEPAC–Pediatric model analysis of early infant HIV diagnosis testing in South Africa.(DOCX)Click here for additional data file.S1 TextThis appendix provides further information on methods and additional model results from extended sensitivity and uncertainty analyses.(DOCX)Click here for additional data file.


Geothermal energy piles are a quite recent renewable energy technique where geothermal energy in the foundation of a building is used to transport and store geothermal energy. In this paper, a structural–functional integrated cement-based composite, which can be used for energy piles, was developed using expanded graphite and graphite nanoplatelet-based composite phase change materials (CPCMs). Its mechanical properties, thermal-regulatory performance, and heat of hydration were evaluated. Test results showed that the compressive strength of GNP-Paraffin cement-based composites at 28 days was more than 25 MPa. The flexural strength and density of thermal energy storage cement paste composite decreased with increases in the percentage of CPCM in the cement paste. The infrared thermal image analysis results showed superior thermal control capability of cement based materials with CPCMs. Hence, the carbon-based CPCMs are promising thermal energy storage materials and can be used to improve the durability of energy piles.  In recent years, the building division of China was one of the principal energy users and accounted for nearly 40% of total fossil energy . The decGeothermal energy piles are utilized to transport and store geothermal energy from the surrounding ground. Many studies have been carried out to investigate geotechnical performance of piled foundations for ground-source heat-pump systems ,17. ApplVarious researchers have investigated the mechanical properties as well as heat of the hydration of the thermal energy storage cement-based composites. Zhang et al.  preparedIn this research, two kinds of composite phase change materials i.e., expanded graphite-based PCM (EG-Paraffin) and graphite nanoplatelet-based PCM (GNP-Paraffin) were prepared for the development of cement-based structural–functional integrated materials. The thermo-regulating performance of thermal energy storage cement-based composite by using infrared thermography was also determined. Finally, the role of CPCM, namely, expanded graphite-based PCM (EG-PCM) and graphene nanoplatelet-based PCM (GNP-PCM), in reducing the heat of the hydration of the cement-based composite was evaluated.3, while the specific surface area of cement was 3980 cm2/g. The details of the chemical composition of the ordinary Portland cement (OPC) are specified in Industrial grade paraffin from China Petrochemical Corporation was used as PCM, while expanded graphite  purchased from Qingdao Teng Sheng Da Carbon Machinery Co., Ltd., Qingdao, China, and technical-grade graphene nanoplatelets (a diameter of 5–7 μm and a nanosheet number <20) purchased from Chinese Academy of Sciences Chengdu Organic Chemical Co., Ltd., Chengdu, China, were used as supporting materials. For the preparation of CPCM cement paste, Portland cement  conforming to BS 12-1996 (Specification for Portland cement) was used (a 28-day compressive strength of 60.1 MPa). The specific gravity of cement was 3.44 g/cmTwo kinds of CPCMs, i.e., EG-Paraffin and GNP-Paraffin, were prepared using vacuum impregnation ,23. Cons3 prisms , 20 × 20 × 20 mm3 cubes (for compressive strength), and Ф 30 mm × 4 mm cylinders (for infrared thermography) were prepared.It is known that PCM require a larger specific surface area to exchange heat efficiently. Hence, CPCM was added into a cement paste matrix rather than partially replacing aggregates in mortar or concrete. The details of mix proportions are shown in The thermal properties of the CPCMs  were determined by using DSC (under nitrogen atmosphere). The parameters used for testing are as follows: temperature range: 0–60 °C; heating/cooling rate: 2 °C /min; flow rate: 40 mL/min.The SEM images of cement pastes were captured using ESEM . The machine was operated in secondary-electron detection mode (under low vacuum) at an accelerating voltage of 15 kV. In order to get representative images, several regions of the powdered samples were observed. The SEM micrographs were also captured for thermal energy storage cement paste, while the energy dispersive spectrometer (EDS) was used to evaluate CPCMs dispersion in cement paste. Since PCM is absorbed by carbon-based CPCM and there is no carbon element present in pure cement paste, the EDS map showing distribution of carbon element can be used to represent the distribution of EG-Paraffin/GNP-Paraffin in CPCM.At 28 days, the mechanical properties  of the cement composite with 0%, 10%, and 20% CPCMs (EG-PCM and GNP-PCM) by weight of cement were determined. The loading rate for compressive strength was 2400 ± 200 N/s, while it was 50 ± 10 N/s for flexural strength.Infrared thermography has been used sucessfully to determine the thermal-regulating performance of CPCMs cement paste . Hence, The heat of the hydration of the cement paste with and without CPCM was evaluated. The control cement paste and the cement paste containing 25% CPCM (EG-paraffin and GNPs-Paraffin) was made with a water/cement ratio of 0.35. The heat of the hydration of the CPCM cement paste was evaluated for the first 72 h using ToniCal Trio 7338 .The SEM micrographs of EG, GNPs, EG-Paraffin CPCM, and GNPs-Paraffin CPCM are shown in The thermal properties of paraffin and CPCMs are presented in It is pertinent to mention here that the developed CPCMs were found to be chemically compatible, thermally stable, and reliable.The compressive strength results of cement composites are presented in The flexural strength of thermal energy storage cement paste was also determined. The flexural strength decreased with the addtion of CPCM in the cement paste. For 10 wt % and 20 wt % replacement level, the percentage decrease for EG-Paraffin thermal energy storage paste was found to be 73.4% and 83.5%, respectively, while the percentage decrease for GNP-Paraffin thermal energy storage cement paste was found to be 31.64% and 41.8%, respectively. In Xu et al.’s research , the fleThe density values of the thermal energy storage cement paste is shown in The results of the surface temperature distribution of cement paste with and without CPCMs at various times are shown in The results of the heat of the hydration of the thermal energy storage cement paste are shown in From an experimental investigation, the following conclusions can be drawn.The compressive strength of GNP-Paraffin cement-based composites at 28 days was more than 25 MPa and hence can open an opportunity for structural purposes. Moreover, with increases in the percentage of CPCM in cement paste, the flexural strength and density of thermal energy storage cement paste composite decreased. The carbon-based CPCMs were well dispersed in the cement paste, depicting the uniform mixing of CPCM during mixing. This would help the geothermal energy in the piles to be stored evenly.From infrared thermal image analysis results, the thermal-regulating performance of cement paste with carbon-based PCM was found to be superior. Moreover, in comparison to EG-Parffin-20, the GNP-Paraffin-10 showed better thermal-regulatory performance due to a higher thermal conductivity coefficient of GNP. The temperature controlling capacity of PCM in CPCM gradually reduced when the temperature exceeded the melting point of PCM.The heat of the hydration results showed that carbon-based PCMs are not only more efficient in lowering the total hydration heat of cement paste but are also effective in lowering the hydration heat releasing rate. Therefore, thermal energy storage cement paste can be utilized in larger sections such as dams to reduce the undesirable tensile stresses resulting from the heat of the hydration of the cement paste.


Trans-arterial radioembolization (TARE) is a recognized, although not explicitly recommended, experimental therapy for unresectable hepatocellular carcinoma (HCC).A systematic literature review was performed to identify published studies on the use of TARE in intermediate and advanced stages HCC exploring the efficacy and safety of this innovative treatment.Twenty-one studies reporting data on overall survival (OS) and time to progression (TTP), were included in a meta-analysis. The pooled post-TARE OS was 63% (95% CI: 56-70%) and 27% (95% CI: 21-33%) at 1- and 3-years respectively in intermediate stage HCC, whereas OS was 37% (95% CI: 26-50%) and 13% (95% CI: 9-18%) at the same time intervals in patients with sufficient liver function (Child-Pugh A-B7) but with an advanced HCC because of the presence of portal vein thrombosis. When an intermediate and advanced case-mix was considered, OS was 58% (95% CI: 48-67%) and 17% (95% CI: 12-23%) at 1- and 3-years respectively. As for TTP, only four studies reported data: the observed progression probability was 56% (95% CI: 41-70%) and 73% (95% CI: 56-87%) at 1 and 2 years respectively. The safety analysis, focused on the risk of liver decompensation after TARE, revealed a great variability, from 0-1% to more than 36% events, influenced by the number of procedures, patient Child-Pugh stage and treatment duration.Evidence supporting the use of radioembolization in HCC is mainly based on retrospective and prospective cohort studies. Based on this evidence, until the results of the ongoing randomized trials become available, radioembolization appears to be a viable treatment option for intermediate-advanced stage HCC. Hepatocellular carcinoma represents the third most common cause of cancer death, causing nearly 746,000 deaths per year in the world , 2. In aThe Child-Pugh score is used to assess the prognosis of chronic liver disease, mainly cirrhosis . PatientIn current practice, advanced stage patients present as such in 60-70% of cases while the rest progresses to this stage despite treatment of more precocious cancer presentations , 9 but sIn the intermediate HCC stage, a wide range of interventional loco-regional treatments are available and trans-arterial chemoembolization (TACE) variously administered, is considered as the standard of care , 6. AlsoTrans-arterial radioembolization (TARE), often referred as a form of selective internal radiation therapy (SIRT) is a recognized, although not explicitly recommended therapy in several guidelines on clinical management of non-resectable HCC , 6, 12. ®) or biocompatible resin-based (SIR-Spheres®) radioactive (Yttrium90 - Y90) spheres [On technical grounds, TARE is a catheter-based interventional procedure that allows the emission of β-radiations at therapeutic levels directly into the tumour through its feeding arteries. Such a delivery mechanism, as for TACE, is aimed at minimizing the damage to the healthy liver parenchyma adjacent to the tumour. The main mechanism of action of TARE is a local brachytherapy and, unlike TACE, it doesn't result in microvascular embolization and tumour ischemia . Devices spheres .In the light of the increasing use of this innovative therapy in clinical practice, this study aims to systematically review the available evidence for the clinical efficacy and safety of TARE (glass or resin-based) in patients with intermediate-advanced stages HCC.Out of 6641 references screened, 26 studies met the selection criteria. The study selection process is summarized in Figure The vast majority of included studies were observational cohorts, however three comparative studies were found: two RCTs comparing TARE with either TARE + sorafenib  or TACE A summary of the critical appraisal of TARE studies is reported in All studies showed low to medium methodological quality. One study  did not Studies presenting OS or TTP data, stratified by presence or absence of PVT were all included in the meta-analyses except for two studies, one which did not report survival curves  and the Studies considering patients with extrahepatic spread  or patieDetails on the 21 studies included in the quantitative analyses are listed in Table The pooled OS was 63% (95% CI: 56-70%) and 27% (95% CI: 21-33%) at 1- and 3-years respectively, for the population receiving TARE at an intermediate-advanced stage  and 17% (95% CI: 12-23%) at 1- and 3-years respectively . In the In terms of TTP, only four studies reported clear data: two of them had non-stratified TTP curves , 36, in All results were confirmed in fixed effect meta-analysis models (data not shown).As described above, tumour progression after TARE was reported as a late event mainly due to deterioration of performance status and of Child-Pugh stage.More specifically, the analysis on the adverse events related to TARE was focused on liver decompensation and/or failure following treatment. There was a large heterogeneity in definition of liver decompensation in the included studies and with that bias the percentage of patients suffering liver decompensation after TARE is reported in Table In the last decade trans-arterial radioembolization has emerged as a viable loco-regional treatment option for patients with unresectable hepatocellular carcinoma associated or not with portal vein thrombosis, although its use is still not formally recommended in clinical guidelines due to lack of prospective randomized studies. While large RCTs have been implemented and likely to be reported in the near future, the present study aimed at identifying the available evidence around the efficacy and safety of TARE through a systematic review of published studies conducted on patients with intermediate and advanced HCC.We identified 23 observational cohort studies, two RCTs of TARE vs. TARE + sorafenib and TARE vs. TACE and one propensity score matching study comparing TARE vs. sorafenib. All studies were of intermediate to low methodological quality. After excluding papers not presenting the outcomes of interest (OS or TTP) in a suitable form for the meta-analysis, a pooled summary estimate on the 21 remaining studies confirmed the good efficacy performance of TARE in HCC unsuitable for curative treatment options.Included studies suggest that median OS in patients receiving TARE for intermediate-advanced HCC falls in the range of 12-24 months, halved to 6-12 months should PVT be present. Pooled survival rates at 3-years after TARE were estimated as 13% (with PVT) and 27% (without PVT). These results are consistent with those presented in other published studies reporting median OS of 7-41.6 months in BCLC B to C patients [2 - was observed particularly in TTP while being less evident for OS. This reflected different schedules and protocols for definition and identification of tumour progression, which is considered a secondary endpoint in the large majority of studies [Residual heterogeneity among studies - as measured by I studies . High he studies .This review has a number of limitations. First, only English language studies were included: considering that several clinical studies retrieved were conducted in non-English speaking countries, it is possible that some evidence on the clinical role of TARE has been overlooked. Moreover, individual level data used in the selected studies were not accessible. Individual rather than aggregate data, would have enriched the overall analysis .As regards to the clinical outcomes, the number of papers in which post-progression survival after TARE is described is very limited, although sorafenib is used quite often as second-line therapy after TARE, thus affecting post-progression and overall survival. This was an unavoidable bias assumed to be equally distributed among the studies and therefore not considered as an exclusion driver. Inclusion of post-progression therapies reflected in fact the field practice adopted in the management of HCC patients.The evidence that supports the use of radioembolization in HCC is based on retrospective or prospective cohort studies and no RCTs have been published comparing TARE with systemic therapies, in particular sorafenib, currently the mainstay for treating advanced HCC.Large-scale randomized controlled trials with overall survival as a primary endpoint exploring this comparison have been started . These trials and future prospective randomized studies of TARE vs. suitable comparators, are crucial to provide direct evidence to evaluate comparative effectiveness because, at least in advanced HCC radioembolization may achieve overall survivals in the range of 6-10 months  competitUnfortunately, a pooled analysis focused on tumor response was not feasible due to high heterogeneity in reporting this outcome across the included studies. In fact, different response criteria , imaging techniques, and time of radiological evaluation prevented a reliable assessment of this secondary endpoint. However, tumor response usually represents only a surrogate endpoint whereas OS, which is universally considered the primary outcome in oncological studies, was consistently assessed in our meta-analysis.versus TARE, two used Drug Eluting BeadsDEB-TACE) [Among the studies comparing TACE EB-TACE) , 29 and EB-TACE) , 35, 36.EB-TACE) , 45.Observational data allow a preliminary assessment of the incremental costs vs. incremental effectiveness (i.e. cost-effectiveness) of TARE vs. sorafenib and help in this setting to assess the value of presumably similar treatment options in field practice. In a recent cost-effectiveness analysis of TARE vs. TACE, patients with advanced BCLC-C were found to benefit from radioembolization at an increased cost  while inGiven the findings of this systematic review, based on safety and efficacy data from included studies, until the results of the ongoing trials become available, radioembolization appears to be a viable treatment option for patients with intermediate-advanced stage HCC.This review adopts the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement . In May 90, the review was conducted with a focus on patients with intermediate and advanced HCC stages according to BCLC staging system (stages B and C), the latter particularly when presenting with PVT.Inclusion criteria are shown in Table Abstracts and full-text selection was conducted independently by two expert reviewers . In case of debate on study eligibility a third senior reviewer (AF) was involved to reach consensus. Data were extracted using a customized template developed in Microsoft Excel based on the PICOS statement. Information recorded included study features, participants', intervention's and comparator's characteristics, safety and efficacy outcomes.Data referring to TARE were retrieved from all comparative and non-comparative studies identified. Relevant efficacy outcomes  were summarized and graphically presented through forest plots. When necessary, survival rates were derived from digitalization of Kaplan-Meier survival curves using the software Plot Digitizer 2.6.6©. OS was calculated as the difference between the date of the first treatment and the date of death from any cause, or last observation date in case of censoring. TTP was calculated from the first TARE treatment to the first progression at any site. Main adverse events, such as liver impairment, were tabulated and discussed qualitatively.2 metric [® software .Survival rates for OS and TTP from different studies were pooled through a random effect meta-analysis of proportions with exact binomial confidence intervals . A test 2 metric : the higThe methodological quality of included studies was assessed according to a modified version of the National Health Service Centre of Review and Dissemination criteria . Followi