Spatial small area smoothing models for handling survey data with nonresponse.

Spatial smoothing models play an important role in the field of small area estimation. In the context of complex survey designs, the use of design weights is indispensable in the estimation process. Recently, efforts have been made in these spatial smoothing models, in order to obtain reliable estimates of the spatial trend. However, the concept of missing data remains a prevalent problem in the context of spatial trend estimation as estimates are potentially subject to bias. In this paper, we focus on spatial health surveys where the available information consists of a binary response and its associated design weight. Furthermore, we investigate the impact of nonresponse as missing data on a range of spatial models for different missingness mechanisms and different degrees of missingness by means of an extensive simulation study. The computations were performed in R, using INLA and other existing packages. The results show that weight adjustment to correct for missingness has a beneficial effect on the bias in the missing at random setting for all models. Furthermore, we estimate the geographical distribution of perceived health at the district level based on the Belgian Health Interview Survey (2001). Copyright © 2017 John Wiley & Sons, Ltd.

Spatiotemporal multivariate mixture models for Bayesian model selection in disease mapping.

It is often the case that researchers wish to simultaneously explore the behavior of and estimate overall risk for multiple, related diseases with varying rarity while accounting for potential spatial and/or temporal correlation. In this paper, we propose a flexible class of multivariate spatio-temporal mixture models to fill this role. Further, these models offer flexibility with the potential for model selection as well as the ability to accommodate lifestyle, socio-economic, and physical environmental variables with spatial, temporal, or both structures. Here, we explore the capability of this approach via a large scale simulation study and examine a motivating data example involving three cancers in South Carolina. The results which are focused on four model variants suggest that all models possess the ability to recover simulation ground truth and display improved model fit over two baseline Knorr-Held spatio-temporal interaction model variants in a real data application.

Spatio-temporal Bayesian model selection for disease mapping.

Spatio-temporal analysis of small area health data often involves choosing a fixed set of predictors prior to the final model fit. In this paper, we propose a spatio-temporal approach of Bayesian model selection to implement model selection for certain areas of the study region as well as certain years in the study time line. Here, we examine the usefulness of this approach by way of a large-scale simulation study accompanied by a case study. Our results suggest that a special case of the model selection methods, a mixture model allowing a weight parameter to indicate if the appropriate linear predictor is spatial, spatio-temporal, or a mixture of the two, offers the best option to fitting these spatio-temporal models. In addition, the case study illustrates the effectiveness of this mixture model within the model selection setting by easily accommodating lifestyle, socio-economic, and physical environmental variables to select a predominantly spatio-temporal linear predictor.

Services and supports for young children with Down syndrome: parent and provider perspectives.

BACKGROUND: As individuals with Down syndrome are living longer and more socially connected lives, early access to supports and services for their parents will ensure an optimal start and improved outcomes. The family's journey begins at the child's diagnosis, and cumulative experiences throughout infancy and childhood set the tone for a lifetime of decisions made by the family regarding services, supports and activities. METHODS: This study utilized focus groups and interviews with seven nurses, five therapists, 25 service co-ordinators, and 10 English- and three Spanish-speaking parents to better understand family experiences and perceptions on accessing Down syndrome-related perinatal, infant and childhood services and supports. RESULTS: Parents and providers reflected on key early life issues for children with Down syndrome and their families in five areas: prenatal diagnosis; perinatal care; medical and developmental services; care co-ordination and services; and social and community support. CONCLUSIONS: Systems of care are not consistently prepared to provide appropriate family-centred services to individuals with Down syndrome and their families. Individuals with disabilities require formal and informal supports from birth to achieve and maintain a high quality of life.

Space-Time Areal Mixture Model: Relabeling Algorithm and Model Selection Issues.

With the growing popularity of spatial mixture models in cluster analysis, model selection criteria have become an established tool in the search for parsimony. However, the label-switching problem is often inherent in Bayesian implementation of mixture models and a variety of relabeling algorithms have been proposed. We use a space-time mixture of Poisson regression models with homogeneous covariate effects to illustrate that the best model selected by using model selection criteria does not always support the model that is chosen by the optimal relabeling algorithm. The results are illustrated for real and simulated datasets. The objective is to make the reader aware that if the purpose of statistical modeling is to identify clusters, applying a relabeling algorithm to the model with the best fit may not generate the optimal relabeling.

Spatial smoothing models to deal with the complex sampling design and nonresponse in the Florida BRFSS survey.

Public health and governmental organizations have acknowledged the importance of obtaining information of various characteristics for small areas, such as counties. Spatial smoothing models have been developed to gain reliable information on the geographical distribution of the outcome of interest. When the geographical analysis is based on survey data, two issues pose challenges: (1) the complex design of the survey and (2) the presence of missing data due to non-response. We investigate the influence of missing data and the adjustment thereof in the context of the 2013 Florida Behavioral Risk Factor Surveillance System (BRFSS) health survey. We focus on the application and comparison of the Hajek ratio estimator and two model-based approaches for estimation of the spatial trend of the prevalence of having no health insurance coverage. The model-based methods are compared using the Deviance Information Criterion which show the benefits of modeling the weights as flexibly as possible. Methods are extended towards subgroup analyses and the estimation of area-specific standardized rates, where household incomes was identified as an important factor to include in the analysis.

A selected review and personal experience with robotic prostatectomy: implications for adoption of this new technology in the United Kingdom.

Robot-assisted laparoscopic prostatectomy (RALP) is a rapidly evolving technique for the treatment of localized prostate cancer. However, cynics point to the increasing role of market forces in the robotic revolution. As yet, Europe has not taken up RALP in large numbers and this may in part relate to the high level of expertise in laparoscopy previously gained. Furthermore, setting up a robotic programme is a major undertaking for many surgical units. This review discusses some of the challenges in the development of a robotic service drawn from personal experience within the United Kingdom. Furthermore, available data on RALP versus open and laparoscopic approaches are reviewed for surgical and cancer-related outcomes. Preliminary data appear to show an advantage over open prostatectomy with reduced blood loss, decreased pain and early mobilisation and shorter hospital stay. Most intra-institutional studies demonstrate better postoperative continence and potency with RALP; however, this needs to be viewed in the context of a paucity of randomized data available in the literature. There is no definitive data to show an advantage over standard laparoscopic surgery, but the fact that this technique has reached parity with laparoscopy within 5 years is encouraging: with continued experience, the hope is that results will continue to improve.

Comparison of glyburide and insulin for the management of gestational diabetics with markedly elevated oral glucose challenge test and fasting hyperglycemia.

OBJECTIVE: To compare the effectiveness of glyburide and insulin for the treatment of Gestational diabetes mellitus (GDM) in women who had OGCT >or=200 mg/dl and fasting hyperglycemia. STUDY DESIGN: A retrospective study was performed among a subset of women treated with glyburide or insulin for GDM from 1999 to 2002 with an OGCT >or=200 mg/dl and pretreatment fasting plasma glucose >or=105 mg/dl. Exclusion criteria included pretreatment fasting >or=140 mg/dl, gestational age >or=34 weeks and multiple gestation. Maternal and neonatal outcomes were assessed. Statistical methods included bivariate and multivariable logistic regression analyses. RESULTS: In 1999 to 2000, 78 women were treated with insulin; in 2001 to 2002, 44 of 69 (64%) received glyburide. There were no statistically significant differences between the two groups with regards to mean OGCT (230+/-25 vs 223+/-23 mg/dl, P=0.07) and mean pretreatment fasting (120+/-10 vs 119+/-11 mg/dl, P=0.45). Seven women (16%) failed glyburide. Women in the insulin group were younger (31.5+/-5.8 vs 35.2+/-4.7 years, P<0.001) and had a higher mean BMI (32.4+/-6.4 vs 29.1+/-5.8 kg/m(2), P=0.003) compared to glyburide group. There were no significant differences in birth weight (3524+/-548 vs 3420+/-786 g, P=0.65), macrosomia (19 vs 23%, P=0.65), pre-eclampsia (12 vs 11%, P=0.98) or cesarean delivery (39 vs 46%, P=0.45). Neonates in the glyburide group were diagnosed more frequently with hypoglycemia (34 vs 14%, P=0.01). When controlled for confounders, macrosomia was found to be associated with glyburide treatment (OR 3.5, 95% CI 1.1 to 11.4). CONCLUSION: In women with GDM who had a markedly elevated OGCT and fasting hyperglycemia, glyburide achieved similar birth weights and delivery outcomes but was associated with an increased risk of macrosomia. The possible increased risk of neonatal hypoglycemia in the glyburide group warrants further investigation.

Testosterone replacement therapy for late onset hypogonadism: what is the risk of inducing prostate cancer?

Prescription sales of testosterone have risen considerably over the last decade and are likely to continue to grow as further preparations become available. Testosterone promotes existing prostate cancer; however, concern does exist as to whether or not testosterone therapy induces prostate cancer. The aim of this article is to review the evidence for such a link.

Allelic imbalance and biochemical outcome after radical prostatectomy.

OBJECTIVE: To compare the incidence of allelic imbalance (AI) in men with rapid disease progression with those who remained disease free after radical prostatectomy, with the aim of identifying genetic markers to predict prognosis and guide further treatment. PATIENTS AND METHODS: Tumour and normal DNA were extracted from two matched groups of 31 men with extracapsular node-negative (pT3N0) prostate cancer who had undergone radical prostatectomy. One group comprised men who developed biochemical recurrence within 2 years of surgery and one group were prostate-specific antigen (PSA) free for at least 3 years. Men were matched for Gleason grade, preoperative PSA and pathological stage. Analysis was performed by genotyping. RESULTS: Allelic imbalance was analysed using 30 markers, and was seen in at least one marker in 57 (92%) of the cases. Deletion at marker D10S211 (10p12.1) was significantly more common in the relapse group than the non-relapse group (35 vs 5%, P=0.03). CONCLUSIONS: This study demonstrates significant association between AI on chromosome 10 and biochemical progression after radical prostatectomy.

The frequency of germ-line mutations in the breast cancer predisposition genes BRCA1 and BRCA2 in familial prostate cancer. The Cancer Research Campaign/British Prostate Group United Kingdom Familial Prostate Cancer Study Collaborators.

Predisposition to prostate cancer has a genetic component, and there are reports of familial clustering of breast and prostate cancer. Two highly penetrant genes that predispose individuals to breast cancer (BRCA1 and BRCA2) are known to confer an increased risk of prostate cancer of about 3-fold and 7-fold, respectively, in breast cancer families. Blood DNA from affected individuals in 38 prostate cancer clusters was analyzed for germ-line mutations in BRCA1 and BRCA2 to assess the contribution of each of these genes to familial prostate cancer. Seventeen DNA samples were each from an affected individual in families with three or more cases of prostate cancer at any age; 20 samples were from one of affected sibling pairs where one was < or = 67 years at diagnosis. No germ-line mutations were found in BRCA1. Two germ-line mutations in BRCA2 were found, and both were seen in individuals whose age at diagnosis was very young (< or = 56 years) and who were members of an affected sibling pair. One is a 4-bp deletion at base 6710 (exon 11) in a man who had prostate cancer at 54 years, and the other is a 2-bp deletion at base 5531 (exon 11) in a man who had prostate cancer at 56 years. In both cases, the wild-type allele was lost in the patient's prostate tumor at the BRCA2 locus. However, intriguingly, in neither case did the affected brother also carry the mutation. Germ-line mutations in BRCA2 may therefore account for about 5% of prostate cancer in familial clusters.

Estimating bias in derived body mass index in the Maternity Experiences Survey. / Estimation du biais lié à l'indice de masse corporelle utilisé dans l'Enquête canadienne sur l'expérience de la maternité.

INTRODUCTION: The objective of this study was to assess bias in the body mass index (BMI) measure in the Canadian Maternity Experiences Survey (MES) and possible implications of bias on the relationship between BMI and selected pregnancy outcomes. METHODS: We assessed BMI classification based on self-reported versus measured values. We used a random sample of 6175 women from the MES, which derived BMI from self-reported height and weight, and a random sample of 259 women who had previously given birth from the Canadian Health Measures Survey (CHMS), which derived BMI from self-reported and measured height and weight. Two correction equations were applied to self-reported based BMI, and the impact of these corrections on associations between BMI and caesarean section, small-for-gestational age (SGA) and large-for-gestational age (LGA) births was studied. RESULTS: Overall, 86.9% of the CHMS subsample was classified into the same BMI category based on self-reported versus measured data. However, misclassification had a substantial effect on the proportion of women in underweight and obese BMI categories. For example, 14.5% versus 20.8% of women were classified as obese based on self-reported data versus measured data. Corrections improved estimates of obesity prevalence, but over- and underestimated other BMI categories. Corrections had nonsignificant effects on the associations between BMI and SGA, LGA, and caesarean section. CONCLUSION: While there was high concordance in BMI classification based on selfreported versus measured height and weight, bias in self-reported based measures may slightly over- or underestimate the risks associated with a particular BMI class. However, the general trend in associations is unaffected.

INTRODUCTION: Cette étude visait à évaluer le biais dans la mesure de l'indice de masse corporelle (IMC) dans l'Enquête canadienne sur l'expérience de la maternité (ECEM) ainsi que les répercussions possibles de ce biais sur l'association entre l'IMC et certaines issues de grossesse. MÉTHODOLOGIE: Nous avons évalué la répartition des valeurs de l'IMC en comparant des données autodéclarées et des données mesurées. Nous avons utilisé un échantillon aléatoire de 6 175 participantes à l'ECEM dont l'IMC avait été calculé d'après la taille et le poids autodéclarés et un échantillon aléatoire de 259 participantes à l'Enquête canadienne sur les mesures de santé (ECMS) ayant déjà accouché et dont l'IMC avait été calculé d'après la taille et le poids autodéclarés et mesurés. Nous avons appliqué deux équations de correction à l'IMC fondé sur des valeurs autodéclarées, et nous avons examiné l'impact de ces corrections sur les associations entre l'IMC et un accouchement par césarienne, un faible poids pour l'âge gestationnel (FPAG) et un poids élevé pour l'âge gestationnel (PEAG). RÉSULTATS: Dans l'ensemble, 86,9 % des femmes du sous-échantillon de l'ECMS appartenaient à la même catégorie d'IMC lorsque ses valeurs étaient autodéclarées et lorsqu'elles étaient mesurées. Cependant, les différences de répartition ont eu un effet considérable sur la proportion de femmes des catégories de poids insuffisant et d'obésité. Par exemple, le pourcentage de femmes classées comme obèses était de 14,5 % avec les données autodéclarées contre 20,8 % avec les données mesurées. Les corrections ont permis d'améliorer les estimations de la prévalence de l'obésité, mais ont surestimé ou sous-estimé les autres catégories d'IMC. Les corrections ont eu un effet non significatif sur les associations entre l'IMC et l'accouchement par césarienne, le FPAG et le PEAG. CONCLUSION: Bien que la concordance pour la répartition des valeurs de l'IMC entre la taille et le poids autodéclarés et la taille et le poids mesurés soit élevée, il existe un biais dans les mesures fondées sur les valeurs autodéclarées susceptible d'entraîner de légères surestimations ou sous-estimations des risques associés à une catégorie d'IMC donnée. La tendance générale des associations reste néanmoins inchangée.

Model-based inference for small area estimation with sampling weights.

Obtaining reliable estimates about health outcomes for areas or domains where only few to no samples are available is the goal of small area estimation (SAE). Often, we rely on health surveys to obtain information about health outcomes. Such surveys are often characterised by a complex design, stratification, and unequal sampling weights as common features. Hierarchical Bayesian models are well recognised in SAE as a spatial smoothing method, but often ignore the sampling weights that reflect the complex sampling design. In this paper, we focus on data obtained from a health survey where the sampling weights of the sampled individuals are the only information available about the design. We develop a predictive model-based approach to estimate the prevalence of a binary outcome for both the sampled and non-sampled individuals, using hierarchical Bayesian models that take into account the sampling weights. A simulation study is carried out to compare the performance of our proposed method with other established methods. The results indicate that our proposed method achieves great reductions in mean squared error when compared with standard approaches. It performs equally well or better when compared with more elaborate methods when there is a relationship between the responses and the sampling weights. The proposed method is applied to estimate asthma prevalence across districts.

Clinical ease of using doxazosin in BPH patients with and without hypertension.

Clinical studies have demonstrated that doxazosin therapy reduced blood pressure (BP) in patients with benign prostatic hyperplasia (BPH) who were hypertensive at baseline but not in patients who were physiologically or pharmacologically normotensive at baseline. In patients with BPH and uncontrolled hypertension, despite treatment with other antihypertensive drugs, the addition of doxazosin resulted in improved control with significant reductions in BP. The new formulation, doxazosin gastrointestinal therapeutic system (GITS), is initiated at a therapeutic dose, simplifying dose titration. Based on its efficacy and pharmacokinetic and tolerability profiles, doxazosin GITS is an effective and well-tolerated treatment for normotensive and hypertensive patients with BPH.

Nerve-sparing radical retropubic prostatectomy: techniques and clinical considerations.

There are essentially two ways to accomplish nerve preservation during radical retropubic prostatectomy: the 'apical approach' described by Walsh and the so-called 'lateral approach', a simplified method where the dissection is initially conducted on the portion of the bundles that courses posterolateral to the prostate. Do the different techniques differ in the ability to preserve potency and in the positive surgical margins rate? No previous study has addressed this question. Above all, the preoperative and intraoperative indications to spare or not the nerves remain a matter of debate. The present review is an attempt to elucidate these questions in light of the current literature.

p21WAF1/CIP1 gene is inactivated in metastatic prostatic cancer cell lines by promoter methylation.

INTRODUCTION: p21WAF1/CIP1 may act as a tumour suppressor gene (TSG) and loss of the p21WAF1/CIP1 gene has been reported in several solid tumours. The aim of this study was to see whether p21WAF1/CIP1 was expressed in metastatic prostate cancer cell lines and to determine if there was methylation of the p21WAF1/CIP1 promoter. METHOD: PC3, LNCaP and DU145 metastatic prostate cancer cell lines, 1542NP normal prostate, and RD rhabdomyosarcoma cell lines were cultured in the demethylating agent 5-Aza-2 deoxycytidine (5-Aza-CdR). p21WAF1/CIP1 mRNA expression was analysed by RT-PCR. DNA from untreated cell lines was modified with sodium bisulphite and promoter sequencing was performed. RESULTS: p21WAF1/CIP1 was expressed at low or undetectable levels in metastatic prostate cancer cell lines but expression was reactivated by treatment with 5-Aza-CdR. Sequence analysis of the promoter region revealed several sites of methylation at the 5' end of a CpG island in the PC3, LNCaP and DU145 cell line DNA but not in the normal prostate control DNA. Most notably the Sis-inducible element (SEI)-1-a STAT1-binding site, was methylated. CONCLUSIONS: In this study, we show that p21WAF1/CIP1 expression in metastatic prostate cancer cell lines is enhanced as a result of demethylation of the DNA. Furthermore, several cytosine residues in the promoter region are methylated, including critical binding sites. The inhibition of the STAT1-signalling pathway by methylation of the promoter may inactivate the p21WAF1/CIP1 TSG in prostate cancer.

Prostatic intraepithelial neoplasia: a risk factor for prostate cancer.

Prostatic Intraepithelial Neoplasia (PIN) is an increasingly common finding at ultrasound guided prostate biopsy, with the high grade form (HGPIN) thought to be "precancerous". With the more widespread use of extended biopsy protocols, taking sometimes up to 14 cores or more, the incidence of HGPIN can be up to 25%. Histologically, it has many features in common with cancer of the prostate and has been shown to be both associated with cancer at the time of its finding and predictive for the development of prostate cancer in the future. Basic science research has demonstrated genes common specifically to both prostate cancer and HGPIN and immunostaining studies of microvessel density may help to differentiate HGPIN from lower risk PIN. There are no active treatments for HGPIN although there are trials to assess the effectiveness of hormonal therapy and nutritional supplements. Currently most urologists recommend that patients should be followed at 6 monthly intervals with regular PSA and repeat biopsies as indicated.