The aim of this study was to evaluate the diagnostic performance of 18 F-FDG PET/CT for the preoperative assessment of lymph node metastases (LNM) in endometrial cancer patients and for the assessment of endometrial cancer recurrence (ECR) after primary surgical treatment. Methods: A comprehensive search was performed on Pubmed/MEDLINE databases for studies reporting the diagnostic performance of 18 F-FDG PET/CT for assessment of LNM and ECR published up to August 15, 2015. Twenty-one studies (13 for LNM and 8 for ECR) were included in the systematic review and meta-analysis. Pooled estimates of sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio of the 18 F-FDG PET/CT were calculated along with 95% confidence intervals (CIs). A summary receiver-operating-characteristics curve (SROC) was constructed, and the area under the SROC curve (AUC) was determined along with Q* index. Results: The overall pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio, and AUC (with 95% CI) of 18 F-FDG PET/CT for detection of LNM were 0.72 (95% CI, 0.63-0.80), 0.94 (95% CI, 0.93-0.96), 10.9 (95% CI, 7.9-15.1), 0.36 (95% CI, 0.27-0.48), 39.7 (95% CI, 21.4-73.6), and 0.94 (95% CI, 0.85-0.99), respectively, whereas the corresponding numbers for detection of ECR were 0.95 (95% CI, 0.91-0.98), 0.91 (95% CI, 0.86-0.94), 8.8 (95% CI, 0.08 (95% CI, 171.7 (95% CI,3), and 0.97 (95% CI, 0.95-0.98), respectively. The overall diagnostic accuracy (Q* index) in LNM and ECR were 0.88 and 0.93, respectively. Conclusion: 18 F-FDG PET/CT has an excellent diagnostic performance for detecting LNM preoperatively and disease recurrence postoperatively in endometrial cancer patients.Key Words: endometrial cancer; FDG; PET and CT J Nucl Med 2016; 57:879-885 DOI: 10.2967/jnumed.115.170597 Endomet rial cancer is the most common gynecologic malignancy in the developed countries (1). The prognosis is traditionally determined by clinical and histopathologic factors-that is, age, histologic type, grade, and stage of disease including assessment of cervical invasion, depth of myometrial invasion, lymph node spread, and distant metastases (2-4). The 5-y overall survival rate is generally favorable, around 80%. However, pelvic lymph node metastases (LNM) represents the most common site for extrauterine disease at primary treatment, and the 5-y survival rate is around 50% for this patient subgroup (5).Currently, the final staging of endometrial cancer is based on histopathologic findings at primary surgery, which includes abdominal exploration, peritoneal cytology washing from the pelvis, hysterectomy, bilateral salpingo-oophorectomy, and lymphadenectomy in selected patients presumed to have a high risk of disease spread (6-8). Routine systemic pelvic lymphadenectomy for earlystage endometrial cancer disease, although not well defined as a surgical technique, improves detection of LNM, but the procedure showed no survival benefit in 2 randomized clinic...

Statistics Netherlands applies a design-based estimation procedure to produce road transportation figures. Frequent survey redesigns caused discontinuities in these series which obstruct the comparability of figures over time. Reductions in the sample size and changes in the sample design resulted in variance breaks and unacceptably large sampling errors in the recent part of the series. Both problems are addressed and solved simultaneously. Discontinuities and small sample sizes are accounted for by using a multivariate structural time series model that borrows strength over time and space. The paper illustrates an increased precision when we move from univariate models to a multivariate model where the domains are jointly modelled. This increase is especially significant in the most recent period when sample sizes become smaller, with standard errors of the design-based estimator of the target variables being reduced by 40-70% with the model-based approach.

Summary This study compares state space models (estimated with the Kalman filter with a frequentist approach to hyperparameter estimation) with multilevel time series models (based on the hierarchical Bayesian framework). The application chosen is the Dutch Travel Survey featuring small sample sizes and discontinuities caused by the survey redesigns. Both modelling approaches deliver similar point and variance estimates. Slight differences in model‐based variance estimates appear mostly in small‐scaled domains and are due to neglecting uncertainty around the hyperparameter estimates in the state space models, and to a lesser extent to skewness in the posterior distributions of the parameters of interest. The results suggest that the reduction in design‐based standard errors with the hierarchical Bayesian approach is over 50% at the provincial level, and over 30% at the national level.