We evaluated geographic variation of Type 1 and Type 2 diabetes mellitus (T1DM, T2DM) in four regions of the United States. Data on 807 incident T1DM cases diabetes and 313 T2DM cases occurring in 2002-03 in South Carolina (SC) and Colorado (CO), 5 counties in Washington (WA), and an 8 county region around Cincinnati, Ohio (OH) among youth aged 10 through 19 years were obtained from the SEARCH for Diabetes in Youth Study. Geographic patterns were evaluated in a Bayesian framework. Incidence rates differed between the study regions, even within race/ethnic groups. Significant small area variation within study region was observed for T1DM and for T2DM. Evidence for joint spatial correlation between T1DM and T2DM was present at the county level for SC (rSC= 0.31) and CO non-Hispanic whites (rCO= 0.40) and CO Hispanics (rCO= 0.72). At the tract level no evidence for meaningful joint spatial correlation was observed (rSC= -0.02; rCO= -0.02; rOH= 0.03; rWA= 0.09). Our study provides evidence for the presence of both regional and small-area, localized variation in type 1 and type 2 incidence among youth aged 10-19 years in the United States.

We developed a nomogram to predict the probability of extracapsular extension (ECE) in localized prostate cancer and to determine when the neurovascular bundle (NVB) may be spared. Total 1,471 Korean men who underwent radical prostatectomy for prostate cancer between 1995 and 2008 were included. We drew nonrandom samples of 1,031 for nomogram development, leaving 440 samples for nomogram validation. With multivariate logistic regression analyses, we made a nomogram to predicts the ECE probability at radical prostatectomy. Receiver operating characteristic (ROC) analyses were also performed to assess the predictive value of each variable alone and in combination. The internal validation was performed from 200 bootstrap re-samples and the external validation was also performed from the another cohort. Overall, 314 patients (30.5%) had ECE. Age, Prostate specific antigen (PSA), biopsy Gleason score, positive core ratio, and maximum percentage of biopsy tumor were independent predictors of the presence of ECE (all P values <0.05). The nomogram predicted ECE with good discrimination (an area under the ROC curve of 0.777). Our nomogram allows for the preoperative identification of patients with an ECE and may prove useful in selecting patients to receive nerve sparing radical prostatectomy.

PurposeDue to the availability of serum prostate specific antigen (PSA) testing, the detection rate of insignificant prostate cancer (IPC) is increasing. To ensure better treatment decisions, we developed a nomogram to predict the probability of IPC.Materials and MethodsThe study population consisted of 1,471 patients who were treated at multiple institutions by radical prostatectomy without neoadjuvant therapy from 1995 to 2008. We obtained nonrandom samples of n = 1,031 for nomogram development, leaving n = 440 for nomogram validation. IPC was defined as pathologic organ-confined disease and a tumor volume of 0.5 cc or less without Gleason grade 4 or 5. Multivariate logistic regression model (MLRM) coefficients were used to construct a nomogram to predict IPC from five variables, including serum prostate specific antigen, clinical stage, biopsy Gleason score, positive cores ratio and maximum % of tumor in any core. The performance characteristics were internally validated from 200 bootstrap resamples to reduce overfit bias. External validation was also performed in another cohort.ResultsOverall, 67 (6.5%) patients had a so-called "insignificant" tumor in nomogram development cohort. PSA, clinical stage, biopsy Gleason score, positive core ratio and maximum % of biopsy tumor represented significant predictors of the presence of IPC. The resulting nomogram had excellent discrimination accuracy, with a bootstrapped concordance index of 0.827.ConclusionOur current nomogram provides sufficiently accurate information in clinical practice that may be useful to patients and clinicians when various treatment options for screen-detected prostate cancer are considered.

This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.Abstract With the increasing development and commercial use of genetically modified maize, it is essential to develop an appropriate method for detection of individual LMO (Living modified organism) events for monitoring the samples. In South Korea, commercial planting and accidental or unintentional releases of LMOs into the environment were not approved. In this study, to increase the efficiency of LMO detection, we developed simultaneous detection methods for 11 LM maize events. This multiplex PCR detection method is economical, as it saves time, cost and labor. We developed 11 individual LM maize events, and applied 4 multiplex PCR sets to the LM maize samples. These results are confirmed by applying the multiplex analysis of LMO environmental monitoring from 2012 to 2014, which represents the unintentionally released LM maize samples. The data were correlated with event specific PCR results. Our results indicate that the multiplex PCR method developed is suitable for detection of LM maize in LMO monitoring.

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