Intensity modulated radiotherapy for high risk prostate cancer based on sentinel node SPECT imaging for target volume definition

BACKGROUND: The RTOG 94-13 trial has provided evidence that patients with high risk prostate cancer benefit from an additional radiotherapy to the pelvic nodes combined with concomitant hormonal ablation. Since lymphatic drainage of the prostate is highly variable, the optimal target volume definition for the pelvic lymph nodes is problematic. To overcome this limitation, we tested the feasibility of an intensity modulated radiation therapy (IMRT) protocol, taking under consideration the individual pelvic sentinel node drainage pattern by SPECT functional imaging. METHODS: Patients with high risk prostate cancer were included. Sentinel nodes (SN) were localised 1.5–3 hours after injection of 250 MBq (99m)Tc-Nanocoll using a double-headed gamma camera with an integrated X-Ray device. All sentinel node localisations were included into the pelvic clinical target volume (CTV). Dose prescriptions were 50.4 Gy (5 × 1.8 Gy / week) to the pelvis and 70.0 Gy (5 × 2.0 Gy / week) to the prostate including the base of seminal vesicles or whole seminal vesicles. Patients were treated with IMRT. Furthermore a theoretical comparison between IMRT and a three-dimensional conformal technique was performed. RESULTS: Since 08/2003 6 patients were treated with this protocol. All patients had detectable sentinel lymph nodes (total 29). 4 of 6 patients showed sentinel node localisations (total 10), that would not have been treated adequately with CT-based planning ('geographical miss') only. The most common localisation for a probable geographical miss was the perirectal area. The comparison between dose-volume-histograms of IMRT- and conventional CT-planning demonstrated clear superiority of IMRT when all sentinel lymph nodes were included. IMRT allowed a significantly better sparing of normal tissue and reduced volumes of small bowel, large bowel and rectum irradiated with critical doses. No gastrointestinal or genitourinary acute toxicity Grade 3 or 4 (RTOG) occurred. CONCLUSION: IMRT based on sentinel lymph node identification is feasible and reduces the probability of a geographical miss. Furthermore, IMRT allows a pronounced sparing of normal tissue irradiation. Thus, the chosen approach will help to increase the curative potential of radiotherapy in high risk prostate cancer patients

Indicators of "Healthy Aging" in older women (65-69 years of age). A data-mining approach based on prediction of long-term survival

<p>Abstract</p> <p>Background</p> <p>Prediction of long-term survival in healthy adults requires recognition of features that serve as early indicators of successful aging. The aims of this study were to identify predictors of long-term survival in older women and to develop a multivariable model based upon longitudinal data from the Study of Osteoporotic Fractures (SOF).</p> <p>Methods</p> <p>We considered only the youngest subjects (<it>n </it>= 4,097) enrolled in the SOF cohort (65 to 69 years of age) and excluded older SOF subjects more likely to exhibit a "frail" phenotype. A total of 377 phenotypic measures were screened to determine which were of most value for prediction of long-term (19-year) survival. Prognostic capacity of individual predictors, and combinations of predictors, was evaluated using a cross-validation criterion with prediction accuracy assessed according to time-specific AUC statistics.</p> <p>Results</p> <p>Visual contrast sensitivity score was among the top 5 individual predictors relative to all 377 variables evaluated (mean AUC = 0.570). A 13-variable model with strong predictive performance was generated using a forward search strategy (mean AUC = 0.673). Variables within this model included a measure of physical function, smoking and diabetes status, self-reported health, contrast sensitivity, and functional status indices reflecting cumulative number of daily living impairments (HR ≥ 0.879 or RH ≤ 1.131; P < 0.001). We evaluated this model and show that it predicts long-term survival among subjects assigned differing causes of death (e.g., cancer, cardiovascular disease; P < 0.01). For an average follow-up time of 20 years, output from the model was associated with multiple outcomes among survivors, such as tests of cognitive function, geriatric depression, number of daily living impairments and grip strength (P < 0.03).</p> <p>Conclusions</p> <p>The multivariate model we developed characterizes a "healthy aging" phenotype based upon an integration of measures that together reflect multiple dimensions of an aging adult (65-69 years of age). Age-sensitive components of this model may be of value as biomarkers in human studies that evaluate anti-aging interventions. Our methodology could be applied to data from other longitudinal cohorts to generalize these findings, identify additional predictors of long-term survival, and to further develop the "healthy aging" concept.</p

Web-based tool for dynamic functional outcome after acute ischemic stroke and comparison with existing models

BACKGROUND: Acute ischemic stroke (AIS) is one of the leading causes of death and adult disability worldwide. In the present study, we aimed to develop a web-based risk model for predicting dynamic functional status at discharge, 3-month, 6-month, and 1-year after acute ischemic stroke (Dynamic Functional Status after Acute Ischemic Stroke, DFS-AIS). METHODS: The DFS-AIS was developed based on the China National Stroke Registry (CNSR), in which eligible patients were randomly divided into derivation (60%) and validation (40%) cohorts. Good functional outcome was defined as modified Rankin Scale (mRS) score ≤ 2 at discharge, 3-month, 6-month, and 1-year after AIS, respectively. Independent predictors of each outcome measure were obtained using multivariable logistic regression. The area under the receiver operating characteristic curve (AUROC) and plot of observed and predicted risk were used to assess model discrimination and calibration. RESULTS: A total of 12,026 patients were included and the median age was 67 (interquartile range: 57–75). The proportion of patients with good functional outcome at discharge, 3-month, 6-month, and 1-year after AIS was 67.9%, 66.5%, 66.9% and 66.9%, respectively. Age, gender, medical history of diabetes mellitus, stroke or transient ischemic attack, current smoking and atrial fibrillation, pre-stroke dependence, pre-stroke statins using, admission National Institutes of Health Stroke Scale score, admission blood glucose were identified as independent predictors of functional outcome at different time points after AIS. The DFS-AIS was developed from sets of predictors of mRS ≤ 2 at different time points following AIS. The DFS-AIS demonstrated good discrimination in the derivation and validation cohorts (AUROC range: 0.837-0.845). Plots of observed versus predicted likelihood showed excellent calibration in the derivation and validation cohorts (all r = 0.99, P < 0.001). When compared to 8 existing models, the DFS-AIS showed significantly better discrimination for good functional outcome and mortality at discharge, 3-month, 6-month, and 1-year after AIS (all P < 0.0001). CONCLUSION: The DFS-AIS is a valid risk model to predict functional outcome at discharge, 3-month, 6-month, and 1-year after AIS. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12883-014-0214-z) contains supplementary material, which is available to authorized users