Tumor regression grade of urothelial bladder cancer after neoadjuvant chemotherapy: a novel and successful strategy to predict survival.

Histopathologic tumor regression grades (TRGs) after neoadjuvant chemotherapy predict survival in different cancers. In bladder cancer, corresponding studies have not been conducted. Fifty-six patients with advanced invasive urothelial bladder cancer received neoadjuvant chemotherapy before cystectomy and lymphadenectomy. TRGs were defined as follows: TRG1: complete tumor regression; TRG2: >50% tumor regression; TRG3: 50% or less tumor regression. Separate TRGs were assigned for primary tumors and corresponding lymph nodes. The prognostic impact of these 2 TRGs, the highest (dominant) TRG per patient, and competing tumor features reflecting tumor regression (ypT/ypN stage, maximum diameter of the residual tumor) were determined. Tumor characteristics in initial transurethral resection of the bladder specimens were tested for response prediction. The frequency of TRGs 1, 2, and 3 in the primary tumors were n=16, n=19, and n=21; corresponding data from the lymph nodes were n=31, n=9, and n=16. Interobserver agreement in determination of the TRG was strong (κ=0.8). Univariately, all evaluated parameters were significantly (P≤0.001) related to overall survival; however, the segregation of the Kaplan-Meier curves was best for the dominant TRG. In multivariate analysis, only dominant TRG predicted overall survival independently (P=0.035). In transurethral resection specimens of the chemotherapy-naive bladder cancer, the only tumor feature with significant (P<0.03) predictive value for therapy response was a high proliferation rate. In conclusion, among all parameters reflecting tumor regression, the dominant TRG was the only independent risk factor. A favorable chemotherapy response is associated with a high proliferation rate in the initial chemotherapy-naive bladder cancer. This feature might help personalize neoadjuvant chemotherapy.

Comparison of partial least squares regression and principal component regression for pelvic shape prediction.

This paper studied two different regression techniques for pelvic shape prediction, i.e., the partial least square regression (PLSR) and the principal component regression (PCR). Three different predictors such as surface landmarks, morphological parameters, or surface models of neighboring structures were used in a cross-validation study to predict the pelvic shape. Results obtained from applying these two different regression techniques were compared to the population mean model. In almost all the prediction experiments, both regression techniques unanimously generated better results than the population mean model, while the difference on prediction accuracy between these two regression methods is not statistically significant (α=0.01).

3D volumetric intensity reconsturction from 2D x-ray images using partial least squares regression

Reconstruction of shape and intensity from 2D x-ray images has drawn more and more attentions. Previously introduced work suffers from the long computing time due to its iterative optimization characteristics and the requirement of generating digitally reconstructed radiographs within each iteration. In this paper, we propose a novel method which uses a patient-specific 3D surface model reconstructed from 2D x-ray images as a surrogate to get a patient-specific volumetric intensity reconstruction via partial least squares regression. No DRR generation is needed. The method was validated on 20 cadaveric proximal femurs by performing a leave-one-out study. Qualitative and quantitative results demonstrated the efficacy of the present method. Compared to the existing work, the present method has the advantage of much shorter computing time and can be applied to both DXA images as well as conventional x-ray images, which may hold the potentials to be applied to clinical routine task such as total hip arthroplasty (THA).

Robust Proximal Femur Segmentation in Conventional X-Ray Images via Random Forest Regression on Multi-resolution Gradient Features

In this paper, we propose a fully automatic, robust approach for segmenting proximal femur in conventional X-ray images. Our method is based on hierarchical landmark detection by random forest regression, where the detection results of 22 global landmarks are used to do the spatial normalization, and the detection results of the 59 local landmarks serve as the image cue for instantiation of a statistical shape model of the proximal femur. To detect landmarks in both levels, we use multi-resolution HoG (Histogram of Oriented Gradients) as features which can achieve better accuracy and robustness. The efficacy of the present method is demonstrated by experiments conducted on 150 clinical x-ray images. It was found that the present method could achieve an average point-to-curve error of 2.0 mm and that the present method was robust to low image contrast, noise and occlusions caused by implants.

Fully Automatic Segmentation of AP Pelvis X-rays via Random Forest Regression and Hierarchical Sparse Shape Composition

Knowledge of landmarks and contours in anteroposterior (AP) pelvis X-rays is invaluable for computer aided diagnosis, hip surgery planning and image-guided interventions. This paper presents a fully automatic and robust approach for landmarking and segmentation of both pelvis and femur in a conventional AP X-ray. Our approach is based on random forest regression and hierarchical sparse shape composition. Experiments conducted on 436 clinical AP pelvis x-rays show that our approach achieves an average point-to-curve error around 1.3 mm for femur and 2.2 mm for pelvis, both with success rates around 98%. Compared to existing methods, our approach exhibits better performance in both the robustness and the accuracy.

Somatostatin-based radiopeptide therapy with [177Lu-DOTA]-TOC versus [90Y-DOTA]-TOC in neuroendocrine tumours

PURPOSE Somatostatin-based radiopeptide treatment is generally performed using the β-emitting radionuclides (90)Y or (177)Lu. The present study aimed at comparing benefits and harms of both therapeutic approaches. METHODS In a comparative cohort study, patients with advanced neuroendocrine tumours underwent repeated cycles of [(90)Y-DOTA]-TOC or [(177)Lu-DOTA]-TOC until progression of disease or permanent adverse events. Multivariable Cox regression and competing risks regression were employed to examine predictors of survival and adverse events for both treatment groups. RESULTS Overall, 910 patients underwent 1,804 cycles of [(90)Y-DOTA]-TOC and 141 patients underwent 259 cycles of [(177)Lu-DOTA]-TOC. The median survival after [(177)Lu-DOTA]-TOC and after [(90)Y-DOTA]-TOC was comparable (45.5 months versus 35.9 months, hazard ratio 0.91, 95% confidence interval 0.63-1.30, p = 0.49). Subgroup analyses revealed a significantly longer survival for [(177)Lu-DOTA]-TOC over [(90)Y-DOTA]-TOC in patients with low tumour uptake, solitary lesions and extra-hepatic lesions. The rate of severe transient haematotoxicities was lower after [(177)Lu-DOTA]-TOC treatment (1.4 vs 10.1%, p = 0.001), while the rate of severe permanent renal toxicities was similar in both treatment groups (9.2 vs 7.8%, p = 0.32). CONCLUSION The present results revealed no difference in median overall survival after [(177)Lu-DOTA]-TOC and [(90)Y-DOTA]-TOC. Furthermore, [(177)Lu-DOTA]-TOC was less haematotoxic than [(90)Y-DOTA]-TOC.

Somatostatin-based radiotherapy with [90Y-DOTA]-TOC in neuroendocrine tumors: long-term outcome of a phase I dose escalation study

BACKGROUND We describe the long-term outcome after clinical introduction and dose escalation of somatostatin receptor targeted therapy with [90Y-DOTA]-TOC in patients with metastasized neuroendocrine tumors. METHODS In a clinical phase I dose escalation study we treated patients with increasing [90Y-DOTA]-TOC activities. Multivariable Cox regression and competing risk regression were used to compare efficacy and toxicities of the different dosage protocols. RESULTS Overall, 359 patients were recruited; 60 patients were enrolled for low dose (median: 2.4 GBq/cycle, range 0.9-7.8 GBq/cycle), 77 patients were enrolled for intermediate dose (median: 3.3 GBq/cycle, range: 2.0-7.4 GBq/cycle) and 222 patients were enrolled for high dose (median: 6.7 GBq/cycle, range: 3.7-8.1 GBq/cycle) [90Y-DOTA]-TOC treatment. The incidences of hematotoxicities grade 1-4 were 65.0%, 64.9% and 74.8%; the incidences of grade 4/5 kidney toxicities were 8.4%, 6.5% and 14.0%, and the median survival was 39 (range: 1-158) months, 34 (range: 1-118) months and 29 (range: 1-113) months. The high dose protocol was associated with an increased risk of kidney toxicity (Hazard Ratio: 3.12 (1.13-8.59) vs. intermediate dose, p = 0.03) and a shorter overall survival (Hazard Ratio: 2.50 (1.08-5.79) vs. low dose, p = 0.03). CONCLUSIONS Increasing [90Y-DOTA]-TOC activities may be associated with increasing hematological toxicities. The dose related hematotoxicity profile of [90Y-DOTA]-TOC could facilitate tailoring [90Y-DOTA]-TOC in patients with preexisting hematotoxicities. The results of the long-term outcome suggest that fractionated [90Y-DOTA]-TOC treatment might allow to reduce renal toxicity and to improve overall survival. (ClinicalTrials.gov number NCT00978211).

Plotting regression coefficients and other estimates in Stata

Graphical presentation of regression results has become increasingly popular in the scientific literature, as graphs are much easier to read than tables in many cases. In Stata such plots can be produced by the -marginsplot- command. However, while -marginsplot- is very versatile and flexible, it has two major limitations: it can only process results left behind by -margins- and it can only handle one set of results at the time. In this article I introduce a new command called -coefplot- that overcomes these limitations. It plots results from any estimation command and combines results from several models into a single graph. The default behavior of -coefplot- is to plot markers for coefficients and horizontal spikes for confidence intervals. However, -coefplot- can also produce various other types of graphs. The capabilities of -coefplot- are illustrated in this article using a series of examples.

COEFPLOT: Stata module to plot regression coefficients and other results

coefplot plots results from estimation commands or Stata matrices. Results from multiple models or matrices can be combined in a single graph. The default behavior of coefplot is to draw markers for coefficients and horizontal spikes for confidence intervals. However, coefplot can also produce various other types of graphs.

Reference Values and Factors Associated With Renal Resistive Index in a Family-Based Population Study

Increased renal resistive index (RRI) has been recently associated with target organ damage and cardiovascular or renal outcomes in patients with hypertension and diabetes mellitus. However, reference values in the general population and information on familial aggregation are largely lacking. We determined the distribution of RRI, associated factors, and heritability in a population-based study. Families of European ancestry were randomly selected in 3 Swiss cities. Anthropometric parameters and cardiovascular risk factors were assessed. A renal Doppler ultrasound was performed, and RRI was measured in 3 segmental arteries of both kidneys. We used multilevel linear regression analysis to explore the factors associated with RRI, adjusting for center and family relationships. Sex-specific reference values for RRI were generated according to age. Heritability was estimated by variance components using the ASSOC program (SAGE software). Four hundred women (mean age±SD, 44.9±16.7 years) and 326 men (42.1±16.8 years) with normal renal ultrasound had mean RRI of 0.64±0.05 and 0.62±0.05, respectively (P<0.001). In multivariable analyses, RRI was positively associated with female sex, age, systolic blood pressure, and body mass index. We observed an inverse correlation with diastolic blood pressure and heart rate. Age had a nonlinear association with RRI. We found no independent association of RRI with diabetes mellitus, hypertension treatment, smoking, cholesterol levels, or estimated glomerular filtration rate. The adjusted heritability estimate was 42±8% (P<0.001). In a population-based sample with normal renal ultrasound, RRI normal values depend on sex, age, blood pressure, heart rate, and body mass index. The significant heritability of RRI suggests that genes influence this phenotype.

Systematic review of the survival rate and incidence of biologic, technical, and esthetic complications of single implant abutments supporting fixed prostheses

Purpose: To assess the 5-year survival rate and number of technical, biologic, and esthetic complications involving implant abutments. Materials and Methods: Electronic (Medline) and hand searches were performed to assess studies on metal and ceramic implant abutments. Relevant data from a previous review were included. Two reviewers independently extracted the data. Failure and complication rates were analyzed, and estimates of 5-year survival proportions were calculated from the relationship between event rate and survival function. Multivariable robust Poisson regression was used to compare abutment characteristics. Results: The search yielded 1,558 titles and 274 abstracts. Twenty-four studies were selected for data analysis. The survival rate for ceramic abutments was 97.5% (95% confidence interval [CI]): 89.6% to 99.4%) and 97.6% (95% CI: 96.2% to 98.5%) for metal abutments. The overall 5-year rate for technical complications was 11.8% (95% CI: 8.5% to 16.3%), 8.9% (95% CI: 4.3% to 17.7%) for ceramic and 12.0% (95% CI: 8.5% to 16.8%) for metal abutments. Biologic complications occurred with an overall rate of 6.4% (95% CI: 3.3% to 12.0%), 10.4% (95% CI: 1.9% to 46.7%) for ceramic, and 6.1% (95% CI: 3.1% to 12.0%) for metal abutments. Conclusions: The present meta-analysis on single-implant prostheses presents high survival rates of single implants, abutments, and prostheses after 5 years of function. No differences were found for the survival and failure rates of ceramic and metal abutments. No significant differences were found for technical, biologic, and esthetic complications of internally and externally connected abutments.

Improvements in Implant Dentistry over the Last Decade: Comparison of Survival and Complication Rates in Older and Newer Publications

Purpose: The objective of this systematic review was to assess and compare the survival and complication rates of implant-supported prostheses reported in studies published in the year 2000 and before, to those reported in studies published after the year 2000. Materials and Methods: Three electronic searches complemented by manual searching were conducted to identify 139 prospective and retrospective studies on implant-supported prostheses. The included studies were divided in two groups: a group of 31 older studies published in the year 2000 or before, and a group of 108 newer studies published after the year 2000. Survival and complication rates were calculated using Poisson regression models, and multivariable robust Poisson regression was used to formally compare the outcomes of older and newer studies. Results: The 5-year survival rate of implant-supported prostheses was significantly increased in newer studies compared with older studies. The overall survival rate increased from 93.5% to 97.1%. The survival rate for cemented prostheses increased from 95.2% to 97.9%; for screw-retained reconstruction, from 77.6% to 96.8%; for implant-supported single crowns, from 92.6% to 97.2%; and for implant-supported fixed dental prostheses (FDPs), from 93.5% to 96.4%. The incidence of esthetic complications decreased in more recent studies compared with older ones, but the incidence of biologic complications was similar. The results for technical complications were inconsistent. There was a significant reduction in abutment or screw loosening by implant-supported FDPs. On the other hand, the total number of technical complications and the incidence of fracture of the veneering material was significantly increased in the newer studies. To explain the increased rate of complications, minor complications are probably reported in more detail in the newer publications. Conclusions: The results of the present systematic review demonstrated a positive learning curve in implant dentistry, represented in higher survival rates and lower complication rates reported in more recent clinical studies. The incidence of esthetic, biologic, and technical complications, however, is still high. Hence, it is important to identify these complications and their etiology to make implant treatment even more predictable in the future.