Incorporating PHI in decision making: external validation of the Rotterdam risk calculators for detection of prostate cancer.

PURPOSE: External validation of existing risk calculators (RC) to assess the individualized risk of detecting prostate cancer (PCa) in prostate biopsies is needed to determine their clinical usefulness. The objective was to externally validate the Rotterdam Prostate Cancer RCs 3 and 4 (RPCRC-3/4) and that incorporating PHI (RPCRC-PHI) in a contemporary Spanish cohort. METHODS: Multicenter prospective study that included patients suspicious of harboring PCa. Men who attended the urology consultation were tested for PHI before prostate biopsy. To evaluate the performance of the prediction models: discrimination (receiver operating characteristic (ROC) curves), calibration and net benefit [decision curve analysis (DCA)] were calculated. These analyses were carried out for detection of any PCa and clinically significant (cs)PCa, defined as ISUP grade ≥ 2. RESULTS: Among the 559 men included, 337 (60.28%) and 194 (34.7%) were diagnosed of PCa and csPCa, respectively. RPCRC-PHI had the best discrimination ability for detection of PCa and csPCa with AUCs of 0.85 (95%CI 0.82-0.88) and 0.82 (95%CI 0.78-0.85), respectively. Calibration plots showed that RPCRC-3/4 underestimates the risk of detecting PCa showing the need for recalibration. In DCA, RPCRC-PHI shows the highest net benefit compared to biopsy all men. CONCLUSIONS: The RPCRC-PHI performed properly in a contemporary clinical setting, especially for prediction of csPCa.

Do PHI and PHI density improve detection of clinically significant prostate cancer only in the PSA gray zone?

OBJECTIVES: Prostate health index (PHI) is a predictive biomarker of positive prostate biopsy. The majority of evidence refers to its use in the PSA gray zone (4-10 ng/mL) and negative digital rectal exam (DRE). We aim to evaluate and compare the predictive accuracy of PHI and PHI density (PHId) with PSA, percentage of free PSA and PSA density, in a wider range of patients for the detection of clinically significant prostate cancer (csPCa). METHODS: Multicenter prospective study that included patients suspicious of harboring prostate cancer. Non-probabilistic convenience sampling, where men who attended the urology consultation were tested for PHI before prostate biopsy. To evaluate and compare diagnostic accuracy AUC and decision curve analysis (DCA) were calculated. All these procedures were performed for the overall sample and the following subsamples: PSA < 4 ng/ml; PSA 4-10 ng/ml; PSA 4-10 ng/ml plus negative DRE and PSA > 10 ng/ml. RESULTS: Among the 559 men included, 194 (34.7%) were diagnosed of csPCa. PHI and PHId outperfomed PSA in all subgroups. PHI best diagnostic performance was found in PSA 4-10 ng/ml with negative DRE (sensitivity 93.33, NPV 96.04). Regarding AUC, significant differences were found between PHId and PSA in the subgroup of PSA 4-10 ng/ml, whatever DRE status. In DCA, PHI density shows the highest net benefit. CONCLUSIONS: PHI and PHId outperfom PSA in csPCa detection, not only in the PSA grey zone with negative DRE, but also in a wider range of PSA values. There is an urgent need of prospective studies to established a validated threshold and its incorporation in risk calculators.

Integrated 3D Hydrogel Waveguide Out-Coupler by Step-and-Repeat Thermal Nanoimprint Lithography: A Promising Sensor Device for Water and pH.

Hydrogel materials offer many advantages for chemical and biological sensoring due to their response to a small change in their environment with a related change in volume. Several designs have been outlined in the literature in the specific field of hydrogel-based optical sensors, reporting a large number of steps for their fabrication. In this work we present a three-dimensional, hydrogel-based sensor the structure of which is fabricated in a single step using thermal nanoimprint lithography. The sensor is based on a waveguide with a grating readout section. A specific hydrogel formulation, based on a combination of PEGDMA (Poly(Ethylene Glycol DiMethAcrylate)), NIPAAm (N-IsoPropylAcrylAmide), and AA (Acrylic Acid), was developed. This stimulus-responsive hydrogel is sensitive to pH and to water. Moreover, the hydrogel has been modified to be suitable for fabrication by thermal nanoimprint lithography. Once stimulated, the hydrogel-based sensor changes its topography, which is characterised physically by AFM and SEM, and optically using a specific optical set-up.

Modeling neural differentiation on micropatterned substrates coated with neural matrix components.

Topographical and biochemical characteristics of the substrate are critical for neuronal differentiation including axonal outgrowth and regeneration of neural circuits in vivo. Contact stimuli and signaling molecules allow neurons to develop and stabilize synaptic contacts. Here we present the development, characterization and functional validation of a new polymeric support able to induce neuronal differentiation in both PC12 cell line and adult primary skin-derived precursor cells (SKPs) in vitro. By combining a photolithographic technique with use of neural extracellular matrix (ECM) as a substrate, a biocompatible and efficient microenvironment for neuronal differentiation was developed.