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Background Multiparametric magnetic resonance imaging (mpMRI) is gaining widespread acceptance in prostate cancer (PC) diagnosis and improves significant PC (sPC; Gleason score≥3+4) detection. Decision making based on European Randomised Study of Screening for PC (ERSPC) risk-calculator (RC) parameters may overcome prostate-specific antigen (PSA) limitations. Objective We added pre-biopsy mpMRI to ERSPC-RC parameters and developed risk models (RMs) to predict individual sPC risk for biopsy-naive men and men after previous biopsy. Design, setting, and participants We retrospectively analyzed clinical parameters of 1159 men who underwent mpMRI prior to MRI/transrectal ultrasound fusion biopsy between 2012 and 2015. Outcome measurements and statistical analysis Multivariate regression analyses were used to determine significant sPC predictors for RM development. The prediction performance was compared with ERSPC-RCs, RCs refitted on our cohort, Prostate Imaging Reporting and Data System (PI-RADS) v1.0, and ERSPC-RC plus PI-RADSv1.0 using receiver-operating characteristics (ROCs). Discrimination and calibration of the RM, as well as net decision and reduction curve analyses were evaluated based on resampling methods. Results and limitations PSA, prostate volume, digital-rectal examination, and PI-RADS were significant sPC predictors and included in the RMs together with age. The ROC area under the curve of the RM for biopsy-naive men was comparable with ERSPC-RC3 plus PI-RADSv1.0 (0.83 vs 0.84) but larger compared with ERSPC-RC3 (0.81), refitted RC3 (0.80), and PI-RADS (0.76). For postbiopsy men, the novel RM's discrimination (0.81) was higher, compared with PI-RADS (0.78), ERSPC-RC4 (0.66), refitted RC4 (0.76), and ERSPC-RC4 plus PI-RADSv1.0 (0.78). Both RM benefits exceeded those of ERSPC-RCs and PI-RADS in the decision regarding which patient to receive biopsy and enabled the highest reduction rate of unnecessary biopsies. Limitations include a monocentric design and a lack of PI-RADSv2.0. Conclusions The novel RMs, incorporating clinical parameters and PI-RADS, performed significantly better compared with RMs without PI-RADS and provided measurable benefit in making the decision to biopsy men at a suspicion of PC. For biopsy-naive patients, both our RM and ERSPC-RC3 plus PI-RADSv1.0 exceeded the prediction performance compared with clinical parameters alone. Patient summary Combined risk models including clinical and imaging parameters predict clinically relevant prostate cancer significantly better than clinical risk calculators and multiparametric magnetic resonance imaging alone. The risk models demonstrate a benefit in making a decision about which patient needs a biopsy and concurrently help avoid unnecessary biopsies.

Objective Smoking is an important risk factor in the development of community-acquired pneumonia (CAP). This study was designed to investigate the relationship between nicotine dependence level and the development of CAP. Materials and Methods The Fagerstrom test for nicotine dependence (FTND) was performed to measure nicotine dependence level (NDL). Subjects with a Fagerstrom score (FS) of 5 or lower were defined as low dependence level and a FS score of 6 or higher was defined as high dependence level. Results The risk of pneumonia development was higher in smokers than in nonsmokers (OR=2.19, 95% CI 1.13-4.23). The pneumonia development risk was 1.91 times higher in the low dependence level group compared to nonsmokers (OR=1.91, 95% CI 0.95-3.83). In the high nicotine dependence level group pneumonia risk was 2.93 times higher than in nonsmokers (OR=2.93, 95% CI 1.34-6.36). We also studied the relationship between CAP and the time to the first cigarette of the day. Risk was the lowest in the smoker group of after 60 minutes and risk ratios increased with decreased time. Conclusion In this study, a high nicotine dependence level was found to be a risk factor associated with smoking for CAP development. The time period of the first cigarette after waking up is also important in pneumonia development as well as in the nicotine dependence level.

Aim: We aimed to describe the levels of leucocyte count, erythrocyte sedimentation rate (ESR) and high sensitive C-Reactive Protein (hsCRP), and to investigate the relation of these biomarkers with the ratio of parenchymal infiltration (RPI) in patients with Chlamydia pneumoniae pneumonia (CPP). Material and Methods: The diagnosis of CPP was based on serologic testing. Patients with CPP were analyzed the blood leucocyte counts, ESR and hsCRP levels. The parenchymal infiltration ratio, given as percent, was calculated from the high resolution computerized tomography (HRCT) images using the following formula: Pulmonary infiltration ratio = number of images showing infiltration in HRCT x 100 / number of all images x 2. The relation of the extent of the infiltrated lung parenchyma, shown by HRCT, with the leucocyte count, ESR and sCRP was investigated.Results: Thirty two patients with CPP were included this study. Increasing levels of blood leucocyte counts in 14 (43.7 %), ESR in 27 (84.3 %) and hsCRP in 26 (81.2 %) patients were observed. High sensitive CRP was moderately but significantly correlated with RPI (r = 0.476, p = 0.006). However, RPI was not significantly correlated with blood leucocyte count and ESR (r = 0,011, p = 0,952 ve r = ,102, p = 0,580, respectively). Conclusions: Although both ESR and hsCRP were useful to detect infection, only hsCRP was correlated with the extent of parenchymal infiltration. Therefore, as a parameter sCRP can be used to evaluate the severity of CPP but larger series are needed to confirm this finding.