Background: Prostate-specific antigen (PSA) testing is the primary method used to diagnose prostate cancer in the United States. Methods to integrate other risk factors associated with prostate cancer into individualized risk prediction are needed. We used prostate biopsy data from men who participated in the Prostate Cancer Prevention Trial (PCPT) to develop a predictive model of prostate cancer. Methods: We included 5519 men from the placebo group of the PCPT who underwent prostate biopsy, had at least one PSA measurement and a digital rectal examination (DRE) performed during the year before the biopsy, and had at least two PSA measurements performed during the 3 years before the prostate biopsy. Logistic regression was used to model the risk of prostate cancer and high-grade disease associated with age at biopsy, race, family history of prostate cancer, PSA level, PSA velocity, DRE result, and previous prostate biopsy. Risk equations were created from the estimated logistic regression models. All statistical tests were two-sided. Results: A total of 1211 (21.9%) men were diagnosed with prostate cancer by prostate biopsy. Variables that predicted prostate cancer included higher PSA level, positive family history of prostate cancer, and abnormal DRE result, whereas a previous negative prostate biopsy was associated with reduced risk. Neither age at biopsy nor PSA velocity contributed independent prognostic information. Higher PSA level, abnormal DRE result, older age at biopsy, and African American race were predictive for high-grade disease (Gleason score ≥7) whereas a previous negative prostate biopsy reduced this risk. Conclusions: This predictive model allows an individualized assessment of prostate cancer risk and risk of high-grade disease for men who undergo a prostate biopsy.

It has not been firmly established whether disturbed calcium-phosphate metabolism affects progression of chronic kidney disease (CKD) in humans. In this cohort study of 227 nondiabetic patients with CKD, we assessed fibroblast growth factor 23 (FGF23) plasma concentrations in addition to other variables involved in calcium-phosphate metabolism, and we followed 177 of the patients prospectively for a median of 53 months to assess progression of renal disease. In the baseline cohort, we found a significant inverse correlation between glomerular filtration rate and both c-terminal and intact FGF23 levels (both P < 0.001). The 65 patients who experienced a doubling of serum creatinine and/or terminal renal failure were significantly older, had a significantly lower glomerular filtration rate at baseline, and significantly higher levels of intact parathormone, c-terminal and intact FGF23, and serum phosphate (all P < 0.001). Cox regression analysis revealed that both c-terminal and intact FGF23 independently predict progression of CKD after adjustment for age, gender, GFR, proteinuria, and serum levels of calcium, phosphate, and parathyroid hormone. The mean follow-up time to a progression end point was 46.9 (95% CI 40.2 to 53.6) months versus 72.5 (95% CI 67.7 to 77.3) months for patients with c-terminal FGF23 levels above or below the optimal cut-off level of 104 rU/mL (derived by receiver operator curve analysis), respectively. In conclusion, FGF23 is a novel independent predictor of progression of renal disease in patients with nondiabetic CKD. Its pathophysiological significance remains to be elucidated.

Research from JAMA — Operating Characteristics of Prostate-Specific Antigen in Men With an Initial PSA Level of 3.0 ng/mL or Lower — ContextThree fourths of US men older than 50 years have been screened with prostate-specific antigen (PSA) for prostate cancer.ObjectiveTo estimate the receiver operating characteristic (ROC) curve for PSA.Design, Setting, and ParticipantsCalculation of PSA ROC curves in the placebo group of the Prostate Cancer Prevention Trial, a randomized, prospective study conducted from 1993 to 2003 at 221 US centers. Participants were 18 882 healthy men aged 55 years or older without prostate cancer and with PSA levels less than or equal to 3.0 ng/mL and normal digital rectal examination results, followed up for 7 years with annual PSA measurement and digital rectal examination. If PSA level exceeded 4.0 ng/mL or rectal examination result was abnormal, a prostate biopsy was recommended. After 7 years of study participation, an end-of-study prostate biopsy was recommended in all cancer-free men.Main Outcome MeasuresOperating characteristics of PSA for prostate cancer detection, including sensitivity, specificity, and ROC curve.ResultsOf 8575 men in the placebo group with at least 1 PSA measurement and digital rectal examination in the same year, 5587 (65.2%) had had at least 1 biopsy; of these, 1225 (21.9%) were diagnosed with prostate cancer. Of 1213 cancers with Gleason grade recorded, 250 (20.6%) were Gleason grade 7 or greater and 57 (4.7%) were Gleason grade 8 or greater. The areas under the ROC curve (AUC) for PSA to discriminate any prostate cancer vs no cancer, Gleason grade 7 or greater cancer vs no or lower-grade cancer, and Gleason grade 8 or greater cancer vs no or lower-grade cancer were 0.678 (95% confidence interval [CI], 0.666-0.689), 0.782 (95% CI, 0.748-0.816), and 0.827 (95% CI, 0.761-0.893), respectively (all P values <.001 for AUC vs 50%). For detecting any prostate cancer, PSA cutoff values of 1.1, 2.1, 3.1, and 4.1 ng/mL yielded sensitivities of 83.4%, 52.6%, 32.2%, and 20.5%, and specificities of 38.9%, 72.5%, 86.7%, and 93.8%, respectively. Age-stratified analyses showed slightly better performance of PSA in men younger than 70 years vs those 70 years or older with AUC values of 0.699 (SD, 0.013) vs 0.663 (SD, 0.013) (P = .03).ConclusionThere is no cutpoint of PSA with simultaneous high sensitivity and high specificity for monitoring healthy men for prostate cancer, but rather a continuum of prostate cancer risk at all values of PSA.

Inter-annual crop yield variation is driven in large parts by climate variability, wherein the climate components of temperature and precipitation often play the biggest role. Nonlinear effects of temperature on yield as well as interactions among the climate variables have to be considered. Links between climate and crop yield variability have been previously studied, both globally and at regional scales, but typically with additive models with no interactions, or when interactions were included, with implications not fully explained. In this study yearly country level yields of maize, rice, soybeans, and wheat of the top producing countries were combined with growing season temperature and SPEI (standardized precipitation evapotranspiration index) to determine interaction and intensification effects of climate variability on crop yield variability during 1961–2014. For maize, soybeans, and wheat, heat and dryness significantly reduced yields globally, while global effects for rice were not significant. But because of interactions, heat was more damaging in dry than in normal conditions for maize and wheat, and temperature effects were not significant in wet conditions for maize, soybeans, and wheat. Country yield responses to climate variability naturally differed between the top producing countries, but an accurate description of interaction effects at the country scale required sub-national data (shown only for the USA). Climate intensification, that is consecutive dry or warm years, reduced yields additionally in some cases, however, this might be linked to spillover effects of multiple growing seasons. Consequently, the effect of temperature on yields might be underestimated in dry conditions: While there were no significant global effects of temperature for maize and soybeans yields for average SPEI, the combined effects of high temperatures and drought significantly decreased yields of maize, soybeans, and wheat by 11.6, 12.4, and 9.2%, respectively.

Background: In the Prostate Cancer Prevention Trial (PCPT), men receiving finasteride had a 24.8% lower risk of prostate cancer than men receiving placebo but a higher risk of high-grade cancer. We examined the impact of finasteride on the sensitivity and area under the receiver operating characteristic curve (AUC) of prostate-specific antigen (PSA) for detecting prostate cancer. Methods: We studied men in the placebo and finasteride groups of the PCPT who had a prostate biopsy and concurrent PSA tests during the 7-year study. We compared the placebo and finasteride groups for sensitivity and AUC of PSA for the detection of all prostate cancer, of Gleason grade 7 or higher prostate cancer, and of Gleason grade 8 or higher prostate cancer. All statistical tests were two-sided. Results: Of 5112 men in the placebo group, prostate cancer was detected in 1111. Gleason tumor grade was available for 1100 men, of whom 240 had grade 7 or higher and 55 had grade 8 or higher. Of 4579 men in the finasteride group, 695 had prostate cancer. Gleason grade was available for 686 men, of whom 264 had grade 7 or higher and 81 had grade 8 or higher. The AUC of PSA for all outcomes was greater for the finasteride group than the placebo group. For detecting prostate cancer versus no cancer, the AUCs were 0.757 and 0.681, respectively ( P <.001); for detecting Gleason grade ≥7 versus ≤6 or no cancer, the AUCs were 0.838 and 0.781, respectively ( P = .003); and for detecting Gleason grade ≥8 versus ≤7 or no cancer, the AUCs were 0.886 and 0.824, respectively ( P = .071). The sensitivity of PSA was higher for men in the finasteride group than in the placebo group at all PSA cutoffs matched by specificity. Conclusions: PSA had statistically significantly better sensitivity and AUC for detecting prostate cancer in the finasteride arm of the PCPT than in the placebo arm. This bias would be expected to contribute to greater detection of all grades of prostate cancer with finasteride.