Making decisions about treatment for localized prostate cancer

Objective To describe the decision-making processes used by men diagnosed with localized prostate cancer who were considering treatment. Patients and methods Men newly diagnosed with localized prostate cancer from outpatient urology clinics and urologist's private practices were approached before treatment. Their decision-making processes and information-seeking behaviour was assessed; demographic information was also obtained. Results Of 119 men approached, 108 (90%) were interviewed; 91% reported non-systematic decision processes, with deferral to the doctor, positive and negative recollections of others' cancer experiences, and the pre-existing belief that surgery is a better cancer treatment being most common. For systematic information processing the mean (SD, range) number of items considered was 4.19 (2.28, 0-11), with 57% of men considering four or fewer treatment/medical aspects of prostate cancer. Men most commonly considered cancer stage (59%), urinary incontinence (55%) and impotence (51%) after surgery, and low overall mortality (45%). Uncertainty about probabilities for cure was reported by 43% of men and fear of cancer spread by 37%. Men also described uncertainty about the probabilities of side-effects (27%), decisional uncertainty (25%) and anticipated decisional regret (18%). Overall, 73% of men sought information about prostate cancer from external sources, most commonly the Internet, followed by family and friends. Conclusions In general, men did not use information about medical treatments comprehensively or systematically when making treatment decisions, and their processing of medical information was biased by their previous beliefs about cancer and health. These findings have implications for the provision of informational and decisional support to men considering prostate cancer treatment.

Comparison of an ELISA and an LC/MS/MS method for measuring tacrolimus concentrations and making dosage decisions in transplant recipients

This study compared an enzyme-linked immunosorbent assay (ELISA) to a liquid chromatography-tandem mass spectrometry (LC/MS/MS) technique for measurement of tacrolimus concentrations in adult kidney and liver transplant recipients, and investigated how assay choice influenced pharmacokinetic parameter estimates and drug dosage decisions. Tacrolimus concentrations measured by both ELISA and LC/MS/MS from 29 kidney (n = 98 samples) and 27 liver (n = 97 samples) transplant recipients were used to evaluate the performance of these methods in the clinical setting. Tacrolimus concentrations measured by the two techniques were compared via regression analysis. Population pharmacokinetic models were developed independently using ELISA and LC/MS/MS data from 76 kidney recipients. Derived kinetic parameters were used to formulate typical dosing regimens for concentration targeting. Dosage recommendations for the two assays were compared. The relation between LC/MS/MS and ELISA measurements was best described by the regression equation ELISA = 1.02 . (LC/MS/MS) + 0.14 in kidney recipients, and ELISA = 1.12 . (LC/MS/MS) - 0.87 in liver recipients. ELISA displayed less accuracy than LC/MS/MS at lower tacrolimus concentrations. Population pharmacokinetic models based on ELISA and LC/MS/MS data were similar with residual random errors of 4.1 ng/mL and 3.7 ng/mL, respectively. Assay choice gave rise to dosage prediction differences ranging from 0% to 30%. ELISA measurements of tacrolimus are not automatically interchangeable with LC/MS/MS values. Assay differences were greatest in adult liver recipients, probably reflecting periods of liver dysfunction and impaired biliary secretion of metabolites. While the majority of data collected in this study suggested assay differences in adult kidney recipients were minimal, findings of ELISA dosage underpredictions of up to 25% in the long term must be investigated further.

Future contributions of crop modelling - from heuristics and supporting decision making to understanding genetic regulation and aiding crop improvement

Crop modelling has evolved over the last 30 or so years in concert with advances in crop physiology, crop ecology and computing technology. Having reached a respectable degree of acceptance, it is appropriate to review briefly the course of developments in crop modelling and to project what might be major contributions of crop modelling in the future. Two major opportunities are envisioned for increased modelling activity in the future. One opportunity is in a continuing central, heuristic role to support scientific investigation, to facilitate decision making by crop managers, and to aid in education. Heuristic activities will also extend to the broader system-level issues of environmental and ecological aspects of crop production. The second opportunity is projected as a prime contributor in understanding and advancing the genetic regulation of plant performance and plant improvement. Physiological dissection and modelling of traits provides an avenue by which crop modelling could contribute to enhancing integration of molecular genetic technologies in crop improvement. Crown Copyright (C) 2002 Published by Elsevier Science B.V. All rights reserved.