The Vaccine Adverse Event Reporting System (VAERS) received thousands of reports of adverse events that occurred after vaccine administrations from the post-marketing vaccine safety surveillance. However, the causality between vaccines and reported adverse events cannot be taken for granted. In this report several data mining methods were applied to VAERS database that is coded in MedDRA terms to discover possible associations between vaccines and adverse events. Efforts were devoted to identify events that are reported more frequently after administering one vaccine than other vaccines using the following data mining techniques: relative ratio (RR), statistical significance (LogP), proportional reporting ratio (PRR), and screened PRR (SPRR). The vaccine-event combinations that ranked top in each method varied substantially among the methods. RR and PRR gave excessive weight to small counts of vaccine-event pairs, but SPRR was able to correct this weakness. There are only 33 vaccine-event pairs that were shared among the top 1,000 ranked in each method. Evaluating the properties of these data mining methods and exploring other methods will help improve vaccine safety surveillance. / text

Increased possibilities during the last decades for early detection of prostate cancer have sparked research on preventable or treatable risk factors and on improvements in therapy. Treatments of the disease still entail significant side effects potentially affecting men during the rest of their lives. The studies of the present thesis concern different aspects of prostate cancer from etiological risk factors and factors influencing treatment to an improved methodology for the detection of treatment side effects. Papers I, II, both based in the population based cohort ULSAM (Uppsala Longitudinal Study of Adult Men), investigate possible risk factors of prostate cancer with options for intervention: selenium levels and the metabolic syndrome. The phenomenon of competing risk of death from other causes than prostate cancer and its impact on and importance for choice of statistical methods is also exemplified and discussed for the first time in prostate cancer research. -Smokers with low selenium status have an increased future risk of later development of prostate cancer. Influence of genetic variability appears plausible. -The metabolic syndrome and especially its increased waist circumference component are associated with later development of prostate cancer – taking competing risks of death from other causes into account. Papers III and IV using pharmacoepidemiological methods investigate aspects of drug utilisation in prostate cancer using nationwide and international databases. In Paper III factors influencing anti-androgen use in prostate cancer are investigated, both from a prescriber- and patient perspective.  The age and disease risk group of the patient, unsupported scientifically, influence both the prescribers’ choice of dose and the patients’ adherence to treatment. -Adherence, not previously investigated in male cancer patients, was considerably higher than reported for adjuvant breast cancer treatment. Subgroups of men suitable for intervention to increase adherence were identified. Paper IV, investigates the feasibility of improving an established method for screening large adverse drug reactions databases, the proportional reporting ratio (PRR), this by using restricted sub-databases according to treatment area (TA), introducing the concept of PRR-TA. -The PRR-TA method increases the signal-noise relationship of analyses; a finding highly relevant for possibly conserving manual resources in Pharmacovigilance work in a drug-authority setting.