Flexible transition probability model for assessing cost-effectiveness of breast cancer screening extension to include women aged 45-49 and 70-74.

Breast cancer is the most common cancer among Western women. Fortunately, organized screening has reduced breast cancer mortality. New recommendation by the European Union suggests extending screening with mammography from 50-69-year-old women to 45-74-year-old women. However, before extending screening to new age groups, it's essential to carefully consider the benefits and costs locally as circumstances vary between different regions and/or countries. We propose a new approach to assess cost-effectiveness of breast cancer screening for a long-ongoing program with incomplete historical screening data. The new model is called flexible stage distribution model. It is based on estimating the breast cancer incidence and stage distributions of breast cancer cases under different screening strategies. The model parameters, for each considered age group, include incidence rates under screening/non-screening, probability distribution among different stages, survival by stages, and treatment costs. Out of these parameters, we use the available data to estimate survival rates and treatment costs, while the modelling is done for incidence rates and stage distributions under screening policies for which the data is not available. In the model, an ongoing screening strategy may be used as a baseline and other screening strategies may be incorporated by changes in the incidence rates. The model is flexible, as it enables to apply different approaches for estimating the altered stage distributions. We apply the proposed flexible stage distribution model for assessing incremental cost of extending the current biennial breast cancer screening to younger and older target ages in Finland.

Atorvastatin induces adrenal androgen downshift in men with prostate cancer: A post Hoc analysis of a pilot adaptive Randomised clinical trial.

BACKGROUND: Prostate cancer (PCa) progression depends on androgen receptor activity. Cholesterol is required for biosynthesis of all steroid hormones, including androgens. Impact of cholesterol-lowering statins on androgens is unknown. We explored atorvastatin influence on serum and prostatic tissue steroidomic profiles (SP) to expose novel pathways for limiting androgen concentration in men with PCa. METHODS: This is a pre-planned post hoc analysis of ESTO-1 pilot randomised, double-blinded, clinical trial. Statin naïve men, scheduled for radical prostatectomy due to localised PCa, were randomised 1:1 to use daily 80 mg of atorvastatin or placebo before the surgery for a median of 28 days. Participants were recruited and treated at the Pirkanmaa Hospital District, Tampere, Finland. 108 of the 158 recruited men were included in the analysis based on sample availability for hormone profiling. Serum and prostatic tissue steroid profiles were determined using liquid chromatography mass spectrometry. Wilcoxon rank sum test and bootstrap confidence intervals (CI) were used to analyse the difference between placebo and atorvastatin arms. FINDINGS: Most serum and prostatic steroids, including testosterone and dihydrotestosterone, were not associated with atorvastatin use. However, atorvastatin use induced serum SP changes in 11-ketoandrostenedione (placebo 960pM, atorvastatin 617.5pM, p-value <0.0001, median difference -342.5; 95% CI -505.23 - -188.98). In the prostatic tissue, atorvastatin was associated with plausible downshift in 11- ketodihydrotestosterone (placebo 25.0pM in 100 mg tissue/1 mL saline, atorvastatin 18.5pM in 100 mg tissue/1 mL saline, p-value 0.027, median difference -6.53; 95% CI -12.8 - -0.29); however, this association diminished after adjusting for multiple testing. No serious harms were reported. INTERPRETATION: Atorvastatin was associated with adrenal androgen downshift in the serum and possibly in the prostate. The finding warrants further investigation whether atorvastatin could improve androgen deprivation therapy efficacy. FUNDING: Funded by grants from the Finnish Cultural Foundation, Finnish Cancer Society, Academy of Finland, and the Expert Responsibility Area of the Tampere University Hospital. CLINICALTRIALS. GOV IDENTIFIER: NCT01821404.

Circulatory and prostatic tissue lipidomic profiles shifts after high-dose atorvastatin use in men with prostate cancer.

Prostate cancer patients using cholesterol-lowering statins have 30% lower risk of prostate cancer death compared to non-users. The effect is attributed to the inhibition of the mevalonate pathway in prostate cancer cells. Moreover, statin use causes lipoprotein metabolism changes in the serum. Statin effect on serum or intraprostatic lipidome profiles in prostate cancer patients has not been explored. We studied changes in the serum metabolomic and prostatic tissue lipidome after high-dose 80 mg atorvastatin intervention to expose biological mechanisms causing the observed survival benefit. Our randomized, double-blind, placebo-controlled clinical trial consisted of 103 Finnish men with prostate cancer. We observed clear difference in post-intervention serum lipoprotein lipid profiles between the study arms (median classification error 11.7%). The atorvastatin effect on intraprostatic lipid profile was not as clear (median classification error 44.7%), although slightly differing lipid profiles by treatment arm was observed, which became more pronounced in men who used atorvastatin above the median of 27 days (statin group median classification error 27.2%). Atorvastatin lowers lipids important for adaptation for hypoxic microenvironment in the prostate suggesting that prostate cancer cell survival benefit associated with statin use might be mediated by both, local and systemic, lipidomic/metabolomic profile changes.

On Exploring Hidden Structures Behind Cervical Cancer Incidence.

Finding new etiological components is of great interest in disease epidemiology. We consider time series version of invariant coordinate selection (tICS) as an exploratory tool in the search of hidden structures in the analysis of population-based registry data. Increasing cancer burden inspired us to consider a case study of age-stratified cervical cancer incidence in Finland between the years 1953 and 2014. The latent components, which we uncover using tICS, show that the etiology of cervical cancer is age dependent. This is in line with recent findings related to the epidemiology of cervical cancer. Furthermore, we are able to explain most of the variation of cervical cancer incidence in different age groups by using only two latent tICS components. The second tICS component, in particular, is interesting since it separates the age groups into three distinct clusters. The factor that separates the three clusters is the median age of menopause occurrence.