Breast cancer is a potentially fatal malignancy in females despite the improvement in therapeutic techniques. The identification of novel molecular signatures is needed for earlier detection, monitoring effects of treatment, and predicting prognosis. We have previously used microarray analysis to identify differentially expressed genes in aggressive breast tumors. The purpose of the present study was to investigate the prognostic value of the candidate biomarkers CCNB2, ASPM, CDCA7, KIAA0101, and SLC27A2 in breast cancer.

In epidemiological studies researchers use logistic regression as an analytical tool to study the association of a binary outcome to a set of possible exposures.

Ends. Country-specific projection estimates that address limitations of past projections are necessary. In Australia, a high-income country with the 7th highest incidence of TKA and 15th highest incidence of THA of the Organization for Economic Cooperation and Development (OECD) countries, the volume of TKAs and THAs increased 198% between 1994 and 2014. Questions/purpose To determine the projected incidence and volume of primary TKAs and THAs from 2014 to 2046 in the Australian population older than 40 years. Methods Australian State and Territory Health Department data were used to identify TKAs and THAs performed between 1994 and 1995 and 2013 and 2014. The Australian Bureau of Statistics was the source of the population estimates for the same periods and population-projected estimates until 2046. The incidence rate (IR), 95% CI, and prediction interval (PI) of TKAs and THAs per 100,000 Australian citizens older than 40 years were calculated. Future IRs were estimated using a logistic model, and volume was calculated from projected IR and population. The logistic growth model assumes the existence of an upper limit of the TKA and THA incidences and a growth rate directly related to this incidence. At the beginning, when the observed incidence is much lower than the asymptote, the increase is exponential, but it decreases as it approaches the upper limit. Results A 66% increase in the IR of primary THAs between 2013 and 2046 is projected for Australia (2013: IR = 307 per 100,000, [95% CI, 262-329 per 100,000] compared with 2046: IR= 510 per 100,000, [95% PI, 98-567 per 100,000]), which translates to a 219% increase in the volume during this period. For TKAs the IR is expected to increase by 26% by 2046 (IR = 575 per 100,000; 95% PI, 402-717 per 100,000) compared with 2013 (IR = 437 per 100,000; 95% CI, 397-479 per 100,000) and the volume to increase by 142%. Conclusion A large increase in the volume of arthroplasties is expected using a conservative projection model that accounts for past surgical trends and future population changes in Australia. These findings have international implications, as they show that using country- specific, conservative projection approaches, a substantial increase in the number of these procedures is expected. This increase in joint arthroplasty volume will require appropriate workforce planning, resource allocation, and budget planning so that demand can be met. Level of Evidence Level II, economic and decision analysis....

The continuously increasing demand for joint replacement surgery in the past decades imposes higher constraints on the budgets of hospitals and healthcare providers. We undertook an analysis of historical trends in total hip replacement performed in Sweden between 1968 and 2012 in order to provide projections of future demand. We obtained data on total hip replacements registered every year and on the evolution of the Swedish population between 1968 and 2012. We assumed the existence of a maximum incidence. So we adopted a regression framework that assumes the existence of an upper limit of total hip replacement incidence. We found that the incidence of total hip replacement will continue to increase until a projected upper incidence level of about 400 total hip replacements per 10(5) Swedish residents aged 40 years and older will be reached around the year 2107. In 2020, the estimated incidence of total hip replacement will be 341 (95% prediction interval (PI): 302-375) and in 2030 it will be 358 (PI: 317-396). Using official forecasted population growth data, about 18,000 operations would be expected to be performed in 2020 and 20,000 would be expected to be performed in 2030. Growing incidence, population growth, and increasing life expectancy will probably result in increased demand for hip replacement surgery. Our findings could serve as a basis for decision making.