Revealing Factors Explaining Breast Cancer Survival

The purpose of this research is to reveal factors that impact breast cancer survival in Slovenia, with a focus on evaluating the burden of breast cancer and identifying systemic factors that predict survival. The study aims to assess the incidence of breast cancer in the last 20 years, determine whether healthcare system factors affect survival, and compare different survival estimators.

ABSTRACT
Breast cancer is the most common cancer in women in Slovenia, with increasing incidence
and presence differences in survival. Individual and systemic factors are used to explain its
burden. Latter are from the public health perspective relevant. Populational survival is a
complex indicator, reflecting patients characteristics as well as the health care system
organization, accessibility, quality and effectiveness. Despite efforts of the proffesion, there is
no consensus on different survival methods use.
The purpose of research is to reveal factors explaining breast cancer survival in
Slovenia. Its goal is to assess female breast cancer burden in the last twenty years in Slovenia
and recognize systemic factors as survival predictive; it also aims to compare relative and net
survival estimator. Routinely collected, population-based data from Cancer registry of
Slovenia data will be used. I predict to observe the fastes increase of new cases in the
youngest age-group and to find hospital-related differences in survival among breast cancer
patients.
In my opinion this study represents a unique opportunity to objectively estimate
breast cancer burden in Slovenia. Moreover, it is the first study to explain cancer burden
through healthcare system related factors Slovenia.
Keywords: breast cancer burden, survival, predictive factors, Slovenia.
PURPOSE, OBJECTIVES AND HYPOTHESES
The purpose of the research is to reveal and evaluate factors that have an impact on the
Slovenian breast cancer survival. Therefor, following objectives are set: (1) to assess the
burden of breast cancer in the last 20 years in Slovenia; (2) to determine whether survival, in
addition to the already well-known individual factors (eg. age, stage), is affected by existing
health care system factors.
As there is still no clear consensus on the most appropriate statistical approach when
calculating the population survival, the complementary objective of the research is also to
quantify the difference between different survival estimators. Based on these objectives, the
following hypotheses are set:

H1: The number of breast cancer patients in the last twenty years across Slovenia is steadily
increasing, with fastest increase among those aged 50 years or less.
H2: Slovenian breast cancer survival dependents on the hospital where the disease had been
discovered and cured.
H3: Different estimators for breast cancer survival calculations provide similar results with
little impact on public health interpretation.
STUDY POPULATION AND METHODS
I will conduct a population-based survival analysis based on routinely collected individual-
level data. For this purpose anonymized data of the Cancer Registry of Slovenia (CRS) will
be used. The study population will be females residing in Slovenia, to whom a diagnosis of
breast cancer was placed and reported to CRS between 1 January 1995 and 31 December
2013 (disease coded as C50 after 10 revision of the International Classification of Diseases
and related health problems, for statistical purposes; ICD-10). Status of CRS database on 1
June 2016 will be taken into account.
The burden of breast cancer in the population will be shown as the absolute number of
patients and with crude and age-standardized incidence rate, calculated for the entire period
and for each 5-year period. Results will be shown for the entire population, as well as
separately by age group and area of residence. Time trends will be analyzed using log-linear
regression method in the program Joinpoint 4.0.4 (11). Trends will be expressed as average
annual percentage change (APC), for each APC the 95% confidence interval will be
calculated. Statistical significance of trends will be set at p ≤ 0.05.
I will estimate population survival with two methods: the method of relative survival (Ederer
2) (12) and the method of Pohar-Perme net survival estimator (13). The results will be
stratified by prognostic factors (age, stage, the first hospital treatment, ...). In addition of
survival estimates, a 95% confidence interval will be reported. Statistically significant
differences will be observed at p ≤ 0.05. For analysis Stata (StataCorp LP Version 13) will be
used.