Screening strategy modification based on personalized breast cancer risk stratification and its implementation in the national guidelines – pilot study

In order to test S-IBIS and the newly-proposed risk categories we used data from women who visited either the regional Breast Unit (BU) in Kranj or a general practitioner working in the field of breast cancer prevention at the Primary Health Care Centre (PHCC) in Logatec (21, 22). Combining data from both pilot studies, 197 women were included in our analysis, 100 from BU and 97 from PHCC. Both centres represent locations in Slovenia at the primary health level where women may be assessed and referred for breast cancer screening. All the personal and family history data necessary for the calculation of individual risk in the S-IBIS software (version–8) was collected during interviews. Additional information on the anticipated screening procedures (mammography, ultrasound examinations or just further appointments) was obtained from their health records. For each woman a personalized breast cancer risk was calculated with S-IBIS. According to the calculated 10-year or lifetime risk and age group, every woman was assigned to one of the Slovenian breast cancer risk categories: low risk, population risk, moderately increased risk, high risk. The McNemar test was used to determine if there were differences between the anticipated screening according to the current rules on carrying out preventive health careat the primary level and the screening according to the updated Slovenian guidelines (7).

SPSS version 24 (IBM Corp., Armonk, NY, USA) was used for the statistical analyses.

The Tyrer-Cuzick model has been shown in several independent studies to be the most consistently accurate when compared with other models, in other words it performs accurately in the identification of a moderately increased to high risk of developing breast cancer, and currently it is the tool that includes the largest number of established breast cancer risk factors (23). The model has been incorporated into a computer programme, the IBIS software, which gives a personalized breast cancer risk estimate (17). The Tyrer-Cuzick model (now in version-8) combines family history, endogenous hormonal factors, benign breast disease, and other risk factors such as age, body mass index, hormone replacement therapy use, and mammographic density, as well as genetic factors (including BRCA and a polygenic risk score) into a single statistical model. The program assumes that there is genetic but yet unknown gene predisposing to breast cancer, in addition to the BRCA1/2 genes, to account for the remaining familial risk not explained by BRCA1/2. The woman’s family history is used to calculate the likelihood of her carrying a pathogenic genetic variant, which in turn affects her likelihood of developing breast cancer. The phenotype of the woman can be modelled by (17):

where the first column contains information about the pathogenic variant in BRCA genes and may either contain the normal allele, a BRCA1 mutated allele or a BRCA2 mutated allele. The second column contains an adverse gene (the “low penetrance gene”) which was created to act as a surrogate for the effect of all the other “unknown” genes and which causes an increase in the relative hazard of breast cancer. This low penetrance gene is dominant so that a woman with two copies will have the same phenotype as a woman with one copy. To estimate this risk from family history (caused by the adverse genes), the model fits the results of the study done by Anderson et al. (24).

The family history of breast and ovarian cancer of the woman’s blood relatives is used to calculate the distribution of her genotype probabilities, which is used in calculation of the phenotypic probabilities. For a woman the absolute risk (Pr) of developing breast cancer between ages t₁ and t₂ is given by (17):

where pi is the probability of the woman having the relevant phenotype, F_i(t₁,t₂) is the probability of getting breast cancer between ages t₁ and t₂ given the woman’s phenotype i and α is the relative risk due to personal factors. The IBIS software routinely estimates the likelihood of a woman developing breast cancer specifically within 10 years of her current age and over the course of her lifetime. The tool is not intended to assess the risk for women who have already been diagnosed with breast cancer (25).

For the purpose of this study, IBIS software was adjusted using Slovenian specific population breast cancer risks. Breast cancer incidence and mortality rates for the period 2006–2010 were obtained from the population-based Slovenian Cancer Registry (2).

The calculations of threshold values of breast cancer risk categories for Slovenian women followed the procedures used in the development of the English guidelines (NICE – National Institute for Health and Care Excellence) (26, 27, 28). The direct application of the NICE threshold values of breast cancer risk categories would not be appropriate, however, because the Slovenian population risk of breast cancer is about 10% lower compared to the English population risk (29). The appropriate threshold values for Slovenian women were thus determined based on the data on the cumulative 10-year and lifetime breast cancer risks from the Slovenian Cancer Registry.

In the NICE guidelines, which are internationally available and therefore might be used by other countries, the decision to define moderately increased breast cancer risk with a threshold of 3% 10-year risk at age 40 years (or 17% lifetime risk) was taken as that is a level of risk equivalent to the average population risk of a 50-year old woman eligible for breast screening through English national breast screening programmes.

On the other hand, in Slovenia, a level of risk equivalent to the average population risk of 50 to 59 year-old women is lower, at about 2%, so the same 2% for 10-year risk was considered to be a threshold value for moderately increased risk at the age of 40. The upper threshold of moderately increased risk category for those aged 40 and 49 was set as five times the 10-year risk in the same age group. In the Slovenian female population aged 40-49 the 10-year risk was 1.3% in period 2011-2015, so the upper threshold value was set at 6.5% (the number is rounded up). For the age groups 50-59 and 60+ the lower threshold value of the moderately increased risk category was set as two times the 10-year relative risk (1.9% and 2.8%, respectively) yielding thresholds of 4.0% and 5.5% (the numbers are rounded for future use in practice); the upper threshold values remained the same as for the age group 40-49 (20).

For women in their twenties, it is more reasonable to report their lifetime risk. In our project, the calculation was done for a woman aged 25 years: first, using S-IBIS software we created a hypothetical case of a woman aged 40 with a family history of only one first- or second-degree relative diagnosed with breast cancer at older than age 40 who is at a 2% 10-year risk of developing breast cancer. By only changing the age from 40 to 25 the moderately increased risk threshold was obtained. The calculated lifetime risk of this woman was 16%, so the threshold for moderately increased risk in those aged between 20 and 39 was set at 16% or greater (20).

In the study we calculated breast cancer risk scores of 197 women that consecutively attended preventive visits at the Breast Unit or Primary Health Centre and agreed to participate in the study, using S-IBIS software. In Table 2 we present the characteristics of the women studied according to breast cancer risk factors (age, family history, age at menarche, age at first full-term birth).

For the division into breast cancer risk categories the newly calculated breast cancer risk thresholds for Slovenian women were used (Table 3). Table 3 presents the calculated breast cancer risk thresholds that are suggested for the division of women into risk categories according to the individual’s ten-year risk for women age 40 and more, and lifetime risk for women between 20 and 39 (20).

Based on the population of Slovenia and its average lifetime risk to develop breast cancer (i.e. up to age 85), women with a lower risk were assigned to the lower risk category, women with a risk that was 2- to 3-fold that of the population (16% – 29% lifetime risk) were assigned to the moderately increased risk category, and women with a lifetime risk of 30% and above the population risk were assigned to the high breast cancer risk category. Since the risk may vary over a woman’s lifetime, we also set the cutoff values for 10 year-risk groups (40–49, 50–60, and 60+ years) as defined in Table 3 (20).

By using S-IBIS and newly calculated breast cancer risk categories, a total of 197 women were assigned to breast cancer risk groups. Of these, 148/197 (75.1%) were assigned to the population risk category and 49/197 (24.9%) to moderately increased risk category, and none to the high or low risk categories.

The comparison of anticipated mammographic and ultrasound screening (according to the current rules on carrying out preventive health care at the primary level) in women who visited preventive centres, and the foreseen screening according to the new Slovenian guidelines, are presented in Tables 4 and 5, respectively.

Out of the 148 women who fall into the population risk category, 49 (33.1%) were deemed suitable for mammographic screening according to the current rules of primary practice, while 31 (63.3%) women out of 49 were in the moderate risk category. Thus, from all of the 197 women included in the pilot studies, 80 (40.6%) would be eligible for mammographic surveillance until the age of 55. In contrast, with the implementation of the new Slovenian guidelines, only six women from the population risk category and 34 (17.3%) from the moderate risk category would be eligible for mammographic screening. All women above the age of 50 would be offered mammographic screening in the population-based organized screening program that is already available.

When comparing both approaches, 28 women of 80 who were offered mammographic screening according to the current rules, would also be offered mammographic screening according to the new guidelines. On the other hand, 12 women out of 117 that were not offered mammographic screening by current rules would be offered it with the implementation of the new guidelines. An exact McNemar’s test determined that there was a statistically significant difference between current practice and the new Slovenian guidelines for mammographic screening, at p<0.001.

In the population risk category, 21 (14.2%) women out of 148 had ultrasound screening, in the moderately increased risk category it was 12 (24.5%) women out of 49, giving a total of 33 (16.8%) out of 197 women. With the implementation of the new Slovenian guidelines, ultrasound would only be performed on referral from a radiologist.