ANALYSIS
OF THE RELATIONSHIP OF FACTORS TRIGGERING BREAST DISORDERS WITH THE RESULTS OF
ULTRASOUND IMAGE EXPECTATION IN THE IMPLEMENTATION OF THE MAMMAE ORGAN
SCANNING PROTOCOL
Puspa
Pamella Suci1, Diyah
Fatmasari2, Gatot Murti Wibowo3
Poltekkes Kemenkes Semarang, Jawa Tengah, Indonesia
|
KEYWORDS |
ABSTRACT |
|
ultrasound, mammae, screening, awareness, trigger factors. |
This study aims to determine
the relationship between trigger factors for breast abnormalities with the
results of ultrasound image observation. This study is an analytical
observational study with a retrospective approach. The research design used
was a control case design. Data collection will be carried out from April to
June 2023 at the MCU Clinic in the Jabodetabek area. The study data were
analyzed using bivariate and multivariate analysis. The results of the
bivariate analysis showed p values = 0.000 < 0.005 for each of the
internal and external trigger factor variables. The conclusion in this study
is that there is a significant relationship between the history of BSE,
history of childbirth, history of breastfeeding, history of hormonal birth
control use, genetic history, history of alcohol consumption, history of
smoking, history of menarche, history of menopause, history of consumption of
junk food, and history of consumption of soft drinks (p-value = 0.000) with
observation of ultrasound images on the breast organ scanning protocol. Higher
Diagnostic Accuracy through consideration of the triggering factors of breast
disorders in ultrasound image results. Guide to the Development of Scanning
Protocols that are More Effective in detecting breast disorders. Identify
Risk Factors that allow special attention in the management of breast health.
Increased Public Awareness of the importance of routine breast exams.
Direction for Advanced Research to understand more deeply the relationship
between trigger factors and ultrasound image outcomes. Potential Improvement
of Clinical Practice and Guidelines by considering research findings. |
|
DOI: 10.58860/ijsh.v2i9.96 |
|
Corresponding Author: Puspa Pamella Suci
E-mail: najihaalawiyah@gmail.com
INTRODUCTION
Breast cancer ranks first
in Indonesia with the highest cancer incidence. It is the leading cause of
death caused by cancer (Wulandari,
Bahar, & Ismail, 2017). Breast cancer accounts for 68,858
cases (16.6%) of 396,914 new cancer cases, while the death rate reached more
than 22,000 in 2020. As many as 43% of deaths due to cancer can be prevented if
people living with cancer routinely carry out early detection and avoid factors
of cancer risk (Riawati,
2019). Cancer (malignant tumor, neoplasm)
is a general term for a group of masses that can attack any body part
(Dinuriah, 2015). One of the characteristics of
cancer is the formation of abnormal cells that quickly grow beyond normal
limits, then can attack adjacent parts of the body and spread to other organs (
metastases ) (Awaliyah,
2021). The leading cause of death from
cancer is extensive metastasis (Mukherjee,
2020). Apart from breast cancer, several
other disorders are often encountered in daily practice, for example,
fibroadenoma mammae, tumors, galactocelles, intraductal papillomas, mastitis,
fibrocystic (Saktiawan
& Atmiasri, 2017). Unhealthy lifestyle, consumption of
foods that contain lots of fat, not breastfeeding, malnutrition, not having
children, giving birth to the first child over 35 years, radiation, alcohol
consumption, obesity, and long-term hormones are factors that trigger cancer in
women (Mulyani
& Rinawati, 2013).
Studies show that the
prevalence of breast self-examination is low. Family history of breast cancer,
knowledge about Breast Self-Examination (BSE), and self-awareness in performing
BSE have a statistically significant relationship with BSE practice (Dagne,
Ayele, & Assefa, 2019). According to the 2016
Non-Communicable Diseases (NCD) Research, it was found that 53.7% of people had
never done BSE, 46.3% of people had done BSE; and 95.6% of people did not do
SADANIS, while 4.4% had done SADANIS (Yusnilawati,
Mawarti, & Rudini, 2019).
There are several ways to
examine the mammary glands, including mammography examination, tomosynthesis
mammogram (DBT), magnetic resonance image (MRI), and ultrasonography (USG).
However, each examination has its advantages and disadvantages. Mammography has
limitations compared to other examinations, such as the possibility of
discomfort, and tends to be painful (Dibble,
Singer, Baird, & Lourenco, 2021). This is because mammography
examinations require compression of the patient's breasts, and storing
radiographic films is also troublesome. Suppose the film is damaged or the
image results are inadequate. In that case, the process must be repeated and
has a long duration for interpretation, so mammography is rarely used (Wulandari
et al., 2017). The use of MRI for breast screening
is relatively expensive; apart from that, in Jabodetabek, there are still very
few hospitals that have MRI equipment, which makes breast screening to detect
BSE. In contrast, 46.3% of people have had BSE, and 95.6% of people did not do
SADANIS, while 4.4% had done SADANIS.
There are several ways to
examine the mammary glands, including mammography, mammogram tomosynthesis
(DBT), magnetic resonance image (MRI), and ultrasonography (USG). However, each
examination has its advantages and disadvantages. Mammography has limitations
compared to other examinations, such as the possibility of discomfort, and
tends to be painful (Dibble
et al., 2021). This is because mammography
examination requires breast compression on the patient; storing radiographic
films is also a hassle. Suppose the film is damaged or the image results are
inadequate. In that case, the process must be repeated and has a long duration
for interpretation, so mammography is rarely used (Wulandari
et al., 2017).
Using MRI for breast
screening is relatively expensive; besides that, in Jabodetabek, very few
hospitals still have MRI equipment, making breast screening to detect
abnormalities using MRI impractical and rarely of interest (Comstock
et al., 2020). Ultrasound using a high-frequency
transducer and Doppler examination can not differentiate cystic or solid tumors
very well. However, it can also determine the blood supply and condition of the
surrounding tissue to be the basis for an excellent diagnosis (Siregar et al.
N, Santoso T, 2022).
Mammary ultrasound
abnormalities in women of reproductive age, coupled with the culture of young
women who are lazy about carrying out routine mammary screening due to the
absence of symptoms and the low level of knowledge regarding BSE techniques,
makes it necessary to analyze the relationship between findings of mammary
abnormalities in women of childbearing age and factors. Factors that cause
breast cancer using ultrasound imaging are increasingly needed (Evans
et al., 2018). A sonographer carries out the
ultrasound examination at the Medical Check-Up clinic. RI Minister of Manpower
Decree No. 237 of 2020 explains that a sonographer can perform an ultrasound by
the applicable code of ethics.
Diagnostic biomarkers
that identify disease subtypes often play an important role when diagnostic
classification results can be used as prognostic biomarkers and predictive
biomarkers (Atallah,
Abd. Aziz, Teik, Shafiee, & Kampan, 2021). Treatment of breast cancer has a
high possibility of being cured by doing regular treatment, resulting in a good
quality of life and can carry out activities. The fulfillment of his needs
returns without dependence on others. So that it can be independent
emotionally, socially, and physically well-being. In general, the quality of
life of breast cancer patients depends on the support relationship between
family and patient (Kesler
et al., 2013).
Based on the background
stated above, this study aimed to identify and analyze the relationship between
triggering factors for breast abnormalities and the results of ultrasound image
expertise in applying the mammary organ scanning protocol. By understanding the
relationship between trigger factors and ultrasound image results, this study
can provide benefits in improving accuracy in diagnosing breast disorders.
Patients can get a more precise and quick diagnosis.
Higher Diagnostic
Accuracy through consideration of the triggering factors of breast disorders in
ultrasound image results. Guide to the Development of Scanning Protocols that
are More Effective in detecting breast disorders. Identify Risk Factors that
allow special attention in the management of breast health. Increased Public
Awareness of the importance of routine breast exams. Direction for Advanced
Research to understand more deeply the relationship between trigger factors and
ultrasound image outcomes. Potential Improvement of Clinical Practice and
Guidelines by considering research findings.
METHOD
This type of research is
analytical observational research with a retrospective approach. The research
design used in this study was a
case-control design, which is a study in which the research begins by
determining the case group (with disease) and the control group (without
disease) and then looking at the risk factors in the past. Data collection will
be carried out from April to June 2023 at the MCU Clinic in the Jabodetabek
area. The study data were analyzed using bivariate and multivariate analysis.
RESULTS AND DISCUSSION
Data was collected at the
Tirta Medical Center Bellagio Clinic, Cakra Medika Clinic, and PT Multitama
Mitra Sejahtera, with 160 patients as samples. The number of samples, namely
average mammary ultrasound results,
was 80, and abnormal mammary ultrasound
results were 80. The patient underwent a mammary ultrasound by a
sonographer, and one radiologist read
the examination results; then, three different radiologists carried out the
results of the examination by the
kappa test.
Table 1. Radiologist Kappa Test Results
|
radiology g |
Frequency is Normal (n) |
Frequency is Abnormal (n) |
⅀ |
Presenta si Valid (%) |
|
RAD 1 |
80 |
80 |
160 |
100% |
|
RAD 2 |
80 |
80 |
160 |
100% |
|
RAD 3 |
80 |
80 |
16 0 |
100 % |
From the
sample results of 160 samples, with 80 regular and 80 abnormalities, the three
radiologists assessed them as 100% valid with expert results and imaging
results.
In line with previous
research, 135 masses were assessed as BI-RADS categories 4 and 5 on ABUS. They
underwent ultrasound-guided core needle biopsy (Sabour,
2019). Agreement of BI-RADS categories was
evaluated with the kappa statistical test, and the positive predictive value of
each examination was calculated. They reported that the overall agreement
between ABUS and HHUS in all cases was good. In both situations, the prevalence
of concordant cells is the same. Cells opposite 90° have 10%; However, the different
kappa values obtained in each situation were interpreted as very good.
Table 2.
Frequency Distribution I
|
Triggers |
F |
F |
|
|||
|
|
|
N |
% |
AN |
% |
|
|
Internals |
1.1 R. Childbirth |
75 |
93.8 |
46 |
57.5 |
121 (75.6%) |
|
|
1.2 R. Non-giving birth |
5 |
6.3 |
34 |
42.5 |
39 (24.4%) |
|
|
1.3 R. Breastfeeding |
74 |
92.5 |
11 |
13.8 |
85 (53.1%) |
|
|
1.4 R. Non-breastfeeding |
6 |
7.5 |
69 |
86.3 |
75 (46.9%) |
|
|
1.5 R. Genetics |
6 |
7.9 |
70 |
92.1 |
76 (47.5%) |
|
|
1.6 R. Non Genetic |
74 |
88.1 |
10 |
11.9 |
84 (52.5%) |
|
|
1.7 R. Late Menarche |
3 |
3.8 |
45 |
38.3 |
48 (30%) |
|
|
1.8 R. Non Slow Menarche |
77 |
96.3 |
35 |
43.8 |
112 (70%) |
|
|
1.9. Slow Menopause |
5 |
6.8 |
69 |
69 |
74 (46.3) |
|
|
1.10 Delayed Menopause |
75 |
87.2 |
11 |
11 |
86 (53.8) |
|
External |
2.1 R. REALIZE |
72 |
90 |
27 |
33.8 |
99 (61.9%) |
|
|
2.2 R Non-BSE |
8 |
10 |
53 |
66.3 |
61 (38.1%) |
|
|
2.3 R. Hormonal birth control |
9 |
11.3 |
61 |
78.3 |
70 (43.8%) |
|
|
2.4 R. Non-hormonal birth control |
71 |
88.8 |
19 |
23.8 |
90 (56.3%) |
|
|
2.5 R. Alcohol consumption |
7 |
8.8 |
42 |
52.5 |
49 (30.6%) |
|
|
2.6 R. Non-consumption of alcohol |
73 |
91.3 |
38 |
47.5 |
111 (69.4%) |
|
|
2.7 R Smoke |
3 |
3.8 |
50 |
62.5 |
53 (33.1%) |
|
|
2.8 R Non-Smoking |
77 |
96.3 |
30 |
37.5 |
107 (66.9%) |
|
|
2.9 R Consumption of junk food |
36 |
45 |
80 |
100 |
116 (72.5%) |
|
|
2.10 R non Consumption of junk food |
44 |
55 |
0 |
0 |
44 (27.5%) |
|
|
2.11 R. Consumption of soft drink |
31 |
38.8 |
80 |
100 |
111 (69.%) |
|
|
2.12 R Consumption of soft drinks |
9 |
61.3 |
0 |
0 |
49 (30.6%) |
Table 3.
Bivariate Analysis
|
Variable |
OR |
CI 9% |
P value |
Strength Connection |
|
Internals |
||||
|
1. Status: Give
birth to |
11,087 |
4,046 – 30,397 |
0.000 |
There is Connection |
|
2.
Status Breastfeed |
77,364 |
27,143 – 220,505 |
0.000 |
There is Connection |
|
3.
Status Genetic |
86,333 |
29,804 – 250,081 |
0.000 |
There is Connection |
|
4. Status Menarche |
33,000 |
9,596 – 113,479 |
0.000 |
There is Connection |
|
5. Status Menopause |
94,091 |
31,116 – 284,516 |
0.000 |
There is Connection |
|
External |
||||
|
1. BE AWARE |
17.67 |
7,438
– 41,960 |
0.000 |
There is Connection |
|
2. Use KB Hormonal |
25,327 |
10,677 – 60,079 |
0.000 |
There is Connection |
|
3. History Consumption Alcohol |
11,526 |
4,728 – 28,097 |
0.000 |
There is Connection |
|
4. History Smoke |
42,778 |
12,391 – 147,684 |
0.000 |
There is Connection |
|
5. History Consumption junk food |
3,222 |
2,457 – 4,226 |
0.000 |
There is Connection |
|
6. History Consumption soft drinks |
3,581 |
2,656 – 4,828 |
0.000 |
There is Connection |
After the analysis,
bivariate chi-square results for all
variables. Trigger factors with mammary ultrasound
image observation results show a value of p = 0.000 < 0.05, so it can be
concluded that there is a relationship between all variables and mammary ultrasound image observation results.
For internal factors, the
first highest proportion was menopausal
status, where the 95% CI value increased (OR = 94.091; p = 0.000).
Meanwhile, the external factor that experienced an increase in CI was smoking
history (OR=42.778; p = 0.000).
To find
out the variables that have the most dominant influence on mammary ultrasound
image observation results, further statistical tests were carried out using
multiple logistic regression tests. All independent variables are candidates
for logistic regression testing.
Table 4.
Logistic Regression of Trigger Factors
|
Factor Trigger |
B |
SE |
Wald |
Df |
Sig. |
Exp(B) |
|
|
Inter bad |
R. giving birth right |
-.897 |
.915 |
,961 |
1 |
.327 |
.408 |
|
|
R. Breastfeeding ui |
- 18,445 |
40192.9 91 |
,000 |
1 |
1,000 |
,000 |
|
|
R. Menarch e |
2,606 |
.781 |
11.135 |
1 |
,001 |
13,546 |
|
|
R. Genetic |
2,593 |
2,112 |
1,507 |
1 |
.220 |
13,375 |
|
|
R. Menopause |
4,079 |
.594 |
47,158 |
1 |
,000 |
59.102 |
|
Extrn al |
R. Consumption Alcohol |
1907 |
,689 |
7,662 |
1 |
,006 |
6,731 |
|
|
R. Smoke |
3,049 |
,791 |
14,840 |
1 |
,000 |
21,094 |
|
|
R. consumption of soft drinks |
22,368 |
4711.948 |
,000 |
1 |
,996 |
5179588289.152 |
|
|
R. Consume I junk food |
17,660 |
4779.774 |
,000 |
1 |
.997 |
46753331.756 |
|
|
R. KB Hormone al |
2,711 |
,616 |
19,347 |
1 |
,000 |
15,045 |
|
|
R. AWARE I |
2,423 |
.647 |
14,045 |
1 |
,000 |
11,285 |
The results
of the logistic/multivariate regression analysis on internal factors show that
of the five candidate variables analyzed together, there is one variable that
is proven to have a significant influence on breast cancer, namely menopausal
history, which is the most dominant variable influencing breast cancer with p( sig, ) = 0.000 and the Exp(B)/OR value =
59.102, meaning that a history of menopause
is 59,102 times greater risk of developing breast cancer than a history of
giving birth, a history of breastfeeding, a history of menarche and genetic history.
The results of the
logistic/multivariate regression test show that the variable that influences
diagnosis simultaneously with external factors is a history of smoking with
p(sig,) = 0.000 and a value of (Exp B/OR= 21.904), meaning that a history of
smoking has a 21,904 times greater risk of developing cancer. Breast compared
to other external factors. This research aligns with research (Rukmi, 2018),
with the statistical analysis results showing a significant relationship
between menopausal age ≥55
years and the incidence of breast cancer with a value of p=0.003. The risk is
1.010 (95% CI: 0.00-0.22) times greater than that of women who experience menopause at age ≥55.
The statistical analysis
results in research (Ningrum
& Rahayu, 2021) show a relationship between smoking
and the incidence of breast cancer. Breast Cancer at RSUD Dr. Achmad Mochtar
Bukittinggi with a p-value of 0.003 for breast cancer to occur compared to
respondents in the category of non-smokers.
CONCLUSION
Mammary ultrasound sonograms can be differentiated between expected results and
abnormalities identified using the results of the images carried out by a
competent sonographer and the results of
the expertise carried out by a radiologist. Most respondents have a high
level of knowledge about BSE, and most respondents have good behavior about
BSE. There is a significant relationship between BSE behavior and the incidence
of breast abnormalities in this study. It can be seen from the results of
mammary ultrasound, which shows that more
respondents had average results. There is a relationship between birth
history, breastfeeding history, history of hormonal birth control use, genetic
history, history of alcohol consumption, smoking history, age at menarche, age at menopause, history of junk
food consumption, and history of soft
drink consumption with ultrasound image observation in the implementation
of the mammary organ scanning protocol. The more dominant
variable is the history of menopause.
REFERENCES
Atallah,
Ghofraan Abdulsalam, Abd. Aziz, Nor Haslinda, Teik, Chew Kah, Shafiee, Mohamad
Nasir, & Kampan, Nirmala Chandralega. (2021). New predictive biomarkers for
ovarian cancer. Diagnostics, 11(3), 465.
Awaliyah, Andi Ulfa Hijrah.
(2021). Korelasi Faktor Risiko Dengan Stadium Penderita Kanker Serviks Di
RSUP Dr. Wahidin Sudirohusodo Tahun 2019. Universitas Hasanuddin.
Comstock, Christopher E.,
Gatsonis, Constantine, Newstead, Gillian M., Snyder, Bradley S., Gareen, Ilana F.,
Bergin, Jennifer T., Rahbar, Habib, Sung, Janice S., Jacobs, Christina, &
Harvey, Jennifer A. (2020). Comparison of abbreviated breast MRI vs digital
breast tomosynthesis for breast cancer detection among women with dense breasts
undergoing screening. Jama, 323(8), 746–756.
Dagne, Asrat Hailu, Ayele,
Alemu Degu, & Assefa, Ephrem Mengesha. (2019). Assessment of breast
self-examination practice and associated factors among female workers in Debre
Tabor Town public health facilities, North West Ethiopia, 2018: Cross-sectional
study. PloS One, 14(8), e0221356.
Dibble, Elizabeth H.,
Singer, Tisha M., Baird, Grayson L., & Lourenco, Ana P. (2021). BI-RADS 3
on dense breast screening ultrasound after digital mammography versus digital
breast tomosynthesis. Clinical Imaging, 80, 315–321.
Dinuriah, Syahdah. (2015). Gambaran
gangguan mental emosional pada Penderita kanker dalam masa kemoterapi di RSU
Kabupaten Tangerang. FKIK UIN Jakarta.
Evans, Andrew, Trimboli,
Rubina M., Athanasiou, Alexandra, Balleyguier, Corinne, Baltzer, Pascal A.,
Bick, Ulrich, Camps Herrero, Julia, Clauser, Paola, Colin, Catherine, &
Cornford, Eleanor. (2018). Breast ultrasound: recommendations for information
to women and referring physicians by the European Society of Breast Imaging. Insights
into Imaging, 9, 449–461.
Kesler, Shelli, Hosseini, S.
M. Hadi, Heckler, Charles, Janelsins, Michelle, Palesh, Oxana, Mustian, Karen,
& Morrow, Gary. (2013). Cognitive training for improving executive function
in chemotherapy-treated breast cancer survivors. Clinical Breast Cancer,
13(4), 299–306.
Mukherjee, Siddhartha.
(2020). Kanker: Biografi Suatu Penyakit. Kepustakaan Populer Gramedia.
Mulyani, Nina Siti, &
Rinawati, Mega. (2013). Kanker Payudara dan PMS pada Kehamilan. Yogyakarta:
Nuha Medika.
Ningrum, Megawati Puspa,
& Rahayu, R. R. Sri Ratna. (2021). Determinan Kejadian Kanker Payudara pada
Wanita Usia Subur (15-49 Tahun). Indonesian Journal of Public Health and
Nutrition, 1(3), 362–370.
Riawati, Danik. (2019).
Hubungan antara usia dengan deteksi dini kanker serviks metode Iva. Avicenna:
Journal Of Health Research, 2(2), 104–110.
Sabour, Siamak. (2019).
Automated versus handheld breast ultrasound examinations of suspicious breast
masses: methodological errors in the reliability analysis. Ultrasonography,
39(1), 102–103.
Saktiawan, Renny Agus, &
Atmiasri, Atmiasri. (2017). Pemanfaatan Tanaman Toga Bagi Kesehatan Keluarga
Dan Masyarakat. Jurnal Abadimas Adi Buana, 1(2), 57–64.
Siregar HK, Nugroho N,
Santoso T, All. (2022). E. Keperawatan Onkologi.
Wulandari, Novia, Bahar,
Hartati, & Ismail, Cece Suriani. (2017). Gambaran kualitas hidup pada
penderita kanker payudara di Rumah Sakit Umum Bahteramas Provinsi Sulawesi
Tenggara tahun 2017. Haluoleo University.
Yusnilawati, Ns, Mawarti, Ns
Indah, & Rudini, Dini. (2019). Pendidikan Kesehatan Tentang Deteksi Dini
Kanker Payudara Melalui Pemeriksaan Sadari (Periksa Payudara Sendiri) Di Pondok
Pesantren Al-Hidayah dan Al-Maarif Kota Jambi. Jurnal Karya Abdi Masyarakat,
3(2), 129–132.
|
|
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2023 by the authors. It was submitted for possible open-access publication under
the terms and conditions of the Creative Commons Attribution (CC BY SA ) license ( https://creativecommons.org/licenses/by-sa/4.0/
). |
