Keywords
multimorbidity; breast cancer; newly diagnosed; risk factors; Sudan
This article is included in the Oncology gateway.
multimorbidity; breast cancer; newly diagnosed; risk factors; Sudan
Breast cancer is the commonest cancer in women and the leading cause of cancer-related death globally.1 It is the commonest cancer in sub-Saharan Africa women.1 Factors such as geography, age,2 family history,3 menstrual history, nulliparous,4 and existing benign breast disease5 are identified as risk factors for breast cancer. Patients, and especially those who are elderly, may have comorbidities when they are diagnosed with cancer.6 Previous studies have shown that 20–35% of women with breast cancer have one or more comorbidities at the time of breast cancer diagnosis.6 The presence of comorbidities at the time of diagnosis of breast cancer poses an additional challenge for the management of the disease.7 Communicable disease, urbanization, and cardiovascular disease are risk factors for breast cancer.8 Bensken et al. recently reported that women with multimorbidity and breast cancer are at increased risk of death.9 Investigating the presence of comorbidities along with breast cancer is very important not only because they are potential risk factors for breast cancer but also because they can affect the stage of the disease at diagnosis, the treatment modality, and the prognosis of the disease.6,9
Breast cancer is the most frequent hospital-treated malignancy in Sudan. Its incidence and mortality in the country have been estimated at 22.5 and 16.6 per 100,000 women (among hospital treated malignancy), respectively.10 Risk factors for breast cancer among Sudanese patients include past history of benign breast disease, pesticide exposure, overweight, physical inactivity, and being unmarried.11 The country’s epidemiological transition, through enhanced control of communicable diseases, increased life expectancy, urbanization, and lifestyle modifications, has led to a rise in the prevalence of risk factors for non-communicable disease.12 Increased life expectancy also results in multimorbidity (coexisting diseases) at the personal level, including in breast cancer patients.6 The aim of this study is to estimate the prevalence and associated factors for multimorbidity (hypertension, obesity, diabetes, cardiovascular disease, asthma, tuberculosis, and HIV) and their association with breast cancer stage in women newly diagnosed with breast cancer in eastern Sudan.
The study followed the “Strengthening the Reporting of Observational studies in Epidemiology (STROBE) Statement standard checklists.13 A retrospective study was conducted at East Oncology Center in eastern Sudan, from) 03/01/2021 to 31/10/2021. The center is located in Gadarif city, which has a population of 1,727,401 residents and is located on the Ethiopian border, 400 km from the capital, Khartoum. Although East Oncology Center is located in Gadarif, its catchment covers the eastern part of Sudan (Gadarif, Kassala, and Port Sudan), from where patients are treated for free. The main services provided in the centre are diagnostic services, endocrine treatment, surgery, chemotherapy, as well as radiation therapy.
Outcome measures
The main outcome measures were to estimate the prevalence and associated factors for the most common comorbidities (hypertension, obesity, diabetes, cardiovascular disease, asthma, obesity, tuberculosis, and HIV) in women newly diagnosed with breast cancer in eastern Sudan and the associated stage of their cancer.
Sample size
The sample size (384) was calculated using the formula of the sample size for proportion; (n) for this study was calculated by using a single proportional formula (n = Z2pq/d2). Where p was the expected prevalence of multimorbidity among women with breast cancer (50%), based on a similar study from Africa6=, q = (1-p), Z1-α = confidence interval of 95% =1.96, d = margin of error of 5%= 0.05. OpenEpi was used to calculate the sample size.14
This study included consecutive files of women newly diagnosed with breast cancer.
Women with a previous cancer diagnosis, who had previously received treatment (radiotherapy, chemotherapy, or any endocrine therapy), or who were unable to give informed consent were excluded.
Data were retrieved from the medical files (papers) and a questionnaire used to collect data from these files of women who had newly diagnosed breast cancer, which had been confirmed by histopathological analysis. Data extracted were about age and comorbidities (hypertension, diabetes, cardiovascular disease, asthma, cerebrovascular accident, thyroid disorders, tuberculosis, and HIV). Body height and weight were recorded to compute body mass index (BMI).
Women were grouped by stage at diagnosis as early (I–II) or advanced (III–IV), as per the guidelines outlined in the American Joint Committee on Cancer’s staging system.15
The data were analyzed using Statistical Package for the Social Sciences (SPSS, RRID:SCR_002865) software for Windows, version 22.0 (IBM, Armonk, NY, USA). Continuous data were checked for normality using the Shapiro–Wilk test; those found to be not normally distributed were expressed as a median (interquartile [IQR]), while the categorized data were expressed as frequency (proportion). Univariate analyses were performed with multimorbidity and newly diagnosed advanced breast cancer (stages III–IV) as the dependent variable and sociodemographic and clinical factors (multimorbidity for advanced breast cancer) as the independent variables. Multicollinearity was initially evaluated (by the presence of high correlation between the variables (r ≥0.9) or if the variance inflation factor was more than 4. Multicollinearity was not detected between the variables. Then variables with p <0.200 were shifted to build multivariable analysis, and the “backward likelihood ratio (LR) was used to evaluate the independent effects of each covariate by controlling the effects of other variables. The adjusted odds ratios (AOR) and 95% confidence intervals (CI) were computed”. A p-value less than 0.05 was considered statistically significant.
In this study, a total of 384 files of women with newly diagnosed breast cancer were included in the analysis. The median (IQR) of their age and parity (number of deliveries) were 50.0 (39.0–60.0) and 5.0 (2.0–7.0), respectively. The majority (88.5%) of women were housewives. Around two-thirds (68.2%) of women had less than secondary school education. Of the women, 239 (62.2%) were from urban areas (Table 1).
65 women (16.9%) had multimorbidity. Obesity (n=77, 20.1%), hypertension (n=66, 17.20%), diabetes mellites (n=50, 13.0%), asthma (n=5, 1.3%), tuberculosis and HIV (n=6, 1.6%), cerebrovascular accident (n=5, 1.3%), and thyroid disease (n=2, 0.5%) were morbidities encountered among these women.
The median (IQR) of age was significantly higher in women with multimorbidity, who also tended to have a lower level of education and resided in urban areas. There was no significant difference in parity, marital status, and menopause between women with multimorbidity compared with those without (Table 1).
Multivariate analysis showed that age was positively associated with multimorbidity (AOR = 1.04, 95% CI = 1.02–1.07). Women with a lower level of education (AOR = 3.23, 95% CI = 1.73–6.04) and who resided in urban areas (AOR = 2.22, 95% CI = 1.14–4.34) were at higher risk for multimorbidity (Table 2).
Variable | OR (95% CI) | P-value | |
---|---|---|---|
Age, years | 1.04 (1.02–1.07) | <0.001 | |
Education | > secondary level | Reference | |
≤ secondary level | 3.23 (1.73–6.04) | <0.001 | |
Residence | Urban | Reference | |
Rural | 2.22 (1.14–4.34) | 0.018 |
There was no significant difference in age, parity, education level, residency, or menopause between women with a new diagnosis of early breast cancer compared with those with a new diagnosis of advanced breast cancer (Table 3).
Multivariate analysis showed that women with multimorbidity were at higher risk of presenting with newly diagnosed advanced breast cancer (AOR = 3.36, 95% CI = 1.85–6.08) (Table 4).
In the current study, we observed that 16.9% of the women with newly diagnosed breast cancer had multimorbidity. Obesity was detected in 20.1% of the women, and 17.20% had hypertension. It was recently reported that 36.6% of adult females in eastern Sudan are obese16 and 40.9% have hypertension.17 The low prevalence of hypertension among the women with newly diagnosed breast cancer in this study could be explained by the method followed in the current study (retrospective and self-reported by the patient). Our results for the prevalence of obesity and hypertension among women newly diagnosed with breast cancer was significantly lower than the reported prevalence of obesity (35%) and hypertension (32%) that had recently been reported among women newly diagnosed with breast cancer in other African countries.6 Our results indicate that multimorbidity in women with newly diagnosed breast cancer was positively associated with age. We previously reported that age was positively associated with hypertension in a community-based study in the same setting (Gadarif).17 This aligns with a recent report that showed that age is positively associated with multimorbidity in women with breast cancer in Africa.6 Moreover, Gurney et al. reported that patients with various cancers (breast, colon, rectal, liver, stomach, ovarian, uterine, bladder, or kidney) and comorbidity are older.18 It is well accepted that multimorbidity is associated with increasing age, due to age-related chronic health conditions, and may be explained by the increased stiffness of the arteries (mainly aorta) as a result of the ageing process.
The current study showed that women with multimorbidity were at 3.36 higher risk of presenting with advanced breast cancer. Interestingly, a large cohort study in several African countries showed multimorbidity not to be associated with stage at diagnosis, although it was associated with earlier stage in obese and hypertensive women alone.6 It is worth mentioning that our results should be compared cautiously with those of the later study because of different sociodemographic characteristics and the prevalence of HIV (higher in the later study).6 Moreover, it has been shown that patients with various cancers and comorbidity are at increased risk of being diagnosed with distant metastases and present late for diagnosis.18 Likewise, Sarfati et al., showed that patients with comorbidity with colon cancer have an increased risk of being diagnosed with distant metastases than patients with no comorbidity burden.19 It should be noted that comorbidity may distract both the patient as well the physician from early signs and symptoms of cancer and hence lead to delay in the cancer diagnosis. On the other hand, the presence of comorbidity can increase patients’ contact with health services, which may lead to earlier diagnosis of the cancer.
Our study was retrospective one and it was designed to assess multimorbidity and not each comorbidity independent from each other. Moreover, the low prevalence of some individual disease comorbidities, such as HIV, could have influenced the ability to detect significant differences for such disease.
In eastern Sudan, older women, women with less education, and those who reside in urban areas are at higher risk for multimorbidity associated with advanced newly diagnosed breast cancer.
Ethical approval was received from the Ethics Committee at the Faculty of Medicine, Gadarif University, Sudan (reference number: 2021/08). Files were analyzed unanimously.
Figshare: Multimorbidity in Sudanese women newly diagnosed with breast cancer: a retrospective cross-sectional study. https://doi.org/10.17605/OSF.IO/ZUY2K.
The project contains the following underlying data:
Figshare: STROBE checklist for ‘Multimorbidity in Sudanese women newly diagnosed with breast cancer: a retrospective cross-sectional study’. https://doi.org/10.17605/OSF.IO/ZUY2K
Data are available under the terms of the Creative Commons Zero “No rights reserved” data waiver (CC0 1.0 Public domain dedication).
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Is the work clearly and accurately presented and does it cite the current literature?
Partly
Is the study design appropriate and is the work technically sound?
Yes
Are sufficient details of methods and analysis provided to allow replication by others?
No
If applicable, is the statistical analysis and its interpretation appropriate?
I cannot comment. A qualified statistician is required.
Are all the source data underlying the results available to ensure full reproducibility?
No
Are the conclusions drawn adequately supported by the results?
Yes
Competing Interests: No competing interests were disclosed.
Reviewer Expertise: Breast Cancer
Alongside their report, reviewers assign a status to the article:
Invited Reviewers | |
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Version 1 23 Jan 23 |
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