Time to adjuvant chemotherapy and its predictors among postoperative breast cancer patients at Cancer Treatment Center of Hawassa University Comprehensive Specialized Hospital, Hawassa, Ethiopia 2022: a retrospective follow-up study

¹School of Medicine, College of Medicine and Health Sciences, Hawassa University, Hawassa, Ethiopia, ²School of Public Health, College of Medicine and Health Sciences, Hawassa University, Hawassa, Ethiopia, ³School of Medicine Oncology Department, College of Medicine and Health Sciences, Hawassa University, Hawassa, Ethiopia

^&Corresponding author
Adugna Getahun Deboch, School of Medicine, College of Medicine and Health Sciences, Hawassa University, Hawassa, Ethiopia

Introduction    

Cancer remains a major global health challenge, affecting various organs and systems in the body. According to the World Health Organization (WHO), cancer was the second leading cause of death worldwide in 2018, accounting for approximately 9.6 million deaths, or one in six fatalities. Among these, breast cancer is one of the most prevalent, with serious malignancies affecting women across all age groups, with incidence rates rising with age [1]. Cancer is responsible for roughly 5.8% of all fatalities in Ethiopia. Globally, breast cancer stands as the most prevalent form of cancer, comprising 30.2% of all cancer instances [2].

The majority of breast cancer cases (85%) originate in the epithelial cells lining the ducts, while a smaller percentage (15%) develop in the lobules of the breast's glandular tissue. In its early stages, the malignant growth remains confined within the duct or lobule, referred to as "in situ". At this point, it typically produces no noticeable symptoms and has a limited capacity for metastasis. As time progresses, these stage 0 cancers may advance, infiltrating the surrounding breast tissue (becoming invasive breast cancer) and potentially spreading to nearby lymph nodes (regional metastasis) or other organs in the body (distant metastasis) [1].

Increased exposure to estrogen is associated with an increased risk of breast cancer, whereas reduced exposure to estrogen is thought to be protective [3]. Correspondingly, factors that increase the number of menstrual cycles, such as early menarche, null parity, and late menopause, are associated with an increased risk. Moderate exercise levels and longer lactation periods were protective factors that decreased the total number of menstrual cycles [3]. Obesity is associated with an increased risk of breast cancer. Non-hormonal risk factors include increasing age, family history of breast cancer, radiation exposure, and alcohol consumption, with high-fat content contributing to an increased risk of breast cancer [3].

A systematic review and meta-analysis of 49 studies assessing breast cancer survival patterns in sub-Saharan Africa reported a 1-year survival rate of 79%, a 3-year survival rate of 56%, and a 5-year survival rate of 40% [4]. The review highlighted disparities in survival based on socioeconomic development, with countries classified as low on the Human Development Index (HDI) reporting a 5-year survival rate of 36%, compared to 46% in middle-HDI countries and 54% in high-HDI countries. These disparities underscore the impact of economic and healthcare infrastructure on breast cancer outcomes [4].

Breast cancer treatment can be highly effective, achieving survival probabilities of 90% or higher, particularly when the disease is identified early [5]. Treatment typically involves a combination of surgical and non-surgical approaches, including chemotherapy, radiation therapy, and hormonal therapy. While this study primarily focuses on chemotherapy, it is important to acknowledge the significant role of radiation and hormonal therapy as adjuvant treatments in improving patient outcomes [1,3,5].

Chemotherapy can be categorized into two types based on its timing relative to surgery: neoadjuvant therapy, which is given prior to surgical intervention, and adjuvant therapy, administered post-surgery. Adjuvant chemotherapy (AC) is frequently employed to enhance outcomes for breast cancer patients, especially those with primary tumors exceeding 1 cm in size, estrogen receptor (ER) negative status, high-grade malignancies, and lymph node involvement [5]. It decreases the risk of breast cancer mortality mainly through the eradication of micro metastatic tumor deposits in patients with breast cancer, reduces the recurrence rate, and improves long-term overall survival [5,6].

The increasing incidence of breast cancer in Ethiopia is concerning, especially since most cases are diagnosed at late stages, similar to other low-resource settings [7,8]. Infrastructure and resources for routine mammography screening are often unavailable in low- and middle-income countries (LMCs). In such low-resource settings, breast cancer is commonly diagnosed at late stages, and women may receive inadequate treatment, pain relief, or palliative care. Since breast cancer is often diagnosed in the late stages in low- and middle-income countries (LMCs) in women, mortality rates are often much higher than in developed countries [2].

Research suggests that the timing of AC administration influences both overall survival (OS) and disease-free survival (DFS) in breast cancer patients. While the specific timeframes used to define early versus delayed initiation of adjuvant chemotherapy varied, studies indicate that beginning treatment sooner rather than later led to improved survival outcomes for individuals with BC [7-9].

The timely initiation of adjuvant chemotherapy is crucial in improving overall survival and reducing recurrence rates among breast cancer patients. However, multiple factors influence the time to adjuvant chemotherapy, including patient-related, tumor-related, and healthcare system-related factors [8]. While studies from high-income countries have well-documented these predictors, there is limited data from Ethiopia and other low-resource settings, where delayed chemotherapy initiation is a common challenge. Understanding the predictors of chemotherapy timing can help inform interventions to improve patient outcomes.

Literature review

Adjuvant chemotherapy use among women with breast cancer: following surgery, adjuvant chemotherapy (AC) is commonly prescribed for the majority of breast cancer patients. According to the National Comprehensive Cancer Network guidelines, AC is recommended for patients whose tumors exceed 1 cm in size, are estrogen receptor (ER) negative, or have lymph node involvement [10]. AC is of minimal benefit to women with negative nodes and cancers ≤0.5 cm in size and is not recommended. Patients with node-negative breast cancers measuring 0.6 to 1.0 cm are categorized into two groups: those at low risk of recurrence and those with unfavorable prognostic characteristics indicating a higher likelihood of recurrence, necessitating adjuvant chemotherapy. Factors associated with poor prognosis include invasion of blood or lymphatic vessels, high nuclear and histological grades, and hormone receptor-negative status [3].

Several clinical trials demonstrating the benefits of adjuvant chemotherapy have been published over the past 20 years, and clinical practice guidelines recommend chemotherapy for many breast cancer patients following the completion of definitive surgery to reduce the risk of recurrence [11]. Following surgery, adjuvant chemotherapy is typically suggested for 60-80% of breast cancer patients, reducing mortality risk by 30-40% [8].

Time to initiate adjuvant chemotherapy: the interval between surgical intervention and the initial dose of chemotherapy was used to define the time to adjuvant chemotherapy. For the majority of breast cancer patients, AC is considered the standard care approach. Clinical trials that have been published do not provide specific recommendations for the timing of chemotherapy following surgery, and there is considerable variation among trials in the permitted duration between surgical procedures and the commencement of adjuvant chemotherapy [12]. The criteria used to distinguish between early and delayed initiation of adjuvant chemotherapy varied across studies, with different cut-off points being employed [12]. However, there is a substantial theoretical rationale for initiating adjuvant chemotherapy immediately after curative surgery. Studies in animal models have demonstrated that surgery may increase the number of circulating tumor cells and oncogenic growth factors and accelerate the growth of metastases [11-13]. as a single dose of chemotherapy administered early seems more efficient than treatment given later [5]. Biological plausibility, clinical observations, and published studies have led to a comprehensive hypothesis that early initiation of AC is clinically crucial to patient survival, and long intervals between surgery and chemotherapy have been associated with poorer disease-specific outcomes [6,11,14].

Several professional societies have applied time-dependent quality measures. For example, the American Society of Clinical Oncology (ASCO)/National Comprehensive Cancer Network (NCCN) recommends adjuvant chemotherapy within 120 days of diagnosis for women aged less than 70 years with stage II or III hormone receptor-negative breast cancer [9]. Additionally, evidence suggests that while early chemotherapy initiation (within 4-8 weeks post-surgery) does not necessarily improve prognosis, delays beyond 12 weeks can significantly reduce disease-free survival [7].

Limited research has been conducted on the timing of adjuvant chemotherapy initiation for breast cancer patients. Studies across various countries have reported different median times to begin adjuvant chemotherapy for individuals with breast cancer. These include 35 days in Egypt, 46 days in the United States, 21 days in Turkey, 49 days in New Zealand, 38 days in Italy, and 44 days in Canada [9,11,15-17].

In the United States, an observational, population-based investigation using data from the California Cancer Registry studied 24,843 patients with stage I to III invasive breast cancer diagnosed between January 1, 2005, and December 31, 2010, and treated with adjuvant chemotherapy [15]. Data analysis was performed between August 2014 and August 2015. The median time to adjuvant chemotherapy was 46 days, and a delayed time to adjuvant chemotherapy was defined as ≥ 91 days from surgery to the first dose of adjuvant chemotherapy. Compared with patients receiving chemotherapy within 31 days of surgery, there was no evidence of adverse outcomes among those with a time to adjuvant chemotherapy (TTAC) of 31-60 or 60-90 days. Patients treated 91 days or more after surgery experienced worse overall survival (hazard ratio (HR), 1.34; 95% confidence interval (CI), 1.15-1.57) and worse breast cancer-specific survival (HR, 1.27; 95% CI, 1.05-1.53) [15]. In a study conducted in 2018, multiple U.S.A. cancer centers found that the median time to chemotherapy ranged from 35.6 to 55.4 days, with 94% of patients receiving treatment within 12 weeks, aligning with current standards of care [7]. In Ethiopia, a retrospective cohort study at the University of Gondar Comprehensive Specialized Hospital (2015-2019) found a median TTAC of 67 days (IQR: 34-102 days), suggesting that chemotherapy initiation is often delayed in Ethiopian settings compared to international standards [8].

Predictors of delayed time to adjuvant chemotherapy: the existing research indicates that several predicting factors influence the time to adjuvant chemotherapy. These predictors include economic constraints, insufficient awareness about breast cancer, delayed medical attention or limited access to affordable healthcare, patient age, place of residence, body mass index, marital status, year of diagnosis, surgical approach, cancer stage, presence of other health conditions, number of excisions performed, tumor grade, complications arising from surgery, and the status of surgical margins [8,17,18].

A retrospective study at Ain Shams University Hospital (Egypt) involving 300 patients with non-metastatic breast cancer found that 50% of chemotherapy delays were due to socioeconomic barriers and travel distance. Other delays were linked to health system issues (20%, e.g. late referrals, waiting lists, and insurance delays), surgical complications (1.7%), and comorbidities (1%). Notably, older postmenopausal women and those with multiple comorbidities were more likely to experience delays [12].

While numerous studies have been conducted in developed countries, there is a scarcity of research on the timing and factors influencing adjuvant chemotherapy in developing nations, including Ethiopia. A retrospective study was carried out at the University of Gondar Compressive Specialized Hospital in Ethiopia from January 2015 to February 2019. The log-rank test was employed to assess survival differences among groups. The study revealed significant variations in survival times across categories of comorbidity, surgical complications, surgical margin status, age, surgery type, and lymph node involvement [8]. A substantial 96.6% of patients with comorbidities received adjuvant chemotherapy after 30 days. Similarly, 97.0% of patients experiencing surgical complications underwent adjuvant chemotherapy after 30 days. In the multivariate analysis, age, comorbidity, margin status, and surgical complications emerged as significant predictors of time to adjuvant chemotherapy for breast cancer patients at a 5% significance level. The likelihood of initiating adjuvant chemotherapy was 66% lower (AHR= 0.34, 95% CI: 0.16-0.71) in breast cancer patients over 70 years old compared to those under 40.

Patients with comorbidities had a 57% decreased likelihood (AHR=0.43, 95% CI: 0.29, 0.62) of starting adjuvant chemotherapy compared to those without. The probability of beginning adjuvant chemotherapy was reduced by 45% (AHR=0.55, 95% CI: 0.34, 0.88) in patients with surgical complications versus those without. Women with positive surgical margins faced a 60% higher risk (AHR=0.40, 95% CI: 0.25, 0.64) of delayed adjuvant chemotherapy compared to those with negative margins [8]. The rising cancer incidence has not been met with adequate healthcare infrastructure, which has traditionally focused on managing infectious diseases. The scarcity of cancer specialists and treatment facilities in the country severely limits access to cancer care for most of the population, resulting in extended wait times for services. Furthermore, the study revealed that over a quarter (27%) of breast cancer patients were unable to afford chemotherapy due to its high cost, as the treatment was not covered by any exemption policy. This financial barrier further compounds the challenges in accessing cancer treatment services [8].

Methods     

Study area: this study was conducted at Hawassa University Comprehensive Specialized Hospital (HUCSH) in Hawassa, Sidama, Ethiopia, 275 km from Addis Ababa. Geographically, Hawassa lies between 7°03´43.38” latitude North and 38°28´34.86” longitudes East. It is bounded by Lake Hawassa in the West, Oromia Region in the North, Wondo Genet Woreda in the East, and Shebedino Woreda in the South.

Hawassa University Comprehensive Specialized Hospital was established in 1996 and currently provides health services to both inpatients and outpatients. Major inpatient services include obstetrics and gynecology, pediatric and child health, internal medicine, and surgery. other outpatient services include ophthalmology, dermatology and psychiatry, radiology, and pathology. The HUCSH Cancer Treatment Center initiated cancer treatment and follow-up services in September 2020. This includes outpatient and inpatient departments that provide services. Only 17 functional beds are available for chemotherapy in inpatient departments.

Serving as the sole comprehensive specialized facility for cancer care, the HUCSH Cancer Treatment Center provides services to over 18 million individuals residing in Sidama, southern nations and nationalities, and portions of the Oromia regions. The cancer treatment center administer chemotherapy to more than 800 new cancer patients each year.

Study period: this investigation was conducted from September 2020 and March 2022.

Study design: a facility-based retrospective follow-up study design was used by reviewing the paper-based medical records of all patients who met the inclusion criteria and started adjuvant chemotherapy at the HUCSH Cancer Treatment Center from September 2020 to March 2022.

Population

Sources population: the source population for this study was patients diagnosed with breast cancer at the Cancer Treatment Center of Hawassa University Comprehensive Specialized Hospital between September 2020 and March 2022.

Study population: patients with breast cancer who met the inclusion criteria and received adjuvant chemotherapy at the Cancer Treatment Center of Hawassa University Comprehensive Specialized Hospital were selected.

Eligibility criteria

Inclusion criteria: all women postoperative patients with breast cancer who attended the treatment center and initiated adjuvant chemotherapy at the HUCSH Oncology Center during the study period were enrolled.

Exclusion criteria: patients whose medical charts could not be found and incomplete data; male breast cancer patients; patients who had not undergone surgery; patients treated with Neo-adjuvant chemotherapy before adjuvant chemotherapy; patients who received radiation before or on the same day as the chemotherapy were excluded from the study.

Sample size determination: this study is a facility-based, retrospective follow-up study. All eligible breast cancer patients who met the inclusion criteria during the study period were included in the analysis, resulting in a final sample size of 205. While a sample size calculation was initially considered during the planning phase to ensure the study's statistical validity, it became unnecessary to limit the sample since all available patients were included to improve the precision of the study.

Sampling procedure: all eligible patients who attended the HUCSH Cancer Treatment Center and whose medical records were accessed at the hospital during the study period were enrolled.

Variables

Dependent variable: time to adjuvant chemotherapy.

Independent variable: independent variables that were included in this study: sociodemographic variables (Age at diagnosis and years since diagnosis, residence, marital status); type of surgery; body mass index (BMI) categories are defined as follows: under 18.5 kg/m² is "underweight", 18.5-24.9 kg/m² is "normal weight", 25-29.9 kg/m² is "overweight", and 30 kg/m² or higher is classified as "obesity"; marginal status and surgical complications encompass the occurrence of seroma, stitch granuloma, hematoma, lymphocele, lymphedema, or surgical wound infection; breast cancer stages at diagnosis are classified using the tumor, node, and metastasis classification system (TNM) criteria. stages IA and IB are grouped as stage I; stages IIA and IIB are classified as stage II; and stages IIIA, IIIB, and IIIC are categorized as stage III; the number of involved lymph nodes is categorized as 0, 1-3, or more than 3; co-morbidity is characterized by the presence of at least one of the following conditions: congestive heart failure, respiratory disease, acute myocardial infarction, liver disease, diabetes, renal disease, HIV/AIDS, or another type of cancer.

Operational definitions: adjuvant chemotherapy is defined as systemic cancer directed chemotherapy given after surgery; the date of definitive surgery was defined as the date of the most extensive procedure, such as modified radical mastectomy (MRM) or breast-constructive surgery (BCS), including axillary lymph node dissection; the time to adjuvant chemotherapy was defined as the number of days between definitive surgery and the first administration of adjuvant chemotherapy; for the study, an event was characterized as breast cancer patients receiving treatment with cyclophosphamide, 5-fluorouracil, adriamycin (doxorubicin), or a combination of cyclophosphamide and adriamycin during the observation period; breast cancer patients were considered censored in two scenarios: if they had not undergone any adjuvant chemotherapy by the end of the follow-up period, or if they were transferred to a different healthcare facility during the study before receiving adjuvant chemotherapy, resulting in a loss to follow-up; the interval between definitive surgery and the start of adjuvant chemotherapy was determined by comparing the dates of these two events using the compiled information.

Data collection procedure: breast cancer patients were originally distinguished from those with other cancer types through the use of paper-based medical records or cancer registries. The English version of the checklist was employed to extract data for all women who met the eligibility criteria. The checklist was designed using Google Forms, and data collectors filled out the Google Forms containing a checklist for each selected medical record. Incomplete data were excluded.

Data quality management: to ensure that the collected data were of high quality, they were evaluated for their completeness and consistency. Inconsistent or incomplete data were excluded from the analysis. Before the actual survey, the checklist was evaluated on 21 patients, which is 10% of the total sample size required for a pre-test to check its clarity, consistency, and acceptability. All the required changes were made based on the results of the pre-test.

Data processing and analysis: data gathered using the designed checklist were entered into Google Forms. After all the needed data were gathered, this information was downloaded to Excel and sent to SPSS program version 26 for data analysis. Categorical data was summarized using variable frequencies, while descriptive statistics were displayed through tables, graphs, and textual descriptions. Variables yielding a p-value below 0.2 in bi-variable analysis were incorporated into the multivariable analysis. The strength of association was indicated by the adjusted hazard ratio (AHR) with a 95% confidence interval (CI).

The event was characterized as breast cancer patients who began treatment with cyclophosphamide, 5-fluorouracil, adriamycin, or a combination of cyclophosphamide and adriamycin during the follow-up period. Censored cases included breast cancer patients who did not receive any adjuvant chemotherapy by the end of the follow-up period, as well as those who died, were lost to follow-up, or transferred to another care unit before receiving adjuvant chemotherapy during the study. The initiation of adjuvant chemotherapy was the primary event of interest, coded as "1" for occurrence and "0" for censored cases.

Ethical clearance: the research protocol approval was obtained from the Research Ethics and Evaluation Bureau (IRB) and the official letter of cooperation to the Hawassa University Compressive Specialized Hospital with Ethical Clearance number IRB/402/16 was obtained from the Institute of Public Health. Permission was obtained from the Oncology Department of the Cancer Treatment Center. Prior to conducting the study, verbal informed consent was obtained from the study participants before data collection, and all data obtained were kept confidential using codes instead of any personal identifier. Participants were informed that the information obtained from them would not be disclosed to a third party, and for some study participants who were not able to be reached, a waiver of consent to participate was requested and granted by the Research Ethics and Evaluation Bureau (IRB). To maintain confidentiality, the names and other personally identifiable information of patients were not recorded in the data extraction checklist. All collected data were used solely for this study and handled with strict confidentiality.

Results     

Sociodemographic characteristics of study participants: the research identified 205 breast cancer patients during the study period. However, the final analysis included only 155 patients, representing 75.6% of the total cases. The remaining 50 surveys included 15 clients with incomplete data, which were excluded after verification by two independent reviewers; 19 clients had neo-adjuvant chemotherapy, 12 clients did not undergo surgery, and 4 were male.

The mean age of the participants was 45.06 years (±11.74 years), ranging from 22 to 75 years. As indicated in Table 1, most of the participants were between the ages of 40 and 54 (40.0%), and of all 114 (73.5%) were married and residing in urban regions 100 (64.5%). Regarding educational and occupational status, 55(35.5%) were illiterate and 81 (52.3%) were housewives. Further information is provided in Table 1.

Other background characteristics of study participants: in this study, 85 (54.8%) patients were at clinical stage III at the time of diagnosis, and 45 (29.0%) breast cancer patients had additional comorbidity. Of these, 17.4% had hypertension, followed by diabetes (9.0%). Thirteen (8.4%) patients experienced surgical complications. Of these, 8 patients had surgical wound infections (5.2%). Further information is presented in Table 2.

Time to adjuvant chemotherapy of study participants: in this study, the median time before initiating adjuvant chemotherapy was 69 days, with an interquartile range of 26 days and a range from 28 to 157 days. Patients were categorized into four groups according to their waiting periods: 12.9% (20 patients) started treatment within 30 days, 23.2% (36 patients) waited 31-60 days, 43.9% (68 patients) began chemotherapy between 61-90 days, and 20% (31 patients) faced delays of over 90 days before commencing their adjuvant chemotherapy protocol (Figure 1).

Predictors of Time to adjuvant chemotherapy and comparison survival function among different categories of breast cancer patients: to evaluate survival differences among groups, the log-rank test was performed. Significant variations in survival time were observed across categories of age, educational status, body mass index, comorbidity, histological grades, surgical margin, and surgical complication in this study.

Among patients with comorbidity, 92.5% received adjuvant chemotherapy after 61 days. For those experiencing surgical complications, 58.3% took adjuvant chemotherapy between 31-60 days post-surgery.

The Kaplan-Meier (KM) survival function was utilized to illustrate survival difference between variables. The KM curve plots for breast cancer (BC) patients revealed that those with an underweight (BMI) had lower survival probabilities compared to patients with normal weight, overweight, and obese classifications (Figure 2). These findings indicated varying survival outcomes for BC patients across different BMI categories: normal, overweight, obese, and underweight. Furthermore, BC patients who experienced surgical complications displayed lower KM curve plots than those without such complications (Figure 3, Table 3).

The Cox proportional hazards (PH) model operates on the premise that the hazard ratio between any two specifications of the independent variables remains constant over time. This implies that the hazard for one category is a constant multiple of the hazard for any other category, with the multiplier being time independent.

In the bi-variable and multivariable stratified Cox regression analyses, several factors were identified as being linked to the commencement of adjuvant chemotherapy. These factors included age, BMI, educational background, presence of comorbidities, histological grade, complications from surgery, and the status of surgical margins (Table 4).

Multivariate Cox regression analysis revealed several significant associations between post-operative breast cancer and the timing of adjuvant chemotherapy. Patients who experienced surgical complications were 1.5 times more likely to initiate adjuvant chemotherapy earlier than those without such complications, with an adjusted hazard ratio (AHR) of 1.512 (95% CI: 1.287-3.140) (Figure 3). Patients with BMI classified as underweight were 1.5 times high likely to receive adjuvant chemotherapy earlier (AHR, 1.569 (95%CI) 1.569 (1.336, 3.887)).

Patients with post-operative breast cancer with comorbidity had a 25% lower likelihood of receiving adjuvant chemotherapy earlier than those without comorbidity (AHR, 0.751; 95%CI, 0.474-0.817). The presence of comorbidity (AHR =0.751 (95% CI: (0.474, 0.817)), age > 55 years (AHR=0.501 (95% CI: (0.110-0.582)), and illiteracy (AHR=0.829, 95% CI: (0.458-0.950)) were significantly associated with delayed time to adjuvant chemotherapy. To assess the PH assumption, a plot of -ln (- ln (survival probability) versus ln (survival time)) was plotted for body mass index and surgical complications. As shown in the graph of Body mass index and surgical complications, the hazards did not cross, indicating that the proportional hazard assumption was satisfied (Figure 2). However, the graphs cross each other in other categories.

In the multivariate model, histological grade and educational status were significant predictors of time to adjuvant chemotherapy in patients with breast cancer at a 5% level of significance.

Discussion     

In this study, the median time to initiate adjuvant chemotherapy was 69 days (95% CI: 55.76). Several factors, including body mass index (BMI), educational status, and surgical complications, were identified as significant predictors of the time to initiate adjuvant chemotherapy among breast cancer patients. The median time observed in this study aligns closely with findings from research conducted at Gonder University Comprehensive Specialized Hospital, where the median time was reported as 67 days [8]. A possible explanation for this median time to chemotherapy initiation at both hospitals is that, although both are university-owned, Gondar University Comprehensive Specialized Hospital´s Cancer Treatment Center has been operational since 2015, five years earlier than Hawassa University Comprehensive Specialized Hospital. This earlier establishment may have contributed to better infrastructure, more experienced oncology staff, and more efficient treatment processes, potentially offsetting any expected differences in treatment delays.

Compared to the recommended initiation of adjuvant chemotherapy (within 4-8 weeks) [7]. Following surgery and other studies conducted internationally, the time to chemotherapy initiation in this study was notably longer than findings reported in Egypt (35 days), the United States (35.6 to 55.4 days), Turkey (21 days), New Zealand (49 days), Italy (38 days), and Canada (44 days) [7,9,11,15-17]. This disparity can likely be attributed to the increasing incidence of cancer in Ethiopia, which has not been matched by a proportional expansion in cancer care resources. Furthermore, the Ethiopian health system has historically focused on combating communicable diseases, leaving cancer care under-resourced [2]. The limited number of oncology specialists and treatment centers exacerbates these challenges, contributing to prolonged waiting times for chemotherapy services.

Interestingly, the time to chemotherapy initiation in this study was shorter than that reported in Brazil (137 days) [19]. One potential explanation is the difference in the stages of cancer diagnosis. In Ethiopia, a significant proportion of patients are diagnosed at advanced stages (stage III), prompting expedited initiation of chemotherapy. Conversely, in Brazil, delays may be more prevalent among patients diagnosed at earlier stages, such as stage I, where treatment urgency may be perceived as lower [19,20].

Despite ongoing debate regarding the optimal timing for adjuvant chemotherapy, systematic reviews and meta-analyses recommend initiating treatment within 30 days to achieve the best outcomes [10]. Implementing a multidisciplinary approach to the diagnosis and treatment of breast cancer has been shown to significantly reduce delays in care. A multidisciplinary team enhances coordination, streamlines processes, and improves overall patient management, as evidenced by findings from systematic reviews. BMI was found to be a predictor of time to adjuvant chemotherapy. Patients who were underweight started adjuvant chemotherapy earlier than others. This finding is comparable to that of a study conducted at the National Comprehensive Cancer Network institutions. This could be the result of an increased likelihood of comorbidity as the BMI increases.

Educational status was also a predictor of the time to adjuvant chemotherapy. Patients who were educated started adjuvant chemotherapy earlier than the illiterate patients. This could be due to increased awareness of adjuvant chemotherapy. Surgical complications are another predictor of early adjuvant chemotherapy. This finding contradicts those of a retrospective study conducted in Egypt. This could be due to the increased health-seeking behavior of patients with surgical complications.

Limitations: while the study provides valuable insights, the limitation of this study was the collection of data on financial status, which was significant in other studies and was not assessed owing to the retrospective nature of the data. Additionally, it did not explore the effect of delayed adjuvant chemotherapy on survival outcomes, an area critical for clinical and public health interventions.

Recommendations: to address the challenges identified in this study, a multifaceted approach is essential. Strengthening national and regional policies, programs, and strategies for breast cancer prevention and treatments, including adjuvant chemotherapy, is a critical first step. The ministry of health, in collaboration with regional health bureaus and hospital management, should take the lead in formulating and implementing these policies. Policymakers and healthcare providers must work collaboratively to ensure early diagnosis and timely management throughout the patient care continuum. Special attention should be given to those who face additional barriers to initiating adjuvant chemotherapy to minimize delays and improve outcomes. Furthermore, hospital oncology units and cancer care teams should spearhead public awareness campaigns and patient counseling initiatives focused on the importance of timely initiating adjuvant chemotherapy should be prioritized. Additionally, addressing the significant healthcare infrastructure gap is vital. The HUCSH Cancer Treatment Center, currently the only specialized facility serving over 18 million people in the region, expanding cancer treatment facilities and establishing additional centers in underserved areas should be an urgent priority for the ministry of health and other stakeholders. These efforts will not only enhance access to timely care but also significantly improve the quality of life and survival outcomes for breast cancer patients in Ethiopia.

Conclusion     

This study identified that the time to initiate adjuvant chemotherapy was longer than the recommended initiation time. Body Mass Index, presence of surgical complications, presence of comorbidity, and educational status were key predictors of time to adjuvant chemotherapy. To address these delays, coordinated measures to strengthen policies, programs, and the implementation of breast cancer treatment strategies at both national and regional levels are essential. Policymakers and healthcare providers should prioritize early diagnosis and effective management during admission and ongoing care. Special attention should be given to overweight or obese patients to minimize delays in initiating adjuvant chemotherapy. Moreover, public awareness campaigns to enhance knowledge about breast cancer and adjuvant chemotherapy, along with robust patient counseling, should be actively promoted, particularly by the Ministry of Health in Ethiopia.

Competing interests     

The authors declare no competing interests.

Authors' contributions     

Adugna Getahun Deboch, Amanuel Hibistu Gashu, Abraham Negash Hailu, and Girum Mathewos Herego contributed to the acquisition, analysis, or interpretation of data; Adugna Getahun Deboch and Amanuel Hibistu Gashu drafted the manuscript, while Adugna Getahun Deboch, Kebede Tefera Betru, and Netsanet Bogale Akale critically reviewed it for important intellectual content; the concept and design of the study were developed by Adugna Getahun Deboch and Kebede Tefera Betru; supervision of the study was provided by Kebede Tefera Betru and Netsanet Bogale Akale. All the authors read and approved the final version of this manuscript.

Acknowledgments     

We would first like to express our deep and sincere gratitude to the Hawassa University College of Medicine and Health Science, School of Public Health, HUCSH Oncology Department, and the Surgical Department for their support and for providing the necessary information. Moreover, we extend our thanks to our data collectors and participants for their contribution to this study.

Tables and figures     

Table 1: sociodemographic characteristics of women with postoperative breast cancer patients attended Hawassa University Comprehensive Specialized Hospital Cancer Treatment Center, from September 2020 to March 2022

Table 2: other background characteristics of women with postoperative breast cancer patients attended Hawassa University Comprehensive Specialized Hospital Cancer Treatment Center, from September 2020 to March 2022

Table 3: survival time and log-rank test for different variables of women with postoperative breast cancer patients who attended Hawassa University Comprehensive Specialized Hospital Cancer Treatment Center, from September 2020 to March 2022

Table 4: adjusted hazard ratio of multivariable stratified Cox regression analysis of women with postoperative breast cancer patients at Hawassa University Comprehensive Specialized Hospital Cancer Treatment Center, from September 2020 to March 2022

Figure 1: histogram showing time to adjuvant chemotherapy of breast cancer patients attended Hawassa University Comprehensive Specialized Hospital Cancer Treatment Center, from September 2020 to March 2022

Figure 2: Kaplan-Meier survival curves for breast cancer patients with BMI categories attended Hawassa University Comprehensive Specialized Hospital Cancer Treatment Center, from September 2020 to March 2022

Figure 3: Kaplan-Meier survival curves for breast cancer patients with surgical complication categories attended Hawassa University Comprehensive Specialized Hospital Cancer Treatment Center, from September 2020 to March 2022

References