Treatment adherence and Associated Factors among Patients With breast Cancer in Ethiopia, systematic review and meta-analysis

Treatment adherence and Associated Factors among Patients With breast Cancer in Ethiopia, systematic review and meta-analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Treatment adherence and Associated Factors among Patients With breast Cancer in Ethiopia, systematic review and meta-analysis Mihretie Gedfew, Addisu Getie, Temesgen Ayenew, Haile Amha This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6582886/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Breast cancer is the most common cancer among women globally. In Ethiopia, limited healthcare resources and socioeconomic constraints impede treatment adherence. This review evaluates treatment adherence among Ethiopian breast cancer patients and suggests targeted interventions. Methods Following PRISMA guidelines, we searched PubMed, MEDLINE, EMBASE, CINAHL, Google Scholar, Science Direct, and Cochrane Library for English-language studies on breast cancer treatment adherence in Ethiopia. Observational studies on female breast cancer patients were included, with data extracted using Endnote X7. The Newcastle-Ottawa Scale assessed study quality and STATA Version 13 analyzed the data, revealing high heterogeneity. Results Seven studies, with 20,100 participants, were included. The pooled treatment adherence was 51.01% (95% CI: 48.83, 53.20), with significant heterogeneity (I² = 98.9%, p < 0.001). Key factors associated with adherence included no treatment side effects (OR: 5.34, 95% CI: 3.52, 7.16), family history of breast cancer (OR: 3.12, 95% CI: 1.95, 4.30), social support (OR: 4.33, 95% CI: 2.76, 5.89), and no comorbidity (OR: 4.33, 95% CI: 2.76, 5.89). Conclusion Treatment adherence among Ethiopian breast cancer patients was low. Higher adherence rates were linked to a lack of treatment side effects, a family history of breast cancer, good social support, and no comorbidity. Strategies should focus on reducing side effects, supporting patients with a family history of breast cancer, strengthening social support systems, and ensuring comprehensive care for comorbidities. Breast Cancer Treatment Adherence Associated Factors Ethiopia Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Background Breast cancer is the most common cancer among women worldwide, with considerable variations in incidence and outcomes between locations( 1 , 2 ). Breast cancer treatment frequently combines surgery, radiation therapy, chemotherapy, and hormone therapy. Adherence to these specified treatment regimens is critical for achieving optimal therapeutic outcomes, including increased survival rates and lower risk of recurrence( 3 ). Non-adherence can result in poor treatment outcomes, increased morbidity, and mortality. Breast cancer is a significant public health concern in Ethiopia due to the limited healthcare resources and infrastructure( 4 ). The Ethiopian healthcare system is frequently overwhelmed by a high disease burden, with patients having difficulty accessing specialized cancer treatments due to socioeconomic constraints, cultural beliefs, logistical impediments, treatment costs, distance to facilities, a lack of transportation, and insufficient provider-patient communication( 5 ). Treatment adherence is highly influenced by educational status, awareness, and family support. Educated patients better appreciate the need of adherence and controlling side effects, while family support provides critical emotional and practical assistance( 6 ). Effective healthcare provider-patient communication is critical for adherence; yet, in Ethiopia, a lack of qualified professionals and a high patient-to-provider ratio impede effective communication and patient education ( 7 ).Treatment side effects like nausea, exhaustion, and discomfort can impact adherence, making proper management of these effects critical for increasing adherence and treatment success ( 6 ). The purpose of this systematic review and meta-analysis is to assess treatment adherence among Ethiopian breast cancer patients, identify associated factors, and make recommendations for targeted interventions and policies to promote adherence and outcomes Methods This meta-analysis was prepared in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA)( 8 ). To find possibly relevant papers, the databases PubMed, MEDLINE, EMBASE, CINAHL, Google Scholar, Science Direct, and Cochrane Library were exhaustively searched with no time constraint. It has no effect on the outcomes of the systematic reviews and meta-analyses that all searches were restricted to English-language articles( 9 ). Unpublished documents were reviewed with the assistance of content specialists and reference list reviews. In addition, we searched additional research institutes, including the Addis Abeba Digital Library, for unpublished papers in the topic of our systematic review and meta-analysis. Endnote X7 (Thomson Reuters, Philadelphia, PA, USA) was utilized to obtain and manage the studies discovered by our search technique. The search was carried out between January 1 and February 1, 2024. All papers published through January 1, 2024 were included. The following keywords were used in the search: Sub Saharan Africa, Breast cancer, Cancer, Breast malignancy, magnitude of recurrence, prevalence of recurrence, Recurrence, and magnitude of reoccurrence of breast cancer. The search phrases were used alone and in combination with Boolean operators such as "OR" or "AND" ( supplemental table 1 ). Inclusion and exclusion criteria Inclusion criteria : The meta-analysis only included research that matched the following criteria: ( 1 ) all observational studies required to describe RBCa; ( 2 ) articles published in peer-reviewed journals or grey literature; and ( 3 ) articles written in English. Exclusion criteria Prior to exclusion, we were able to assess their eligibility by reading the research titles and abstracts. We reviewed the entire texts after determining which papers were relevant to our investigation. Throughout the article selection process, research that was not completely accessible (with full text available) was omitted. But, before we removed the items, we made at least two email efforts to contact the principal author. We were unable to evaluate the quality of each article without access to their entire content, thus they were eliminated. Furthermore, full-text reviews were undertaken for journals that did not publish our research findings. Study area Only studies done in Ethiopia. Population Research addressing just female breast cancer patients.. Publication condition The included articles were published and unpublished.. Study design This meta-analysis included all cross-sectional, case-control, and cohort observational study types that reported treatment adherence for breast cancer. Language Only English-language research was considered. Outcome measurements Treatment adherence is the degree to which a patient's behavior in taking medication, following a diet, and making lifestyle changes corresponds to the advice of a healthcare professional. Measurement tools for treatment adherence include self-reported surveys, pill counts, pharmacy refill records, and electronic medication monitoring systems( 10 ). Demographic characteristics, socioeconomic level, healthcare system factors, and patient-provider interactions all have a role in treatment adherence. Structured interviews, validated questionnaires, and a review of medical records are frequently used to examine these characteristics( 7 ). The second goal of the study was to identify the characteristics associated with treatment adherence in breast cancer patients. We computed the log odds ratio for this outcome, which depicts the connection between treatment adherence and associated covariates. We looked into the relationship between four critical criteria measured in each primary study and treatment adherence. Each study provided binary outcome data that was used to calculate the odds ratio for each factor. This review looked at characteristics such as having side effects, having family history, no history of comorbidity and having social support Data extraction Two authors (MG and AG) extracted the relevant data independently using a standardized data extraction form modified from the JBI data extraction format. Any discrepancies that developed between the two writers during the data collection process were resolved by consensus and discussion (a Delphi technique). If additional information or explanation was requested, the principal author of the original study was contacted. The data extraction form for the first outcome, prevalence, includes the following: sample size, study design, country of study, study area, primary author, publication year, and prevalence with 95% confidence interval. After extracting data from the secondary outcome (associated factors) in a two-by-two table format, the log odds ratio for each factor was calculated using the original study reports. Quality assessment MG and AG used the quality evaluation technique to separately assess the quality of each original study. The quality of research in cross-sectional, cohort, and case control studies was evaluated using a modified Newcastle-Ottawa Scale( 11 ). There are three main sections to this tool. The first component, which is scored from one to five stars, focuses on each study's methodological quality, including its sample size, response rate, and sampling process. The second section of the instrument assesses the comparability of the study cases or cohorts and has the potential to award two stars. The results and statistical analysis of the original study are reported in the last section, which may earn three stars. The mean score of the two reviewers was utilized to resolve any disagreements between them. Articles with a minimum score of six out of ten were considered to be of good quality. Following an examination of relevant research, this cut-off point was established Data processing and analysis Before analysis, the essential data from each original study were extracted using a Microsoft Excel spreadsheet form. The data was imported and then analyzed using the statistical application STATA Version 13. The standard error for each original study was calculated with the binomial distribution formula. Heterogeneity in reported prevalence was assessed by calculating p-values for the chi-square test, Q-statistics, and I2 test( 12 ). To evaluate the Der Simonian and Laird's pooled effect, a random effects meta-analysis model was created based on statistical test results. The included studies exhibited substantial heterogeneity (I2 = 93.0%, p < 0.001). To eliminate random fluctuations in the point estimates of the major research subgroups, analysis was performed based on study conditions such as the country of study, the year of publication, and the sample size. In addition, we used univariate meta-regression with sample size, primary study nation, and publication year as covariates to assess the likely cause of heterogeneity; none of these were found to be statistically significant. Egger's and Begg's tests revealed no publication bias at a 5% significance level ( 13 ). Point prevalence was displayed using a forest plot approach, with 95% confidence intervals. This graph depicted each crossing line as the 95% confidence interval, and the size of each box denoted the study's weight. A log odds ratio was used to determine the connection between RBCa and related factors in secondary outcomes. Results PubMed/MEDLINE, EMBASE, CINAHL, Google Scholar, Science Direct, Cochrane Library, and other previously mentioned sites. About 524 entries were eliminated from the original batch of articles due to duplication. After assessing titles and abstracts, 5,811 articles from the remaining 13,765 were discarded. Additionally, 9,252 articles were eliminated as they were deemed irrelevant to the review, and 4,501 items were removed because the complete articles were inaccessible. Consequently, the established criteria were applied to assess the eligibility of 13 articles, and the results indicated that 6 articles were rejected. Seven papers met the inclusion criteria and were therefore included in the final meta-analysis ( 6 , 14 ),( 15 ),( 16 ),( 17 ) supplementary table 1 ). Characteristics of original studies The present meta-analysis encompassed 20,100 participants, as illustrated in Table 1 below. According to the data from the primary studies, the ages of the respondents varied from 41.99 ± 10.9 ( 6 )to 48 ± 15.80( 17 ) years. Regarding publication year and study design, all included studies were published after 2020, with half being cross-sectional. Sample sizes varied from 66( 15 ) to 433( 17 ). In this analysis, a study conducted in Addis Ababa reported the highest treatment adherence at 83.5%( 6 ), while the lowest was in Amhara at 26.33%( 17 ). These seven studies were conducted in four regions: three in Amhara ( 18 ) ( 17 ), ( 16 ) one in Oromia ( 15 ), one in SNNPE( 5 ) and two in Addis Ababa( 14 ),( 6 )Ethiopia(Table 1 ) . Table 1 Baseline characteristics of the included studies Corresponding Author P. year Region study design sample size Prevalence (%) Quality score Zerko Wako ( 14 ) 2021 Adiss Ababa Cross-sectional 209 77.51 8 Christian Felix Reibold ( 15 ) 2021 Oromia Prospective cohort 66 34.85 7 Fatuma Hassen( 6 ) 2022 Adiss Ababa Cross-sectional 164 83.54 8 Yemane Eshetu Bekalu( 16 ) 2023 Amhara Cross-sectional 460 42.39 9 Sewunet Ademe( 17 ) unpublished Amhara Retrospective cohort 433 26.33 7 Amsalu Degu( 18 ) 2020 Amhara Cross-sectional 107 67.3 9 Sefonias Getachew( 5 ) unpublished SNNPE Random controlled trial 162 70.00 8 Meta-analysis A pooled prevalence of Treatment adherence was determined to be 51.01% (95%CI: 48.83, 53.20) based on the overall prevalence calculated from the 7 included studies (Fig. 1 ). We estimated the pooled prevalence of treatment adherence in Ethiopia by using a random effect meta-analysis model, as the included studies showed high heterogeneity (I 2 = 98.9, p < 0.001). Using Begg's and Egger's tests, publication bias was also evaluated. The results indicated no statistical significance for calculating the prevalence of treatment adherence among women in Ethiopia, with p-values of p = 0.000and p = 0.000, respectively (Fig. 1 ). Subgroup analysis The prevalence of treatment adherence was multiple-compared in this meta-analysis using several parameters. Having side effects, having family history of breast cancer, no history of comorbidity, and having social support were among the contributing variables. With 80.5% (95%CI: 74.62, 86.42) prevalence, Adiss Ababa had the greatest prevalence, followed by Amhara region at 34.33% (95%CI: 18.59, 50.08) as the subgroup by region. Similarly, this study's subgroup analysis showed that treatment prevalence was higher among studies with a sample size of less than 400, with a prevalence of 660.2% (95%CI: 44.58, 87.45), than in studies with a sample size of more than 400, with a prevalence of 34.33% (95CI: 18.59, 50.08). When it comes to cancer stage, advanced cancer account for 83.92% (29.84, 137.9) of cases, while early stage make up 42.866(27.331, 58.4%). Comparatively speaking to their counterparts, women residing in rural areas reported lower adherence rates ( Table 2 ). Table 2 Baseline characteristics of the included studies and subgroup prevalence of treatment adherence among patients with breast cancer Sub-group Category No. of studies Sample size Prevalence (95% CI) p-value I 2 Region Adiss Ababa 2 299 80.520 (74.616,, 86.424) 0.000 98.9% Amhara 3 416 33.840(22.519,45.160) 0.000 96.2% Oromia 1 66 34.848 (23.353, 46.344) 0.000 0.00% SNNPE 1 162 69.753(62.680,76.826) 0.000 0.00% Study design cross-sectional 4 833 67.767 (40.998, 94.536) 0.000 98.7% Prospective cohort 1 66 34.848(23.353, 46.344) 0.000 0.00% Retrosp. cohort 1 433 26.328 (22.180, 30.476) 0.000 0.00% RCT 1 162 67.95 (62.680,76.830) 0.000 98.5 Sample size ≤ 400 3 439 66.017 (44.581, 87.453) 0.000 96.4% > 400 4 1162 53.012 (29.437,76.587) 0.000 96.2% Residence urban 5 412 87.00(78.247, 95.753) 0.000 94.4% rural 4 415 55.627 (15.248,96.006) 0.007 99.3% Stage Early 4 172 42.866 (27.331,58.400) 0.000 94.6% Advanced 4 336 63.151 (31.478,94.824) 0.000 98.5% Social support yes 2 249 93.451 (82.672, 104.231) 0.000 66.0% No 2 74 36.880 (25.838,99.599 ) 0.000 99.5% Menopause status premenopausal 3 164 54.568 (21.84,87.294) 0.000 98.2% post-menopausal 3 233 62.574 (21.837, 83.310) 0.000 98.8% Educational status Illiterate 4 438 51.886(15.601, 88.172) 0.005 99.1% Literate 4 381 62.903(39.451, 86.354) 0.000 97.1% Comorbidity yes 2 90 44.915 (35.117,54.714) 0.000 71.0% no 3 263 74.88 (68.340, 96.560) 0.000 98.4% Having DM 2 38.0 18.843(9.048, 28.638) 0.000 82.9% Having HIV 2 63 26.369(2.050,54.787) 0.000 97.6% Sensitivity analysis When any of the studies were removed from the sensitivity analysis using the leave-one-out method, the pooled prevalence estimates and indications of heterogeneity within the major studies remained relatively unchanged. Therefore, the sensitivity analysis using the random effects model demonstrated that no single study significantly impacted the overall prevalence of treatment adherence ( table 3). Publication bias was evident among the included studies in the current analysis, as indicated by the asymmetrical distribution of the funnel plot (Fig. 2 ). Furthermore, the results of the Egger test for bias indicated a statistically significant presence of publication bias (P = 0.020). To further address and adjust for potential publication bias, a trim and fill analysis, a nonparametric technique for assessing and estimating the possibility of missing studies, was also conducted trim and fill analysis ( Supplementary Fig. 1) . Factors associated with treatment adherence among patients with breast cancer Association between treatment adherence and having no side effects among patients with breast cancer Based on the findings of three studies ( 14 ), ( 16 ),( 17 ) we investigated the relationship between treatment adherence and not experiencing treatment side effects, as illustrated in Fig. 3 below. The results indicated that having no treatment side effects was significantly associated with adherence (OR: 5.34, 95% CI: 3.52, 7.16). An association was determined using a random effects meta-analysis model, given the high heterogeneity (I2 = 95.6% and p < 0.001) in this analysis. The Begg’s and Eggers tests' results, which showed p-values of 0.785 and 1.83, respectively, suggested that the likelihood of publication bias was minimal ( Fig. 3 ). Association between treatment adherence and having family history of breast cancer From the meta-analysis of two studies ( 17 ),( 16 ) having family history was significantly associated with treatment adherence (OR: 3.12, 95% CI: 1.95, 4.30). In order to perform the final analysis, a random effect meta-analysis was used because the included studies showed high heterogeneity (I 2 = 83.5% and p < 0.014). The absence of publication bias was determined by utilizing Egger's and Begg's tests, yielding p-values of 0.62 and 0.19, respectively, as shown in Fig. 4 . Association between treatment adherence and having social support among patients with breast cancer From the meta-analysis of two studies ( 16 , 17 ) having social support was not significantly associated with treatment adherence (OR: 5.50, 95% CI: 2.56, 8.44). In order to perform the final analysis, a random effect meta-analysis was used although the included studies showed high heterogeneity (I 2 = 99.2% and p < 0.001) Fig. 5 . Association between treatment adherence and having no comorbidity among patients with breast cancer From the meta-analysis of three studies( 17 ), ( 18 ) ( 16 ) having no comorbidity was not significantly associated with treatment adherence (OR: 4.33, 95% CI: 2.76, 5.89). In order to perform the final analysis, a random effect meta-analysis was used although the included studies showed high heterogeneity (I2 = 96.6 and p < 0.001). The absence of publication bias was determined by utilizing Egger's and Begg's tests, yielding p-values of 0.62 and 0.19, respectively, as shown in Fig. 6 . Discursion The purpose of this meta-analysis was to assess the pooled prevalence of treatment adherence among breast cancer patients and find relevant factors. To our knowledge, this is the first study of its sort to give a thorough estimate of treatment adherence and its factors among Ethiopian women with breast cancer. In this systematic review and meta-analysis, the pooled prevalence of treatment adherence in Ethiopia was found to be 51.01% (95% CI: 48.83, 53.20). Our findings are consistent with prior systematic studies, which have found variable adherence rates among breast cancer patients worldwide. For example, a systematic review conducted in the United States revealed an average adherence rate to endocrine therapy of around 50%, which resembles our data( 19 ). Similarly, a review conducted in the United Kingdom ( 20 ) indicated that the adherence rate to adjuvant hormonal therapy was around 52% in their group, which is consistent with our results. However, this adherence rate is slightly lower than the adherence rates in Malaysia (66.2%)( 21 ) and in Australia (65%)( 22 ). The disparities between our findings and those from studies with higher adherence rates could be attributed to a variety of contextual factors. Patients in higher-income countries may benefit from more readily available healthcare services, better control of treatment side effects, and more tailored assistance. For example, the review from Germany( 23 ) highlights the importance of integrated care approaches and access to supporting therapies in improving adherence. Interestingly, our findings demonstrate a higher rate of adherence compared to other studies. For example, a systematic review conducted in India ( 24 ) found that breast cancer patients had reduced adherence rates of about 40%. Similarly, an assessment of Sub-Saharan Africa( 25 ) showed adherence rates as low as 35%. These lower adherence rates in other low-resource settings may reflect obstacles such as restricted access to healthcare, socioeconomic impediments, and insufficient support networks, which may not be as severe in Ethiopia as in these other regions. Several factors could explain Ethiopia's superior adherence rate compared to other trials. Despite experiencing its unique healthcare issues, Ethiopia could benefit from specialized local interventions or changes in healthcare delivery that boost patient adherence. Initiatives focused at enhancing healthcare access and offering targeted patient education, for example, may contribute to higher adherence in comparison to locations with more apparent hurdles. In this review the subgroup analysis by region of primary study indicated that the highest prevalence of treatment adherence was observed in Adiss Ababa, 80.520 (74.616,, 86.424) followed by Amhara, 33.840(22.519,45.160). Addis Abeba is likely to benefit from superior healthcare facilities and more thorough patient support than Amhara, which may have fewer healthcare resources. The subgroup analysis by region of primary study indicated that the highest prevalence of treatment adherence was observed in Adiss Ababa, 80.520 (74.616,, 86.424) followed by Amhara, 33.840(22.519,45.160). The current meta-analysis found that absence of treatment side effects was significantly associated with treatment adherence (OR: 5.34, 95% CI: 3.52, 7.16). Our findings indicated that patient with breast cancer who have no treatment side effect were 5.34 times more likely to experience higher treatment adherence than those who have treatment side effect. This finding is consistent with prior study, which found that reducing side effects can considerably enhance adherence to cancer therapies ( 26 ). Patients who do not experience side effects are more likely to stick to their treatment regimens since they have less disruptions and discomfort( 27 ). According to this meta-analysis, women with a family history of breast cancer are 3.12 times (OR: 3.12, 95% CI: 1.95, 4.30) more likely to adhere to their treatment regimen than those without a family history. Women with a family history of breast cancer more likely to stick to their treatment plan due to increased awareness and perceived importance of adherence resulting from personal or familial experiences( 28 ). This greater adherence is frequently prompted by the need to control their risk successfully ( 29 ). Our findings revealed that having social support among patients with breast cancer had a 5.5 times (OR: 5.50, 95% CI: 2.56, 8.44) higher treatment adherence that its counter parts. Our findings demonstrated that patients with breast cancer who received social support more likely to stick to their treatment plan, emphasizing the importance of social support in increasing adherence( 30 ). This increased adherence is frequently attributed to the emotional and practical support offered by social networks( 31 ). Our findings showed that patients with breast cancer who had no comorbidities were 4.33 times more likely to stick to their treatment plan, implying that the lack of extra health conditions greatly enhances adherence( 32 ). Comorbidities can complicate treatment and impede adherence, whereas a lack of comorbidities allows for more targeted and consistent treatment ( 33 ) Conclusion The pooled treatment adherence rate among Ethiopian breast cancer patients was low. Factors related with higher adherence rates included a lack of treatment adverse effects, a family history of breast cancer, good social support, and no comorbidity. To improve treatment adherence, develop strategies to reduce side effects, provide tailored support to patients with a family history of breast cancer, strengthen social support systems, ensure comprehensive care for comorbidities, Abbreviations BCa: Breast Cancer, CI: Confidence Interval, OR: Odds ratio; Region, WHO: World Health Organization. Declarations Acknowledgments Not applicable. Funding No funding was obtained for this study. Availability of data and materials Data will be available from the corresponding author upon reasonable request. Authors’ contributions "M.G. and A.G. wrote the main manuscript text, T.A. and H.A prepared figures 1-6. All authors reviewed the manuscript." Ethics declaration Not applicable. Consent for publication Not applicable. Competing interests The authors have declared that there are no competing interests. Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Author details 1 College of Health Sciences, Debre Markos University, P.O. Box 269, Debre Markos, Ethiopia . References Lin ID, Lin KH. The impact of adverse drug reactions on medication adherence and outpatient treatment outcomes in female breast cancer: A review protocol. Journal of Advanced Nursing. 2023;79(2):825–31. WHO. 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Supplementary Files Suplementarytable1.docx supplementaryfigure1.docx Supplementary figure 1: Result of trim and filled analysis for adjusting publication bias of the selected studies Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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Gedfew","email":"data:image/png;base64,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","orcid":"","institution":"Debre Markos University","correspondingAuthor":true,"prefix":"","firstName":"Mihretie","middleName":"","lastName":"Gedfew","suffix":""},{"id":467189954,"identity":"f08dfad6-5c3c-4d88-8d20-dc6dc9c17544","order_by":1,"name":"Addisu Getie","email":"","orcid":"","institution":"Debre Markos University","correspondingAuthor":false,"prefix":"","firstName":"Addisu","middleName":"","lastName":"Getie","suffix":""},{"id":467189955,"identity":"97bbce37-00a1-4a4a-b4f4-620f5393ca46","order_by":2,"name":"Temesgen Ayenew","email":"","orcid":"","institution":"Debre Markos University","correspondingAuthor":false,"prefix":"","firstName":"Temesgen","middleName":"","lastName":"Ayenew","suffix":""},{"id":467189956,"identity":"f8001bf8-8940-43b7-a3ce-6789ddefcbe4","order_by":3,"name":"Haile Amha","email":"","orcid":"","institution":"Debre Markos University","correspondingAuthor":false,"prefix":"","firstName":"Haile","middleName":"","lastName":"Amha","suffix":""}],"badges":[],"createdAt":"2025-05-03 08:23:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6582886/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6582886/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":84306038,"identity":"03eb586c-76b5-4e6d-b1e3-51bec946f5d3","added_by":"auto","created_at":"2025-06-10 11:24:28","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":34533,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot of the pooled treatment adherence among breast cancer in Ethiopia\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6582886/v1/5cc5e82d641dbf0c818a063a.png"},{"id":84306157,"identity":"1a1c5b81-f815-43ff-8cde-3bd8992b0176","added_by":"auto","created_at":"2025-06-10 11:24:36","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":15325,"visible":true,"origin":"","legend":"\u003cp\u003eFunnel plot with 95% confidence limits of the pooled treatment adherence among breast cancer in Ethiopia\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6582886/v1/bd9c4001fee4943ab3960a41.png"},{"id":84306021,"identity":"8ddb8abe-2af5-405e-a1f1-5341bd30ea00","added_by":"auto","created_at":"2025-06-10 11:24:27","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":23344,"visible":true,"origin":"","legend":"\u003cp\u003eAssociation between treatment adherence and having no side effects among patients with breast cancer\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6582886/v1/acaab4ec30677ffe38520a1e.png"},{"id":84306177,"identity":"2a07ac6a-b2ed-4dfc-a1cd-fd0b425a5ef6","added_by":"auto","created_at":"2025-06-10 11:24:38","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":23520,"visible":true,"origin":"","legend":"\u003cp\u003eAssociation between treatment adherence and having family history of breast cancer\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6582886/v1/8cceb4f703b1876da4d1914d.png"},{"id":84306150,"identity":"6b7ec04c-2677-46f7-b9de-cbf821516063","added_by":"auto","created_at":"2025-06-10 11:24:35","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":20554,"visible":true,"origin":"","legend":"\u003cp\u003eAssociation between treatment adherence and having social support among patients with breast cancer\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-6582886/v1/816a0011ca4c50c35c9e60db.png"},{"id":84306098,"identity":"52e846e6-4e82-45a8-ae6f-855dd9b78a73","added_by":"auto","created_at":"2025-06-10 11:24:34","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":23223,"visible":true,"origin":"","legend":"\u003cp\u003eAssociation between treatment adherence and having no comorbidity among patients with breast cancer\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-6582886/v1/90df710333963f579c8707d6.png"},{"id":90208465,"identity":"7f4a06d9-0a61-4583-948b-7129ab8ac764","added_by":"auto","created_at":"2025-08-30 00:46:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1307374,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6582886/v1/81616653-55b4-4d27-ae41-21f4e8cec486.pdf"},{"id":84306920,"identity":"3db77cc2-0c39-4d45-9512-b341999fb5d9","added_by":"auto","created_at":"2025-06-10 11:32:36","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":14523,"visible":true,"origin":"","legend":"","description":"","filename":"Suplementarytable1.docx","url":"https://assets-eu.researchsquare.com/files/rs-6582886/v1/d7928cf548c894c2f0c86589.docx"},{"id":84306095,"identity":"194eda1e-f9b6-4b59-a619-427fe57f8b40","added_by":"auto","created_at":"2025-06-10 11:24:33","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":15231,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary\u003c/strong\u003e \u003cstrong\u003efigure 1:\u003c/strong\u003e Result of trim and filled analysis for adjusting publication bias of the selected studies\u003c/p\u003e","description":"","filename":"supplementaryfigure1.docx","url":"https://assets-eu.researchsquare.com/files/rs-6582886/v1/280523987dca84e398966e6e.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Treatment adherence and Associated Factors among Patients With breast Cancer in Ethiopia, systematic review and meta-analysis","fulltext":[{"header":"Background","content":"\u003cp\u003eBreast cancer is the most common cancer among women worldwide, with considerable variations in incidence and outcomes between locations(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Breast cancer treatment frequently combines surgery, radiation therapy, chemotherapy, and hormone therapy. Adherence to these specified treatment regimens is critical for achieving optimal therapeutic outcomes, including increased survival rates and lower risk of recurrence(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Non-adherence can result in poor treatment outcomes, increased morbidity, and mortality.\u003c/p\u003e \u003cp\u003eBreast cancer is a significant public health concern in Ethiopia due to the limited healthcare resources and infrastructure(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). The Ethiopian healthcare system is frequently overwhelmed by a high disease burden, with patients having difficulty accessing specialized cancer treatments due to socioeconomic constraints, cultural beliefs, logistical impediments, treatment costs, distance to facilities, a lack of transportation, and insufficient provider-patient communication(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Treatment adherence is highly influenced by educational status, awareness, and family support. Educated patients better appreciate the need of adherence and controlling side effects, while family support provides critical emotional and practical assistance(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eEffective healthcare provider-patient communication is critical for adherence; yet, in Ethiopia, a lack of qualified professionals and a high patient-to-provider ratio impede effective communication and patient education (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).Treatment side effects like nausea, exhaustion, and discomfort can impact adherence, making proper management of these effects critical for increasing adherence and treatment success (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). The purpose of this systematic review and meta-analysis is to assess treatment adherence among Ethiopian breast cancer patients, identify associated factors, and make recommendations for targeted interventions and policies to promote adherence and outcomes\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThis meta-analysis was prepared in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA)(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). To find possibly relevant papers, the databases PubMed, MEDLINE, EMBASE, CINAHL, Google Scholar, Science Direct, and Cochrane Library were exhaustively searched with no time constraint. It has no effect on the outcomes of the systematic reviews and meta-analyses that all searches were restricted to English-language articles(\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Unpublished documents were reviewed with the assistance of content specialists and reference list reviews.\u003c/p\u003e \u003cp\u003eIn addition, we searched additional research institutes, including the Addis Abeba Digital Library, for unpublished papers in the topic of our systematic review and meta-analysis. Endnote X7 (Thomson Reuters, Philadelphia, PA, USA) was utilized to obtain and manage the studies discovered by our search technique. The search was carried out between January 1 and February 1, 2024. All papers published through January 1, 2024 were included. The following keywords were used in the search: Sub Saharan Africa, Breast cancer, Cancer, Breast malignancy, magnitude of recurrence, prevalence of recurrence, Recurrence, and magnitude of reoccurrence of breast cancer. The search phrases were used alone and in combination with Boolean operators such as \"OR\" or \"AND\" (\u003cb\u003esupplemental table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003c/b\u003e).\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eInclusion and exclusion criteria\u003c/h2\u003e \u003cp\u003e \u003cb\u003eInclusion criteria\u003c/b\u003e: The meta-analysis only included research that matched the following criteria: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) all observational studies required to describe RBCa; (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) articles published in peer-reviewed journals or grey literature; and (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) articles written in English.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eExclusion criteria\u003c/strong\u003e \u003cp\u003ePrior to exclusion, we were able to assess their eligibility by reading the research titles and abstracts. We reviewed the entire texts after determining which papers were relevant to our investigation. Throughout the article selection process, research that was not completely accessible (with full text available) was omitted. But, before we removed the items, we made at least two email efforts to contact the principal author. We were unable to evaluate the quality of each article without access to their entire content, thus they were eliminated. Furthermore, full-text reviews were undertaken for journals that did not publish our research findings.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eStudy area\u003c/strong\u003e \u003cp\u003eOnly studies done in Ethiopia.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003ePopulation\u003c/strong\u003e \u003cp\u003eResearch addressing just female breast cancer patients..\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003ePublication condition\u003c/strong\u003e \u003cp\u003eThe included articles were published and unpublished..\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eStudy design\u003c/strong\u003e \u003cp\u003eThis meta-analysis included all cross-sectional, case-control, and cohort observational study types that reported treatment adherence for breast cancer.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eLanguage\u003c/strong\u003e \u003cp\u003eOnly English-language research was considered.\u003c/p\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eOutcome measurements\u003c/h3\u003e\n\u003cp\u003eTreatment adherence is the degree to which a patient's behavior in taking medication, following a diet, and making lifestyle changes corresponds to the advice of a healthcare professional. Measurement tools for treatment adherence include self-reported surveys, pill counts, pharmacy refill records, and electronic medication monitoring systems(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Demographic characteristics, socioeconomic level, healthcare system factors, and patient-provider interactions all have a role in treatment adherence. Structured interviews, validated questionnaires, and a review of medical records are frequently used to examine these characteristics(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe second goal of the study was to identify the characteristics associated with treatment adherence in breast cancer patients. We computed the log odds ratio for this outcome, which depicts the connection between treatment adherence and associated covariates. We looked into the relationship between four critical criteria measured in each primary study and treatment adherence. Each study provided binary outcome data that was used to calculate the odds ratio for each factor. This review looked at characteristics such as having side effects, having family history, no history of comorbidity and having social support\u003c/p\u003e\n\u003ch3\u003eData extraction\u003c/h3\u003e\n\u003cp\u003eTwo authors (MG and AG) extracted the relevant data independently using a standardized data extraction form modified from the JBI data extraction format. Any discrepancies that developed between the two writers during the data collection process were resolved by consensus and discussion (a Delphi technique). If additional information or explanation was requested, the principal author of the original study was contacted. The data extraction form for the first outcome, prevalence, includes the following: sample size, study design, country of study, study area, primary author, publication year, and prevalence with 95% confidence interval. After extracting data from the secondary outcome (associated factors) in a two-by-two table format, the log odds ratio for each factor was calculated using the original study reports.\u003c/p\u003e\n\u003ch3\u003eQuality assessment\u003c/h3\u003e\n\u003cp\u003eMG and AG used the quality evaluation technique to separately assess the quality of each original study. The quality of research in cross-sectional, cohort, and case control studies was evaluated using a modified Newcastle-Ottawa Scale(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). There are three main sections to this tool. The first component, which is scored from one to five stars, focuses on each study's methodological quality, including its sample size, response rate, and sampling process. The second section of the instrument assesses the comparability of the study cases or cohorts and has the potential to award two stars. The results and statistical analysis of the original study are reported in the last section, which may earn three stars. The mean score of the two reviewers was utilized to resolve any disagreements between them. Articles with a minimum score of six out of ten were considered to be of good quality. Following an examination of relevant research, this cut-off point was established\u003c/p\u003e\n\u003ch3\u003eData processing and analysis\u003c/h3\u003e\n\u003cp\u003eBefore analysis, the essential data from each original study were extracted using a Microsoft Excel spreadsheet form. The data was imported and then analyzed using the statistical application STATA Version 13. The standard error for each original study was calculated with the binomial distribution formula. Heterogeneity in reported prevalence was assessed by calculating p-values for the chi-square test, Q-statistics, and I2 test(\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTo evaluate the Der Simonian and Laird's pooled effect, a random effects meta-analysis model was created based on statistical test results. The included studies exhibited substantial heterogeneity (I2\u0026thinsp;=\u0026thinsp;93.0%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). To eliminate random fluctuations in the point estimates of the major research subgroups, analysis was performed based on study conditions such as the country of study, the year of publication, and the sample size.\u003c/p\u003e \u003cp\u003eIn addition, we used univariate meta-regression with sample size, primary study nation, and publication year as covariates to assess the likely cause of heterogeneity; none of these were found to be statistically significant. Egger's and Begg's tests revealed no publication bias at a 5% significance level (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). Point prevalence was displayed using a forest plot approach, with 95% confidence intervals. This graph depicted each crossing line as the 95% confidence interval, and the size of each box denoted the study's weight. A log odds ratio was used to determine the connection between RBCa and related factors in secondary outcomes.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003ePubMed/MEDLINE, EMBASE, CINAHL, Google Scholar, Science Direct, Cochrane Library, and other previously mentioned sites. About 524 entries were eliminated from the original batch of articles due to duplication. After assessing titles and abstracts, 5,811 articles from the remaining 13,765 were discarded. Additionally, 9,252 articles were eliminated as they were deemed irrelevant to the review, and 4,501 items were removed because the complete articles were inaccessible. Consequently, the established criteria were applied to assess the eligibility of 13 articles, and the results indicated that 6 articles were rejected. Seven papers met the inclusion criteria and were therefore included in the final meta-analysis (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e),(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e),(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e),(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e) \u003cb\u003esupplementary table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003c/b\u003e).\u003c/p\u003e\n\u003ch3\u003eCharacteristics of original studies\u003c/h3\u003e\n\u003cp\u003eThe present meta-analysis encompassed 20,100 participants, as illustrated in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e below. According to the data from the primary studies, the ages of the respondents varied from 41.99\u0026thinsp;\u0026plusmn;\u0026thinsp;10.9 (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e)to 48\u0026thinsp;\u0026plusmn;\u0026thinsp;15.80(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e) years. Regarding publication year and study design, all included studies were published after 2020, with half being cross-sectional. Sample sizes varied from 66(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e) to 433(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). In this analysis, a study conducted in Addis Ababa reported the highest treatment adherence at 83.5%(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e), while the lowest was in Amhara at 26.33%(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). These seven studies were conducted in four regions: three in Amhara (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e) (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e), (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e) one in Oromia (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e), one in SNNPE(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e) and two in Addis Ababa(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e),(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e)Ethiopia(Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline characteristics of the included studies\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCorresponding Author\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eP. year\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRegion\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003estudy design\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003esample\u003c/p\u003e \u003cp\u003esize\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePrevalence (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eQuality score\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZerko Wako (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAdiss Ababa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCross-sectional\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e209\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e77.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChristian Felix Reibold (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOromia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProspective cohort\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e34.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFatuma Hassen(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAdiss Ababa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCross-sectional\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e164\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e83.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYemane Eshetu Bekalu(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAmhara\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCross-sectional\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e460\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e42.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSewunet Ademe(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eunpublished\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAmhara\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRetrospective cohort\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e433\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e26.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAmsalu Degu(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAmhara\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCross-sectional\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e107\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e67.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSefonias Getachew(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eunpublished\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSNNPE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRandom controlled trial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e162\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e70.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eMeta-analysis\u003c/h3\u003e\n\u003cp\u003eA pooled prevalence of Treatment adherence was determined to be 51.01% (95%CI: 48.83, 53.20) based on the overall prevalence calculated from the 7 included studies (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). We estimated the pooled prevalence of treatment adherence in Ethiopia by using a random effect meta-analysis model, as the included studies showed high heterogeneity (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;98.9, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Using Begg's and Egger's tests, publication bias was also evaluated. The results indicated no statistical significance for calculating the prevalence of treatment adherence among women in Ethiopia, with p-values of p\u0026thinsp;=\u0026thinsp;0.000and p\u0026thinsp;=\u0026thinsp;0.000, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eSubgroup analysis\u003c/h2\u003e \u003cp\u003eThe prevalence of treatment adherence was multiple-compared in this meta-analysis using several parameters. Having side effects, having family history of breast cancer, no history of comorbidity, and having social support were among the contributing variables. With 80.5% (95%CI: 74.62, 86.42) prevalence, Adiss Ababa had the greatest prevalence, followed by Amhara region at 34.33% (95%CI: 18.59, 50.08) as the subgroup by region. Similarly, this study's subgroup analysis showed that treatment prevalence was higher among studies with a sample size of less than 400, with a prevalence of 660.2% (95%CI: 44.58, 87.45), than in studies with a sample size of more than 400, with a prevalence of 34.33% (95CI: 18.59, 50.08). When it comes to cancer stage, advanced cancer account for 83.92% (29.84, 137.9) of cases, while early stage make up 42.866(27.331, 58.4%). Comparatively speaking to their counterparts, women residing in rural areas reported lower adherence rates \u003cb\u003e(\u003c/b\u003eTable \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline characteristics of the included studies and subgroup prevalence of treatment adherence among patients with breast cancer\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSub-group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo. of studies\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSample size\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePrevalence (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eI\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eRegion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAdiss Ababa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e299\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e80.520 (74.616,, 86.424)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e98.9%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAmhara\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e416\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e33.840(22.519,45.160)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e96.2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOromia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e34.848 (23.353, 46.344)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.00%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSNNPE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e162\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e69.753(62.680,76.826)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.00%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eStudy design\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ecross-sectional\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e833\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e67.767 (40.998, 94.536)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e98.7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProspective cohort\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e34.848(23.353, 46.344)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.00%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRetrosp. cohort\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e433\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e26.328 (22.180, 30.476)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.00%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRCT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e162\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e67.95 (62.680,76.830)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e98.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eSample size\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026le;\u003c/span\u003e\u0026thinsp;400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e439\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e66.017 (44.581, 87.453)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e96.4%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1162\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e53.012 (29.437,76.587)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e96.2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eResidence\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eurban\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e412\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e87.00(78.247, 95.753)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e94.4%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003erural\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e415\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e55.627 (15.248,96.006)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e99.3%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eStage\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEarly\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e172\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e42.866 (27.331,58.400)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e94.6%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAdvanced\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e336\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e63.151 (31.478,94.824)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e98.5%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSocial support\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eyes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e249\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e93.451 (82.672, 104.231)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e66.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e36.880 (25.838,99.599 )\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e99.5%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMenopause status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003epremenopausal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e164\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e54.568 (21.84,87.294)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e98.2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003epost-menopausal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e233\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e62.574 (21.837, 83.310)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e98.8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducational status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIlliterate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e438\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e51.886(15.601, 88.172)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e99.1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLiterate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e381\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e62.903(39.451, 86.354)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e97.1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eComorbidity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eyes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e44.915 (35.117,54.714)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e71.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e263\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e74.88 (68.340, 96.560)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e98.4%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHaving DM\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e18.843(9.048, 28.638)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e82.9%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHaving HIV\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e26.369(2.050,54.787)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e97.6%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eSensitivity analysis\u003c/h2\u003e \u003cp\u003eWhen any of the studies were removed from the sensitivity analysis using the leave-one-out method, the pooled prevalence estimates and indications of heterogeneity within the major studies remained relatively unchanged. Therefore, the sensitivity analysis using the random effects model demonstrated that no single study significantly impacted the overall prevalence of treatment adherence (\u003cb\u003etable 3).\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cimg 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\" height=\"295\" width=\"584\"\u003e\u003c/p\u003e\u003cp\u003ePublication bias was evident among the included studies in the current analysis, as indicated by the asymmetrical distribution of the funnel plot (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e Furthermore, the results of the Egger test for bias indicated a statistically significant presence of publication bias (P\u0026thinsp;=\u0026thinsp;0.020). To further address and adjust for potential publication bias, a trim and fill analysis, a nonparametric technique for assessing and estimating the possibility of missing studies, was also conducted trim and fill analysis (\u003cb\u003eSupplementary Fig.\u0026nbsp;1)\u003c/b\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eFactors associated with treatment adherence among patients with breast cancer\u003c/h2\u003e \u003cdiv id=\"Sec14\" class=\"Section3\"\u003e \u003ch2\u003eAssociation between treatment adherence and having no side effects among patients with breast cancer\u003c/h2\u003e \u003cp\u003eBased on the findings of three studies (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e), (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e),(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e) we investigated the relationship between treatment adherence and not experiencing treatment side effects, as illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e below. The results indicated that having no treatment side effects was significantly associated with adherence (OR: 5.34, 95% CI: 3.52, 7.16). An association was determined using a random effects meta-analysis model, given the high heterogeneity (I2\u0026thinsp;=\u0026thinsp;95.6% and p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) in this analysis. The Begg\u0026rsquo;s and Eggers tests' results, which showed p-values of 0.785 and 1.83, respectively, suggested that the likelihood of publication bias was minimal \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eAssociation between treatment adherence and having family history of breast cancer\u003c/h2\u003e \u003cp\u003eFrom the meta-analysis of two studies (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e),(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e) having family history was significantly associated with treatment adherence (OR: 3.12, 95% CI: 1.95, 4.30). In order to perform the final analysis, a random effect meta-analysis was used because the included studies showed high heterogeneity (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;83.5% and p\u0026thinsp;\u0026lt;\u0026thinsp;0.014). The absence of publication bias was determined by utilizing Egger's and Begg's tests, yielding p-values of 0.62 and 0.19, respectively, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eAssociation between treatment adherence and having social support among patients with breast cancer\u003c/h2\u003e \u003cp\u003eFrom the meta-analysis of two studies (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e) having social support was not significantly associated with treatment adherence (OR: 5.50, 95% CI: 2.56, 8.44). In order to perform the final analysis, a random effect meta-analysis was used although the included studies showed high heterogeneity (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;99.2% and p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eAssociation between treatment adherence and having no comorbidity among patients with breast cancer\u003c/h2\u003e \u003cp\u003eFrom the meta-analysis of three studies(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e), (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e) (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e) having no comorbidity was not significantly associated with treatment adherence (OR: 4.33, 95% CI: 2.76, 5.89). In order to perform the final analysis, a random effect meta-analysis was used although the included studies showed high heterogeneity (I2\u0026thinsp;=\u0026thinsp;96.6 and p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The absence of publication bias was determined by utilizing Egger's and Begg's tests, yielding p-values of 0.62 and 0.19, respectively, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discursion","content":"\u003cp\u003eThe purpose of this meta-analysis was to assess the pooled prevalence of treatment adherence among breast cancer patients and find relevant factors. To our knowledge, this is the first study of its sort to give a thorough estimate of treatment adherence and its factors among Ethiopian women with breast cancer.\u003c/p\u003e \u003cp\u003eIn this systematic review and meta-analysis, the pooled prevalence of treatment adherence in Ethiopia was found to be 51.01% (95% CI: 48.83, 53.20). Our findings are consistent with prior systematic studies, which have found variable adherence rates among breast cancer patients worldwide. For example, a systematic review conducted in the United States revealed an average adherence rate to endocrine therapy of around 50%, which resembles our data(\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). Similarly, a review conducted in the United Kingdom (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e) indicated that the adherence rate to adjuvant hormonal therapy was around 52% in their group, which is consistent with our results. However, this adherence rate is slightly lower than the adherence rates in Malaysia (66.2%)(\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e) and in Australia (65%)(\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe disparities between our findings and those from studies with higher adherence rates could be attributed to a variety of contextual factors. Patients in higher-income countries may benefit from more readily available healthcare services, better control of treatment side effects, and more tailored assistance. For example, the review from Germany(\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e) highlights the importance of integrated care approaches and access to supporting therapies in improving adherence.\u003c/p\u003e \u003cp\u003eInterestingly, our findings demonstrate a higher rate of adherence compared to other studies. For example, a systematic review conducted in India (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e) found that breast cancer patients had reduced adherence rates of about 40%. Similarly, an assessment of Sub-Saharan Africa(\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e) showed adherence rates as low as 35%. These lower adherence rates in other low-resource settings may reflect obstacles such as restricted access to healthcare, socioeconomic impediments, and insufficient support networks, which may not be as severe in Ethiopia as in these other regions.\u003c/p\u003e \u003cp\u003eSeveral factors could explain Ethiopia's superior adherence rate compared to other trials. Despite experiencing its unique healthcare issues, Ethiopia could benefit from specialized local interventions or changes in healthcare delivery that boost patient adherence. Initiatives focused at enhancing healthcare access and offering targeted patient education, for example, may contribute to higher adherence in comparison to locations with more apparent hurdles.\u003c/p\u003e \u003cp\u003eIn this review the subgroup analysis by region of primary study indicated that the highest prevalence of treatment adherence was observed in Adiss Ababa, 80.520 (74.616,, 86.424) followed by Amhara, 33.840(22.519,45.160). Addis Abeba is likely to benefit from superior healthcare facilities and more thorough patient support than Amhara, which may have fewer healthcare resources.\u003c/p\u003e \u003cp\u003eThe subgroup analysis by region of primary study indicated that the highest prevalence of treatment adherence was observed in Adiss Ababa, 80.520 (74.616,, 86.424) followed by Amhara, 33.840(22.519,45.160).\u003c/p\u003e \u003cp\u003eThe current meta-analysis found that absence of treatment side effects was significantly associated with treatment adherence (OR: 5.34, 95% CI: 3.52, 7.16). Our findings indicated that patient with breast cancer who have no treatment side effect were 5.34 times more likely to experience higher treatment adherence than those who have treatment side effect. This finding is consistent with prior study, which found that reducing side effects can considerably enhance adherence to cancer therapies (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). Patients who do not experience side effects are more likely to stick to their treatment regimens since they have less disruptions and discomfort(\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAccording to this meta-analysis, women with a family history of breast cancer are 3.12 times (OR: 3.12, 95% CI: 1.95, 4.30) more likely to adhere to their treatment regimen than those without a family history. Women with a family history of breast cancer more likely to stick to their treatment plan due to increased awareness and perceived importance of adherence resulting from personal or familial experiences(\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). This greater adherence is frequently prompted by the need to control their risk successfully (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOur findings revealed that having social support among patients with breast cancer had a 5.5 times (OR: 5.50, 95% CI: 2.56, 8.44) higher treatment adherence that its counter parts. Our findings demonstrated that patients with breast cancer who received social support more likely to stick to their treatment plan, emphasizing the importance of social support in increasing adherence(\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). This increased adherence is frequently attributed to the emotional and practical support offered by social networks(\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOur findings showed that patients with breast cancer who had no comorbidities were 4.33 times more likely to stick to their treatment plan, implying that the lack of extra health conditions greatly enhances adherence(\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). Comorbidities can complicate treatment and impede adherence, whereas a lack of comorbidities allows for more targeted and consistent treatment (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e)\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe pooled treatment adherence rate among Ethiopian breast cancer patients was low. Factors related with higher adherence rates included a lack of treatment adverse effects, a family history of breast cancer, good social support, and no comorbidity. To improve treatment adherence, develop strategies to reduce side effects, provide tailored support to patients with a family history of breast cancer, strengthen social support systems, ensure comprehensive care for comorbidities,\u003c/p\u003e "},{"header":"Abbreviations","content":"\u003cp\u003eBCa: Breast Cancer, CI: Confidence Interval, OR: Odds ratio; Region, WHO: World Health Organization.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo funding was obtained for this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData will be available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026quot;M.G. and A.G. wrote the main manuscript text, T.A. and H.A prepared figures 1-6. All authors reviewed the manuscript.\u0026quot;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have declared that there are no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePublisher\u0026rsquo;s Note\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSpringer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor details\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003csup\u003e1\u003c/sup\u003e\u003c/em\u003e\u003cem\u003eCollege of Health Sciences, Debre Markos University, P.O. Box 269, Debre Markos, Ethiopia\u003c/em\u003e.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLin ID, Lin KH. The impact of adverse drug reactions on medication adherence and outpatient treatment outcomes in female breast cancer: A review protocol. Journal of Advanced Nursing. 2023;79(2):825\u0026ndash;31.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWHO. Breast cancer: prevention and control. The World Health Organization Geneva; 2018.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHershman DL, Kushi LH, Shao T, Buono D, Kershenbaum A, Tsai W-Y, et al. Early discontinuation and nonadherence to adjuvant hormonal therapy in a cohort of 8,769 early-stage breast cancer patients. Journal of Clinical Oncology. 2010;28(27):4120\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSuda K, Mizuuchi H, Sato K, Takemoto T, Iwasaki T, Mitsudomi T. 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Minia Scientific Nursing Journal. 2023;14(2):8\u0026ndash;20.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNewcastle O. Newcastle-Ottawa: scale customized for cross-sectional studies in. 2018. Google Scholar.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eR\u0026uuml;cker G, Schwarzer G, Carpenter JR, Schumacher M. Undue reliance on I 2 in assessing heterogeneity may mislead. BMC medical research methodology. 2008;8:1\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBorenstein M, Hedges LV, Higgins JP, Rothstein HR. A basic introduction to fixed-effect and random‐effects models for meta‐analysis. Research synthesis methods. 2010;1(2):97\u0026ndash;111.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWako Z, Mengistu D, Dinegde NG, Asefa T, Wassie M. 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Breast Cancer Research and Treatment (United States). 2020.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMurphy CC, Bartholomew LK, Carpentier MY, Bluethmann SM, Vernon SW. Adherence to adjuvant hormonal therapy among breast cancer survivors in clinical practice: a systematic review. Breast cancer research and treatment. 2012;134:459\u0026ndash;78.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYussof I, Tahir NAM, Hatah E, Shah NM. Factors influencing five-year adherence to adjuvant endocrine therapy in breast cancer patients: a systematic review. The Breast. 2022;62:22\u0026ndash;35.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRosso R, D\u0026rsquo;Alonzo M, Bounous VE, Actis S, Cipullo I, Salerno E, et al. Adherence to adjuvant endocrine therapy in breast cancer patients. Current Oncology. 2023;30(2):1461\u0026ndash;72.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eal. NHe. Barriers and facilitators to adherence to breast cancer adjuvant therapy: A systematic review of the literature. Supportive Care in Cancer. 2016..\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eal. ABe. Adherence to breast cancer treatment in India: A systematic review. 2021\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eal. CDe. Factors influencing treatment adherence among breast cancer patients in Sub-Saharan Africa: A systematic review. 2022\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePan Y, Yang K, Shi X, Liang H, Shen X, Wang R, et al. Clinical benefits of acupuncture for the reduction of hormone therapy\u0026ndash;related side effects in breast cancer patients: a systematic review. Integrative cancer therapies. 2018;17(3):602\u0026ndash;18.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee J, Kim, S., \u0026amp; Park, H.. Relationship between side effects and adherence in cancer therapy: A comprehensive review.. Journal of Clinical Oncology. 2019.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLipscomb J, Escoffery C, Gillespie TW, Henley SJ, Smith RA, Chociemski T, et al. Improving screening uptake among breast cancer survivors and their first-degree relatives at elevated risk to breast cancer: Results and implications of a randomized study in the state of Georgia. International Journal of Environmental Research and Public Health. 2020;17(3):977.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrown L, \u0026amp; Wilson, T. The impact of family history on patient adherence to cancer treatment.. Oncology Nursing Forum. 2021.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMkuu RS, Harvey IS, Brown E, Spears EC, Jira MG, Johnson KL, et al. \u0026ldquo;I Struggle with breast cancer and I struggle with God\u0026rdquo;: insights from African American breast cancer survivors. Journal of Racial and Ethnic Health Disparities. 2021:1\u0026ndash;10.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWilliams H, \u0026amp; Davis, R.. Social support and cancer treatment adherence: A review.. Oncology Nursing Forum. 2019.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJones R, Smith, A., \u0026amp; Brown, L. The impact of comorbidities on treatment adherence in breast cancer patients.. Journal of Clinical Oncology. 2020.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTaylor M, \u0026amp; Green, P.. Comorbid conditions and their effect on cancer treatment adherence.. Cancer Care Review. 2021.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Breast Cancer, Treatment Adherence, Associated Factors, Ethiopia","lastPublishedDoi":"10.21203/rs.3.rs-6582886/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6582886/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eBreast cancer is the most common cancer among women globally. In Ethiopia, limited healthcare resources and socioeconomic constraints impede treatment adherence. This review evaluates treatment adherence among Ethiopian breast cancer patients and suggests targeted interventions.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003e Following PRISMA guidelines, we searched PubMed, MEDLINE, EMBASE, CINAHL, Google Scholar, Science Direct, and Cochrane Library for English-language studies on breast cancer treatment adherence in Ethiopia. Observational studies on female breast cancer patients were included, with data extracted using Endnote X7. The Newcastle-Ottawa Scale assessed study quality and STATA Version 13 analyzed the data, revealing high heterogeneity.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eSeven studies, with 20,100 participants, were included. The pooled treatment adherence was 51.01% (95% CI: 48.83, 53.20), with significant heterogeneity (I\u0026sup2; = 98.9%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Key factors associated with adherence included no treatment side effects (OR: 5.34, 95% CI: 3.52, 7.16), family history of breast cancer (OR: 3.12, 95% CI: 1.95, 4.30), social support (OR: 4.33, 95% CI: 2.76, 5.89), and no comorbidity (OR: 4.33, 95% CI: 2.76, 5.89).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eTreatment adherence among Ethiopian breast cancer patients was low. Higher adherence rates were linked to a lack of treatment side effects, a family history of breast cancer, good social support, and no comorbidity. Strategies should focus on reducing side effects, supporting patients with a family history of breast cancer, strengthening social support systems, and ensuring comprehensive care for comorbidities.\u003c/p\u003e","manuscriptTitle":"Treatment adherence and Associated Factors among Patients With breast Cancer in Ethiopia, systematic review and meta-analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-10 11:24:07","doi":"10.21203/rs.3.rs-6582886/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"40d59b5d-9866-4322-82d7-5ad7b08114a5","owner":[],"postedDate":"June 10th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-08-30T00:38:16+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-10 11:24:07","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6582886","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6582886","identity":"rs-6582886","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}