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Mortality rate and predictors of colorectal cancer patients in Ethiopia: a systematic review and meta-analysis

BMC Cancer volume 24, Article number: 821 (2024) Cite this article

Abstract

Introduction

The incidence of colorectal cancer (CRC) has been increasing in Sub-Saharan countries, including Ethiopia. However, the real mortality rate for CRC patients in Ethiopia has not been established. Therefore, this systematic review and meta-analysis aimed to determine the overall mortality rate and identify predictors among CRC patients in Ethiopia.

Methods

PubMed, EMBASE, Web of Science, Scopus, Science Direct, and Google Scholar were searched to identify relevant articles. The preferred reporting items for systematic reviews and meta-analyses (PRISMA) were followed. The quality of the included studies was assessed using the Newcastle-Ottawa Scale Critical Appraisal checklist. A random effect model was used to estimate the pooled mortality rate and adjusted hazard ratio (AHR). Publication bias was assessed using funnel plots and Egger’s regression test, while heterogeneity was evaluated through the Cochran Q test and I2 statistics.

Results

After reviewing 74 articles, only 7 studies met the criteria and were included in the analysis. The analysis revealed that the overall mortality rate among CRC patients in Ethiopia was 40.5% (95% confidence interval [CI]: 32.05, 48.87) while the survival rates at 1 year, 3 years, and 5 years were 82.3% (95% CI: 73.33, 91.31), 48.8% (95% CI: 43.35, 54.32), and 26.6% (95% CI: 21.26, 31.91) respectively. Subgroup analysis indicated that studies conducted after 2017 had higher mortality rates compared to those studied earlier (43.0% vs. 38.2%). Older age (AHR: 1.89, 95% CI: 1.27, 2.82); being married (AHR: 2.53, 95% CI: 1.79, 3.57); having comorbidities (AHR: 1.84, 95% CI: 1.45, 2.35); having high CEA levels (AHR: 2.06, CI: 1.35, 3.13); being in stage II (AHR: 4.13, 95% CI: 1.85, 9.22), III (AHR: 8.62, 95% CI: 3.88, 19.15), and IV (AHR: 8.06, CI: 2.89, 22.49) were the most important predictors.

Conclusion

In Ethiopia, the mortality rate among individuals diagnosed with CRC is high, with two out of five patients dying from this disease. Age, marital status, CEA level, comorbidities, and cancer stage were identified as predictors of mortality in CRC patients. Therefore, early detection and screening should be prioritized, particularly for older patients, those who are married, have comorbidities, elevated CEA levels, and advanced cancer stages.

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Introduction

Colorectal cancer (CRC), an umbrella term encompassing colon, rectal, and anal cancer, is a major public health problem worldwide [1, 2]. It’s more common in developed countries, but it’s on the rise in middle and low-income countries because of westernization [3]. In recent years, the number of cases has been growing at an alarming rate, with about 1.93 million new cases and 935,000 deaths globally [4, 5]. Among these deaths, 46.3% were recorded in Asia, while Europe, North America, and Africa recorded 29.7%, 8.4%, and 4.6% respectively [6]. These numbers collectively make up about 9% of all cancer-related deaths [7].

It is estimated that by 2030, the worldwide burden of CRC will upsurge by 60%, reaching more than 2.2 million new cases and 1.1 million deaths [8]. In the same vein, by the year 2040, there will be 1.6 million deaths from colorectal cancer, an increase of 63% [9]. What’s concerning is that this surge is primarily affecting young adults under 50, who play a crucial role in economic growth and societal development [10]. Despite declining rates among older adults in the past 10 years [11], CRC is now the leading cause of cancer-related deaths in men and the second leading cause in women. In the late 1990s, it was the fourth leading cause of cancer-related deaths in individuals under 50 [12]. The number of young adults dying from this cancer has been increasing by 1.3% every year, emphasizing the need for urgent action to combat this disease [13].

Colorectal cancer mortality rates differ from country to country due to variations in healthcare systems, early detection programs, lifestyles, and socioeconomic status [14, 15]. For example, in the United States, over 50,630 patients lost their lives due to CRC in 2018, ranking it second next to lung cancer [16]. In China, the number of deaths from CRC in 2020 was approximately 250,000, making up about 28.11% of all deaths [2]. Malaysia recorded that among 4,501 cases, 44.7% of deaths were attributed to colorectal cancer [17]. Sub-Saharan Africa has the highest proportion of colorectal cancer-related deaths globally [18]. This is primarily because the majority of colorectal cancers in this region are detected at advanced and late stages with limited treatment options [19,20,21]. Additionally, multiple predictors, such as patient demographics, cancer stage, histological characteristics, comorbidities, treatment modalities, lifestyles, and socioeconomic factors might be attributed to this high mortality [8, 22,23,24].

In recent times, there has been significant advancement in understanding the pathogenesis, screening, diagnosis, and treatment of CRC. Despite these improvements, CRC mortality remains high in low- and middle-income countries, including Ethiopia [25,26,27,28]. In Ethiopia, although some primary studies have reported CRC mortality rate and predictors, there is a lack of comprehensive research on the national mortality rate and contributing factors. As a result, the true mortality rates for CRC in Ethiopia remain largely unknown.

Mortality figures for colorectal cancer are primarily estimated from population-based cancer registries and vital registration sources. The establishment of such a system is crucial for acquiring accurate data on cancer trends, treatment effectiveness, and overall outcomes. Establishing and using such systems is essential for acquiring accurate data on cancer trends, treatment effectiveness, and overall health outcomes and serves as the backbone for informed decision-making in healthcare and research. Unfortunately, Ethiopia at present has only one population-based cancer registry, which covers a mere 3–5% of the total population. This registry is only confined to small urban areas, lacking comprehensive coverage of cancer statistics from rural areas or the entire nation. As well as the quality of mortality data is poor. Given the infancy stage of population-based cancer registration in Africa, including Ethiopia, individual cohort studies play a crucial role. They provide valuable insights into the cancer burden until a comprehensive national and regional cancer registry system is fully developed [29,30,31,32].

Determining the mortality rate and identifying the factors contributing to increased mortality rate among colorectal cancer patients is crucial for improving patient outcomes, personalizing treatment approaches, and guiding healthcare decision-making [33, 34]. Without concrete data, it is challenging for the government to allocate resources appropriately for CRC management compared to the support given to breast and cervical cancer management. As a result, this systematic review and meta-analysis aimed to fill the above mentioned gaps.

Methods

Reporting

The Preferred Reporting Items of Systematic Reviews and Meta-Analysis (PRISMA) checklist [35] was followed to conduct this review (Supplementary Table 1). In addition, the protocol was registered in PROSPERO with registration number CRD42024498810.

Search strategy

PubMed, EMBASE, Web of Science, Scopus, Science Direct, and Google Scholar databases were searched to identify relevant articles from December 21–30, 2023. The search terms used were “colorectal cancer,” “colorectal neoplasm,” “colorectal tumor,” “colonic neoplasm,” “colon cancer,” “rectal cancer,” “outcomes of colorectal cancer,” “mortality,” “death,” “mortality rate,” “predictors,” “determinant,” “risk factors,” and “Ethiopia.” These search terms were combined using the Boolean operators “OR” and “AND.” The search was carried out from inception until December 30, 2023. To improve the search coverage, cross-references from the bibliographies of selected studies were also searched. In addition, articles with incomplete data were accessed by contacting the corresponding author. EndNote X8 was used to import all searched records and duplicates were then eliminated.

Inclusion and exclusion criteria

This systematic review and meta-analysis encompassed the following studies: (1) primary studies that provided clear reports on either the mortality rates or predictors of colorectal cancer in Ethiopia; (2) all observational studies available electronically until December 30, 2023; (3) studies published in English language. However, studies that were expert opinions, case reports, conference presentations, articles without full access, studies that did not report the outcome of interest, and studies with methodological problems were excluded.

Data extraction

Five authors (ZBA, TMD, GMB, AGY, and TDT) independently extracted all necessary data using this format. The data extraction format included author, year of publication, sample size, follow-up year, study quality, overall mortality rate, and the selected predictors of mortality from colorectal cancer. Any disagreement while data extractions were resolved through discussion.

Quality assessment

To assess the quality of included studies, the Newcastle-Ottawa Scale (NOS) score for cohort studies was utilized as it is currently the most commonly used tool [36]. This tool consists of 3 distinct sections: selection (containing 4 items), comparison (containing 1 item), and outcome (containing 3 items). Studies were scored based on their overall scores and categorized into 3 groups: good quality (3 or 4 stars in the selection domain AND 1 or 2 stars in the comparability domain AND 2 or 3 stars in the outcome domain); fair quality (2 stars in the selection domain AND 1 or 2 stars in the comparability domain AND 2 or 3 stars in the outcome domain); and poor quality (0 or 1 star in the selection domain OR 0 star in the comparability domain OR 0 or 1 star in the outcome domain) (Supplementary Table 2). Only studies that scored five or more on the NOS were included in the analysis.

Outcome measurement

The outcome variable of the study was CRC mortality rate, which refers to the number of deaths attributed to CRC within a specific timeframe. The pooled mortality rate was calculated by dividing the total number of deaths that occurred during the follow-up period by the total number of observed patients, and then multiplying by 100.

Heterogeneity test and publication bias

Cochran Q-test and Higgins’s I2 test statistics were computed to assess heterogeneity among all studies. Accordingly, I2 results of 25%, 50%, and 75% represent low, medium, and high heterogeneity, respectively [37]. A random-effect model of analysis was used due to the high heterogeneity between studies [38]. A funnel plot and Egger’s test were used to assess publication bias at a significance level lower than 0.05 [39, 40]. The visual inspection of the funnel plot was approximately asymmetrical, suggesting publication bias (Supplementary Fig. 1). Therefore, the Egger test was used as a statistical method to assess publication bias and found p = 0.097 (statistically not significant) indicating that there was no evidence of publication bias.

Statistical analysis

The data was extracted using a Microsoft Excel spreadsheet and imported into STATA version 11 for analysis. A random effect meta-analysis model was used to estimate the pooled mortality rate. Statistical heterogeneity was evaluated by Cochran’s Q test and Higgins’s I2 statistics, with I2 values of 25%, 50%, and 75% indicating low, medium, and high heterogeneity, respectively. Subgroup analysis was performed based on factors like study year, sample size, and year of publication. Funnel plots were constructed to visually assess publication bias, with a p-value of < 0.05 indicating significant bias. Furthermore, Egger’s regression test was used to detect evidence of publication bias. A forest plot was used to present the pooled mortality rate of colorectal cancer. To identify predictors of colorectal cancer mortality, a hazard ratio for each factor was calculated. Finally, a p-value of less than 0.05 at 95% CI was used to declare statistical prediction.

Results

Selection and characteristics of the included studies

Initially, a total of 74 articles were retrieved from the PubMed, EMBASE, Web of Science, Scopus, Science Direct, and Google Scholar databases. 34 duplicates were found and removed. Of the remaining 40 articles, 21 were removed after careful examination of their titles and abstracts. Subsequently, 11 full-text articles were assessed, out of which 4 were excluded due to reasons such as poor quality, different outcomes, or failure to report the outcome of interest. Finally, a total of 7 studies that fulfilled the inclusion criteria were included in this systematic review and meta-analysis. The detailed retrieval process is shown in Fig. 1.

Fig. 1
figure 1

PRISMA flowchart diagram of the study selection

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The general characteristics of the included studies are summarized in Table 1. These studies were conducted between 2013 and 2022 and involved a total of 2,539 patients diagnosed with colorectal cancer. Six of the included studies were retrospective cohorts [32, 41,42,43,44,45] and one was a prospective cohort study [46]. The sample sizes ranged from 161 [32] to 621 [41] participants. Geographically, six studies were conducted in Addis Ababa [32, 41,42,43,44, 46], while one study was conducted in the Amhara region [45]. In the included studies, the mean age of the participants was 46.27 (SD ± 17.13) years. More than half of them (55.57%) were male, while 49.52% had colon cancer and 41.21% had stage IV cancer. About 28.05% of the participants had a history of alcohol consumption, 16.57% were smokers, and 9.97% had a family history of colorectal cancer. Nearly one-fourth (22.95%) of them had preexisting comorbidities, of which 7.17% had high blood pressure, 4.13% had diabetes mellitus and 2.5% had HIV/AIDS. The overall mortality rate among colorectal patients ranged from 27.75 [45] to 67.46 [46].

Table 1 Characteristics of included studies
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Pooled mortality and survival rate among colorectal cancer patients in Ethiopia

The overall mortality rate among colorectal cancer patients in Ethiopia was 40.5% (95% CI: 32.05%, 48.87%; I2 = 95.0%; p-value < 0.001) (Fig. 2). The pooled median follow-up time across the studies was 28.74 months, and the pooled survival rates at 1, 2, 3, 4, and 5 years were estimated to be 82.3% (95% CI: 73.33, 91.31), 63.3% (95% CI: 51.24, 75.45), 48.8% (95% CI: 43.35, 54.32), 33.1% (95% CI: 30.04, 36.22), and 26.6% (95% CI: 21.26, 31.91) respectively.

Fig. 2
figure 2

Forest plot showing the pooled mortality rate among colorectal patients in Ethiopia

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Subgroup analysis

In order to address the observed heterogeneity in the study (I2 = 95.0%), the subgroup analysis was conducted based on the study year, sample size, and year of publication. Subgroup analyses based on study year showed that the rate of death among colorectal cancer patients was higher in studies done in or after 2017 than in studies studied before 2017 (43.0% versus 38.2%). Similarly, when analyzing the results based on sample size, it was found that studies with a sample size of less than 384 had a higher mortality rate for colorectal cancer compared to studies with a sample size of 384 or more (43.9% versus 36.1%). However, significant variation was not observed in the rates of colorectal cancer deaths between studies published before or in 2021 compared to those published after 2021 (39.71% before/in 2021 versus 40.91% after 2021).

Predictors of colorectal cancer mortality

In order to identify the main predictors of mortality in patients with colorectal cancer, this systematic review and meta-analysis considered variables that were associated with the risk of mortality in two or more primary studies using a multivariable Cox regression model. Accordingly, the patient’s age, marital status, comorbidities, stage of cancer, and baseline CEA level were the most common predictors of mortality among colorectal cancer patients in Ethiopia.

Older patients, aged 70 and above, were nearly 2 times more likely to die as compared to those under 40 years old (AHR: 1.89, 95% CI: 1.27–2.82). Married CRC patients had a 2.5 times higher risk of death compared to single patients (AHR: 2.53, 95% CI: 1.79–3.57). Patients with CEA levels ≥ 5ng/mL during diagnosis had a 2.06 times higher risk of death compared to those with < 5ng/mL CEA level (AHR: 2.06, CI: 1.35–3.13). The hazard of CRC death was 84% higher in patients with comorbidities compared to those without any comorbidity (AHR: 1.84, 95% CI: 1.45–2.35). Moreover, when compared to patients diagnosed at clinical stage I, those diagnosed at stage IV had an 8.06-fold increased risk of death (AHR: 8.06, CI: 2.89–22.49) (Table 2).

Table 2 Predictors of mortality among CRC patients in Ethiopia
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Discussion

Ethiopia, as part of a low-income country, is experiencing a demographic and epidemiological transition. With rapid urbanization, changes in lifestyle, and improved life expectancy, non-communicable diseases, including colorectal cancer, are becoming more prevalent [47, 48]. However, limited resources, inadequate cancer screening programs, and challenges in early diagnosis and treatment could contribute to increased mortality rates [45, 49, 50]. Therefore, this study aimed to figure out how many patients are dying from colorectal cancer in Ethiopia and what predictors are contributing to it.

In this review, the pooled median follow-up time was 28.74 months and the pooled 1, 3, and 5-year survival rate of colorectal cancer was 82.3% (95% CI: 73.33, 91.31), 48.8% (95% CI: 43.35, 54.32) and 26.6% (95% CI: 21.26, 31.91) respectively. The 1-year survival rate of patients with CRC in our study is consistent with reviews done in different parts of the world. In Sub-Saharan Africa, the rate was 74% [51], while in Iran it was around 84–85% [52, 53]. In Eastern Mediterranean Region Countries it was 88.07% [54] and in China, it was 79% [55]. This finding was also consistent with a population-based study conducted in European countries like England, Denmark, Norway, Canada, Sweden, and Australia where the 1-year survival rate of CRC patients was 74.7%, 77.7%, 82.4%, 83.5%, 83.8%, and 84.9% respectively [56].

The 3-year survival rate for CRC patients in Ethiopia was found to be 48.8%. This rate is much lower compared to the survival rates observed in other countries such as Iran 64–65% [52, 53], Eastern Mediterranean Region Countries 70.67% [54], China 72–74% [55, 57], and Brunei Darussalam 62.5% [58]. For the 5-year survival rate, Ethiopia had a rate of 26.6%, which was again lower compared to colorectal cancer survival rates in sub-Saharan Africa 43.5% [59], Iran 52–54% [52, 53], Eastern Mediterranean region 57.26% [54], China 62–68% [55, 57], Jordan 58.2% [60], German 63.0% [61], Brazil 63.5% [62], Spain 55.5% [63] and Australia 63.3% [11]. However, the 5-year CRC survival rate in African countries such as Uganda, Ghana, and Gambia was less than 13%, 16%, and 22%, respectively [64]. This rate implies that Ethiopia and other African countries have a lot of room for improvement in terms of colorectal cancer survival rates. The reason why CRC survival rates differ could be because of a bunch of reasons like differences in patient characteristics: tobacco use [65], alcohol consumption [66], obesity [67], sedentary lifestyle [68], and comorbidity [69, 70]; dietary factors (meat vs. cereal intake) [71]; screening methods [72] and physician’s knowledge and attitudes towards screening [73, 74]. Variations in survival rates can also be brought by the stage of CRC at diagnosis [75, 76], and treatment option differences [77]. Moreover, the better survival rate in other countries compared to Ethiopia might be explained because they had more advanced cancer care and benefited from a large number of local and western-trained doctors who can provide a range of cancer treatment modalities [78].

This systematic review and meta-analysis found that the combined mortality rate for colorectal cancer patients was 40.5% (95% CI: 32.05%, 48.87%). This means that, on average, two out of every five colorectal cancer patients die from the disease. This mortality rate surpasses the national average death rate for cervical cancer, which is 16.39% [79], and lung cancer, which is only 10% [80]. However, it is noteworthy that the mortality rate was similar to Malaysia’s and other Asian countries rates of 44.7% and 52.4% for colorectal cancer mortality respectively [17, 81]. On the other hand, China [2] and Canada [82] had the lowest mortality rates for colorectal cancer, which were 28.11%, and 6% respectively. In the United States, approximately 51.3% [83] and 51.4% [84] of colorectal deaths occurred within 5 years of diagnosis. The variation in mortality rates can be explained by differences in the availability and advancement of screening, diagnostic, and treatment facilities [85]. However, the increase in mortality rates in low and middle-income countries like Ethiopia may be due to limited access to treatment options and adjunctive therapy [86], with only a small percentage of patients (1.3–3.1%) receiving radiotherapy in these countries [87]. Moreover, delays in diagnosis, referral, and treatment, along with cultural beliefs and financial constraints, may have contributed to higher mortality rates in these regions [86, 88].

This review found that elderly patients were more susceptible to death than their younger counterparts. Patients aged 70 and older were nearly 2 times more likely to die as compared to those under 40 years old (AHR: 1.89, 95% CI: 1.27–2.82). This finding is supported by a study conducted in China revealed that patients aged 70 or older had a higher risk of colorectal cancer-specific death and a reduced chance of survival [89]. It is unsurprising that younger patients exhibited a decreased mortality risk, given that they often have fewer comorbidities, a lower chance of dying from other causes, and are more likely to receive aggressive and intense treatments [90]. Once more, the elevated mortality rates among the elderly, in contrast to individuals under the age of 50, can be attributed to a heightened occurrence of cardiac complications within the older group. Grosso et al., who studied a European sample of patients, discovered that cardiovascular complications in colon cancer patients aged 65 and above were twice as prevalent as in their younger counterparts [91] and it is worth noting that cardiovascular diseases are the main cause of death among colorectal cancer patients [83].

Despite previous findings indicating that being married is associated with improved survival rates in various types of cancer, such as breast [92], colorectal [93, 94], lung [95], ovarian [96], pancreatic [97], and prostate cancer [98], our review revealed that married patients had a 2.5 times higher risk of death compared to single patients (AHR: 2.53, 95% CI: 1.79–3.57). Despite the fact that being married improved social support and had positive effects on psychological well-being, screening, diagnosis, and treatment adherence [99], it should be acknowledged that cancer outcomes are affected by a mix of biological, environmental, and social factors, regardless of marital status [100,101,102]. Furthermore, the association between married individuals and a higher likelihood of dying from colorectal cancer can be explained by the fact that marriage often involves shared lifestyle habits, such as dietary choices, physical activity levels, and tobacco use and alcohol consumption. If one partner engages in unhealthy lifestyle, it can potentially influence the other partner to adopt similar lifestyles, which could potentially increase the risk of dying from colorectal cancer. Another possible explanation could be that many individuals marry later in life, and our study identified older age as a significant predictor for higher mortality rates. Also, as age increases the likelihood of developing comorbidities increases, which our research highlights as another contributing factor. Thus, the combination of older age and greater comorbidity rates among married individuals may explain their increased susceptibility to colorectal cancer mortality. However, we advise to conduct further research to fully comprehend the exact link between marital status and colorectal cancer mortality.

Patients with CEA levels ≥ 5ng/mL during diagnosis were 2.1 times more likely to die (AHR: 2.06, CI: 1.35–3.13) compared to those with < 5ng/mL CEA level. This finding aligns with the results of the COLOFOL clinical trial conducted in 24 hospitals across Denmark, Sweden, and Uruguay [103]. Similar results were also observed by Becerra et al., who found a 62% increased hazard of death in patients with elevated CEA levels compared to those with normal levels [104]. This is likely due to the fact that a higher preoperative CEA level indicates poor treatment response, lower survival rates, advanced cancer stage, and nodal metastasis [105,106,107]. All these can contribute to an increased risk of colorectal cancer-related death.

Patients with existing comorbidities had an 84% higher hazard of death (AHR: 1.84, 95% CI: 1.45–2.35) compared to those without any comorbidity. This finding was consistent across various studies conducted in countries such as Germany, Spain, Australia, and the Netherlands [69, 108,109,110], which revealed that comorbidities like hypertension, diabetes, myocardial infarction, chronic obstructive pulmonary disease, and asthma were strong predictors of mortality in colorectal cancer patients. The reason behind this prediction could be that comorbidities affect the physical characteristics (morphology), tissue structure (histology), differentiation, and proliferation rate of colorectal cancer [111, 112]. Furthermore, they weaken the immune system and complicate the management and treatment of the disease, ultimately leading to a higher risk of death [113].

Moreover, when compared to patients diagnosed at clinical stage I, those diagnosed at stage II, III, and IV had a 4.1-fold (AHR: 4.13, 95% CI: 1.85–9.22), 8.6-fold (AHR: 8.62, 95% CI: 3.88–19.15), and 8.1-fold (AHR: 8.06, CI: 2.89–22.49) increased risk of death, respectively. This correlation between advanced stage at diagnosis and increased mortality rate and poor survival has been observed in studies conducted in Iran, England, and Malaysia [114,115,116]. This can be attributed to the fact that stage I tumors are typically small and localized in the inner layers of the colon or rectum. However, as the disease advances, tumors grow larger, invade deeper into the bowel walls, and may even spread to nearby structures [117]. This increased invasion leads to more complications and challenges in treating the cancer, eventually resulting in death.

Our meta-analysis has both strengths and limitations. One strength is that being the first study of its kind, it can provide valuable insights for program planners, policymakers, and healthcare providers involved in CRC prevention, diagnosis, and treatment. It also gives clues on the quality of healthcare provided by hospitals to CRC patients. However, several limitations to our study should be considered when interpreting the findings. Firstly, some predictor variables were only pooled from two studies, which may impact the strength of the meta-analysis. Secondly, due to the limited number of cancer centers in Ethiopia, many regions have not published studies on CRC mortality rates. As a result, certain subgroup analyses, such as analyzing mortality rates based on specific study regions, were not possible. Furthermore, there was significant heterogeneity across the included studies, possibly due to variations in follow-up periods, which ranged from 17 to 39 months. Therefore, the overall pooled mortality rate should be interpreted cautiously.

Conclusion

In Ethiopia, the mortality rate among individuals diagnosed with CRC is high, with two out of five patients dying from this disease. This has been noticed in studies published since 2017. Age, marital status, CEA level, comorbidities, and cancer stage were identified as predictors of mortality in CRC patients. Ethiopia needs to undertake various measures to lower death rates among colorectal cancer patients. This includes, early detection and screening should be prioritized, particularly for older patients, those who are married, have comorbidities, elevated CEA levels, and advanced cancer stages. Additionally, future studies need to investigate the exact association between being married and colorectal cancer mortality, along with exploring the impact of different treatment modalities on CRC mortality rates and overall patient survival.

Implications

The findings of this systematic review and meta-analysis have several implications. Firstly, it will contribute to the existing body of knowledge by providing valuable insights into mortality rates and predictors among Ethiopian colorectal cancer patients. This will benefit healthcare professionals, researchers, and policymakers by enhancing their understanding of factors that affect patient outcomes, guiding clinical decisions, and resource allocation. Also, the findings highlight areas that require further research and contribute to the development of evidence-based strategies to improve patient care and reduce mortality rates among colorectal cancer patients in Ethiopia.

Data availability

All data relating to the present study are provided within the manuscript or supplementary information files.

Abbreviations

AHR:

Adjusted Hazard Ratio

CRC:

Colorectal Cancer

CEA:

Carcinoembryonic Antigen

PRISMA:

Preferred Reporting Items for Systematic Reviews and Meta-Analyses

References

  1. Favoriti P, Carbone G, Greco M, Pirozzi F, Pirozzi REM, Corcione F. Worldwide burden of colorectal cancer: a review. Updates Surg. 2016;68:7–11.

    Article  PubMed  Google Scholar 

  2. Zhou J, Zheng R, Zhang S, Zeng H, Wang S, Chen R, Sun K, Li M, Gu J, Zhuang G. Colorectal cancer burden and trends: comparison between China and major burden countries in the world. Chin J Cancer Res. 2021;33(1):1.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Xi Y, Xu P. Global colorectal cancer burden in 2020 and projections to 2040. Translational Oncol. 2021;14(10):101174.

    Article  Google Scholar 

  4. Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, Bray F. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. Cancer J Clin. 2021;71(3):209–49.

    Article  Google Scholar 

  5. Obafemi F, Umahi-Ottah G. A review of Global Cancer Prevalence and Therapy. J Cancer Res Treat Prev. 2023;1(3):128–47.

    Google Scholar 

  6. World Health Organization: Colorectal cancer. International agency for research on cancer. (accessed January 2, 2024). https://gco.iarc.who.int/media/globocan/factsheets/cancers/8-colon-fact-sheet.pdf.

  7. Baidoun F, Elshiwy K, Elkeraie Y, Merjaneh Z, Khoudari G, Sarmini MT, Gad M, Al-Husseini M, Saad A. Colorectal cancer epidemiology: recent trends and impact on outcomes. Curr Drug Targets. 2021;22(9):998–1009.

    Article  CAS  PubMed  Google Scholar 

  8. Arnold M, Sierra MS, Laversanne M, Soerjomataram I, Jemal A, Bray F. Global patterns and trends in colorectal cancer incidence and mortality. Gut 2016:gutjnl–2015.

  9. Morgan E, Arnold M, Gini A, Lorenzoni V, Cabasag C, Laversanne M, Vignat J, Ferlay J, Murphy N, Bray F. Global burden of colorectal cancer in 2020 and 2040: incidence and mortality estimates from GLOBOCAN. Gut. 2023;72(2):338–44.

    Article  PubMed  Google Scholar 

  10. Siegel RL, Torre LA, Soerjomataram I, Hayes RB, Bray F, Weber TK, Jemal A. Global patterns and trends in colorectal cancer incidence in young adults. Gut 2019:gutjnl–2019.

  11. Karuppannan S, Kelty E, Sodhi-Berry N, Ee HC, Preen DB. Trends in incidence, mortality rates, and survival of colorectal cancer in Western Australia from 1990 to 2014: a retrospective whole-population longitudinal study. Int J Colorectal Dis. 2020;35:1719–27.

    Article  PubMed  Google Scholar 

  12. Siegel RL, Giaquinto AN, Jemal A. Cancer statistics, 2024. CA Cancer J Clin. 2024;74(1):12–49.

    Article  PubMed  Google Scholar 

  13. Siegel RL, Miller KD, Goding Sauer A, Fedewa SA, Butterly LF, Anderson JC, Cercek A, Smith RA, Jemal A. Colorectal cancer statistics, 2020. Cancer J Clin. 2020;70(3):145–64.

    Article  Google Scholar 

  14. Thatcher EJ, Camacho F, Anderson RT, Li L, Cohn WF, DeGuzman PB, Porter KJ, Zoellner JM. Spatial analysis of colorectal cancer outcomes and socioeconomic factors in Virginia. BMC Public Health. 2021;21:1–10.

    Article  Google Scholar 

  15. Douaiher J, Ravipati A, Grams B, Chowdhury S, Alatise O, Are C. Colorectal cancer—global burden, trends, and geographical variations. J Surg Oncol. 2017;115(5):619–30.

    Article  PubMed  Google Scholar 

  16. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2018. Cancer J Clin. 2018;68(1):7–30.

    Article  Google Scholar 

  17. Hassan MRA, Ismail I, Suan MAM, Ahmad F, Khazim WKW, Othman Z, Said RM, Tan WL, Rahmah S, Mohammed NS. Incidence and mortality rates of colorectal cancer in Malaysia. Epidemiol Health 2016, 38.

  18. Sharma R, Nanda M, Fronterre C, Sewagudde P, Ssentongo AE, Yenney K, Arhin ND, Oh J, Amponsah-Manu F, Ssentongo P. Mapping cancer in Africa: a comprehensive and comparable characterization of 34 cancer types using estimates from GLOBOCAN 2020. Front Public Health. 2022;10:744.

    Article  Google Scholar 

  19. Asombang AW, Madsen R, Simuyandi M, Phiri G, Bechtold M, Ibdah JA, Lishimpi K, Banda L. Descriptive analysis of colorectal cancer in Zambia, Southern Africa using the national cancer disease hospital database. Pan Afr Med J 2018, 30(1).

  20. Kebede AG, Kebede T, Atnafu A. High Magnitude Advanced Colorectal Cancer at diagnosis in Ethiopian patients: Imaging Pattern and Associated factors. Ethiop J Health Sci 2023, 33(1).

  21. Sharma A, Alatise OI, Adisa AO, Arowolo OA, Olasehinde O, Famurewa OC, Omisore AD, Komolafe A, Olaofe O, Katung AI. Treatment of colorectal cancer in Sub-saharan Africa: results from a prospective Nigerian hospital registry. J Surg Oncol. 2020;121(2):342–9.

    Article  PubMed  Google Scholar 

  22. Magaji BA, Moy FM, Roslani AC, Law CW. Survival rates and predictors of survival among colorectal cancer patients in a Malaysian tertiary hospital. BMC Cancer. 2017;17(1):1–8.

    Article  Google Scholar 

  23. Tannenbaum SL, Hernandez M, Zheng DD, Sussman DA, Lee DJ. Individual-and neighborhood-level predictors of mortality in Florida colorectal cancer patients. PLoS ONE. 2014;9(8):e106322.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Saidi H, Abdihakin M, Njihia B, Jumba G, Kiarie G, Githaiga J, Abinya N. Clinical outcomes of colorectal cancer in Kenya. Annals Afr Surg 2011, 7.

  25. Khan SZ, Lengyel CG. Challenges in the management of colorectal cancer in low-and middle-income countries. Cancer Treat Res Commun 2023:100705.

  26. Ogunwobi OO, Mahmood F, Akingboye A. Biomarkers in colorectal cancer: current research and future prospects. Int J Mol Sci. 2020;21(15):5311.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Nikolouzakis TK, Vassilopoulou L, Fragkiadaki P, Mariolis Sapsakos T, Papadakis GZ, Spandidos DA, Tsatsakis AM, Tsiaoussis J. Improving diagnosis, prognosis and prediction by using biomarkers in CRC patients. Oncol Rep. 2018;39(6):2455–72.

    CAS  PubMed  PubMed Central  Google Scholar 

  28. Deressa BT, Cihoric N, Tefesse E, Assefa M, Zemenfes D. Multidisciplinary cancer management of colorectal cancer in Tikur Anbessa Specialized Hospital, Ethiopia. J Global Oncol. 2019;5:1–7.

    Google Scholar 

  29. Bebington B, Singh E, Fabian J, Jan Kruger C, Prodehl L, Surridge D, Penny C, McNamara L, Ruff P. Design and methodology of a study on colorectal cancer in Johannesburg, South Africa. JGH Open. 2018;2(4):139–43.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Awedew AF, Asefa Z, Belay WB. National Burden and Trend of Cancer in Ethiopia, 2010–2019: a systemic analysis for global burden of disease study. Sci Rep. 2022;12(1):12736.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Memirie ST, Habtemariam MK, Asefa M, Deressa BT, Abayneh G, Tsegaye B, Abraha MW, Ababi G, Jemal A, Rebbeck TR. Estimates of cancer incidence in Ethiopia in 2015 using population-based registry data. J Global Oncol. 2018;4:1–11.

    Google Scholar 

  32. Teka MA, Yesuf A, Hussien FM, Hassen HY. Histological characteristics, survival pattern and prognostic determinants among colorectal cancer patients in Ethiopia: a retrospective cohort study. Heliyon 2021, 7(2).

  33. Aran V, Victorino AP, Thuler LC, Ferreira CG. Colorectal cancer: epidemiology, disease mechanisms and interventions to reduce onset and mortality. Clin Colorectal Cancer. 2016;15(3):195–203.

    Article  PubMed  Google Scholar 

  34. Sjoquist KM, Renfro LA, Simes RJ, Tebbutt NC, Clarke S, Seymour MT, Adams R, Maughan TS, Saltz L, Goldberg RM. Personalizing survival predictions in advanced colorectal cancer: the ARCAD nomogram project. JNCI: J Natl Cancer Inst. 2018;110(6):638–48.

    Article  PubMed  Google Scholar 

  35. Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, Shamseer L, Tetzlaff JM, Akl EA, Brennan SE. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. Int J Surg. 2021;88:105906.

    Article  PubMed  Google Scholar 

  36. Ma L-L, Wang Y-Y, Yang Z-H, Huang D, Weng H, Zeng X-T. Methodological quality (risk of bias) assessment tools for primary and secondary medical studies: what are they and which is better? Military Med Res. 2020;7:1–11.

    Article  Google Scholar 

  37. Huedo-Medina TB, Sánchez-Meca J, Marín-Martínez F, Botella J. Assessing heterogeneity in meta-analysis: Q statistic or I² index? Psychol Methods. 2006;11(2):193–206.

    Article  PubMed  Google Scholar 

  38. Higgins JP, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. BMJ. 2003;327(7414):557–60.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Rücker G, Schwarzer G, Carpenter J. Arcsine test for publication bias in meta-analyses with binary outcomes. Stat Med. 2008;27(5):746–63.

    Article  PubMed  Google Scholar 

  40. Egger M, Smith GD, Schneider M, Minder C. Bias in meta-analysis detected by a simple, graphical test. BMJ. 1997;315(7109):629–34.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Atinafu BT, Bulti FA, Demelew TM. Survival status and predictors of mortality among colorectal cancer patients in Tikur Anbessa Specialized Hospital, Addis Ababa, Ethiopia: a retrospective followup study. J cancer Prev. 2020;25(1):38.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Atinafu BT, Kebede WM, Demlew TM, Aynalem YA, Shiferaw WS, Tarekegn FN, Mulu GB. Mortality rate and its determinants among colorectal cancer patients in comprehensive specialized hospitals, Ethiopia: a retrospective cohort study. PAMJ-One Health 2022, 7(26).

  43. Etissa EK, Assefa M, Ayele BT. Prognosis of colorectal cancer in Tikur Anbessa Specialized Hospital, the only oncology center in Ethiopia. PLoS ONE. 2021;16(2):e0246424.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Getabile F, Enawgaw Y, Shibiru WG. Time to death and associated factors of Colorectal Cancer patients in Tikur Anbessa Specialized Hospital, Addis Ababa, Ethiopia. J Posit School Psychol 2022:6138–47.

  45. Tiruneh YM, Beshah DT, Wassie M. Incidence of Mortality and Associated factors among Colorectal Cancer patients at Oncology Units of Northwest Ethiopia: a retrospective cohort study. Cancer Manage Res 2022:1445–55.

  46. Zingeta GT, Worku YT, Getachew A, Feyisa JD, Furgassa H, Belay W, Mengesha T, Jemal A, Assefa M. Clinical presentation, treatment patterns, and outcomes of colorectal cancer patients at Tikur Anbessa Specialized Hospital in Addis Ababa, Ethiopia: a prospective cohort study. Cancer Rep. 2023;6(9):e1869.

    Article  Google Scholar 

  47. Donohue JF, Elborn JS, Lansberg P, Javed A, Tesfaye S, Rugo H, Duddi SRD, Jithoo N, Huang P-H, Subramaniam K. Bridging the Know-Do gaps in five non-communicable diseases using a common Framework driven by implementation science. J Healthc Leadersh 2023:103–19.

  48. Temu F, Leonhardt M, Carter J, Thiam S. Integration of non-communicable diseases in health care: tackling the double burden of disease in African settings. Pan Afr Med J 2014, 18.

  49. Haileselassie W, Mulugeta T, Tigeneh W, Kaba M, Labisso WL. The situation of cancer treatment in Ethiopia: challenges and opportunities. J cancer Prev. 2019;24(1):33.

    Article  PubMed  PubMed Central  Google Scholar 

  50. Solomon S, Mulugeta W. Diagnosis and risk factors of advanced cancers in Ethiopia. J cancer Prev. 2019;24(3):163.

    Article  PubMed  PubMed Central  Google Scholar 

  51. Hassen HY, Hussien FM, Hassen AM, Dewau R, Amsalu ET, Limenih MA, Berhe NM, Kassaw NA, Sisay BG, Manzar MD. Survival pattern of colorectal cancer in Sub-saharan Africa: a systematic review and meta-analysis. Cancer Epidemiol. 2022;81:102276.

    Article  PubMed  Google Scholar 

  52. Maajani K, Khodadost M, Fattahi A, Shahrestanaki E, Pirouzi A, Khalili F, Fattahi H. Survival rate of colorectal cancer in Iran: a systematic review and meta-analysis. Asian Pac J cancer Prevention: APJCP. 2019;20(1):13.

    Article  Google Scholar 

  53. Tahmasbi B, Abedi G, Moosazadeh M, Janbabai G, Farshidi F, Mansori K, Moradi Y, Shadmani FK, Parang S, Khazaei Z. Determining the survival rate of colorectal cancer in Iran: a systematic review and meta-analysis. Asian Pac J cancer Prevention: APJCP. 2018;19(11):3009.

    Article  Google Scholar 

  54. Nikbakht H-A, Hassanipour S, Shojaie L, Vali M, Ghaffari-Fam S, Ghelichi-Ghojogh M, Maleki Z, Arab-Zozani M, Abdzadeh E, Delam H. Survival rate of colorectal cancer in Eastern Mediterranean region countries: a systematic review and meta-analysis. Cancer Control. 2020;27(1):1073274820964146.

    Article  PubMed  PubMed Central  Google Scholar 

  55. Wang R, Lian J, Wang X, Pang X, Xu B, Tang S, Shao J, Lu H. Survival rate of colorectal cancer in China: a systematic review and meta-analysis. Front Oncol. 2023;13:1033154.

    Article  PubMed  PubMed Central  Google Scholar 

  56. Coleman M, Forman D, Bryant H, Butler J, Rachet B, Maringe C, Nur U, Tracey E, Coory M, Hatcher J. Cancer survival in Australia, Canada, Denmark, Norway, Sweden, and the UK, 1995–2007 (the International Cancer Benchmarking Partnership): an analysis of population-based cancer registry data. Lancet. 2011;377(9760):127–38.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Yuan Y, Li M-D, Hu H-G, Dong C-X, Chen J-Q, Li X-F, Li J-J, Shen H. Prognostic and survival analysis of 837 Chinese colorectal cancer patients. World J Gastroenterology: WJG. 2013;19(17):2650.

    Article  PubMed Central  Google Scholar 

  58. Lee SH, Abdul Rahman H, Abidin N, Ong SK, Leong E, Naing L. Survival of colorectal cancer patients in Brunei Darussalam: comparison between 2002–09 and 2010–17. BMC Cancer. 2021;21(1):1–15.

    Article  CAS  Google Scholar 

  59. Gullickson C, Goodman M, Joko-Fru YW, Gnangnon FHR, N’Da G, Woldegeorgis MA, Buziba NG, Karugu C, Manraj SS, Lorenzoni CF. Colorectal cancer survival in sub‐Saharan Africa by age, stage at diagnosis and Human Development Index: a population‐based registry study. Int J Cancer. 2021;149(8):1553–63.

    Article  CAS  PubMed  Google Scholar 

  60. Sharkas GF, Arqoub KH, Khader YS, Tarawneh MR, Nimri OF, Al-Zaghal MJ, Subih HS. Colorectal cancer in Jordan: survival rate and its related factors. J Oncol 2017, 2017.

  61. Májek O, Gondos A, Jansen L, Emrich K, Holleczek B, Katalinic A, Nennecke A, Eberle A, Brenner H. Survival from colorectal cancer in Germany in the early 21st century. Br J Cancer. 2012;106(11):1875–80.

    Article  PubMed  PubMed Central  Google Scholar 

  62. AGUIAR JUNIOR S, MMd OLIVEIRA, CALd MELLO, CURADO CALSAVARAVF. Survival of patients with colorectal cancer in a cancer center. Arq Gastroenterol. 2020;57:172–7.

    Article  PubMed  Google Scholar 

  63. Agüero F, Murta-Nascimento C, Gallén M, Andreu-García M, Pera M, Hernández C, Burón A, Macià F. Colorectal cancer survival: results from a hospital-based cancer registry. Rev Esp Enferm Dig. 2012;104(11):572–7.

    Article  PubMed  Google Scholar 

  64. Sankaranarayanan R, Swaminathan R, Jayant K, Brenner H. An overview of cancer survival in Africa, Asia, the Caribbean and Central America: the case for investment in cancer health services. IARC Sci Publ. 2011;162(162):257–91.

    Google Scholar 

  65. Walter V, Jansen L, Hoffmeister M, Brenner H. Smoking and survival of colorectal cancer patients: systematic review and meta-analysis. Ann Oncol. 2014;25(8):1517–25.

    Article  CAS  PubMed  Google Scholar 

  66. Kim Y, Je Y, Giovannucci EL. Association between alcohol consumption and survival in colorectal cancer: a meta-analysis. Cancer Epidemiol Biomarkers Prev. 2019;28(11):1891–901.

    Article  PubMed  Google Scholar 

  67. Lee J, Meyerhardt JA, Giovannucci E, Jeon JY. Association between body mass index and prognosis of colorectal cancer: a meta-analysis of prospective cohort studies. PLoS ONE. 2015;10(3):e0120706.

    Article  PubMed  PubMed Central  Google Scholar 

  68. Je Y, Jeon JY, Giovannucci EL, Meyerhardt JA. Association between physical activity and mortality in colorectal cancer: a meta-analysis of prospective cohort studies. Int J Cancer. 2013;133(8):1905–13.

    Article  CAS  PubMed  Google Scholar 

  69. Boakye D, Rillmann B, Walter V, Jansen L, Hoffmeister M, Brenner H. Impact of comorbidity and frailty on prognosis in colorectal cancer patients: a systematic review and meta-analysis. Cancer Treat Rev. 2018;64:30–9.

    Article  PubMed  Google Scholar 

  70. Erichsen R, Horváth-Puhó E, Iversen H, Lash L, Sørensen T. Does comorbidity interact with colorectal cancer to increase mortality? A nationwide population-based cohort study. Br J Cancer. 2013;109(7):2005–13.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. van Meer S, Leufkens AM, Bueno-de-Mesquita HB, van Duijnhoven FJ, van Oijen MG, Siersema PD. Role of dietary factors in survival and mortality in colorectal cancer: a systematic review. Nutr Rev. 2013;71(9):631–41.

    Article  PubMed  Google Scholar 

  72. Zheng S, Schrijvers JJ, Greuter MJ, Kats-Ugurlu G, Lu W, de Bock GH. Effectiveness of Colorectal Cancer (CRC) screening on all-cause and CRC-Specific Mortality reduction: a systematic review and Meta-analysis. Cancers. 2023;15(7):1948.

    Article  PubMed  PubMed Central  Google Scholar 

  73. Li X, Zhou Y, Luo Z, Gu Ya, Chen Y, Yang C, Wang J, Xiao S, Sun Q, Qian M. The impact of screening on the survival of colorectal cancer in Shanghai, China: a population based study. BMC Public Health. 2019;19(1):1–9.

    Article  Google Scholar 

  74. Ooi CY, Hanafi NS, Liew SM. Knowledge and practice of colorectal cancer screening in an urban setting: cross-sectional survey of primary care physicians in government clinics in Malaysia. Singapore Med J. 2019;60(11):596.

    Article  PubMed  PubMed Central  Google Scholar 

  75. Institute NC. Surveillance, epidemiology, and end results (SEER) program. Cancer Statistics, SEER Data & Software, Registry Operations 2018.

  76. Rawla P, Sunkara T, Barsouk A. Epidemiology of colorectal cancer: incidence, mortality, survival, and risk factors. Gastroenterol Review/Przegląd Gastroenterologiczny. 2019;14(2):89–103.

    CAS  PubMed  Google Scholar 

  77. Maimard Y, Woradet S, Chaimay B. Factors associated with mortality among patients with colorectal cancer at the secondary care hospital in Southern Thailand: hospital-based retrospective cohort study. Int J Prev Med 2023, 14.

  78. Abdel-Razeq H, Attiga F, Mansour A. Cancer care in Jordan. Hematol Oncol Stem Cell Ther. 2015;8(2):64–70.

    Article  PubMed  Google Scholar 

  79. Hambisa HD, Asfaha BT, Ambisa B, Gudeta A. Common Predictors of cervical cancer related mortality in Ethiopia. A systematic review and Meta-analysis. 2023.

  80. Tesfaw LM, Dessie ZG, Fenta HM. Lung cancer mortality and associated predictors: systematic review using 32 scientific research findings. Front Oncol 2023, 13.

  81. Onyoh EF, Hsu W-F, Chang L-C, Lee Y-C, Wu M-S, Chiu H-M. The rise of colorectal cancer in Asia: epidemiology, screening, and management. Curr Gastroenterol Rep. 2019;21:1–10.

    Article  Google Scholar 

  82. Yu Y, Carey M, Pollett W, Green J, Dicks E, Parfrey P, Yilmaz YE, Savas S. The long-term survival characteristics of a cohort of colorectal cancer patients and baseline variables associated with survival outcomes with or without time-varying effects. BMC Med. 2019;17(1):1–12.

    Article  Google Scholar 

  83. Chen J, Zheng Y, Wang H, Zhang D, Zhao L, Yu D, Lin Z, Zhang T. Cause of death among patients with colorectal cancer: a population-based study in the United States. Aging. 2020;12(22):22927.

    CAS  PubMed  PubMed Central  Google Scholar 

  84. Afifi AM, Elmehrath AO, Ruhban IA, Saad AM, Gad MM, Al-Husseini MJ, Bekaii-Saab T, Sonbol MB. Causes of death following nonmetastatic colorectal cancer diagnosis in the US: a population-based analysis. Oncologist. 2021;26(9):733–9.

    Article  PubMed  PubMed Central  Google Scholar 

  85. Pacini A, Stickland A, Iniguez K, Di Malta G. Implementation of home practice support strategies for older adults attending an online mindfulness based cognitive therapy course: an adaptive intervention protocol. 2023.

  86. Kingham TP, Alatise OI, Vanderpuye V, Casper C, Abantanga FA, Kamara TB, Olopade OI, Habeebu M, Abdulkareem FB, Denny L. Treatment of cancer in sub-saharan Africa. Lancet Oncol. 2013;14(4):e158–67.

    Article  PubMed  Google Scholar 

  87. Barton MB, Frommer M, Shafiq J. Role of radiotherapy in cancer control in low-income and middle-income countries. Lancet Oncol. 2006;7(7):584–95.

    Article  PubMed  Google Scholar 

  88. Goss PE, Lee BL, Badovinac-Crnjevic T, Strasser-Weippl K, Chavarri-Guerra Y, St Louis J, Villarreal-Garza C, Unger-Saldaña K, Ferreyra M, Debiasi M. Planning cancer control in Latin America and the Caribbean. Lancet Oncol. 2013;14(5):391–436.

    Article  PubMed  Google Scholar 

  89. Fu J, Ruan H, Zheng H, Cai C, Zhou S, Wang Q, Chen W, Fu W, Du J. Impact of old age on resectable colorectal cancer outcomes. PeerJ. 2019;7:e6350.

    Article  PubMed  PubMed Central  Google Scholar 

  90. Berian JR, Benson AB, Nelson H. Young age and aggressive treatment in colon cancer. JAMA. 2015;314(6):613–4.

    Article  CAS  PubMed  Google Scholar 

  91. Grosso G, Biondi A, Marventano S, Mistretta A, Calabrese G, Basile F. Major postoperative complications and survival for colon cancer elderly patients. BMC Surg. 2012;12:1–5.

    Article  Google Scholar 

  92. Liu Y-l, Wang D-w, Yang Z-c, Ma R, Li Z, Suo W, Zhao Z, Li Z-w. Marital status is an independent prognostic factor in inflammatory breast cancer patients: an analysis of the surveillance, epidemiology, and end results database. Breast Cancer Res Treat. 2019;178:379–88.

    Article  PubMed  PubMed Central  Google Scholar 

  93. Feng Y, Dai W, Li Y, Mo S, Li Q, Cai S. The effect of marital status by age on patients with colorectal cancer over the past decades: a SEER-based analysis. Int J Colorectal Dis. 2018;33:1001–10.

    Article  PubMed  Google Scholar 

  94. Wang L, Wilson SE, Stewart DB, Hollenbeak CS. Marital status and colon cancer outcomes in US Surveillance, Epidemiology and End results registries: does marriage affect cancer survival by gender and stage? Cancer Epidemiol. 2011;35(5):417–22.

    Article  PubMed  Google Scholar 

  95. Wu Y, Ai Z, Xu G. Marital status and survival in patients with non-small cell lung cancer: an analysis of 70006 patients in the SEER database. Oncotarget. 2017;8(61):103518.

    Article  PubMed  PubMed Central  Google Scholar 

  96. Gardner AB, Sanders B, Mann AK, Liao C-I, Kapp DS, Chan JK. The association of marital status, socioeconomic status, and race on the survival of ovarian cancer patients. In.: American Society of Clinical Oncology; 2019.

  97. Zhou H, Zhang Y, Song Y, Tan W, Qiu Z, Li S, Chen Q, Gao S. Marital status is an independent prognostic factor for pancreatic neuroendocrine tumors patients: an analysis of the Surveillance, Epidemiology, and end results (SEER) database. Clin Res Hepatol Gastroenterol. 2017;41(4):476–86.

    Article  PubMed  Google Scholar 

  98. Khan S, Nepple KG, Kibel AS, Sandhu G, Kallogjeri D, Strope S, Grubb R, Wolin KY, Sutcliffe S. The association of marital status and mortality among men with early-stage prostate cancer treated with radical prostatectomy: insight into post-prostatectomy survival strategies. Cancer Causes Control. 2019;30:871–6.

    Article  PubMed  PubMed Central  Google Scholar 

  99. Gram MA, Therkildsen C, Clarke RB, Andersen KK, Mørch LS, Tybjerg AJ. The influence of marital status and partner concordance on participation in colorectal cancer screening. Eur J Pub Health. 2021;31(2):340–6.

    Article  Google Scholar 

  100. McDaniel JT, Nuhu K, Ruiz J, Alorbi G. Social determinants of cancer incidence and mortality around the world: an ecological study. Global Health Promotion. 2019;26(1):41–9.

    Article  PubMed  Google Scholar 

  101. Jochum F, Hamy A-S, Gougis P, Dumas É, Grandal B, Laas E, Feron J-G, Gaillard T, Girard N, Pauly L. Effects of gender and socio-environmental factors on health-care access in oncology: a comprehensive, nationwide study in France. Eclinicalmedicine 2023, 65.

  102. Freedman JA, Al Abo M, Allen TA, Piwarski SA, Wegermann K, Patierno SR. Biological aspects of cancer health disparities. Annu Rev Med. 2021;72:229–41.

    Article  CAS  PubMed  Google Scholar 

  103. Egenvall M, Martling A, Veres K, Horváth-Puhó E, Wille-Jørgensen P, Petersen SH, Laurberg S, Sørensen HT, Syk I, Andersen PV. No benefit of more intense follow-up after surgery for colorectal cancer in the risk group with elevated CEA levels–An analysis within the COLOFOL randomized clinical trial. Eur J Surg Oncol. 2021;47(8):2053–9.

    Article  PubMed  Google Scholar 

  104. Becerra AZ, Probst CP, Tejani MA, Aquina CT, González MG, Hensley BJ, Noyes K, Monson JR, Fleming FJ. Evaluating the prognostic role of elevated preoperative carcinoembryonic antigen levels in colon cancer patients: results from the national cancer database. Ann Surg Oncol. 2016;23:1554–61.

    Article  PubMed  Google Scholar 

  105. Hall C, Clarke L, Pal A, Buchwald P, Eglinton T, Wakeman C, Frizelle F. A review of the role of carcinoembryonic antigen in clinical practice. Annals Coloproctology. 2019;35(6):294.

    Article  Google Scholar 

  106. Li Destri G, Rubino AS, Latino R, Giannone F, Lanteri R, Scilletta B, Di Cataldo A. Preoperative carcinoembryonic antigen and prognosis of colorectal cancer. An independent prognostic factor still reliable. Int Surg. 2015;100(4):617–25.

    Article  PubMed  PubMed Central  Google Scholar 

  107. Baqar AR, Wilkins S, Staples M, Lee CHA, Oliva K, McMurrick P. The role of preoperative CEA in the management of colorectal cancer: a cohort study from two cancer centres. Int J Surg. 2019;64:10–5.

    Article  PubMed  Google Scholar 

  108. Luque-Fernandez MA, Gonçalves K, Salamanca-Fernández E, Redondo-Sanchez D, Lee SF, Rodríguez-Barranco M, Carmona-García MC, Marcos-Gragera R, Sánchez M-J. Multimorbidity and short-term overall mortality among colorectal cancer patients in Spain: a population-based cohort study. Eur J Cancer. 2020;129:4–14.

    Article  PubMed  Google Scholar 

  109. Pule ML, Buckley E, Niyonsenga T, Roder D. The effects of comorbidity on colorectal cancer mortality in an Australian cancer population. Sci Rep. 2019;9(1):8580.

    Article  PubMed  PubMed Central  Google Scholar 

  110. van den Bosch T, Warps A-LK, tot Babberich MPN, Stamm C, Geerts BF, Vermeulen L, Wouters MW, Dekker JWT, Tollenaar RA, Tanis PJ. Predictors of 30-day mortality among Dutch patients undergoing colorectal cancer surgery, 2011–2016. JAMA Netw open. 2021;4(4):e217737–217737.

    Article  PubMed  PubMed Central  Google Scholar 

  111. Panigrahi G, Ambs S. How comorbidities shape cancer biology and survival. Trends cancer. 2021;7(6):488–95.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  112. Søgaard M, Thomsen RW, Bossen KS, Sørensen HT, Nørgaard M. The impact of comorbidity on cancer survival: a review. Clin Epidemiol. 2013;5(sup1):3–29.

    Article  PubMed  PubMed Central  Google Scholar 

  113. Michalopoulou E, Matthes KL, Karavasiloglou N, Wanner M, Limam M, Korol D, Held L, Rohrmann S. Impact of comorbidities at diagnosis on the 10-year colorectal cancer net survival: a population-based study. Cancer Epidemiol. 2021;73:101962.

    Article  PubMed  Google Scholar 

  114. Ahmadi A, Mosavi-Jarrahi A, Pourhoseingholi MA. Mortality determinants in colorectal cancer patients at different grades: a prospective, cohort study in Iran. Asian Pac J Cancer Prev. 2015;16(3):1069–72.

    Article  PubMed  Google Scholar 

  115. McPhail S, Johnson S, Greenberg D, Peake M, Rous B. Stage at diagnosis and early mortality from cancer in England. Br J Cancer. 2015;112(1):S108–15.

    Article  PubMed  PubMed Central  Google Scholar 

  116. Muhamad NA, Ma’amor NH, Rosli IA, Leman FN, Mutalip MHA, Chan H-K, Yusof SN, Tamin NSI, Aris T, Lai NM. Colorectal cancer survival among Malaysia population: data from the Malaysian National Cancer Registry. Front Oncol 2023, 13.

  117. Maurie Markman. Colorectal cancer stages. [(accessed on 28 December 2023)]. Available online: https://www.cancercenter.com/cancer-types/colorectal-cancer/stages.

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Acknowledgements

The authors would like to thank all authors of the primary studies that are included in this systematic review and meta-analysis.

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Authors and Affiliations

  1. Department of Nursing, College of Medicine and Health Sciences, Injibara University, Injibara, Ethiopia

    Zewdu Bishaw Aynalem, Abebaw Bires Adal & Temesgien Fentahun Ayele

  2. Department of Environmental Health, College of Medicine and Health Sciences, Injibara University, Injibara, Ethiopia

    Gashaw Melkie Bayeh & Almaw Genet Yeshiwas

  3. Department of Public Health, College of Medicine and Health Sciences, Injibara University, Injibara, Ethiopia

    Tadesse Miretie Dessie & Tilahun Degu Tsega

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ZBA conceived the idea and participated in data extraction and statistical analysis, and drafted the manuscript. TMD, GMB, AGY and TDT participated in the data extraction, analysis, preparation of the manuscript, and revision. ABA and TFA participated in reviewing and editing the manuscript. All authors read and approved the final manuscript.

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Aynalem, Z.B., Adal, A.B., Ayele, T.F. et al. Mortality rate and predictors of colorectal cancer patients in Ethiopia: a systematic review and meta-analysis. BMC Cancer 24, 821 (2024). https://doi.org/10.1186/s12885-024-12597-9

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  • DOI: https://doi.org/10.1186/s12885-024-12597-9

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BMC Cancer

ISSN: 1471-2407

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