Immunohistochemical biomarkers and overall survival in breast cancer: a real-world cohort from Morocco

Immunohistochemical biomarkers and overall survival in breast cancer: a real-world cohort from Morocco | 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 Immunohistochemical biomarkers and overall survival in breast cancer: a real-world cohort from Morocco Rim Alami, Reyzane El Mjabber, Omar Alami, Reda Alami, Asmaa Naim, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8378544/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Background Breast cancer is the most common malignancy among women worldwide, with marked disparities in survival outcomes across regions (1). In many low- and middle-income countries, immunohistochemistry remains the cornerstone for tumor biological characterization. This study aimed to evaluate overall survival according to routinely assessed immunohistochemical biomarkers and surrogate molecular subtypes in a large real-world cohort from Morocco. Methods This retrospective monocentric cohort study included 623 patients with invasive breast cancer diagnosed in 2014 at a tertiary referral center in Casablanca. Data on age, estrogen receptor (ER), progesterone receptor (PR), HER2 status, Ki-67 proliferation index, molecular subtype, vital status, and date of death were collected. Overall survival was estimated using the Kaplan–Meier method and compared using the log-rank test. Results At five years, vital status was available for 560 patients. Overall survival at five years was 77.5%. Hormone receptor–positive tumors were associated with significantly improved overall survival compared with hormone receptor–negative tumors (p < 0.0001). High Ki-67 (≥ 14%) was associated with poorer survival (p = 0.0038). Overall survival differed significantly according to triple-negative status, with triple-negative tumors exhibiting the worst outcomes. Conclusions Routinely assessed immunohistochemical biomarkers retain strong prognostic value for overall survival in breast cancer. These real-world data provide important population-specific benchmarks and support the continued use of immunohistochemistry for prognostic stratification in resource-constrained settings. Breast cancer Immunohistochemistry Overall survival Prognosis Triple-negative breast cancer Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 INTRODUCTION Breast cancer is the most commonly diagnosed malignancy among women worldwide and remains a leading cause of cancer-related mortality. According to global estimates from the GLOBOCAN project, breast cancer represents the first cancer in incidence and mortality among women, accounting for a substantial proportion of the global cancer burden (1). Despite major improvements in survival in high-income countries over recent decades, important disparities persist across regions, reflecting differences in early detection, access to care, and healthcare system resources. Beyond traditional clinicopathological parameters, tumor biology is a key determinant of prognosis in breast cancer. Advances in molecular profiling have identified biologically distinct subtypes associated with different clinical behaviors and survival outcomes. However, genomic assays remain costly and are not routinely available in many low- and middle-income countries (LMICs). In this context, immunohistochemistry (IHC) continues to represent the cornerstone of tumor biological characterization in routine clinical practice, providing essential prognostic and predictive information through widely accessible biomarkers (2). Immunohistochemical markers, including estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), and the proliferation index Ki-67, allow the classification of breast cancer into surrogate molecular subtypes such as luminal A, luminal B, HER2-enriched, and triple-negative tumors. These IHC-defined subtypes have been consistently shown to be associated with distinct survival patterns in large population-based studies and real-world cohorts, supporting their relevance as pragmatic prognostic tools in settings where genomic profiling is not routinely feasible (3). Among these biomarkers, Ki-67 reflects tumor proliferative activity and has been widely investigated as a prognostic factor in invasive breast cancer. Higher Ki-67 expression has been associated with more aggressive tumor behavior and poorer survival outcomes, further supporting its integration into routine pathological assessment despite ongoing debates regarding optimal cut-off values (4). In Morocco, breast cancer is the most frequent cancer among women and is often diagnosed at a relatively younger age compared with Western populations. Although several studies have described the distribution of immunohistochemical subtypes in Moroccan patients, large real-world cohorts evaluating long-term survival outcomes according to tumor biological characteristics remain limited, particularly in North African settings (5). Generating population-specific survival data based on routinely assessed biomarkers is therefore essential to better understand prognosis and to establish regional benchmarks. The present study aimed to evaluate overall survival according to immunohistochemical biomarkers and surrogate molecular subtypes in a large retrospective cohort of breast cancer patients treated at a tertiary referral center in Casablanca, Morocco. By focusing on routinely available biological markers, this study provides real-world prognostic data that may serve as a baseline for future improvements in breast cancer outcomes in similar resource-constrained settings. MATERIALS AND METHODS Study design and setting This was a retrospective, monocentric cohort study conducted at the Mohammed VI Cancer Treatment Center, Ibn Rochd University Hospital, Casablanca, Morocco. The study was designed to evaluate the prognostic value of routinely assessed immunohistochemical biomarkers on overall survival in breast cancer patients, using real-world data. Study population All patients with a histologically confirmed diagnosis of invasive breast carcinoma between January 1 and December 31, 2014, were eligible for inclusion. Patients with non-invasive breast tumors, metastatic tumors from non-breast primary sites, or recurrent breast cancer at diagnosis were excluded. A total of 623 patients met the inclusion criteria and constituted the final study cohort. Data collection Clinical and pathological data were extracted from institutional medical records and archived pathology reports. Collected variables included age at diagnosis, estrogen receptor (ER) status, progesterone receptor (PR) status, HER2 status, Ki-67 proliferation index (when available), date of diagnosis, vital status, and date of death when applicable. Vital status at five years was obtained from medical records and, when necessary, by telephone contact with patients or their relatives. Immunohistochemical assessment and biomarker definitions ER and PR status were assessed by immunohistochemistry (IHC) and reported as positive or negative according to contemporaneous international recommendations. HER2 status was evaluated by IHC, with equivocal cases further assessed by in situ hybridization when available, following standard practice guidelines (6). Ki-67 was reported as the percentage of positively stained tumor cell nuclei and categorized using a 14% cut-off, in line with international consensus recommendations during the study period (7,8). Based on IHC results, tumors were classified into surrogate molecular subtypes as follows: luminal A (ER and/or PR positive, HER2 negative), luminal B (ER and/or PR positive with either HER2 positivity or high Ki-67), HER2-enriched (ER and PR negative, HER2 positive), and triple-negative (ER, PR, and HER2 negative), according to established surrogate definitions (8,9). Outcome definition Outcome definition The primary outcome was overall survival (OS), defined as the time from the date of breast cancer diagnosis to death from any cause. Patients alive at the end of follow-up were censored at the date of last contact. Statistical analysis Continuous variables were summarized using means and ranges, while categorical variables were described using frequencies and percentages. Overall survival was estimated using the Kaplan–Meier method, and survival curves were compared using the log-rank test (10). Statistical significance was defined as a two-sided p-value < 0.05. All analyses were performed using standard statistical software. Ethical considerations The study was approved by the local ethics committee of Ibn Rochd University Hospital, Casablanca. Given the retrospective nature of the study and the use of anonymized routinely collected data, the requirement for informed consent was waived. RESULTS Patient characteristics A total of 623 patients with invasive breast carcinoma diagnosed in 2014 were included in the analysis. The mean age at diagnosis was 51 years (range: 17–91 years). Baseline clinicopathological characteristics of the study population are summarized in Table 1 . Hormone receptor status was available for the majority of patients: estrogen and/or progesterone receptors were positive in 383 cases (61.5%) and negative in 194 cases (31.1%), while data were missing for 46 patients (7.4%). HER2 status was positive in 148 tumors (23.8%), negative in 387 (62.1%), and unavailable in 88 cases (14.1%). Ki-67 proliferation index was available for 301 tumors (48.3% of the cohort). Among the entire study population, 151 tumors (24.2%) had a Ki-67 ≥ 14%, 150 (24.1%) had a Ki-67 < 14%, while Ki-67 status was missing in 322 cases (51.7%). Based on immunohistochemical results, tumors were classified into surrogate molecular subtypes in cases with complete data (Table 1 ). The molecular subtype could not be determined in 88 patients due to missing biomarker data. Table 1 Baseline characteristics of the study population. Baseline demographic and tumor biological characteristics of the 623 patients included in the study, including age at diagnosis, hormone receptor status, HER2 status, Ki-67 proliferation index, and surrogate immunohistochemical molecular subtypes. Variable n (%) Age at diagnosis Mean age (years) 51 Range (years) 17–91 Age group 65 years 63 (10.1%) Hormone receptor status Positive 383 (61.5%) Negative 194 (31.1%) Missing 46 (7.4%) HER2 status Positive 148 (23.8%) Negative 387 (62.1%) Missing 88 (14.1%) Ki-67 proliferation index < 14% 150 (24.1%) ≥ 14% 151 (24.2%) Missing 322 (51.7%) Molecular subtype Luminal A 279 (44.8%) Luminal B 104 (16.7%) HER2-like 148 (23.8%) Triple-negative 100 (16.1%) Not determined 88 (14.1%) Data are presented as number (percentage) unless otherwise indicated. Percentages may not total 100% due to missing data. The number of patients with missing data for each variable is reported. Overall survival Vital status at five years was available for 560 patients (89.9% of the cohort). At the end of follow-up, 125 deaths were recorded. The estimated overall survival rates were 97.3% at 1 year, 88.4% at 3 years, and 77.5% at 5 years. The Kaplan–Meier curve for overall survival of the entire cohort is shown in Fig. 1 . Kaplan–Meier curve showing overall survival of the entire cohort. Overall survival was defined as the time from date of breast cancer diagnosis to death from any cause. Shaded areas represent the 95% confidence intervals. Time is expressed in months. Overall survival according to age Patients were categorized into three age groups: 65 years (10.1%). Overall survival differed significantly across age groups (log-rank p = 0.043). Five-year overall survival rates were 76.2% in patients 65 years (Figure 2 ). Kaplan–Meier curves showing overall survival stratified by age at diagnosis ( 65 years). Survival curves were compared using the log-rank test. Time is expressed in months. Overall survival according to hormone receptor status Hormone receptor–positive tumors were associated with significantly improved overall survival compared with hormone receptor–negative tumors (log-rank p < 0.0001). Five-year overall survival was 85.8% in patients with hormone receptor–positive tumors versus 68.8% in those with hormone receptor–negative tumors (Fig. 3 ). Kaplan–Meier curves comparing overall survival between patients with hormone receptor–positive (estrogen and/or progesterone receptor positive) and hormone receptor–negative tumors. Survival curves were compared using the log-rank test. Time is expressed in months. Overall survival according to HER2 status No significant difference in overall survival was observed according to HER2 status (log-rank p = 0.23). Five-year overall survival rates were 81.7% in patients with HER2-positive tumors and 78.0% in those with HER2-negative tumors (Fig. 4 ). Kaplan–Meier curves comparing overall survival between patients with HER2-positive and HER2-negative tumors. Survival curves were compared using the log-rank test. Time is expressed in months. Overall survival according to Ki-67 proliferation index Among patients with available Ki-67 data, those with a Ki-67 ≥ 14% had significantly worse overall survival compared with patients with Ki-67 < 14% (log-rank p = 0.0038). Five-year overall survival rates were 72.5% and 86.7%, respectively (Fig. 5 ). Kaplan–Meier curves comparing overall survival between tumors with Ki-67 < 14% and Ki-67 ≥ 14%. Survival curves were compared using the log-rank test. Time is expressed in months. Overall survival in triple-negative versus non–triple-negative breast cancer Patients with triple-negative (basal-like) tumors exhibited the poorest survival outcomes, with a five-year overall survival rate of 63.8%, compared with 82.8% in patients with non-triple-negative tumors (Fig. 6 ). Kaplan–Meier curves comparing overall survival between patients with triple-negative tumors and those with non–triple-negative tumors. Survival curves were compared using the log-rank test. Time is expressed in months. DISCUSSION In this large real-world cohort of breast cancer patients treated at a tertiary referral center in Morocco, overall survival differed significantly according to routinely assessed immunohistochemical biomarkers. Hormone receptor status, Ki-67 proliferation index, and surrogate molecular subtypes were strongly associated with overall survival, supporting the prognostic relevance of tumor biological characteristics assessed by immunohistochemistry. Hormone receptor positivity was associated with significantly improved overall survival, consistent with findings from large population-based studies showing more favorable outcomes in estrogen and/or progesterone receptor–positive tumors compared with receptor-negative disease (3). This observation reinforces the central prognostic role of hormone receptor expression, even in settings where detailed staging and treatment data are not available. Triple-negative (basal-like) tumors exhibited the poorest survival outcomes in our cohort, in line with international data reporting aggressive clinical behavior and inferior prognosis for this subtype (3). Conversely, patients with luminal subtypes demonstrated more favorable survival patterns. Although direct comparisons with high-income country cohorts should be interpreted cautiously, the relative survival differences between subtypes observed in our study are broadly consistent with previously published reports. A high Ki-67 proliferation index was associated with worse overall survival. This finding aligns with prior studies and expert consensus highlighting Ki-67 as a marker of tumor aggressiveness and adverse prognosis in invasive breast cancer, despite ongoing variability in assessment and cut-off values (4,7). The prognostic value of Ki-67 observed in our real-world cohort supports its continued use as a pragmatic biomarker in routine clinical practice. Data on breast cancer outcomes in North African populations remain limited. Previous studies from Morocco have primarily focused on the distribution of immunohistochemical subtypes rather than long-term survival outcomes (5). By providing five-year overall survival estimates according to tumor biological characteristics, the present study contributes population-specific data that may serve as a benchmark for future evaluations of breast cancer outcomes in similar settings. Several limitations should be acknowledged. The retrospective design and the absence of tumor stage and treatment-related variables preclude adjustment for these potentially important prognostic factors. Additionally, missing data for some biomarkers, particularly Ki-67, may have introduced selection bias. However, the study deliberately focused on routinely available biological markers to reflect real-world diagnostic practice. Despite these limitations, the strengths of this study include its large sample size, robust follow-up, and focus on immunohistochemical biomarkers that are widely accessible in resource-constrained settings. These findings underscore the prognostic importance of tumor biology assessed by immunohistochemistry and provide valuable real-world survival data from a North African tertiary care center. CONCLUSION In this large real-world cohort of breast cancer patients from a North African tertiary center, routinely assessed immunohistochemical biomarkers were strongly associated with overall survival. Hormone receptor status, Ki-67 proliferation index, and surrogate molecular subtypes provided meaningful prognostic stratification despite the absence of detailed staging and treatment data. These findings highlight the continued relevance of immunohistochemistry as a pragmatic prognostic tool in resource-constrained settings and provide population-specific survival benchmarks for future outcome evaluations. Declarations Ethics approval and consent to participate The study was approved by the local ethics committee of Ibn Rochd University Hospital, Casablanca. Given the retrospective nature of the study and the use of anonymized data, informed consent was waived. Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests. Funding The authors received no specific funding for this study. Author Contribution RA contributed to the study conception and design, data collection, interpretation of the data, and drafting of the manuscript.EMR and NA contributed to data collection and validation of clinical and pathological data.BK performed the statistical analysis and contributed to interpretation of the results.AO and AR contributed to data interpretation and critical revision of the manuscript.BN and BA contributed to critical revision of the manuscript for important intellectual content, supervised the study, contributed to study design and interpretation of the data, and critically revised the manuscript.All authors read and approved the final manuscript and agree to be accountable for all aspects of the work. Acknowledgements The authors thank the medical and pathology staff of the Mohammed VI Cancer Treatment Center for their support. References Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2021;71(3):209–249. doi:10.3322/caac.21660. Colomer R, Sola M, Llombart-Cussac A, et al. Biomarkers in breast cancer: an updated consensus statement. Breast Cancer Res Treat. 2024;195(1):1–15. doi:10.1007/s10549-024-07215-7. Parise CA, Caggiano V. Breast cancer survival defined by the ER/PR/HER2 subtypes. PLoS One. 2014;9(3):e91188. doi:10.1371/journal.pone.0091188. Davey MG, Ryan EJ, McAnena PF, et al. The role of Ki-67 as a prognostic biomarker in invasive breast cancer. Cancers (Basel). 2021;13(3):445. doi:10.3390/cancers13030445. El Idrissi Errahhali M, Ouarzane M, El Fakir S, et al. Molecular subtypes of breast cancer and their clinicopathological associations in Eastern Morocco. Pan Afr Med J. 2017;28:112. doi:10.11604/pamj.2017.28.112.12415. Wolff AC, Hammond MEH, Allison KH, Harvey BE, Mangu PB, Bartlett JMS, et al. Human epidermal growth factor receptor 2 testing in breast cancer: American Society of Clinical Oncology/College of American Pathologists clinical practice guideline update. J Clin Oncol. 2018;36(20):2105–2122. doi:10.1200/JCO.2018.77.8738. Dowsett M, Nielsen TO, A’Hern R, Bartlett J, Coombes RC, Cuzick J, et al. Assessment of Ki-67 in breast cancer: recommendations from the International Ki-67 in Breast Cancer Working Group. J Natl Cancer Inst. 2011;103(22):1656–1664. doi:10.1093/jnci/djr393. Goldhirsch A, Wood WC, Coates AS, Gelber RD, Thürlimann B, Senn HJ. Strategies for subtypes—dealing with the diversity of breast cancer: highlights of the St Gallen International Expert Consensus on the primary therapy of early breast cancer 2011. Ann Oncol. 2011;22(8):1736–1747. doi:10.1093/annonc/mdr304. Parise CA, Caggiano V. Survival outcomes for breast cancer defined by the ER/PR/HER2 subtypes. PLoS One. 2014;9(3):e91188. doi:10.1371/journal.pone.0091188. Kaplan EL, Meier P. Nonparametric estimation from incomplete observations. J Am Stat Assoc. 1958;53(282):457–481. doi:10.1080/01621459.1958.10501452. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 25 Feb, 2026 Reviewers agreed at journal 24 Feb, 2026 Reviewers invited by journal 24 Feb, 2026 Editor invited by journal 22 Dec, 2025 Editor assigned by journal 17 Dec, 2025 Submission checks completed at journal 17 Dec, 2025 First submitted to journal 16 Dec, 2025 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. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8378544","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":596901120,"identity":"394935dd-512e-4dfd-ab8f-4d527a68e150","order_by":0,"name":"Rim Alami","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+0lEQVRIiWNgGAWjYDACZhBRwMDAxt588EFCBUiEuYEILQZALTzHkg0enAGJMBLQwgDVwiDhYyb5sA3EI6DFvJ07geGHgV00nwSPmUTivNpo/naglh8V23BqkTnMu4GxxyA5t026rdgicdvx3BmHGRsYe87cxqlFgpl3AwOPAXNum8zhjTcStx3LbQBqYWZsw6+F8Y9BfW6bRIKBROKcY7nzidHCzGNwGKglxUgisaEmdwMxWg7LGBzPbQMFcsKxA7kbgVoO4vUL/9mND99UVOfOb28++PBHTV3uvPOHDz74UYFbCwgcQGIfxhAhCOpIUTwKRsEoGAUjBAAA44haVWJE+F4AAAAASUVORK5CYII=","orcid":"","institution":"Université Mohammed VI des Sciences de la Santé","correspondingAuthor":true,"prefix":"","firstName":"Rim","middleName":"","lastName":"Alami","suffix":""},{"id":596901121,"identity":"df8c65aa-3c86-4a41-bbdd-1ac9a48db4d0","order_by":1,"name":"Reyzane El Mjabber","email":"","orcid":"","institution":"Université Mohammed VI des Sciences de la Santé","correspondingAuthor":false,"prefix":"","firstName":"Reyzane","middleName":"El","lastName":"Mjabber","suffix":""},{"id":596901122,"identity":"e47ba5a9-6fa1-4558-8d09-61b5eacb8a95","order_by":2,"name":"Omar Alami","email":"","orcid":"","institution":"Ryad oncologia clinic","correspondingAuthor":false,"prefix":"","firstName":"Omar","middleName":"","lastName":"Alami","suffix":""},{"id":596901123,"identity":"8c9159c1-6c23-4a76-bae0-ad3ba3b8331f","order_by":3,"name":"Reda Alami","email":"","orcid":"","institution":"Université Mohammed VI des Sciences de la Santé","correspondingAuthor":false,"prefix":"","firstName":"Reda","middleName":"","lastName":"Alami","suffix":""},{"id":596901124,"identity":"ad104590-f5fe-4805-a448-04e6d007d015","order_by":4,"name":"Asmaa Naim","email":"","orcid":"","institution":"Université Mohammed VI des Sciences de la Santé","correspondingAuthor":false,"prefix":"","firstName":"Asmaa","middleName":"","lastName":"Naim","suffix":""},{"id":596901126,"identity":"c6776f38-2365-4a95-beae-afa95d3379dd","order_by":5,"name":"Karima Bendahhou","email":"","orcid":"","institution":"Centre Mohammed VI pour le traitement des cancers","correspondingAuthor":false,"prefix":"","firstName":"Karima","middleName":"","lastName":"Bendahhou","suffix":""},{"id":596901128,"identity":"cf7d43d2-3635-4ebb-9e27-c59d76f493d4","order_by":6,"name":"Nadia Benchakroun","email":"","orcid":"","institution":"Centre Mohammed VI pour le traitement des cancers","correspondingAuthor":false,"prefix":"","firstName":"Nadia","middleName":"","lastName":"Benchakroun","suffix":""},{"id":596901130,"identity":"f4245f0c-d8f6-4dfc-bd33-6732c9cb2916","order_by":7,"name":"Abdellatif Benider","email":"","orcid":"","institution":"Centre Mohammed VI pour le traitement des cancers","correspondingAuthor":false,"prefix":"","firstName":"Abdellatif","middleName":"","lastName":"Benider","suffix":""}],"badges":[],"createdAt":"2025-12-16 17:08:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8378544/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8378544/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":103587364,"identity":"a994cbee-90af-4390-b004-4c1cf6926766","added_by":"auto","created_at":"2026-02-27 11:27:49","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":29630,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eOverall survival of the study population.\u003c/strong\u003e\u003cbr\u003e\nKaplan–Meier curve showing overall survival of the entire cohort. Overall survival was defined as the time from date of breast cancer diagnosis to death from any cause. Shaded areas represent the 95% confidence intervals. Time is expressed in months.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8378544/v1/b6d1ac50d4bca56b377fb83c.jpg"},{"id":103587367,"identity":"41f87d6b-acc1-4e14-90f4-669b3a0e81d6","added_by":"auto","created_at":"2026-02-27 11:27:49","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":42480,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eOverall survival according to age at diagnosis.\u003c/strong\u003e\u003cbr\u003e\nKaplan–Meier curves showing overall survival stratified by age at diagnosis (\u0026lt;45 years, 45–65 years, and \u0026gt;65 years). Survival curves were compared using the log-rank test. Time is expressed in months.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8378544/v1/d492da24a4195b921fe24566.jpg"},{"id":103587361,"identity":"965ffb99-43e0-405d-b05f-5f7566828689","added_by":"auto","created_at":"2026-02-27 11:27:48","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":38077,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eOverall survival according to hormone receptor status.\u003c/strong\u003e\u003cbr\u003e\nKaplan–Meier curves comparing overall survival between patients with hormone receptor–positive (estrogen and/or progesterone receptor positive) and hormone receptor–negative tumors. Survival curves were compared using the log-rank test. Time is expressed in months.\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8378544/v1/c4fa850b2cf9b0f922e1a67c.jpg"},{"id":103587372,"identity":"bfb8f0a3-d67a-43ee-886a-f9f2a288d3b8","added_by":"auto","created_at":"2026-02-27 11:27:50","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":40478,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eOverall survival according to HER2 status.\u003c/strong\u003e\u003cbr\u003e\nKaplan–Meier curves comparing overall survival between patients with HER2-positive and HER2-negative tumors. Survival curves were compared using the log-rank test. Time is expressed in months.\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8378544/v1/1344b79cc6087bece173910a.jpg"},{"id":103587374,"identity":"41067f49-43db-4f47-813b-2c231af96841","added_by":"auto","created_at":"2026-02-27 11:27:50","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":41220,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eOverall survival according to Ki-67 proliferation index.\u003c/strong\u003e\u003cbr\u003e\nKaplan–Meier curves comparing overall survival between tumors with Ki-67 \u0026lt;14% and Ki-67 ≥14%. Survival curves were compared using the log-rank test. Time is expressed in months.\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8378544/v1/16ce3ed0ea63ab51f74a8c2a.jpg"},{"id":103587362,"identity":"d806cca7-82d7-46e5-af70-2c482927872b","added_by":"auto","created_at":"2026-02-27 11:27:48","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":47674,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eOverall survival in triple-negative versus non–triple-negative breast cancer.\u003c/strong\u003e\u003cbr\u003e\nKaplan–Meier curves comparing overall survival between patients with triple-negative tumors and those with non–triple-negative tumors. Survival curves were compared using the log-rank test. Time is expressed in months.\u003c/p\u003e","description":"","filename":"6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8378544/v1/5b69b4f1a2aab33ceb24b876.jpg"},{"id":104398833,"identity":"3cc4e83f-2f1d-4579-9b21-b1ca33710bc3","added_by":"auto","created_at":"2026-03-11 12:03:53","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1037066,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8378544/v1/df4abe0e-542e-4f2b-8013-d05f05181788.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Immunohistochemical biomarkers and overall survival in breast cancer: a real-world cohort from Morocco","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eBreast cancer is the most commonly diagnosed malignancy among women worldwide and remains a leading cause of cancer-related mortality. According to global estimates from the GLOBOCAN project, breast cancer represents the first cancer in incidence and mortality among women, accounting for a substantial proportion of the global cancer burden (1). Despite major improvements in survival in high-income countries over recent decades, important disparities persist across regions, reflecting differences in early detection, access to care, and healthcare system resources.\u003c/p\u003e \u003cp\u003eBeyond traditional clinicopathological parameters, tumor biology is a key determinant of prognosis in breast cancer. Advances in molecular profiling have identified biologically distinct subtypes associated with different clinical behaviors and survival outcomes. However, genomic assays remain costly and are not routinely available in many low- and middle-income countries (LMICs). In this context, immunohistochemistry (IHC) continues to represent the cornerstone of tumor biological characterization in routine clinical practice, providing essential prognostic and predictive information through widely accessible biomarkers (2).\u003c/p\u003e \u003cp\u003eImmunohistochemical markers, including estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), and the proliferation index Ki-67, allow the classification of breast cancer into surrogate molecular subtypes such as luminal A, luminal B, HER2-enriched, and triple-negative tumors. These IHC-defined subtypes have been consistently shown to be associated with distinct survival patterns in large population-based studies and real-world cohorts, supporting their relevance as pragmatic prognostic tools in settings where genomic profiling is not routinely feasible (3).\u003c/p\u003e \u003cp\u003eAmong these biomarkers, Ki-67 reflects tumor proliferative activity and has been widely investigated as a prognostic factor in invasive breast cancer. Higher Ki-67 expression has been associated with more aggressive tumor behavior and poorer survival outcomes, further supporting its integration into routine pathological assessment despite ongoing debates regarding optimal cut-off values (4).\u003c/p\u003e \u003cp\u003eIn Morocco, breast cancer is the most frequent cancer among women and is often diagnosed at a relatively younger age compared with Western populations. Although several studies have described the distribution of immunohistochemical subtypes in Moroccan patients, large real-world cohorts evaluating long-term survival outcomes according to tumor biological characteristics remain limited, particularly in North African settings (5). Generating population-specific survival data based on routinely assessed biomarkers is therefore essential to better understand prognosis and to establish regional benchmarks.\u003c/p\u003e \u003cp\u003e The present study aimed to evaluate overall survival according to immunohistochemical biomarkers and surrogate molecular subtypes in a large retrospective cohort of breast cancer patients treated at a tertiary referral center in Casablanca, Morocco. By focusing on routinely available biological markers, this study provides real-world prognostic data that may serve as a baseline for future improvements in breast cancer outcomes in similar resource-constrained settings.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and setting\u003c/h2\u003e \u003cp\u003eThis was a retrospective, monocentric cohort study conducted at the Mohammed VI Cancer Treatment Center, Ibn Rochd University Hospital, Casablanca, Morocco. The study was designed to evaluate the prognostic value of routinely assessed immunohistochemical biomarkers on overall survival in breast cancer patients, using real-world data.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy population\u003c/h3\u003e\n\u003cp\u003eAll patients with a histologically confirmed diagnosis of invasive breast carcinoma between January 1 and December 31, 2014, were eligible for inclusion. Patients with non-invasive breast tumors, metastatic tumors from non-breast primary sites, or recurrent breast cancer at diagnosis were excluded. A total of 623 patients met the inclusion criteria and constituted the final study cohort.\u003c/p\u003e\n\u003ch3\u003eData collection\u003c/h3\u003e\n\u003cp\u003eClinical and pathological data were extracted from institutional medical records and archived pathology reports. Collected variables included age at diagnosis, estrogen receptor (ER) status, progesterone receptor (PR) status, HER2 status, Ki-67 proliferation index (when available), date of diagnosis, vital status, and date of death when applicable. Vital status at five years was obtained from medical records and, when necessary, by telephone contact with patients or their relatives.\u003c/p\u003e\n\u003ch3\u003eImmunohistochemical assessment and biomarker definitions\u003c/h3\u003e\n\u003cp\u003eER and PR status were assessed by immunohistochemistry (IHC) and reported as positive or negative according to contemporaneous international recommendations. HER2 status was evaluated by IHC, with equivocal cases further assessed by in situ hybridization when available, following standard practice guidelines (6). Ki-67 was reported as the percentage of positively stained tumor cell nuclei and categorized using a 14% cut-off, in line with international consensus recommendations during the study period (7,8).\u003c/p\u003e \u003cp\u003eBased on IHC results, tumors were classified into surrogate molecular subtypes as follows: luminal A (ER and/or PR positive, HER2 negative), luminal B (ER and/or PR positive with either HER2 positivity or high Ki-67), HER2-enriched (ER and PR negative, HER2 positive), and triple-negative (ER, PR, and HER2 negative), according to established surrogate definitions (8,9).\u003c/p\u003e\n\u003ch3\u003eOutcome definition\u003c/h3\u003e\n\u003cdiv class=\"Heading\"\u003eOutcome definition\u003c/div\u003e \u003cp\u003eThe primary outcome was overall survival (OS), defined as the time from the date of breast cancer diagnosis to death from any cause. Patients alive at the end of follow-up were censored at the date of last contact.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eContinuous variables were summarized using means and ranges, while categorical variables were described using frequencies and percentages. Overall survival was estimated using the Kaplan\u0026ndash;Meier method, and survival curves were compared using the log-rank test (10). Statistical significance was defined as a two-sided p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05. All analyses were performed using standard statistical software.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eEthical considerations\u003c/h3\u003e\n\u003cp\u003e The study was approved by the local ethics committee of Ibn Rochd University Hospital, Casablanca. Given the retrospective nature of the study and the use of anonymized routinely collected data, the requirement for informed consent was waived.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003ePatient characteristics\u003c/h2\u003e \u003cp\u003eA total of 623 patients with invasive breast carcinoma diagnosed in 2014 were included in the analysis. The mean age at diagnosis was 51 years (range: 17\u0026ndash;91 years). Baseline clinicopathological characteristics of the study population are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eHormone receptor status was available for the majority of patients: estrogen and/or progesterone receptors were positive in 383 cases (61.5%) and negative in 194 cases (31.1%), while data were missing for 46 patients (7.4%). HER2 status was positive in 148 tumors (23.8%), negative in 387 (62.1%), and unavailable in 88 cases (14.1%). Ki-67 proliferation index was available for 301 tumors (48.3% of the cohort). Among the entire study population, 151 tumors (24.2%) had a Ki-67\u0026thinsp;\u0026ge;\u0026thinsp;14%, 150 (24.1%) had a Ki-67\u0026thinsp;\u0026lt;\u0026thinsp;14%, while Ki-67 status was missing in 322 cases (51.7%).\u003c/p\u003e \u003cp\u003eBased on immunohistochemical results, tumors were classified into surrogate molecular subtypes in cases with complete data (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The molecular subtype could not be determined in 88 patients due to missing biomarker data.\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\u003e\u003cb\u003eBaseline characteristics of the study population.\u003c/b\u003e Baseline demographic and tumor biological characteristics of the 623 patients included in the study, including age at diagnosis, hormone receptor status, HER2 status, Ki-67 proliferation index, and surrogate immunohistochemical molecular subtypes.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAge at diagnosis\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean age (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRange (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17\u0026ndash;91\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAge group\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;45 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e209 (33.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e45\u0026ndash;65 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e351 (56.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;65 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e63 (10.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eHormone receptor status\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e383 (61.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e194 (31.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46 (7.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eHER2 status\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e148 (23.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e387 (62.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e88 (14.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eKi-67 proliferation index\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;14%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e150 (24.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;14%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e151 (24.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e322 (51.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMolecular subtype\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLuminal A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e279 (44.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLuminal B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e104 (16.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHER2-like\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e148 (23.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTriple-negative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100 (16.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot determined\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e88 (14.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eData are presented as number (percentage) unless otherwise indicated. Percentages may not total 100% due to missing data. The number of patients with missing data for each variable is reported.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eOverall survival\u003c/h2\u003e \u003cp\u003eVital status at five years was available for 560 patients (89.9% of the cohort). At the end of follow-up, 125 deaths were recorded. The estimated overall survival rates were 97.3% at 1 year, 88.4% at 3 years, and 77.5% at 5 years.\u003c/p\u003e \u003cp\u003eThe Kaplan\u0026ndash;Meier curve for overall survival of the entire cohort is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eKaplan\u0026ndash;Meier curve showing overall survival of the entire cohort. Overall survival was defined as the time from date of breast cancer diagnosis to death from any cause. Shaded areas represent the 95% confidence intervals. Time is expressed in months.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eOverall survival according to age\u003c/h2\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003ePatients were categorized into three age groups: \u0026lt;45 years (33.5%), 45\u0026ndash;65 years (56.3%), and \u0026gt;65 years (10.1%). Overall survival differed significantly across age groups (log-rank p = 0.043). Five-year overall survival rates were 76.2% in patients \u0026lt;45 years, 81.5% in patients aged 45\u0026ndash;65 years, and 70.3% in patients \u0026gt;65 years (Figure \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eKaplan\u0026ndash;Meier curves showing overall survival stratified by age at diagnosis (\u0026lt;\u0026thinsp;45 years, 45\u0026ndash;65 years, and \u0026gt;\u0026thinsp;65 years). Survival curves were compared using the log-rank test. Time is expressed in months.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eOverall survival according to hormone receptor status\u003c/h2\u003e \u003cp\u003eHormone receptor\u0026ndash;positive tumors were associated with significantly improved overall survival compared with hormone receptor\u0026ndash;negative tumors (log-rank p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Five-year overall survival was 85.8% in patients with hormone receptor\u0026ndash;positive tumors versus 68.8% in those with hormone receptor\u0026ndash;negative tumors (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eKaplan\u0026ndash;Meier curves comparing overall survival between patients with hormone receptor\u0026ndash;positive (estrogen and/or progesterone receptor positive) and hormone receptor\u0026ndash;negative tumors. Survival curves were compared using the log-rank test. Time is expressed in months.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eOverall survival according to HER2 status\u003c/h2\u003e \u003cp\u003eNo significant difference in overall survival was observed according to HER2 status (log-rank p\u0026thinsp;=\u0026thinsp;0.23). Five-year overall survival rates were 81.7% in patients with HER2-positive tumors and 78.0% in those with HER2-negative tumors (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eKaplan\u0026ndash;Meier curves comparing overall survival between patients with HER2-positive and HER2-negative tumors. Survival curves were compared using the log-rank test. Time is expressed in months.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eOverall survival according to Ki-67 proliferation index\u003c/h2\u003e \u003cp\u003eAmong patients with available Ki-67 data, those with a Ki-67\u0026thinsp;\u0026ge;\u0026thinsp;14% had significantly worse overall survival compared with patients with Ki-67\u0026thinsp;\u0026lt;\u0026thinsp;14% (log-rank p\u0026thinsp;=\u0026thinsp;0.0038). Five-year overall survival rates were 72.5% and 86.7%, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eKaplan\u0026ndash;Meier curves comparing overall survival between tumors with Ki-67\u0026thinsp;\u0026lt;\u0026thinsp;14% and Ki-67\u0026thinsp;\u0026ge;\u0026thinsp;14%. Survival curves were compared using the log-rank test. Time is expressed in months.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eOverall survival in triple-negative versus non\u0026ndash;triple-negative breast cancer\u003c/h2\u003e \u003cp\u003ePatients with triple-negative (basal-like) tumors exhibited the poorest survival outcomes, with a five-year overall survival rate of 63.8%, compared with 82.8% in patients with non-triple-negative tumors (Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eKaplan\u0026ndash;Meier curves comparing overall survival between patients with triple-negative tumors and those with non\u0026ndash;triple-negative tumors. Survival curves were compared using the log-rank test. Time is expressed in months.\u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eIn this large real-world cohort of breast cancer patients treated at a tertiary referral center in Morocco, overall survival differed significantly according to routinely assessed immunohistochemical biomarkers. Hormone receptor status, Ki-67 proliferation index, and surrogate molecular subtypes were strongly associated with overall survival, supporting the prognostic relevance of tumor biological characteristics assessed by immunohistochemistry.\u003c/p\u003e \u003cp\u003eHormone receptor positivity was associated with significantly improved overall survival, consistent with findings from large population-based studies showing more favorable outcomes in estrogen and/or progesterone receptor\u0026ndash;positive tumors compared with receptor-negative disease (3). This observation reinforces the central prognostic role of hormone receptor expression, even in settings where detailed staging and treatment data are not available.\u003c/p\u003e \u003cp\u003eTriple-negative (basal-like) tumors exhibited the poorest survival outcomes in our cohort, in line with international data reporting aggressive clinical behavior and inferior prognosis for this subtype (3). Conversely, patients with luminal subtypes demonstrated more favorable survival patterns. Although direct comparisons with high-income country cohorts should be interpreted cautiously, the relative survival differences between subtypes observed in our study are broadly consistent with previously published reports.\u003c/p\u003e \u003cp\u003eA high Ki-67 proliferation index was associated with worse overall survival. This finding aligns with prior studies and expert consensus highlighting Ki-67 as a marker of tumor aggressiveness and adverse prognosis in invasive breast cancer, despite ongoing variability in assessment and cut-off values (4,7). The prognostic value of Ki-67 observed in our real-world cohort supports its continued use as a pragmatic biomarker in routine clinical practice.\u003c/p\u003e \u003cp\u003eData on breast cancer outcomes in North African populations remain limited. Previous studies from Morocco have primarily focused on the distribution of immunohistochemical subtypes rather than long-term survival outcomes (5). By providing five-year overall survival estimates according to tumor biological characteristics, the present study contributes population-specific data that may serve as a benchmark for future evaluations of breast cancer outcomes in similar settings.\u003c/p\u003e \u003cp\u003eSeveral limitations should be acknowledged. The retrospective design and the absence of tumor stage and treatment-related variables preclude adjustment for these potentially important prognostic factors. Additionally, missing data for some biomarkers, particularly Ki-67, may have introduced selection bias. However, the study deliberately focused on routinely available biological markers to reflect real-world diagnostic practice.\u003c/p\u003e \u003cp\u003eDespite these limitations, the strengths of this study include its large sample size, robust follow-up, and focus on immunohistochemical biomarkers that are widely accessible in resource-constrained settings. These findings underscore the prognostic importance of tumor biology assessed by immunohistochemistry and provide valuable real-world survival data from a North African tertiary care center.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eIn this large real-world cohort of breast cancer patients from a North African tertiary center, routinely assessed immunohistochemical biomarkers were strongly associated with overall survival. Hormone receptor status, Ki-67 proliferation index, and surrogate molecular subtypes provided meaningful prognostic stratification despite the absence of detailed staging and treatment data. These findings highlight the continued relevance of immunohistochemistry as a pragmatic prognostic tool in resource-constrained settings and provide population-specific survival benchmarks for future outcome evaluations.\u003c/p\u003e"},{"header":"Declarations","content":" \u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e \u003cp\u003eThe study was approved by the local ethics committee of Ibn Rochd University Hospital, Casablanca. Given the retrospective nature of the study and the use of anonymized data, informed consent was waived.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThe authors received no specific funding for this study.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eRA contributed to the study conception and design, data collection, interpretation of the data, and drafting of the manuscript.EMR and NA contributed to data collection and validation of clinical and pathological data.BK performed the statistical analysis and contributed to interpretation of the results.AO and AR contributed to data interpretation and critical revision of the manuscript.BN and BA contributed to critical revision of the manuscript for important intellectual content, supervised the study, contributed to study design and interpretation of the data, and critically revised the manuscript.All authors read and approved the final manuscript and agree to be accountable for all aspects of the work.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eThe authors thank the medical and pathology staff of the Mohammed VI Cancer Treatment Center for their support.\u003c/p\u003e "},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2021;71(3):209\u0026ndash;249. doi:10.3322/caac.21660.\u003c/li\u003e\n\u003cli\u003eColomer R, Sola M, Llombart-Cussac A, et al. Biomarkers in breast cancer: an updated consensus statement. Breast Cancer Res Treat. 2024;195(1):1\u0026ndash;15. doi:10.1007/s10549-024-07215-7.\u003c/li\u003e\n\u003cli\u003eParise CA, Caggiano V. Breast cancer survival defined by the ER/PR/HER2 subtypes. PLoS One. 2014;9(3):e91188. doi:10.1371/journal.pone.0091188.\u003c/li\u003e\n\u003cli\u003eDavey MG, Ryan EJ, McAnena PF, et al. The role of Ki-67 as a prognostic biomarker in invasive breast cancer. Cancers (Basel). 2021;13(3):445. doi:10.3390/cancers13030445.\u003c/li\u003e\n\u003cli\u003eEl Idrissi Errahhali M, Ouarzane M, El Fakir S, et al. Molecular subtypes of breast cancer and their clinicopathological associations in Eastern Morocco. Pan Afr Med J. 2017;28:112. doi:10.11604/pamj.2017.28.112.12415.\u003c/li\u003e\n\u003cli\u003eWolff AC, Hammond MEH, Allison KH, Harvey BE, Mangu PB, Bartlett JMS, et al. Human epidermal growth factor receptor 2 testing in breast cancer: American Society of Clinical Oncology/College of American Pathologists clinical practice guideline update. J Clin Oncol. 2018;36(20):2105\u0026ndash;2122. doi:10.1200/JCO.2018.77.8738.\u003c/li\u003e\n\u003cli\u003eDowsett M, Nielsen TO, A\u0026rsquo;Hern R, Bartlett J, Coombes RC, Cuzick J, et al. Assessment of Ki-67 in breast cancer: recommendations from the International Ki-67 in Breast Cancer Working Group. J Natl Cancer Inst. 2011;103(22):1656\u0026ndash;1664. doi:10.1093/jnci/djr393.\u003c/li\u003e\n\u003cli\u003eGoldhirsch A, Wood WC, Coates AS, Gelber RD, Th\u0026uuml;rlimann B, Senn HJ. Strategies for subtypes\u0026mdash;dealing with the diversity of breast cancer: highlights of the St Gallen International Expert Consensus on the primary therapy of early breast cancer 2011. Ann Oncol. 2011;22(8):1736\u0026ndash;1747. doi:10.1093/annonc/mdr304.\u003c/li\u003e\n\u003cli\u003eParise CA, Caggiano V. Survival outcomes for breast cancer defined by the ER/PR/HER2 subtypes. PLoS One. 2014;9(3):e91188. doi:10.1371/journal.pone.0091188.\u003c/li\u003e\n\u003cli\u003eKaplan EL, Meier P. Nonparametric estimation from incomplete observations. J Am Stat Assoc. 1958;53(282):457\u0026ndash;481. doi:10.1080/01621459.1958.10501452.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Breast cancer, Immunohistochemistry, Overall survival, Prognosis, Triple-negative breast cancer","lastPublishedDoi":"10.21203/rs.3.rs-8378544/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8378544/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 malignancy among women worldwide, with marked disparities in survival outcomes across regions (1). In many low- and middle-income countries, immunohistochemistry remains the cornerstone for tumor biological characterization. This study aimed to evaluate overall survival according to routinely assessed immunohistochemical biomarkers and surrogate molecular subtypes in a large real-world cohort from Morocco.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis retrospective monocentric cohort study included 623 patients with invasive breast cancer diagnosed in 2014 at a tertiary referral center in Casablanca. Data on age, estrogen receptor (ER), progesterone receptor (PR), HER2 status, Ki-67 proliferation index, molecular subtype, vital status, and date of death were collected. Overall survival was estimated using the Kaplan\u0026ndash;Meier method and compared using the log-rank test.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAt five years, vital status was available for 560 patients. Overall survival at five years was 77.5%. Hormone receptor\u0026ndash;positive tumors were associated with significantly improved overall survival compared with hormone receptor\u0026ndash;negative tumors (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). High Ki-67 (\u0026ge;\u0026thinsp;14%) was associated with poorer survival (p\u0026thinsp;=\u0026thinsp;0.0038). Overall survival differed significantly according to triple-negative status, with triple-negative tumors exhibiting the worst outcomes.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eRoutinely assessed immunohistochemical biomarkers retain strong prognostic value for overall survival in breast cancer. These real-world data provide important population-specific benchmarks and support the continued use of immunohistochemistry for prognostic stratification in resource-constrained settings.\u003c/p\u003e","manuscriptTitle":"Immunohistochemical biomarkers and overall survival in breast cancer: a real-world cohort from Morocco","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-27 11:27:30","doi":"10.21203/rs.3.rs-8378544/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-02-25T11:40:23+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"122772519977545168174961118610551089926","date":"2026-02-24T13:35:33+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-24T10:03:50+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-12-22T07:25:56+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-18T03:31:16+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-18T03:30:09+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Cancer","date":"2025-12-16T16:53:05+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"21564446-e17b-4d42-97ce-958810883087","owner":[],"postedDate":"February 27th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-02-27T11:27:30+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-27 11:27:30","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8378544","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8378544","identity":"rs-8378544","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}