European Journal of Cardiovascular Medicine

Noncommunicable diseases (NCDs) have become the leading cause of death globally, with cancer emerging as a major contributor to premature mortality. As of 2015, cancer ranked as the first or second leading cause of death before age 70 in over half of the world’s countries, according to WHO estimates. The global cancer burden continues to rise, driven by population aging, growth, and shifts in the prevalence of key risk factors—many linked to socioeconomic development. Notably, emerging economies are experiencing a transition marked by a decline in infection-related cancers and a rise in lifestyle-associated cancers common in high-income nations. Despite this, significant geographic variation persists due to local risk factors and disparities in development. Against this backdrop, the current report draws on GLOBOCAN 2018 estimates from the International Agency for Research on Cancer (IARC) to provide an updated overview of cancer incidence and mortality across 20 world regions, highlighting the magnitude, distribution, and key determinants of the global cancer burden.[1].

In India, the age-adjusted incidence rate of breast cancer is reported as 25.8 per 100,000, significantly lower than that in high-income countries like the United Kingdom (95 per 100,000). However, the mortality rate remains nearly comparable, highlighting the disparities in screening, early detection, and access to timely treatment [2]. The high mortality in India, despite lower incidence, is attributed to delayed presentation, inadequate public health awareness, lack of systematic screening programs, and treatment dropouts [3,4]. This calls for urgent public health strategies to promote early diagnosis and equitable access to comprehensive care.

Unlike Western populations where the peak age for breast cancer diagnosis is between 60–64 years, Indian women tend to develop breast cancer a decade earlier, with the highest incidence seen between 45–49 years [5,6]. Studies from various regions of India—including Odisha, Jharkhand, Andhra Pradesh, and Central India—have repeatedly shown a higher burden of cases in premenopausal women, with over one-third of patients below the age of 40 [7–9].

India also reports a high proportion of locally advanced breast cancer (LABC). In contrast to Western countries where 60–70% of cases are diagnosed at an early stage due to robust screening programs, more than 45–57% of Indian women present with Stage III disease, and around 10–15% have distant metastasis at initial diagnosis [5,9]. This reflects the pressing need to enhance breast health literacy and develop region-specific screening protocols, especially in rural and semi-urban populations.

Histopathologically, infiltrating ductal carcinoma (IDC) is the most common subtype across all regions of India, accounting for more than 90% of diagnosed cases [6–8,13]. Immunohistochemistry (IHC) profiling has revealed a high burden of hormone receptor-negative tumors, particularly Triple-Negative Breast Cancer (TNBC). TNBC is characterized by the absence of ER, PR, and HER2/neu expression, and is more aggressive, prone to early recurrence, and resistant to hormonal and HER2-targeted therapies. Indian studies have reported TNBC prevalence ranging from 22% to 48%, which is significantly higher than in Western populations (10–20%) [7–11].

Subtypes like Metaplastic Breast Carcinoma (MBC), although rare (0.2–5% of all invasive breast cancers), are emerging as distinct pathological entities due to their aggressive clinical course, large tumor size, relatively fewer nodal metastases, and limited response to conventional chemotherapy. These tumors are commonly triple-negative and may express unconventional markers like cytokeratin, vimentin, and P63. While surgery remains the mainstay of treatment, evolving evidence supports the potential role of immunotherapy targeting PD-L1 in MBC cases .

Several institutional and regional studies in India have documented these clinicopathological patterns, yet there is a paucity of comprehensive data from tertiary centers in Andhra Pradesh. There is also a need to correlate clinical staging with pathological findings and evaluate the role of receptor status in guiding treatment modalities. This study, therefore, aims to fill this knowledge gap by evaluating the age distribution, clinical staging, correlation with pathological staging, and hormone receptor status in breast cancer patients presenting to a government tertiary care center in Visakhapatnam. The findings aim to contribute to existing literature and support evidence-based practices for improving patient care and outcomes.

Aims and Objectives

• To study the age distribution among breast cancer patients.
• To evaluate the distribution of clinical staging in diagnosed cases.
• To assess the correlation between clinical and pathological staging.
• To analyze the distribution of hormone receptor status (ER, PR, HER2neu).

This observational study was conducted on 50 patients diagnosed with breast carcinoma who attended the Department of General Surgery, King George Hospital, Andhra Medical College, Visakhapatnam, during the period August 2017 to June 2019.

Inclusion Criteria

• All diagnosed cases of carcinoma breast, regardless of age or sex.
• All stages of carcinoma breast were included in the study.

Exclusion Criteria

• Patients not willing to provide informed consent were excluded from the study.

Study Design

This was a single-institution, retrospective study conducted at King George Hospital, Andhra Medical College, Visakhapatnam. Data were collected from the medical records of 50 histopathologically confirmed breast cancer patients to analyze their demographic characteristics, clinicopathological features, and immunohistochemical (IHC) profiles, including estrogen receptor (ER), progesterone receptor (PR), and HER2/neu status. All cases were staged using the American Joint Committee on Cancer (AJCC) TNM Staging System, 8th Edition. Treatment modalities were administered based on individual staging and biomarker expression and included neo-adjuvant or adjuvant chemotherapy, surgical intervention, external beam radiotherapy, hormone therapy, and trastuzumab-based targeted therapy where applicable. Prior to initiation of therapy, all patients underwent a detailed pre-treatment workup comprising routine blood tests, tru-cut biopsy for histopathology and IHC, chest X-ray (posteroanterior view), electrocardiography (ECG), echocardiography, ultrasonography (USG) of bilateral breasts and axilla, whole abdominal USG, contrast-enhanced computed tomography (CECT) of the thorax and abdomen, whole-body bone scan, and PET-CT when indicated.

Table 1: Age-wise Distribution of Patients with Carcinoma Breast (n = 50)

The majority of breast carcinoma cases in this study were seen in the 41–60 years age group, accounting for 56% of the total population. Notably, a significant portion (34%) of patients were under 40 years of age, indicating a concerning trend toward younger onset of breast cancer. The smallest group was the 61–80 years category, comprising 10% of cases. This distribution underlines the need for early screening and awareness, especially among women in their third and fourth decades of life.

FIGURE 1: Age-wise Distribution of Patients

Table 2A: Breast Side Involvement

Table 2B: Tumor Quadrant Distribution

In terms of laterality, breast carcinoma showed nearly equal involvement of right and left breasts, with the right breast slightly more affected (50%). Only one patient (2%) had bilateral breast cancer.When analyzing quadrant-wise tumor location, the upper outer quadrant was the most commonly affected site (70%), which is consistent with known anatomical density of glandular tissue in this region. The central quadrant was the next most affected (14%), followed by lower outer (10%) and upper inner (6%) quadrants.

FIGURE 2 : Tumor Quadrant Distribution (n=50)

Table 3: Clinical Stage Distribution by Age Group

Interpretation:

Among the 21–40 years group, a larger proportion presented in Stage III (58.8%), reinforcing the trend of more aggressive disease in younger individuals. The 41–60 years group had an even distribution between Stage II and Stage III (50% each), while patients aged 61–80 were mostly in Stage II, likely due to more regular screening or slower tumor progression.

This table and chart emphasize that younger patients often present at a more advanced clinical stage, necessitating early and targeted screening programs for younger populations at risk.

FIGURE 3: Clinical Stage by Age Group. ​

Table 4: Tumor Size (T Stage) vs Nodal Status (N Stage)

Interpretation:

The table clearly demonstrates a correlation between tumor size and nodal involvement. Patients with T2 tumors mostly had N0 status (60%), indicating lesser nodal spread. In contrast, T3 and T4 tumors showed greater nodal involvement, especially N1 and N2 status, reflecting advanced disease.

• T3 tumors had only 1 case with N0, while most were N1 (66.7%) and N2 (13.3%).
• All T4 tumors showed nodal positivity, with 53.3% having N1 and 13.3% having N2 involvement.

This underscores the importance of early tumor detection before lymph node involvement escalates.

FIGURE 4: Tumor Size (T) vs Nodal Status (N).

Table 5: Pathological Stage Distribution by Age Group

Interpretation:

The pathological staging pattern is consistent with clinical staging, showing that younger patients tend to present with more advanced disease.

• In the 21–40 years group, 70.6% were Stage III pathologically.
• The 41–60 years group showed 57.1% in Stage III.
• Interestingly, the older group (61–80) had 60% in Stage II, suggesting earlier detection or slower tumor biology.

This supports the idea that younger patients tend to have more aggressive tumor biology, requiring vigilant follow-up and potentially different treatment planning.

FIGURE 5: Pathological Stage by Age Group.

Table 6: Clinical vs Pathological Node Status (n = 50)

A significant discrepancy is observed between clinical and pathological node staging:

• 20 patients were clinically N0, but only 13 remained N0 on pathology, indicating 7 patients were under-staged clinically.
• Pathological N1 increased to 33, up from 25 clinically — showing progressive nodal disease confirmed only post-operatively.
• N2 status remained relatively consistent.

This emphasizes the importance of pathological assessment to reveal true disease extent, which may not be apparent on physical exam or imaging alone.

FIGURE 6: Clinical vs Pathological Node Status.

Table 7: Hormonal Receptor and HER2neu Status (n = 50)

The dominant molecular subtype observed was Luminal A (ER/PR+, HER2−), comprising 70% of the cases, which generally indicates a better prognosis and response to hormonal therapy.

• Triple Negative Breast Cancer (TNBC) made up 22% of the cases. These patients typically have poorer outcomes and limited treatment options due to lack of receptor targets.
• HER2-positive only cases were fewer (8%), while triple-positive tumors were absent in this cohort.

This receptor distribution has important implications for targeted therapy planning, especially considering the aggressive nature of TNBC.

FIGURE 7: Hormonal Receptor and HER2neu Status.

Table 8: Histological Subtype Distribution (n = 50)

The most common histological subtype observed was Infiltrating Ductal Carcinoma (IDC), accounting for a significant 92% of all cases. This is in line with global data, where IDC remains the predominant type of breast cancer.

• Metaplastic and papillary carcinomas, although rare (4% each), were present and are clinically significant due to their variable prognosis and differing treatment responses.
• Among the IDC group, there were subtypes with triple-negative status and HER2 positivity, adding to the diversity in molecular characteristics.

This distribution highlights the need for histological confirmation and molecular typing in all breast cancer diagnoses to ensure precise classification and personalized treatment.

FIGURE 8: Histological Subtype Distribution (n=50)

Age and Demographic Trends

In the current study, a significant proportion of breast cancer patients (34%) were below 40 years of age, with the median age at diagnosis being 48 years. This aligns with previous Indian studies such as Aslam, H. M.et al. [7], Talpur, K. A. H et al. [8], and Gogia, A.,et al. [6], who reported mean or median ages around 47–48 years. Jacob, L. A., et al [9], studying young breast cancer patients, observed a mean age of 35.8 years. Comparatively, Western populations report a median age of 62 years at diagnosis [1]. These findings highlight that Indian women develop breast cancer at a younger age, necessitating early screening strategies tailored for younger age groups. Additionally, it raises issues related to fertility preservation, aggressive biology, and the need for tailored survivorship plans.

Tumor Laterality and Quadrant Involvement

This study observed a nearly equal distribution of laterality: 50% right and 48% left, which is consistent with findings by Aslam, H. M., et al. [7] and Gogia, A., et al. [6]. Although global data suggest a slight left-sided predominance, Indian studies often show near-equal distribution. The upper outer quadrant (UOQ) was the mostinvolved site (70%), which aligns with the 66.6% reported by Aslam, H. M., et al. [7]. This anatomical quadrant houses the densest breast tissue, making it more susceptible to malignant changes and reinforcing its importance in focused screening exams and mammography interpretation.

Stage at Presentation – Clinical and Pathological

More than half the patients in our study presented in Stage III (52%), suggesting late diagnosis. This trend is well-documented across Indian studies—Takalkar, U. V et al. [3], Mir, M. A., et al. [4], Budzik, M. P., et al  [5], and Gogia, A. et al. [6] each reported Stage III presentation rates between 46–51%. Young patients in the Chaudhary and Sinha cohort [9] also presented in Stage III in 52% of cases. The underlying causes may include poor awareness, sociocultural stigma, and lack of access to timely screening or care. These findings underscore the need for earlier detection programs and outreach in rural and semi-urban India.

Tumor Size and Nodal Involvement

A direct relationship between tumor size and lymph node status was observed. Most T2 tumors were node-negative, whereas T3 and T4 tumors showed progressive nodal involvement. This correlates with findings by Malvia, Set al [10], who noted that 63.9% of TNBC patients had T2 tumors with 44% having N1/N2 disease. Aslam, H. M.,  et al. [7] similarly reported 66.9% of patients had pT2 tumors, with 59.6% showing nodal positivity. Early tumor detection could substantially reduce lymph node spread, improving both staging and long-term prognosis.

Hormonal Receptor and HER2neu Status

Our study found 70% hormone receptor-positive cases, 22% TNBC, and 8% HER2neu-positive cases. This is comparable with Budzik, M. P., et al  [5], who found 56.2% hormone receptor positivity and 26.9% TNBC. Mir, M. A., et al. [4] reported a TNBC rate of 46.9%, although their IHC data was incomplete. Aslam, H. M.,  et al. [7] reported a notably higher TNBC rate at 47.9%. Variations may stem from geographical, genetic, or methodological differences. Given the aggressive nature and limited treatment options for TNBC [14], identifying hormone receptor and HER2neu status is essential for planning effective, individualized therapy—especially in resource-constrained environments.

Histological Subtypes

Infiltrating ductal carcinoma (IDC) was the dominant subtype (92%), consistent with Aslam, H. M.,  et al. [7] (96.5%), Gogia, A.,  et al. [6] (90.8%), and Talpur, K. A. H et al. [8] (85.2%). Rare subtypes such as metaplastic and papillary carcinoma were also noted. Chand, P et al. [11] conducted a focused study on metaplastic carcinoma, revealing large tumor size, high lymphovascular invasion, and poor survival outcomes. As metaplastic and triple-negative breast cancers frequently overlap biologically , histological and immunohistochemical profiling remains critical for therapeutic decisions and prognostication.

Clinical Implications and Public Health Significance

Across the board, Indian studies confirm that breast cancer patients tend to be younger and often present at an advanced stage [3–6,8]. This pattern underscores an urgent need for public health interventions—especially awareness campaigns, mobile mammography units, and regionally tailored screening guidelines. Hormonal and HER2 profiling must be made widely accessible, as these directly influence treatment strategies. Regional and molecular heterogeneity, particularly the variability in TNBC prevalence, supports the establishment of population-based biobanks and cancer registries to better understand and address local disease biology [12,13].

Comparative Summary of Key Indian Breast Cancer Studies

This study highlights key clinicopathological features of breast cancer in our region, marked by a younger age of onset, with one-third of patients below 40 years. The majority presented at Stage III, reflecting delayed diagnosis and limited screening awareness. Hormone receptor-positive tumors were predominant, though triple-negative breast cancer remained a significant subset, particularly among younger women. Infiltrating ductal carcinoma was the most common histological type. These findings underscore the need for earlier screening strategies, widespread availability of molecular testing, and public health initiatives to promote timely detection and tailored treatment. Strengthening cancer registries and regional research will be essential to address India's unique breast cancer profile.

1. Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018 Nov;68(6):394-424. doi: 10.3322/caac.21492. Epub 2018 Sep 12. Erratum in: CA Cancer J Clin. 2020 Jul;70(4):313. doi: 10.3322/caac.21609. PMID: 30207593.
2. Indian Council of Medical Research (ICMR). National Cancer Registry Programme Report 2020.
3. Takalkar, U. V., Asegaonkar, S. B., Kulkarni, U., Saraf, M., & Advani, S. (2016). Clinicopathological profile of breast cancer patients at a tertiary care hospital in marathwada region of Westen India. Asian Pacific Journal of Cancer Prevention, 17(4), 2195-2198.
4. Mir, M. A., Manzoor, F., Singh, B., Raja, W., Jeelani, S., Zargar, W. A., ... & Sofi, I. A. (2017). Clinicopathological profile of breast cancer patients at a tertiary care hospital in Kashmir valley. Surgical Science, 8(03), 162.
5. Budzik, M. P., Patera, J., Sobol, M., Czerw, A. I., Deptała, A., & Badowska-Kozakiewicz, A. M. (2019). Clinicopathological characteristics of metaplastic breast cancer–analysis of the basic immunohistochemical profile and comparison with other invasive breast cancer types. The Breast, 43, 135-141.
6. Gogia, A., Deo, S. V. S., Shukla, N. K., Mathur, S., Sharma, D. N., & Tiwari, A. (2018). Clinicopathological profile of breast cancer: An institutional experience. Indian journal of cancer, 55(3), 210-213.
7. Aslam, H. M., Saleem, S., Shaikh, H. A., Shahid, N., Mughal, A., & Umah, R. (2013). Clinico-pathological profile of patients with breast diseases. Diagnostic pathology, 8, 1-6.
8. Talpur, K. A. H., Laghari, A. A., Malik, A. M., & Memon, A. (2006). Clinico-pathological profile of patients with breast diseases at university hospital, Jamshoro. Jlumhs, 5(2), 71-75.
9. Jacob, L. A., Anand, A., Lakshmaiah, K. C., Babu, G. K., Lokanatha, D., Babu, M. S. S., ... & Koppaka, D. (2018). Clinicopathological profile and treatment outcomes of bilateral breast cancer: A study from tertiary cancer center in South India. Indian Journal of Medical and Paediatric Oncology, 39(01), 58-61.
10. Malvia, S., Bagadi, S. A. R., Pradhan, D., Chintamani, C., Bhatnagar, A., Arora, D., ... & Saxena, S. (2019). Study of gene expression profiles of breast cancers in Indian women. Scientific reports, 9(1), 10018.
11. Chand, P., Garg, A., Singla, V., & Rani, N. (2018). Evaluation of immunohistochemical profile of breast cancer for prognostics and therapeutic use. Nigerian Journal of Surgery, 24(2), 100-106.
12. Das, D. S., Yengkhom, I. S., Sekar, V., Akoijam, S., Adhikarimayum, A. D., & Chongthu, J. L. (2019). Study of evolving trends in the clinicopathological profile of breast cancer patients attending a tertiary cancer center. Journal of Medical Society, 33(2), 71-75.
13. Badwe R, Sinha P, Thorat MA. Breast cancer subtypes in India. Natl Med J India. 2020.
14. Thike AA, Chng MJ, Tan PH. Predicting outcomes in triple-negative breast cancer. Pathology. 2010;42(5):409–415.