Triple Negative Breast Cancer: Immunohistochemistry-Based Sub-Classification and Correlation with Clinico-Demographic Profile and Survival in Indian Patients

Abstract

In India, breast cancer number is increasing at an alarming pace in younger women. Majority of the patients are presenting in an advanced stage and are frequently showing triple negative phenotype. Additionally, in India, triple negative breast cancer (TNBC) prevalence is much higher in comparison to the western world. We undertook this study with an aim to characterize TNBC based on a panel of immunohistochemical markers to explore their pathogenesis, behavior, treatment response, and outcomes in respect to disease progression, disease-free survival, and death. The study was approved by Institutional Ethics Committee which included 63 TNBC cases for evaluating expression of GATA3 and p53. Basal cell markers were done only in GATA3 negative cases. The IHC markers were correlated with different clinical profile, demographic factors, and outcome. A total of 63 patients were included in the study out of which 37 patients had disease-free survival; 8 patients showed disease progression; and 18 patients died. Among the patients, 29 were GATA positive. Out of those 29 patients, 15 were also p53 positive. Among 34 GATA3 negative cases, 32 showed expression of at least one basal cytokeratin marker, and 13 were also showed p53 expression. Among clinical factors tumor size (OR = 0.37; 0.15–0.81; P = 0.01), and tumors of grade III (OR = 0.02; 0.001–0.22; P = 0.004) showed significant association with reduced survival. BLBC forms a major part of TNBCs in the Indian patients. High tumor grade and large tumor size were significantly associated with reduced disease-free survival. Among immunohistochemistry markers, GATA3 positivity, GATA3 negative with p53 positivity, and CK positive with p53 positive cases showed decreased survival, however, the results were not statistically significant.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13193-024-02141-3.

Introduction

Invasive breast cancer is the most common malignancy in women which accounts for 23% of worldwide cancers in women [1]. Breast cancer incidence increases with age and shows significant variation in the incidence in different parts of the world [2]. As per GLOBOCAN 2020 data worldwide, the incidence of breast cancer is 47.8/lac [3, 4]. In India, the age-adjusted incidence of breast cancer has increased from 25.8 to 31.2/lacs in the last decade (2012–2022). Also, in India, mortality-to-incidence ratio is as high as 66 in rural registries, whereas it is as low as 8 in urban registries [3].

Hormone receptor status such as estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor-2 (HER2) are very important both for prognostic and therapeutic purpose and are routinely evaluated in breast carcinoma. Hormonal profile of breast carcinoma is very crucial in deciding neoadjuvant and adjuvant therapy. Similarly, ER and PR positive breast cancers show better response to chemotherapy and overall have good prognosis in comparison to TNBC and Her2 positive tumors. Recently, triple-negative breast cancers (TNBCs), defined by the lack of ER, PR, and HER2 receptor expression, have been enormously explored owing to their poor outcomes and lack of targeted treatment. Literature suggests that breast cancers with different histological and immunohistochemical features exhibit distinct behaviors which lead to different treatment outcomes and should be given different therapeutic strategies [5]. A grouping system based on pathological characteristics and hormone expression status can be used to segregate these tumors into different prognostic and therapeutic categories. Multiple classification systems are advised for breast carcinoma based on genetic, pathological, and hormonal pattern. However, the pioneer studies conducted by Sørlie et al. classified breast tumors into five intrinsic subtypes with distinct clinical outcomes, such that luminal A, luminal B, HER2 over-expression, and basal and normal-like tumors [6]. The rational underlying such classification is that the differences underlying the gene expression patterns among cancer subtypes reflect the fundamental differences of the tumors at the molecular level [7, 8]. Among these molecular subtypes, basal-like breast cancers (BLBCs) have aggressive behavior and poor outcome as compared with other subtypes. They account for 15 to 19% of all breast cancers [6, 7]. The BLBCs show negative or weak expression of ER, PR, and HER2, while positive expression of genes associated with basal cytokeratins (CK5/6, CK17, and CK14), nestin, p-cadherin, and other cellular proliferation genes [9, 10]. Though, there is analogy between TNBCs and BLBCs in respect to aggressive clinical presentation, histomorphological features, and molecular profile; but these two groups of tumors are distinct and cannot be used interchangeably or synonymously [11].

Although about 90% of the TNBCs turned out to BLBC cases but 18 to 40% of BLBCs did not show triple negative immunohistochemical profile [12]. TNBCs have more heterogeneous response to therapeutic interventions as well as targeted therapies than BLBCs [13]. This heterogeneity and unpredictable responses in TNBCs led to several researches which tried to further sub-classify these tumors based on their molecular profile. Many researchers have used a cocktail of basal CKs and epidermal growth factor receptor (EGFR) to segregate BLBCs from the rest of the TNBCs [11, 14, 15]. Lehmann et al. [16] further divided TNBCs into six different subgroups based on genomic expression profiling (GEP), namely basal-like 1 and 2 subtypes; immunomodulatory subtype; mesenchymal and mesenchymal stem-like subtypes; and luminal androgen receptor subtype. However, the actual differences in clinical behavior and prognosis among these subtypes are yet not fully understood. Some of the luminal breast cancer cases may be falsely labeled as TNBCs due to inter-laboratory and inter-observer variations in the interpretation of immunohistochemistry (IHC), and heterogeneous expression of triple markers in different areas of tumor which actually bear better prognosis. GATA3 and FOX1A are other sensitive luminal markers which can be used to identify such cases [17]. We undertook this study to explore the molecular profile, histological correlation, and outcomes of TNBCs using surrogate IHC markers suggested for GEP in patients presenting at our Institute.

Materials and Methods

This is a prospective cohort study involving primary TNBC cases diagnosed at our institute over a period of 2 years, from 11.03.2020 to 10.03.2022. TNBCs are defined as tumors with negative expression of ER, PR, and HER2 as per the American Society of Clinical Oncology (ASCO)/College of American Pathologists (CAP) guidelines [18, 19]. The study is approved by Institutional Ethics Committee (974/IEC-AIIMSRPR/2019). A written informed consent was obtained from all the patients.

The cases not fulfilling the inclusion criteria’s such that recurrent cases, inadequate tissue in paraffin block and patients not willing to give consent were excluded from the study.

Immunohistochemistry

Tumor samples received in neutral buffered formalin and were routinely processed and paraffin embedded. Five-micron-thick sections were cut for IHC. For immunohistochemical staining, streptavidin–biotin conjugate immunoperoxidase method was used, after appropriate antigen retrieval wherever required. Immunohistochemical studies were performed using antibodies directed against ER (Diagnostic BioSystems, dilution, 1:100), PR (Diagnostic BioSystems, dilution, 1:100), Her2/neu (Diagnostic BioSystems, dilution, 1:100), GATA3 (Diagnostic BioSystems, RTU), p53 (Diagnostic BioSystems, RTU), CK14 (Diagnostic BioSystems, RTU), CK17 (Diagnostic BioSystems, RTU), and CK5/6 (BioGenex, RTU). Labeled streptavidin biotin kit (Universal) was used as a detection system (Dako, Denmark). Antigen retrieval was performed in a microwave oven using citrate buffer at pH 6.0 for all antibodies.

For each batch, appropriate positive controls were taken and for negative controls, primary antibodies were omitted. All the cases were initially subjected to GATA3 antibody. The cases with positive GATA3 staining were considered as luminal type and were further analyzed for the expression of P53. GATA3 negative cases were considered as BLBCs and evaluated for the expression of basal markers CK5/6, CK14, CK17, as well as p53 (Fig. 1).

Fig. 1.

Immunohistochemistry images showing a GATA3 nuclear positivity, b p53 nuclear positivity, c CK5/6 membranous and cytoplasmic positivity, d CK14 membranous and cytoplasmic positivity, and e CK17 membranous and cytoplasmic positivity (each × 200)

GATA3 scoring was done as score 0: < 10% positivity, score 1: 10–25%, score 2: 25–50%, and score 3: > 50%. For CK5/6, CK14, and CK17, any cytoplasmic and membrane staining of > 1% tumor cells was considered positive. p53 scoring was done as score 1: score 0: < 10% positivity, score 1: 10–25%, score 2: 25–50%, and score 3: > 50%.

Treatment

In breast cancer, the role of NACT is defined in the patients in whom upfront surgery is not possible (large tumor: breast tissue ratio, multiple lymphadenopathies, or higher stage) or in selected patients, for conversion of radical surgery into breast conservation surgery for better cosmesis. In such patients, NACT is followed by surgery and then on the basis of final histopathology reports (stage, grade, and hormonal status) adjuvant chemotherapy is delivered. In TNBC patients, there is no role of adjuvant hormonal therapy or therapy directed towards Her2neu receptor. Radiation therapy is given as per recommendations to all the patients, when indicated.

Ten patients received four cycles of adriamycin and cyclophosphamide based neoadjuvant chemotherapy, every 3 weekly and then underwent surgical management. Out of 63 patients, 41 received four cycles of adriamycin and cyclophosphamide-based adjuvant chemotherapy every 3 weekly and then four cycles of paclitaxel-based chemotherapy every 3 weekly. Twelve out of 63 patients received loco-regional radiotherapy with a dose of 50 Gy in 25 fractions, five times a day.

Statistical Analysis

The data is presented as mean and percentage for continuous and categorical variables. Multiple logistic regression was used for association of variables with the poor outcome. The poor outcome was defined as the patients who died or have shown progression of disease. Survival analysis was performed using Kaplan–Meier curve. P value < 0.05 was considered statistically significant.

Results

Demographic and Clinical Characteristics

Total 324 breast cancer patients reported between 11.03.2020 and 10.03.2022 at the Institute of which 63 were found to be of TNBC type constituting 19.4% of total cases. The mean age of patients was 49.4 years (28–75 years) (Table 1). Patients (77.8%) were < 60 years of age, while only 22.2% patients were in ≥ 60 year’s age group. Majority of patients were in post-menopausal phase (60.3%). Only one patient had a positive family history of carcinoma breast in sister. Upper outer quadrant (UOQ) was the predominant site of involvement noted in 47.6% of cases followed by upper inner quadrant (UIQ) in 15.8% cases. In 8 (12.6%) patients, more than one quadrant was involved, of which two had involvement of the entire quadrant. Majority of the patients had tumor size ≥ 5 cm with mean duration of illness at the time of presentation was approximately 7 months (Table 1). Neoadjuvant chemotherapy (NACT) was given to 10 (15.8%) patients, of which four showed disease progression, three died during the course of treatment and three had disease-free survival till last follow-up (mean follow-up period of 15 months). On histopathology, most cases were invasive breast carcinomas, not special type (NST), except three cases with medullary features (high grade nuclei, syncytial growth, tumor infiltrating lymphocytes, and pushing borders) and one case each of invasive lobular carcinoma and metaplastic carcinoma with squamous differentiation (Fig. 2). All the 07 patients in NACT group, who showed either disease progression or died, had a tumor size ≥ 5 cm. Hence, tumor size ≥ 5 cm may be an independent poor prognostic factor, which can be further validated in large sample size. Adjuvant chemotherapy (AdjCT) was administered in 41 patients, of which 12 patients subsequently received radiotherapy (RT). One patient had metastatic disease, received RT without CT, and later died during the course of treatment. Follow-up was available in 59 patients varying from 80 to 819 days with a mean of 405 days. Four patients were lost to follow-up. At last follow-up, 37 patients had disease-free survival; 8 patients showed disease progression; and 18 patients died.

Table 1.

Demographic and clinical characteristics of patients

S. no	Characteristics	Values
1	Age (years)	49.4*
2	Locality	Urban: 34 Rural: 29
3	Side of involvement	Right: 31 Left: 32
4	Site	Single quadrant: 55 Multiple quadrant: 08
5	Size (cm)	6.2*
6	Duration of illness (months)	7.1*
7	Tumor grade	Grade II: 24 Grade III: 39
8	Chemotherapy	Yes: 41 No: 22
9	Menopausal status	Premenopausal: 25 Postmenopausal: 38

*Presented as mean

Fig. 2.

Histological images showing a invasive breast carcinoma, medullary pattern with dense tumor infiltrating lymphocytes, pushing margins, and peritumoral lymphoid follicles (arrow) (HE × 20); b invasive lobular carcinoma with Indian file pattern arrangement of tumor cells and perineural invasion (arrows) (HE × 200); c invasion into dermal lymphatics (HE × 100); and d invasive breast carcinoma with lymphovascular invasion (HE × 200); and e invasive breast carcinoma infiltrating into deep muscle (HE × 20)

Predictors of Survival

The factors associated with disease-free survival were analyzed. The patients of postmenopausal group (OR = 0.10; 0.005–1.43), belonging to rural locality (OR = 0.65; 0.12–3.17), having tumor origin in right side breast (OR = 0.71; 0.12–3.76), multiple quadrants (OR = 0.42; 0.02–6.68), presented with more duration of illness (OR = 0.93; 0.75–0.99), and not receiving chemotherapy (OR = 0.56; 0.08–3.69) had reduced disease-free survival, but these findings were not statistically significant. The age was also not a predictor of poor outcome (OR = 1.05; 0.94–1.19; P = 0.34). Modified Bloom Richardson’s grade 3 tumors had statistically significant reduced disease-free survival in comparison to grade 2 tumors (OR = 0.02; 0.001–0.22; P = 0.004).

The size of tumor (OR = 0.37; 0.15–0.81) and grade (OR = 0.02; 0.001–0.22) were significant predictor of reduced disease-free survival (Table 2). GATA3 positivity was noted in 29 cases with concurrent p53 positivity in 15 cases. Among 34 GATA3 negative cases, 32 showed expression of at least one basal cytokeratin (CK5/6, CK14, and CK17) marker and 13 of which also showed p53 positivity. The GATA3 positive patients were associated with poor outcome (OR = 0.58; 0.21–1.6). The p53 expression in GATA3 negative patients also correlated with poor outcome (OR = 0.41; 0.09–1.69); however, similar findings were not observed in patients expressing p53 who were GATA3 positive (OR = 2.7; 0.61–12.98). The cases with both CK positivity and p53 expression showed poor survival (OR = 0.38; 0.08–1.64). Although, the mentioned IHC markers showed an association with decreased overall survival; however, results were not significant which is likely due to small sample size (Table 3). Based on the results, GATA3 and p53 seem to be predictor of poor outcome. The two cases of 7-negative phenotype (7NP) such that negative for both GATA3 and cytokeratins showed disease-free survival.

Table 2.

Different predictors of disease-free survival in the study

S. no	Patient characteristics	Odd’s ratio, 95% confidence interval	P-value
1	Age	1.05 [0.94 to 1.19]	0.34
2	Locality (rural)	0.65 [0.12 to 3.17]	0.59
3	Side (right)	0.71 [0.12 to 3.76]	0.69
4	Site (multiple quadrant)	0.42 [0.02 to 6.68]	0.52
5	Size	0.37 [0.15 to 0.81]	0.01*
6	Duration of illness	0.93 [0.75 to 0.99]	0.24
7	Grade 3	0.02 [0.001 to 0.22]	0.004*
8	No chemotherapy	0.56 [0.08 to 3.69]	0.53
9	Post-menopausal	0.10 [0.005 to 1.43]	0.10

*Statistically significant

Table 3.

Immunohistochemistry markers and their correlation with disease-free survival

S. no	IHC categorization	Odd’s ratio, 95% confidence interval	P-value (chi-square test)
1	GATA3  + Positive  − Negative	0.58 (0.21–1.6)	0.3
2	GATA3 positive p53  + Positive  − Negative	2.7 (0.61–12.98)	0.19
3	GATA3 negative p53  + Positive  − Negative	0.41 (0.09–1.69)	0.22
4	CK positive P53  + Positive  − Negative	0.38 (0.08–1.64)	0.20

The survival proportion was estimated in cases negative for GATA3 and expressing p53. The patients expressing p53 were likely to have decreased overall survival compared to patients who were not expressing p53 (hazard ratio 1.60; 95% CI 0.38–6.6) (Fig. 3a). The survival proportion was also estimated in the cases with CK positivity and p53 expression. The cases expressing p53 were likely to have decreased overall survival compared to patients who were not expressing p53 (hazard ratio 1.68; 95% CI 0.40–7.1) (Fig. 3b). However, due to the wider CI, the result should be interpreted cautiously.

Fig. 3.

Kaplan–Meier survival curve showing relationship between a p53 expression and outcome in GATA3 negative cases and b p53 expression and outcome in CK positive cases

Discussion

This is a prospective cohort study in TNBC patients correlating various clinicopathological parameters and immunohistochemistry markers with the survival. We have classified the TNBC cohort into three groups luminal-like, BLBCs, and 7NP based on GATA3 and basal cytokeratin expressions. Further, p53 IHC was also done in all the cases to look for its relationship with the survival.

GATA3 is an important transcription factor which plays a pivotal role in the morphogenesis of mammary gland and maintains luminal epithelial differentiation; hence, it serves as a defining marker for luminal subtype of breast cancers [20, 21]. Wilson et al. [21] in their meta-analysis reported that both ER-α and GATA3 are co-expressed with ER-α-associated genes. FOXA1 is another important transcription factor which acts as downstream target for GATA3 and enhances the binding of ER-α with chromatin. Furthermore, the chromatin binding activities of GATA3 and FOXA1 are relatively independent of estrogen action; hence, GATA3 and FOXA1 can mark epithelial genes and for downstream estrogen regulation [22, 23]. Initially, we have included FOX1A in the study; however, due to troubleshoot, it was omitted.

Therefore, a network comprising transcription factors GATA3, FOXA1, ER-α, and estrogen constitutes main proliferation and outcome signal for luminal A group of breast cancer [24]. GATA3 mutation can independently disrupt this network by causing redistribution of FOXA1 and ER-α transcription factors [23]. Based on the fact that all the TNBC cases do not correspond to core BLBC, heterogeneous expression of triple markers and a very close genetic mapping and linking between GATA3 and ER-α, we assumed that TNBC cases showing GATA3 expression should still be considered under luminal subtype of breast cancer. Thus, we applied GATA3 IHC to all the cases in the study and subsequently only GATA3 negative cases were further subjected to core basal markers CK5/6, CK14, and CK17. Though many studies reported GATA3 as good prognostic marker, some did not find any correlation of GATA3 expression with the outcome. We also did not find any significant differences in the outcome of patients in respect to GATA3 expression.

Among 34 GATA3 negative TNBC cases, 32 (94.1%) were turned out to be core basal type with expression of at least one basal marker. This result is similar to the study conducted by Sable et al. [11], who reported 91.2% TNBC cases to be of core BLBC type. However, the rate of occurrence of core BLBC cases among TNBCs in non-Indian patients is much lower and varies from 56 to 84% [15]. The definition of BLBC case identification based on IHC is not standardized. Various studies in the literature suggest a different combination of a set of markers in their panel for defining BLBC cases. However, most of them used a group of cytokeratins with or without EGFR. We have also included three cytokeratins (CK5/6, CK14, and CK17) with EGFR, however, due to technical error in performing EGFR IHC; it was omitted from the study. This panel of markers also varies in sensitivity and specificity; hence a wise selection is very important for accurately sub-classifying TNBC cases. Nielson et al. [25] used EGFR with CK5/6 and Thieke et al. [26] used combination of CK14, EGFR, and high molecular weight cytokeratin (HMWCK). They have reported sensitivity of 76% and 78%, respectively with 100% specificity. In our study, CK5/6 showed best sensitivity (96.8%), followed by CK14 (68.7%), while CK17 (53.1%) turned out to be least sensitive basal marker. Sable et al. [11] reported a sensitivity of 84.4%, 53.4%, and 69.5% for CK5/6, CK14, and CK17, respectively, in their study. The sensitivity of CK5/6 is much better in our study. Only one case which was not picked up by CK5/6 showed CK14 positivity. Hence, CK14 and CK17 in this study were non-beneficial and proved no additional benefits in identifying core BLBC cases, except single case. Shao et al. [27] also found CK5/6 as more sensitive marker in comparison to CK14 for BLBC. The cutoff for cytokeratins’ positivity in the literature ranges from any positive cytoplasmic staining to 20% of tumor cells [28]. In this study, we considered cytoplasmic and membranous staining of > 1% tumor cells as positive for cytokeratins.

Korsching et al. [29] reported that CK5/6 expression in breast cancer is linked with expression of EGFR, Ki-67, p53, and increased cytogenetic abnormalities. Different studies have variable observations regarding expression of p53 and outcome in breast carcinoma patients [30, 31]. We have found p53 expression as an independent factor for poor survival; however, the results were not statistically significant.

Most investigators used 10% of nuclear staining in tumor cells as the cutoff value for p53 positivity [32]. We have also considered 10% of nuclear staining in tumor cells as the cutoff for p53 positivity. A small percentage of cases may not fit into any particular group and negative for all the markers. We have identified two cases in this series accounting for 5.8% of the cases which is comparable to 8.8% cases reported by Sable et al. [11]. These cases are rarely associated with BRCA1 mutation and show better disease-free survival in comparison to core BLBC [14, 15]. Both the cases in this series also showed a disease-free survival at the last follow-up.

The likelihood of occurrence of breast cancer increases with the age; however, in India, the incidence of early onset breast cancer is very high. In India, breast cancer has relatively early occurrence than western countries with a peak at 40–50 years of age [33]. In this series, the mean age at presentation was 49.3 years which correspond to other Indian studies [3]. Furthermore, early onset breast cancer behaves more aggressively with advanced stage at presentation and frequently carrying triple negative phenotype [34]. Thangjam et al. [35] suggested that younger women have more dense breast tissue which is less amenable for routine screening leading to large palpable tumor frequently with nodal involvement at the time of presentation. In India, patients usually present at advanced or metastatic stage at the time of diagnosis. As per literature-TNBC is highly invasive and approximately 46% of TNBC patients will have distant metastasis [36, 37]. We found even higher number (65%) patients presented at advanced stage with largest tumor dimension ≥ 5 cm at the time of presentation. The tumor size was noted as a significant independent poor prognostic factor (P value 0.01). Delayed presentation attributed by various demographic factors such as illiteracy, poor healthcare facilities, lack of awareness, economic constraints, and social taboos leading to advanced stage at the time of diagnosis which increases mortality rate. We found long duration of illness at the time of presentation as an important factor resulting in decreased disease-free survival (OR = 0.93; 0.75–0.99). As there is a direct relationship between younger age breast carcinoma patients and triple negative phenotype, in India, prevalence of TNBC is much higher in comparison to the western world [38, 39]. TNBC tends to be larger in size, locally advanced and show high grade histological features [40]. Nagrani et al. [41] reported a low risk of developing breast cancer in people living in rural areas as compared to urban population which is mainly attributed to the lifestyle. We also found higher number of patients belonging to urban regions with a better survival in comparison to rural patients; however, it was not statistically significant.

Breast cancer, is known for its intra-tumoral heterogeneity. Although, in most cases they can be classified into different groups’ however, they differ in outcome because of tumor heterogeneity. Due to its special molecular phenotype, TNBCs are not sensitive to endocrine therapy or molecular targeted therapy. Hence, personalized medicine has an important role in the treatment of breast carcinoma. Additionally, various current studies on new CD marker expression will be helpful for prognostication and possible therapeutic intervention in invasive breast carcinoma and of interest in the field of target therapy [42]. The study with the CD4/CD8 ratio at the tumor-host interface was significantly associated with both relapse-free survival and overall survival [42]. A universal uniform scoring system for different IHC markers, standard definitions for molecular classification, and addition of new markers is need of the hour for standardized routine utilization of IHC-based molecular classification.

To conclude, immunohistochemistry is an important adjunct in resource poor setting for classification of breast carcinoma with relatively similar prognostic and predictive information as gene expression profiling. High tumor grade and large tumor size were significantly associated with reduced disease-free survival. Among immunohistochemistry markers, GATA3 positivity, GATA3 negative with p53 positivity, and CK positive with p53 positive cases showed decreased survival; however the results were not statistically significant. p53 is a good prognostic marker in BLBC patients which predicts poor outcome. BLBC forms a major part of TNBCs in the Indian patients. In India, breast cancer show early age onset, higher TNBC frequency, and locally advanced stage at the time of diagnosis.

Limitations

This is an IHC-based prospective study involving a limited number of breast carcinoma patient’s result of which needs further validation in a larger cohort with gene expression profile correlation.

Supplementary Information

Below is the link to the electronic supplementary material.

Author Contribution

Dr. Rakesh K Gupta, MD: concept of work, drafting, intellectual content, and finer editing; Dr. Alok Singh, MD: statistical analysis and intellectual content; Dr. Siddhartha Nanda, MD: clinical work-up, follow-up, and literature review; Dr. Debajyoti Mohanty, MS: surgical work-up and literature review; and ⁵Dr. Yashwant Kashyap, MD, DM: clinical work-up, follow-up, and literature review.

Funding

The source of financial support was from Intramural research grants (No. 22/41/2019/Admin/403), All India Institute of Medical Sciences, Raipur.

Data Availability

The original data set is available with the corresponding author.

Declarations

Ethics Approval

The study is approved by the Institutional Ethics Committee (974/IEC-AIIMSRPR/2019).

Conflict of Interest

The authors declare no competing interests.