Literature DB >> 36094928

Association between epidemiological and clinico-pathological features of breast cancer with prognosis, family history, Ki-67 proliferation index and survival in Tunisian breast cancer patients.

Najah Mighri1, Nesrine Mejri1,2, Maroua Boujemaa1, Yosra Berrazega2, Haifa Rachdi2, Houda El Benna1,2, Soumaya Labidi1,2, Farouk Benna3, Samir Boubaker1,4, Hamouda Boussen1,2, Sonia Abdelhak1, Yosr Hamdi1,4.   

Abstract

Breast cancer has different epidemio-clinical characteristics in Middle East and North-African populations compared to those reported in the Western countries. The aim of this study is to analyze the epidemiological and clinico-pathological features of breast cancer in Tunisia and to determine prognostic factors with special interest to family history, Ki-67 proliferation index and comorbidity. We retrospectively reviewed epidemiological and clinico-pathological data from patients' medical records, treated in the Medical Oncology Department at Abderrahmane Mami Hospital, in the period 2011-2015. Data has been collected on 602 breast cancer patients and analyzed using SPSS software V.23.0. Our study showed high fractions of young breast cancer patients and cases with dense breasts. The most prevalent comorbidities observed in the studied cohort were cardiovascular diseases and diabetes. Familial breast cancer was found in 23.3% of cases and was associated with younger age at diagnosis (p<0.001) and advanced stage (p = 0.015). Ki-67 index >20% was significantly associated with early age at diagnosis, lymph node involvement (p = 0.002), advanced tumor grade (p<0.001) and high risk of relapse (p = 0.007). Ki-67 cut-off 30% predicted survival in luminal cases. Survival was worse in patients with triple negative breast cancer compared to non-triple negative breast cancer, inflammatory breast cancer compared to non-inflammatory breast cancer, moderately to poorly differentiated tumors compared to well-differentiated tumors and with positive lymph nodes compared to pN0 (p<0.05). Our study showed new insights into epidemiological and clinico-pathological characteristics of breast cancer that are not well explored in Tunisian population. Considering our findings along with the implementation of electronic health record system may improve patient health care quality and disease management.

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Year:  2022        PMID: 36094928      PMCID: PMC9467370          DOI: 10.1371/journal.pone.0269732

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.752


Introduction

Breast cancer is the most common malignancy among women and the first leading cause of cancer death in women worldwide, with 2.1 million new cases and 626.679 deaths predicted in 2018 [1]. In Tunisia, breast cancer represents 31.4% of all female malignancies with 2305 annual diagnosed cases in 2018 and with an incidence of 32.2 per 100.000 inhabitants making it a major public health concern [1]. Based on the latest World Health Statistics reports, breast cancer represents also the first cause of death from cancer among Tunisian females [2]. This heterogenous disease is characterized by several clinical and histological forms [3]. Indeed, large differences have been observed in the age of onset, stages at presentation, clinical manifestation and prognosis of breast cancer between various countries, mainly between Middle-East and North African breast cancer women and breast cancer patients from Western populations [4, 5]. Epidemio-clinical studies of breast cancer in Tunisia were mainly focused on breast cancer in young women [6-9], inflammatory breast cancer [10-12], prognostic factors for relapse [13, 14], survival [15-17] and the prognosis of molecular subtypes [18-20]. Indeed, Tunisian population was characterized by a younger age of onset of breast cancer when compared to Western countries and by a relatively high incidence rate among young patients under 35 years representing around 11% of all breast cancer cases in the country [21]. In addition, a high frequency of aggressive forms such as triple negative (TNBC) and inflammatory breast cancers (IBC) was also observed [5]. One of the strongest risk factors for breast cancer that is not well explored in Tunisian population is the presence of a positive family history of breast and ovarian cancers which has long been thought to indicate the presence of a strong inherited genetic component that predispose to the disease and to predict clinical characteristics and outcomes [22-25]. In addition, Ki-67 index which is a predictive and diagnostic biomarker that plays a significant prognostic role [26, 27], is not well studied in Tunisian breast cancer patients. Moreover, no Tunisian studies have studied comorbidities observed in breast cancer cohorts, although literature data showed that comorbidities negatively impacts overall breast cancer prognosis [28]. The aim of this report was to investigate epidemio-clinical characteristics of breast cancer in Tunisian population with special interest in clinico-pathological features and prognostic factors associated with familial breast cancer (FBC) cases. We also aimed to assess the clinico-pathological parameters associated with Ki-67 index value, comorbidities and survival among the studied cohort.

Material and methods

Patients

We retrospectively reviewed a cohort of 602 patients with histologically confirmed breast cancer treated in the period between 2011 and 2015, in Medical Oncology Department of “Abderrahmen Mami” Hospital which is the second national reference center for chemotherapy and radiation in Tunisia, with dedicated multidisciplinary teams. Data were collected from patient’s medical record. The study was conducted according to the declaration of Helsinki and with the approval of the biomedical ethics committee of Institut Pasteur de Tunis (2017/16/E/Hôpital A-M). The need for consent has been waived by ethics committee, while ensuring additional data protection measures that preserve patient anonymity.

Data collection

Several clinico-pathological parameters were investigated in this study including: age and delay at diagnosis (time between symptoms self-reported by patients and final histological diagnosis of breast cancer), age at menarche, parity, age at first delivery, breastfeeding, oral contraceptive use, menopausal status, breast density, body mass index and comorbidities. Furthermore, consanguinity and data including information on family history of breast and ovarian cancers and other malignancies were also recorded. All patients had a biopsy with complete immunohistochemical evaluation before the initiation of any systemic therapy. TNM classification was based on reported clinical evaluation. In addition, clinico-pathological parameters have been collected including tumor size, lymph node involvement, Scarff-Bloom-Richardson (SBR) grade, hormone receptors and HER2 status, Ki-67 index, treatment type, relapse, outcome. Patients with metastatic disease were excluded. Ki-67 (Clone MIB-1 (DAKO) dilution 1/100) was used for the automated immunohistochemical technique. The assessment procedure was manually performed on 10 fields using high magnification (x400). All the pathologists of the department were used to the estimation and evaluation of the ki-67 index. There was no centralized assessment and data was based on what was reported from multiple labs. In order to determine if there are special epidemiological and/or clinico-pathological differences between familial and sporadic breast cancer cases, we classified our cohort into two subgroups. The selection of familial cases was based on several criteria mainly the family history of breast and ovarian cancers and the age at diagnosis; patients were selected if at least one of the following criteria was fulfilled: (1) The patient was diagnosed with breast cancer before the age of 36 years, (2) The patient was diagnosed with triple negative breast cancer regardless of age, (3) The patient has at least two first or second-degree relatives with breast cancer, (4) The patient has at least two first or second-degree relatives with breast or ovarian cancer regardless of age, and at least one case of pancreatic or prostate cancer. Secondly, in order to study the correlation of Ki-67 index with the clinicopathological features and its survival prediction in the luminal breast cancer group, we used several Ki-67 cut-off points (14%, 20%, 30% and 50%). Authors evaluated these cut-offs based on previously published data [29]. Ki67 is already well studied in the literature as a continuous variable. Intrinsic subtype classification into Luminal A, Luminal B and Triple negative was based on immuno-histochemical criteria.

Statistical analysis

Statistical analyses were performed using the Statistical Package for Social Sciences (SPSS Inc., Chicago, IL, USA) Version 23.0. Data were summarized by numbers and percentages for categorical variables, mean and range for continuous variables. Logistic regression was performed to evaluate prognostic factors. The assessment of the association between familial breast cancer status, young age at onset, Ki-67 cut-off levels and prognostic factors was performed using Khi2 test or Fisher test. An independent t-test was used to compare the means of two studied groups. We evaluated the prognostic value of several cut-off levels of Ki-67 in terms of overall survival (OS). We also considered different subgroups according to axillary lymph node involvement: pN0, 1-3pN+ and ≥4pN+. Survival curves were dressed according to the Kaplan-Meier analysis and compared with the log-rank test. All p-values were two-sided, and p<0.05 was used to indicate a statistically significant difference.

Results

A total of 602 patients with a histologically proven breast cancer have been included in this study. Epidemiological features and clinico-pathological characteristics of the studied population were presented in S1 and S2 Tables. The collection of these epidemiological and clinico-pathological parameters allowed us to set up an electronic database in the Oncology Department of Abderrahmane Mami hospital, which facilitates the storage, retrieval modification, the management of patients medical records and their follow-up.

Epidemiological features

Among breast cancer patients that participated in the current study, 54.6% were premenopausal. At the time of their breast cancer diagnosis, 4.8% of patients were nulliparous and 2.9% were pregnant. Mean age at menarche was 12.9±1.618 years. Mean age at first childbirth was 25.9±10.727 years. 72.15% have received oral contraception and 22.6% of patients have never breastfed. According to the Breast Imaging-reporting and Data System (BI-RADS) classification, 56% of patients had dense breasts. Obesity defined by BMI ≥30kg/m2 was seen in 28% of cases. We considered comorbidities known to be associated with breast cancer from the literature such as diabetes, hypertension, dyslipidemia, metabolic syndrome and rheumatologic diseases. Most prevalent comorbidities observed in our breast cancer cohort were cardiovascular diseases (50.78%) and diabetes (18.32%). 25.3% of patients were from consanguineous families. Familial cases represented 23.3% of breast cancer patients. The family history of ovarian cancer was observed in as few as 2% of patients. In addition, personal history of cancer was found in 2% of the studied patients (S1 Table). All patients were Tunisian without other ethnicity groups presented.

Clinicopathological features

The mean age at diagnosis of breast cancer was 48.7±11.417 years (ranging from 22 to 83 years) and 13.4% of patients were ≤35 years. The mean diagnostic delay was 8 months and 39% of patients reported a delay in diagnosis of 6 months or less before their first consultation after the onset of symptoms. Mean clinical tumor size at diagnosis was 38.95 mm. Locally advanced tumors (T3, T4) were seen in 21.6% of patients. Data for histological tumor type showed that invasive ductal carcinoma (IDC) was the most frequent (91.4%) while infiltrating lobular carcinoma (ILC) was observed in 2.7% of cases. The presence of the intraductal component was observed in 50% of breast cancer patients. Multifocality defined as the presence of 2 or more separate invasive tumors was noticed in 29.7% of cases. Upper outer and upper inner quadrants were mostly affected in 47.3% and 13.1% of patients, respectively. SBR grade II was the most frequent (53.1%). Approximately, 50% of patients were diagnosed with lymph node positive disease. The median Ki-67 value was 30% (range, 1–90%). Luminal B was the most common subtype (46.26%) followed by luminal A (27.95%), TNBC (15.47%), and HER2+ (10.32%). Luminal B patients with HER2 negative disease represented 35.9% (S2 Table). Distant metastases at diagnosis were observed in 14.5% of patients. Among non-metastatic cases, 21.7% have relapsed and the most frequent sites of relapses were bones and lungs.

Treatment of breast cancer cases

Nearly 34.5% of patients had tumorectomy and 65.5% had mastectomy. Neoadjuvant chemotherapy (CT) was performed in 124 cases (14%) and adjuvant chemotherapy was performed in 406 patients (67.9%). From 406 patients who received adjuvant chemotherapy, 83.6% had sequential Epirubicin and Taxane-based chemotherapy. 83.4% received adjuvant radiation therapy with a mean dose of 55 Gray. Three hundred and sixty-two patients (67.9%) had adjuvant hormonal therapy: 212 started with tamoxifen and 149 with aromatase-inhibitors. From patients whose tumors overexpressed the HER2 biomarker, 84.2% received Trastuzumab. The following part of our report will be devoted to the study of particular epidemio-clinical parameters mainly family history, early onset disease (≤35 years), Ki-67 proliferation index, comorbidity and survival.

Comparison of epidemiological characteristics and clinico-pathological features between familial and sporadic breast cancer patients

Familial breast cancer has been observed in 139 out of 596 patients (23.3%) (Table 1). There was a significant difference in the distribution of age at diagnosis among familial and sporadic breast cancer cases (mean 42.46 vs 50.63 years) (Table 1). Indeed, familial breast cancer cases were significantly younger than sporadic patients (p<0.001). Furthermore, familial breast cancer patients were more likely to be premenopausal (p = 0.001). A delay in diagnosis was observed in sporadic cases (9.47 months) when compared to familial cases (6.19 months) but no significant difference between the two groups was observed. No significant differences have been also observed between the two groups in histological subtype, nodal status, SBR grade, hormonal receptors status, HER2 receptor expression, Ki-67 index, metastases, and relapse status. However, a statistically significant difference was observed regarding intraductal component (p = 0.027) and a significantly high tumor stage was noted among familial cases (p = 0.048) (Table 1).
Table 1

Comparison of epidemiological and clinicopathological parameters between familial and sporadic breast cancer patients.

VariablesFamilial casesSporadic casesP value*
N = 139N = 457
Mean age at diagnosis (years) 42.46±11.95150.63±10.587 <0.001
Mean diagnostic delay (months) 6.199.470.187
Menopausal status
Premenopausal 93/138 (67.39)228/451 (50.55) 0.001
Postmenopausal 45/138 (32.61)223/451 (49.45)
Breast density
Dense breasts 15/28 (53.57)45/79 (56.96)0.756
Non-dense breasts 13/28 (46.43)34/79 (54.43)
Histological type
IDC 126/139 (90.65)418/457 (91.47)0.896
ILC 5/139 (3.6)11/457 (2.40)
MC 5/139 (3.6)17/457 (3.72)
Other 3/139 (2.15)11/457 (2.41)
Histological grade status
Grade I 13/134 (9.7)49/444 (11.04)0.889
Grade II 71/134 (52.99)236/444 (53.15)
Grade III 50/134 (37.31)159/444 (35.81)
T stage
T1-T2 82/112 (73.21)311/399 (77.94) 0.048
T3 16/112 (14.29)28/399 (7.02)
T4 14/112 (12.5)60/399 (15.04)
Intraductal component
Yes 40/99 (40.40)185/349 (53) 0.027
No 59/99 (59.6)164/349 (47)
Nodes involvement
N+ 63/118 (53.39)230/388 (59.28)0.257
N- 55/118 (46.61)158/388 (40.72)
Ki-67 index status
Ki-67 ≤20% 43/105 (40.95)169/398 (42.46)0.780
Ki-67>20% 62/105 (59.05)229/398 (57.54)
Molecular subtypes
Luminal A 40/138 (28.99)126/457 (27.57)0.247
Luminal B 68/138 (49.27)208/457 (45.51)
HER2+ 8/138 (5.80)54/457 (11.82)
TNBC 22/138 (15.94)69/457 (15.10)
ER status
ER+ 105/137 (76.64)327/457 (71.55)0.241
ER- 32/137 (23.36)130/457 (28.45)
PR status
PR+ 93/137 (67.88)289/457 (63.24)0.320
PR- 44/137 (32.12)168/457 (36.76)
HER2 status
HER2+ 42/138 (30.43)151/4560.556
HER2- 96/138305/456
Metastatic status
M0 118/138 (85.51)390/456 (85.53)0.996
M1 20/138 (14.49)66/456 (14.47)
Relapse
Yes 38/131 (29)89/401 (22.19)0.112
No 93/131 (71)312/401 (77.81)

* Fisher’s exact test is used instead of Khi2 test if one or more variables had an expected frequency of less than five.

Abbreviations: IDC = Invasive Ductal Carcinoma; ILC = Invasive Lobular Carcinoma; MC = Mixed carcinoma; ER = Estrogen Receptor; PR = Progesterone Receptor; HER2 = Human Epidermal Growth Factor Receptor2; TNBC = Triple Negative Breast Cancer.

* Fisher’s exact test is used instead of Khi2 test if one or more variables had an expected frequency of less than five. Abbreviations: IDC = Invasive Ductal Carcinoma; ILC = Invasive Lobular Carcinoma; MC = Mixed carcinoma; ER = Estrogen Receptor; PR = Progesterone Receptor; HER2 = Human Epidermal Growth Factor Receptor2; TNBC = Triple Negative Breast Cancer. Overall survival did not differ between non-metastatic familial and sporadic cases (p = 0.242) (Fig 1).
Fig 1

Kaplan Meier estimates overall survival according to familial breast cancer status.

Blue line represents sporadic and green line familial cases.

Kaplan Meier estimates overall survival according to familial breast cancer status.

Blue line represents sporadic and green line familial cases.

Clinico-pathological features of breast cancer in young patients aged ≤35 years

Our results showed, early onset breast cancer patients (≤35 years) accounted for 13.4% of the total breast cancer cases. A statistically significant difference in diagnostic delay between young (≤35 years) and older (>35 years) patients was observed (p = 0.038). Older patients had longer delays in diagnosis than young patients (more than 6 months). However, no significant differences have been observed between the two age groups in molecular subtypes, hormonal receptors status, HER2 status, nodal involvement, SBR grade, Ki-67 index, metastases and relapse (Table 2).
Table 2

Comparison of clinico-pathological features between 2 age groups (breast cancer patients ≤35 years and >35 years).

VariablesBC patients (≤35 years)BC patients (>35 years)P value*
N = 80N = 516
Diagnostic delay (6months)
Yes 15/56 (26.79)133/321 (41.43) 0.038
No 41/56 (73.21)188/321(58.57)
Histological grade status
Grade I 5/76 (6.58)57/502 (11.35)0.182
Grade II 37/76 (48.68)269/502 (53.59)
Grade III 34/76 (44.74)176/502 (35.06)
Intraductal component
Yes 22/56 (39.29)203/393 (51.65)0.083
No 34/56 (60.71)190/393 (48.35)
Nodes involvement
N+ 35/69 (50.72)259/438 (59.13)0.188
N- 34/69 (49.28)179/438 (40.87)
Molecular subtypes
Luminal A 24/79 (30.38)142/516 (27.52)0.619
Luminal B 34/79 (43.04)242/516 (46.90)
HER2+ 6/79 (7.59)55/516 (10.66)
TNBC 15/79 (18.99)77/516 (14.92)
ER status
ER+ 55/78 (70.51)377/516 (73.06)0.638
ER- 23/78 (29.49)139/516 (26.94)
PR status
PR+ 50/78 (64.10)332/516 (64.34)0.967
PR- 28/78 (35.90)184/516 (35.66)
HER2 status
HER2+ 23/79 (29.11)168/515 (32.62)0.534
HER2- 56/79 (70.89)347/515 (67.38)
Metastatic status
M0 69/79 (87.34)439/515 (85.24)0.622
M1 10/79 (12.66)76/515 (14.76)
Relapse
Yes 23/73 (31.51)106/458 (23.14)0.122
No 50/73 (68.49)352/458 (76.86)

* Fisher’s exact test is used instead of Khi2 test if one or more variables had an expected frequency of less than five.

Abbreviations: ER = Estrogen Receptor; PR = Progesterone Receptor; HER2 = Human Epidermal Growth Factor Receptor2; TNBC = Triple Negative Breast Cancer.

* Fisher’s exact test is used instead of Khi2 test if one or more variables had an expected frequency of less than five. Abbreviations: ER = Estrogen Receptor; PR = Progesterone Receptor; HER2 = Human Epidermal Growth Factor Receptor2; TNBC = Triple Negative Breast Cancer.

Correlation between Ki-67 proliferation index and clinicopathological features of breast cancer and its role in predicting survival in luminal breast cancer

In order to evaluate the value of Ki-67 as a prognostic marker in Tunisian breast cancer patients and to analyze its association with several clinicopathological parameters, we used different Ki-67 cut-off points. Ki-67-high tumors (>20%) were significantly associated with early onset age of breast cancer (p = 0.002), lymph node involvement (p = 0.002) (pN0 vs pN+), high SBR grade (p<0.001) (Grade I vs Grade II-II), ER negativity (p = 0.001), PR negativity (p<0.001), and with positive HER2 receptor (p = 0.001). Furthermore, breast cancer patients with Ki-67 higher than 20% exhibited higher incidence of relapse than those with Ki-67 less than 20% (p = 0.007). Moreover, a statistically significant difference was observed between Ki-67>20% and delayed diagnosis for up to 6 months (p = 0.004) (Table 3).
Table 3

Correlation between Ki-67 expression and clinicopathological features in breast cancer patients.

VariablesKi-67 ≤20%Ki-67>20%P value*
N = 216N = 293
Early age at onset
≤35 years 12/216 (5.56)41/293 (14) 0.002
>35 years 204/216 (94.44)252/293 (86)
Delayed diagnosis (6 months)
Yes 67/142 (47.18)57/182 (31.32) 0.004
No 75/142 (52.82)125/182 (68.68)
Histological type
IDC 193/216 (89.35)269/293 (91.81)0.694
ILC 6/216 (2.78)7/293 (2.39)
MC 11/216 (5.09)9/293 (3.07)
Other 6/216 (2.78)8/293 (2.73)
Histological grade status
I 36/213 (16.90)16/286 (5.59) <0.001
II- III 177/213 (83.1)270/286 (94.41)
Intraductal component
Yes 93/178 (52.25)108/218 (49.54)0.592
No 85/178 (47.75)110/218 (50.46)
Lymph node involvement
N+ 97/197 (49.24)153/238 (64.29) 0.002
N- 100/197 (50.76)85/238 (35.71)
Massive lymph node involvement
>3N+ 33/97 (34.02)80/153 (52.29) 0.005
<3N+ 64/97 (65.98)73/153 (47.71)
ER status
ER+ 174/216 (80.55)196/293 (66.89) 0.001
ER- 42/216 (19.44)97/293 (33.11)
PR status
PR+ 160/216 (74.07)173/293 (59.04) <0.001
PR- 56/216 (25.93)120/293 (40.96)
HER2 status
HER2+ 51/215 (23.72)110/293 (37.54) 0.001
HER2- 164/215 (76.28)183/293 (62.46)
Metastatic status
M0 198/215 (92.09)243/293 (82.94) 0.003
M1 17/215 (7.91)50/293 (17.06)
Relapse
Yes 32/204 (15.69)67/257 (26.07) 0.007
No 172/204 (84.31)190/257 (73.93)

* Khi2 test was conducted.

Abbreviations: IDC = Invasive Ductal Carcinoma; ILC = Invasive Lobular Carcinoma; MC = Mixed carcinoma; ER = Estrogen Receptor; PR = Progesterone Receptor; HER2 = Human Epidermal Growth Factor Receptor2.

* Khi2 test was conducted. Abbreviations: IDC = Invasive Ductal Carcinoma; ILC = Invasive Lobular Carcinoma; MC = Mixed carcinoma; ER = Estrogen Receptor; PR = Progesterone Receptor; HER2 = Human Epidermal Growth Factor Receptor2. Ki-67 expression is used for subdividing luminal breast cancers into luminal A and luminal B groups which tend to grow slowly and have a good prognosis compared to non-luminal breast cancer. In order to evaluate the cut-off value of Ki-67 that predicted survival in the luminal breast cancer group and to investigate its survival impact according to axillary lymph node involvement, we retrospectively selected early breast cancer cases with HR positive tumours. Median Ki-67 value was 28%. Median follow-up was 38 months. In the overall population of luminal breast cancer, we only observed a significant difference in OS with the Ki-67 cut-off of 30% (67 vs 64 months, p = 0.04, HR = 2.76 95% CI [0.89–3.73]). In node negative and in 1-3pN+ positive tumors, there was no significant impact on the survival for different Ki-67 cut-off values. In ≥4pN+ group, where patients with Ki-67>50% had significantly worse OS compared to patients ≤50% (63 vs 30 months, p = 0.01, HR = 11.6 95% CI [1.5–16]) (Table 4).
Table 4

Ki-67 cut-offs predicting survival in overall luminal breast cancer tumours.

All luminal breast cancer group (M median survival)N01–3 pN+≥4 p N+
Ki-67 cut-offM p HR [CI]M p HR [CI]M p HR [CI]M p HR [CI]
≤14% 680.330,41 [0.09–0.82]690.891.18 [0.1–13]610.450.2 [0.3–9.2]640.190.35 [0.1–12]
>14% 67645959
≤20% 670.361.63 [0.57–4.63]700.770.7 [0.6–7.8]650.263.27 [0.3–31]670.442.46 [0.2–22]
>20% 66585256
≤30% 670.042.76 [0.89–3.73]690.81.36 [0.2–15]650.412.27 [0.3–16]630.056.8 [0.7–9.3]
>30% 64595255
≤50% 650.212.07 [0.66–6.53]560.651.97 [0.7–4.7]610.971.36 [0.4–13]630.0111.6 [1.5–16]
>50% 65535430

Abbreviations: M = Median; HR = Hazard Ratio, CI = Confidence Interval.

Survival data were dressed according to the Kaplan-Meier analysis and compared with the log-rank test.

Abbreviations: M = Median; HR = Hazard Ratio, CI = Confidence Interval. Survival data were dressed according to the Kaplan-Meier analysis and compared with the log-rank test.

Comorbidities and breast cancer

The most prevalent comorbidities observed in our breast cancer cohort were cardiovascular diseases (50.78%) and diabetes (18.32%). This study shows that women older than 35 years at the time of their breast cancer diagnosis, had more prevalence of comorbid conditions than younger breast cancer patients (p<0.001). However, no association has been identified between comorbidities and relapse among breast cancer patients (p = 0.075). Similarly, comorbidity was not significantly associated with overall survival in breast cancer patients (p = 0.079) (Fig 2).
Fig 2

Kaplan Meier estimates overall survival according to comorbidity status.

Blue line represents non-comorbid patients and green line comorbid cases.

Kaplan Meier estimates overall survival according to comorbidity status.

Blue line represents non-comorbid patients and green line comorbid cases.

Survival in non-metastatic breast cancer patients

Several clinico-pathological factors that could affect survival of women diagnosed with non-metastatic breast cancer have been assessed such as: grade, stage, molecular subtypes, HR status, HER2 status, Ki-67 expression, and nodes involvement. Our findings showed that overall survival was worse in patients with TNBC (p<0.001) compared to non-TNBC, IBC (p = 0.024) compared to non-IBC, moderately to poorly differentiated tumors (p = 0.013) compared to well-differentiated tumors and with lymph node involvement (p = 0.018) compared to pN0.

Discussion

Breast cancer is a major public health challenge in low and middle income countries (LMICs). In this paper, we described work in progress to develop the first breast cancer database in Tunisia. In fact, the development of this database represents a first step towards the implementation of electronic medical records systems to support safe and standardized cancer care in low-resource settings. In addition, to ensure collection of data relevant to breast cancer phenotypes, a standardized data collection instrument was developed in order to facilitate the harmonization of data which have not been collected in a harmonized way. These outcomes will help improving the quality and efficiency of cancer care and facilitate communication between healthcare personnel, researchers, and patients. This database includes clinico-pathological features of 602 Tunisian breast cancer cases that have been investigated in the current study. The mean age at diagnosis of breast cancer patients was 48.7 years. This result is similar to those described in previous studies on breast cancer in Arab women and different from that reported in patients from Western countries [30, 31]. Inflammatory and triple-negative breast tumors were found among 5.35% and 15.5% of patients, respectively. These proportions of aggressive breast cancer forms are different from those described in previous Tunisian studies (TNBC = 22.5%, IBC = 7–10%) [12, 18, 32] and could be considered as an update of latest data on these breast cancer forms in Tunisian population. Furthermore, our results were different to those described in several other populations, such as Western and Sub-Saharan Africa where TNBC accounts for 27% to 61% of cases. For IBC, it represents 2% of breast cancer in Europe and USA, lower than that reported in North Africa and Tunisia (5–10%) [33, 34]. Furthermore, a delayed diagnosis for up to 6 months after first detection of a breast mass has been observed among 39% of patients. Large mean tumor size, high proportions of T3 and T4 stages, lymph nodes involvement and patients diagnosed with distant metastases were observed. All these characteristics are considered as factors associated with late diagnosis of breast cancer. These results showed that despite large awareness campaigns running in Tunisia, breast cancer is still shrouded in secrecy and is still considered a taboo for several socio-cultural reasons. In our study, luminal B cancer was more prevalent (46.27%) than luminal A (28%). This result is in discordance with previous Tunisian studies [18, 19] which could be explained by the heterogeneity of breast cancer even in different cohorts drawn from the same country. The Inclusion of HER2 positive cases in luminal B groups could also be an explanation. In addition, our results are in discordance with previous studies conducted in several countries all over the world including Algeria [35], Egypt [36], Japan [37] and the USA [38]. Although, other studies conducted in Saudi Arabia and Italy found luminal B subtype more common than luminal A [39, 40]. This variation in the distribution of breast cancer molecular subtypes could be explained by the fact that different cut offs value of Ki-67 index are used for the stratification of luminal breast cancer groups across the world which may lead to misclassification bias. In Tunisian population, the Ki-67 index which is one of the most controversially discussed breast cancer biomarkers [41, 42], was not well investigated. Therefore, we evaluated its clinical significance as a prognostic marker and we analyzed its association with clinico-pathological parameters in breast cancer patients as well as its role in predicting survival among the luminal breast cancer group. Our results demonstrated that there was a statistically significant difference between the 2 groups (Ki-67≤20%) and (Ki-67>20%) regarding a set of parameters. Tumor with Ki-67>20% showed the poorest prognosis; early age at onset, advanced tumors grade, positive node involvement, high risk of relapse (p<0.05). In accordance with our results, other studies found that a higher Ki-67 index is significantly correlated with positive lymph nodes [43, 44], an increased risk of recurrence [45], a high grading [43] and an early age at onset [46]. In our study, higher Ki-67 expression (>20%) was also more frequently associated with HR-negative and HER2-positive tumors. This result was in agreement with studies who reported that a higher Ki-67 index significantly correlated with HER2-positive breast tumors [41, 43] and negatively correlated with HR positivity [47]. Additional analyses performed in the present study demonstrated that Ki-67 index predicted survival with a cut-off value of 30% in the overall luminal breast cancer group and 50% in ≥4pN+ studied tumors. Previous report demonstrated that a Ki-67 index with a cut-off (≥20%) is significantly correlated with poorer prognosis and early recurrence, particularly in luminal A type tumors [43]. Therefore, our study is first to evaluate Ki67 association with clinico-pathological features and outcome among Tunisian breast cancer patients and significant associations were observed. According to these results high levels above 30% could be used to classify tumors into Luminal B, but the data does not confirm that a Ki67 below 30% can be interpreted as luminal A. Furthermore, due to the lack of external validation study, caution should be used when implementing this cut-off as an independent marker; all other clinico-pathological parameters should also be considered when evaluating the prognosis of any given patient. Tumour location was higher in the upper outer quadrant (UOQ) (47.3%). Indeed, tumour location is highest in the UOQ (50–58%) across multiple populations [48] and the high proportion of UOQ carcinomas of the breasts reflects the greater amount of breast tissue in this quadrant [49]. Apart from the characteristics of breast cancer described above, several risk factors such as coexistence of chronic diseases at the time of breast cancer diagnosis are reported. This comorbidity potentially affects the stage at diagnosis, treatment, and outcomes of cancer patients [50]. In our study, no association has been revealed between relapse, survival and comorbidity and most of the comorbid conditions are chronic diseases such as cardiovascular diseases, diabetes and metabolic syndrome which are partly associated with a non-healthy lifestyle behavior. These results can be considered as a form of bias and could be explained by the fact that oncologists usually ask for these particular diseases while they do not ask about other hereditary conditions related to breast cancer, such as Li-Fraumeni, Fanconi anemia, Ataxia telangiectasia and Lynch syndrome which may have an effect on the diagnosis, treatment decision, disease evolution and family healthcare which may explain the few fraction of patients with family history of ovarian cancer that could be underestimated in the studied cohort. Moreover, family history of breast cancer is an established risk factor for the development of the disease [22, 51]. In our study, familial cases represented 23.3% of all breast cancer patients. We based our classification on anamnestic and clinical parameters as well as tumour subtype not on genetic testing. Nevertheless, about 5–10% of all breast cancer cases are thought to be familial. The high fraction of FBC identified in our study could be explained by the special and specific genetic architecture of Tunisian population such as the high consanguinity and endogamy rates. Our results also showed that familial breast cancer seems to affect young and premenopausal women. Similarly, other reports noted a significantly higher frequency of premenopausal women among FBC patients [52, 53] and demonstrated that women with family history were more likely to be diagnosed at an earlier age [54, 55]. Several studies have revealed that FBC has some specific clinical features such as bilateral breast cancer, advanced stage, lymph node involvement and negative hormone receptors compared to sporadic cases [56, 57]. Our study has shown that FBC cases were significantly younger than sporadic patients and were diagnosed at later stages (T3). Rising awareness about the importance of the BRCA1/2 genetic testing among Tunisian patients with a strong family history of breast and/or ovarian cancer will eventually lead to early disease detection. In our study, 13.4% of patients were ≤35 years. This fraction is higher than that reported previously in Tunisia (11%) [21] and this is a brand new update of breast cancer in young Tunisian patients. Compared to older patients, young women generally face more aggressive cancers [58, 59]. In our study, we observed that patients over the age of 35 had longer delays in diagnosis when compared to young patients. Although most breast cancers occur at older ages, young patients may be more prone to screening procedures and self-examination due to their implication in awareness campaigns. In the current study, we highlighted the epidemio-clinical specificities of breast cancer among Tunisian patients with special focus on parameters that were not well investigated in previous Tunisian studies. However, other crucial parameters were not explored in our study due to some missing data such as geographical origin, place of residence, socio-economic and educational level. Results on other parameters like breast density were not conclusive due to the lack of precise scores generated from automated technique for measurement of volumetric mammographic density that were absent in our country. In this study, we propose to use a new form model (S1 File) by the oncologists during the first consultation which contains more details regarding the family history of cancers, consanguinity and comorbidities with special interest to rare hereditary diseases. To summarize, to the best of our knowledge, the present study is the first to assess the association of familial breast cancer, and Ki-67 index with clinico-pathological characteristics and prognostic factors of breast cancer in Tunisian population. We demonstrated that clinico-pathological profile of familial cases differs from sporadic patients. We also showed that Ki-67 cut-off >20% may be considered as a valuable biomarker in Tunisian breast cancer patients and can be used in their follow-up. This biomarker predicted survival with a cut-offs value of 30% in luminal breast cancer patients and 50% in this same group with more than 4pN+. These cut-offs should be more investigated to select patients for adjuvant therapy. The identification of clinico-pathological specificities and prognostic factors of breast cancer in Tunisia will contribute to a better management of the disease and for better health outcomes.

Conclusions

Our study investigated clinico-pathological features of breast cancer that were not well studied in Tunisian population. Our findings show that despite the influence of awareness efforts conducted in Tunisia and advanced screening and detection techniques, the disease remains undetected until it reaches advanced stages. Based on our results, a multidisciplinary approach needs to be employed with implementation of electronic health records systems in order to promote health care coordination and communication. We further recommend more breast cancer awareness programs targeting all medical oncology stakeholders such as radiologists, pathologists and geneticists.

Epidemiological features of breast cancer patients.

(DOCX) Click here for additional data file.

Clinicopathological characteristics of breast cancer patients.

(DOCX) Click here for additional data file.

Form model proposed for the investigation of epidemiological and genetics features of breast cancer in Tunisia.

(DOCX) Click here for additional data file. 11 Mar 2022
PONE-D-21-23455
Association between epidemiological and clinico-pathological features of breast cancer with prognosis, family history, Ki-67 proliferation index and survival in Tunisian breast cancer patients
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PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: No Reviewer #2: Yes ********** 5. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: The article entitled “Association between epidemiological and clinico-pathological features of breast cancer with prognosis, family history, Ki-67 proliferation index and survival in Tunisian breast cancer patients” tackles an important problem in the Tunisian population. However, some improvements are required before its publication. 1) Could you please deepen the description about the Medical Oncology Department at Abderrahmen Mami Hospital? Is it an important centre for all the country? Just part of it? 2) Could you specify the symptoms you used to define diagnostic delay? Are they self-reported by patients or are they derived from clinical examinations? 3) Could you write again how you performed the selection of familial cases? The criteria are not clear. 4) Could you write again the Statistical Analysis paragraph? You mixed indices to describe variables distribution and statistical test. For continuous variables it is recommended to include also standard deviation, not just the mean. 5) In the Epidemiological Features paragraph you wrote “most prevalent comorbidities associated with breast cancer were…”, which other comorbidities have you considered? You should specify that you considered some comorbidities known to be associated with breast cancer from the literature, but you did not check in your study that association. 6) You should include in tables 1,2, and 3 the tests used to obtain each pvalue (Chi-Square or Fisher Exact or T-test). Pvalues lower than 0.001 should be reported as “<0.001”. Furthermore, it is not clear why there are three pvalues for T stage in table 1. 7) Table 3 reported the association between Ki-67 proliferation index and clinicopathological features of breast cancer, why did you include early age at onset? Could describe it in the main text? 8) I would suggest investigating your own ki-67 cut off predicting survival in overall luminal breast cancer tumours and compare it with those highlighted in the literature. 9) Table 4 is not clear. To which test are the pvalues referred? Reviewer #2: the authors analyzed the epidemiological and clinico-pathological features of breast cancer in Tunisia and to determine prognostic factors with special interest to family history, Ki-67 proliferation index and comorbidity. in this paper, the authors showed new insights into epidemiological and clinico-pathological characteristics of breast cancer in Tunisian population. the study is well done. ********** 6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy. 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Please note that Supporting Information files do not need this step. 5 May 2022 PONE-D-21-23455 Association between epidemiological and clinico-pathological features of breast cancer with prognosis, family history, Ki-67 proliferation index and survival in Tunisian breast cancer patients. PLOS ONE Authors’ Responses: Thank you for giving us the opportunity to submit a revised version of our research paper. We have revised the manuscript according to the journal requirements and the reviewers’ comments and suggestions. All page and line numbers have been included; please refer to the revised manuscript file with tracked changes. Journal Requirements: When submitting your revision, we need you to address these additional requirements. Q1.Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf A1: Thank you for this comment. As recommended, we have revised our manuscript to ensure that it meets all PLOS ONE’s style requirements and the following modifications have been made: File naming: We have made modification on the name of the following supporting file: “S1 File” to “S1_File”. Manuscript body formatting: We have made modification on the style of the title “Survival in non-metastatic breast cancer patients” (18pt font. Figures titles: We have made modification on the figure’s title; we don’t use italics type. Authors: We added “Farouk Benna” as an author. Affiliations: Afficliations’s numbers have been updated after adding the affiliation of Farouk Benna. 3 Department of Radiation Oncology, University of Tunis, Tunis, Tunisia. 4Laboratory of Human and Experimental Pathology, Institut Pasteur de Tunis, Tunis, Tunisia. Additional modifications: Page 3, line65: we added “breast cancer patients from”. Q2. Please provide additional details regarding participant consent. In the Methods section, please ensure that you have specified (1) whether consent was informed and (2) what type you obtained (for instance, written or verbal). If your study included minors, state whether you obtained consent from parents or guardians. If the need for consent was waived by the ethics committee, please include this information. A2: We thank the reviewer for this relevant comment. Indeed, our study does not include minors. Our Institutional Review Board has approved our study which is a retrospective study, so the need for consent was waived by the ethics committee while maintaining patients´anonymity. As suggested, we provided more details regarding participant consent and ethics approval of our study. Page 4, lines 94- 95: “The need for consent has been waived by the ethics committee. However, personal data protection has been respected by preserving patient anonymity”. Q3. We note that the grant information you provided in the ‘Funding Information’ and ‘Financial Disclosure’ sections do not match. When you resubmit, please ensure that you provide the correct grant numbers for the awards you received for your study in the ‘Funding Information’ section. A3: We thank the reviewer to pointing this out. Please consider grant information provided in the ‘Financial Disclosure’ section: “This study was supported by the Tunisian Ministry of Health (PEC-4-TUN) and the Tunisian Ministry of Higher Education and Scientific Research (LR16IPT05 and LR20IPT05)”. We added information regarding the role of funders; “The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript”. As recommended, this has been updated in the ‘Funding Information’ section to match information provided within the ‘Financial Disclosure’ section. Q4. In your Data Availability statement, you have not specified where the minimal data set underlying the results described in your manuscript can be found. PLOS defines a study's minimal data set as the underlying data used to reach the conclusions drawn in the manuscript and any additional data required to replicate the reported study findings in their entirety. All PLOS journals require that the minimal data set be made fully available. For more information about our data policy, please see http://journals.plos.org/plosone/s/data-availability. Upon re-submitting your revised manuscript, please upload your study’s minimal underlying data set as either Supporting Information files or to a stable, public repository and include the relevant URLs, DOIs, or accession numbers within your revised cover letter. For a list of acceptable repositories, please see http://journals.plos.org/plosone/s/data-availability#loc-recommended-repositories. Any potentially identifying patient information must be fully anonymized. Important: If there are ethical or legal restrictions to sharing your data publicly, please explain these restrictions in detail. Please see our guidelines for more information on what we consider unacceptable restrictions to publicly sharing data: http://journals.plos.org/plosone/s/data-availability#loc-unacceptable-data-access-restrictions. Note that it is not acceptable for the authors to be the sole named individuals responsible for ensuring data access. We will update your Data Availability statement to reflect the information you provide in your cover letter A4: Thank you for raising this point. We confirm that all data underlying the findings described on our manuscript are fully available in the main text or provided as supporting information files. Responses to Reviewers’ comments: Reviewer #1: The article entitled “Association between epidemiological and clinico-pathological features of breast cancer with prognosis, family history, Ki-67 proliferation index and survival in Tunisian breast cancer patients” tackles an important problem in the Tunisian population. However, some improvements are required before its publication. Q1) Could you please deepen the description about the Medical Oncology Department at Abderrahmen Mami Hospital? Is it an important centre for all the country? Just part of it? A1: We would like to thank the reviewer for the careful reading of our manuscript and for the constructive comments. As recommended, we have provided more details about the Medical Oncology Department of Abderrahmen Mami Hospital. Page 4, lines 89- 92: ‘’ We retrospectively reviewed a cohort of 602 patients with histologically confirmed breast cancer treated in the period between 2011 and 2015, in Medical Oncology Department of “Abderrahmen Mami” Hospital, Tunisia, which is the second national reference center for chemotherapy and radiation in Tunisia, with dedicated multidisciplinary teams. Data were collected from patients’ medical record”. Q2) Could you specify the symptoms you used to define diagnostic delay? Are they self-reportedby patients or are they derived from clinical examinations? A2: Thank you for pointing this out. Delay in diagnosis is referring to the time between self-reported symptoms and final histological diagnosis of breast cancer and it does not include initiation of therapy. As suggested, we added more clarifications on this point in the method section: Page 4, line 98: “time between symptoms self-reported by patients and final histological diagnosis of breast cancer “. Q3) Could you write again how you performed the selection of familial cases? The criteria are not clear. A3: Thank you for your comment. As recommended, we reviewed the selection criteria of familial breast cancer cases to be more clear. Page 5, lines 111- 119: The selection of familial cases was based on several criteria mainly the family history of breast and ovarian cancers and the age at diagnosis; patients were selected if at least one of the following criteria was fulfilled: (1) The patient was diagnosed with breast cancer before the age of 36 years, (2) The patient was diagnosed with triple negative breast cancer regardless of age, (3) The patient has at least two first or second-degree relatives with breast cancer, (4) The patient has at least two first or second-degree relatives with breast or ovarian cancer regardless of age, and at least one case of pancreatic or prostate cancer”. Q4) Could you write again the Statistical Analysis paragraph? You mixed indices to describe variables distribution and statistical test. For continuous variables it is recommended to include also standard deviation, not just the mean. A4: Thank you for pointing this out. As suggested, we reviewed the statistical analysis paragraph to be more comprehensive and clear (Page5, lines 125-141: ‘’Statistical analyses were performed using the Statistical Package for Social Sciences (SPSS Inc., Chicago, IL, USA) Version 23.0. Data were summarized by numbers and percentages for categorical variables, mean or median and range for continuous variables. Logistic regression was performed to evaluate prognostic factors. The assessment of the association between familial breast cancer status, young age at onset, Ki-67 cut-off levels and prognostic factors was performed using Khi-2 statistical test. An independent t-test was used to compare the means of two groups. We evaluated the prognostic value of several cut-off levels of Ki-67 in terms of overall survival (OS). We also considered different subgroups according to axillary lymph node involvement: pN0, 1-3pN+ and ≥4pN+. Survival curves were dressed according to the Kaplan-Meier analysis and compared with the log-rank test. .All p-values were two-sided, and p<0.05 was used to indicate a statistically significant difference’’. As suggested, for continuous variables, we added standard deviation values. Q5) In the Epidemiological Features paragraph you wrote “most prevalent comorbidities associated with breast cancer were…”, which other comorbidities have you considered? You should specify that you considered some comorbidities known to be associated with breast cancer from the literature, but you did not check in your study that association. A5: Thank you for raising this point. Indeed, based on the literature review, we evaluated the presence of the most prevalent comorbidities known to be associated with breast cancer in our studied breast cancer cohort. Based on the reviewer’s suggestion, we updated information regarding comorbidities in all over the manuscript: Abstract section, page2, line 35: “observed in the studied cohort” instead of “associated with breast cancer”. Results section, page13, lines 255-256: “The most prevalent comorbidities observed in our breast cancer cohort were cardiovascular diseases (50.78%) and diabetes (18.32%)”. Discussion section, Page17, line 366: We deleted “and comorbidities”. Q6) You should include in tables 1,2, and 3 the tests used to obtain each pvalue (Chi-Square or Fisher Exact or T-test). Pvalues lower than 0.001 should be reported as “<0.001”.Furthermore, it is not clear why there are three pvalues for T stage in table 1. A6: Thank you for this comment. We have made the suggested modifications. We provided more details regarding used statistical tests as a footnote in each table. In addition, P values lower than 0.001 were reported as “<0.001” all over the manuscript. In our study, we have compared epidemiological and clinico-pathological parameters between familial and sporadic breast cancer patients. For T stage variable, since there are 3 subgroups (T1-T2, T3 and T4), we have conducted Khi2 statistical test for each subgroup separately to determine in which one there are statistical difference between sporadic and familial cases. However, based on the reviewer’s comment, we updated the statistical test to be more coherent and homogeneous with the other studied parameters (Table1). And we updated, information in table 1 as well as in the results section, page7, lines 196-197: “a significantly high tumor stage was noted among familial cases (p=0.048) (Table1)”. Q7) Table 3 reported the association between Ki-67 proliferation index and clinicopathological features of breast cancer, why did you include early age at onset? Could describe it in the main text? A7: Thank you for this comment. Indeed, the Tunisian population was characterized by a mean age at diagnosis younger than that reported in Western countries and by a relatively high incidence rate among young patients under 35 years. Furthermore, it is well known that young breast cancer patients have a poorer prognosis with high fraction of Ki-67 index. However, in Tunisia, the association between Ki-67 and early age at onset was not evaluated which prompt us to study the association between both parameters. We added further statement with reference in the discussion section, page15, lines 308-310: “In accordance with our results, other studies found that a higher Ki-67 index is significantly correlated with positive lymph node, an increased risk of recurrence, a high grading and an early age at onset ‘’. Q8) I would suggest investigating your own ki-67 cut off predicting survival in overall luminal breast cancer tumours and compare it with those highlighted in the literature. A8: We thank the reviewer for this comment. In fact, based on the literature review, the most debatable Ki-67 cut-offs predicting survival for luminal breast cancer cases are 14% and 20. In the current report, we explored these cut-offs and the 30% and 50% cut-offs and we observed a significant difference in OS with the Ki-67 cut-off of 30% in luminal breast cancer group. Q9) Table 4 is not clear. To which test are the pvalues referred? A9: For the study of Ki-67 cut-offs predicting survival in overall luminal breast cancer tumours (Table 4), we used Kaplan-Meir Method and the p values were derived from Log-Rank test. Information is provided in the method section, page 5, line 139: “Survival curves were dressed according to the Kaplan-Meier analysis and compared with the log-rank test”. We further noted this statement as a footnote in table 4. Reviewer #2: The authors analyzed the epidemiological and clinico-pathological features of breast cancer in Tunisia and to determine prognostic factors with special interest to family history, Ki-67 proliferation index and comorbidity. In this paper, the authors showed new insights into epidemiological and clinico-pathological characteristics of breast cancer in Tunisian population. The study is well done. A1: We would like to thank the reviewer for the time and efforts dedicated to review our manuscript. Submitted filename: Responses to reviewers.docx Click here for additional data file. 27 May 2022 Association between epidemiological and clinico-pathological features of breast cancer with prognosis, family history, Ki-67 proliferation index and survival in Tunisian breast cancer patients PONE-D-21-23455R1 Dear Dr. Hamdi, We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements. Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication. An invoice for payment will follow shortly after the formal acceptance. 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If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation. Reviewer #1: All comments have been addressed ********** 2. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: Yes ********** 3. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes ********** 4. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #1: Yes ********** 5. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: Yes ********** 6. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: I would like to thank the authors for having improved the manuscript. I do not have any additional comments. ********** 7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #1: No 2 Sep 2022 PONE-D-21-23455R1 Association between epidemiological and clinico-pathological features of breast cancer with prognosis, family history, Ki-67 proliferation index and survival in Tunisian breast cancer patients Dear Dr. Hamdi: I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department. If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org. If we can help with anything else, please email us at plosone@plos.org. 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Review 1.  Inflammatory breast cancer in Tunisia: epidemiological and clinical trends.

Authors:  Hamouda Boussen; Hatem Bouzaiene; Jamel Ben Hassouna; Tarek Dhiab; Fathi Khomsi; Farouk Benna; Amor Gamoudi; Nejib Mourali; Monia Hechiche; Khaled Rahal; Paul H Levine
Journal:  Cancer       Date:  2010-06-01       Impact factor: 6.860

Review 2.  Breast cancer in Arab populations: molecular characteristics and disease management implications.

Authors:  Lotfi Chouchane; Hammouda Boussen; Konduru S R Sastry
Journal:  Lancet Oncol       Date:  2013-09       Impact factor: 41.316

3.  Trends and current challenges of breast cancer in Tunisia: a retrospective study of 1262 cases with survival analysis.

Authors:  Imtinene Belaid; Leila Ben Fatma; Faten Ezzairi; Makrem Hochlaf; Imene Chabchoub; Olfa Gharbi; Salma Gahbiche; Moncef Mokni; Abdelfattah Zakhama; Mohamed Bibi; Hedi Khairi; Slim Ben Ahmed
Journal:  Breast J       Date:  2018-05-20       Impact factor: 2.431

4.  Ki-67 as a prognostic marker according to breast cancer subtype and a predictor of recurrence time in primary breast cancer.

Authors:  Reiki Nishimura; Tomofumi Osako; Yasuhiro Okumura; Mitsuhiro Hayashi; Yasuo Toyozumi; Nobuyuki Arima
Journal:  Exp Ther Med       Date:  2010-07-21       Impact factor: 2.447

5.  Multicentricity and histopathological background features of familial breast cancers stratified by menopausal status.

Authors:  T Fukutomi; S Akashi-Tanaka; T Nanasawa; K Matsuo; C Shimizu
Journal:  Int J Clin Oncol       Date:  2001-04       Impact factor: 3.402

6.  Protein expression profile and prevalence pattern of the molecular classes of breast cancer--a Saudi population based study.

Authors:  Dalal M Al Tamimi; Mohamed A Shawarby; Ayesha Ahmed; Ammar K Hassan; Amal A AlOdaini
Journal:  BMC Cancer       Date:  2010-05-21       Impact factor: 4.430

7.  Young age at diagnosis correlates with worse prognosis and defines a subset of breast cancers with shared patterns of gene expression.

Authors:  Carey K Anders; David S Hsu; Gloria Broadwater; Chaitanya R Acharya; John A Foekens; Yi Zhang; Yixin Wang; P Kelly Marcom; Jeffrey R Marks; Phillip G Febbo; Joseph R Nevins; Anil Potti; Kimberly L Blackwell
Journal:  J Clin Oncol       Date:  2008-07-10       Impact factor: 44.544

8.  Descriptive analysis of molecular subtypes in Tunisian breast cancer.

Authors:  Asma Fourati; Hamouda Boussen; Michéle V El May; Aida Goucha; Bouthaina Dabbabi; Amor Gamoudi; Rachida Sfar; Khaled Rahal; Ahmed El May; Mansour Ben Abdallah
Journal:  Asia Pac J Clin Oncol       Date:  2012-11-26       Impact factor: 2.601

9.  Relapse profile of early breast cancer according to immunohistochemical subtypes: guidance for patient's follow up?

Authors:  Nesrine Mejri; H Boussen; S Labidi; F Benna; M Afrit; K Rahal
Journal:  Ther Adv Med Oncol       Date:  2015-05       Impact factor: 8.168

10.  Tumour location within the breast: Does tumour site have prognostic ability?

Authors:  Seth Rummel; Matthew T Hueman; Nick Costantino; Craig D Shriver; Rachel E Ellsworth
Journal:  Ecancermedicalscience       Date:  2015-07-13
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