Determinants of late detection and advanced-stage diagnosis of breast cancer in Nigeria.

OBJECTIVE: To describe the risk factors for late detection and advanced-stage diagnosis among patients who detected their BC early.
METHOD: Using secondary data, we analyzed the impact of socio-demographic factors, premorbid experience, BC knowledge, and health-seeking pattern on the risk of late detection and advanced-stage diagnosis after early BC detection. Test of statistical significance in SPSS and EasyR was set at 5% using Sign-test, chi-square tests (of independence and goodness of fit), odds ratio, or risk ratio as appropriate. RESULT: Most socio-demographic factors did not affect detection size or risk of disease progression in the 405 records analyzed. High BC knowledge, p-value = 0.001, and practicing breast self-examination (BSE) increased early detection, p-value = 0.04, with a higher probability (OR 1.6 (95% CI 1.1-2.5) of detecting <2cm lesions. Visiting alternative care (RR 1.5(95% CI 1.2-1.9), low BC knowledge (RR 1.3(95% CI 1.1-1.9), and registering concerns for hospital care increased the risk of advanced-stage diagnosis after early detection (64% (95% CI 55-72)). Adhering to the monthly BSE schedule reduced the risk of advanced-stage diagnosis by -25% (95% CI -49, -1.1) in the presence of socioeconomic barriers.
CONCLUSION: Strategies to increase BC knowledge and BSE may help BC downstaging, especially among women with common barriers to early diagnosis.

Introduction

Downstaging symptomatic breast cancer (BC) through early detection and diagnosis is a topical issue in sub-Saharan Africa (SSA) because socioeconomic barriers and lack of infrastructure make asymptomatic population-based screening impractical. The patient demographic and presentation patterns also make mammography an ineffective screening tool [1, 2].

Promoting early detection practices and following through with early diagnosis and timely treatment will improve BC outcomes in Africa [1]. Most breast cancers are incidental self-detection in Africa, and up to 80% are diagnosed at stage III or IV, with most patients delaying treatment for more than six months.

There are reports on the risk factors for late presentations in SSA [3-6]. However, direct reports on determinants of late detection among BC patients are rare. The few reports on early detection practices identified in a Black et al. [1] review were in healthcare providers and non-afflicted laywomen. Furthermore, reports on advanced-stage diagnosis failed to distinguish tumors already advanced at the time of detection or recognition from those progressing after early detection. Yet, our previous research showed that late detection and progressing to advanced disease after an early detection contributed differently to advanced-stage diagnosis and challenges of managing BC. In that research, 10% of tumors detected inadvertently were already advanced, while 30–70% of those detected early progressed to advanced-stage before diagnosis [7].

Late detection and progressing after early detection may have different determinants, and understanding the difference might improve cancer education programs’ effectiveness in SSA. This study aimed to describe risk factors for late-stage detection and advanced-stage diagnosis among a subpopulation of BC patients who detected their cancers early.

Materials and method

This research was a secondary data analysis using de-identified data from a study sponsored by the African Research Group for Oncology (ARGO). The original research was a cross-sectional multicentered survey in referral centers in Northcentral and Southwestern Nigeria, including convenience sampling of newly diagnosed BC patients between June 2017 and May 2018 after obtaining ethical approval from all institutions and written consent from participants. The ethical review committee gave additional approval for the current study [UITH ERC PAN/2021/01/0170].

Trained personnel collected the data using specially designed pilot-tested proforma and entered it into a specially designed Microsoft Access database. The primary research instituted mechanisms to minimize recall bias and ensure data reliability. Details of the design and original data collection are available elsewhere [7].

Data of interest in the present research were the demographics and socioeconomic variables, including age, sex, employment status, religion, and marital status. The premorbid experience including the source of BC information, awareness, prior knowledge of BC treatment and outcomes, concern about hospital treatment of BC, and health-seeking pattern: premorbid help-seeking preferences, breast self-examination/ clinical breast examination, number of hospitals, and health care providers (HCP) visited to treat current disease, the initial symptom, tumor size at detection and diagnosis, and reason for referral. The tumor size at detection was a retrospective record, while the size at diagnosis was prospective in the original research.

Statistical analysis

In this analysis, clinical tumor size (T-size) was the surrogate for disease stage using the T1-3 according to the 7th edition of the American Joint Committee on Cancer (AJCC) staging for BC, where T1 was ≤2cm, T2 was 2.1-5cm, and T3 was >5cm. We defined early detection and early diagnosis as size ≤5cm and small tumor as size ≤2cm. To evaluate each risk factor, we analyzed its impact on the T-size distribution, the odds of detecting small tumors (≤2cm), and the probability of being diagnosed early after early detection.

The effect of age was analyzed by comparing three subgroups; <40, 41–60, and >60. Marital status was analyzed as married vs. unmarried (with unmarried comprising single, widows, separated, or divorced). The level of education was analyzed as secondary/tertiary vs. no education/ primary level. Three subgroups of BC Knowledge were compared; no, low and high knowledge. [We defined none as the lack of BC awareness, low as BC awareness only, and high as BC awareness plus any additional information such as knowing screening modalities, types of breast lumps, BC treatment, or outcome of someone who had BC]. Being employed was compared to being unemployed. Living close to the study center (<30 minutes drive) was compared to living remotely (31–60 minutes and >60 minutes). Consulting an orthodox health care provider first was compared to consulting alternative medicine first. Visiting only one healthcare provider (HCP) was compared to visiting more than one HCP, and visiting a single hospital was compared to visiting multiple hospitals before diagnosis.

The inferential statistic for single proportion used the binomial test, comparison of two or more proportions used the chi-square test of independence/ Fisher’s exact or goodness of fit. The risks (probabilities of events) were compared using either the binary logistic regression for the odds ratio or the risk ratio. We presented the results using descriptive statistics, including the 95% confidence intervals (95% CI). We set the test of statistical significance at 5% for all analysis. The analysis was conducted in SPSS v20 and EasyR.

Results

This research included 405 records of patients aged 24–95 (mean 49.3±16, median 49). The majority were middle age (176,43.4%), married (274, 79%), and educated (175, 43.2%). The younger age groups were more educated (p-value = 0.001). The majority (294, 73%) were aware of BC, 162 (55%) of which had low knowledge, and 132 (45%) had high knowledge. The most common source of BC information was a radio program. The younger patients had more BC information (p-value = 0.02) despite similar information sources across all age groups. Many patients obtaining information from non-medics (person-to-person social contacts and media outlets) had high BC knowledge. Fifty-five percent (95% CI 50–60) of the patients reported practicing breast self-examination (BSE), with only 17% (95% CI 12–23) maintaining the standard monthly schedule (Table 1).

Table 1

The patient demographics, distribution of information source, the comparison of level of eduction, practice of breast self-examination and information across age groups, comparison of breast cancer knowledge based on information source and education and distribution of BC knowledge across age groups.

The patient demographics
		N(%)				N(%)
Age	40 & below	103(25)		Marital	Married	274(68)
	41 to 60	176(43)			Divorced	7(2)
	Above 60	70(17)			Widow	43(11)
	NS	56(15)			Single	21(5)
					NS	57(14)
Education	None	44(11)		Religion	Christian	283(70)
	Primary	48(12)			Muslim	108(27)
	Secondary	57(14)			NS	11(3)
	Tertiary	118(29)		Side	left	147(37)
	NS	138(34)			Right	143(36)
					NS	112(27)
Distribution of information source
Social contact/person-to-person	Church	13(3.1)
	Facebook	9(2.2)
	Relations/Friends	41(10)
	School	11(3.0)
Media	Flier	2(0.5)
	Newsprint	3(0.7)
	Radio	76(19)
	Television	21(5.1)
Health talk	Hospital/NGO	49(12)
	NS	180(44.4)
Comparison of the level of education across age groups
	Age distribution (years)			p-value
	40	41–60	>60
Low education	11	43	39	0.001
High education	98	168	47
Comparison of the practice of Breast Self-Examination across age groups
Practice BSE	49	106	28	0.01
Not practice	45	73	45
Comparison of the source of information across age groups
Person-to-person	6	35	10	0.26
media	20	58	23
healthtalk	13	24	7
Comparison of BC knowledge based on the information source
	Person to person	Media	Healthtalk
Low BC knowledge	30	57	33	0.01
High BC knowledge	32	48	11
Distribution of BC knowledge in low education compared to high education
	Breast cancer knowledge
	None	Low	High
Low education	36	36	22	0.02
High education	76	127	109
Distribution of BC knowledge across age groups
≤40	42	41	38	0.02
41–60	48	85	78
>60	25	45	20

BSE- Breast Self Examination, Divorced = Divorced or separated, NGO- Nongovernmental, NS- Not specified Organization, Person-to-person = social and person-to-person contact.

Determinants of tumor size distribution at detection

Common social and demographic factors such as age, level of education, marital status, education level, and employment status did not significantly affect tumor size distribution at detection. The premorbid health-seeking behavior, BC information source, and tumor laterality did not significantly affect tumor size distribution at detection (Table 2). More Christians detected earlier (≤5cm) tumors than Muslims (p-value = 0.001). Women with higher knowledge of BC detected earlier (≤5cm) tumor (p-value = 0.001), and women practicing BSE also detected earlier (≤5cm) tumors (p-value = 0.04) (Table 2). The odds of detecting small tumors (≤2cm) were also significantly higher among women practicing BSE (OR 1.6 (95%CI 1.1–2.5)). However, being educated (low education OR 0.9 (95% CI 0.6–1.1), high education OR 1.4 (95% CI 0.8–2.2) did not significantly affect the odds of detecting small tumors ((≤2cm) compared to being uneducated. Also, being a Christian (OR 1.2 (95% CI 0.8–2.0) did not significantly affect the odds of detecting small tumors compared to being a Muslim. More women with high BC knowledge practiced BSE and adhered to the regular monthly schedule. Tumor laterality did not affect BSE’s impact on the probability of detecting small tumors.

Table 2

The effect of the demographics, premorbid treatment preferences, level of knowledge, and practice of breast-self examination on tumor size distribution at detection.

Also, showing the regularity of Breast Self-Examination based on breast cancer knowledge.

Effect of age on the distribution of tumor size at detection
		T1 n(%)	T2 n(%)	T3 n(%)	p-value
Age	40 and below	52(46)	51(45)	11(9)	0.42
	41–60	80(39)	102(49)	24(11)
	Above 60	30(34)	45(51)	14(15)
Effect of Premorbid treatment preference on the distribution of tumor size at detection
	Alternative	8(27)	14(49)	7(24)	0.17
	Self-medicate	61(46)	60(44)	15(10)
	Visit hospital	71(39)	92(50)	20(11)
Effect of religion on the distribution of tumor size at detection
	Muslim	39(19)	57(26)	111(55)	0.001
	Christian	116(40)	137(46)	35(14)
Effect of breast cancer knowledge on the distribution of tumor size at detection
	No knowledge	42(38)	60(54)	10(8)	0.001
	Low knowledge	61(36)	79(49)	25(15)
	High knowledge	60(45)	59(44)	15(11)
Effect of level of education on the distribution of tumor size at detection
	Low education	32(33)	51(53)	12(12)	0.38
	High education	131(44)	147(47)	38(9)
Effect of employment status on the distribution of tumor size at detection
	Unemployed	5(31)	6(38)	5(31)	0.14
	Employed	81(38)	103(49)	28(13)
	Unmarried	25(35)	34(49)	12(16)	0.24
	Married	114(45)	135(49)	28(6)
Effect of practice of Breast Self-Examination on the distribution of tumor size at detection
Practice BSE	No	58(36)	92(57)	12(7)	0.04
	Yes	93(47)	82(41)	25(12)
BSE schedule	Daily	27(54)	19(38)	4(8)	0.03
	Weekly	4(20)	9(45)	7(35)
	Monthly	14(42)	16(47)	4(11)
	Occasionally	48(47)	38(42)	10(11)
Effect of tumor laterality on the distribution of size at detection
	left	51(34)	81(53)	19(13)	0.21
	right	60(41)	63(43)	22(16)
Effect of information source on the distribution of tumor size at detection
	Person to person	20(32)	31(49)	12(19)	0.42
	Media	46(42)	52(47)	12(11)
	Healthtalk	21(47)	20(43)	5(10)
Comparison of the distribution of tumor size based on the laterality of lesion
		T1n (%)	T2n (%)	T3n (%)	p-value
Among those performing BSE	left	25(42)	27(45)	8(13)	0.33
	Right	35(47)	24(32)	14(21)
Among those on regular BSE	Left	4(29)	8(57)	2(14)	0.32
	Right	6(55)	3(27)	2(18)
Regularity of Breast Self-Examination based on breast cancer knowledge
		No know	Low know	High know
BSE regularity	Occasional	9(10)	16 (18)	64(72)	0.001
	Too frequent	26(35)	43(57)	6(8)
	Standard monthly	1(3)	4(12)	29(85)

Risk factors for tumor progression after early detection

Age, level of education, employment, marital status, and place of residence did not significantly affect the risk of tumor progression after early detection. The pattern of symptomatology, learning about BC from non-medical personnel, and visiting multiple hospitals or multiple health care providers did not significantly affect the risk of tumor progression. First visiting an alternative to orthodox medical care, low BC knowledge, and not practicing BSE were associated with significant risk of progression (Table 3 and Fig 1). Among 79 patients who visited alternative care first, the majority resided close to the referral center (89% (95% CI 80–95). In the same population, 70% of those residing <60 minutes away experienced disease progression whereas a smaller proportion (44% (4 of 9)) of those living remotely experienced disease progression. The difference was not statistically significant (p-value = 0.14). Familiarity with BC patients and knowing poor BC outcomes were not significant deterrents to early-stage diagnosis (Table 3).

Table 3

The effect of the demographics and socioeconomic factors, symptomatology, premorbid preferences, and level of breast cancer information on the risk of disease progression after early detection and the probability of disease progression in the presence of barriers to early presentation.

	Progression	No(n)	Yes(n)	p-value	Risk Ratio (95%CI)
Age
	<40	33	70	0.43	1
	41–60	66	110		0.9(0.8–1.1)
	>60	29	41		0.9(0.7–1.1)
Level of Education
	Educated	105	167	0.16	1
	Uneducated	23	56		1.2(1.0–1.4)
Religion
	Christian	83	162	0.44	1
	Muslim	36	56		0.9(0.9–1.1)
Distance (Drive to study center in minutes)
	0–30	61	79	0.74	1
	31–60	25	40		1.1(0.9–1.4)
	>60	11	13		1.0(0.6–1.4)
Marital Status
	Married	85	159	1.0	1
	Unmarried	20	38		1(0.8–1.2)
Employment Status
	Employed	61	20	0.47	1
	Unemployed	7	4		1.4(0.6–3.5)
Tumor Laterality
	Right	42	48	0.64	1
	Left	81	79		1.1(0.9–1.3)
Tumor size
	<2cm	65	95		1
	>2cm	63	123		1.1(0.9–1.3)
Symptomatology
	lump	33	70	0.97	1
	No lump	84	171		1.0(0.9–1.2)
Health seeking preference
	Visit hospital	68	89	0.007	1
	Self-medicate	36	83		1.2(1–1.5)
	Alternative care	3	18		1.5(1.2–1.9)
Number of Hospital or HCP visited
	1hospital	48	70	0.33	1
	>1hospital	16	35		1.1(0.9–1.5
HCP	1HCP	44	61	0.37	1
	>1HCP	66	118		1.1 (0.9–1.3)
Breast Self Examination
BSE	perform	77	83	0.0003	1
	Not Perform	40	107		1.4(1.2–1.7)
Regularity	Monthly	16	13	0.78	1
	Weekly	7	6		1.0(0.5–2)
	Daily	19	21		1.2(0.7–2)
	Occasionally	35	43		1.2(0.8–2)
Source of BC information
e	Health talk	21	20	0.31	1
	Others	99	141		1.2(0.9–1.7)
Level of Breast Cancer Knowledge
	High knowledge	56	60	0.0002	1
	No knowledge	21	79		1.5(1.2–1.9)
	Low knowledge	51	84		1.3(1.1–1.5)
Previous Interaction With BC Patients
Interaction	No patient known	5	2	0.23	1
	Knows BC patient	13	19		2.0(0.6–7.0)
Outcome known	Alive	4	5	1.0	1
	Died	9	12		1.0(0.5–2.0)
Prompt for Visiting Specialist
Reason	referred	42	73	0.57	1
	self	11	27		1.1(0.9–1.4)
	advice	14	33		1.0(0.8–1.3
The probability of disease progression in the presence of barriers to early presentation
	Subgroups with Barrier (Concerns)	No(n)	Yes(n)		Risk of Progression in subgroup% (95% CI)
	Concern for mastectomy	21	34	0.11	62 (48–75)
	Mastectomy concern in forty years and below	7	15	0.13	68 (45–86)
	Mastectomy concern above 40 years	14	19	0.48	58 (39–75)
	Cost concern	21	41	0.015	66 (53–78)
	Other concerns	11	15	0.56	58 (37–77)

HCP- Health Care Provider.

Other concerns: The attitude of personnel, chemotherapy/fertility, conflicting statements, delay/bureaucracy/stress, death.

Fig 1

Forest plot of risk ratio for disease progression.

Showing the Risk Ratio for disease progression based on demographic, socioeconomic factors, symptomatology premorbid preferences, and knowledge. BC- Breast Cancer, BSE-Breast Self-Examination, HCP-Healthcare Provider, vs = ‘compared to’.

Risk of disease progression after early detection in patients with barriers to early presentation

Subgroup exploratory analysis showed significant risk of disease progression among women expressing any concern (64%(95% CI 55–72). The risk of progression was also significant among those expressing cost concern (67% (95% CI 53–79), whereas the risk was high but not statistically significant among those expressing concern about having a mastectomy (62% (95%CI 42–71) (Table 4 and Fig 2).

Table 4

Showing interaction between practice of BSE and incidence of progression.

Risk of progression among patients with barrier
Concern (N)	No progression	Progression	Risk of Progression (95%CI)	p-value
Any (141)	51	90	64(55–72)	0.001
Mastectomy (49)	21	28	57(42–71)	0.39
Cost (57)	19	38	67(53–79)	0.016
Others (35)	11	24	69(51–83)	0.041
Among those practicing any BSE
Any concern (74)	33	41	54(43–67)	0.42
Mastectomy (27)	14	13	49(29–68)	1.0
Cost (28)	13	15	53(34–75)	0.85
Others (19)	6	13	68(43–87)	0.17
Among those practicing monthly BSE
Any concern (18)	11	7	39(17–64)	0.48
Mastectomy (7)	6	1	14(0.4–58)	0.13
Cost (60	3	3	50(12–88)	1.0
Others (5)	2	3	60(15–95)	1.0
Comparison between those practicing BSE and those not practicing
	No BSE N(progession)	Practice BSE N(progression)	Risk Ratio for progression
Any	67(49)	74(41)	1.32(1.0–1.7)	0.04
Mastectomy	22(15)	27(13)	1.4(0.9–2.3)	0.25
Cost	29(23)	28(15)	1.5(1.0–2.2)	0.05
Others	16(11)	19(13)	1.0(0.6–1.6)	1.0

BSE- Breast Self Examination.

Progression = number progressing from early to an advanced stage before diagnosis.

Risk of progression = number progressing divided by the total number (N).

Fig 2

Forest plot of risk ratio of disease progression among those performing BSE.

Showing Risk Ratio of disease progression among patients not performing Breast Self-Examination compared to those performing Breast Self-Examination.

In patients expressing any concern for hospital care, the risk of disease progression was lower among those practicing BSE (-8.5% (95% CI -22, 5.4) compared to not practicing BSE and more so among those adhering to a monthly routine, with a significantly reduced risk of -25% (95% CI -49, -1.1).

Discussion

Breast cancer causes significant morbidity and mortality in SSA, and much-needed information on late detection and factors associated with advanced-stage diagnosis to improve BC outcomes in SSA is scarce. We researched the risk factors for late detection and advanced stage diagnosis of the disease after early detection. We found that high BC knowledge and practicing BSE were associated with detecting smaller tumors and lowered the risk of progressing to advanced stages before diagnosis. Visiting alternatives to orthodox care and concerns about healthcare costs were associated with disease progression.

The initial breast lump detection mode has prognostic implications; lesions detected by mammography are often smaller with a better prognosis than those seen by BSE [8]. Our finding here suggests that women practicing BSE detected small lumps. BSE’s role is controversial as studies in developed countries [9, 10] showed that it increased the frequency of breast complaints, prompted more visits to physicians, and led to more biopsies without significant benefits in tumor size at detection or survival [11]. Nonetheless, the evidence supporting BSE/ clinical breast examination (CBE) is mounting, especially in centers where BC is detected inadvertently and diagnosed at the late stages [12-15].

Significant gaps exist in our knowledge of how best to improve early presentation and acceptance of BC treatment in SSA. Since population-based screening is not feasible [16] due to economic, infrastructural, and personnel deficiencies, Africa must explore innovative low-cost, and sustainable means of downstaging the disease. A program [12] in Sudan’s rural communities used volunteers in door-to-door breast examination to increase early BC detection. Another research to integrate breast health services into clinical practice in Ghana [17] proposed a model grounded in human interaction and based on the experience of BC patient and their relations whereby trained personnel offered breast cancer information, the teaching of BSE, and CBE to the relations and micro-communities of breast cancer patients [17].

Given that most breast cancer in Africa is self-detected, understanding the BSE barriers and determinants is essential. Factors reported to affect BSE performance are years of college education, knowledge of BSE and its method, perception of the benefit of associating BSE with a likelihood of detecting smaller lesions, longer breastfeeding duration, the pressure of responsibilities, and forgetfulness [18-20].

Strategies to downsize Breast cancer rely on widespread patient-level education, personnel training, and an organized healthcare system [13] to retain patients and complete treatment. Unfortunately, ensuring timely diagnosis and adhering to medical care after disease detection is still a challenge in Nigeria and Africa. Encouragingly, we found that practicing BSE increased the chances of early diagnosis despite known barriers, even among those registering concern for mastectomy and cost of hospital treatment. This suggests that practicing BSE might not only influence early detection; it might also be a predictor of the willingness or motivation to follow through with timely diagnosis and treatment, with the strongest association among women practicing BSE in the standard monthly schedule.

The influence of the common socio-demographic factors on delay varies remarkably within and across regions of Africa. Such factors as age, level of education, marital status, residing remotely, and employment status did not influence detection size and risk of disease progression in the cohort studied here. Nevertheless, these factors merit further research as they often contribute to delay and treatment challenges in SSA.

The influence of symptomatology on delay is fairly consistent in the literature; the absence of breast lump, pain, and ulceration are linked to delays. Recently, the implication of laterality is becoming more apparent. A report in India [21] found right-sided tumors were diagnosed at later stages compared to left-sided tumors, suggesting the impact of handedness. It is reassuring in this study that tumor laterality did not appear to diminish the effect of BSE on detecting small tumors.

Another possibly advantageous exploratory finding pertinent to the challenges of managing BC in poor-resource centers is that receiving information from non-medics might not negatively affect its benefit. Getting comprehensible breast health messages to as many women as possible might be more important than the source. Similarly, A recent report from Uganda found that irrespective of the source, women who received breast health education previously participated more in BSE and CBE [22]. However, there was segregation depending on the place of health care service, with women receiving care in public services preferring messages from healthcare providers. In contrast, those paying out of pocket preferred messages from friends and family.

Africa needs more context-specific interventional research similar to the effort in Sudan [12] using locally trained personnel for CBE and in Ghana [17] intervening on BC patients’ micro-communities using CBE and BSE. Such studies should assess the feasibility, cost-effectiveness, and benefit of the BC down-staging strategies. Simple assumptions or over-generalization of research findings should be avoided in rolling out interventional programs or policies because of unexpected and counterintuitive findings. For instance, family history of BC and history of benign lesions were associated with increased risk of endstage disease [21], negating the expected positive effect of prior knowledge in an Iranian study. Our findings showed significant use of alternatives and a higher proportion of disease progression among those living close to referral centers, thus negating the expected effect of distance.

Being a secondary analysis limits our findings. Also, we did not directly determine that the tumors were detected during BSE, and we did not assess the knowledge of BSE and the method. Furthermore, we could not evaluate the association between detection, time to treatment, and treatment outcome. Notwithstanding, the present report is one of few studies on factors associated with advanced-stage diagnosis in Africa, providing insight into some previously unreported and under-researched associations that might aid down-staging breast cancer in Africa.

Conclusion

Most of the socioeconomic and demographic risk factors commonly influencing late presentation and diagnosis of BC in Africa did not affect early detection or risk of progression among patients who detected their disease early. High knowledge of BC and practicing BSE were consistently associated with early detection and early diagnosis. Additionally, the simple habit of checking the breast might increase early BC detection while adhering to the standard routines of BSE might be associated with detecting even smaller tumors and following through with early diagnosis in the face of common barriers.

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29 Jun 2021

PONE-D-21-10135

Determinants of late detection and advanced-stage diagnosis of breast cancer in Nigeria

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. 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: Partly

Reviewer #2: Yes

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: No

Reviewer #2: Yes

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3. 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: No

Reviewer #2: Yes

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4. Is the manuscript presented in an intelligible fashion and written in standard English?

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Reviewer #1: No

Reviewer #2: Yes

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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: Overall: thank you to the authors for presenting this piece of work. I would however, recommend that more work and care is taken to proof read the manuscript and the way the results are presented.

1. Spelling and grammar for example affiliations should be corrected to “Department” not “department”.

- “… socioeconomic barriers and lack of infrastructure make asymptomatic population-based screening impractical. And, patient demographic and presentation patterns make mammography an ineffective screening tool” – use of ‘and’ at the beginning of the sentence

- Revise where the full stops are placed within the sentence e.g. page 13 full stops are placed before (Table 3) and after as well

2. Results need re-working. As the tables stand now it is hard to understand what is being presented:

- Why are odds ratios presented only for some variables in table 2 and not for all

- Table 1 requires a has marital status on the side without any headings

- The use of (a), (b) etc. in the tables is better replaced by actual sub-headings in the tables so that the reader is not required to go back and forth

- Some p-values are written as p-value = … and others just has the numbers – please be consistent

- What are the p-values for table 3? Symptomatology does not have the reference value of 1 in the table

- What is the risk of progression i.e. how did you arrive at that percentage?

3. Not sure what the legend is supposed to show on page 22

Reviewer #2: 1. percentage of variables are missing in the tables. Authors should provide the percentages in the tables.

2. Page 7: Authors wrote "Fischer’s exact" . It should correct as " Fisher's exact test".

3. Table 3 and 4 are helpful to understand the progression.However, additional to table 3 and table 4, forest plot for OR and RR could be helpful to see risk and to visualize.

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Reviewer #1: No

Reviewer #2: No

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7 Aug 2021

We thank the reviews and editor for taking the time and effort to review and suggest corrections in our manuscript. The suggestions have greatly improved the manuscript.

Kind regards

Reviewer 1 comment Review made in Manuscript Location in manuscript

1 Spelling and grammar corrections Spelling, grammar, and punctuations reviewed throughout the article Throughout the article

Use of “And” to begin sentence not appropriate Sentence reviewed manuscript line 64)

2 Results need re-working to make tables more understandable Result section and all tables reviewed to simplify Results section

Why are odds ratio presented for only a few variables in table 2 Odds ratio presented only for variables with statistically significant analysis. However, the odds ratio has been moved to prose section of the result to maintain uniformity Manuscript line 156-169

Use of letters better replaced with actual headings in tables Letters replaced with actual headings describing each subsection in tables In tables

Presenting of the p-values not uniform p-values presented uniformly through out the article Results section

What is the risk of progression, how did you arrive at that percentage Progression is the number progressing from early to an advanced stage before diagnosis

Risk of progression is number progressing divided by the total number (N)

Description inserted in footnote of table 4

What the legend in page 22 mean They are just legends of the tables, they have been removed

Reviewer 2

1 Percentages missing in tables Percentages included where appropriate in all tables

2 Fischer’s exact should be corrected as Fisher’s exact Corrected Manuscript line 129

3 Present forest plots for the OR and RR values in tables 3 and 4 Forest plots presented as figures 1 and 2

Journal requirements

Review reference list Reference list reviewed and corrected; retracted manuscript not used

Ensure manuscript conforms with journal style Headings reviewed to conform to journal style

Make data available Minimum data available in excel spread sheet

Provide additional information about database used The database was a local simple Microsoft database produced specially for the purpose of the original research Manuscript line 94

Give information on whether data was deidentified and if IRB gave waiver De identified data was used and IRB approval was obtained Manuscript lines 87 and 92

Submitted filename: Response to Review comment August 7 2021.docx

Click here for additional data file.

18 Aug 2021

Determinants of late detection and advanced-stage diagnosis of breast cancer in Nigeria

PONE-D-21-10135R1

Dear Dr. Olayide Agodirin,

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.

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Kind regards,

Shah Md Atiqul Haq

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Dear authors,

Congrtaulations!

The paper is accepted.

Best wishes,

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. 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 #2: All comments have been addressed

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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 #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: 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 #2: 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 #2: 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 #2: (No Response)

**********

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.

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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 #2: No

1 Sep 2021

PONE-D-21-10135R1

Determinants of late detection and advanced-stage diagnosis of breast cancer in Nigeria

Dear Dr. Agodirin:

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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on behalf of

Dr. Shah Md Atiqul Haq

Academic Editor

PLOS ONE