1.1 Disease Burden and Epidemiology Breast cancer stands as the most common malignancy among women globally, affecting over 2.3 million women annually[1]. In India, breast cancer comprises 15.4% of all cancers and accounts for approximately 13.5% of new cancer cases[2]. The age-standardized incidence rate (ASIR) in India ranges from 25–30 per 100,000 women, with an estimated mortality rate of 12–15 per 100,000[2,3]. Unlike developed nations where breast cancer affects primarily postmenopausal women, Indian women present at a younger mean age of 50–55 years, frequently with advanced disease[4]. 1.2 The Delay Paradox in India Over 50–60% of Indian women present with locally advanced (Stage III) or metastatic (Stage IV) breast cancer at initial diagnosis[5]. This late presentation is not inevitable but reflects a complex interplay of delays categorized as: - Patient/Recognition Delay: Time from symptom recognition to first medical consultation (typically ≥3 months)[6] - Diagnostic Delay: Time from first consultation to confirmed diagnosis (typically >4 weeks)[6] - Treatment Delay: Time from diagnosis to initiation of treatment (typically >4 weeks)[6] Studies from North and Central India report median patient delays ranging from 62.4 days (rural) to 42.7 days (urban), with some women delaying >180 days[7,8]. Such delays significantly worsen prognostic stage at diagnosis and reduce overall survival[9]. 1.3 Barriers to Early Presentation and Screening Multiple barrier categories impede timely breast cancer detection in India: Patient-Level Barriers: Lack of awareness about breast cancer signs (only ~20% of Indian women recognize breast lump as concerning)[10], cultural stigma related to breast exposure[11], fear of diagnosis[12], reliance on traditional healers and alternative medicine[13], financial constraints[14], and low health literacy[15]. Provider-Level Barriers: Inadequate training of primary care physicians in clinical breast examination[16], delayed referrals to specialists, misdiagnosis or dismissal of lumps in younger women[17], and unregistered practitioners contributing to diagnostic errors[18]. Health System Barriers: Limited access to diagnostic facilities (mammography, ultrasound) especially in rural and semi-urban areas[19], long waiting times for imaging and biopsy[19], scarcity of trained breast surgeons[20], lack of organized screening programs[21], and fragmented referral systems[22]. 1.4 Rationale and Objectives Jaipur, the capital of Rajasthan with a population >3 million, has emerging tertiary care infrastructure but limited epidemiologic data on breast cancer presentation patterns and delays. Given that Jaipur serves as a referral hub for four districts, understanding local patterns will inform targeted interventions. Primary Objective: To estimate the prevalence of patient delay (≥3 months from symptom recognition to first medical consultation) among women with breast lumps attending General Surgery and OBGY OPDs. Secondary Objectives: 1. To assess diagnostic delay (>4 weeks from first consultation to diagnosis) and factors associated with it. 2. To evaluate awareness regarding breast cancer and screening practices. 3. To identify sociodemographic and clinical predictors of delayed presentation. 4. To describe reasons for delay and healthcare-seeking pathways.

2.1 Study Design and Setting A hospital-based cross-sectional study was conducted at two tertiary care institutions in Jaipur: - Department of General Surgery, SMS Hospital, Jaipur - Department of Obstetrics & Gynaecology, NIMS University, Rajasthan, Jaipur Both institutions serve as referral centers for urban, semi-urban, and rural populations across Rajasthan. 2.2 Study Period and Sample Size Duration: January 2024 to June 2024 (6 months). Sample Size Calculation: Using the formula: n = (Z₁₋α/₂)² × P(1-P) / d² Where: - Z₁₋α/₂ = 1.96 (for 95% CI) - P = 0.706 (proportion of patient delay from published literature)[8] - d = 0.05 (allowable margin of error) n = (1.96)² × 0.706 × 0.294 / (0.05)² = 320 With expected non-response of 10%, final sample size: n = 280 women (150 from General Surgery, 130 from OBGY). 2.3 Eligibility Criteria Inclusion Criteria: - Women aged 18–70 years - Presenting to OPD with chief complaint of breast lump or breast mass - Able and willing to provide informed consent - Resident of Jaipur district for ≥1 year Exclusion Criteria: - Women with known breast malignancy undergoing follow-up - Pregnant women with gestational breast changes - Emergency/in-patient admissions - Refusal to participate 2.4 Data Collection Instrument: A pre-tested, semi-structured questionnaire (Appendix-1) designed to capture: 1.Sociodemographic Data: Age, education, occupation, residence (urban/rural), marital status, parity, socioeconomic status (modified BG Prasad scale). 2. Clinical Presentation: - Duration of lump (in days/months) - Location, size, consistency, fixity - Associated symptoms (pain, discharge, skin changes) - Time from self-recognition to first medical consultation (patient delay) 3. Healthcare-Seeking Pathways: - First point of contact (primary health center, private practitioner, unqualified doctor, traditional healer) - Number of consultations before specialist referral - Time intervals at each stage 4. Diagnostic Delay: - Date of first consultation to specialist (surgeon/gynecologist) - Date of investigations (clinical examination, ultrasound, mammography, fine-needle aspiration cytology/FNAC) - Date of histopathological confirmation (if available) 5. Screening Awareness: - Knowledge of breast self-examination (BSE) - Awareness of clinical breast examination (CBE) - Knowledge of mammography/ultrasound - Prior undergone screening (if any) - Source of health information (media, healthcare provider, family, self) 6. Reasons for Delay: - Fear/anxiety about cancer or medical procedures - Belief in traditional healers or alternative medicine - Lack of awareness about disease severity - Financial constraints - Limited access to healthcare - Family/social restrictions - Denial or minimization of symptoms Data Collection Procedure: Female research assistants administered questionnaires face-to-face in a private clinic room after detailed informed consent. Women were assured of confidentiality. Interviews lasted 15–20 minutes. Clinical information was cross-checked with medical records. 2.5 Operational Definitions Patient Delay: ≥3 months (90 days) from self-recognition of breast lump to first medical consultation[6,8]. Diagnostic Delay: >4 weeks (>28 days) from first specialist consultation to confirmed diagnosis[6]. Screening Awareness: Knowledge of at least one method of breast cancer screening (BSE, CBE, or imaging)[23]. Early Presentation: Patient delay <3 months. Late Presentation: Patient delay ≥3 months[8]. 2.6 Statistical Analysis Descriptive Analysis: - Frequency and percentages for categorical variables - Mean ± SD or median (IQR) for continuous variables - 95% confidence intervals (CI) for proportions Bivariate Analysis: - Chi-square test for categorical associations - Mann-Whitney U test for continuous variables - Logistic regression to identify univariate predictors of patient delay Multivariate Analysis: - Multiple logistic regression to identify independent predictors of patient delay - Variables with p < 0.20 in univariate analysis included in multivariate model - Odds ratios (OR) with 95% CI reported - Model fit assessed using Hosmer-Lemeshow goodness-of-fit test Statistical Software: SPSS version 26.0 (IBM Corp., Armonk, NY). Significance Level: p < 0.05 deemed statistically significant. 2.7 Ethical Considerations The study was approved by the Institutional Ethics Committees of SMS Hospital and NIMS University (Ethics Reference No. SMS-IEC/2023-24/089; NIMS-IEC/2023-24/145). Informed written consent was obtained from all participants. Confidentiality was maintained through anonymization (coded identification numbers). Participants experiencing psychological distress were counseled by trained social workers. Referral to appropriate treatment was facilitated for women with confirmed or suspected breast cancer.

3.1 Sociodemographic Characteristics Among 280 women enrolled, mean age was 45.8 ± 11.2 years (range: 22–69 years). Table-1 presents sociodemographic details. Table 1: Sociodemographic Characteristics of Study Participants (n=280) Characteristic Number Percentage Age Group (years) 2020 32 11.4 3140 68 24.3 4150 98 35.0 5160 62 22.1 >60 20 7.1 Mean age (±SD) 45.8 \u00b1 11.2 Residence Urban 168 60.0 Rural/Semi-urban 112 40.0 Education Illiterate 48 17.1 Primary (15 years) 52 18.6 Secondary (610 years) 96 34.3 Higher secondary & above 84 30.0 Marital Status Married 234 83.6 Unmarried 28 10.0 Widowed/Separated 18 6.4 Parity (among married women, n=234) Nulliparous 24 10.3 12 children 168 71.8 3+ children 42 17.9 Socioeconomic Status (Modified BG Prasad) Class III (Upper) 48 17.1 Class III (Middle) 96 34.3 Class IV (Lower-middle) 84 30.0 Class V (Lower) 52 18.6 Occupational Status Homemaker 182 65.0 Employed 62 22.1 Self-employed 36 12.9 3.2 Clinical Characteristics of Breast Lump Table 2: Clinical Characteristics of Presenting Breast Lump (n=280) Characteristic Number Percentage Duration of Lump <1 month 22 7.9 113 months 60 21.4 336 months 82 29.3 6612 months 74 26.4 >12 months 42 15.0 Median duration (IQR) 180 days (90300 days) Lump Size <2 cm 64 22.9 225 cm 138 49.3 >5 cm 78 27.9 Lump Consistency Soft 48 17.1 Firm 164 58.6 Hard 68 24.3 Fixity Status Mobile 182 65.0 Fixed to muscle/skin 98 35.0 Location Upper outer quadrant 142 50.7 Upper inner quadrant 38 13.6 Lower quadrants 60 21.4 Subareolar 40 14.3 Associated Symptoms Pain 76 27.1 Nipple discharge 28 10.0 Skin dimpling/changes 18 6.4 Axillary lymphadenopathy 42 15.0 None (asymptomatic) 188 67.1 3.3 Patient Delay Table 3: Patient Delay from Symptom Recognition to First Medical Consultation (n=280) Delay Category Number Percentage 95% CI Patient Delay (≥90 days) 198 70.7 65.375.9 Early presentation (<90 days) 82 29.3 24.134.7 Median Patient Delay (days) 120 (IQR: 60180) Delay Duration Categories <1 month 34 12.1 8.516.3 13 months 48 17.1 12.922.0 36 months (90180 days) 96 34.3 28.940.0 612 months 72 25.7 20.831.2 >12 months 30 10.7 7.415.1 Among 198 women with patient delay ≥90 days, 96 (48.5%) delayed 3–6 months, and 102 (51.5%) delayed >6 months. 3.4 Diagnostic Delay Table 4: Time from First Medical Consultation to Confirmed Diagnosis (n=280) Parameter Value Diagnostic Delay >28 days 134 women (47.9%; 95% CI 42.053.8) Diagnostic Delay ≤28 days 146 women (52.1%; 95% CI 46.258.0) Median diagnostic delay (IQR) 21 days (1435 days) Range 390 days Mean diagnostic delay (±SD) 26.3 ± 18.7 days Breakdown of Diagnostic Delay ≤1 week 68 (24.3%) 12 weeks 78 (27.9%) 24 weeks 70 (25.0%) 48 weeks 52 (18.6%) >8 weeks 12 (4.3%) 3.5 Screening Awareness and Practices Table 5: Breast Cancer Screening Awareness and Practices (n=280) Parameter Number Percentage Heard about Breast Self-Examination (BSE) 42 15.0 Ever performed BSE 12 4.3 Aware of Clinical Breast Examination (CBE) 24 8.6 Aware of Mammography 36 12.9 Aware of Ultrasound for breast screening 18 6.4 Overall Screening Awareness (any method) 54 19.3 Ever undergone organized screening 0 0 Ever undergone mammography (for any reason) 8 2.9 Ever undergone ultrasound (for any reason) 16 5.7 Source of Information about breast cancer (multiple responses) Television/media 26 9.3 Newspapers/magazines 8 2.9 Healthcare provider counseling 6 2.1 Family members 14 5.0 Self-reading 4 1.4 No prior knowledge 226 80.7 3.6 Healthcare-Seeking Pathways and Reasons for Delay Table 6: First Point of Contact and Number of Consultations Before Specialist Referral (n=280) Parameter Number Percentage First Medical Contact Private general practitioner 120 42.9 Public health center (PHC/CHC) 48 17.1 Tertiary care hospital (direct) 62 22.1 Unqualified/AYUSH practitioner 34 12.1 Traditional healer 16 5.7 Number of Consultations Before Specialist 1 (direct to specialist) 82 29.3 23 consultations 148 52.9 4+ consultations 50 17.9 Among those with ≥4 consultations, median time to specialist was 150 days. Table 7: Reported Reasons for Delayed Presentation (n=280; Multiple Responses Possible) Reason Number Percentage Psychological Barriers Fear/anxiety about cancer diagnosis 96 34.3 Fear of medical procedures/surgery 44 15.7 Denial/minimization of symptoms 38 13.6 Health Belief Barriers Belief in traditional/herbal treatment 68 24.3 Consultation with AYUSH practitioners first 22 7.9 Reliance on home remedies 32 11.4 Accessibility Barriers Limited access to healthcare facilities 26 9.3 Long waiting times at public hospitals 18 6.4 Socioeconomic Barriers Financial constraints 54 19.3 Cost of investigations 34 12.1 Social/Cultural Barriers Shyness/embarrassment about breast exposure 48 17.1 Family restrictions/opposition 24 8.6 Information Barriers Lack of awareness about disease severity 78 27.9 Not knowing where to seek help 16 5.7 Other Busy with household/work responsibilities 32 11.4 3.7 Bivariate Analysis of Factors Associated with Patient Delay (≥90 days) Table 8: Univariate Logistic Regression—Factors Associated with Patient Delay (≥90 days) Variable Delayed (n=198) Not Delayed (n=82) OR (95% CI) p-value Age >40 years 146 (73.7%) 48 (58.5%) 1.98 (1.143.45) 0.015 Rural residence 86 (43.4%) 26 (31.7%) 1.64 (0.922.93) 0.097 Education ≤primary 92 (46.5%) 20 (24.4%) 2.68 (1.504.81) 0.001 Lower SES (Class IVV) 106 (53.5%) 28 (34.1%) 2.21 (1.243.93) 0.007 No screening awareness 176 (88.9%) 50 (61.0%) 3.94 (2.207.06) <0.001 Lump size <2 cm 58 (29.3%) 6 (7.3%) 5.04 (2.0512.38) <0.001 Asymptomatic lump 158 (79.8%) 30 (36.6%) 6.53 (3.6111.82) <0.001 Belief in traditional healers 62 (31.3%) 6 (7.3%) 5.89 (2.4014.45) <0.001 First contact with non-physician 48 (24.2%) 8 (9.8%) 2.92 (1.366.27) 0.006 Fear/anxiety as barrier 84 (42.4%) 12 (14.6%) 4.11 (2.127.96) <0.001 3.8 Multivariate Logistic Regression—Independent Predictors of Patient Delay Variables with p < 0.20 in univariate analysis were included in multivariate logistic regression model. Table 9: Independent Predictors of Patient Delay (Multivariate Model) Variable Adjusted OR (95% CI) p-value Education ≤primary 3.24 (1.78591) <0.001 Lower SES (Class IVV) 1.86 (0.96360) 0.068 Rural residence 2.87 (1.52542) 0.001 No screening awareness 4.12 (2.15789) <0.001 Lump size <2 cm 4.28 (1.681090) 0.002 Asymptomatic presentation 3.62 (1.82719) <0.001 Belief in traditional healers 3.48 (1.34905) 0.010 Fear/anxiety as barrier 2.84 (1.38584) 0.005 Model Fit: Hosmer-Lemeshow test χ² = 5.23, p = 0.730 (good fit). 3.9 Diagnostic Findings and Final Diagnosis Among 280 women, investigations were completed as follows: - Clinical breast examination: 280 (100%) - Ultrasound breast: 248 (88.6%) - Mammography: 102 (36.4%) - Fine-needle aspiration cytology (FNAC): 174 (62.1%) - Core needle biopsy: 48 (17.1%) - Histopathology: 186 (66.4%) Final Diagnoses (n=280): - Benign breast disease (fibroadenoma, cyst, fibrocystic changes, lipoma, phyllodes): 186 (66.4%) - Suspicious for malignancy (undergoing further workup): 52 (18.6%) - Confirmed malignancy: 42 (15.0%) - Ductal carcinoma in situ (DCIS): 6 (14.3% of malignancies) - Invasive ductal carcinoma (IDC): 28 (66.7% of malignancies) - Invasive lobular carcinoma (ILC): 6 (14.3% of malignancies) - Others: 2 (4.8% of malignancies) Among the 42 confirmed malignancies: - Stage I–II: 8 (19.0%) - Stage III: 24 (57.1%) - Stage IV: 10 (23.8%) 3.10 Department-Wise Comparison Table 10: Comparison of Delays and Awareness Between General Surgery and OBGY Departments Parameter General Surgery (n=150) OBGY (n=130) p-value Patient Delay ≥90 days, n (%) 108 (72.0%) 90 (69.2%) 0.58 Median patient delay (IQR), days 125 (70290) 115 (502170) 0.31 Diagnostic delay >28 days, n (%) 74 (49.3%) 60 (46.2%) 0.51 Median diagnostic delay (IQR), days 22 (14238) 20 (13232) 0.17 Screening awareness, n (%) 28 (18.7%) 26 (20.0%) 0.75 Ever undergone any screening, n (%) 2 (1.3%) 1 (0.8%) 0.63 Mean age (±SD), years 46.2 ± 11.4 45.2 ± 10.9 0.45 Rural residence, n (%) 62 (41.3%) 50 (38.5%) 0.60 No statistically significant differences observed between departments.

4.1 Key Findings This cross-sectional study of 280 women with breast lumps in Jaipur tertiary care centers identified substantial diagnostic and presentation delays, minimal screening awareness, and multiple modifiable barriers to early detection. Patient Delay: Magnitude and Significance Patient delay (≥3 months from symptom recognition to first medical consultation) was documented in 198 women (70.7%; 95% CI 65.3–75.9%), with a median delay of 120 days. This finding is consistent with earlier Indian studies reporting delays ranging from 42–62 days in urban settings and 62–90 days in rural settings[7,8]. However, the 70.7% prevalence in our study represents the proportion of the studied population experiencing delay, emphasizing that delayed presentation is the norm rather than the exception in Jaipur. Several women in our cohort (n=102; 36.4%) delayed >6 months, which contrasts unfavorably with international standards where >60% of women present within 2–3 weeks of symptom recognition[24]. Why Small Lumps Matter: Perception and Delay A striking finding was that asymptomatic lumps <2 cm carried the strongest association with patient delay (OR = 4.28; 95% CI 1.68–10.90 in multivariate analysis). Of the 64 women presenting with lumps <2 cm, 58 (90.6%) delayed ≥3 months. This reflects a common misconception that "small" lumps are benign and "nothing serious."[25] In contrast, larger lumps (>5 cm) prompted faster consultation, though by that stage disease may have progressed. This finding aligns with international literature showing that early-stage cancers (including small tumors) often remain undetected due to lack of screening and symptom misinterpretation[26]. Educational Status as a Powerful Predictor Lower education (≤primary level) emerged as the strongest independent predictor of patient delay (adjusted OR = 3.24; 95% CI 1.78–5.91)[27]. Among the 100 women with ≤primary education, 78 (78.0%) delayed ≥3 months compared to 24.0% (20/84) with higher secondary education. Education correlates not only with health literacy and disease awareness but also with decision-making autonomy, economic status, and access to information[28]. Educational interventions and community health worker programs targeting less-educated populations may significantly reduce delays[29]. Rural-Urban Divide Rural residence remained a significant independent predictor (adjusted OR = 2.87; 95% CI 1.52–5.42), with 76.8% (86/112) of rural women delaying ≥3 months versus 67.3% (112/168) in urban areas. This reflects known barriers: limited access to specialists, distances, transportation costs, and reliance on local practitioners (often unqualified) first-line contacts[30]. Screening Awareness: A Gaping Void Most striking was the profound lack of screening awareness: - Only 54 women (19.3%) reported awareness of any breast cancer screening method. - Only 42 women (15.0%) had heard about breast self-examination. - None had undergone organized screening. - Only 2.9% (8/280) had ever undergone mammography. This contrasts sharply with countries where >70% of eligible women know about mammography[31]. The finding that 226 women (80.7%) had no prior knowledge of breast cancer highlights a critical gap in health communication in Jaipur. Lack of screening awareness independently predicted patient delay (adjusted OR = 4.12; 95% CI 2.15–7.89). A woman unaware of breast cancer screening is unlikely to recognize a lump as worrisome or to seek prompt medical evaluation[32]. Diagnostic Delays: System-Level Factors Beyond patient delays, diagnostic delays (>28 days from first consultation to diagnosis) occurred in 134 women (47.9%). Median diagnostic delay was 21 days, with some women waiting >60 days for confirmation. Causes were multifactorial: - Waiting periods for imaging appointments (ultrasound: 15–30 days in public centers) - Delayed biopsy scheduling (up to 45 days in some cases) - Courier delays for histopathology reports - Multiple visits required for sequential investigations These system-level delays are addressable through: - Dedicated rapid diagnostic clinics (one-stop breast clinics)[33] - Point-of-care ultrasound by trained surgeons - In-house biopsy and histopathology facilities - Telemedicine consultations for secondary opinions Health-Seeking Pathways: The Role of Unqualified Practitioners Notably, 50 women (17.8%) first contacted unqualified or traditional healers, resulting in median delays of 90–150 days before reaching an allopathic doctor. This reflects limited regulation of AYUSH practitioners and public trust in traditional medicine[34]. Additionally, women visiting private general practitioners first (n=120; 42.9%) often experienced delayed specialist referrals, with 72 of these 120 women waiting ≥60 days before surgical consultation. Psychological and Socioeconomic Barriers Fear and anxiety emerged as the most common reasons for delay (n=96; 34.3%), particularly fear of cancer diagnosis. Such psychological barriers require sensitive counseling, reassurance, and health communication emphasizing that early diagnosis improves outcomes[35]. Belief in traditional healers (adjusted OR = 3.48) and financial constraints (19.3%) were also significant. Among 54 women citing financial reasons, 48 were from socioeconomic classes IV–V. This underscores the need for subsidized/free diagnostic services[36]. Clinical Stage at Diagnosis: A Consequence of Delay Among the 42 women with confirmed malignancy, only 8 (19.0%) presented with Stage I–II disease, while 34 (80.9%) presented with Stage III–IV disease. This aligns with national statistics showing >60% of Indian breast cancers presenting in advanced stages[37]. The median interval from symptom recognition to diagnosis in the malignancy group was 140 days (range: 45–300 days), allowing substantial disease progression. 4.2 Comparison with Published Literature Patient Delay Prevalence: Our 70.7% prevalence of patient delay (≥3 months) aligns closely with: - JIPMER study (70.6% delayed >3 months)[8] - Central India tertiary center (66.7% delayed >3 months)[7] - But exceeds some rural studies reporting 40–50% delays in screened populations[38] Diagnostic Delay: Our 47.9% prevalence of diagnostic delay >28 days exceeds typical tertiary care standards but reflects resource constraints in India[39]. Screening Awareness: Our 19.3% screening awareness is lower than: - Urban-based studies (25–35% awareness)[40] - But comparable to rural Rajasthan data (~15–20%)[41] Education and Socioeconomic Status as Predictors: Multiple studies from India and South Asia confirm our findings that lower education and socioeconomic status are strong independent predictors of presentation delay[42,43]. Small Lumps and Diagnostic Delay: Our observation that small lumps incur longer delays is novel and aligns with breast cancer psychology literature showing "optimism bias" toward minor symptoms[44]. 4.3 Public Health Implications Individual Level Women in Jaipur require targeted health education about: - Breast self-awareness (not just examination) and recognition of concerning changes - Availability and efficacy of early detection methods - Reassurance regarding benign breast disease - Prompt consultation for persistent lumps Community Level - Community health worker programs in rural areas - School-based health education (young women education increases awareness in family units)[45] - Media campaigns in regional languages highlighting early detection benefits - Regulation and training of AYUSH practitioners to recognize breast pathology and refer promptly Healthcare System Level - Establishment of rapid diagnostic clinics with specialist oversight - Integration of Community Medicine and Surgical services for patient tracking and follow-up - Training of primary care physicians in clinical breast examination and referral criteria - Awareness programs for private practitioners (majority first-line contacts) - Subsidized/free diagnostic services in public centers - Telemedicine consultations to reduce travel burden Policy Level - Inclusion of breast cancer in Rajasthan's cancer registries for surveillance - Integration of organized screening in public health programs - Guidelines for primary care referral pathways - Advocacy for insurance coverage of preventive mammography 4.4 Strengths and Limitations Strengths: 1. Hospital-based cross-sectional design with adequate sample size (n=280) calculated to detect prevalence of patient delay 2. Use of standardized definitions aligned with WHO and international studies 3. Prospective data collection with structured questionnaire 4. Cross-checking of reported delays against medical records 5. Multivariate analysis controlling for confounders 6. Inclusion of both General Surgery and OBGY patients (comprehensive coverage) Limitations: 1. Hospital-based sampling: Findings may overestimate delays compared to population-based prevalence (only women with palpable lumps who reached tertiary care included; those lost to follow-up at primary care not captured) 2. Recall bias: Patients asked to recall date of symptom recognition (up to 2 years prior) may misremember; median delay of 120 days suggests some women's recollection may be inaccurate 3. Single setting: Results from Jaipur tertiary centers may not generalize to other Indian cities or rural-only populations 4. Lack of prospective follow-up: Study captured point-in-time delays; longitudinal follow-up would strengthen causal inference 5. Limited data on quality of investigations: We documented diagnostic delay but did not assess quality of imaging/biopsy interpretation, which may contribute to delays 6. No control group: Without a comparison group of women without lumps, we cannot calculate attributable risk of various barriers 7. Missing data: Three women declined to complete screening awareness questions (1.1% missing data) 4.5 Clinical and Research Recommendations Clinical Practice: 1. Implement one-stop breast diagnostic clinics in both General Surgery and OBGY departments 2. Establish protocols for urgent referral of women with breast lumps from peripheral health centers 3. Training programs for private practitioners and primary care physicians 4. Patient education materials in local language (Hindi) in clinics Research: 1. Population-based survey to estimate community prevalence of breast lumps and screening awareness 2. Qualitative studies exploring psychological barriers and coping mechanisms 3. Implementation research evaluating effectiveness of rapid diagnostic clinics 4. Cost-effectiveness analysis of community-based screening vs. clinic-based detection 5. Longitudinal study tracking women from first symptom to treatment initiation

Substantial patient delays (70.7%) and diagnostic delays (47.9%) characterize breast lump management in Jaipur, reflecting a complex nexus of patient-level factors (low awareness, fear, small lump size), provider-level factors (delayed referral from primary care), and system-level factors (limited rapid diagnostic capacity). Education, rural residence, screening awareness, and psychological barriers independently predict patient delay. The finding that none of 280 women had undergone organized screening and only 19.3% had any screening awareness indicates a fundamental failure of public health communication and screening infrastructure. The concentration of 80.9% of confirmed breast cancers in advanced stages (Stage III–IV) is a direct consequence of these delays and underscores the urgency of intervention. Addressing delays requires concurrent action at multiple levels: community health education, provider training, health system strengthening (one-stop clinics), and supportive policies (insurance coverage, subsidized diagnostics). The synergy between General Surgery and Community Medicine departments, as demonstrated by integrated teaching and research, provides an opportunity to link clinical care with population-level preventive strategies. As Jaipur positions itself as a tertiary care hub, investing in early detection infrastructure and awareness programs will not only improve individual outcomes but also reduce the disease burden across Rajasthan.

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Educational Status: - [ ] Illiterate - [ ] Primary (1–5 years) - [ ] Secondary (6–10 years) - [ ] Higher secondary and above Q4. Occupational Status: - [ ] Homemaker - [ ] Employed - [ ] Self-employed Q5. Marital Status & Parity: - [ ] Married, Parity: ___________ - [ ] Unmarried - [ ] Widowed/Separated CLINICAL PRESENTATION Q6. When did you first notice the breast lump? (Date or duration) - Duration: __________ days/months Q7. Characteristics of lump (by clinical examination): - Location: ___________ - Size: ___________ - Consistency: [ ] Soft [ ] Firm [ ] Hard - Fixity: [ ] Mobile [ ] Fixed Q8. Associated symptoms: - [ ] Pain - [ ] Nipple discharge - [ ] Skin changes - [ ] Axillary lumps - [ ] None (asymptomatic) DELAYS & HEALTHCARE PATHWAYS Q9. When did you first consult a doctor about this lump? (Date) ___________ Patient Delay = Date of Q9 – Date of Q6 Q10. Who was your first medical contact? - [ ] Private doctor/clinic - [ ] Public health center - [ ] Hospital (directly) - [ ] Unqualified/AYUSH practitioner - [ ] Traditional healer Q11. How many doctors/healthcare providers did you consult before reaching a specialist surgeon/gynecologist? ___________ Q12. When did you first see a specialist surgeon/gynecologist? (Date) ___________ Q13. When was your diagnosis confirmed? (Date) ___________ Diagnostic Delay = Date of Q13 – Date of Q12 SCREENING AWARENESS Q14. Have you heard about breast self-examination? - [ ] Yes - [ ] No Q15. Have you ever performed breast self-examination? - [ ] Yes - [ ] No Q16. Have you heard about mammography for breast cancer screening? - [ ] Yes - [ ] No Q17. Have you ever undergone mammography? - [ ] Yes - [ ] No Q18. Have you heard about ultrasound for breast imaging? - [ ] Yes - [ ] No Q19. Have you ever undergone screening for breast cancer (in any form)? - [ ] Yes - [ ] No REASONS FOR DELAY (Multiple responses allowed) Q20. Why did you delay in seeking medical help? (Rank top 3) - [ ] Fear of cancer/anxiety - [ ] Belief in traditional/herbal treatment - [ ] Lack of awareness about disease severity - [ ] Financial constraints - [ ] Limited access to healthcare - [ ] Shyness about breast exposure - [ ] Thought it was not serious/would resolve on own - [ ] Did not know where to go - [ ] Family opposition - [ ] Busy with other responsibilities AUTHOR CONTRIBUTIONS Study Concept & Design: Dr. Sunil Singh Rathore, Dr. Dharmendra Mandarwal, Dr. Akhileshwar Reddy Vangala Data Collection: Research team (training by Dr. Sunil Singh Rathore) Statistical Analysis: Dr. Akhileshwar Reddy Vangala Manuscript Writing: All authors Critical Review & Editing: Dr. Dharmendra Mandarwal, Dr. Sanvar Mal Kantva, Dr. Hemlata Dangi --- CONFLICTS OF INTEREST Conflicts of Interest: The authors declare no conflicts of interest. ETHICS APPROVAL Ethics approval reference: SMS-IEC/2023-24/089; NIMS-IEC/2023-24/145