This dataset contains Cancer Incidence data for Breast Cancer (Late Stage^) including: Age-Adjusted Rate, Confidence Interval, Average Annual Count, and Trend field information for US States for the average 5 year span from 2016 to 2020.Data are for females segmented by age (All Ages, Ages Under 50, Ages 50 & Over, Ages Under 65, and Ages 65 & Over), with field names and aliases describing the sex and age group tabulated.For more information, visit statecancerprofiles.cancer.govData NotationsState Cancer Registries may provide more current or more local data.TrendRising when 95% confidence interval of average annual percent change is above 0.Stable when 95% confidence interval of average annual percent change includes 0.Falling when 95% confidence interval of average annual percent change is below 0.† Incidence rates (cases per 100,000 population per year) are age-adjusted to the 2000 US standard population (19 age groups: <1, 1-4, 5-9, ... , 80-84, 85+). Rates are for invasive cancer only (except for bladder cancer which is invasive and in situ) or unless otherwise specified. Rates calculated using SEER*Stat. Population counts for denominators are based on Census populations as modified by NCI. The US Population Data File is used for SEER and NPCR incidence rates.‡ Incidence Trend data come from different sources. Due to different years of data availability, most of the trends are AAPCs based on APCs but some are APCs calculated in SEER*Stat. Please refer to the source for each area for additional information.Rates and trends are computed using different standards for malignancy. For more information see malignant.^ Late Stage is defined as cases determined to be regional or distant. Due to changes in stage coding, Combined Summary Stage (2004+) is used for data from Surveillance, Epidemiology, and End Results (SEER) databases and Merged Summary Stage is used for data from National Program of Cancer Registries databases. Due to the increased complexity with staging, other staging variables maybe used if necessary.Data Source Field Key(1) Source: National Program of Cancer Registries and Surveillance, Epidemiology, and End Results SEER*Stat Database - United States Department of Health and Human Services, Centers for Disease Control and Prevention and National Cancer Institute. Based on the 2022 submission.(5) Source: National Program of Cancer Registries and Surveillance, Epidemiology, and End Results SEER*Stat Database - United States Department of Health and Human Services, Centers for Disease Control and Prevention and National Cancer Institute. Based on the 2022 submission.(6) Source: National Program of Cancer Registries SEER*Stat Database - United States Department of Health and Human Services, Centers for Disease Control and Prevention (based on the 2022 submission).(7) Source: SEER November 2022 submission.(8) Source: Incidence data provided by the SEER Program. AAPCs are calculated by the Joinpoint Regression Program and are based on APCs. Data are age-adjusted to the 2000 US standard population (19 age groups: <1, 1-4, 5-9, ... , 80-84,85+). Rates are for invasive cancer only (except for bladder cancer which is invasive and in situ) or unless otherwise specified. Population counts for denominators are based on Census populations as modified by NCI. The US Population Data File is used with SEER November 2022 data.Some data are not available, see Data Not Available for combinations of geography, cancer site, age, and race/ethnicity.Data for the United States does not include data from Nevada.Data for the United States does not include Puerto Rico.

Legacy unique identifier: P00155

This dataset contains Cancer Incidence data for Breast Cancer (All Stages^) including: Age-Adjusted Rate, Confidence Interval, Average Annual Count, and Trend field information for US States for the average 5 year span from 2016 to 2020.Data are for females segmented by age (All Ages, Ages Under 50, Ages 50 & Over, Ages Under 65, and Ages 65 & Over), with field names and aliases describing the sex and age group tabulated.For more information, visit statecancerprofiles.cancer.govData NotationsState Cancer Registries may provide more current or more local data.TrendRising when 95% confidence interval of average annual percent change is above 0.Stable when 95% confidence interval of average annual percent change includes 0.Falling when 95% confidence interval of average annual percent change is below 0.† Incidence rates (cases per 100,000 population per year) are age-adjusted to the 2000 US standard population (19 age groups: <1, 1-4, 5-9, ... , 80-84, 85+). Rates are for invasive cancer only (except for bladder cancer which is invasive and in situ) or unless otherwise specified. Rates calculated using SEER*Stat. Population counts for denominators are based on Census populations as modified by NCI. The US Population Data File is used for SEER and NPCR incidence rates.‡ Incidence Trend data come from different sources. Due to different years of data availability, most of the trends are AAPCs based on APCs but some are APCs calculated in SEER*Stat. Please refer to the source for each area for additional information.Rates and trends are computed using different standards for malignancy. For more information see malignant.^ All Stages refers to any stage in the Surveillance, Epidemiology, and End Results (SEER) summary stage.Data Source Field Key(1) Source: National Program of Cancer Registries and Surveillance, Epidemiology, and End Results SEER*Stat Database - United States Department of Health and Human Services, Centers for Disease Control and Prevention and National Cancer Institute. Based on the 2022 submission.(5) Source: National Program of Cancer Registries and Surveillance, Epidemiology, and End Results SEER*Stat Database - United States Department of Health and Human Services, Centers for Disease Control and Prevention and National Cancer Institute. Based on the 2022 submission.(6) Source: National Program of Cancer Registries SEER*Stat Database - United States Department of Health and Human Services, Centers for Disease Control and Prevention (based on the 2022 submission).(7) Source: SEER November 2022 submission.(8) Source: Incidence data provided by the SEER Program. AAPCs are calculated by the Joinpoint Regression Program and are based on APCs. Data are age-adjusted to the 2000 US standard population (19 age groups: <1, 1-4, 5-9, ... , 80-84,85+). Rates are for invasive cancer only (except for bladder cancer which is invasive and in situ) or unless otherwise specified. Population counts for denominators are based on Census populations as modified by NCI. The US Population Data File is used with SEER November 2022 data.Some data are not available, see Data Not Available for combinations of geography, cancer site, age, and race/ethnicity.Data for the United States does not include data from Nevada.Data for the United States does not include Puerto Rico.

Breast cancer is a disease which affects much more women than men. In England in 2022, over 50 thousand new cases of breast cancer were registered among women. The most affected age group was women aged 65 to 69 years of age with over 6.3 thousand cases reported.

Mortality from breast cancer (ICD-10 C50 equivalent to ICD-9 174). To reduce deaths from breast cancer. The next release date for this indicator is to be confirmed. Legacy unique identifier: P00147

IntroductionYounger age at diagnosis is a risk factor for poor health-related quality of life (HRQOL) in long-term breast cancer survivors. However, few studies have specifically addressed HRQOL in young adults with breast cancer (i.e., diagnosed prior to age 40), nor have early changes in HRQOL been fully characterized.MethodsEligible female patients with breast cancer were identified through our local cancer center. To establish HRQOL, patients completed the Functional Assessment of Cancer Therapy-Breast (FACT-B) around diagnosis and 12 months later. Sociodemographic factors, genetic susceptibility to cancer, tumor- and treatment-related factors, and comorbidities (e.g., depression/anxiety) were abstracted from medical records and the local oncology registry. Mixed-effects models were used to identify changes in FACT-B scores during the first year of treatment and to determine whether any demographic/treatment-related factors modulated changes in scores.ResultsHealth-related quality of life in young patients with breast cancer was within normal limits at baseline, with a FACT-B overall well-being score of 108.5 (95% confidence limits [CI] = 103.7, 113.3). Participants reported slight improvements over a 12-month period: FACT-B overall well-being scores increased 6.6 points (95% CI = 2.1, 11.1, p < 0.01), functional well-being improved 3.0 points (95% CI = 2.0, 4.1, p < 0.01), emotional well-being improved 1.9 points (95% CI = 0.9, 2.8, p < 0.01), and physical well-being improved 1.5 points (95% CI = 0.2, 2.8, p = 0.03), on average. Participants with anxiety/depression at baseline reported greater improvements in FACT-B overall well-being (change: 12.9, 95% CI = 6.4, 9.5) and functional well-being (change: 5.2, 95% CI = 3.5, 6.9) than participants who did not have anxiety/depression at baseline (change in FACT-B overall well-being: 4.9, 95% CI = 0.2, 9.7; change in functional well-being: 2.3, 95% CI = 1.1, 3.4). Marital status, reconstructive surgery, and baseline clinical staging were also significantly associated with changes in aspects of HRQOL, although their impact on change was relatively minimal.ConclusionYoung women with breast cancer do not report HRQOL concerns during the first year of treatment. Improvements in HRQOL during the first year of treatment may be attributable to a sense of relief that the cancer is being treated, which, in the short run, may outweigh the negative late effects of treatment.

Editor’s Choice

• Global Breast Cancer Market size is expected to be worth around USD 49.2 Bn by 2032 from USD 19.8 Bn in 2022, growing at a CAGR of 9.8% during the forecast period from 2022 to 2032.
• Breast cancer is the most common cancer among women worldwide. In 2020, there were about 2.3 million new cases of breast cancer diagnosed globally.
• Breast cancer is the leading cause of cancer-related deaths in women. In 2020, it was responsible for approximately 685,000 deaths worldwide.
• The survival rate of breast cancer has improved over the years. In the United States, the overall five-year survival rate of breast cancer is around 90%.
• The American Cancer Society recommends annual mammograms starting at age 40 for women at average risk.
• Although rare, breast cancer also occurs in men. Less than 1% of breast cancer cases are diagnosed in males.

(Source: WHO, American Cancer Society)

The rate of breast cancer deaths in the U.S. has dramatically declined since 1950. As of 2022, the death rate from breast cancer had dropped from 31.9 to 18.7 per 100,000 population. Cancer is a serious public health issue in the United States. As of 2021, cancer is the second leading cause of death among women. Breast cancer incidence Breast cancer symptoms include lumps or thickening of the breast tissue and may include changes to the skin. Breast cancer is driven by many factors, but age is a known risk factor. Among all age groups, the highest number of invasive breast cancer cases were among those aged 60 to 69. The incidence rate of new breast cancer cases is higher in some ethnicities than others. White, non-Hispanic women had the highest incidence rate of breast cancer, followed by non-Hispanic Black women. Breast cancer treatment Breast cancer treatments usually involve several methods, including surgery, chemotherapy and biological therapy. Types of cancer diagnosed at earlier stages often require fewer treatments. A majority of the early stage breast cancer cases in the U.S. receive breast conserving surgery and radiation therapy.

In 2022, the highest breast cancer incidence in women in Europe was estimated in Luxembourg with approximately 190 per 100,000 population. Belgium and Cyprus followed closely. The average breast cancer incidence across EU-27 was 147.6 per 100,00 population, in 2022. Cancer incidence in Europe In 2022, Denmark was the European country with the highest cancer incidence, with 728.5 cases per 100,000 population, followed by Ireland and Netherlands, with both around 641 cases per 100,000 people. Overall, the age-standardized incidence rate of cancer in all sites, excluding non-melanoma skin cancers, was 568.7 per 100,000 population in the whole of EU, with the most prevalent type of cancer being prostate cancer, followed by breast and colorectal cancer. Deaths from breast cancer In the same year, breast cancer also had the highest mortality rate among all types of cancers in women, standing at 34.1 deaths per 100,000 females. Cyprus had the highest mortality rate from breast cancer in all of EU with 45.1 deaths per 100,000 women. Meanwhile, the highest number of deaths due to breast cancer in the given year was reported in Germany, where approximately 20.6 thousand women lost their lives to breast cancer.

Legacy unique identifier: P00767

BackgroundCardiovascular disease (CVD) is the leading cause of morbidity and mortality among older postmenopausal women. The impact of postmenopausal breast cancer on CVD for older women is uncertain. We hypothesized that older postmenopausal women with breast cancer would be at a higher risk of CVD than similar aged women without breast cancer and that CVD would be a major contributor to the subsequent morbidity and mortality.MethodsIn a prospective Women’s Health Initiative study, incident CVD events and total and cause-specific death rates were compared between postmenopausal women with (n = 4,340) and without (n = 97,576) incident invasive breast cancer over 10 years post-diagnosis, stratified by 3 age groups (50–59, 60–69, and 70–79).ResultsPostmenopausal women, regardless of breast cancer diagnosis, had similar and high levels of CVD risk factors (e.g., smoking and hypertension) at baseline prior to breast cancer, which were strong predictors of CVD and total mortality over time. CVD affected mostly women age 70–79 with localized breast cancer (79% of breast cancer cases in 70–79 age group): only 17% died from breast cancer and CVD was the leading cause of death (22%) over the average 10 years follow up. Compared to age-matched women without breast cancer, women age 70–79 at diagnosis of localized breast cancer had a similar multivariate-adjusted hazard ratio (HR) of 1.01 (95% confidence interval [CI]: 0.76–1.33) for coronary heart disease, a lower risk of composite CVD (HR = 0.84, 95% CI: 0.70–1.00), and a higher risk of total mortality (HR = 1.20, 95% CI: 1.04–1.39).ConclusionCVD was a major contributor to mortality in women with localized breast cancer at age 70–79. Further studies are needed to evaluate both screening and treatment of localized breast cancer tailored to the specific health issues of older women.

BackgroundEarlier studies of breast cancer, screening mammography, and mortality reduction may have inflated lifetime and long-term risk estimates for invasive breast cancer due to limitations in their data collection methods and interpretation.ObjectiveTo estimate the percentage of asymptomatic peri/postmenopausal women who will be diagnosed with a first invasive breast cancer over their next 25 years of life.MethodsA systematic review identified peer-reviewed published studies that: 1) enrolled no study participants with a history of invasive breast cancer; 2) specified the number of women enrolled; 3) reported the number of women diagnosed with a first invasive breast cancer; 4) did not overcount [count a woman multiple times]; and, 5) defined the length of follow-up. Data sources included PubMed, Cochrane Library, and an annotated library of 4,409 full-text menopause-related papers collected and reviewed by the first author from 1974 through 2008. Linear regression predicted incidence of first invasive breast cancer, based on follow-up duration in all studies that met the our inclusion criteria, and in a subset of these studies that included only women who were 1) at least 50 years old and 2) either at least 50 or less than 50 but surgically menopausal at enrollment.ResultsNineteen studies met the inclusion criteria. They included a total of 2,305,427 peri/postmenopasual women. The mean cumulative incidence rate of first invasive breast cancer increased by 0.20% for each year of age (95% CI: 0.17, 0.23; p < 0.01; R2 = 0.90). Over 25 years of follow-up, an estimated 94.55% of women will remain breast cancer-free (95% CI: 93.97, 95.13). In the 12 studies (n = 1,711,178) that enrolled only postmenopausal women, an estimated 0.23% of women will be diagnosed with a first invasive breast cancer each year (95% CI: 0.18, 0.28; p < 0.01, R2 = 0.88).ConclusionThe vast majority (99.75%) of screened asymptomatic peri/postmenopasual women will not be diagnosed with invasive breast cancer each year. Approximately 95% will not be diagnosed with invasive breast cancer during 25 years of follow-up. Women who receive clinical examinations, but do not have mammograms, will have higher cancer-free rates because innocuous positives (comprising 30-50% of mammography diagnoses) will remain undetected. Informed consent to asymptomatic women should include these results and consideration of the benefits of avoiding mammograms.

The aim of this study was to assess the acceptability and feasibility of offering risk-based breast cancer screening and its integration into regular clinical practice. A single-arm proof-of-concept trial was conducted with a sample of 387 women aged 40–50 years residing in the city of Lleida (Spain). The study intervention consisted of breast cancer risk estimation, risk communication and screening recommendations, and a follow-up. A polygenic risk score with 83 single nucleotide polymorphisms was used to update the Breast Cancer Surveillance Consortium risk model and estimate the 5-year absolute risk of breast cancer. The women expressed a positive attitude towards varying the frequency of breast screening according to individual risk and, especially, more frequently inviting women at higher-than-average risk. A lower intensity screening for women at lower risk was not as welcome, although half of the participants would accept it. Knowledge of the benefits and harms of breast screening was low, especially with regard to false positives and overdiagnosis. The women expressed a high understanding of individual risk and screening recommendations. The participants’ intention to participate in risk-based screening and satisfaction at 1-year were very high. Methods From January 2019 to February 2021, 387 women aged 40 to 50 years were enrolled in the study. Potential participants were the 2038 women living in the “Primer de Maig” Basic Health Area in Lleida, Catalonia, on 31 December 2018, who would have turned between 40 to 50 years of age during the following 1.5 years. Accrual was suspended because of the COVID-19 pandemic in March 2020 when 252 women had been included and resumed in October 2020. All women who turned 50 during the study period would have received the first invitation to participate in the population-based Breast Cancer Early Detection Program. Instead, they were invited to participate in our study. Women that declined were invited by the early detection program. From women that turned 40 to 49 years during the study period, random samples of 20 to 50 women were selected from the potential participants on a monthly basis, and the women were invited to participate until the accrual goal was achieved. Exclusion criteria included having a previous diagnosis of breast cancer, undergoing a current breast study, or fulfilling clinical criteria for cancer-related genetic counseling. We also excluded women not understanding or speaking Catalan or Spanish or those with a physical or cognitive disability that prevented breast screening or the main outcome’s assessment. The study intervention consisted of a baseline visit, the breast cancer risk estimation, a visit for risk communication and screening recommendations, the administration of a follow-up questionnaire, and a phone call to assess satisfaction after one year. The baseline visit was held at the Primary Care center, where the healthcare professional provided information about the study objectives; facilitated an informative brochure about the benefits and adverse effects of breast cancer screening; obtained information on sociodemographic variables, risk factors, previous screening experience, perceived personal risk of breast cancer, and general screening knowledge, attitudes, and intentions; obtained a saliva sample to determine the genomic profile; and scheduled a screening mammogram with breast density measurement. For women that had a mammogram during the year before the first visit, breast density and presence/absence of benign lesions were obtained from that mammogram and the radiologist’s report. Breast density was classified according to the Breast Imaging Reporting and Data System (BI-RADS), 5th edition, scoring system: almost entirely fatty (a), scattered areas of fibroglandular density (b), heterogeneously dense (c), and extremely dense (d). Mammographic findings were coded from 0 (incomplete—additional imaging needed) to 6 (known biopsy—proven malignancy). In the case of abnormal results, additional tests were requested. Collection, conservation, and delivery of saliva samples was completed following the saliva collection protocol provided by the University of Lleida’s Proteomics and Genomics Service. Details about the genotyping process can be found in the protocol. The PRS was obtained using the 83 SNPs associated with breast cancer, based on Shieh et al.’s or Mavaddat et al.’s studies, as a composite likelihood ratio representing the individual effects of each SNP. The primary outcome measures were attitude towards, intention to participate in, and satisfaction with personalized breast cancer screening by participating women. Attitude was measured with a three-item scale, each item ranging from 1 to 5, with higher scores indicating more positive attitudes. A “positive attitude” was defined as a total score greater than or equal to 12. Intention to participate was measured with a 5-point Likert scale from definitely will (1) to definitely will not (5). The variable was also dichotomized as intending to participate (definitely or likely) or not. Satisfaction was assessed after one year of recruitment and was measured on a 5-point Likert scale from very unsatisfied (1) to very satisfied (5). Secondary outcomes (e.g., attitude towards screening mammography, attitude towards measuring breast cancer risk, emotional impact of the measure of breast cancer risk, preference with regard to the current screening, knowledge, decisional conflict, confidence, and participation) have been detailed in full in the study protocol. The R programming language and the RStudio environment were used for the data analysis. The Likert function of the HH package was used to obtain the graphical representation of the primary outcomes measured as Likert scales.

Background: Limited information is available for patients with breast cancer (BC) and coronavirus disease 2019 (COVID-19), especially among underrepresented racial/ethnic populations. Methods: This is a COVID-19 and Cancer Consortium (CCC19) registry-based retrospective cohort study of females with active or history of BC and laboratory-confirmed severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection diagnosed between March 2020 and June 2021 in the US. Primary outcome was COVID-19 severity measured on a five-level ordinal scale, including none of the following complications, hospitalization, intensive care unit admission, mechanical ventilation, and all-cause mortality. Multivariable ordinal logistic regression model identified characteristics associated with COVID-19 severity. Results: 1,383 female patient records with BC and COVID-19 were included in the analysis, the median age was 61 years, and median follow-up was 90 days. Multivariable analysis revealed higher odds of COVID-19 severity for older age (aOR per decade, 1.48 [95% CI, 1.32–1.67]); Black patients (aOR 1.74; 95 CI 1.24–2.45), Asian Americans and Pacific Islander patients (aOR 3.40; 95 CI 1.70–6.79) and Other (aOR 2.97; 95 CI 1.71–5.17) racial/ethnic groups; worse ECOG performance status (ECOG PS ≥2: aOR, 7.78 [95% CI, 4.83–12.5]); pre-existing cardiovascular (aOR, 2.26 [95% CI, 1.63–3.15])/pulmonary comorbidities (aOR, 1.65 [95% CI, 1.20–2.29]); diabetes mellitus (aOR, 2.25 [95% CI, 1.66–3.04]); and active and progressing cancer (aOR, 12.5 [95% CI, 6.89–22.6]). Hispanic ethnicity, timing, and type of anti-cancer therapy modalities were not significantly associated with worse COVID-19 outcomes. The total all-cause mortality and hospitalization rate for the entire cohort were 9% and 37%, respectively; however, it varied according to the BC disease status. Conclusions: Using one of the largest registries on cancer and COVID-19, we identified patient- and BC-related factors associated with worse COVID-19 outcomes. After adjusting for baseline characteristics, underrepresented racial/ethnic patients experienced worse outcomes compared to Non-Hispanic White patients.

Clinical metadata of all samples included in the study "Proteogenomics decodes the evolution of human ipsilateral breast cancer". De Marchi T, Pyl PT, Sjöström M, Reinsbach SE, DiLorenzo S, Nystedt B, Tran L, Pekar G, Wärnberg F, Fredriksson I, Malmström P, Fernö M, Malmström L, Malmström J, Nimèus E..

File reports clinical data of 27 primary breast cancers and their associated ipsilateral breast tumor recurrences (samples marked with S). Additionally, a cohort of 21 primary breast tumors with no recurrence is reported (samples marked with V). Data includes age at diagnosis of primary tumor, time to recurrence (S samples) or follow-up (V samples), Estrogen receptor status (positive/negative), progesterone receptor status (positive/negative), ERBB2 status (normal/amplified), proliferation marker Ki-67 (low/high), tumor grade (1/2/3), and adjuvant therapies (yes/no).

This dataset was used for Figure 1-6 in the following manuscript: "Proteogenomics decodes the evolution of human ipsilateral breast cancer". De Marchi T, Pyl PT, Sjöström M, Reinsbach SE, DiLorenzo S, Nystedt B, Tran L, Pekar G, Wärnberg F, Fredriksson I, Malmström P, Fernö M, Malmström L, Malmström J, Nimèus E. accepted for publication

To compare the clinical characteristics and prognosis of pregnancy-associated breast cancer (PABC) patients and non-PABC subjects in Hebei Breast Disease Treatment Center. A total of 40 PABC patients, including 10 pregnant women and 30 postpartum women, and 80 non-PABC subjects were recruited. The mean age of pregnancy in PABC patients was significantly older than that of non-PABC subjects (26.8 years vs. 23.5 years, P<0.05). Categorized by the receptor status, the ratio of hormone receptor (HR) positive breast cancer was lower in PABC patients than that of non-PABC subjects (57.5% vs. 70.0%, P=0.221), while the ratios of HER2- (42.5% vs. 37.5%, P=0.692) and triple-negative PABC patients (20% vs. 12.5%, P=0.578) were higher than those of non-PABC patients, although no significant differences were detected. There were no significant differences in the DFS (54.2 months vs. 63.5 months, P=0.271) and OS (54.2 months vs. 65.4 months, P=0.116) between PABC patients and non-PABC subjects. Compared with non-PABC subjects, the average age of pregnancy of PABC patients was later, while share similar pathological characteristics, as well as DFS and OS.

The proportion of women eligible for screening who have had a test with a recorded result at least once in the previous 36 months.RationaleBreast screening supports early detection of cancer and is estimated to save 1,400 lives in England each year. This indicator provides an opportunity to incentivise screening promotion and other local initiatives to increase coverage of breast screening.Improvements in coverage would mean more breast cancers are detected at earlier, more treatable stages.Breast screening supports early detection of cancer and is estimated to save 1,400 lives in England each year. This indicator provides an opportunity to incentivise screening promotion and other local initiatives to increase coverage of breast screening.Improvements in coverage would mean more breast cancers are detected at earlier, more treatable stages.Definition of numeratorTested women (numerator) is the number of eligible women aged 53 to 70 registered with a GP with a screening test result recorded in the past 36 months.Definition of denominatorEligible women (denominator) is the number of women aged 53 to 70 years resident in the area (determined by postcode of residence) who are eligible for breast screening at a given point in time, excluding those whose recall has been ceased for clinical reasons (for example, due to previous bilateral mastectomy).CaveatsData for ICBs are estimated from local authority data. In most cases ICBs are coterminous with local authorities, so the ICB figures are precise. In cases where local authorities cross ICB boundaries, the local authority data are proportionally split between ICBs, based on population located in each ICB.The affected ICBs are:Bath and North East Somerset, Swindon and Wiltshire;Bedfordshire, Luton and Milton Keynes;Buckinghamshire, Oxfordshire and Berkshire West;Cambridgeshire and Peterborough;Frimley;Hampshire and Isle of Wight;Hertfordshire and West Essex;Humber and North Yorkshire;Lancashire and South Cumbria;Norfolk and Waveney;North East and North Cumbria;Suffolk and North East Essex;Surrey Heartlands;Sussex;West Yorkshire.Please be aware that the April 2019 to March 2020, April 2020 to March 2021 and April 2021 to March 2022 data covers the time period affected by the COVID19 pandemic and therefore data for this period should be interpreted with caution.This indicator gives screening coverage by local authority . This is not the same as the indicator based on population registered with primary care organisations which include patients wherever they live. This is likely to result in different England totals depending on selected (registered or resident) population footprint.The indicator excludes women outside the target age range for the screening programme who may self refer for screening.Standards say "Women who are ineligible for screening due to having had a bilateral mastectomy, women who are ceased from the programme based on a ‘best interests’ decision under the Mental Capacity Act 2005 or women who make an informed choice to remove themselves from the screening programme will be removed from the numerator and denominator.There are a number of categories of women in the eligible age range who are not registered with a GP and subsequently not called for screening as they are not on the Breast Screening Select (BS Select) database. Screening units have a responsibility to maximise coverage of eligible women in their target population and should therefore be accessible to women in this category through self referral and GP referral ."This indicator gives screening coverage by local authority . This is not the same as the indicator based on population registered with primary care organisations which include patients wherever they live. This is likely to result in different England totals depending on selected (registered or resident) population footprint.

Most women with breast cancer in sub-Saharan Africa (SSA) are diagnosed with late-staged disease. The current study assesses patient-related barriers among women from a general SSA population to better understand how patient-related barriers contribute to diagnostic delays. Using convenience-based sampling, 401 Ugandan women without breast cancer were surveyed to determine how prior participation in cancer detection practices correlate with patient-related barriers to prompt diagnosis. In a predominantly poor (76%) and rural population (75%), the median age of the participants was 38. Of the women surveyed, 155 (46%) had prior exposure to breast cancer education, 92 (27%) performed breast self-examination (BSE) and 68 (20%) had undergone a recent clinical breast examination (CBE), breast ultrasound or breast biopsy. The most commonly identified barriers to prompt diagnosis were knowledge deficits regarding early diagnosis (79%), economic barriers to accessing care (68%), fear (37%) and poor social support (24%). However, only women who reported knowledge deficits – a modifiable barrier – were less likely to participate in cancer detection practices (p<0.05). Women in urban and rural areas were similarly likely to report economic barriers, knowledge deficits and/or poor social support, but rural women were less likely than urban women to have received breast cancer education and/or perform BSE (p<0.001). Women who have had prior breast cancer education (p<0.001) and/or who perform BSE (p=0.02) were more likely to know where she can go to receive a diagnostic breast evaluation. These findings suggest that SSA countries developing early breast cancer detection programs should specifically address modifiable knowledge deficits among women less likely to achieve a diagnostic work-up to reduce diagnostic delays and improve breast cancer outcomes.

Breast cancer is the most common invasive cancer in women worldwide. Next-generation sequencing (NGS) provides a high-resolution profile of cancer genome. Our study ultimately gives the insight for genetic screening to identify the minority of patients with breast cancer with a poor prognosis, who might benefit from the most intensive possible treatment. The detection of mutations can polish the traditional method to detect high-risk patients who experience poor prognosis, recurrence and death early. In total, 147 breast cancer tumors were sequenced with targeted sequencing using a RainDance Cancer Hotspot Panel. The average age of all 147 breast cancer patients in the study was 51.7 years, with a range of 21–77 years. The average sequencing depth was 5,222x (range 2,900x-8,633x), and the coverage was approximately 100%. A total of 235 variants in 43 genes were detected in 147 patients by high-depth Illumina sequencing. A total of 219 single nucleotide variations were found in 42 genes from 147 patients, and 16 indel mutations were found in 13 genes from 84 patients. After filtering with the 1000 Genomes database and for synonymous SNPs, we focused on 54 somatic functional point mutations. The functional point mutations contained 54 missense mutations in 22 genes. Additionally, mutation of genes within the RET, PTEN, CDH1, MAP2K4, NF1, ERBB2, RUNX1, PIK3CA, FGFR3, KIT, KDR, APC, SMO, NOTCH1, and FBXW7 in breast cancer patients were with poor prognosis. Moreover, TP53 and APC mutations were enriched in triple-negative breast cancer. APC mutations were associated with a poor prognosis in human breast cancer (log-rank P

Effect of different screening scenarios on screening program