Delayed time from first medical visit to diagnosis for breast cancer patients in Taiwan

Shieh, Shwn Huey; Hsieh, Vivian Chia Rong; Liu, Shu Hui; Chien, Chun Ru; Lin, Cheng Chieh; Wu, Trong Neng

doi:10.1016/j.jfma.2012.12.003

Cited by 25 publications

(37 citation statements)

References 20 publications

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“…; Shieh et al . ) used interviews and/or questionnaires for data collection, while two articles (Elmore et al . ; Redondo et al .…”

Section: Resultsmentioning

confidence: 99%

“…; Shieh et al . ), while four studies examined components of the diagnostic interval, with one study examining delay in the primary care interval (Burgess et al . ), another examining delay in the time from first presentation to specialist visit (Nosarti et al .…”

Section: Resultsmentioning

confidence: 99%

“…Of the remaining 81 articles, 61 were excluded after full-text review, leaving 20 articles examining predictors of delay in time intervals from first symptom to diagnosis. We performed a cited reference search and bibliographic reviews on the final 20 articles retrieved through the database search, which identified two additional articles so that the final review included 22 original research articles (Burgess et al 1998(Burgess et al , 2000(Burgess et al , 2006Haas et al 2000;Nosarti et al 2000;Montella et al 2001;Arndt et al 2002;Meechan et al 2003;Elmore et al 2005;Friedman et al 2006;De Gelder et al 2008;Gullatte et al 2009Gullatte et al , 2010O'Mahony & Hegarty 2009;Redondo et al 2009;Rauscher et al 2010;Yau et al 2010;Maly et al 2011;Warner et al 2012;O'Mahony et al 2013;Ruddy et al 2014;Shieh et al 2014).…”

Section: Ethics Statementmentioning

confidence: 99%

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Identifying predictors of delayed diagnoses in symptomatic breast cancer: a scoping review

et al. 2016

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Delayed diagnosis of breast cancer can adversely impact patient outcomes. To better understand this issue, we conducted a scoping review of literature from 1996 to 2015 that examined predictors of delayed presentation and diagnosis among women with breast cancer symptoms. We performed searches to identify studies of predictors of the time from symptom onset to first presentation (the patient interval), first presentation to diagnosis (the diagnostic interval) and symptom onset to diagnosis (the total interval) among women with breast cancer symptoms. Two reviewers independently reviewed and abstracted the findings of these studies. Of the 22 studies included in this review, 16 examined predictors of the patient interval, six examined predictors of the diagnostic interval and four examined predictors of the total interval. A total of 116 predictors were examined; three had evidence of an association with a less timely diagnosis: not disclosing symptoms to others, non-lump breast symptoms and African American ethnicity. Improving awareness of atypical breast cancer symptoms and encouraging disclosure could improve the timeliness of a breast cancer diagnosis. Access concerns for vulnerable groups need to be addressed. Future research should be more purposeful in its choice of predictors, possibly through the use of established conceptual frameworks.

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“…; Shieh et al . ) used interviews and/or questionnaires for data collection, while two articles (Elmore et al . ; Redondo et al .…”

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Ethics Statementmentioning

confidence: 99%

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Identifying predictors of delayed diagnoses in symptomatic breast cancer: a scoping review

et al. 2016

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“…The economic, geographic, and socio-cultural structure of the region where the study was conducted affected the patients' ways of seeking treatment. In a study by Shieh et al (27), 64.3% of the patients consulted one hospital and 28.1% consulted two hospitals before diagnosis. The authors found that those who consulted three hospitals were diagnosed 10 times later than those who only went to one hospital.…”

Section: Discussionmentioning

confidence: 97%

“…The number of consulted hospitals is one of the factors that causes delay in diagnosis. It was also reported that in cases when the first healthcare organization had an extensive diagnosis and treatment center, the delay in diagnosis was much shorter (27).…”

Section: Discussionmentioning

confidence: 99%

The Treatment Approach and Social Support Needs for Patients with Breast Cancer

Soylar

Genç

2016

J Breasth Health

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IntroductionBreast cancer is the second most common cancer type in the world and the most common cancer type in women. The number of newly diagnosed breast cancers in 2012 was 1.67 million, and breast cancer makes up 25% of all types of cancer in women (1). According to the data of the World Health Organization (WHO), the number of women who died of breast cancer worldwide in 2011 was 508 000. Breast cancer incidence increases as life expectancy increases, and urbanization and western lifestyles are adopted more and more in today's ever-developing world. It frequently occurs in both developed and less developed countries (2).As breast cancer incidence increases in most parts of the world, there are major disparities between poor and rich countries in this regard (3). Patients in undeveloped and less developed countries are diagnosed later compared with patients in developed countries. Diagnosis at a late stage decreases treatment options and increases mortality (4).Diagnosis in an advanced stage could occur because of patient-related as well as healthcare system-related reasons. Reasons such as lack of knowledge on symptoms, risk factors, and screening methods of breast cancer, cultural taboos regarding cancer treatment centers, and fear of hospitals are amongst reasons for patient-related latency. Although there is less information regarding healthcare system-related reasons, physicians' lack of knowledge on diagnosis and treatment and obstacles patients experience in reaching a physician or a hospital are considered amongst these reasons (5, 6).The negative effects of breast cancer on women's health are multidimensional. Problems that arise based on cancer treatment, problems about family and occupational life, and uncertainties toward life in the future influence the individual's physical and psychologic health negatively. Therefore, making emotional and social support attempts during the duration of the disease is of vital importance (7). Materials and Methods:The study included 200 patients with breast cancer who were treated at the chemotherapy unit during 2013 and 2014.Results: The mean age of the patients was 51.16±1.10 years and 60% of the women were graduates of elemantary school. The majority of patients (69.5%) noticed breast mass as the first symptom and 56.5% were diagnosed at later stages. Thirty-four percent of the patients delayed their visit to a health care centers after realizing the first symptom. No statistically significant relationship was determined between women's education level, residential area, age, the first symptom noticed, stages of tumor, and patients and system-related delay (p>0.05). In terms of family history of breast cancer, there was a significant difference between patient-related and system-related delays (p<0.05). The family support score (24.8±4.6) was higher than those of friends and husbands (23.8±5.5, 21.3±6.4, respectively). The husband support score was statistically different in terms of intimacy between women and their husbands after disease (p<0.001). Conclusi...

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DenseNet for Breast Tumor Classification in Mammographic Images

Jiménez-Gaona

Rodríguez-Álvarez

Morató

et al. 2021

Lecture Notes in Computer Science

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Breast cancer is the most common invasive cancer in women, and the second main cause of death. Breast cancer screening is an efficient method to detect indeterminate breast lesions early. The common approaches of screening for women are tomosynthesis and mammography images. However, the traditional manual diagnosis requires an intense workload by pathologists, who are prone to diagnostic errors. Thus, the aim of this study is to build a deep convolutional neural network method for automatic detection, segmentation, and classification of breast lesions in mammography images. Based on deep learning the Mask-CNN (RoIAlign) method was developed to features selection and extraction; and the classification was carried out by DenseNet architecture. Finally, the precision and accuracy of the model is evaluated by cross validation matrix and AUC curve. To summarize, the findings of this study may provide a helpful to improve the diagnosis and efficiency in the automatic tumor localization through the medical image classification.

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Delayed time from first medical visit to diagnosis for breast cancer patients in Taiwan

Abstract: Results of this study are anticipated to serve as a reference for the government and medical institutions to develop policies to reduce the number of hospitals visited before diagnosis for breast cancer patients, and ultimately to achieve the goal of early detection and treatment.

Cited by 25 publications

References 20 publications

Identifying predictors of delayed diagnoses in symptomatic breast cancer: a scoping review

Identifying predictors of delayed diagnoses in symptomatic breast cancer: a scoping review

The Treatment Approach and Social Support Needs for Patients with Breast Cancer

DenseNet for Breast Tumor Classification in Mammographic Images

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