Standardized pathology report for breast cancer.
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ABSTRACT:
SUBMITTER: Cho SY
PROVIDER: S-EPMC7829577 | biostudies-literature | 2021 Jan
REPOSITORIES: biostudies-literature
Publications
Standardized pathology report for breast cancer.
Cho Soo Youn SY Park So Yeon SY Bae Young Kyung YK Kim Jee Yeon JY Kim Eun Kyung EK Kim Woo Gyeong WG Kwon Youngmee Y Lee Ahwon A Lee Hee Jin HJ Lee Ji Shin JS Park Jee Young JY Gong Gyungyub G Yoon Hye Kyoung HK
Journal of pathology and translational medicine 20210111 1
Given the recent advances in management and understanding of breast cancer, a standardized pathology report reflecting these changes is critical. To meet this need, the Breast Pathology Study Group of the Korean Society of Pathologists has developed a standardized pathology reporting format for breast cancer, consisting of 'standard data elements,' 'conditional data elements,' and a biomarker report form. The 'standard data elements' consist of the basic pathologic features used for prognosticat ...[more]
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Project description:Given the recent advances in management and understanding of breast cancer, a standardized pathology report reflecting these changes is critical. To meet this need, the Breast Pathology Study Group of the Korean Society of Pathologists has developed a standardized pathology reporting format for breast cancer, consisting of 'standard data elements,' 'conditional data elements,' and a biomarker report form. The 'standard data elements' consist of the basic pathologic features used for prognostication, while other factors related to prognosis or diagnosis are described in the 'conditional data elements.' In addition to standard data elements, all recommended issues are also presented. We expect that this standardized pathology report for breast cancer will improve diagnostic concordance and communication between pathologists and clinicians, as well as between pathologists inter-institutionally.
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Project description:The first edition of the 'Standardized Pathology Report for Colorectal Cancer,' which was developed by the Gastrointestinal Pathology Study Group (GIP) of the Korean Society of Pathologists, was published 13 years ago. Meanwhile, there have been many changes in the pathologic diagnosis of colorectal cancer (CRC), pathologic findings included in the pathology report, and immunohistochemical and molecular pathology required for the diagnosis and treatment of colorectal cancer. In order to reflect these changes, we (GIP) decided to make the second edition of the report. The purpose of this standardized pathology report is to provide a practical protocol for Korean pathologists, which could help diagnose and treat CRC patients. This report consists of "standard data elements" and "conditional data elements." Basic pathologic findings and parts necessary for prognostication of CRC patients are classified as "standard data elements," while other prognostic factors and factors related to adjuvant therapy are classified as "conditional data elements" so that each institution could select the contents according to the characteristics of the institution. The Korean version is also provided separately so that Korean pathologists can easily understand and use this report. We hope that this report will be helpful in the daily practice of CRC diagnosis.
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Project description:The first edition of 'A Standardized Pathology Report for Gastric Cancer' was initiated by the Gastrointestinal Pathology Study Group of the Korean Society of Pathologists and published 17 years ago. Since then, significant advances have been made in the pathologic diagnosis, molecular genetics, and management of gastric cancer (GC). To reflect those changes, a committee for publishing a second edition of the report was formed within the Gastrointestinal Pathology Study Group of the Korean Society of Pathologists. This second edition consists of two parts: standard data elements and conditional data elements. The standard data elements contain the basic pathologic findings and items necessary to predict the prognosis of GC patients, and they are adequate for routine surgical pathology service. Other diagnostic and prognostic factors relevant to adjuvant therapy, including molecular biomarkers, are classified as conditional data elements to allow each pathologist to selectively choose items appropriate to the environment in their institution. We trust that the standardized pathology report will be helpful for GC diagnosis and facilitate large-scale multidisciplinary collaborative studies.
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Project description:The first edition of 'A Standardized Pathology Report for Gastric Cancer' was initiated by the Gastrointestinal Pathology Study Group of the Korean Society of Pathologists and published 17 years ago. Since then, significant advances have been made in the pathologic diagnosis, molecular genetics, and management of gastric cancer (GC). To reflect those changes, a committee for publishing a second edition of the report was formed within the Gastrointestinal Pathology Study Group of the Korean Society of Pathologists. This second edition consists of two parts: standard data elements and conditional data elements. The standard data elements contain the basic pathologic findings and items necessary to predict the prognosis of GC patients, and they are adequate for routine surgical pathology service. Other diagnostic and prognostic factors relevant to adjuvant therapy, including molecular biomarkers, are classified as conditional data elements to allow each pathologist to selectively choose items appropriate to the environment in their institution. We trust that the standardized pathology report will be helpful for GC diagnosis and facilitate large-scale multidisciplinary collaborative studies.
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Project description:Several studies have demonstrated that familial breast cancers associated with BRCA1 or BRCA2 germline mutations differ in their morphological and immunohistochemical characteristics. Cancers associated with BRCA1 are poorly differentiated infiltrating ductal carcinomas (IDCs) with higher mitotic counts and pleomorphism and less tubule formation than sporadic tumours. In addition, more cases with the morphological features of typical or atypical medullary carcinoma are seen in these patients. Breast carcinomas from BRCA2 mutation carriers tend to be of higher grade than sporadic age-matched controls. Regarding immunophenotypic features. BRCA1 tumours have been found to be more frequently oestrogen receptor- (ER) and progesterone receptor-(PR) negative, and p53-positive than age-matched controls, whereas these differences are not usually found in BRCA2-associated tumours. A higher frequency and unusual location of p53 mutations have been described in BRCA1/2 carcinomas. Furthermore, BRCA1- and BRCA2-associated breast carcinomas show a low frequency of HER-2 expression. Recent studies have shown that most BRCA1 carcinomas belong to the basal cell phenotype, a subtype of high grade, highly proliferating ER/HER2-negative breast carcinoma characterized by the expression of basal or myoepithelial markers, such as basal keratins, P-cadherin, EGFR, etc. This phenotype occurs with a higher incidence in BRCA1 tumours than in sporadic carcinomas and is rarely found in BRCA2 carcinomas. Hereditary carcinomas not attributable to BRCA1/2 mutations have phenotypic similarities with BRCA2 tumours, but tend to be of lesser grade and lower proliferation index. The pathological features of hereditary breast cancer can drive specific treatment and influence the process of mutation screening.
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Project description:BackgroundCurrent data on the pathologic diagnoses of breast biopsy after mammography can inform patients, clinicians, and researchers about important population trends.MethodsBreast Cancer Surveillance Consortium data on 4,020,140 mammograms between 1996 and 2008 were linked to 76,567 pathology specimens. Trends in diagnoses in biopsies by time and risk factors (patient age, breast density, and family history of breast cancer) were examined for screening and diagnostic mammography (performed for a breast symptom or short-interval follow-up).ResultsOf the total mammograms, 88.5% were screening and 11.5% diagnostic; 1.2% of screening and 6.8% of diagnostic mammograms were followed by biopsies. The frequency of biopsies over time was stable after screening mammograms, but increased after diagnostic mammograms. For biopsies obtained after screening, frequencies of invasive carcinoma increased over time for women ages 40-49 and 60-69, Ductal carcinoma in situ (DCIS) increased for those ages 40-69, whereas benign diagnoses decreased for all ages. No trends in pathology diagnoses were found following diagnostic mammograms. Dense breast tissue was associated with high-risk lesions and DCIS relative to nondense breast tissue. Family history of breast cancer was associated with DCIS and invasive cancer.ConclusionsAlthough the frequency of breast biopsy after screening mammography has not changed over time, the percentages of biopsies with DCIS and invasive cancer diagnoses have increased. Among biopsies following mammography, women with dense breasts or family history of breast cancer were more likely to have high-risk lesions or invasive cancer. These findings are relevant to breast cancer screening and diagnostic practices.
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Project description:In cancer research, pathology report text is a largely un-tapped data source. Pathology reports are routinely generated, more nuanced than structured data, and contain added insight from pathologists. However, there are no publicly-available datasets for benchmarking report-based models. Two recent advances suggest the urgent need for a benchmark dataset. First, improved optical character recognition (OCR) techniques will make it possible to access older pathology reports in an automated way, increasing data available for analysis. Second, recent improvements in natural language processing (NLP) techniques using AI allow more accurate prediction of clinical targets from text. We apply state-of-the-art OCR and customized post- processing to publicly available report PDFs from The Cancer Genome Atlas, generating a machine-readable corpus of 9,523 reports. We perform a proof-of-principle cancer-type classification across 32 tissues, achieving 0.992 average AU-ROC. This dataset will be useful to researchers across specialties, including research clinicians, clinical trial investigators, and clinical NLP researchers.
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