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Background: Molecular testing of thyroid nodules is an essential tool to help risk stratify nodules with indeterminate cytology. Although ThyroSeq testing has been around for over a decade, there is a paucity of long‐term follow‐up data on cytologically indeterminate nodules that are determined to be molecularly negative or low‐risk. The objective of this study is to assess the outcomes of nodules with indeterminate cytology (Bethesda III or IV) and negative or low‐risk ThyroSeq results. Methods: This is a single academic institution retrospective cohort study. Patients with at least one thyroid nodule sampled with fine‐needle aspiration who underwent ThyroSeq testing from 2012 to 2018 and had negative or low‐risk ThyroSeq results on a cytologically indeterminate sample (n = 159 patients, 167 nodules) were included in the study. Outcomes include the false‐negative rate and negative predictive value of each test version, as well as follow‐up length for each nodule. Results: There were 159 patients with a mean age of 58 years (7–84 years) included in this study; the majority were female (81.8%). The mean follow‐up was 4.0 years. Of 167 nodules, three were found to be malignant on resection (1.8%). The negative predictive value for the entire cohort was 98.2% and it was 89.3% for the surgical series. Conclusion: ThyroSeq testing has good negative predictive value and can help risk stratify cytologically indeterminate nodules. Routine follow‐up allows for safe monitoring of nodules for features suggestive of malignancy. ThyroSeq testing can be used to risk stratify cytologically indeterminate nodules and decrease the number of unnecessary surgeries due to its low rates of false negatives and a high negative predictive value. [ABSTRACT FROM AUTHOR]

BACKGROUND: The American Thyroid Association recommends either repeat fine‐needle aspiration biopsy (FNAB) or molecular testing (eg, ThyroSeq) of Bethesda category III (atypia of undetermined significance/follicular lesion of undetermined significance [AUS/FLUS]) nodules to provide further risk stratification. How a testing algorithm that uses ancillary molecular tests performs as a reflex test for repeat sampling of indeterminant nodules remains unclear. METHODS: Thyroid FNABs performed over a 24‐month period that received a diagnosis of AUS/FLUS and underwent subsequent FNAB were analyzed. RESULTS: In total, 187 patients were identified who received an FNAB diagnosis of AUS/FLUS and had repeat sampling. Of these patients, 64% received a subsequent indeterminant diagnosis on repeat biopsy: 7 (3.7%) repeat biopsies were diagnosed as nondiagnostic/unsatisfactory, 104 (55.6%) were diagnosed as AUS/FLUS, and 8 (4.3%) were diagnosed as follicular neoplasm/suspicious for follicular neoplasm. Of the repeat biopsied nodules, 63% underwent subsequent testing with ThyroSeq version 3. The diagnostic performance was calculated using only surgically confirmed nodules (sensitivity, 100%; specificity, 30%; positive predictive value, 41%; negative predictive value, 100%) and by assigning nonresected nodules with negative ThyroSeq or benign cytology results as benign (sensitivity, 100%; specificity, 88%; positive predictive value, 41%; negative predictive value, 100%). CONCLUSIONS: In the majority of patients, repeat FNAB for AUS/FLUS did not preclude subsequent molecular ancillary testing because of the high rate of indeterminant results on repeat biopsy. The diagnostic performance of the testing algorithm reported here was very similar to other reports using either repeat biopsy or molecular testing alone. Ultimately, the algorithm of performing molecular testing on repeat indeterminant nodules increased the number of biopsies performed and lengthened the time to definitive risk stratification without a disproportionate decrease in the use of molecular testing or an appreciable improvement in diagnostic performance.; Some institutions use molecular testing as a reflex test for nodules that repeat as indeterminate. The performance of this combined testing algorithm is examined, and the results are compared with other studies that have used either repeat biopsy or molecular testing alone. [ABSTRACT FROM AUTHOR]

Abstract Background Despite the pressing need for the creation of applications that facilitate the aggregation of clinical and molecular data, most current applications are proprietary and lack the necessary compliance with standards that would allow for cross-institutional data exchange. In line with its mission of accelerating research discoveries and improving patient outcomes by linking networks of researchers, physicians, and patients focused on cancer research, caBIG (cancer Biomedical Informatics Grid™) has sponsored the creation of the caTRIP (Cancer Translational Research Informatics Platform) tool, with the purpose of aggregating clinical and molecular data in a repository that is user-friendly, easily accessible, as well as compliant with regulatory requirements of privacy and security. Results caTRIP has been developed as an N-tier architecture, with three primary tiers: domain services, the distributed query engine, and the graphical user interface, primarily making use of the caGrid infrastructure to ensure compatibility with other tools currently developed by caBIG. The application interface was designed so that users can construct queries using either the Simple Interface via drop-down menus or the Advanced Interface for more sophisticated searching strategies to using drag-and-drop. Furthermore, the application addresses the security concerns of authentication, authorization, and delegation, as well as an automated honest broker service for deidentifying data. Conclusion Currently being deployed at Duke University and a few other centers, we expect that caTRIP will make a significant contribution to further the development of translational research through the facilitation of its data exchange and storage processes.

Context.--Biospecimens must have appropriate clinical annotation (data) to ensure optimal quality for both patient care and research. Clinical preanalytic variables are the focus of this study. Objectives.--To define the essential preanalytic variables (data fields) that should be attached to every collected biospecimen and to provide a complete list of such variables, along with their relative importance, which can vary, depending on downstream use, institutional needs, and information technology capabilities. Design.--The College of American Pathologists Diagnostic Intelligence and Health Information Technology Committee sponsored a Biorepository Working Group to develop a ranked list of the preanalytic variables for annotating biospecimens. Members of the working group were experts in anatomic, clinical, and molecular pathology; biobanking; medical informatics; and accreditation. Several members had experience with federal government programs, such as the National Cancer Institute's Biospecimens and Biorepository Branch and the National Cancer Institute's Community Cancer Center Program. Potential preanalytic variables were identified and ranked along with available supporting evidence, definitions, and potential negative effects if the variable was not attached to the biospecimen. Additional national and international stakeholders reviewed the draft manuscript. Results.--The ranked listing of 170 preanalytic variables produced can be used as a guide for site-specific implementation into patient care and/or research biorepository processes. Conclusions.--In our collective experience, it is often difficult to choose which of the many preanalytic variables to attach to any specific set of biospecimens used for patient care and/or research. The provided ranked list should aid in the selection of preanalytic variables for a given biospecimen collection. (Arch Pathol Lab Med. 2014; 138:526-537; doi: 10.5858/arpa.2013-0250-CP), The College of American Pathologists (CAP) is committed to helping pathologists and the medical specialty of pathology successfully implement genomically informed, personalized, precision health care. As part of that mission, [...]

* Pathologists have long served as custodians of human biospecimens collected for diagnostic purposes. Rapid advancements in diagnostic technologies require that pathologists change their practices to optimize patient care. The proper handling of biospecimens creates opportunities for pathologists to improve their diagnoses while assessing prognosis and treatment. In addition, the growing need for high-quality biorepositories represents an opportunity for community pathologists to strengthen their role within the health care team, ensuring that clinical care is not compromised while facilitating research. This article provides a resource to community pathologists learning how to create high-quality biorepositories and participating in emerging opportunities in the biorepository field. While a variety of topics are covered to provide breadth of information, the intent is to facilitate a level of understanding that permits community pathologists to make more informed choices in identifying how best their skills and practice may be augmented to address developments in this field. (Arch Pathol Lab Med. 2012;136:668-678; doi: 10.5858/arpa.2011-0274-SO), BACKGROUND AND CHALLENGES FOR THE COMMUNITY PATHOLOGIST Drivers of this transformation relate to the concept of 'personalized medicine,' namely, the idea of tailoring medical management to a patient's genetic background [...]

Context.--Granular cell tumors (GCTs) of the breast are rare neoplasms that mimic epithelial malignancy clinically and rarely occur in association with it. Granular cell tumors of the breast are not infrequently excised with positive margins. Reports describing risk of recurrence including data on margin status and follow-up are lacking. Objective.--To review our series of GCTs of the breast to determine the risk of recurrence if excised with positive or close margins. Design.--Cases of GCT of the breast were reviewed. Margin status of specimens was recorded as positive, close ( Results.--Thirteen female patients with GCT of the breast were identified. Mean patient age at presentation was 45 years. Seventy-seven percent of patients were African American and 23% were white. African American patients presented on average 13 years earlier than white patients. Average tumor size was 1.22 cm. Fifteen percent of lesions had positive margins on excisional biopsy or lumpectomy and 31% had tumor cells within 1 mm of the margin. One of 13 patients (8%) had coexistent invasive ductal carcinoma. Average follow -up for the entire group was 77 months. Patients with positive margins remained free of tumor progression or recurrence for 89 months and patients with close margins also remained disease free during a 64-month follow-up period. No tumors recurred out of the entire group. Conclusion.--Granular cell tumors of the breast have little long-term risk for recurrence, even when excised with positive margins. Surgical evaluation after nonexcisional biopsy may still be indicated to assess for the possible association of colocalized carcinoma. (Arch Pathol Lab Med. 2011;135:890-895), Granular cell tumors (GCTs) are Schwann cell-derived neoplasms that frequently involve skin and soft tissues. (1) Most commonly, they present in the tongue in middle-aged patients but also occur in [...]

Context.--Machine learning applications in the pathology clinical domain are emerging rapidly. As decision support systems continue to mature, laboratories will increasingly need guidance to evaluate their performance in clinical practice. Currently there are no formal guidelines to assist pathology laboratories in verification and/or validation of such systems. These recommendations are being proposed for the evaluation of machine learning systems in the clinical practice of pathology. Objective.--To propose recommendations for performance evaluation of in vitro diagnostic tests on patient samples that incorporate machine learning as part of the preanalytical, analytical, or postanalytical phases of the laboratory workflow. Topics described include considerations for machine learning model evaluation including risk assessment, predeployment requirements, data sourcing and curation, verification and validation, change control management, human-computer interaction, practitioner training, and competency evaluation. Data Sources.--An expert panel performed a review of the literature, Clinical and Laboratory Standards Institute guidance, and laboratory and government regulatory frameworks. Conclusions.--Review of the literature and existing documents enabled the development of proposed recommendations. This white paper pertains to performance evaluation of machine learning systems intended to be implemented for clinical patient testing. Further studies with real-world clinical data are encouraged to support these proposed recommendations. Performance evaluation of machine learning models is critical to verification and/or validation of in vitro diagnostic tests using machine learning intended for clinical practice. [ABSTRACT FROM AUTHOR]