-
Archives of Pathology & Laboratory... Jan 2022The presence of allogeneic contamination impacts clinical reporting in cancer next-generation sequencing specimens. Although consensus guidelines recommend the...
CONTEXT.—
The presence of allogeneic contamination impacts clinical reporting in cancer next-generation sequencing specimens. Although consensus guidelines recommend the identification of contaminating DNA as a part of quality control, implementation of contamination assessment methods in clinical molecular diagnostic laboratories has not been reported in the literature.
OBJECTIVE.—
To develop and implement a method to assess allogeneic contamination in clinical cancer next-generation sequencing specimens.
DESIGN.—
We describe a method to detect contamination based on the evaluation of single-nucleotide polymorphic sites from tumor-only specimens. We validate this method and apply it to a large cohort of cancer sequencing specimens.
RESULTS.—
Identification of specimen contamination was validated via in silico and in vitro mixtures, and reference range and reproducibility were established in a panel of normal specimens. The algorithm accurately detects an episode of systemic contamination due to reagent impurity. We prospectively applied this algorithm across 7571 clinical cancer specimens from a targeted next-generation sequencing panel, in which 262 specimens (3.5%) were predicted to be affected by greater than 5% contamination.
CONCLUSIONS.—
Allogeneic contamination can be inferred from intrinsic cancer next-generation sequencing data without paired normal sequencing. The adoption of this approach can be useful as a quality control measure for laboratories performing clinical next-generation sequencing.
Topics: High-Throughput Nucleotide Sequencing; Humans; Neoplasms; Pathology, Molecular; Polymorphism, Single Nucleotide; Reproducibility of Results
PubMed: 34015814
DOI: 10.5858/arpa.2020-0679-OA -
Molecular Biology Reports Oct 2022During the course of 2020, the outbreak of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) spread rapidly across the world. Clinical diagnostic testing for... (Review)
Review
During the course of 2020, the outbreak of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) spread rapidly across the world. Clinical diagnostic testing for SARS-Cov-2 infection has relied on the real-time Reverse Transcriptase Polymerase Chain Reaction and is considered the gold standard assay. Commercial vendors and laboratories quickly mobilised to develop diagnostic tests to detect the novel coronavirus, which was fundamentally important in the pandemic response. These SARS-Cov-2 assays were developed in line with the Food Drug Administration-Emergency Use Authorization guidance. Although new tests are continuously being developed, information about SARS-CoV-2 diagnostic molecular test accuracy has been limited and at times controversial. Therefore, the analytical and clinical performance of SARS-CoV-2 test kits should be carefully considered by the appropriate regulatory authorities and evaluated by independent laboratory validation. This would provide improved end-user confidence in selecting the most reliable and accurate diagnostic test. Moreover, it is unclear whether some of these rapidly developed tests have been subjected to rigorous quality control and assurance required under good manufacturing practice. Variable target gene regions selected for currently available tests, potential mutation in target gene regions, non-standardized pre-analytic phase, a lack of manufacturer independent validation data all create difficulties in selecting tests appropriate for different countries and laboratories. Here we provide information on test criteria which are important in the assessment and selection of SARS-CoV-2 molecular diagnostic tests and outline the potential issues associated with a proportion of the tests on the market.
Topics: COVID-19; COVID-19 Testing; Humans; Pandemics; Pathology, Molecular; SARS-CoV-2; Sensitivity and Specificity
PubMed: 35441938
DOI: 10.1007/s11033-022-07455-5 -
The Journal of Molecular Diagnostics :... May 2022Systematic implementation of bioinformatics resources for next generation sequencing (NGS)-based clinical testing is an arduous undertaking. One of the key challenges... (Review)
Review
Systematic implementation of bioinformatics resources for next generation sequencing (NGS)-based clinical testing is an arduous undertaking. One of the key challenges involves developing an ecosystem of information technology infrastructure for enabling scalable and reproducible bioinformatics services that is resilient and secure for handling genetic and protected health information, often embedded in an existing non-bioinformatics-oriented infrastructure. Container technology provides an ideal and infrastructure-agnostic solution for molecular laboratories developing and using bioinformatics pipelines, whether on-premise or using the cloud. A container is a technology that provides a consistent computational environment and enables reproducibility, scalability, and security when developing NGS bioinformatics analysis pipelines. Containers can increase the bioinformatics team's productivity by automating and simplifying the maintenance of complex bioinformatics resources, as well as facilitate validation, version control, and documentation necessary for clinical laboratory regulatory compliance. Although there is increasing popularity in adopting containers for developing NGS bioinformatics pipelines, there is wide variability and inconsistency in the usage of containers that may result in suboptimal performance and potentially compromise the security and privacy of protected health information. In this article, the authors highlight the current state and provide best or recommended practices for building, using containers in NGS bioinformatics solutions in a clinical setting with focus on scalability, optimization, maintainability, and data security.
Topics: Computational Biology; Ecosystem; High-Throughput Nucleotide Sequencing; Humans; Pathology, Molecular; Reproducibility of Results; Software
PubMed: 35189355
DOI: 10.1016/j.jmoldx.2022.01.006 -
American Journal of Clinical Pathology Sep 2022The aim of this study was to assess expectations of performance that exist in the marketplace for entry-level pathologists' assistants (PathAs), defined as recent...
OBJECTIVES
The aim of this study was to assess expectations of performance that exist in the marketplace for entry-level pathologists' assistants (PathAs), defined as recent graduates of a pathologists' assistant program on their first day of employment.
METHODS
A voluntary, anonymous survey was distributed to pathologist and PathA members of the American Society for Clinical Pathology by email. We assessed 98 professional activities of PathAs using a 5-point scale of expectations based on levels of trust placed in them. We also collected demographic information.
RESULTS
A total of 728 participants responded to this survey, including 280 pathologists and 448 PathAs. We classified 98 activities according to expectations: independent performance (20/98), developing independence (48/98), and not expected of PathAs (5/98). Some activities (25/98) were indeterminate yet likely represent areas of developing independence.
CONCLUSIONS
This study demonstrates an expectation for entry-level PathAs to perform some activities included in the scope of practice independently but eventually to develop independent proficiency for most professional activities. A minority of activities were identified as responsibilities that are not expected of PathAs. Entry-level PathAs, therefore, remain "works in progress," with an expectation for independent performance of core activities while developing abilities in many areas of professional practice.
Topics: Humans; Motivation; Pathologists; Pathology, Clinical; Surveys and Questionnaires; United States
PubMed: 35760554
DOI: 10.1093/ajcp/aqac065 -
Journal of Medical Virology Jun 2021Respiratory syncytial virus (RSV) is the leading cause of acute respiratory infections in children worldwide and a frequent cause of hospitalization. Rapid diagnostic... (Comparative Study)
Comparative Study
BACKGROUND
Respiratory syncytial virus (RSV) is the leading cause of acute respiratory infections in children worldwide and a frequent cause of hospitalization. Rapid diagnostic assays (RDAs) are available for RSV and they help guide management; however, they are underutilized in developing countries. We compared molecular diagnostics to RSV RDA in hospitalized children in Amman, Jordan.
MATERIALS AND METHODS
Children under 2 years of age, admitted with fever and/or respiratory symptoms were enrolled prospectively from March 2010 to 2012. Demographic and clinical data were collected through parent/guardian interviews and medical chart abstraction. RSV RDAs were performed, and nasal/throat swabs were tested for RSV using quantitative reverse transcription-polymerase chain reaction (qRT-PCR).
RESULTS
RSV RDA and PCR were performed on specimens from 1271 subjects. RSV RDA had a sensitivity of 26% and a specificity of 99%, with positive and negative predictive values of 98.6% and 43%, respectively. RDA-positive patients had fewer days of symptoms at presentation and were more likely to have a history of prematurity, lower birth weight, require supplemental oxygen, and a longer hospitalization as compared with subjects with negative RDA. Multivariate analysis showed only lower birth weight, lack of cyanosis on examination, and lower cycle threshold to be independently associated with positive RDA (p ≤ .001).
CONCLUSION
RSV RDAs had high specificity, but low sensitivity as compared with qRT-PCR. Positive RDA was associated with patients with a more severe disease, as indicated by oxygen use, longer length of stay, and higher viral load. Implementation of RDAs in developing countries could be an inexpensive and expedient method for predicting RSV disease severity and guiding management.
Topics: Female; Fever; Hospitalization; Humans; Infant; Infant, Newborn; Jordan; Male; Pathology, Molecular; Pharynx; Predictive Value of Tests; Respiratory Syncytial Virus Infections; Respiratory Syncytial Virus, Human; Respiratory Tract Infections; Seasons; Viral Load
PubMed: 32966624
DOI: 10.1002/jmv.26546 -
The American Journal of Pathology May 2021Correct use of statistical methods is important to ensure the reliability and value of the published experimental pathology literature. Considering increasing interest... (Review)
Review
Correct use of statistical methods is important to ensure the reliability and value of the published experimental pathology literature. Considering increasing interest in the quality of statistical reporting in pathology, the statistical methods used in 10 recent issues of the American Journal of Pathology were reviewed. The statistical tests performed in the articles were summarized, with attention to their implications for contemporary pathology research and practice. Among the 195 articles identified, 93% reported using one or more statistical tests. Retrospective statistical review of the articles revealed several key findings. First, tests for normality were infrequently reported, and parametric hypothesis tests were overutilized. Second, studies reporting multisample hypothesis tests (eg, analysis of variance) infrequently performed post hoc tests to explore differences between study groups. Third, correlation, regression, and survival analysis techniques were underutilized. On the basis of these findings, a primer on relevant statistical concepts and tests is presented, including issues related to optimal study design, descriptive and comparative statistics, and regression, correlation, survival, and genetic data analysis.
Topics: Humans; Pathology; Periodicals as Topic; Reproducibility of Results; Research Design; Retrospective Studies; Statistics as Topic
PubMed: 33652018
DOI: 10.1016/j.ajpath.2021.02.009 -
European Urology Oncology Jun 2024Computational pathology is a new interdisciplinary field that combines traditional pathology with modern technologies such as digital imaging and machine learning to... (Review)
Review
CONTEXT
Computational pathology is a new interdisciplinary field that combines traditional pathology with modern technologies such as digital imaging and machine learning to better understand the diagnosis, prognosis, and natural history of many diseases.
OBJECTIVE
To provide an overview of digital and computational pathology and its current and potential applications in renal cell carcinoma (RCC).
EVIDENCE ACQUISITION
A systematic review of the English-language literature was conducted using the PubMed, Web of Science, and Scopus databases in December 2022 according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines (PROSPERO ID: CRD42023389282). Risk of bias was assessed according to the Prediction Model Study Risk of Bias Assessment Tool.
EVIDENCE SYNTHESIS
In total, 20 articles were included in the review. All the studies used a retrospective design, and all digital pathology techniques were implemented retrospectively. The studies were classified according to their primary objective: detection, tumor characterization, and patient outcome. Regarding the transition to clinical practice, several studies showed promising potential. However, none presented a comprehensive assessment of clinical utility and implementation. Notably, there was substantial heterogeneity for both the strategies used for model building and the performance metrics reported.
CONCLUSIONS
This review highlights the vast potential of digital and computational pathology for the detection, classification, and assessment of oncological outcomes in RCC. Preliminary work in this field has yielded promising results. However, these models have not yet reached a stage where they can be integrated into routine clinical practice.
PATIENT SUMMARY
Computational pathology combines traditional pathology and technologies such as digital imaging and artificial intelligence to improve diagnosis of disease and identify prognostic factors and new biomarkers. The number of studies exploring its potential in kidney cancer is rapidly increasing. However, despite the surge in research activity, computational pathology is not yet ready for widespread routine use.
Topics: Humans; Carcinoma, Renal Cell; Kidney Neoplasms; Pathology, Clinical; Computational Biology; Machine Learning
PubMed: 37925349
DOI: 10.1016/j.euo.2023.10.018 -
Journal of Clinical Pathology Oct 2019Rapid procurement of a wide variety of metastatic and primary cancers and normal tissues after death through rapid autopsy opens largely unexplored avenues in cancer...
AIMS
Rapid procurement of a wide variety of metastatic and primary cancers and normal tissues after death through rapid autopsy opens largely unexplored avenues in cancer research. We describe a high-volume rapid research autopsy programme at a large academic medical centre.
METHODS
Advanced-stage cancer patients, most commonly inpatients in palliative care facilities, were approached to participate in a cancer research autopsy programme with the goal of acquiring multidimensionally annotated tissue for cancer research. On death of an enrolled patient, a predetermined notification plan was enacted, with the medical oncologist/clinical research coordinator informing a team of pathologists, researchers and allied staff. Quality assurance metrics were measured. Thereafter, tissues were annotated in a tissue bioinformatics database and linked to electronic patient records. All banked tissues were reviewed for tumour integrity, including DNA and RNA quality.
RESULTS
Over 100 rapid research autopsies from diverse cancer sites were performed, and specimens were procured and annotated with detailed clinical information, including treatment and response. Tissues were successfully enabling studies of tumour immunology, xenografts, genomics and proteomics.
CONCLUSIONS
Large-scale rapid procurement and biobanking of cancer tissues from a rapid autopsy programme is feasible. Multidisciplinary integration between health and administrative staff from medical oncology, palliative care, pathology and biospecimen sciences is critical for the success of this challenging endeavour.
Topics: Adult; Aged; Aged, 80 and over; Autopsy; Female; Genomics; Humans; Male; Medical Oncology; Middle Aged; Neoplasms; Palliative Care; Pathology, Surgical; Proteomics; Tissue Banks; Young Adult
PubMed: 31262953
DOI: 10.1136/jclinpath-2019-205874 -
Pathology, Research and Practice Dec 2022The development of whole slide image and deep neural network technologies has contributed to the paradigm shift in diagnostic pathology and has received much attention... (Review)
Review
BACKGROUND
The development of whole slide image and deep neural network technologies has contributed to the paradigm shift in diagnostic pathology and has received much attention from researchers, with related publications increasing yearly and "exploding" in recent years. However, few studies have systematically reviewed "digital pathology" using bibliometric tools. In this study, we will use multiple approaches to visualize and analyze "digital pathology" to provide a comprehensive and objective picture of the field's historical evolution and future development.
METHODS
We use VOSviewer, CiteSpace, Gephi, and R to analyze the authors, institutional and national collaboration networks, keyword co-occurrence, and co-citation analysis to visualize the current status of global digital pathology research.
RESULTS
Digital pathology-related research is mainly active in "molecular, biological, and immunology" journal groups, "pharmaceutical, medical, and clinical" journal groups, and "psychology, education, and health" journal groups; in addition to "digital pathology," "diagnosis," "deep learning," "histopathology," and "surgical pathology" are also active research topics; the U.S. has significant research results in digital pathology, with the top 10 publishing institutions all coming from the U.S. In the past two decades, global digital pathology-related research can be divided into two major research areas. One is about system verification and optimization of WSI, and the other is about the application and development of artificial intelligence technology in digital pathology. Among them, based on the development of computer technology and the update of the machine learning concept, the research results for deep neural network technologies have been more concentrated in recent years. The robust performance of deep neural networks in feature extraction and image analysis provides a new research direction for improving digital pathology-aided diagnosis systems, which is where the research hotspots have been in recent years.
CONCLUSIONS
The bibliometric analysis may help better understand the current status of research within the field of digital pathology and provide references and lessons for future related research.
Topics: Humans; Artificial Intelligence; Bibliometrics; Pathology, Surgical; Image Processing, Computer-Assisted
PubMed: 36274267
DOI: 10.1016/j.prp.2022.154171 -
American Journal of Clinical Pathology Nov 2021Corruption is a widely acknowledged problem in the health sector of low- and middle-income countries (LMICs). Yet, little is known about the types of corruption that... (Review)
Review
OBJECTIVES
Corruption is a widely acknowledged problem in the health sector of low- and middle-income countries (LMICs). Yet, little is known about the types of corruption that affect the delivery of pathology and laboratory medicine (PALM) services. This review is a first step at examining corruption risks in PALM.
METHODS
We performed a critical review of medical literature focused on health sector corruption in LMICs. To provide context, we categorized cases of laboratory-related fraud and abuse in the United States.
RESULTS
Forms of corruption in LMICs that may affect the provision of PALM services include informal payments, absenteeism, theft and diversion, kickbacks, self-referral, and fraudulent billing.
CONCLUSIONS
Corruption represents a functional reality in many LMICs and hinders the delivery of services and distribution of resources to which individuals and entities are legally entitled. Further study is needed to estimate the extent of corruption in PALM and develop appropriate anticorruption strategies.
Topics: Fraud; Humans; Laboratories; Pathology; United States
PubMed: 34219146
DOI: 10.1093/ajcp/aqab046