Archives of pathology & laboratory medicine最新文献

Context.—: The College of American Pathologists (CAP) surveys provide national benchmarks of pathology practice.

Objective.—: To investigate pancreaticobiliary cytology practice in domestic and international laboratories in 2021.

Design.—: We analyzed data from the CAP Pancreaticobiliary Cytology Practice Supplemental Questionnaire that was distributed to laboratories participating in the 2021 CAP Nongynecologic Cytopathology Education Program.

Results.—: Ninety-three percent (567 of 612) of respondent laboratories routinely evaluated pancreaticobiliary cytology specimens. Biliary brushing (85%) was the most common pancreaticobiliary cytology specimen evaluated, followed by pancreatic fine-needle aspiration (79%). The most used sampling methods reported by 235 laboratories were 22-gauge needle for fine-needle aspiration (62%) and SharkCore needle for fine-needle biopsy (27%). Cell block was the most used slide preparation method (76%), followed by liquid-based cytology (59%) for pancreatic cystic lesions. Up to 95% (303 of 320) of laboratories performed rapid on-site evaluation (ROSE) on pancreatic solid lesions, while 56% (180 of 320) performed ROSE for cystic lesions. Thirty-six percent (193 of 530) of laboratories used the Papanicolaou Society of Cytopathology System for Reporting Pancreaticobiliary Cytology in 2021. Among all institution types, significant differences in specimen volume, specimen type, ROSE practice, and case sign-out were identified. Additionally, significant differences in specimen type, slide preparation, and ROSE practice were found.

Conclusions.—: This is the first survey from the CAP to investigate pancreaticobiliary cytology practice. The findings reveal significant differences among institution types and between domestic and international laboratories. These data provide a baseline for future studies in a variety of practice settings.

Context: In recent years, several reporting systems have been developed by national and international cytopathology organizations to standardize the evaluation of specific cytopathology specimen types.

Objective: To assess the current implementation rates, implementation methods, and barriers to implementation of commonly used nongynecologic reporting systems in cytopathology laboratories.

Design: Data were analyzed from a survey developed by the College of American Pathologists Cytopathology Committee and distributed to participants in the College of American Pathologists Nongynecologic Cytopathology Education Program mailing.

Results: Nongynecologic reporting systems with the highest rate of adoption were the Bethesda System for Reporting Thyroid Cytopathology, 2nd edition (74.1%; 552 of 745); the Paris System for Reporting Urinary Cytology (53.9%; 397 of 736); and the Milan System for Reporting Salivary Gland Cytopathology (29.1%; 200 of 688). The most common reason given for not adopting a reporting system was satisfaction with a laboratory's current system. Implementation varied among laboratories with regard to which stakeholders were involved in deciding to implement a system and the amount of education provided during the implementation process.

Conclusions: The implementation of nongynecologic reporting systems in cytopathology laboratories was highly variable.

Context: Social media (SM) use in pathology and medicine today is widespread, receives active advocacy, and is said to bring a host of benefits. In latter days, the harmful effects of SM have received attention, but they have yet been followed by greater encouragement of professionalized SM usage. SM use in medicine has seen adoption in parallel to its general ascendancy, even though the platforms are products with purposes misaligned with the practice of medicine.

Objective: To (1) characterize premises and forces that propel professional SM platform adoption and use, and (2) examine wide-ranging literature, both medical and nonmedical, that substantiates the premises and to find counteracting perspectives and evidence.

Data sources: Review of the literature using relevant keyword searches in PubMed, Google Scholar, Dimensions, and Web of Science for articles that study/describe professional SM use in pathology and medicine. Additionally, we examined business, technology, and social sciences literature and high-quality gray literature (newspapers, books, blogs) that addressed questions in relation to the topic of professional SM adoption.

Conclusions: We identified 6 major premises as motivators of professional SM use and highlight significant counteracting factors. We conclude that the harms of professionalized SM use have not been fully considered in the medical literature and that a change in direction and the creation of new communication platforms would be beneficial.

Context: Infection-related glomerulonephritis (IRGN) usually manifests as a proliferative immune-complex glomerulonephritis. The degree of renal dysfunction at presentation can vary. Association with histologic features on kidney biopsy remains unknown.

Objective: To study the correlation between renal function in IRGN at the time of biopsy and the severity of histologic features.

Design: Culture-proven IRGN cases at our facility were included and divided based on estimated glomerular filtration rate (eGFR) 15 ml/min/1.73 m2. Patients' demographic and pathologic findings were obtained from electronic medical records and kidney biopsy reports.

Results: In total, 104 cases were diagnosed with IRGN on biopsy (mean age, 55.6 ± 15.6 years; male, n = 79 [76%]; median eGFR, 14.5 mL/min/1.73 m2), and 51 of 104 showed eGFR <15 mL/min/1.73 m2. Among all the histologic features assessed, only percent tubules with red blood cell (RBC) casts showed statistical difference, being significantly higher in the lower-eGFR group (P = .004). Multivariable logistic regression analysis also showed that %tubules with RBC casts were associated with lower eGFR (odds ratio, 1.12; 95% CI, 1.01-1.24; P = .01). Patients with 5% or more RBC casts (n = 31) showed a lower eGFR (P = .02) and a higher %cellular crescent (P < .001) compared with those with less than 5% RBC casts. Patients with concomitant anticoagulant therapy (n = 11) showed higher percentages of RBC casts than those without anticoagulants (P = .02).

Conclusions: Particular attention to the extent of RBC casts on kidney biopsy is recommended in patients with IRGN because these portend worse renal dysfunction, more so in patients requiring anticoagulation (including for hemodialysis) because they are especially vulnerable to developing anticoagulant-related nephropathy.

Context: Droplet digital polymerase chain reaction (ddPCR) is a sensitive method to detect common pathogenic EGFR mutations in non-small cell lung cancer. Although targeted assays have not been specifically designed to detect them, uncommon EGFR mutations have been linked to response to targeted therapy.

Objective: To describe atypical ddPCR patterns that correspond to uncommon but clinically actionable EGFR mutations.

Design: A cohort of 1134 consecutive non-small cell lung cancers that underwent targeted next-generation sequencing was reviewed. Uncommon EGFR mutations involving probe binding sites were evaluated by ddPCR.

Results: Two hundred fifty-five of 1134 cancers (22.5%) harbored pathogenic EGFR mutations. One hundred eighty-six of 255 (72.9%) had canonical EGFR exon 19 deletion or exon 21 p.L858R variants designed for detection by ddPCR. An additional 25 of 255 cases (9.8%) had uncommon EGFR mutations within the probe-binding site, including 1 case with concurrent uncommon mutations in both exon 19 and exon 21. These mutations included uncommon EGFR exon 19 deletions (n = 6), EGFR exon 19 substitutions p.L747P (n = 3) and p.L747A (n = 1), dinucleotide substitutions leading to EGFR p.L858R (n = 5), EGFR exon 21 substitutions p.K860I (n = 1) and p.L861Q (n = 9), and EGFR p.[L858R;K860I] (n = 1). Droplet digital polymerase chain reaction generated atypical but reproducible signal for each of these uncommon variants.

Conclusions: Droplet digital polymerase chain reaction analysis of uncommon pathogenic EGFR variants can yield unique and reproducible results. Recognition of atypical patterns in EGFR ddPCR testing can prompt confirmatory molecular testing and aid appropriate targeted therapy selection for patients with non-small cell lung cancer.

Context: Antinuclear antibodies (ANAs) against certain antigens are useful for identifying autoimmune disorders. Although new solid phase-based immunoassays have been developed for evaluating ANAs, the conventional line immunoassay (LIA) is commonly used in clinical practice.

Objective: To compare the clinical performance of 2 newly developed methods for detecting specific ANAs with LIA.

Design: Six hundred ninety-six serum samples were collected from 559 patients with autoimmune disease (AID) and 137 controls. The samples were screened by using the LIA, digital liquid chip method (DLCM), and chemiluminescent immunoassay (CLIA) for specific ANAs. The agreement across assays and the clinical performance of each assay in diagnosing ANA-associated rheumatic diseases (AARDs) were evaluated.

Results: Almost perfect agreement was observed among all assays for anti-centromere protein B (κ = 0.85-0.97), anti-ribosome P (κ = 0.85-0.88), anti-SSA 52 (κ = 0.86-0.89), and anti-SSA 60 (κ = 0.89-0.91); moderate to substantial agreement was detected for the autoantibodies against Sm, Jo-1, ribonucleoprotein, Scl-70, and SSB (κ = 0.55-0.80). LIA exhibited better sensitivity for diagnosing AARDs, while DLCM and CLIA demonstrated higher specificity. In the subset of AIDs, especially systemic lupus erythematosus, antibody positive percentages varied greatly between assays.

Conclusions: The 3 assays showed comparable qualitative agreement; however, the standardization of testing for ANAs remains challenging owing to intermanufacturer variations. Moreover, DLCM and CLIA exhibited better specificity in distinguishing non-AID individuals, whereas LIA was more sensitive in diagnosing AARDs.

Context: Next-generation sequencing-based approaches using RNA have increasingly been used by clinical laboratories for the detection of fusion genes, intragenic rearrangements, and exon-skipping events. Correspondingly, the College of American Pathologists (CAP) has advanced RNA sequencing proficiency testing (PT) to ensure optimal performance of these assays.

Objective: To report on laboratory performance and practices of RNA sequencing for the detection of fusion genes, intragenic rearrangements, and exon-skipping events using CAP PT data from 8 mailings (2018-A through 2021-B).

Design: CAP PT RNA sequencing program results from 153 laboratories across 24 proficiency test specimens, interrogating 22 distinct engineered fusion transcripts, were analyzed for correct identification of the fusion event, associated performance variables, and laboratory practices.

Results: Overall, the 4-year program detection rate (sensitivity) was 95.5% (1486 of 1556 results). False-negative rates were 3.6% (53 of 1463) and 18.3% (17 of 93) for fusion gene and intragenic rearrangement/exon-skipping events, respectively. Only 19 false-positive results were reported among the 8 PT mailings, and most were likely the result of preanalytical or postanalytical errors. There were no practice characteristics (eg, instrumentation, sequencing method) significantly associated with the fusion detection results.

Conclusions: These data reveal a high overall sensitivity and specificity for fusion gene detection by participating laboratories using clinical RNA sequencing. Performance was comparable across all laboratories, regardless of methodology. The fraction of false-negative results for intragenic rearrangement/exon-skipping events was greater than that for the chimeric fusion genes. False-negative results could not be attributed to any specific practice characteristics.

Context: Loose tumor cells and tumor cell clusters can be recognized in the lumen of intratumoral pulmonary arteries of resected non-small cell lung cancer specimens. It is unclear whether these should be considered tumor-emboli, and as such could predict a worsened prognosis.

Objective: To investigate the nature and prognostic impact of pulmonary artery intraluminal tumor cells.

Design: This multicenter study involved an exploratory pilot study and a validation study from 3 institutions. For the exploratory pilot study, a retrospective pulmonary resection cohort of primary adenocarcinomas, diagnosed between November 2007 and November 2010, were scored for the presence of tumor cells, as well as potentially other cells in the intravascular spaces, using hematoxylin-eosin and cytokeratin 7 (CK7) stains. In the validation part, 2 retrospective cohorts of resected pulmonary adenocarcinomas, between January 2011 and December 2016, were included. Recurrence-free survival (RFS) and overall survival (OS) data were collected.

Results: In the pilot study, CK7+ intravascular cells, mainly tumor cells, were present in 23 of 33 patients (69.7%). The 5-year OS for patients with intravascular tumor cells was 61%, compared with 40% for patients without intravascular tumor cells (P = .19). In the validation study, CK7+ intravascular tumor cells were present in 41 of 70 patients (58.6%). The 5-year RFS for patients with intravascular tumor cells was 80.0%, compared with 80.6% in patients without intravascular tumor cells (P = .52). The 5-year OS rates were, respectively, 82.8% and 71.6% (P = .16).

Conclusions: Loose tumor cells in pulmonary arterial lumina were found in most non-small cell lung cancer resection specimens and were not associated with a worse RFS or OS. Therefore, most probably they represent an artifact.

Context: Automated prostate cancer detection using machine learning technology has led to speculation that pathologists will soon be replaced by algorithms. This review covers the development of machine learning algorithms and their reported effectiveness specific to prostate cancer detection and Gleason grading.

Objective: To examine current algorithms regarding their accuracy and classification abilities. We provide a general explanation of the technology and how it is being used in clinical practice. The challenges to the application of machine learning algorithms in clinical practice are also discussed.

Data sources: The literature for this review was identified and collected using a systematic search. Criteria were established prior to the sorting process to effectively direct the selection of studies. A 4-point system was implemented to rank the papers according to their relevancy. For papers accepted as relevant to our metrics, all cited and citing studies were also reviewed. Studies were then categorized based on whether they implemented binary or multi-class classification methods. Data were extracted from papers that contained accuracy, area under the curve (AUC), or κ values in the context of prostate cancer detection. The results were visually summarized to present accuracy trends between classification abilities.

Conclusions: It is more difficult to achieve high accuracy metrics for multiclassification tasks than for binary tasks. The clinical implementation of an algorithm that can assign a Gleason grade to clinical whole slide images (WSIs) remains elusive. Machine learning technology is currently not able to replace pathologists but can serve as an important safeguard against misdiagnosis.

Context: In 2021 the World Health Organization distributed a new classification of central nervous system tumors that incorporated modern testing modalities in the diagnosis. Although universally accepted as a scientifically superior system, this schema has created controversy because its deployment globally is challenging in the best of circumstances and impossible in resource-poor health care ecosystems. Compounding this problem is the significant challenge that neuropathologists with expertise in central nervous system tumors are rare.

Objective: To demonstrate diagnostic use of simple unsupervised machine learning techniques using publicly available data sets. I also discuss some potential solutions to the deployment of neuropathology classification in health care ecosystems burdened by this classification schema.

Data sources: The Cancer Genome Atlas RNA sequencing data from low-grade and high-grade gliomas.

Conclusions: Methylation-based classification will be unable to solve all diagnostic problems in neuropathology. Information theory quantifications generate focused workflows in pathology, resulting in prevention of ordering unnecessary tests and identifying biomarkers that facilitate diagnosis.