Clinical impact and frequency of anatomic pathology errors in cancer diagnoses
- PMID: 16216029
- DOI: 10.1002/cncr.21431
Clinical impact and frequency of anatomic pathology errors in cancer diagnoses
Abstract
Background: To the authors' knowledge, the frequency and clinical impact of errors in the anatomic pathology diagnosis of cancer have been poorly characterized to date.
Methods: The authors examined errors in patients who underwent anatomic pathology tests to determine the presence or absence of cancer or precancerous lesions in four hospitals. They analyzed 1 year of retrospective errors detected through a standardized cytologic-histologic correlation process (in which patient same-site cytologic and histologic specimens were compared). Medical record reviews were performed to determine patient outcomes. The authors also measured the institutional frequency, cause (i.e., pathologist interpretation or sampling), and clinical impact of diagnostic cancer errors.
Results: The frequency of errors in cancer diagnosis was found to be dependent on the institution (P < 0.001) and ranged from 1.79-9.42% and from 4.87-11.8% of all correlated gynecologic and nongynecologic cases, respectively. A statistically significant association was found between institution and error cause (P < 0.001); the cause of errors resulting from pathologic misinterpretation ranged from 5.0-50.7% (the remainder were due to clinical sampling). A statistically significant association was found between institution and assignment of the clinical impact of error (P < 0.001); the aggregated data demonstrated that for gynecologic and nongynecologic errors, 45% and 39%, respectively, were associated with harm. The pairwise kappa statistic for interobserver agreement on cause of error ranged from 0.118-0.737.
Conclusions: Errors in cancer diagnosis are reported to occur in up to 11.8% of all reviewed cytologic-histologic specimen pairs. To the authors' knowledge, little agreement exists regarding whether pathology errors are secondary to misinterpretation or poor clinical sampling of tissues and whether pathology errors result in serious harm.
Copyright 2005 American Cancer Society
Similar articles
-
The "Big Dog" effect: variability assessing the causes of error in diagnoses of patients with lung cancer.J Clin Oncol. 2006 Jun 20;24(18):2808-14. doi: 10.1200/JCO.2005.04.3661. J Clin Oncol. 2006. PMID: 16782918
-
Improving patient safety by examining pathology errors.Clin Lab Med. 2004 Dec;24(4):849-63. doi: 10.1016/j.cll.2004.05.014. Clin Lab Med. 2004. PMID: 15555746 Review.
-
Use of a new method in reaching consensus on the cause of cytologic-histologic correlation discrepancy.Am J Clin Pathol. 2006 Dec;126(6):836-42. doi: 10.1309/1790JN2YWCG833VU. Am J Clin Pathol. 2006. PMID: 17074685
-
Cytohistologic discrepancies: a means to improve pathology practice and patient outcomes.Am J Clin Pathol. 2002 Apr;117(4):567-73. doi: 10.1309/0N45-CC0E-R802-D9NG. Am J Clin Pathol. 2002. PMID: 11939731
-
Measuring errors in surgical pathology in real-life practice: defining what does and does not matter.Am J Clin Pathol. 2007 Jan;127(1):144-52. doi: 10.1309/5KF89P63F4F6EUHB. Am J Clin Pathol. 2007. PMID: 17145620 Review.
Cited by
-
Grading of Gliomas by Contrast-Enhanced CT Radiomics Features.J Biomed Phys Eng. 2024 Apr 1;14(2):151-158. doi: 10.31661/jbpe.v0i0.2306-1628. eCollection 2024 Apr. J Biomed Phys Eng. 2024. PMID: 38628893 Free PMC article.
-
Understanding the errors made by artificial intelligence algorithms in histopathology in terms of patient impact.NPJ Digit Med. 2024 Apr 10;7(1):89. doi: 10.1038/s41746-024-01093-w. NPJ Digit Med. 2024. PMID: 38600151 Free PMC article. Review.
-
An Experimental Platform for Tomographic Reconstruction of Tissue Images in Brightfield Microscopy.Sensors (Basel). 2023 Nov 23;23(23):9344. doi: 10.3390/s23239344. Sensors (Basel). 2023. PMID: 38067718 Free PMC article.
-
Development and validation of a deep learning algorithm for pattern-based classification system of cervical cancer from pathological sections.Heliyon. 2023 Aug 21;9(8):e19229. doi: 10.1016/j.heliyon.2023.e19229. eCollection 2023 Aug. Heliyon. 2023. PMID: 37664714 Free PMC article.
-
Advancing Research on Medical Image Perception by Strengthening Multidisciplinary Collaboration.JNCI Cancer Spectr. 2022 Jan 5;6(1):pkab099. doi: 10.1093/jncics/pkab099. JNCI Cancer Spectr. 2022. PMID: 35699495 Free PMC article.
Publication types
MeSH terms
Grants and funding
LinkOut - more resources
Full Text Sources
