Journal articles: 'Cancer grading'

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Epstein, Jonathan I. "Prostate Cancer Grading." American Journal of Surgical Pathology 40, no. 1 (2016): 137. http://dx.doi.org/10.1097/pas.0000000000000563.

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Thomas, Marie S. "GRADING CANCER HANDOUTS." AJN, American Journal of Nursing 90, no. 11 (1990): 27. http://dx.doi.org/10.1097/00000446-199011000-00020.

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Herrera, Guillermo A., Elba A. Turbat-Herrera, and David G. Bostwick. "Prostate Cancer Grading." Pathology Case Reviews 19, no. 3 (2014): 108–17. http://dx.doi.org/10.1097/pcr.0000000000000033.

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Thomas, Marie S. "Grading Cancer Handouts." American Journal of Nursing 90, no. 11 (1990): 27. http://dx.doi.org/10.2307/3464068.

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Koshrawipour, Tanja, Ingo Stricker, Andrea Tannapfel, Lars Steinstraesser, Stefan Langer, and Andrej Ring. "Risk factors leading to grading changes within 300 low-grade soft tissue sarcomas." Journal of Clinical Oncology 30, no. 15_suppl (2012): 10059. http://dx.doi.org/10.1200/jco.2012.30.15_suppl.10059.

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10059 Background: Soft tissue sarcomas (STS) are rare, mesenchymal derived tumors. Based on malignancy, three grades are distinguished with G1 equaling low grade, G2 intermediate grade and G3 high grade, respectively. Studies have shown that some G1 tumors which underwent complete surgical resection reoccurred as lesions with a grading shift from G1 to higher malignancy. This grading change is referred to as up grading. Patients with grading changes were thoroughly examined in our study. Our aim was to find possible risk factors for up gradings, such as age, localization of tumor and tumor type. Methods: This retrospective case control study evaluated 333 Patients, who, between 1996 to 2011 were treated for G1 STS at Bergmannsheil Bochum, university clinic. These patients received complete initial surgical resection. Among our 333 patients, 9.9% (n=33) developed up gradings of their STS. These were then reviewed more closely in the aim of finding possible risk factors. We did not exclude any patients from our data or deliberately pick any grading changers and regard our collective as randomly sampled. The processed data includes age, gender, tumor type, tumor localization, occurrence of recidive and grading change. Results: Patients with up gradings were found to have a higher mean age of 4, 5 years than reference collective. The tumor type has a strong, statistically significant effect on grading change as patients with fibrosarcomas have a threefold risk of developing up gradings when compared to patients with other G1 STS. Conclusions: Our results indicate that age and tumor type play the key role in the development of up gradings in low malignant STS .Patients aged 60 and above diagnosed with fibrosarcomas are at a 3 times higher risk of developing a grading change as opposed to patients younger than 60 with other low grade STS than fibrosarcoma. We discussed the significance of these risk factors and argued whether, in addition to wide tumor resection, a short term postoperative radiotherapy should be applied for these patients to improve therapeutical outcome.

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Shah, Rajal B. "Current Perspectives on the Gleason Grading of Prostate Cancer." Archives of Pathology & Laboratory Medicine 133, no. 11 (2009): 1810–16. http://dx.doi.org/10.5858/133.11.1810.

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Abstract Context.—Since its description in 1966 by Donald Gleason, the Gleason grading has remained a cornerstone in the diagnosis and management of prostate cancer. With widespread use of the prostate specific antigen screening, the diagnosis and management patterns of prostate cancers have dramatically changed. In addition, better understanding of the morphologic spectrum of prostate cancer and its subsequent outcome have prompted the refinement of the grading criteria and reporting practices applicable to contemporary practice management. Objective.—To present contemporary perspectives and approaches to the Gleason grading of prostate cancer. Data Sources.—Personal practice experience, review of medical literature, and excerpts from the 2005 International Society of Urological Pathology Consensus Statement on Gleason Grading of Prostate Cancer. Conclusions.—This review addresses the trend in contemporary practice toward a grading shift, with rare utilization of Gleason patterns 1 and 2, and discusses the refinement of histologic criteria for Gleason patterns 3 and 4; approaches to Gleason grading in the setting of unusual variant morphologies of prostate cancer; significance of higher tertiary pattern 5; and practice recommendations for reporting in the setting of extended multiple core biopsies and multifocal prostate cancers in radical prostatectomy. Finally, the impact of consensus recommendations in current practice, its limitations and pitfalls, are also addressed.

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Zeller, John L. "Grading of Prostate Cancer." JAMA 298, no. 13 (2007): 1596. http://dx.doi.org/10.1001/jama.298.13.1596.

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Sotiriou, C., Wirapati, S. Loi, et al. "Is genomic grading killing histological grading?" European Journal of Cancer Supplements 4, no. 2 (2006): 177. http://dx.doi.org/10.1016/s1359-6349(06)80452-0.

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Elston, E. W., and I. O. Ellis. "Method for grading breast cancer." Journal of Clinical Pathology 46, no. 2 (1993): 189–90. http://dx.doi.org/10.1136/jcp.46.2.189-b.

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Coard, Kathleen C., and Vincent L. Freeman. "Gleason Grading of Prostate Cancer." American Journal of Clinical Pathology 122, no. 3 (2004): 373–76. http://dx.doi.org/10.1309/mhcy35fj296cllc8.

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Ueno, Hideki, Hidetaka Mochizuki, Yojiro Hashiguchi, et al. "Histological Grading of Colorectal Cancer." Annals of Surgery 247, no. 5 (2008): 811–18. http://dx.doi.org/10.1097/sla.0b013e318167580f.

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Theissig, F., K. D. Kunze, G. Haroske, and W. Meyer. "Histological Grading of Breast Cancer." Pathology - Research and Practice 186, no. 6 (1990): 732–36. http://dx.doi.org/10.1016/s0344-0338(11)80263-3.

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Helpap, Burkhard. "Nucleolar grading of breast cancer." Virchows Archiv A Pathological Anatomy and Histopathology 415, no. 6 (1989): 501–8. http://dx.doi.org/10.1007/bf00718643.

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Heathfield, H. A., G. Winstanley, and N. Kirkham. "Computer-assisted breast cancer grading." Journal of Biomedical Engineering 10, no. 5 (1988): 379–86. http://dx.doi.org/10.1016/0141-5425(88)90139-2.

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Carriaga, Marisa T., and Donald Earl Henson. "The histologic grading of cancer." Cancer 75, S1 (1995): 406–21. http://dx.doi.org/10.1002/1097-0142(19950101)75:1+<406::aid-cncr2820751322>3.0.co;2-w.

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Kryvenko, Oleksandr N., and Jonathan I. Epstein. "Prostate Cancer Grading: A Decade After the 2005 Modified Gleason Grading System." Archives of Pathology & Laboratory Medicine 140, no. 10 (2016): 1140–52. http://dx.doi.org/10.5858/arpa.2015-0487-sa.

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Since 1966, when Donald Gleason, MD, first proposed grading prostate cancer based on its histologic architecture, there have been numerous changes in clinical and pathologic practices relating to prostate cancer. Patterns 1 and 2, comprising more than 30% of cases in the original publications by Gleason, are no longer reported on biopsy and are rarely diagnosed on radical prostatectomy. Many of these cases may even have been mimickers of prostate cancer that were described later with the use of contemporary immunohistochemistry. The original Gleason system predated many newly described variants of prostate cancer and our current concept of intraductal carcinoma. Gleason also did not describe how to report prostate cancer on biopsy with multiple cores of cancer or on radical prostatectomy with separate tumor nodules. To address these issues, the International Society of Urological Pathology first made revisions to the grading system in 2005, and subsequently in 2014. Additionally, a new grading system composed of Grade Groups 1 to 5 that was first developed in 2013 at the Johns Hopkins Hospital and subsequently validated in a large multi-institutional and multimodal study was presented at the 2014 International Society of Urological Pathology meeting and accepted both by participating pathologists as well as urologists, oncologists, and radiation therapists. In the present study, we describe updates to the grading of prostate cancer along with the new grading system.

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Minner, S., J. Schreiner, and W. Saeger. "Adrenal cancer: relevance of different grading systems and subtypes." Clinical and Translational Oncology 23, no. 7 (2021): 1350–57. http://dx.doi.org/10.1007/s12094-020-02524-2.

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Abstract Purpose The subclassification of adrenal cancers according to the WHO classification in ordinary, myxoid, oncocytic, and sarcomatoid as well as pediatric types is well established, but the criteria for each subtype are not sufficiently determined and the relative frequency of the different types of adrenal cancers has not been studied in large cohorts. Therefore, our large collection of surgically removed adrenal cancers should be reviewed o establish the criteria for the subtypes and to find out the frequency of the various types. Methods In our series of 521 adrenal cancers the scoring systems of Weiss et al., Hough et al., van Slooten et al. and the new Helsinki score system were used for the ordinary type of cancer (97% of our series) and the myxoid type (0.8%). For oncocytic carcinomas (2%), the scoring system of Bisceglia et al. was applied. Results Discrepancies between benign and malignant diagnoses from the first thee classical scoring systems are not rare (22% in our series) and could be resolved by the Helsinki score especially by Ki-67 index (more than 8% unequivocally malignant). Since all our cancer cases are positive in the Helsinki score, this system can replace the three elder systems. For identification of sarcomatoid cancer as rarest type in our series (0.2%), the scoring systems are not practical but additional immunostainings used for soft tissue tumors and in special cases molecular pathology are necessary to differentiate these cancers from adrenal sarcomas. According to the relative frequencies of the different subtypes of adrenal cancers the main type is the far most frequent (97%) followed by the oncocytic type (2%), the myxoid type (0.8%) and the very rare sarcomatoid type (0.2%). Conclusions The Helsinki score is the best for differentiating adrenal carcinomas of the main, the oncocytic, and the myxoid type in routine work. Additional scoring systems for these carcinomas are generally not any longer necessary. Signs of proliferation (mitoses and Ki-67 index) and necroses are the most important criteria for diagnosis of malignancy.

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Miles, Brian, Michael Ittmann, Thomas Wheeler, et al. "Moving Beyond Gleason Scoring." Archives of Pathology & Laboratory Medicine 143, no. 5 (2019): 565–70. http://dx.doi.org/10.5858/arpa.2018-0242-ra.

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Context.— The combination of grading and staging is the basis of current standard of care for prediction for most cancers. D. F. Gleason created the current prostate cancer (PCa) grading system. This system has been modified several times. Molecular data have been added. Currently, all grading systems are cancer-cell based. Objective.— To review the literature available on host response measures as reactive stroma grading and stromogenic carcinoma, and their predictive ability for PCa biochemical recurrence and PCa-specific death. Data Sources.— Our own experience has shown that reactive stroma grading and the subsequently binarized system (stromogenic carcinoma) can independently predict biochemical recurrence and/or PCa-specific death, particularly in patients with a Gleason score of 6 or 7. Stromogenic carcinoma has been validated by 4 other independent groups in at least 3 continents. Conclusions.— Broders grading and Dukes staging have been combined to form the most powerful prognostic tools in standard of care. The time has come for us to incorporate measures of host response (stromogenic carcinoma) into the arsenal of elements we use to predict cancer survival, without abandoning what we know works. These data also suggest that our current definition of PCa might need some revision.

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Crocetti, Emanuele, Alessandro Barchielli, Andrea Amorosi, et al. "The Availability of Histologic Grading among 5,923 Italian Cancer Patients and Its Relationship with Survival: A Population-Based Study." Tumori Journal 86, no. 2 (2000): 130–33. http://dx.doi.org/10.1177/030089160008600204.

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Aim The specific goal of the study was to evaluate the availability of the histologic grading of cancer and its effect on survival in an Italian population-based cancer series. Methods Data were drawn from the Tuscany Cancer Registry, active in central Italy since 1985. Among the cases incident during the period 1985 to 1989, bladder, prostate, colon, corpus uteri, rectum and stomach cancers, for which the proportion of graded cases exceeded 50%, were analyzed. Overall, 5,923 cancer cases were included. Ten-year relative survival rates by grade were computed. Results Overall, data on histologic grading was available only for 38% of cases. The sites most frequently graded were urinary bladder (80%), prostate (73%), colon (71%), corpus uteri (69%), rectum (65%) and stomach (56%). For all the cancer sites analyzed, the 10-year relative survival rates increased as the histologic grading improved. The grade distribution resulted related also to the disease extension, more limited the extension higher the proportion of well differentiated cases. Conclusions Due to the evidenced importance of histologic grading as a valuable prognostic factor, it should be requested by clinicians and reported by pathologists more frequently than has been done in the area.

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Yan, Rui, Fei Ren, Jintao Li, et al. "Nuclei-Guided Network for Breast Cancer Grading in HE-Stained Pathological Images." Sensors 22, no. 11 (2022): 4061. http://dx.doi.org/10.3390/s22114061.

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Breast cancer grading methods based on hematoxylin-eosin (HE) stained pathological images can be summarized into two categories. The first category is to directly extract the pathological image features for breast cancer grading. However, unlike the coarse-grained problem of breast cancer classification, breast cancer grading is a fine-grained classification problem, so general methods cannot achieve satisfactory results. The second category is to apply the three evaluation criteria of the Nottingham Grading System (NGS) separately, and then integrate the results of the three criteria to obtain the final grading result. However, NGS is only a semiquantitative evaluation method, and there may be far more image features related to breast cancer grading. In this paper, we proposed a Nuclei-Guided Network (NGNet) for breast invasive ductal carcinoma (IDC) grading in pathological images. The proposed nuclei-guided attention module plays the role of nucleus attention, so as to learn more nuclei-related feature representations for breast IDC grading. In addition, the proposed nuclei-guided fusion module in the fusion process of different branches can further enable the network to focus on learning nuclei-related features. Overall, under the guidance of nuclei-related features, the entire NGNet can learn more fine-grained features for breast IDC grading. The experimental results show that the performance of the proposed method is better than that of state-of-the-art method. In addition, we released a well-labeled dataset with 3644 pathological images for breast IDC grading. This dataset is currently the largest publicly available breast IDC grading dataset and can serve as a benchmark to facilitate a broader study of breast IDC grading.

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Finn, William G. "Alternative to histologic grading of cancer." Human Pathology 32, no. 11 (2001): 1277–78. http://dx.doi.org/10.1053/hupa.2001.28932.

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Castellanos, A. M., and W. S. Fields. "Grading of neurotoxicity in cancer therapy." Journal of Clinical Oncology 4, no. 8 (1986): 1277–78. http://dx.doi.org/10.1200/jco.1986.4.8.1277.

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Kim, Eric H., and Gerald L. Andriole. "A simplified prostate cancer grading system." Nature Reviews Urology 12, no. 11 (2015): 601–2. http://dx.doi.org/10.1038/nrurol.2015.212.

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Harvey, J. M., N. H. de Klerk, P. D. Robbins, and G. F. Sterrett. "Histological grading of breast cancer: a study of reproducibility of consensus grading." Breast 4, no. 4 (1995): 297–300. http://dx.doi.org/10.1016/s0960-9776(95)80007-7.

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Delahunt, Brett, David J. Grignon, Hemamali Samaratunga, et al. "Prostate Cancer Grading: A Decade After the 2005 Modified Gleason Grading System." Archives of Pathology & Laboratory Medicine 141, no. 2 (2017): 182–83. http://dx.doi.org/10.5858/arpa.2016-0300-le.

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Kryvenko, Oleksandr N., and Jonathan I. Epstein. "Changes in prostate cancer grading: Including a new patient-centric grading system." Prostate 76, no. 5 (2015): 427–33. http://dx.doi.org/10.1002/pros.23142.

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Rajasekaran Subramanian, Et al. "Yolov5 AI Deep Learning model driven Nuclear Pleomorphism Grading on Breast Cancer Pathology WSI for Nottingham Cancer Grading." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 10 (2023): 61–65. http://dx.doi.org/10.17762/ijritcc.v11i10.8465.

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Breast cancer is the second largest cancer caused in the world due to the uncontrollable growth in breast cells. Nottingham Grading is the internationally acceptable system to grade breast cancer. Nuclear pleomorphism is one of the breast cancer biomarkers for computing Nottingham grading. Pathologists grade nuclear pleomorphism on breast cancer glass tissue slides using a conventional microscope which is time consuming and has considerable inter-observer variability between pathologists. The paper proposed an Artificial Intelligence (AI) deep learning model to grade grade1, grade2, grade3 nuclear pleomorphism on breast cancer whole slide images (WSI). The proposed Yolov5 model is trained and tested on 1,30,000 WSI tiles having around two lakh annotations. The accuracy of the model is mAP 0.89. The proposed model saves the time and reduces the workload of the pathologist and also helps them to produce accurate results.

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Egevad, Lars, Daniela Swanberg, Brett Delahunt, et al. "Identification of areas of grading difficulties in prostate cancer and comparison with artificial intelligence assisted grading." Virchows Archiv 477, no. 6 (2020): 777–86. http://dx.doi.org/10.1007/s00428-020-02858-w.

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AbstractThe International Society of Urological Pathology (ISUP) hosts a reference image database supervised by experts with the purpose of establishing an international standard in prostate cancer grading. Here, we aimed to identify areas of grading difficulties and compare the results with those obtained from an artificial intelligence system trained in grading. In a series of 87 needle biopsies of cancers selected to include problematic cases, experts failed to reach a 2/3 consensus in 41.4% (36/87). Among consensus and non-consensus cases, the weighted kappa was 0.77 (range 0.68–0.84) and 0.50 (range 0.40–0.57), respectively. Among the non-consensus cases, four main causes of disagreement were identified: the distinction between Gleason score 3 + 3 with tangential cutting artifacts vs. Gleason score 3 + 4 with poorly formed or fused glands (13 cases), Gleason score 3 + 4 vs. 4 + 3 (7 cases), Gleason score 4 + 3 vs. 4 + 4 (8 cases) and the identification of a small component of Gleason pattern 5 (6 cases). The AI system obtained a weighted kappa value of 0.53 among the non-consensus cases, placing it as the observer with the sixth best reproducibility out of a total of 24. AI may serve as a decision support and decrease inter-observer variability by its ability to make consistent decisions. The grading of these cancer patterns that best predicts outcome and guides treatment warrants further clinical and genetic studies. Results of such investigations should be used to improve calibration of AI systems.

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Mohamad Sehmi, Muhammad Nurmahir, Mohammad Faizal Ahmad Fauzi, Wan Siti Halimatul Munirah Wan Ahmad, and Elaine Wan Ling Chan. "Pancreatic cancer grading in pathological images using deep learning convolutional neural networks." F1000Research 10 (October 18, 2021): 1057. http://dx.doi.org/10.12688/f1000research.73161.1.

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Background: Pancreatic cancer is one of the deadliest forms of cancer. The cancer grades define how aggressively the cancer will spread and give indication for doctors to make proper prognosis and treatment. The current method of pancreatic cancer grading, by means of manual examination of the cancerous tissue following a biopsy, is time consuming and often results in misdiagnosis and thus incorrect treatment. This paper presents an automated grading system for pancreatic cancer from pathology images developed by comparing deep learning models on two different pathological stains. Methods: A transfer-learning technique was adopted by testing the method on 14 different ImageNet pre-trained models. The models were fine-tuned to be trained with our dataset. Results: From the experiment, DenseNet models appeared to be the best at classifying the validation set with up to 95.61% accuracy in grading pancreatic cancer despite the small sample set. Conclusions: To the best of our knowledge, this is the first work in grading pancreatic cancer based on pathology images. Previous works have either focused only on detection (benign or malignant), or on radiology images (computerized tomography [CT], magnetic resonance imaging [MRI] etc.). The proposed system can be very useful to pathologists in facilitating an automated or semi-automated cancer grading system, which can address the problems found in manual grading.

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Mohamad Sehmi, Muhammad Nurmahir, Mohammad Faizal Ahmad Fauzi, Wan Siti Halimatul Munirah Wan Ahmad, and Elaine Wan Ling Chan. "Pancreatic cancer grading in pathological images using deep learning convolutional neural networks." F1000Research 10 (November 1, 2022): 1057. http://dx.doi.org/10.12688/f1000research.73161.2.

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Background: Pancreatic cancer is one of the deadliest forms of cancer. The cancer grades define how aggressively the cancer will spread and give indication for doctors to make proper prognosis and treatment. The current method of pancreatic cancer grading, by means of manual examination of the cancerous tissue following a biopsy, is time consuming and often results in misdiagnosis and thus incorrect treatment. This paper presents an automated grading system for pancreatic cancer from pathology images developed by comparing deep learning models on two different pathological stains. Methods: A transfer-learning technique was adopted by testing the method on 14 different ImageNet pre-trained models. The models were fine-tuned to be trained with our dataset. Results: From the experiment, DenseNet models appeared to be the best at classifying the validation set with up to 95.61% accuracy in grading pancreatic cancer despite the small sample set. Conclusions: To the best of our knowledge, this is the first work in grading pancreatic cancer based on pathology images. Previous works have either focused only on detection (benign or malignant), or on radiology images (computerized tomography [CT], magnetic resonance imaging [MRI] etc.). The proposed system can be very useful to pathologists in facilitating an automated or semi-automated cancer grading system, which can address the problems found in manual grading.

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Eberhart, Charles G., James L. Kepner, Patricia T. Goldthwaite, et al. "Histopathologic grading of medulloblastomas." Cancer 94, no. 2 (2002): 552–60. http://dx.doi.org/10.1002/cncr.10189.

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Ho, Donald Ming-Tak, Chih-Yi Hsu, and Hung Chiang. "Histopathologic grading of medulloblastomas." Cancer 95, no. 12 (2002): 2577–78. http://dx.doi.org/10.1002/cncr.11003.

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Sharma, Rachna, Varun Rastogi, Naveen Puri, Satyaranjan Mishra, Lalita Yadav, and Robin Sabharwal. "Dilemmas in Grading Epidermoid Carcinoma." International Journal of Head and Neck Surgery 5, no. 1 (2014): 9–14. http://dx.doi.org/10.5005/jp-journals-10001-1171.

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ABSTRACT Oral squamous cell carcinoma (OSCC) can be preceded by the appearance of lesions which have the potential either to develop into cancer or signal the development of cancer in the oral cavity. Oral squamous cell carcinoma is the 8th most common cancer worldwide and found particularly in low income communities and mainly a problem of older men, 90% being in the 45-year-age group. Histologic grading has been used as a prognostic factor and for clinical evaluation of OSCC for the past several decades. At the same time, the prognostic value of different grading classification remains controversial. So, in this article, we have reviewed the different grading system of oral squamous cell carcinoma and their prognostic value. How to cite this article Rastogi V, Puri N, Mishra S, Sharma R, Yadav L, Sabharwal R. Dilemmas in Grading Epidermoid Carcinoma. Int J Head Neck Surg 2014;5(1):9-14.

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Rabjerg, Maj, Oke Gerke, Birte Engvad, and Niels Marcussen. "Comparing World Health Organization/International Society of Urological Pathology Grading and Fuhrman Grading with the Prognostic Value of Nuclear Area in Patients with Renal Cell Carcinoma." Uro 1, no. 1 (2021): 2–13. http://dx.doi.org/10.3390/uro1010002.

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This study was undertaken to compare Fuhrman grading with World Health Organization/International Society of Urological Pathology (WHO/ISUP) grading and stereologically measured nuclear area in patients with Clear Cell Renal Cell Carcinoma (ccRCC) or Papillary Renal Cell Carcinoma (PRCC) and to evaluate the independent predictive value of Fuhrman, WHO/ISUP and stereologically measured nuclear area combined with necrosis in a series of patients with ccRCC in relation to cancer-specific survival. In all, 124 cases of ccRCC and PRCC were included. All slides were blindly scored by two trained pathologists according to the Fuhrman and WHO/ISUP grading systems. Nuclear measurements were performed on digitally scanned slides in Visiopharm® and correlated to survival. Analysis of ccRCC and PRCC cases showed that application of WHO/ISUP grading resulted in a significant downgrading of cases from G2 to G1, when comparing with Fuhrman grading. Neither of these patients experienced progression. Cancer specific survival estimates in 101 ccRCC patients showed that WHO/ISUP grading was slightly superior in predicting cancer-specific survival. Novel models included WHO/ISUP grading and mean nuclear area (MNA) each of which combined with necrosis. Both demonstrated an increased ability to predict cancer-specific survival. The study demonstrates that WHO/ISUP grading provides superior prognostic information compared to Fuhrman grading and stereologically measured nuclear area. Necrosis in combination with either WHO/ISUP grading or MNA adds additional prognostic information.

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De Souza, Jonas A., Kristen Wroblewski, Ellie Proussaloglou, Laura Nicholson, Andrew Hantel, and Yichen Wang. "Validation of a financial toxicity (FT) grading system." Journal of Clinical Oncology 35, no. 15_suppl (2017): 6615. http://dx.doi.org/10.1200/jco.2017.35.15_suppl.6615.

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6615 Background: FT is an important adverse event (AE) that should be objectively measured in clinical practice. We previously developed an evidence-based FT grading system based on differences in HRQoL, analogous to the NCI-Common Terminology Criteria for Adverse Events (grade 1, mild AE; grade 2, moderate AE; grade 3, severe AE ,de Souza et al - ASCO 2015). We aimed to validate this grading system using a new sample of cancer patients (pts) and report its association with bankruptcy. Methods: FT was assessed by the COST (COmprehensive Score for financial Toxicity) in 2 sets of cancer pts. In the previously reported Development Set (DS), gradations of FT were determined by ROC analyses based on conventions for clinically meaningful small (0.2), medium (0.5) and large (0.8) effect sizes (e.s.) for independent FACT-G differences attributable to FT in pts with Stage IV cancers on chemotherapy. In the Validation Set (VS), differences in HRQoL and the odds ratio for a pt to have declared bankruptcy after the cancer diagnosis were assessed in a larger cohort of cancer pts on chemotherapy. Results: The grading system was developed in 888 cancer pts with cancer (233 pts in the DS and 655 in the VS). In the DS, ROC analyses produced 4 FT grades (G): G0, no FT, COST ≥26 (99 pts, 42%); G1, mild FT: ≥ 14-26 (71 pts, 31%); G2, moderate FT: > 0-14 (58 pts, 25%); and G3, severe FT: COST = 0 (5 pts, 2%). Applying the FT grading to the 655 pts in VS, we had: G0, 146 pts (22%); G1, 281 (43%); G2, 215 (33%); and G3, 13 (2%). The decreases in FACT-G HRQoL measured in e.s. per FT grading in comparison with G0 were small for G1: -0.4 (95%CI: -0.6 – -0.25); large for G2: -0.9 (95%CI: -1.1 – -0.7); and even larger for G3: -1.5 (95%CI: -2.0 – -0.9), all with p < 0.001. In the VS, 23 pts (4%) had declared bankruptcy after their cancer diagnosis. Compared to FT G0, the odds of having declared bankruptcy were 8.6 (95%CI: 1.1 – 67, p = 0.04) times higher for pts with FT G2, and 29 times higher (95% CI: 2.4 – 355, p = 0.008) for those with G3 FT. Conclusions: We developed a FT grading system anchored on independent differences in HRQoL. We applied the system in a different set of cancer pts and it retained its validity. We also found an larger incidence of bankruptcy after the cancer diagnosis in higher grades of FT, adding to the grading’s meaningful use.

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Odukoya, Lateef, Luqman Adebayo, and Charles Anunobi. "Contemporary International Society for Urological Pathology Grade Group System 2014: A 2-Year Retrospective Review of Prostate Cancers Diagnosed in Lagos University Teaching Hospital." American Journal of Clinical Pathology 152, Supplement_1 (2019): S65—S66. http://dx.doi.org/10.1093/ajcp/aqz113.070.

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Abstract Introduction Prostate cancer is the second most frequent cancer worldwide. It is the commonest cancer among men in Nigeria. Gleason grading and scoring system constitute the most useful prognostic indicator in prostate cancer diagnosis and management. Over the years, it has gone through important modifications. The most recent of these changes was in 2014 by the International Society for Urological Pathology (ISUP). The WHO adopted the new grading system in 2016. It was not adopted as part of routine reporting of prostate cancer biopsies in Lagos University Teaching Hospital (LUTH) until 2017. The aim of this study is to categorize prostate cancers diagnosed in LUTH based on the grade group system and determine the pattern of prognostic distribution of prostate cancer cases since its adoption. Methods This is a descriptive study; data were retrieved from the histopathologic records of the Department of Anatomic Pathology. Prostate cancers cases diagnosed between 2017 and 2018 were stratified using the WHO-adopted 2014 ISUP grading system. Results During the 2 years, 93 cases of prostate cancers were diagnosed by core needle biopsies. Overall, mean age of cases was 69.85 years (SD 8.49, median = 70 years). Nearly 39% of the 93 cases were ISUP grade group 5 and about 24% were ISUP grade group 4. Together ISUP grade groups 3, 4, and 5 constituted 76.35% of all cases of prostate cancers. There was no statistically significant association between ISUP grade group and age (P = .266). Perineural invasion was present in 35.82% of cases. Sixty-seven percent of these were ISUP grade group 5. Conclusion The data from this study suggest that high-grade cancers, particularly those of the ISUP grade group 5, are the most frequently diagnosed prostate cancers in our institution. Further studies are required to document biochemical recurrence-free progression and survival among our patients.

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Nagaraju, Kusuma Kodihalli, Chandana Nagendra, and Shilpa Madhav Shetty. "Correlation of Robinson’s Cytological Grading of Breast Carcinoma with Bloom Richardson’s Histological Grading – A Teaching Institutional Experience in Mandya, Karnataka." Journal of Evidence Based Medicine and Healthcare 8, no. 21 (2021): 1620–23. http://dx.doi.org/10.18410/jebmh/2021/306.

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BACKGROUND Breast cancer is increasing in developing countries and the management options are wide; therefore, providing the surgeon with accurate prognostic information on which mode of therapy will be chosen becomes important. Fine needle aspiration cytology (FNAC) is a routinely used initial investigation of choice for rapid diagnosis of breast cancer. Apart from diagnosis of cancer, it also has the ability to predict the grade on smears which will add its diagnostic value without any additional morbidity or expense for the patients. Among various cytological grading systems, Robinson grading is most commonly used for breast carcinoma in fine needle aspirates. The purpose of this study is to evaluate the correlation between Robinson’s cytological grading and Bloom Richardson’s histological grading. METHODS This is a 3 - year retrospective analytical study. 40 cases of infiltrating duct carcinoma (IDC) of breast diagnosed on cytology were included in the study. Cytological grading was done using Robinson’s grading and corresponding histopathology slides were taken, and histological grading using Bloom Richardson’s system was done. Finally, correlation between cytological and histological grading was done using statistical package for social sciences (SPSS) software. RESULTS Age of the patients varied between 32 and 70 yrs. Cytologically, 32.5 % cases were grade I, 40 % were grade II and 27.5 % cases were grade III respectively. Histologically 22.5 %, 47.5 % and 30 % cases were grade I, grade II, and grade III, respectively. Concordance rate between grade I tumours in cytology and histology was 53.84 %, for grade II tumours it was 75 %, and for grade III tumours it was 63.63 %. The absolute concordance rate was 65 %. CONCLUSIONS Robinson’s cytological grading (RCG) of breast carcinoma correlates well with Bloom - Richardson’s histological grading system and could be a helpful parameter in selecting a neoadjuvant treatment for the breast cancer patients on fine needle aspiration cytology alone. KEYWORDS Breast Carcinoma, Robinson’s Cytological Grading, Bloom Richardson’s Histological Grading

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Wang, Yuezhu, Margaret R. Smith, Yin Liu, et al. "Abstract 3782: IASLC grading system predict distant metastases for resected lung adenocarcinoma." Cancer Research 84, no. 6_Supplement (2024): 3782. http://dx.doi.org/10.1158/1538-7445.am2024-3782.

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Abstract The International Association for the Study of Lung Cancer (IASLC) proposed a new histological grading system for invasive lung adenocarcinoma (LUAD). However, whether this new grading system is able to predict distant metastases in LUAD patients has not been evaluated. This study investigated the feasibility of using this grading system to predict the occurrence of brain and bone metastases in patients with resectable LUAD which identifies patients who have a high probability of developing distant metastases after surgery. We collected clinical information and pathological reports of 179 early stage LUAD patients who underwent resection during 2008 to 2015 from Wake Forest Comprehensive Cancer Center. All patients were followed up for 5 years and both bone and brain metastasis-free survival were calculated. Tumor grading of all samples was evaluated by both IASLC grading and predominant pattern-based grading systems. The ability of predicting distant metastases using IASLC grading and tumor stage were examined by receiver operating characteristic curves (ROC). 28 out of 179 patients developed distant metastases in five years with a median overall survival of 60 months for metastasis-free patients and 38.9 for patients with distant metastasis. Compared to predominant pattern-based grading system, IASLC grading system showed a stronger correlation with distant metastasis incidence. Complex gland pattern is enriched in patients who developed bone and brain metastases compared to metastasis-free patients. IASLC grading system also showed a superior prediction power of distant metastasis compared to tumor stage with area under curve (AUC) of 0.69 for brain metastasis and 0.71 for bone metastasis. IASLC grading system is capable of predicting the incidence of distant metastasis among early-stage invasive LUAD patients. Citation Format: Yuezhu Wang, Margaret R. Smith, Yin Liu, Mary E. Green, Omer A. Hassan, Alexandra M. Balmaceda, Tammy Sexton, Wencheng Li, Fei Xing. IASLC grading system predict distant metastases for resected lung adenocarcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3782.

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Fandel, Thomas M., Maria Pfnuer, Claudia Corinth, et al. "745: Confirmation Bias in Prostate Cancer Grading." Journal of Urology 177, no. 4S (2007): 250. http://dx.doi.org/10.1016/s0022-5347(18)30985-6.

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Chouinard, E. E., V. Chen, T. J. D'Souza, and R. H. Riddell. "Reproducibility of pathological grading in breast cancer." Breast 3, no. 2 (1994): 124–29. http://dx.doi.org/10.1016/0960-9776(94)90013-2.

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Gleason, Donald F. "Histologic grading of prostate cancer: A perspective." Human Pathology 23, no. 3 (1992): 273–79. http://dx.doi.org/10.1016/0046-8177(92)90108-f.

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Olsson, Niclas, Petter Carlsson, Peter James, et al. "Grading Breast Cancer Tissues Using Molecular Portraits." Molecular & Cellular Proteomics 12, no. 12 (2013): 3612–23. http://dx.doi.org/10.1074/mcp.m113.030379.

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Epstein, Jonathan I. "A new contemporary prostate cancer grading system." Annales de Pathologie 35, no. 6 (2015): 474–76. http://dx.doi.org/10.1016/j.annpat.2015.09.002.

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Yao, Cindy Q., Francis Nguyen, Syed Haider, Maud H. W. Starmans, Philippe Lambin, and Paul C. Boutros. "The transcriptomic profile of ovarian cancer grading." Cancer Medicine 4, no. 1 (2014): 56–64. http://dx.doi.org/10.1002/cam4.343.

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Andrus, Paul G. L., and Robert D. Strickland. "Cancer grading by Fourier transform infrared spectroscopy." Biospectroscopy 4, no. 1 (1998): 37–46. http://dx.doi.org/10.1002/(sici)1520-6343(1998)4:1<37::aid-bspy4>3.0.co;2-p.

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Jones, Howard W. "The Importance of Grading in Endometrial Cancer." Gynecologic Oncology 74, no. 1 (1999): 1–2. http://dx.doi.org/10.1006/gyno.1999.5508.

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Tiwari, Saumya, Kianoush Falahkheirkhah, Georgina Cheng, and Rohit Bhargava. "Colon Cancer Grading Using Infrared Spectroscopic Imaging-Based Deep Learning." Applied Spectroscopy 76, no. 4 (2022): 475–84. http://dx.doi.org/10.1177/00037028221076170.

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Tumor grade assessment is critical to the treatment of cancers. A pathologist typically evaluates grade by examining morphologic organization in tissue using hematoxylin and eosin (H&E) stained tissue sections. Fourier transform infrared spectroscopic (FT-IR) imaging provides an alternate view of tissue in which spatially specific molecular information from unstained tissue can be utilized. Here, we examine the potential of IR imaging for grading colon cancer in biopsy samples. We used a 148-patient cohort to develop a deep learning classifier to estimate the tumor grade using IR absorption. We demonstrate that FT-IR imaging can be a viable tool to determine colorectal cancer grades, which we validated on an independent cohort of surgical resections. This work demonstrates that harnessing molecular information from FT-IR imaging and coupling it with morphometry is a potential path to develop clinically relevant grade prediction models.

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Zdrojewski, Jakub, Monika Nowak, Kacper Nijakowski, et al. "Potential Immunohistochemical Biomarkers for Grading Oral Dysplasia: A Literature Review." Biomedicines 12, no. 3 (2024): 577. http://dx.doi.org/10.3390/biomedicines12030577.

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Oral cancer is a prevalent global health issue, with significant morbidity and mortality rates. Despite available preventive measures, it remains one of the most common cancers, emphasising the need for improved diagnostic and prognostic tools. This review focuses on oral potentially malignant disorders (OPMDs), precursors to oral cancer, specifically emphasising oral epithelial dysplasia (OED). The World Health Organisation (WHO) provides a three-tier grading system for OED, and recent updates have expanded the criteria to enhance diagnostic precision. In the prognostic evaluation of OED, histological grading is presently regarded as the gold standard; however, its subjectivity and unreliability in anticipating malignant transformation or recurrence pose notable limitations. The primary objective is to investigate whether specific immunohistochemical biomarkers can enhance OED grading assessment according to the WHO classification. Biomarkers exhibit significant potential for comprehensive cancer risk evaluation, early detection, diagnosis, prognosis, and treatment optimisation. Technological advancements, including sequencing and nanotechnology, have expanded detection capabilities. Some analysed biomarkers are most frequently chosen, such as p53, Ki-67, cadherins/catenins, and other proteins used to differentiate OED grades. However, further research is needed to confirm these findings and discover new potential biomarkers for precise dysplasia grading and minimally invasive assessment of the risk of malignant transformation.

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Celmen, Melis, Aya Sato-DiLorenzo, Rosemary Chude-Sokei, et al. "Grading our quality: An academic and community cancer center dashboard." Journal of Clinical Oncology 40, no. 28_suppl (2022): 303. http://dx.doi.org/10.1200/jco.2022.40.28_suppl.303.

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303 Background: Quality scorecards provide a high-level view of key performance metrics and guide data-driven decision making. Dashboards specific to cancer care have not been widely published. Our goal was to implement a quality dashboard to guide and monitor local improvement efforts at an academic and community cancer center. Methods: With the leadership of a Project Manager and Nursing and Physician Quality Directors of the Cancer Center, and input of key Cancer Center stakeholders, quality metrics across national organizations were evaluated. Metrics were chosen based on their ease of collection and their mapping to institutional priorities of clinical quality, patient safety, access, and financial stability. Additional internal measures and benchmarks were created to capture local improvement efforts. Numerous internal and third-party databases were accessed to extract, analyze and display our data. Additionally, a data dictionary was developed for the measure set. Results: Six months of data from fiscal year 2022 was collected, analyzed, and displayed on 10 core and 3 disease-specific measures for breast (B) and lung (L) cancers. (Breast and lung). As of 5/2022, the measures presented on the dashboard include new patient access, non-template chemotherapy orders, medication harm events, likelihood of recommending practice, preventable admissions and emergency department visits, inpatient mortality, and length of stay, readmission, survivorship care plan (B), return to operating room (L), and adequate lymph node sampling (L). These measures pertain to several of the Institute of Medicine’s domains of healthcare quality: effective, efficient, patient-centered, safe, and timely. Conclusions: Compiling data from multiple sources into a single dashboard may guide Cancer Center leadership in strategic planning and monitoring improvement for ongoing initiatives. The data will be updated quarterly. Future iterations will include more disease specific measures and attempts to build automatic data extraction.

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Padang, Okto Sampe, Septiman Septiman, Prihantono Prihantono, et al. "Relationship between body mass index and cholesterol levels with histopathological grading of breast cancer." Breast Disease 40 (June 25, 2021): S77—S84. http://dx.doi.org/10.3233/bd-219011.

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BACKGROUND: Breast cancer, a global health problem with a high mortality rate, has several risk factors, including obesity and increased lipid profile. Postmenopausal obesity is associated with estrogen production from adipose tissue, while abnormal cell growth is triggered by insulin-like growth factor 1 (IGF-1) and insulin. Obesity could be assessed by measuring body mass index (BMI). An increase in lipid profile signifies an increased risk for breast cancer. Histopathological findings in the form of grading and differentiation can indicate how serious the condition is. Breast cancer with good differentiation is always associated with a positive prognosis. OBJECTIVE: This observational analytic study aims to determine the relationship between BMI and cholesterol levels based on the menopausal status and the histopathological grading findings of breast cancer patients. METHODS: The observational cross-sectional study analyzed histopathological grading, total cholesterol level, and body mass index. Data were analyzed with Spearman rank correlation statistical test, and the results are significant when the p-value is <0.05. RESULTS: Analyzing the relationship between cholesterol levels and histopathological gradings indicated a moderate correlation. The results of another correlation test based on menopausal status showed a weak correlation value, while menopause was said to be significant, indicating a moderate correlation. However, results from the analysis of BMI data in the menopausal subject group were associated with histopathological assessment. CONCLUSIONS: There is a relationship between cholesterol levels and histopathological degrees in the two menopausal status groups. However, no relationship was found between BMI and the histopathological grades of breast cancer.

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Journal articles on the topic 'Cancer grading'

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