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High-grade prostatic intraepithelial neoplasia (HGPIN) is an abnormality of prostatic glands and believed to precede the development of prostate adenocarcinoma (the most common form of prostate cancer). [1] [2] It may be referred to simply as prostatic intraepithelial neoplasia (PIN).
This recognizes that prostatic carcinomas have multiple patterns and that prognosis is more accurately determined by adding the scores of the two most prevalent patterns. Using this system, the grades of the most prevalent and second most prevalent patterns (if at least 5% of the total), are added together to yield the overall Gleason score.
This article incorporates text from a free content work. Licensed under Creative Commons Attribution 4.0 International (CC BY 4.0) license. (license statement/permission). Text taken from adenocarcinoma Prostate adenocarcinoma , Patholines.
However, high magnification (right image) shows the key feature of prominent nucleoli (visible at 200x magnification to make the diagnosis of "high-grade"), as well as other typical features of HGPIN. Reference for features: - Margaret Sanders, M.B.B.Ch., Murali Varma, M.B.B.S.. High grade prostatic intraepithelial neoplasia (HGPIN).
The Nottingham prognostic index (NPI) is used to determine prognosis following surgery for breast cancer. [1] [2] Its value is calculated using three pathological criteria: the size of the tumour; the number of involved lymph nodes; and the grade of the tumour. [1] It is calculated to select patients for adjuvant treatment.
On a subsequent biopsy, given the diagnosis of ASAP, the chance of finding prostate adenocarcinoma is approximately 40%; this is higher than if there is high-grade prostatic intraepithelial neoplasia (HGPIN). [2]
Five-year survival rates can be used to compare the effectiveness of treatments. Use of five-year survival statistics is more useful in aggressive diseases that have a shorter life expectancy following diagnosis, such as lung cancer , and less useful in cases with a long life expectancy, such as prostate cancer .
An example of a Kaplan–Meier plot for two conditions associated with patient survival. The Kaplan–Meier estimator, [1] [2] also known as the product limit estimator, is a non-parametric statistic used to estimate the survival function from lifetime data.