Article ID Journal Published Year Pages File Type
4130894 Current Diagnostic Pathology 2006 11 Pages PDF
Abstract

SummaryThe accurate dissection of resection specimens forms a very important part of colorectal cancer patient management in that important prognostic data, gleaned from the resection specimen, strongly influence postoperative management, including being the most important determinant of the decision to institute adjuvant therapy, influencing decisions on patient follow-up and assessing likely prognosis and survival. Furthermore, pathological assessment is being increasingly used as a tool to make judgements on the quality of colorectal cancer surgery. Sadly, the task of dissecting the gross specimen has been seen as an unwanted and less than skilful chore and has, in the past, been the task of the most junior member of staff, who is often ill prepared and untrained for such an important role. The past few years have seen a dramatic change in this practice, in the UK and many Western European countries, such that it is now accepted that no amount of sophisticated microscopic analysis can redeem a case that has not been dissected and sampled for histology appropriately. The introduction of Royal College of Pathologists (RCPath) minimum datasets and protocols, for the accurate pathological assessment of specimens, has done much to improve the situation. However, although pathologists can now diligently record all pathological data of importance as part of such datasets, question marks still remain about the overall quality of such data. For instance, there are now compelling data to indicate the importance of adequate lymph node harvests. Yet recent audits have still demonstrated that lymph node harvests remain low in some centres, and this has an important influence on management decisions for individual patients. In this treatise, we discuss optimal macroscopic assessment practice for colorectal cancer resections and also consider the changes in the newly updated Royal College of Pathologists colorectal cancer minimum dataset and proforma.

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