Department of Human Pathology, University of Messina, Messina, Italy.
Department of Laboratory Integrated Activities, Anatomic Pathology and Legal Medicine, University of Modena and Reggio Emilia, Modena, Italy.
Hum Pathol. 2014 Feb;45(2):268-75. doi: 10.1016/j.humpath.2013.07.046. Epub 2013 Nov 27.
Histologic grading is commonly assessed in colorectal cancer preoperative biopsies. Nevertheless, its clinical impact is limited by low interobserver reproducibility and poor concordance with grading found in the final resection specimen. In the present study, we aimed to investigate the reproducibility, accuracy, and predictive value on lymph node status or pTNM stage of a novel grading system based on the number of poorly differentiated clusters in colorectal cancer preoperative endoscopic biopsies. Grading based on counting poorly differentiated clusters was assessed in 163 colorectal cancer endoscopic biopsies and corresponding surgical specimens. With this system, 152 biopsies could be graded with good interobserver agreement (κ = 0.735). In comparison with the surgical specimens, 75% of colorectal cancers were correctly graded in the biopsy, and 81% of poorly differentiated colorectal cancers were identified at initial biopsy. High poorly differentiated clusters grade in the biopsy was significantly associated with nodal metastasis, high pTNM stage (P < .0001), or histologic features suggestive of more aggressive behavior (tumor budding, perineural invasion, vascular invasion, and infiltrating tumor border) in the surgical specimen. Furthermore, this system identified colorectal cancer with nodal involvement or high pTNM stage with a 78% positive predictive value and 71% and 69% negative predictive values, respectively. Our findings suggest that a grading system based on the quantification of poorly differentiated clusters is feasible in most colorectal cancer endoscopic biopsies. In view of its good reproducibility, accuracy, and predictive value on the anatomical extent of the disease, it may be taken into account for decision-making in colorectal cancer treatment.
组织学分级通常在结直肠癌术前活检中进行评估。然而，其临床意义受到观察者间重复性低和与最终切除标本分级一致性差的限制。本研究旨在探讨一种基于结直肠癌术前内镜活检中低分化簇数量的新型分级系统的重复性、准确性和对淋巴结状态或 pTNM 分期的预测价值。在 163 例结直肠癌内镜活检和相应的手术标本中评估了基于计数低分化簇的分级。使用该系统，152 例活检具有良好的观察者间一致性（κ=0.735）。与手术标本相比，75%的结直肠癌在活检中得到正确分级，81%的低分化结直肠癌在初始活检中得到识别。活检中高分化簇数与淋巴结转移、高 pTNM 分期（P<0.0001）或手术标本中提示侵袭性行为的组织学特征（肿瘤芽生、神经周围浸润、血管浸润和浸润性肿瘤边界）显著相关。此外，该系统对有淋巴结受累或高 pTNM 分期的结直肠癌具有 78%的阳性预测值和 71%和 69%的阴性预测值。我们的研究结果表明，基于低分化簇数量的分级系统在大多数结直肠癌内镜活检中是可行的。鉴于其良好的可重复性、准确性和对疾病解剖范围的预测价值，它可能被考虑用于结直肠癌治疗的决策。
