Suppr超能文献

超越淋巴结分期:一家三级医疗中心的结直肠癌预后临床研究。

Beyond Nodal Stage: A Clinical Study of Colorectal Cancer Outcomes at a Single Tertiary Care Center.

作者信息

Knb Seshaan, Ethirajulu Ruthrendhra, Ganesan Srinath, S Gouthaman, Guru Ganesh

机构信息

General Surgery, Sree Balaji Medical College and Hospital, Chennai, IND.

Surgical Oncology, Good Samaritan Cancer Hospital, Eluru, IND.

出版信息

Cureus. 2025 May 18;17(5):e84365. doi: 10.7759/cureus.84365. eCollection 2025 May.

Abstract

Introduction Colorectal cancer (CRC) continues to be one of the most frequently diagnosed cancers worldwide and a major contributor to cancer-related mortality. The ratio of the number of involved to the total number of resected lymph nodes is termed as lymph node ratio (LNR), which is an important prognostic factor in colorectal malignancies. Aim This study aims to evaluate the prognostic value of lymph node ratio (LNR) in colorectal cancer (CRC), with particular reference to its association with survival outcomes. Materials and methods A retrospective analysis of 46 patients who underwent surgery for CRC in a single tertiary care center from October 2015 to July 2019 was conducted. Data on demographic variables, tumor histology, treatment modalities, and survival outcomes were collected using a retrospective chart review. The chi-square test was used to analyze the variables. All data were recorded using a standard data form and analyzed using SPSS version 21.0 (IBM Corp., Armonk, NY). Statistical significance was defined as p<0.05. We acknowledge that the study is based on a relatively small sample from a single institution, which may limit its statistical power and introduce potential selection bias. However, the findings offer meaningful preliminary data regarding LNR as a prognostic marker in CRC and highlight the need for validation through larger, multicenter studies. Results The mean age of the study population is 56 years. The rectum was the primary cancer site involved in 25 patients (54.3%). The most common pathology was adenocarcinoma in 32 (69%) patients. Lymphovascular and perineural invasion (PNI) was present in 12 (26%) and three (6.5%) patients, respectively. Eighteen patients belonged to the T2 (39%) stage, and 20 patients (60%) had a nodal status of N0. Most patients experienced Grade II postoperative complications (n=37, 80.4%), while Grade III and IV complications were observed in seven (15.2%) and two (4.3%) patients, respectively. Fifteen patients (32%) were given treatment prior to surgery in the form of neoadjuvant chemoradiation. The mean survival period in our study is 50 months. The presence of perineural invasion (p<0.019), node positivity (p<0.005), CD score of more than or equal to 3 (p<0.001), and higher lymph node ratio (p<0.001) were determined as independent prognostic factors for survival (p<0.05). Conclusion Lymph node ratio is a powerful factor for estimating the survival of CRC patients. Good postoperative care and recovery with a low CD score and meticulous surgery with higher lymph node yield would alter the survival status in CRC patients.

摘要

引言

结直肠癌(CRC)仍然是全球最常被诊断出的癌症之一,也是癌症相关死亡的主要原因。受累淋巴结数量与切除淋巴结总数的比值被称为淋巴结比率(LNR),它是结直肠恶性肿瘤的一个重要预后因素。

目的

本研究旨在评估淋巴结比率(LNR)在结直肠癌(CRC)中的预后价值,特别提及它与生存结果的关联。

材料与方法

对2015年10月至2019年7月在一家三级医疗中心接受CRC手术的46例患者进行回顾性分析。通过回顾性病历审查收集人口统计学变量、肿瘤组织学、治疗方式和生存结果的数据。使用卡方检验分析变量。所有数据使用标准数据表格记录,并使用SPSS 21.0版(IBM公司,纽约州阿蒙克)进行分析。统计学显著性定义为p<0.05。我们承认该研究基于来自单一机构的相对较小样本,这可能会限制其统计效力并引入潜在的选择偏倚。然而,这些发现提供了关于LNR作为CRC预后标志物的有意义的初步数据,并强调需要通过更大规模的多中心研究进行验证。

结果

研究人群的平均年龄为56岁。25例患者(54.3%)的原发癌部位在直肠。最常见的病理类型是腺癌,共32例(69%)患者。分别有12例(26%)和3例(6.5%)患者存在淋巴管和神经周围浸润(PNI)。18例患者属于T2期(39%),20例患者(60%)的淋巴结状态为N0。大多数患者术后出现Ⅱ级并发症(n = 37,80.4%),而Ⅲ级和Ⅳ级并发症分别在7例(15.2%)和2例(4.3%)患者中观察到。15例患者(32%)在手术前接受了新辅助放化疗形式的治疗。本研究中的平均生存期为50个月。神经周围浸润(p<0.019)、淋巴结阳性(p<0.005)、CD评分大于或等于3(p<0.001)以及较高的淋巴结比率(p<0.001)被确定为生存的独立预后因素(p<0.05)。

结论

淋巴结比率是评估CRC患者生存的一个重要因素。良好的术后护理和低CD评分的恢复以及淋巴结获取量较高的精细手术将改变CRC患者的生存状况。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/22a8/12174630/0e65961d2af6/cureus-0017-00000084365-i01.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验