Division of Colon and Rectal Surgery, Mayo Clinic, Rochester, MN 55905, USA.
Ann Surg. 2010 Apr;251(4):652-8. doi: 10.1097/SLA.0b013e3181d355f7.
The aim of this study was to perform an external validation of 2 institutionally derived predictive models of laparoscopic conversion in colorectal surgery using the Mayo Clinic, Rochester (MCR) laparoscopic colon and rectal surgery experience.
Two different predictive scoring systems of conversion in laparoscopic colorectal surgery were developed and published based upon single institution experiences. Neither model was validated on an independent data set. Thus, the utility of these models outside of their respective institutions is unknown.
A prospectively collected data set of 998 laparoscopic colorectal procedures from MCR was analyzed. All patient-, procedure-, and surgeon-related factors used in both models were present in our data set. Logistic regression was used to evaluate their ability to predict conversion in our cohort. Model effectiveness was assessed by area under the curve from the logistic regression model, 95% confidence intervals for the observed number of conversions, and a goodness-of-fit test to compare the observed number of conversions with the predicted conversion rates for each score.
The cohort mean age of 552 women was 53, with a median body mass index of 25.2 kg/m. There were 382 right-sided, 251 left-sided, 46 rectal resections, and 151 proctocolectomies. Major diagnoses were inflammatory bowel disease 34%, cancer 18%, polyps 17%, and diverticular disease 13%. The overall MCR conversion rate was 15%. Several variables from the models were statistically significant predictors of conversion in our data set. However, both models performed similarly with an area under the curve of 0.62, suggesting that these models are of limited predictive value in our independent cohort with a performance closer to chance. The numbers of actual conversions were significantly different from the predicted number for both scoring systems.
Patient and clinical factors associated with laparoscopic conversion in colorectal surgery may be institution dependent. This finding cautions surgeons on the applicability of institution-based surgical predictive models. Independent data set validation is recommended before surgical predictive models are applied to general clinical practice.
本研究旨在使用梅奥诊所罗切斯特(MCR)腹腔镜结肠和直肠手术经验,对 2 种机构衍生的腹腔镜结直肠手术中转预测模型进行外部验证。
两种不同的腹腔镜结直肠手术中转预测评分系统基于单机构经验开发并发表。这两个模型都没有在独立数据集上进行验证。因此,这些模型在其各自机构之外的适用性尚不清楚。
分析了 MCR 前瞻性收集的 998 例腹腔镜结直肠手术的数据集。两个模型中使用的所有患者、手术和外科医生相关因素均存在于我们的数据集中。使用逻辑回归评估它们在我们的队列中预测转换的能力。通过逻辑回归模型的曲线下面积、观察到的转换数量的 95%置信区间以及拟合优度检验来评估模型的有效性,拟合优度检验用于比较每个评分的观察到的转换数量与预测的转换率。
女性队列的平均年龄为 552 岁,平均 53 岁,中位体重指数为 25.2kg/m2。右侧 382 例,左侧 251 例,直肠切除术 46 例,直肠结肠切除术 151 例。主要诊断为炎症性肠病 34%、癌症 18%、息肉 17%和憩室病 13%。MCR 的总体转化率为 15%。模型中的几个变量是我们数据集中手术转换的统计学显著预测因子。然而,两个模型的表现相似,曲线下面积为 0.62,表明这些模型在我们的独立队列中的预测价值有限,性能更接近机会。实际转换数量与两个评分系统的预测数量明显不同。
与结直肠手术中转相关的患者和临床因素可能依赖于机构。这一发现告诫外科医生注意机构基础手术预测模型的适用性。建议在将手术预测模型应用于一般临床实践之前,进行独立数据集验证。