Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Center, , Amsterdam, The Netherlands.
Gut. 2014 Mar;63(3):466-71. doi: 10.1136/gutjnl-2013-305013. Epub 2013 Aug 20.
Faecal immunochemical testing (FIT) is increasingly used in colorectal cancer (CRC) screening but has a less than perfect sensitivity. Combining risk stratification, based on established risk factors for advanced neoplasia, with the FIT result for allocating screenees to colonoscopy could increase the sensitivity and diagnostic yield of FIT-based screening. We explored the use of a risk prediction model in CRC screening.
We collected data in the colonoscopy arm of the Colonoscopy or Colonography for Screening study, a multicentre screening trial. For this study 6600 randomly selected, asymptomatic men and women between 50 years and 75 years of age were invited to undergo colonoscopy. Screening participants were asked for one sample FIT (OC-sensor) and to complete a risk questionnaire prior to colonoscopy. Based on the questionnaire data and the FIT results, we developed a multivariable risk model with the following factors: total calcium intake, family history, age and FIT result. We evaluated goodness-of-fit, calibration and discrimination, and compared it with a model based on primary screening with FIT only.
Of the 1426 screening participants, 1112 (78%) completed the questionnaire and FIT. Of these, 101 (9.1%) had advanced neoplasia. The risk based model significantly increased the goodness-of-fit compared with a model based on FIT only (p<0.001). Discrimination improved significantly with the risk-based model (area under the receiver operating characteristic (ROC) curve: from 0.69 to 0.76, (p=0.02)). Calibration was good (Hosmer-Lemeshow test; p=0.94). By offering colonoscopy to the 102 patients at highest risk, rather than to the 102 cases with a FIT result >50 ng/mL, 5 more cases of advanced neoplasia would be detected (net reclassification improvement 0.054, p=0.073).
Adding risk based stratification increases the accuracy FIT-based CRC screening and could be used in preselection for colonoscopy in CRC screening programmes.
粪便免疫化学检测（FIT）越来越多地用于结直肠癌（CRC）筛查，但敏感性不够完美。基于高级肿瘤的既定危险因素进行风险分层，并结合 FIT 结果将筛查者分配到结肠镜检查，可以提高基于 FIT 的筛查的敏感性和诊断收益。我们探讨了在 CRC 筛查中使用风险预测模型的情况。
我们在多中心筛查试验结肠镜检查或结肠成像筛查研究的结肠镜检查臂中收集数据。在这项研究中，我们邀请了 6600 名年龄在 50 岁至 75 岁之间的无症状男性和女性进行结肠镜检查。筛查参与者在结肠镜检查前被要求进行一次 FIT（OC-sensor）检测，并填写一份风险问卷。根据问卷数据和 FIT 结果，我们开发了一个多变量风险模型，其中包括以下因素：总钙摄入量、家族史、年龄和 FIT 结果。我们评估了拟合优度、校准和区分度，并将其与仅基于 FIT 的初级筛查模型进行了比较。
在 1426 名筛查参与者中，有 1112 名（78%）完成了问卷和 FIT。其中，有 101 名（9.1%）患有高级肿瘤。基于风险的模型与仅基于 FIT 的模型相比，显著提高了拟合优度（p<0.001）。基于风险的模型显著提高了区分度（接受者操作特征曲线下面积：从 0.69 提高到 0.76，p=0.02）。校准良好（Hosmer-Lemeshow 检验；p=0.94）。通过为风险最高的 102 名患者提供结肠镜检查，而不是为 102 名 FIT 结果>50ng/mL 的患者提供结肠镜检查，可以发现 5 例更多的高级肿瘤病例（净重新分类改善 0.054，p=0.073）。
增加基于风险的分层可提高基于 FIT 的 CRC 筛查的准确性，并可用于 CRC 筛查计划中结肠镜检查的预选择。
