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粪便潜血丢失准确预测结直肠癌的未来检出。一种预后模型。

Faecal occult blood loss accurately predicts future detection of colorectal cancer. A prognostic model.

机构信息

Department of Public Health, Erasmus MC University Medical Centre, Rotterdam, The Netherlands

Department of Public Health, Erasmus MC University Medical Centre, Rotterdam, The Netherlands.

出版信息

Gut. 2023 Jan;72(1):101-108. doi: 10.1136/gutjnl-2022-327188. Epub 2022 May 10.

DOI:10.1136/gutjnl-2022-327188
PMID:35537811
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9763180/
Abstract

OBJECTIVES

To examine the prognostic potential of repeated faecal haemoglobin (F-Hb) concentration measurements in faecal immunochemical test (FIT)-based screening for colorectal cancer (CRC).

DESIGN

Prognostic model.

SETTING

Dutch biennial FIT-based screening programme during 2014-2018.

PARTICIPANTS

265 881 participants completing three rounds of FIT, with negative test results (F-Hb <47 µg Hb/g faeces) in rounds 1 and 2.

INTERVENTIONS

Colonoscopy follow-up in participants with a positive FIT (F-Hb ≥47 µg Hb/g faeces).

MAIN OUTCOMES

We evaluated prognostic models for detecting advanced neoplasia (AN) and CRC in round 3, with as predictors, participant age, sex, F-Hb in rounds 1 and 2, and categories/combinations/non-linear transformations of F-Hb. Primary evaluation criteria included: risk prediction accuracy (calibration), discrimination of participants with versus without AN or CRC (optimism-adjusted C-statistics, range 0.5-1.0), the degree of risk stratification and C-statistics in external validation.

RESULTS

Among study participants, 8806 (3.3%) had a positive FIT result, 3254 (1.2%) had AN detected and 557 (0.2%) had cancer. F-Hb concentrations in rounds 1 and 2 were the strongest outcome predictors, with adjusted ORs of up to 9.4 (95% CI 7.5 to 11.7) for the highest F-Hb category. Risk predictions matched the observed risk for most participants (calibration intercept -0.008 to -0.099; slope 0.982-0.998), and discriminated participants with versus without AN or CRC with C-statistics of 0.78 (95% CI 0.77 to 0.79) and 0.73 (95% CI 0.71 to 0.75), respectively. The predicted risk ranged from 0.4% to 36.7% for AN and from 0.0% to 5.5% for CRC across participants. In external validation, the model retained similar discrimination accuracy for AN (C-statistic 0.77, 95% CI 0.66 to 0.87) and CRC (C-statistic 0.78, 95% CI 0.66 to 0.91).

CONCLUSION

Participants at lower versus higher risk of future AN or CRC can be accurately identified based on their age, sex and particularly, prior F-Hb concentrations. Risk stratification should be considered based on this information.

摘要

目的

检测粪便血红蛋白(F-Hb)浓度在粪便免疫化学试验(FIT)基础的结直肠癌(CRC)筛查中重复测量的预后潜力。

设计

预后模型。

设置

2014-2018 年荷兰每两年进行一次基于 FIT 的筛查计划。

参与者

265881 名参与者完成了三轮 FIT,前两轮的检测结果为阴性(F-Hb<47µg Hb/g 粪便)。

干预措施

对 FIT 阳性(F-Hb≥47µg Hb/g 粪便)的参与者进行结肠镜随访。

主要结局

我们评估了在第 3 轮检测晚期肿瘤(AN)和 CRC 的预后模型,预测因子包括参与者年龄、性别、第 1 轮和第 2 轮的 F-Hb 以及 F-Hb 的类别/组合/非线性变换。主要评估标准包括:风险预测准确性(校准)、有和无 AN 或 CRC 的参与者之间的区分(校正后 C 统计量,范围 0.5-1.0)、风险分层程度和外部验证的 C 统计量。

结果

在研究参与者中,8806 名(3.3%)的 FIT 结果为阳性,3254 名(1.2%)发现有 AN,557 名(0.2%)患有癌症。第 1 轮和第 2 轮的 F-Hb 浓度是最强的结果预测因子,最高 F-Hb 类别下的调整比值比(OR)高达 9.4(95%CI 7.5-11.7)。风险预测与大多数参与者的实际风险相匹配(校准截距-0.008 至-0.099;斜率 0.982-0.998),并通过 C 统计量为 0.78(95%CI 0.77-0.79)和 0.73(95%CI 0.71-0.75)区分了有和无 AN 或 CRC 的参与者。在整个参与者中,AN 的预测风险范围为 0.4%至 36.7%,CRC 的预测风险范围为 0.0%至 5.5%。在外部验证中,该模型对 AN(C 统计量 0.77,95%CI 0.66-0.87)和 CRC(C 统计量 0.78,95%CI 0.66-0.91)的区分准确性保持相似。

结论

可根据参与者的年龄、性别以及特别是之前的 F-Hb 浓度,准确识别出未来发生 AN 或 CRC 的低风险和高风险人群。应根据这些信息进行风险分层。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3310/9763180/ba635aafcfcf/gutjnl-2022-327188f04.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3310/9763180/0a994b85c13b/gutjnl-2022-327188f01.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3310/9763180/f6b32312ca2c/gutjnl-2022-327188f02.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3310/9763180/aed8e5e4f2d3/gutjnl-2022-327188f03.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3310/9763180/ba635aafcfcf/gutjnl-2022-327188f04.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3310/9763180/0a994b85c13b/gutjnl-2022-327188f01.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3310/9763180/f6b32312ca2c/gutjnl-2022-327188f02.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3310/9763180/aed8e5e4f2d3/gutjnl-2022-327188f03.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3310/9763180/ba635aafcfcf/gutjnl-2022-327188f04.jpg

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