Combining risk factors with faecal immunochemical test outcome for selecting CRC screenees for colonoscopy

Stegeman, Inge; Wijkerslooth, Thomas R. de; Stoop, Esther M.; Leerdam, Monique E. van; Dekker, Evelien; Ballegooijen, Marjolein van; Kuipers, Ernst J.; Fockens, Paul; Kraaijenhagen, Roderik A.; Bossuyt, Patrick M.

doi:10.1136/gutjnl-2013-305013

Cited by 91 publications

(105 citation statements)

References 25 publications

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“…9 Models incorporating sophisticated risk scores to more efficiently stratify screening have been proposed; such models including symptomatology, age, family history, and biomarker cut-off may improve diagnostic yield. 23,24 Repeating the test might also improve the PPV without impacting the NPV. 25 FC offers the promise of a risk stratification for all patients with lower gastrointestinal symptoms, rather than the current focus on those with suspected colorectal cancer that distorts clinical thinking and becomes increasingly inefficient as the symptombased predictive value falls ever lower.…”

Section: Implications For Research and Practicementioning

confidence: 99%

Faecal calprotectin in patients with suspected colorectal cancer: a diagnostic accuracy study

Turvill¹,

Aghahoseini²,

Sivarajasingham³

et al. 2016

Br J Gen Pract

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Section: Implications For Research and Practicementioning

confidence: 99%

Faecal calprotectin in patients with suspected colorectal cancer: a diagnostic accuracy study

Turvill¹,

Aghahoseini²,

Sivarajasingham³

et al. 2016

Br J Gen Pract

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“…Several other statistical methods were used in the development of models such as jackknife feature selection and ANOVA testing [32], multivariate non-linear Poisson regression [42], recursive portioning analysis [44] and classification tree analysis [53]. However, four models were identified as developed from non-statistical methods such as consensus method [25,51], extracting data from previously published validated models [49] or from previous studies [54].…”

Section: Development Of the Modelsmentioning

confidence: 99%

“…However, 11 models are specific for females [20,22,35,42,45,50] while 10 models are specific for males [20,22,35,45,48]. Although many models have not restricted application to a specific age limit, 11 models have been developed from populations aged 30 years and above [15,20,42,43,50], 10 from populations aged 50 years and above [18,25,26,45,51] and seven from populations aged 40 years and above [14,19,23,24,36,38,52]. In addition, one model has used a population above 20 years [35] while another, populations lower than 80 years [34].…”

Section: Questionnairementioning

confidence: 99%

“…A majority (n=35) of models include variables obtained through a questionnaire [18,19,21,22,23,24,25,26,27,28,30,33,36,37,38,39,40,41,42,43,44,45,46,49,50,51,53,54]. The questionnaires range from those with only one or two simple questions to those with detailed questions on factors such as diet, physical activity, alcohol and smoking habits and past medical facts.…”

Section: Development Of the Modelsmentioning

confidence: 99%

“…Three models have been developed in China [16,23,36] and Japan [40] while, Netherlands [25,26], Germany [21], Taiwan [32,46] and United Kingdom [31,34] have developed two models each. Many other countries, such as Australia [19], Poland [24], Hong Kong [28], Italy [29], Qatar [41], Saudi Arabia [43], Spain [52] and Sri Lanka [15] have also developed country-specific risk prediction models for colorectal cancer.…”

Section: Questionnairementioning

confidence: 99%

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Risk prediction models for colorectal cancer: A Scoping review

Samarakoon¹,

Pathmeswaran

Gunawardena³

2018

J. Postgrad. Inst. Med.

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Background and objectives Many risk prediction models have been developed globally to identify specific populations at high risk for colorectal cancer in specific settings. Documentation of available evidence from existing studies will serve as a useful information base. We performed a scoping review, to review and analyse published risk prediction models for colorectal cancer the world over. Methods A scoping review was undertaken to address the following question 'what are the existing risk prediction models to identify the risk of developing colorectal cancer among individuals in different countries and settings?' using the framework developed by Arksey and O'Malley for scoping reviews. Forty-one articles were included in this review from database searches and from additional searches. The titles and abstracts were reviewed using predetermined screening criteria. We limited our search to existing literature in English language and included both observational and interventional studies. Results Out of the 58 risk prediction models identified, most were developed for colorectal cancer followed by advanced colorectal cancer. Most of the articles reviewed were cross sectional studies or cohort studies. Statistical methods such as multiple logistic regression was used by a majority, while few have incorporated non-statistical methods such as consensus method and extracting data from published literature. The authors of the 58 risk prediction models have considered 77 different risk factors excluding the genetic variants. Conclusions This comprehensive scoping review demonstrates the capacity of the existing risk models to stratify the general population into risk categories, detailing the studies conducted, location, study design, outcome, overview of the methods, data source and the identified risk predictors. While striving to build on existing knowledge, the review also identifies the research gaps and the need for further improvement.

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Analysis of population‐based colorectal cancer screening in Guangzhou, 2011‐2015

et al. 2019

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Objective To analyze the detection rates of colorectal cancer (CRC) and polyps by population‐based screening in Guangzhou. Methods From January 2011 to December 2015, the residents aged 30‐79 were selected for CRC screening. The residents were conducted Questionnaires and/or FOBT to assess high‐risk groups, the free colonoscopy examination was recommended, and the results were evaluated in detail. Results There were 98 927 residents involving screening, 5306 high‐risk residents identified (males 1859 and females 3447), and 4713 subjects underwent colonoscopy (males 1690 and females 3023). CRC was seen in 55 individuals (males 28 and females 27), and the detection rates in male were higher than in female ( P = 0.019). And the detection rates increasing with age, for people over 60 years old, were obviously higher than those younger ( x 2 = 18.64, P = 0.000924). The polyps were seen in 1458 (30.94%) cases， and 1420 subjects received pathological examination (adenomas 971 and non‐adenomatous polyps 449). Advanced adenomas were seen in 462 cases (males 240 and females 222) and 509 cases of non‐advanced adenomas (males 255 and females 254). For advanced adenomas, the detection rates in male were higher than female (14.20% vs 7.34%, P = 2.64 × 10 −14 ). For the detection rates of adenomas or advanced adenomas by age, the people over 40 years were higher than younger (20.91% vs 3.61% P = 7.87 × 10 −6 ; 9.94% vs 2.41%, P = 0.009). Conclusions For Guangzhou residents, the detection rates of CRC and adenoma were 1.17% and 20.60%. The detection rates of CRC increasing with age, for people over 60 years old, were obviously higher than those younger. But for people over 40 years, the detection rate of adenoma and advanced adenoma was higher than younger. So for people over 40 years, the CRC screening is recommended.

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Combining risk factors with faecal immunochemical test outcome for selecting CRC screenees for colonoscopy

Abstract: Adding risk based stratification increases the accuracy FIT-based CRC screening and could be used in preselection for colonoscopy in CRC screening programmes.

Cited by 91 publications

References 25 publications

Faecal calprotectin in patients with suspected colorectal cancer: a diagnostic accuracy study

Faecal calprotectin in patients with suspected colorectal cancer: a diagnostic accuracy study

Risk prediction models for colorectal cancer: A Scoping review

Analysis of population‐based colorectal cancer screening in Guangzhou, 2011‐2015

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