Development, validation and effectiveness of diagnostic prediction tools for colorectal cancer in primary care: a systematic review

Table 3 Risk of bias assessment for the included model development/validation studies

Model (author offirst version)	Stage of development covered	I. Participantselection^a	II. Predictors^a	III. Outcome^a	IV. Samplesize andparticipantflow^a	V. Analysis^a
RAT (Hamilton) series of models for colorectal and meta-staticcancer [33, 36, 43]}
	Apparent performance	✓	?	✓	?	x
	External validation (colorectal only) [27]	✓	✓	✓	?	?
QCancer (Hippisley-Cox) series of models for colorectal andmultiple sites for females and males [22, 23, 37, 38]
	Internal validation	✓	✓	✓	✓	✓
	External validation (colorectal only) [23]	✓	✓	✓	✓	✓
Bristol-Birmingham (Marshall) [29] model for colorectal cancer
	External validation	✓	?	✓	?	✓
	External validation (Elias and colleagues,2017) [27]	✓	✓	✓	?	?
Netherlands’ (Fitjen 1995 [28]) model for colorectal cancer
	Apparent performance	x	✓	✓	?	x
	External validation (Hodder and colleagues,2005) [40]	x	?	x	✓	?
	External validation (Elias and colleagues,2017) [27]	✓	✓	✓	?	?
Netherlands’ (Kop) [32] ‘machine learning’ for colorectal cancer
	Apparent performance	✓	?	✓	?	?
Danish (Nørrelund 1996 [31]) model for colorectal cancer
	Apparent performance	✓	?	✓	?	x
	External validation (Elias and colleagues,2017) [27]	✓	✓	✓	?	?
Netherlands’ (Muris 1995 [30]) model for abdominal complaints
	Apparent performance	?	✓	✓	?	x
	External validation (Elias and colleagues,2017) [27]	✓	✓	✓	?	?
Prediction model for abdominal cancers(Holtedahl and colleagues, 2018) [39]
Holtedahl, 2018	Apparent performance	?	✓	?	x	?

ISSN: 1471-2407