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Table 3 Results of the risk of bias for each domain of the PROBAST tool

From: Polygenic risk prediction models for colorectal cancer: a systematic review

First author, year [ref] Risk of bias (ROB) Applicability Overall
Participants Predictors Outcome Analysis Participants Predictors Outcome Risk of Bias Applicability
Dev Val Dev Val Dev Val Dev Val Dev Val Dev Val Dev Val
Abe M, 2017 [22] High High High High Unclear Unclear High High Low Low Low Low Low Low High Low
Balavarca Y, 2019 [23] High   High   Low   High   High   Low   Low   High High
Chandler PD, 2018 [24] Low   High   High   High   Low   Low   Low   High Low
Cho YA, 2019 [25] High   High   High   High   Low   Low   Low   High Low
de Kort S, 2019 [26] Low   High   Low   High   Low   Low   Low   High Low
Dunlop MG, 2013 [27] High High Unclear Unclear Unclear Unclear Low Low Low Low Low Low Low Low High Low
Hiraki LT, 2013 [28] High   High   High   High   Low   Low   Low   High Low
Hosono S, 2016 [29] High High High High Unclear Unclear High High Low Low Low Low Low Low High Low
Hsu L, 2015 [30] High Low Low Low Low Low Unclear Unclear Low Low Low Low Low Low High Low
Huyghe JR, 2019 [31] Low   Low   Low   Unclear   Low   Low   Low   Unclear Low
Ibáñez-Sanz G, 2017 [32] High   Unclear   Low   Unclear   Low   Low   Low   High Low
Iwasaki M, 2017 [33] Low   Unclear   Low   Unclear   Low   Low   Low   High* Low
Jenkins MA, 2019 [34]   High   Low   High   Unclear   Low   Low   Low High Low
Jeon J, 2018 [35] High High Low Low Low Low Unclear Unclear Low Low Low Low Low Low High Low
Jo J, 2012 [36] Low   Unclear   Low   High   Low   Low   Low   High Low
Jung KJ, 2015 [37] Low   Unclear   Low   High   Low   Low   Low   High Low
Jung SY, 2019 [38] Low   High   Unclear   High   High   High   Low   High High
Marshall KW, 2010 [39] High High Unclear Unclear Low Low High High Unclear Unclear Low Low Low Low High Unclear
Prizment AE, 2013 [40] Low   Low   Low   High   High   Low   Low   High High
Rodriguez-Broadbent H, 2017 [41] High   High   High   High   High   Low   Low   High High
Schmit SL, 2019 [42] High High Unclear Unclear Low Low Unclear Unclear Low Low Low Low Low Low High Low
Shi Z, 2019 [43] Low   Low   Low   Unclear   Low   Low   Low   Unclear Low
Smith T, 2018 [44]   Low   Low   Unclear   High   Low   Low   Low High Low
Thrift AP, 2015 [45] High   High   High   High   High   Low   Low   High Low
Thrift AP, 2015 [46] High   High   High   High   High   Low   Low   High Low
Wang HM, 2013 [47] High   Unclear   Low   High   Unclear   Low   Low   High Unclear
Wang K, 2018 [48] Low   Low   Low   High   Low   Low   Low   High Low
Weigl K, 2018 [49] High High Unclear Unclear Low Low High High High High Low Low Low Low High High
Weigl K, 2018 [50] High   Unclear   Low   High   Low   Low   Low   High Low
Xin J, 2018 a [51]   Low   Unclear   Unclear   High   Low   Low   High High High
Xin J, 2019 [52] High   Unclear   Low   Unclear   Low   Low   Low   High Low
Yeh CC, 2007 [53] High   Unclear   Low   High   Low   Low   Low   High Low
Zhang L, 2017 [54] High   Unclear   Unclear   High   Low   Low   Low   High Low
  1. In the risk of bias assessment, “low” means low risk of bias, “high” means high risk of bias, and “unclear” means it was not possible to assess the risk of bias. In the applicability section, “high” means high concern for applicability, “low” means low concern for applicability, and “unclear” means it was not possible to assess the applicability. Risk of bias assessed with the PROBAST tool
  2. * = a high risk of bias was assigned because of the lack of external validation, among other reasons
  3. a = quality assessment conducted only for the validation phase of the study, since model development involved a simulated population (among our exclusion criteria)