Skip to content
DraconiticResearch
Search Sources API
203,203 studies31 sourcesUpdated 28 min ago
Peer-reviewedCC BYCancer medicine

Core Self-Reported Variables for Next-Generation Colorectal Cancer Risk Prediction: An International Expert Consensus Study.

  • Hanna Dubois1,2
  • Eva Torbjörnsson1,3
  • Jessica Norrbom4
  • Alan Hubbard5
  • Mirna Enskär1
  • Rachael V Phillips5
  • Mark van der Laan5
  • Johannes Blom1,6
6 affiliations
  1. 1Department of Clinical Science and Education Södersjukhuset, Karolinska Institutet, Stockholm, Sweden.
  2. 2Theme Cancer, Karolinska University Hospital, Stockholm, Sweden.
  3. 3Department of Perioperative and Intensive Care, Södersjukhuset, Stockholm, Sweden.
  4. 4Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden.
  5. 5Division of Biostatistics, School of Public Health, University of California at Berkeley, California, USA.
  6. 6Department of Surgery, Södersjukhuset, Stockholm, Sweden.
Read full textPDFDOICite

Abstract

Background

Colorectal cancer remains a major global health burden, and although population-based screening is beneficial, current programs have notable limitations. Risk-stratified screening has been proposed, yet existing prediction models vary in performance and in the inclusion of predictors. Data-adaptive modeling (machine learning) may strengthen risk prediction but depends on high-quality input data. Expert consensus methods offer a structured way to identify clinically meaningful variables for future tools.Objective

To establish expert consensus on the selection of relevant variables and refinement of self-reported questionnaire items for next-generation colorectal cancer risk-prediction tools.Methods

A modified Delphi study was conducted with seventeen internationally recognized experts. The process consisted of anonymized, email-based rounds aimed at refining a questionnaire for colorectal cancer risk prediction. Across three iterative rounds, experts rated item relevance, proposed revisions, and identified missing domains while reviewing group-level summaries of ratings and comments. Items not meeting predefined thresholds were removed, and validated lifestyle-related items were incorporated. Consensus was defined as 15 of 17 experts rating an item within a similar three-point range.Results

All seventeen experts completed all rounds. The final I-CRC-RISK Questionnaire comprises 23 items across seven categories: Demography, Health Status, Family Health History, Dietary Patterns, Physical Activity, Smoking, and Alcohol Consumption. Expert consensus was reached for 19 items.Conclusion

The I-CRC-RISK Questionnaire provides an expert-informed set of self-reported variables to support future risk prediction efforts. It offers a structured basis for further validation and psychometric testing before prospective data collection may be undertaken. This foundational work could enhance the predictive performance of both traditional and machine-learning approaches by improving the consistency and relevance of input data.

Related

  1. International expert consensus on managing elective hernia repair in patients with Crohn’s disease using the Delphi method
    BJS openPeer-reviewedCC BYFull textSurgery & anaesthesiaEurope PMC
  2. Handheld Ultrasound: Technical Review and International Expert Consensus Recommendations
    Christoph F. Dietrich, Michael Blaivas, Vito Cantisani +14
    Diagnostics (Basel, Switzerland)Peer-reviewedCC BYFull textGeneral medicineEurope PMC
  3. Protocol for the development of a paediatric core outcome set for arthrogryposis multiplex congenita: an international multi-interest-holder consensus study.
    Naomi Zukerman, Vasiliki Betty Darsaklis, Clarice Araujo +10
    BMJ openPeer-reviewedCC BYFull textGeneral medicineEurope PMCCrossref
  4. Genetic testing in pituitary adenomas: a Pituitary Society International Consensus Statement
    Sunita de Sousa, Cynthia Andoniadou, Adrian Daly +21
    Nature Reviews EndocrinologyPeer-reviewedLicence not statedFull text2 citedGeneral biologyEndocrinology & metabolismHAL
  5. Risk-based pathology reporting after endoscopic submucosal dissection for early gastrointestinal cancer: international consensus standards
    Kareem Khalaf, Huaqi Li, Mai Iwaya +47
    GutPeer-reviewedLicence not statedFull textGeneral biologyGeneral medicineHAL

Cite

BibTeXRIS
BibTeX
@article{dubois2026core,
  title = {{Core Self-Reported Variables for Next-Generation Colorectal Cancer Risk Prediction: An International Expert Consensus Study.}},
  author = {Hanna Dubois and Eva Torbjörnsson and Jessica Norrbom and Alan Hubbard and Mirna Enskär and Rachael V Phillips and Mark van der Laan and Johannes Blom},
  journal = {Cancer medicine},
  year = {2026},
  month = oct,
  doi = {10.1002/cam4.72348},
  url = {https://europepmc.org/article/MED/42910538},
  note = {CC BY},
}
RIS
TY  - JOUR
TI  - Core Self-Reported Variables for Next-Generation Colorectal Cancer Risk Prediction: An International Expert Consensus Study.
AU  - Hanna Dubois
AU  - Eva Torbjörnsson
AU  - Jessica Norrbom
AU  - Alan Hubbard
AU  - Mirna Enskär
AU  - Rachael V Phillips
AU  - Mark van der Laan
AU  - Johannes Blom
PY  - 2026
DA  - 2026/10/01
JO  - Cancer medicine
DO  - 10.1002/cam4.72348
UR  - https://europepmc.org/article/MED/42910538
AB  - Background  Colorectal cancer remains a major global health burden, and although population-based screening is beneficial, current programs have notable limitations. Risk-stratified screening has been proposed, yet existing prediction models vary in performance and in the inclusion of predictors. Data-adaptive modeling (machine learning) may strengthen risk prediction but depends on high-quality input data. Expert consensus methods offer a structured way to identify clinically meaningful variables for future tools.Objective  To establish expert consensus on the selection of relevant variables and refinement of self-reported questionnaire items for next-generation colorectal cancer risk-prediction tools.Methods  A modified Delphi study was conducted with seventeen internationally recognized experts. The process consisted of anonymized, email-based rounds aimed at refining a questionnaire for colorectal cancer risk prediction. Across three iterative rounds, experts rated item relevance, proposed revisions, and identified missing domains while reviewing group-level summaries of ratings and comments. Items not meeting predefined thresholds were removed, and validated lifestyle-related items were incorporated. Consensus was defined as 15 of 17 experts rating an item within a similar three-point range.Results  All seventeen experts completed all rounds. The final I-CRC-RISK Questionnaire comprises 23 items across seven categories: Demography, Health Status, Family Health History, Dietary Patterns, Physical Activity, Smoking, and Alcohol Consumption. Expert consensus was reached for 19 items.Conclusion  The I-CRC-RISK Questionnaire provides an expert-informed set of self-reported variables to support future risk prediction efforts. It offers a structured basis for further validation and psychometric testing before prospective data collection may be undertaken. This foundational work could enhance the predictive performance of both traditional and machine-learning approaches by improving the consistency and relevance of input data.
SN  - 2045-7634
ER  -