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Related Experiment Video

Updated: Jun 13, 2026

A Model for Perineural Invasion in Head and Neck Squamous Cell Carcinoma
08:59

A Model for Perineural Invasion in Head and Neck Squamous Cell Carcinoma

Published on: January 5, 2017

Model-assisted predictions on prognosis in HNSCC: do we learn?

Marc P van der Schroeff1, Kim van Schie, Ton P M Langeveld

  • 1Department of Otorhinolaryngology, Head and Neck Surgery, Erasmus Medical Center, P.O. Box 1738, 3015 CE, Rotterdam, The Netherlands. m.vanderschroeff@erasmusmc.nl

European Archives of Oto-Rhino-Laryngology : Official Journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : Affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
|April 20, 2010
PubMed
Summary

Physician predictions for head and neck cancer survival were optimistic and inaccurate. While feedback improved accuracy slightly, prognostic predictions remain imprecise, highlighting the need for better tools.

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Area of Science:

  • Oncology
  • Medical Informatics

Background:

  • Prognostic models in software aim to assist physicians with accurate prognosis prediction.
  • Head and neck squamous cell carcinoma (HNSCC) poses challenges for accurate survival prediction.

Purpose of the Study:

  • To evaluate the accuracy of physician-based 5-year survival predictions for HNSCC patients against a software prediction (OncologIQ).
  • To assess potential learning effects in physician predictions over time.
  • To determine the impact of feedback on prediction accuracy.

Main Methods:

  • Analysis of 742 physician 5-year survival predictions for newly diagnosed HNSCC patients.
  • Comparison of physician predictions with OncologIQ software predictions using linear regression and linear mixed-effects models.
  • Evaluation of absolute differences and learning effects.

Main Results:

  • Physician predictions were consistently optimistic and inaccurate when compared to the OncologIQ model.
  • Linear models indicated minimal improvement in physician prediction accuracy with successive attempts (learning effect).
  • Providing feedback on the software's predicted survival resulted in only modest increases in physician accuracy.

Conclusions:

  • Physician-based prognostic predictions for HNSCC are generally imprecise.
  • Dedicated software shows potential but physician accuracy gains with feedback are limited.
  • Further research is needed to improve the precision of prognostic predictions in oncology.