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Predicting survival in head and neck cancer: External validation and update of the prognostic model OncologIQ in 2189 patients.


ABSTRACT:

Background

Disclosing prognostic information is necessary to enable patients to make well-informed treatment decisions. OncologIQ is a prognostic model that predicts the overall survival (OS) probability in patients with head and neck squamous cell carcinoma (HNSCC). We aimed to externally validate and update the model with new prognostic factors and translate it to a clinically useful tool.

Methods

A consecutive retrospective sample of 2189 patients eligible for curative treatment of a primary HNSCC were selected. Discriminative performance was determined using the C-statistic.

Results

External validation showed systematic underestimation of OS in the new population, and reasonable discrimination (C-statistic 0.67). Adding smoking, pack years, BMI, weight loss, WHO performance, socioeconomic status, and p16 positivity to the recalibrated multivariable model, improved the internally validated C-statistic to 0.71. The model showed minor optimism and was translated in an online tool (www.oncologiq.nl).

Conclusions

The updated model enables personalized patient counseling during treatment decision consultations.

SUBMITTER: Hoesseini A 

PROVIDER: S-EPMC8359959 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature

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Publications

Predicting survival in head and neck cancer: External validation and update of the prognostic model OncologIQ in 2189 patients.

Hoesseini Arta A   van Leeuwen Nikki N   Offerman Marinella P J MPJ   Zhang Jang J   Dronkers Emilie A C EAC   Sewnaik Aniel A   Lingsma Hester F HF   Baatenburg de Jong Robert Jan RJ  

Head & neck 20210507 8


<h4>Background</h4>Disclosing prognostic information is necessary to enable patients to make well-informed treatment decisions. OncologIQ is a prognostic model that predicts the overall survival (OS) probability in patients with head and neck squamous cell carcinoma (HNSCC). We aimed to externally validate and update the model with new prognostic factors and translate it to a clinically useful tool.<h4>Methods</h4>A consecutive retrospective sample of 2189 patients eligible for curative treatmen  ...[more]

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