External validation of nodal failure prediction models including radiomics in head and neck cancer

Zhai, Tian‐Tian; Wesseling, Frederik; Langendijk, Johannes A.; Shi, Zhenwei; Kalendralis, Petros; Dijk, Lisanne V. van; Hoebers, Frank; Steenbakkers, Roel J.H.M.; Dekker, André; Wee, Leonard; Sijtsema, Nanna M.

doi:10.1016/j.oraloncology.2020.105083

Cited by 23 publications

(15 citation statements)

References 37 publications

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“…2 . Similar variations have been observed in previous external validation studies for head and neck cancer studies for the WHO performance status for instance [28] .…”

Section: Discussionsupporting

confidence: 86%

Independent validation of a dysphagia dose response model for the selection of head and neck cancer patients to proton therapy

Kalendralis

Sloep

George

et al. 2022

Physics and Imaging in Radiation Oncology

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“…2 . Similar variations have been observed in previous external validation studies for head and neck cancer studies for the WHO performance status for instance [28] .…”

Section: Discussionsupporting

confidence: 86%

Independent validation of a dysphagia dose response model for the selection of head and neck cancer patients to proton therapy

Kalendralis

Sloep

George

et al. 2022

Physics and Imaging in Radiation Oncology

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“…It is worth mentioning that there is a chance of variations in the dysphagia CTCAEv4.0-based scoring between UMCG and MAASTRO in the different timepoints and therefore a slightly higher percentage of patients who developed more than second grade dysphagia six months after radiotherapy at MAASTRO compared to the dataset used at UMCG (30% UMCG-31.5% MAASTR0) 13 . Similar variations have been observed in previous external validation studies for head and neck cancer studies for the WHO performance status for instance 24 . This can be one of the possible reasons that explain the underestimation of the risk of patients to develop equal or greater than second grade dysphagia from the original model (model 0) as shown in figure 3.…”

Section: Discussionsupporting

confidence: 86%

Independent validation of dysphagia NTCP model for the selection of head and neck cancer patients for proton therapy in the Netherlands

Kalendralis¹,

Sloep²,

George³

et al. 2022

Preprint

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Purpose/Background: We externally validated the Normal Tissue Complication Probability (NTCP) grade II-IV at 6 months dysphagia model for head and neck cancer patients included in the Dutch National Indication Protocol for Proton Therapy (NIPP) using an independent patients’ cohort treated with (chemo)radiotherapy in MAASTRO clinic.Materials/Methods: We used 277 head and neck cancer patients treated with (chemo)radiotherapy in MAASTRO clinic between 2019-2021. For the evaluation of the model discrimination we used statistical metrics such as the sensitivity, specificity and the area under the receiver operating characteristic (ROC) curve. After validation we evaluated if the NTCP model can be improved using the closed testing procedure (CTP). Specifically, we used calibration curves to graphically assess the i) Original model, ii) Recalibration in the large, iii) Recalibration and iv) Model revision). The discrimination and calibration performance of the models was also quantitatively assessed by statistical metrics such as the Brier score, the area under the receiver operating characteristic curve, and the Hosmer–Lemeshow test.Results: The performance of the original NTCP model for dysphagia grade II-IV at 6 months was good in the independent cohort of MAASTRO clinic (AUC=0.80) but according to its calibration curve, it was underestimating the risk of the head and neck patients to develop dysphagia. Therefore, we implemented the CTP. The CTP indicated that the model had to be updated and selected a revised model with updated predictor coefficients as an updated model. The revised model had also satisfactory discrimination in MAASTRO’s cohort (AUC=0.83) with an improved calibration of predicted and observed NTCP values. Furthermore, the Hosmer–Lemeshow test for the quantitative calibration assessment, showed that the updated revised model presented the best-calibrated distribution of the predicted and observed NTCP values compared with the other models assessed by the CTP, as there was not a statistically significant difference between them (p value=0.98). Moreover, the brier score of the revised model (01.15) was the lowest among all the different calibrated models indicating higher accuracy.Conclusion: The validation of the NIPP NTCP model for grade II-IV dysphagia was successful in our independent validation cohort but can be improved using the CTP. Future steps include the participation of more independent radiotherapy centres for the validation of the NIPP NTCP models through a federated learning approach using the personal health train (PHT) infrastructure.

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“…Previous studies have shown that radiomics in computed tomography (CT) imaging can improve the prediction of prognosis of HNSCC . Radiomics on CT HNSCC imaging has been used to predict HPV status [8,9], overall survival [10][11][12][13][14], progression-free survival [10,[12][13][14], local tumour control [8,12,[15][16][17][18][19][20][21], tumour grade [9,22], lymph node response [23,24], tumour invasiveness [9,25], xerostomia [26][27][28], tumour resectability [29], and classifying molecular subtypes [30,31]. While the survival studies show that radiomics on CT data can significantly stratify patients in multiple survival groups, performance expressed through Harrell's C index ranged widely, from 0.58 to 0.9.…”

Section: Introductionmentioning

confidence: 99%

A Prospectively Validated Prognostic Model for Patients with Locally Advanced Squamous Cell Carcinoma of the Head and Neck Based on Radiomics of Computed Tomography Images

Keek

Wesseling

Woodruff

et al. 2021

Cancers

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Background: Locoregionally advanced head and neck squamous cell carcinoma (HNSCC) patients have high relapse and mortality rates. Imaging-based decision support may improve outcomes by optimising personalised treatment, and support patient risk stratification. We propose a multifactorial prognostic model including radiomics features to improve risk stratification for advanced HNSCC, compared to TNM eighth edition, the gold standard. Patient and methods: Data of 666 retrospective- and 143 prospective-stage III-IVA/B HNSCC patients were collected. A multivariable Cox proportional-hazards model was trained to predict overall survival (OS) using diagnostic CT-based radiomics features extracted from the primary tumour. Separate analyses were performed using TNM8, tumour volume, clinical and biological variables, and combinations thereof with radiomics features. Patient risk stratification in three groups was assessed through Kaplan–Meier (KM) curves. A log-rank test was performed for significance (p-value < 0.05). The prognostic accuracy was reported through the concordance index (CI). Results: A model combining an 11-feature radiomics signature, clinical and biological variables, TNM8, and volume could significantly stratify the validation cohort into three risk groups (p < 0∙01, CI of 0.79 as validation). Conclusion: A combination of radiomics features with other predictors can predict OS very accurately for advanced HNSCC patients and improves on the current gold standard of TNM8.

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External validation of nodal failure prediction models including radiomics in head and neck cancer

Cited by 23 publications

References 37 publications

Independent validation of a dysphagia dose response model for the selection of head and neck cancer patients to proton therapy

Independent validation of a dysphagia dose response model for the selection of head and neck cancer patients to proton therapy

Independent validation of dysphagia NTCP model for the selection of head and neck cancer patients for proton therapy in the Netherlands

A Prospectively Validated Prognostic Model for Patients with Locally Advanced Squamous Cell Carcinoma of the Head and Neck Based on Radiomics of Computed Tomography Images

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