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Treatment response lowers tumor symptom burden in recurrent and/or metastatic head and neck cancer
(2020)
Background: Head and neck squamous cell cancer (HNSCC) frequently causes severe symptoms that may be reduced, when the tumor is successfully treated. The SOCCER trial studied the association of treatment response with patient reported tumor symptom burden in first line treatment of recurrent and/or metastatic HNSCC.
Methods: In this prospective, multi-center, non-interventional trial patients were treated either with platinum-based chemotherapy and cetuximab or radiotherapy and cetuximab. Tumor symptom burden was assessed every four weeks with a questionnaire containing ten visual analogue scales (VAS, range 0–100), which were summarized to the overall VAS score.
Results: Fourhundred seventy patients were registered in 97 German centers. A total of 315 patients with at least the baseline and one subsequent questionnaire were available for analysis. Changes in the VAS score were rated as absolute differences from baseline. Negative values indicate improvement of symptoms. The overall VAS score improved significantly at the first post-baseline assessment in responders (− 2.13 vs. non-responders + 1.15, p = 0.048), and even more for the best post-baseline assessment (− 7.82 vs. non-responders − 1.97, p = 0.0005). The VAS for pain (− 16.37 vs. non-responders − 8.89, p = 0.001) and swallowing of solid food (− 16.67 vs. non-responders − 5.06, p = 0.002) improved significantly more in responders (best post-baseline assessment). In the multivariable Cox regression analysis, worse overall VAS scores were associated with worse overall survival (hazard ratio for death 1.12 per 10 points increment on the overall VAS scale, 95% CI 1.05–1.20, p = 0.0009).
Conclusion: In unselected patients beyond randomized controlled trials, treatment response lowers tumor symptom burden in recurrent and/or metastatic HNSCC.
Trial registration: ClinicalTrials.gov, NCT00122460. Registered 22 Juli 2005,
Comprehensive analysis of tumour sub-volumes for radiomic risk modelling in locally advanced HNSCC
(2020)
Simple Summary: Radiomic risk models are usually based on imaging features, which are extracted from the entire gross tumour volume (GTV entire ). This approach does not explicitly consider the complex biological structure of the tumours. Therefore, in this retrospective study, we investigated the prognostic value of radiomic analyses based on different tumour sub-volumes using computed tomography imaging of patients with locally advanced head and neck squamous cell carcinoma who were treated with primary radio-chemotherapy. The GTV entire was cropped by different margins to define the rim and corresponding core sub-volumes of the tumour. Furthermore, the best performing tumour rim sub-volume was extended into surrounding tissue with different margins. As a result, the models based on the 5 mm tumour rim and on the 3 mm extended rim sub-volume showed an improved performance compared to models based on the corresponding tumour core. This indicates that the consideration of tumour sub-volumes may help to improve radiomic risk models.
Abstract: Imaging features for radiomic analyses are commonly calculated from the entire gross tumour volume (GTVentire). However, tumours are biologically complex and the consideration of different tumour regions in radiomic models may lead to an improved outcome prediction. Therefore, we investigated the prognostic value of radiomic analyses based on different tumour sub-volumes using computed tomography imaging of patients with locally advanced head and neck squamous cell carcinoma. The GTVentire was cropped by different margins to define the rim and the corresponding core sub-volumes of the tumour. Subsequently, the best performing tumour rim sub-volume was extended into surrounding tissue with different margins. Radiomic risk models were developed and validated using a retrospective cohort consisting of 291 patients in one of the six Partner Sites of the German Cancer Consortium Radiation Oncology Group treated between 2005 and 2013. The validation concordance index (C-index) averaged over all applied learning algorithms and feature selection methods using the GTVentire achieved a moderate prognostic performance for loco-regional tumour control (C-index: 0.61 ± 0.04 (mean ± std)). The models based on the 5 mm tumour rim and on the 3 mm extended rim sub-volume showed higher median performances (C-index: 0.65 ± 0.02 and 0.64 ± 0.05, respectively), while models based on the corresponding tumour core volumes performed less (C-index: 0.59 ± 0.01). The difference in C-index between the 5 mm tumour rim and the corresponding core volume showed a statistical trend (p = 0.10). After additional prospective validation, the consideration of tumour sub-volumes may be a promising way to improve prognostic radiomic risk models.
Purpose: To develop and validate a CT-based radiomics signature for the prognosis of loco-regional tumour control (LRC) in patients with locally advanced head and neck squamous cell carcinoma (HNSCC) treated by primary radiochemotherapy (RCTx) based on retrospective data from 6 partner sites of the German Cancer Consortium - Radiation Oncology Group (DKTK-ROG).
Material and methods: Pre-treatment CT images of 318 patients with locally advanced HNSCC were collected. Four-hundred forty-six features were extracted from each primary tumour volume and then filtered through stability analysis and clustering. First, a baseline signature was developed from demographic and tumour-associated clinical parameters. This signature was then supplemented by CT imaging features. A final signature was derived using repeated 3-fold cross-validation on the discovery cohort. Performance in external validation was assessed by the concordance index (C-Index). Furthermore, calibration and patient stratification in groups with low and high risk for loco-regional recurrence were analysed.
Results: For the clinical baseline signature, only the primary tumour volume was selected. The final signature combined the tumour volume with two independent radiomics features. It achieved moderately good discriminatory performance (C-Index [95% confidence interval]: 0.66 [0.55–0.75]) on the validation cohort along with significant patient stratification (p = 0.005) and good calibration.
Conclusion: We identified and validated a clinical-radiomics signature for LRC of locally advanced HNSCC using a multi-centric retrospective dataset. Prospective validation will be performed on the primary cohort of the HNprädBio trial of the DKTK-ROG once follow-up is completed.