Literature DB >> 30241789

External validation of an NTCP model for acute esophageal toxicity in locally advanced NSCLC patients treated with intensity-modulated (chemo-)radiotherapy.

Frank J W M Dankers1, Robin Wijsman2, Esther G C Troost3, Caroline J A Tissing-Tan4, Margriet H Kwint5, José Belderbos5, Dirk de Ruysscher6, Lizza E Hendriks7, Lioe-Fee de Geus-Oei8, Laura Rodwell9, Andre Dekker6, René Monshouwer10, Aswin L Hoffmann11, Johan Bussink10.   

Abstract

BACKGROUND AND
PURPOSE: We externally validated a previously established multivariable normal-tissue complication probability (NTCP) model for Grade ≥2 acute esophageal toxicity (AET) after intensity-modulated (chemo-)radiotherapy or volumetric-modulated arc therapy for locally advanced non-small cell lung cancer.
MATERIALS AND METHODS: A total of 603 patients from five cohorts (A-E) within four different Dutch institutes were included. Using the NTCP model, containing predictors concurrent chemoradiotherapy, mean esophageal dose, gender and clinical tumor stage, the risk of Grade ≥2 AET was estimated per patient and model discrimination and (re)calibration performance were evaluated.
RESULTS: Four validation cohorts (A, B, D, E) experienced higher incidence of Grade ≥2 AET compared to the training cohort (49.3-70.2% vs 35.6%; borderline significant for one cohort, highly significant for three cohorts). Cohort C experienced lower Grade ≥2 AET incidence (21.7%, p < 0.001). For three cohorts (A-C), discriminative performance was similar to the training cohort (area under the curve (AUC) 0.81-0.89 vs 0.84). In the two remaining cohorts (D-E) the model showed poor discriminative power (AUC 0.64 and 0.63). Reasonable calibration performance was observed in two cohorts (A-B), and recalibration further improved performance in all three cohorts with good discrimination (A-C). Recalibration for the two poorly discriminating cohorts (D-E) did not improve performance.
CONCLUSIONS: The NTCP model for AET prediction was successfully validated in three out of five patient cohorts (AUC ≥0.80). The model did not perform well in two cohorts, which included patients receiving substantially different treatment. Before applying the model in clinical practice, validation of discrimination and (re)calibration performance in a local cohort is recommended.
Copyright © 2018 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Acute esophagitis; External validation; Intensity-modulated radiation therapy; Non-small cell lung cancer; Predictive modeling

Mesh:

Year:  2018        PMID: 30241789     DOI: 10.1016/j.radonc.2018.07.021

Source DB:  PubMed          Journal:  Radiother Oncol        ISSN: 0167-8140            Impact factor:   6.280


  3 in total

1.  Perspectives on the model-based approach to proton therapy trials: A retrospective study of a lung cancer randomized trial.

Authors:  Aimee L McNamara; David C Hall; Nadya Shusharina; Amy Liu; Xiong Wei; Ali Ajdari; Radhe Mohan; Zhongxing Liao; Harald Paganetti
Journal:  Radiother Oncol       Date:  2020-03-27       Impact factor: 6.280

2.  Risk factors for esophagitis after hypofractionated palliative (chemo) radiotherapy for non-small cell lung cancer.

Authors:  Carsten Nieder; Kristian S Imingen; Bård Mannsåker; Rosalba Yobuta; Ellinor Haukland
Journal:  Radiat Oncol       Date:  2020-05-01       Impact factor: 3.481

3.  Clinical suitability of deep learning based synthetic CTs for adaptive proton therapy of lung cancer.

Authors:  Adrian Thummerer; Carmen Seller Oria; Paolo Zaffino; Arturs Meijers; Gabriel Guterres Marmitt; Robin Wijsman; Joao Seco; Johannes Albertus Langendijk; Antje-Christin Knopf; Maria Francesca Spadea; Stefan Both
Journal:  Med Phys       Date:  2021-11-16       Impact factor: 4.506

  3 in total

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