Author(s):
|
Dankers, F.J.W.M.; Wijsman, R.;
Troost, E.G.C.
; Tissing-Tan, C.J.A.; Kwint, M.H.; Belderbos, J.; Ruysscher, D. de; Hendriks, L.E.;
Geus-Oei, L.F. de
;
Rodwell, L.
; Dekker, A.; Monshouwer, R.; Hoffmann, A.L.;
Bussink, J.
|
Subject:
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Radboudumc 17: Women's cancers RIHS: Radboud Institute for Health Sciences Radboudumc 9: Rare cancers RIHS: Radboud Institute for Health Sciences |
Organization:
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Radiation Oncology Radboudumc Extern Medical Imaging Health Evidence |
Journal title:
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Radiotherapy and Oncology
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Abstract:
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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.
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