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Proton Radiation Therapy for Nasopharyngeal Cancer Patients: Dosimetric and NTCP Evaluation Supporting Clinical Decision.

ABSTRACT: (1) Background: we proposed an integrated strategy to support clinical allocation of nasopharyngeal patients between proton and photon radiotherapy. (2) Methods: intensity-modulated proton therapy (IMPT) plans were optimized for 50 consecutive nasopharyngeal carcinoma (NPC) patients treated with volumetric modulated arc therapy (VMAT), and differences in dose and normal tissue complication probability (ΔNTCPx-p) for 16 models were calculated. Patient eligibility for IMPT was assessed using a model-based selection (MBS) strategy following the results for 7/16 models describing the most clinically relevant endpoints, applying a model-specific ΔNTCPx-p threshold (15% to 5% depending on the severity of the complication) and a composite threshold (35%). In addition, a comprehensive toxicity score (CTS) was defined as the weighted sum of all 16 ΔNTCPx-p, where weights follow a clinical rationale. (3) Results: Dose deviations were in favor of IMPT (ΔDmean ≥ 14% for cord, esophagus, brainstem, and glottic larynx). The risk of toxicity significantly decreased for xerostomia (-12.5%), brain necrosis (-2.3%), mucositis (-3.2%), tinnitus (-8.6%), hypothyroidism (-9.3%), and trismus (-5.4%). There were 40% of the patients that resulted as eligible for IMPT, with a greater advantage for T3-T4 staging. Significantly different CTS were observed in patients qualifying for IMPT. (4) Conclusions: The MBS strategy successfully drives the clinical identification of NPC patients, who are most likely to benefit from IMPT. CTS summarizes well the expected global gain.

SUBMITTER: Vai A

PROVIDER: S-EPMC8909055 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature

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Proton Radiation Therapy for Nasopharyngeal Cancer Patients: Dosimetric and NTCP Evaluation Supporting Clinical Decision.

Vai Alessandro A Molinelli Silvia S Rossi Eleonora E Iacovelli Nicola Alessandro NA Magro Giuseppe G Cavallo Anna A Pignoli Emanuele E Rancati Tiziana T Mirandola Alfredo A Russo Stefania S Ingargiola Rossana R Vischioni Barbara B Bonora Maria M Ronchi Sara S Ciocca Mario M Orlandi Ester E

Cancers 20220222 5

(1) Background: we proposed an integrated strategy to support clinical allocation of nasopharyngeal patients between proton and photon radiotherapy. (2) Methods: intensity-modulated proton therapy (IMPT) plans were optimized for 50 consecutive nasopharyngeal carcinoma (NPC) patients treated with volumetric modulated arc therapy (VMAT), and differences in dose and normal tissue complication probability (ΔNTCPx-p) for 16 models were calculated. Patient eligibility for IMPT was assessed using a mod ...[more]

PMID: 35267415

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Project description:Radiation therapy (RT) of thoracic cancers may cause severe radiation dermatitis (RD), which impacts on the quality of a patient's life. Aim of this study was to analyze the incidence of acute RD and develop normal tissue complication probability (NTCP) models for severe RD in thoracic cancer patients treated with Intensity-Modulated RT (IMRT) or Passive Scattering Proton Therapy (PSPT). We analyzed 166 Non-Small-Cell Lung Cancer (NSCLC) patients prospectively treated at a single institution with IMRT (103 patients) or PSPT (63 patients). All patients were treated to a prescribed dose of 60 to 74 Gy in conventional daily fractionation with concurrent chemotherapy. RD was scored according to CTCAE v3 scoring system. For each patient, the epidermis structure (skin) was automatically defined by an in house developed segmentation algorithm. The absolute dose-surface histogram (DSH) of the skin were extracted and normalized using the Body Surface Area (BSA) index as scaling factor. Patient and treatment-related characteristics were analyzed. The Lyman-Kutcher-Burman (LKB) NTCP model recast for DSH and the multivariable logistic model were adopted. Models were internally validated by Leave-One-Out method. Model performance was evaluated by the area under the receiver operator characteristic curve, and calibration plot parameters. Fifteen of 166 (9%) patients developed severe dermatitis (grade 3). RT technique did not impact RD incidence. Total gross tumor volume (GTV) size was the only non dosimetric variable significantly correlated with severe RD (p = 0.027). Multivariable logistic modeling resulted in a single variable model including S 20Gy, the relative skin surface receiving more than 20 Gy (OR = 31.4). The cut off for S 20Gy was 1.1% of the BSA. LKB model parameters were TD50 = 9.5 Gy, m = 0.24, n = 0.62. Both NTCP models showed comparably high prediction and calibration performances. Despite skin toxicity has long been considered a potential limiting factor in the clinical use of PSPT, no significant differences in RD incidence was found between RT modalities. Once externally validated, the availability of NTCP models for prediction of severe RD may advance treatment planning optimization.

Project description:PurposeWe propose and simulate a model-based methodology to incorporate heterogeneous treatment benefit of proton therapy (PrT) versus photon therapy into randomized trial designs. We use radiation-induced pneumonitis (RP) as an exemplar. The aim is to obtain an unbiased estimate of how predicted difference in normal tissue complications probability (ΔNTCP) converts into clinical outcome on the patient level.Materials and methodsΔNTCP data from in silico treatment plans for photon therapy and PrT for patients with locally advanced lung cancer as well as randomly sampled clinical risk factors were included in simulations of trial outcomes. The model used at point of analysis of the trials was an iQUANTEC model. Trial outcomes were examined with Cox proportional hazards models, both in case of a correctly specified model and in a scenario where there is discrepancy between the dose metric used for ΔNTCP and the dose metric associated with the "true" clinical outcome, that is, when the model is misspecified. We investigated how outcomes from such a randomized trial may feed into a model-based estimate of the patient-level benefit from PrT, by creating patient-specific predicted benefit probability distributions.ResultsSimulated trials showed benefit in accordance with that expected when the NTCP model was equal to the model for simulating outcome. When the model was misspecified, the benefit changed and we observed a reversal when the driver of outcome was high-dose dependent while the NTCP model was mean-dose dependent. By converting trial results into probability distributions, we demonstrated large heterogeneity in predicted benefit, and provided a randomized measure of the precision of individual benefit estimates.ConclusionsThe design allows for quantifying the benefit of PrT referral, based on the combination of NTCP models, clinical risk factors, and traditional randomization. A misspecified model can be detected through a lower-than-expected hazard ratio per predicted ΔNTCP.

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Dataset Information

Proton Radiation Therapy for Nasopharyngeal Cancer Patients: Dosimetric and NTCP Evaluation Supporting Clinical Decision.

Publications

Proton Radiation Therapy for Nasopharyngeal Cancer Patients: Dosimetric and NTCP Evaluation Supporting Clinical Decision.

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