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

A study on predicting cases that would benefit from proton beam therapy in primary liver tumors of less than or equal to 5 cm based on the estimated incidence of hepatic toxicity

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An advantage of PBT is reducing the liver receiving low doses of radiation.

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The factors predicting the benefit in PBT are different among NTCP models.

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The tumor size, number, and location are useful in estimating the benefits of PBT.

Background

Materials and methods

Results

Conclusions

Predictive performance of different NTCP techniques for radiation-induced esophagitis in NSCLC patients receiving proton radiotherapy

This study aimed to compare the predictive performance of different modeling methods in developing normal tissue complication probability (NTCP) models for predicting radiation-induced esophagitis (RE) in non–small cell lung cancer (NSCLC) patients receiving proton radiotherapy. The dataset was composed of 328 NSCLC patients receiving passive-scattering proton therapy and 41.6% of the patients experienced ≥ grade 2 RE. Five modeling methods were used to build NTCP models: standard Lyman–Kutcher–Burman (sLKB), generalized LKB (gLKB), multivariable logistic regression using two variable selection procedures-stepwise forward selection (Stepwise-MLR), and least absolute shrinkage and selection operator (LASSO-MLR), and support vector machines (SVM). Predictive performance was internally validated by a bootstrap approach for each modeling method. The overall performance, discriminative ability, and calibration were assessed using the Negelkerke R², area under the receiver operator curve (AUC), and Hosmer–Lemeshow test, respectively. The LASSO-MLR model showed the best discriminative ability with an AUC value of 0.799 (95% confidence interval (CI): 0.763–0.854), and the best overall performance with a Negelkerke R² value of 0.332 (95% CI: 0.266–0.486). Both of the optimism-corrected Negelkerke R² values of the SVM and sLKB models were 0.301. The optimism-corrected AUC of the gLKB model (0.796) was higher than that of the SVM model (0.784). The sLKB model had the smallest optimism in the model variation and discriminative ability. In the context of classification and probability estimation for predicting the NTCP for radiation-induced esophagitis, the MLR model developed with LASSO provided the best predictive results. The simplest LKB modeling had similar or even better predictive performance than the most complex SVM modeling, and it was least likely to overfit the training data. The advanced machine learning approach might have limited applicability in clinical settings with a relatively small amount of data.

A scoping review of patient selection methods for proton therapy

The aim was to explore various national and international clinical decision‐making tools and dose comparison methods used for selecting cancer patients for proton versus X‐ray radiation therapy. To address this aim, a literature search using defined scoping review methods was performed in Medline and Embase databases as well as grey literature. Articles published between 1 January 2015 and 4 August 2020 and those that clearly stated methods of proton versus X‐ray therapy patient selection and those published in English were eligible for inclusion. In total, 321 studies were identified of which 49 articles met the study’s inclusion criteria representing 13 countries. Six different clinical decision‐making tools and 14 dose comparison methods were identified, demonstrating variability within countries and internationally. Proton therapy was indicated for all paediatric patients except those with lymphoma and re‐irradiation where individualised model‐based selection was required. The most commonly reported patient selection tools included the Normal Tissue Complication Probability model, followed by cost‐effectiveness modelling and dosimetry comparison. Model‐based selection methods were most commonly applied for head and neck clinical indications in adult cohorts (48% of studies). While no ‘Gold Standard’ currently exists for proton therapy patient selection with variations evidenced globally, some of the patient selection methods identified in this review can be used to inform future practice in Australia. As literature was not identified from all countries where proton therapy centres are available, further research is needed to evaluate patient selection methods in these jurisdictions for a comprehensive overview.

Development and Implementation of Proton Therapy for Hodgkin Lymphoma: Challenges and Perspectives

Simple Summary

Hodgkin lymphoma (HL) is a highly curable disease; proton therapy for mediastinal HL irradiation might theoretically reduce late toxicities compared with classical radiotherapy techniques. However, optimal patient selection for this technique is subject to debate. While implementation at a larger scale of proton therapy for HL may face organizational, political, and societal challenges, new highly effective systematic drugs are being widely evaluated for this disease.

Abstract

Consolidative radiation therapy for early-stage Hodgkin lymphoma (HL) improves progression-free survival. Unfortunately, first-generation techniques, relying on large irradiation fields, were associated with an increased risk of secondary cancers, and of cardiac and lung toxicity. Fortunately, the use of smaller target volumes combined with technological advances in treatment techniques currently allows efficient organs-at-risk sparing without altering tumoral control. Recently, proton therapy has been evaluated for mediastinal HL treatment due to its potential to significantly reduce the dose to organs-at-risk, such as cardiac substructures. This is expected to limit late radiation-induced toxicity and possibly, second-neoplasm risk, compared with last-generation intensity-modulated radiation therapy. However, the democratization of this new technique faces multiple issues. Determination of which patient may benefit the most from proton therapy is subject to intense debate. The development of new effective systemic chemotherapy and organizational, societal, and political considerations might represent impediments to the larger-scale implementation of HL proton therapy. Based on the current literature, this critical review aims to discuss current challenges and controversies that may impede the larger-scale implementation of mediastinal HL proton therapy.

Exploiting the full potential of proton therapy: An update on the specifics and innovations towards spatial or temporal optimisation of dose delivery

Prescription and delivery of protons are somewhat different compared to photons and may influence outcomes (tumour control and toxicity). These differences should be taken into account to fully exploit the clinical potential of proton therapy. Innovations in proton therapy treatment are also required to widen the therapeutic window and determine appropriate populations of patients that would benefit from new treatments. Therefore, strategies are now being developed to reduce side effects to critical normal tissues using alternative treatment configurations and new spatial or temporal-driven optimisation approaches. Indeed, spatiotemporal optimisation (based on flash, proton minibeam radiation therapy or hypofractionated delivery methods) has been gaining some attention in proton therapy as a mean of improving (biological and physical) dose distribution. In this short review, the main differences in planning and delivery between protons and photons, as well as some of the latest developments and methodological issues (in silico modelling) related to providing scientific evidence for these new techniques will be discussed.