Prospective study of proton‐beam radiation therapy for limited‐stage small cell lung cancer

Rwigema, Jean‐Claude M.; Verma, Vivek; Lin, Liyong; Berman, Abigail T.; Levin, William P.; Evans, Tracey L.; Aggarwal, Charu; Rengan, Ramesh; Langer, Corey J.; Cohen, Roger B.; Simone, Charles B.

doi:10.1002/cncr.30870

Cited by 49 publications

(31 citation statements)

References 33 publications

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“…The comparatively low radiation esophagitis rates we report here may reflect treatment improvements over eras reflecting improved symptom prevention and proactive care, as well as advanced radiation treatment modalities. Importantly, to our knowledge, our series is the first machine learning analysis to include a cohort of patients treated with proton beam therapy, which may also result in lower than expected radiation esophagitis rates, as has been reported in locally advanced lung cancer prospective population treated with proton therapy [38]. Additionally, the lower than expected toxicity rates may contribute to a lack of reliable predictors in our models due to insufficient radiation esophagitis events.…”

Section: Discussionmentioning

confidence: 92%

Machine learning highlights the deficiency of conventional dosimetric constraints for prevention of high-grade radiation esophagitis in non-small cell lung cancer treated with chemoradiation

Luna

Chao

Shinohara

et al. 2020

Clinical and Translational Radiation Oncology

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a b s t r a c tBackground and Purpose: Radiation esophagitis is a clinically important toxicity seen with treatment for locally-advanced non-small cell lung cancer. There is considerable disagreement among prior studies in identifying predictors of radiation esophagitis. We apply machine learning algorithms to identify factors contributing to the development of radiation esophagitis to uncover previously unidentified criteria and more robust dosimetric factors. Materials and Methods: We used machine learning approaches to identify predictors of grade 3 radiation esophagitis in a cohort of 202 consecutive locally-advanced non-small cell lung cancer patients treated with definitive chemoradiation from 2008 to 2016. We evaluated 35 clinical features per patient grouped into risk factors, comorbidities, imaging, stage, histology, radiotherapy, chemotherapy and dosimetry. Univariate and multivariate analyses were performed using a panel of 11 machine learning algorithms combined with predictive power assessments. Results: All patients were treated to a median dose of 66.6 Gy at 1.8 Gy per fraction using photon (89.6%) and proton (10.4%) beam therapy, most often with concurrent chemotherapy (86.6%). 11.4% of patients developed grade 3 radiation esophagitis. On univariate analysis, no individual feature was found to predict radiation esophagitis (AUC range 0.45-0.55, p 0.07). In multivariate analysis, all machine learning algorithms exhibited poor predictive performance (AUC range 0.46-0.56, p 0.07). Conclusions: Contemporary machine learning algorithms applied to our modern, relatively large institutional cohort could not identify any reliable predictors of grade 3 radiation esophagitis. Additional patients are needed, and novel patient-specific and treatment characteristics should be investigated to develop clinically meaningful methods to mitigate this survival altering toxicity.

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Section: Discussionmentioning

confidence: 92%

Machine learning highlights the deficiency of conventional dosimetric constraints for prevention of high-grade radiation esophagitis in non-small cell lung cancer treated with chemoradiation

Luna

Chao

Shinohara

et al. 2020

Clinical and Translational Radiation Oncology

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“…A possible reason for this result is that previous studies used large and 2-dimensional fields with elective nodal irradiation, which increased radiation exposure to normal tissues (9). At present, 3D-or intensity-modulated radiotherapy provides fewer, higher dose fractions and achieves similar results as the hyper-fractionated regimen (32). We suggest that future studies should use advanced radiotherapy techniques to determine the optimal dose and fractionation for limited-stage SCLC therapy.…”

Section: Discussionmentioning

confidence: 92%

A Meta-Analysis of the Efficacy and Toxicity of Twice-Daily vs. Once-Daily Concurrent Chemoradiotherapy for Limited-Stage Small Cell Lung Cancer Based on Randomized Controlled Trials

Xiong

Zhang

et al. 2020

Front. Oncol.

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Background: Currently, the accepted standard management of limited-stage small cell lung cancer (SCLC) is concurrent chemoradiotherapy (CCRT), but the frequency of radiotherapy is controversial. Therefore, this meta-analysis, which compared the efficacy and toxicity between twice-daily (BID) and once-daily (OD) CCRT, was performed to help clinicians make better decisions. Methods: Relevant randomized controlled trials (RCTs) were collected by searching the PubMed, Ovid MEDLINE, Embase, ScienceDirect, Web of Science, the Cochrane Library, Scopus and Google Scholar databases to assess antitumor effects (overall survival, OS; progression-free survival, PFS; overall response rate, ORR) and toxicity (adverse effects, AEs). Results: We screened 1499 articles and included 5 RCTs including 1421 patients. We found that BID CCRT improved OS (hazard ratio, HR = 0.88, 95% confidence interval, CI 0.78-0.99, p = 0.03), the 1-year OS rate (OSR-1y, risk ratio, RR = 1.07, 95%CI 1.01-1.13, p = 0.03), and OSR-4y (RR = 1.22, 95%CI 1.03-1.43, p = 0.02), with better trends in OSR-2y, OSR-3y, and OSR-5y, compared to OD CCRT. In addition, BID CCRT had a higher complete response (CR, RR = 1.31, 95%CI 1.01-1.70, p = 0.04) than OD CCRT. PFS (HR = 0.92, 95%CI 0.79-1.07, p = 0.29), annual PFS rate, ORR (RR = 0.99, 95%CI 0.93-1.05, p = 0.72), and AEs for all grades (RR = 1.00, 95%CI 0.98-1.01, p = 0.57), and grades 3-5 (RR = 1.02, 95%CI 0.95-1.09, p = 0.60) were similar between the two arms. Conclusions: BID CCRT appears to be better than OD CCRT for limited-stage SCLC, with better antitumor effects (OS, OSR, and CR) and similar AEs. However, the high levels of AEs in both arms should be taken as a sign of caution. More large sample and high-quality RCTs need to be conducted to confirm our conclusions.

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“…Although, there were no improvements in dose-volume indices for lung, PSPT significantly reduced the mean radiation dose to the heart (P=0.002). Similarly, other studies have demonstrated lower doses to the heart, but suggested that lower mean lung doses and V 20 could also be achieved with improving planning and delivery techniques over time (19,20).…”

Section: Editorialmentioning

confidence: 87%

Comparison of proton therapy and intensity modulated photon radiotherapy for locally advanced non-small cell lung cancer: considerations for optimal trial design

2018

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Prospective study of proton‐beam radiation therapy for limited‐stage small cell lung cancer

Abstract: In the first prospective registry study and largest analysis to date of PBT for LS-SCLC, PBT was found to be safe with a limited incidence of high-grade toxicities. Cancer 2017;123:4244-4251. © 2017 American Cancer Society.

Cited by 49 publications

References 33 publications

Machine learning highlights the deficiency of conventional dosimetric constraints for prevention of high-grade radiation esophagitis in non-small cell lung cancer treated with chemoradiation

Machine learning highlights the deficiency of conventional dosimetric constraints for prevention of high-grade radiation esophagitis in non-small cell lung cancer treated with chemoradiation

A Meta-Analysis of the Efficacy and Toxicity of Twice-Daily vs. Once-Daily Concurrent Chemoradiotherapy for Limited-Stage Small Cell Lung Cancer Based on Randomized Controlled Trials

Comparison of proton therapy and intensity modulated photon radiotherapy for locally advanced non-small cell lung cancer: considerations for optimal trial design

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