Modeling the Risk of Radiation Pneumonitis in Esophageal Squamous Cell Carcinoma Treated with Definitive Chemoradiotherapy

Abstract

Purpose: To develop and validate a nomogram for the prediction of symptomatic radiation pneumonitis (RP) in patients with esophageal squamous cell carcinoma (ESCC) who received definitive concurrent chemoradiotherapy.

Methods: Clinical factors, dose-volume histogram parameters, and pulmonary function parameters were collected from 402 ESCC patients between 2010 and 2017, including 321 patients in the primary cohort and 81 in the validation cohort. The end-point was the occurrence of symptomatic RP (grade ≥2) within the first 12 months after radiotherapy. Univariate and multivariate logistic regression analyses were applied to evaluate the predictive value of each factor for RP. A prediction model was generated in the primary cohort, which was internally validated to assess its performance.

Results: In the primary cohort, 31 patients (9.7%) experienced symptomatic RP. Based on logistic regression model, patients with larger planning target volumes (PTVs) or higher lung V₂₀ had a higher predictive risk of RP, whereas the overall risk was substantially higher for three-dimensional conformal radiotherapy (3DCRT) than intensity-modulated radiotherapy. On multivariate analysis, independent predictive factors for RP were smoking history (P=0.018), radiotherapy modality (P<0.001), PTV (P=0.014), and lung V₂₀ (P=0.002), which were incorporated into the nomogram. The areas under the receiver operating characteristic curve of the nomogram in the primary and validation cohorts were 0.772 and 0.900, respectively, which were superior to each predictor alone.

Conclusions: Non-smoking status, 3DCRT, lung V₂₀ (>27.5%), and PTV (≥713.0 cc) were significantly associated with a higher risk of RP. A nomogram was built with satisfactory prediction ability.

Introduction

Esophageal cancer (EC) is one of the leading causes of cancer-related death worldwide, with an estimated 508,585 deaths yearly [1]. Definitive chemoradiotherapy (CRT) is the standard care in the management of unresectable EC [2, 3]. Radiation pneumonitis (RP) is one of the major complications after thoracic irradiation. Despite low mortality, RP can result in respiratory insufficiency, seriously affect patients’ quality of life, influence the completion of radiotherapy and following treatment, and even reduce the curative effect, particularly for patients with symptomatic RP [4]. Although the survival benefit of concurrent CRT over radiotherapy alone is evident, the former has been demonstrated to be correlated with an increased risk of RP[5]. Therefore, decreasing the incidence of RP is of critical clinical significance for EC patients who received concurrent CRT.

An increasing number of studies have investigated predictors for RP [4–12]. Various risk factors, including clinical characteristics, dosimetric parameters, treatment-related variables, as well as serum biomarkers have been reported to be associated with the occurrence of RP [4–12]. However, the majority of these reports focused on patients with lung cancer, and data regarding EC patients undergoing definitive CRT is limited. Considering the differences in baseline pulmonary function and in the level of radiation dose between lung cancer and EC patients, it is unreasonable to extrapolate risk factors for RP in lung cancer to EC. On the other hand, despite the significantly increasing use of intensity-modulated radiotherapy (IMRT) in recent years, its impact on RP remains unclear in EC.

Therefore, the purpose of study was to investigate the associations between clinical factors, dose-volume histogram (DVH) parameters, as well as pulmonary function parameters, and the risk of symptomatic RP in patients with esophageal squamous cell carcinoma (ESCC) who received definitive concurrent CRT. Then a nomogram model predicting RP was developed and validated to guide clinical decision-making.

Patients And Methods

Results

Discussion

Symptomatic RP is a common side effect of radiotherapy for EC with incidence of 5.7–35.0% [5–11], which is confirmed by our study. In this cohort of ESCC patients undergoing definitive CRT, smoking history, radiotherapy modality, PTV, and lung V₂₀ were significant predictive factors for symptomatic RP. More importantly, a nomogram has been built and validated, indicating satisfactory prediction ability. Thus, this prediction model could help clinicians select high-risk patients who may benefit from modified treatment approaches to reduce the risk of RP prior to the initiation of treatment.

In recent years, radiation techniques have evolved from 3DCRT to IMRT and proton therapy in EC. Numerous dosimetric studies have well demonstrated the superiority of IMRT over 3DCRT in improving target coverage and sparing adjacent organs, but whether the dosimetric benefits could translate into clinical benefit, especially reducing the incidence of radiation-related toxicities, remains inconclusive due to the lack of prospective evidence [14]. In a large-scale retrospective study reported by He et al, IMRT significantly reduced the incidence and postponed the onset of pleural effusion in EC patients, compared to 3DCRT [15]. However, Haefner et al found no evident difference in acute toxicities between IMRT and 3DCRT, possibly due to the small sample size of the cohort and the higher radiation dose in the IMRT group [16]. In our study, after adjusting for smoking history, PTV, and Lung V₂₀, IMRT was associated with a substantially lower risk of RP than 3DCRT. This is in consistence with the secondary analysis of results from RTOG 0617, which prospectively demonstrated that IMRT group had significantly less severe RP than 3DCRT group in locally advanced non-small cell lung cancer (3.5% vs. 7.9%, P = 0.039) [17]. In addition, IMRT could also reduce the incidence of postoperative pulmonary and cardiac complication in EC patients who received neoadjuvant CRT and surgery, as reported by Lin et al [18]. Furthermore, IMRT was associated with more favorable survival outcomes than 3DCRT in EC [14]. Collectively, despite the paucity of prospective evidence, the current findings strongly suggest the routine use of IMRT in EC.

As a novel radiation technique with superior physical properties, proton therapy has the potential to improve normal tissue sparing as compared to 3DCRT or IMRT [14]. Several studies have investigated the clinical advantages of proton therapy compared to photon therapy. For EC patients who underwent neoadjuvant CRT, proton therapy was superior to IMRT in reducing incidence of pulmonary complications [18]. Recently, Lin et al reported that the proton arm experienced numerically fewer cardiopulmonary toxicities compared with IMRT arm in a phase IIB randomized trial for EC [19]. The ongoing larger cooperative group studies will clarify the clinical benefit of proton therapy in EC, such as NRG-GI006.

There has been a general consensus that DVH parameters are important predictors for RP. However, there is still no recommendation of dose-volume constraints for EC. Wang et al reported that the volume of the lung spared from doses of ≥ 5 Gy was the only independent dosimetric factor associated with pulmonary complications [20]. Cho et al indicated that MLD was the parameter most related to pulmonary complications in EC [21]. Likewise, a recent study demonstrated the strong correlation between MLD and severe RP in 416 EC patients undergoing CRT [22]. Consistent with studies reported by Asakura et al and Shaikh et al [9, 23], all DVH parameters (lung V₅-V₃₀ and MLD) were significantly associated with RP in univariate analysis in our cohort. Of them, V₂₀ was the only independent predictor in multivariate analysis, with the optimal threshold value of V₂₀ (27.5%). The failure of the other dosimetric parameters to be retained significance in the multivariate model could be explained by their potential correlation with V₂₀. Thus, other dosimetric parameters should also be taken into consideration when performing treatment planning for EC.

In addition to lung dosimetric parameters, we observed that patients with greater PTVs had a remarkably higher incidence of RP. In line with our results, Cui et al also reported the strong correlation between PTV and the occurrence of RP in elderly EC [24]. Considering PTV is a variable that could be modified, smaller radiation volumes might reduce the risk of RP. A meta-analysis reported that neither local control rates nor survival outcomes differed significantly between elective nodal irradiation and involved-field irradiation in ESCC, whereas incidences of severe RP and radiation esophagitis were significantly lower in the latter group [25]. Therefore, involved-field irradiation should be considered in clinical practice, especially for elderly patients. Among clinical factors, smoking history was found to be a protective factor for RP in our study, which is consistent with previous studies [26, 27]. The possible explanations are smoking-associated hypoxia and a decreased inflammatory reaction induced by irradiation among smokers [28, 29], but the underlying mechanism for the smoking effect on RP remains unclear.

Compared with each separate predictor, integrating predictive factors to develop a statistical model will further improve predictive accuracy. So far, only one study reported by Wang et al had built a combined model to predict severe RP in EC [22]. However, this study included a fraction of patients without concurrent chemotherapy during radiotherapy, which might affect the incidence of RP. Moreover, this study incorporated not only pretreatment factors but also the changes of inflammatory indexes during radiotherapy into the nomogram [22]. Despite excellent discriminatory power of the model, it is of less value to guide decision-making before the initiation of treatment.

It should be noted that our work also has several limitations. Firstly, selection bias existed due to the retrospective nature of this study. Secondly, the sample size of the validation set is relatively small, and an independent external validation is needed. Thirdly, although all patients included were treated with concurrent CRT, treatment modalities such as the utility of induction chemotherapy and chemotherapy regimens were not identical in this study. However, these factors were not correlated with the risk of RP in univariate analysis. Finally, serum biomarkers as well as radiomics-based features were not incorporated into the study, which might further promote predictive ability of the model.

Conclusions

Non-smoking status, 3DCRT, lung V₂₀ (> 27.5%), and PTV (≥ 713.0 cc) were significantly associated with a higher risk of symptomatic RP in ESCC patients treated with definitive CRT. Then a nomogram was built and validated, exhibiting satisfactory prediction ability. Further studies are warranted to verify the efficacy of the predicting model and to explore potential strategies for minimizing the risk of RP in high-risk patients.

Abbreviations

AUC: Area Under the Curve; CI: Confidence Interval; COPD: Chronic Obstructive Pulmonary Disease; CRT: Definitive Chemoradiotherapy; CTCAE: National Cancer Institute Common Toxicity Criteria for Adverse Events; CTV: Clinical Target Volume; DCA: Decision Curve Analysis; DLCO: Diffusing Capacity for Carbon Monoxide; DVH: Dose-Volume Histogram; EC: Esophageal Cancer; ECOG: Eastern Cooperative Oncology Group; ESCC: Esophageal Squamous Cell Carcinoma; FEV1: Forced Expiratory Volume in the First Second; GTV: Gross Tumor Volume; IMRT: Intensity-Modulated Radiotherapy; MLD: Mean Lung Dose; PTV: Planning Target Volume; ROC: Receiver Operating Characteristic; RP: Radiation Pneumonitis; TLV: Total Lung Volume; Vx: Percentage of the Total Lung Volume Receiving more than x Gy; 3DCRT: Three-Dimensional Conformal Radiotherapy.

Declarations

Ethics approval and consent to participate

The study was approved by our institution.

Consent for publication

Not applicable.

Availability of data and materials

All data generated or analysed during this study were included in this published article.

Competing interests

The authors declare that there is no conflict of interest.

Funding

This work was supported by grants from the Fundamental Research Funds for the Central Universities (19ykpy176) and Natural Science Foundation of Guangdong Province (2019A1515011420).

Author contributions

Conception and design: LZ, MX.

Acquisition of data: KQL, CX, SLL, JHZ, YDY, LZ, MX.

Analysis and interpretation of data: KQL, CX, SLL, JHZ, YDY, LZ, MX.

Writing, review, and/or revision of the manuscript: KQL, CX, SLL, JHZ, YDY, LZ, MX.

All authors read and approved the final manuscript.

Acknowledgements

We thank all the patients who participated in this study.

Author details

¹State Key Laboratory of Oncology in South China, Collaborative Innovation Centre for Cancer Medicine, Guangdong Esophageal Cancer Institute, Guangzhou, China;

²Department of Nasopharyngeal Carcinoma, Sun Yat-sen University Cancer Center, Guangzhou, China;

³Department of Radiation Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China;

⁴Department of Imaging Diagnosis and Interventional Center, Sun Yat-sen University Cancer Center, Guangzhou, China.

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