Using inflammatory indexes and clinical parameters to predict radiation esophagitis in patients with small-cell lung cancer undergoing chemoradiotherapy

Research progress of radiation esophagitis: A narrative review

Radiation esophagitis (RE) is an adverse reaction to radiotherapy for thoracic malignancies and a major factor limiting the dosage for thoracic tumors. In cases of RE, mild conditions may involve only discomfort in the throat, severe cases can present with intense pain and significant difficulty swallowing, and may lead to interruptions in radiation therapy, affecting the treatment outcome. However, much of the current research focuses on how to diagnose and treat the disease and needs to address the prevention of RE. In this review, several online databases, including PubMed, Web of Science, Google Scholar, the China National Knowledge Infrastructure, and the Chinese Medical Journal Database, were searched to collect relevant published studies. This review provides updated information on the pathogenesis, diagnosis, risk factors, development of predictive models, prevention, and treatment of RE, aiming to serve as a reference for its diagnosis, treatment, and prevention.

Predicting Severe Radiation Pneumonitis in Patients With Locally-Advanced Non-Small-Cell Lung Cancer After Thoracic Radiotherapy: Development and Validation of a Nomogram Based on the Clinical, Hematological, and Dose-Volume Histogram Parameters

PURPOSE

This study aimed to investigate the risk factors for severe radiation pneumonitis (RP) after thoracic radiotherapy (RT) in patients with locally advanced non-small cell lung cancer (NSCLC), develop a prediction model to identify high-risk groups, and investigate the impact of severe RP on overall survival (OS).

METHODS

We retrospectively collected clinical, dosimetric, and hematological factors of patients with stage III NSCLC receiving thoracic RT without immunotherapy. The primary and secondary end points were severe RP and OS, respectively. Fine-Gray competing risk regression analyses were used to identify the risk factors for severe RP. The patients were randomly divided into training and validation cohorts at a ratio of 6:4. The model was evaluated using receiver operating characteristic (ROC) and calibration curves, and decision curve analysis (DCA). The OS of patients in the RP vs. non-RP and mild RP vs. severe RP groups was analyzed using the Kaplan-Meier method.

RESULTS

A total of 305 patients were enrolled in the analysis, and 32 (10.5%) developed severe RP. Interstitial lung disease (ILD) (P = .013), percentage of ipsilateral lung volume receiving ≥ 20 Gy (ipsilateral V20) (P = .029), pre-RT derived neutrophil lymphocyte ratio (dNLR) (P = .026), and post-RT systemic inflammation response index (SIRI) (P = .010) were independent predictors of severe RP, and were used to establish the nomogram based on a training cohort. The ROC area under the curve (AUC) of the nomogram was 0.804. Calibration curves and DCA showed favorable consistency and positive net benefits in both training and validation cohorts. Cases who developed severe RP had a shorter OS than those who developed mild RP (P = .027).

CONCLUSION

ILD, ipsilateral V20, pre-RT dNLR, and post-RT SIRI could predict severe RP in patients with locally advanced NSCLC receiving thoracic RT. By combining these indicators, a nomogram was constructed and validated, demonstrating its potential value in clinical practice.

Clinical implications of the serum platelet-to-lymphocyte ratio in the modern radiation oncology era: research update and literature review

Radiation therapy (RT) continues to be the primary approach for treating cancer, and numerous cancer biomarkers associated with oncological outcomes have been investigated in the context of RT. The serum platelet-to-lymphocyte ratio (PLR) is one of the emerging landmark biomarker in the oncologic field. Mounting evidence indicates that an elevated serum PLR may function as a marker of unfavorable tumor characteristics, adverse treatment outcomes and treatment-related toxicities among individuals undergoing RT. However, the findings of these investigations have revealed a few disparities among researchers, highlighting the need for further meticulously planned studies to draw conclusive results. This article provides a comprehensive literature review and in-depth discussion regarding the clinical implications of the serum PLR in the modern RT era.

Prognostic value of pretreatment modified Glasgow Prognostic Score in small cell lung cancer: A meta-analysis

BACKGROUND

The prognostic role of pretreatment modified Glasgow Prognostic Score (mGPS) in small cell lung cancer (SCLC) patients remains unclear now.

METHODS

The PubMed, EMBASE, Web of Science, and CNKI electronic databases were searched up to December 14, 2022. The primary and secondary outcomes were overall survival and progression-free survival, respectively. The hazard ratios (HRs) and 95% confidence intervals (CIs) were combined to assess the association between pretreatment mGPS and survival of SCLC patients. Subgroup analysis based on the country, tumor stage, treatment and comparison of mGPS were further conducted and all statistical analyses were performed by STATA 15.0 software.

RESULTS

A total of ten retrospective studies involving 2831 SCLC patients were included. The pooled results demonstrated that elevated pretreatment mGPS was significantly related to poorer overall survival (HR = 1.90, 95% CI: 1.36-2.63, P < .001) and progression-free survival (HR = 1.40, 95% CI: 1.13-1.74, P = .002). Subgroup analysis stratified by the country, tumor stage, treatment and comparison of mGPS also showed similar results.

CONCLUSION

Pretreatment mGPS was significantly associated with prognosis in SCLC and patients with elevated mGPS experienced obviously worse survival. Thus, pretreatment mGPS could serve as a novel and reliable prognostic indicator in SCLC patients.

Enhanced prediction of postoperative radiotherapy-induced esophagitis in non-small cell lung cancer: Dosiomic model development in a real-world cohort and validation in the PORT-C randomized controlled trial

BACKGROUND

Radiotherapy-induced esophagitis (RE) diminishes the quality of life and interrupts treatment in patients with non-small cell lung cancer (NSCLC) undergoing postoperative radiotherapy. Dosimetric models showed limited capability in predicting RE. We aimed to develop dosiomic models to predict RE.

METHODS

Models were trained with a real-world cohort and validated with PORT-C randomized controlled trial cohort. Patients with NSCLC undergoing resection followed by postoperative radiotherapy between 2004 and 2015 were enrolled. The endpoint was grade ≥2 RE. Esophageal three-dimensional dose distribution features were extracted using handcrafted and convolutional neural network (CNN) methods, screened using an entropy-based method, and selected using minimum redundancy and maximum relevance. Prediction models were built using logistic regression. The areas under the receiver operating characteristic curve (AUC) and precision-recall curve were used to evaluate prediction model performance. A dosimetric model was built for comparison.

RESULTS

A total of 190 and 103 patients were enrolled in the training and validation sets, respectively. Using handcrafted and CNN methods, 107 and 4096 features were derived, respectively. Three handcrafted, four CNN-extracted and three dosimetric features were selected. AUCs of training and validation sets were 0.737 and 0.655 for the dosimetric features, 0.730 and 0.724 for handcrafted features, and 0.812 and 0.785 for CNN-extracted features, respectively. Precision-recall curves revealed that CNN-extracted features outperformed dosimetric and handcrafted features.

CONCLUSIONS

Prediction models may identify patients at high risk of developing RE. Dosiomic models outperformed the dosimetric-feature model in predicting RE. CNN-extracted features were more predictive but less interpretable than handcrafted features.

Clinical impact of first-line PD-1 or PD-L1 inhibitors combined with chemotherapy in extensive-stage small cell lung cancer patients: A real-world multicenter propensity score-matched study

OBJECTIVES

Our research aimed to evaluate the effectiveness of first-line immune checkpoint inhibitors (ICIs) with etoposide and platinum (EP) for extensive-stage small cell lung cancer (ES-SCLC) and identify prognostic factors, as real-world outcomes and the inconsistency of PD-1 and PD-L1 inhibitors are uncertain.

METHODS

We selected ES-SCLC patients in three centers and conducted a propensity score-matched analysis. The Kaplan-Meier method and Cox proportional hazards regression were conducted to compare the survival outcomes. We also performed univariate and multivariate Cox regression analyses to investigate predictors.

RESULTS

Among 236 patients included, 83 pairs of cases were matched. The EP plus ICIs cohort had a longer median overall survival (OS) (17.3 months) than the EP cohort (13.4 months) (hazard ratio [HR],  0.61 [0.45, 0.83]; p = 0.001). The median progression-free survival (PFS) was also longer in the EP plus ICIs cohort (8.3 months) than in the EP cohort (5.9 months) (HR,   0.44 [0.32, 0.60]; p < 0.001). The EP plus ICIs group had a higher objective response rate (ORR) (EP: 62.3%, EP + ICIs: 84.3%, p < 0.001). Multivariate analysis presented that liver metastases (HR, 2.08; p = 0.018) and lymphocyte-monocyte ratio (LMR) (HR, 0.54; p = 0.049) were independent prognostic factors for OS, and performance status (PS) (HR, 2.11; p = 0.015), liver metastases (HR, 2.64; p = 0.002), and neutrophil-lymphocyte ratio (NLR) (HR, 0.45; p = 0.028) were for PFS in patients with chemo-immunotherapy.

CONCLUSION

Our real-world data demonstrated that ICIs with chemotherapy as the first-line setting for ES-SCLC are effective and safe. PS, liver metastases, and inflammatory markers could serve as valuable risk factors.