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A literature-based meta-analysis of clinical risk factors for development of radiation induced pneumonitis.

ABSTRACT: The risk of developing side effects after radiotherapy is not only dependent on radiation dose, but may also be affected by patient-related risk factors. Here we perform a literature-based meta-analysis to estimate the effect of various clinical risk factors on the incidence of symptomatic radiation pneumonitis (RP).A systematic review of English language articles in the Pubmed, Embase and Cochrane controlled trials registers. Studies with the mesh term "radiation pneumonitis" or the search term "radiation pneumonitis" were included. Additional studies were identified by manual searching of the references. Studies reporting crude incidence or odds ratios (OR) for radiation pneumonitis vs. age, disease location, smoking status, chemotherapy schedule or comorbidity were included. A systematic overview (meta-analysis) was conducted to synthesize data across multiple studies.Significant risk factors for RP were: older age (OR?=?1.7, p?

SUBMITTER: Vogelius IR

PROVIDER: S-EPMC3557496 | biostudies-literature | 2012 Nov

REPOSITORIES: biostudies-literature

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A literature-based meta-analysis of clinical risk factors for development of radiation induced pneumonitis.

Vogelius Ivan R IR Bentzen Søren M SM

Acta oncologica (Stockholm, Sweden) 20120905 8

<h4>Introduction</h4>The risk of developing side effects after radiotherapy is not only dependent on radiation dose, but may also be affected by patient-related risk factors. Here we perform a literature-based meta-analysis to estimate the effect of various clinical risk factors on the incidence of symptomatic radiation pneumonitis (RP).<h4>Material and methods</h4>A systematic review of English language articles in the Pubmed, Embase and Cochrane controlled trials registers. Studies with the me ...[more]

PMID: 22950387

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Project description:PurposeWhilst survival benefits of thoracic radiotherapy (TRT) followed by immune checkpoint inhibitor (ICI) have been reported in patients with lung cancer, the potential high risk of treatment-related pneumonitis remains a concern. Asians may be more sensitive to lung toxicity than other races. This retrospective study intended to provide a comprehensive pneumonitis profile of TRT followed by ICI and investigate the risk factors from a Chinese cohort of lung cancer.Methods and materialsFrom January 2016 to July 2021, 196 patients with lung cancer who received TRT prior to ICI were retrospectively analyzed. Treatment-related pneumonitis, including checkpoint inhibitor pneumonitis (CIP), radiation pneumonitis (RP), and radiation recall pneumonitis (RRP), were recorded and graded through medical records and chest computed tomography. Characteristics predictive of pneumonitis were assessed using logistic regression models, and the receiver operating characteristic analyses were performed to identify optimal cut points for quantitative variables.ResultsWith a median follow-up of 18 months, a total of 108 patients (55.1%) developed treatment-related pneumonitis during ICI therapy, with an incidence of 25.5% for grade 2 or higher (G2+) and 4.1% for G3+. The overall rates of CIP, RP and RRP were 8.2% (n=16), 46.9% (n=92) and 7.1% (n=14), respectively. With a total mortality rate of 1.5%, vast majority of the patients recovered from pneumonitis or remained stable. No patients died of RRP. Half of the patients with G2+ RP who withheld ICI therapy restarted ICI safely after resolution of RP. The history of chronic pulmonary diseases (P=0.05), mean lung dose (MLD, P=0.038), percent volume of lung receiving ≥5 Gy (V5, P=0.012) and percent volume of lung receiving ≥20 Gy (V20, P=0.030) predicted the occurrence of RRP in univariate analyses. Interval between TRT and ICI less than 3 months was an independent predictor for G2+ treatment-related pneumonitis in a multivariate model (Odds ratio OR=2.787, P=0.004).ConclusionsTreatment-related pneumonitis, especially RRP, is acceptable and manageable in the setting of TRT followed by ICI in this Asian population. Dosimetric parameters MLD, V5 and V20 may improve the predictions of RRP in clinical practice.

Project description:Previous studies have suggested that DNA double-strand break (DSB) repair is an important protective pathway after damage. The ataxia telangiectasia mutated (ATM) gene plays an important role in the DNA DSB repair pathway. DNA damage is a major cytotoxic effect that can be caused by radiation, and the ability to repair DNA after damage varies among different tissues. Impaired DNA repair pathways are associated with high sensitivity to radiation exposure. Hence, ATM gene polymorphisms are thought to influence the risk of cancer and radiation-induced pneumonitis (RP) risk in cancer patients treated with radiotherapy. However, the results of previous studies are inconsistent. We therefore conducted this comprehensive meta-analysis.A systematic literature search was performed in the PubMed, Embase, China National Knowledge Internet (CNKI) and Wanfang databases to identify studies that investigated the association between the ATM gene polymorphisms and both lung cancer and RP radiotherapy-treated lung cancer (the last search was conducted on Dec.10, 2015). The odds ratio (OR) and 95% confidence interval (CI) were used to investigate the strength of these relationships. Funnel plots and Begg's and Egger's tests were conducted to assess the publication bias. All analyses were performed in STATA 13.0 software.Ten eligible case-control studies (4731 cases and 5142 controls) on lung cancer susceptibility and four (192 cases and 772 controls) on RP risk were included. The results of the overall and subgroup analyses indicated that in the ATM gene, the rs189037 (-111G?>?A, -4519G?>?A), rs664677 (44831C?>?T, 49238C?>?T) and rs664143 (131,717 T?>?G) polymorphisms were significantly associated with lung cancer susceptibility (OR?=?1.21, 95% CI?=?1.04-1.39, P?=?0.01; OR?=?1.26, 95% CI?=?1.06-1.49, P?=?0.01; OR?=?1.43, 95% CI?=?1.15-1.78, P?<?0.01). Additionally, the rs189037 variant was significantly associated with RP risk (OR?=?1.74, 95% CI?=?1.02-2.97, P?=?0.04). No publication bias was found in the funnel plots, Begg's tests or Egger's tests.The results indicate that the ATM rs189037, rs664677 and rs664143 gene polymorphisms are risk factors for lung cancer, while the ATM rs189037 variant was significantly associated with RP risk.

Project description:Objective The study aims to establish and validate an effective CT-based radiation pneumonitis (RP) prediction model using the multiomics method of radiomics and EQD2-based dosiomics. Materials and Methods The study performed a retrospective analysis on 91 nonsmall cell lung cancer patients who received radiotherapy from 2019 to 2021 in our hospital. The patients with RP grade ≥1 were labeled as 1, and those with RP grade < 1 were labeled as 0. The whole lung excluding clinical target volume (lung-CTV) was used as the region of interest (ROI). The radiomic and dosiomic features were extracted from the lung-CTV area's image and dose distribution. Besides, the equivalent dose of the 2 Gy fractionated radiation (EQD2) model was used to convert the physical dose to the isoeffect dose, and then, the EQD2-based dosiomic (eqd-dosiomic) features were extracted from the isoeffect dose distribution. Four machine learning (ML) models, including DVH, radiomics combined with DVH (radio + DVH), radiomics combined with dosiomics (radio + dose), and radiomics combined with eqd-dosiomics (radio + eqdose), were established to construct the prediction model via eleven different classifiers. The fivefold cross-validation was used to complete the classification experiment. The area under the curve (AUC) of the receiver operating characteristics (ROC), accuracy, precision, recall, and F1-score were calculated to assess the performance level of the prediction models. Results Compared with the DVH, radio + DVH, and radio + dose model, the value of the training AUC, accuracy, and F1-score of radio + eqdose was higher, and the difference was statistically significant (p < 0.05). Besides, the average value of the precision and recall of radio + eqdose was higher, but the difference was not statistically significant (p > 0.05). Conclusion The performance of using the ML-based multiomics method of radiomics and eqd-dosiomics to predict RP is more efficient and effective.

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A literature-based meta-analysis of clinical risk factors for development of radiation induced pneumonitis.

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A literature-based meta-analysis of clinical risk factors for development of radiation induced pneumonitis.

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