Quantifying causal effects from observed data using quasi-intervention.

BACKGROUND: Causal inference is a crucial element within medical decision-making. There have been many methods for investigating potential causal relationships between disease and treatment options developed in recent years, which can be categorized into two main types: observational studies and experimental studies. However, due to the nature of experimental studies, financial resources, human resources, and patients' ethical considerations, researchers cannot fully control the exposure of the research participants. Furthermore, most existing observational research designs are limited to determining causal relationships and cannot handle observational data, let alone determine the dosages needed for medical research. RESULTS: This paper presents a new experimental strategy called quasi-intervention for quantifying the causal effect between disease and treatment options in observed data by using a causal inference method, which converts the potential effect of different treatment options on disease into computing differences in the conditional probability. We evaluated the accuracy of the quasi-intervention by quantifying the impact of adjusting Chinese patients' neutrophil-to-lymphocyte ratio (NLR) on their overall survival (OS) (169 lung cancer patients and 79 controls).The results agree with the literature in this study, consisting of nine papers on cohort studies on the NLR and the prognosis of lung cancer patients, proving that our method is correct. CONCLUSION: Taken together, the results imply that quasi-intervention is a promising method for quantifying the causal effect between disease and treatment options without clinical trials, and it could improve confidence about treatment options' efficacy and safety.

Prediction of radiation-induced acute skin toxicity in breast cancer patients using data encapsulation screening and dose-gradient-based multi-region radiomics technique: A multicenter study.

Purpose: Radiation-induced dermatitis is one of the most common side effects for breast cancer patients treated with radiation therapy (RT). Acute complications can have a considerable impact on tumor control and quality of life for breast cancer patients. In this study, we aimed to develop a novel quantitative high-accuracy machine learning tool for prediction of radiation-induced dermatitis (grade ≥ 2) (RD 2+) before RT by using data encapsulation screening and multi-region dose-gradient-based radiomics techniques, based on the pre-treatment planning computed tomography (CT) images, clinical and dosimetric information of breast cancer patients. Methods and Materials: 214 patients with breast cancer who underwent RT between 2018 and 2021 were retrospectively collected from 3 cancer centers in China. The CT images, as well as the clinical and dosimetric information of patients were retrieved from the medical records. 3 PTV dose related ROIs, including irradiation volume covered by 100%, 105%, and 108% of prescribed dose, combined with 3 skin dose-related ROIs, including irradiation volume covered by 20-Gy, 30-Gy, 40-Gy isodose lines within skin, were contoured for radiomics feature extraction. A total of 4280 radiomics features were extracted from all 6 ROIs. Meanwhile, 29 clinical and dosimetric characteristics were included in the data analysis. A data encapsulation screening algorithm was applied for data cleaning. Multiple-variable logistic regression and 5-fold-cross-validation gradient boosting decision tree (GBDT) were employed for modeling training and validation, which was evaluated by using receiver operating characteristic analysis. Results: The best predictors for symptomatic RD 2+ were the combination of 20 radiomics features, 8 clinical and dosimetric variables, achieving an area under the curve (AUC) of 0.998 [95% CI: 0.996-1.0] and an AUC of 0.911 [95% CI: 0.838-0.983] in the training and validation dataset, respectively, in the 5-fold-cross-validation GBDT model. Meanwhile, the top 12 most important characteristics as well as their corresponding importance measures for RD 2+ prediction in the GBDT machine learning process were identified and calculated. Conclusions: A novel multi-region dose-gradient-based GBDT machine learning framework with a random forest based data encapsulation screening method integrated can achieve a high-accuracy prediction of acute RD 2+ in breast cancer patients.

Tomotherapy as a neoadjuvant treatment for locally advanced esophageal cancer might increase bone marrow toxicity in comparison with intensity-modulated radiotherapy and volumetric-modulated arc therapy.

This study compares dosimetric parameters in these following 3 neoadjuvant chemoradiotherapy (NCRT) methods in treating locally advanced esophagus cancer: helical tomotherapy (TOMO), volumetric modulated arc therapy (VMAT), and intensity-modulated radiotherapy (IMRT). It is aimed to ascertain the efficient technique that kept high target coverage and availed the dose sparing of bone marrow (BM). This research collected data on 11 patients from October 2014 to June 2017 who received NCRT for pathologically confirmed esophageal cancer. The prescription doses to the planning target volume (PTV) were all given as 60 Gy (2 Gy per fraction, 5 days a week). Three physicists via Varian Eclipse Treatment Planning System and Accuray planning stations redesigned 5 radiotherapy plans (fixed 5-field IMRT, fixed 7-field IMRT, 2-arc VMAT, 3-arc VMAT, and TOMO) for each of the patients. At the end of the planning, we then appraised the dosimetric quality based on the PTV parameters and the doses to organs at risk (OARs). In the study VMAT reached the highest conformity index (CI; 2 arcs VMAT: 0.74 ± 0.10; 3 arcs VMAT: 0.78 ± 0.07; p< 0.05), and IMRT the lowest homogeneity index (HI; fivefields IMRT: 0.12 ± 0.03; sevenfields IMRT: 0.10 ± 0.02; p< 0.05). Besides, 7 fields IMRT (0.10 ± 0.02) achieved superior HI to that of 5 fields IMRT (0.12 ± 0.03, p< 0.01). TOMO (p< 0.05) and VMAT (p< 0.05) were both significantly superior to IMRT in terms of the dose to lung (V5, V10, V15, V20, and V30). These 5 radiation techniques were similar regarding the dose to heart (V5, V20, and V30), but IMRT (5 fields IMRT: 19.27 ± 5.33; 7 fields IMRT: 20.05 ± 4.19) significantly raised the dose to the V50 of the heart when compared to VMAT (2 arcs VMAT: 16.6 ± 5.68; 3 arcs VMAT: 15.04 ± 5.75; p< 0.05) and TOMO (15.05 ± 4.7, p< 0.05). VMAT reduced the dose to BM (V5, V10, V20, and V30) as compared to TOMO (p< 0.05) and IMRT (p< 0.05). The CI of VMAT was the supreme one in those of the techniques in this study, so was the HI of IMRT. VMAT also provided another advantage that it reduced the dose to the BM. TOMO ameliorated the dose sparing of the lung, but the dose that the BM absorbed from TOMO was of some concern about BM toxicity.

Radiation-induced muscle fibrosis rat model: establishment and valuation.

BACKGROUND: Lack of animal model of radiation induced muscle fibrosis, this study aimed to establish such a model by using 90 Gy single dose irradiation to mimic clinical relevance and also to explore the potential post-irradiation regenerative mechanism. METHODS: SD rats were randomly divided into dose investigation groups and time gradient groups. Group1-6 were irradiated with a single dose of 65Gy, 70Gy, 75Gy, 80Gy, 85Gy and 90Gy respectively, and the degree of rectus femoris fibrosis in the irradiated area was detected at 4 weeks after irradiation. Group 7-9 were irradiated with a single dose of 90Gy, and the results were detected 1, 2, 4, and 8 weeks after irradiation. Then the general condition of rats was recorded. Masson staining was used to detect muscle fibrosis. The ultrastructure of muscles was observed by electron microscope, and the expression changes of satellite cell proliferation and differentiation related genes were detected by quantitative real-time-PCR. RESULTS: A single dose of 90Gy irradiation could cause muscle fibrosis in rats. As time goes on, the severity of muscle fibrosis and the expression of TGF- ß1 increased. Significant swelling of mitochondria, myofilament disarrangement and dissolution, obvious endothelial cell swelling, increased vascular permeability, decrease of blood cell, deposition of fibrosis tissue around the vessel could be found compared with the control group. At around the 4th week, the expressions of Pax7, Myf5, MyoD, MyoG, Mrf4 increased. CONCLUSION: Irradiation of 90Gy can successfully establish the rat model of radiation-induced muscle fibrosis. This model demonstrated that regenerative process was initiated by the irradiation only at an early stage, which can serve a suitable model for investigating regenerative therapy for post-radiation muscle fibrosis.

BPIFB1 (LPLUNC1) inhibits radioresistance in nasopharyngeal carcinoma by inhibiting VTN expression.

Bactericidal/permeability-increasing-fold-containing family B member 1 (BPIFB1, previously named LPLUNC1) is highly expressed in the nasopharynx and significantly downregulated in nasopharyngeal carcinoma (NPC). Low expression is also associated with poor prognosis in patients with NPC. Radiotherapy is a routine treatment for NPC; however, radioresistance is a major cause of treatment failure. Thus, we aimed to investigate the role of BPIFB1 in the radioresponse of NPC. Colony formation and cell survival results showed that BPIFB1 sensitized NPC cells to ionizing radiation. VTN, a previously identified BPIFB1-binding protein, was shown to induce cell proliferation and survival, G2/M phase arrest, DNA repair, activation of the ATM-Chk2 and ATR-Chk1 pathways, and anti-apoptotic effects after exposure to radiation, facilitating NPC cell radioresistance. However, BPIFB1 inhibited this VTN-mediated radioresistance, ultimately improving NPC radiosensitivity. In conclusion, this study is the first to demonstrate the functions of BPIFB1 and VTN in the NPC radioresponse. Our findings indicated that promoting BPIFB1 expression and targeting VTN might represent new therapeutic strategies for NPC.

Long non-coding RNA PVT1 predicts poor prognosis and induces radioresistance by regulating DNA repair and cell apoptosis in nasopharyngeal carcinoma.

The long non-coding RNA, plasmacytoma variant translocation 1 (PVT1), is highly expressed in a variety of tumors, and is believed to be a potential oncogene. However, the role and mechanism of action of PVT1 in the carcinogenesis and progression of nasopharyngeal carcinomas (NPCs) remains unclear. In this study, for the first time, we have discovered that PVT1 shows higher expression in NPCs than in normal nasopharyngeal epithelial tissue, and patients with NPCs who show higher expression of PVT1 have worse progression-free and overall survivals. Additionally, we observed that the proliferation of NPC cells decreased, and their rate of apoptosis increased; these results indicated that the knockdown of PVT1 expression in the NPC cells induced radiosensitivity. Further, we have shown that the knockdown of PVT1 expression can induce apoptosis in the NPC cells by influencing the DNA damage repair pathway after radiotherapy. In general, our study shows that PVT1 may be a novel biomarker for prognosis and a new target for the treatment of NPCs. Additionally, targeting PVT1 may be a potential strategy for the clinical management of NPC and for the improvement of the curative effect of radiation in NPCs.