A model combining age, equivalent uniform dose and IL-8 may predict radiation esophagitis in patients with non-small cell lung cancer.
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ABSTRACT:
SUBMITTER: Wang S
PROVIDER: S-EPMC5874799 | biostudies-literature | 2018 Mar
REPOSITORIES: biostudies-literature
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A model combining age, equivalent uniform dose and IL-8 may predict radiation esophagitis in patients with non-small cell lung cancer.
Wang Shulian S Campbell Jeff J Stenmark Matthew H MH Stanton Paul P Zhao Jing J Matuszak Martha M MM Ten Haken Randall K RK Kong Feng-Ming FM
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology 20180301 3
<h4>Background and purpose</h4>To study whether cytokine markers may improve predictive accuracy of radiation esophagitis (RE) in non-small cell lung cancer (NSCLC) patients.<h4>Materials and methods</h4>A total of 129 patients with stage I-III NSCLC treated with radiotherapy (RT) from prospective studies were included. Thirty inflammatory cytokines were measured in platelet-poor plasma samples. Logistic regression was performed to evaluate the risk factors of RE. Stepwise Akaike information cri ...[more]
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Project description:PurposeTo demonstrate the use of generalized equivalent uniform dose (gEUD) atlas for data pooling in radiation pneumonitis (RP) modeling, to determine the dependence of RP on gEUD, to study the consistency between data sets, and to verify the increased statistical power of the combination.Methods and materialsPatients enrolled in prospective phase I/II dose escalation studies of radiation therapy of non-small cell lung cancer at Memorial Sloan-Kettering Cancer Center (MSKCC) (78 pts) and the Netherlands Cancer Institute (NKI) (86 pts) were included; 10 (13%) and 14 (17%) experienced RP requiring steroids (RPS) within 6 months after treatment. gEUD was calculated from dose-volume histograms. Atlases for each data set were created using 1-Gy steps from exact gEUDs and RPS data. The Lyman-Kutcher-Burman model was fit to the atlas and exact gEUD data. Heterogeneity and inconsistency statistics for the fitted parameters were computed. gEUD maps of the probability of RPS rate≥20% were plotted.ResultsThe 2 data sets were homogeneous and consistent. The best fit values of the volume effect parameter a were small, with upper 95% confidence limit around 1.0 in the joint data. The likelihood profiles around the best fit a values were flat in all cases, making determination of the best fit a weak. All confidence intervals (CIs) were narrower in the joint than in the individual data sets. The minimum P value for correlations of gEUD with RPS in the joint data was .002, compared with P=.01 and .05 for MSKCC and NKI data sets, respectively. gEUD maps showed that at small a, RPS risk increases with gEUD.ConclusionsThe atlas can be used to combine gEUD and RPS information from different institutions and model gEUD dependence of RPS. RPS has a large volume effect with the mean dose model barely included in the 95% CI. Data pooling increased statistical power.
| S-EPMC3586556 | biostudies-literature
Project description:PurposeThe study aimed to predict acute radiation esophagitis (ARE) with grade ≥ 2 for patients with locally advanced lung cancer (LALC) treated with intensity-modulated radiation therapy (IMRT) using multi-omics features, including radiomics and dosiomics.Methods161 patients with stage IIIA-IIIB LALC who received chemoradiotherapy (CRT) or radiotherapy by IMRT with a prescribed dose from 45 to 70 Gy from 2015 to 2019 were enrolled retrospectively. All the toxicity gradings were given following the Common Terminology Criteria for Adverse Events V4.0. Multi-omics features, including radiomics, dosiomics (including dose-volume histogram dosimetric parameters), were extracted based on the planning CT image and three-dimensional dose distribution. All data were randomly divided into training cohorts (N = 107) and testing cohorts (N = 54). In the training cohorts, features with reliably high outcome relevance and low redundancy were selected under random patient subsampling. Four classification models (using clinical factors (CF) only, using radiomics features (RFs) only, dosiomics features (DFs) only, and the hybrid features (HFs) containing clinical factors, radiomics and dosiomics) were constructed employing the Ridge classifier using two-thirds of randomly selected patients as the training cohort. The remaining patient was treated as the testing cohort. A series of models were built with 30 times training-testing splits. Their performances were assessed using the area under the ROC curve (AUC) and accuracy.ResultsAmong all patients, 51 developed ARE grade ≥ 2, with an incidence of 31.7%. Next, 8990 radiomics and 213 dosiomics features were extracted, and 3, 6, 12, and 13 features remained after feature selection in the CF, DF, RF and DF models, respectively. The RF and HF models achieved similar classification performance, with the training and testing AUCs of 0.796 ± 0.023 (95% confidence interval (CI [0.79, 0.80])/0.744 ± 0.044 (95% CI [0.73, 0.76]) and 0.801 ± 0.022 (95% CI [0.79, 0.81]) (p = 0.74), respectively. The model performances using CF and DF features were poorer, with training and testing AUCs of 0.573 ± 0.026 (95% CI [0.56, 0.58])/ 0.509 ± 0.072 (95% CI [0.48, 0.53]) and 0.679 ± 0.027 (95% CI [0.67, 0.69])/0.604 ± 0.041 (95% CI [0.53, 0.63]) compared with the above two models (p < 0.001), respectively.ConclusionsIn LALC patients treated with CRT IMRT, the ARE grade ≥ 2 can be predicted using the pretreatment radiotherapy image features. To predict ARE, the multi-omics features had similar predictability with radiomics features; however, the dosiomics features and clinical factors had a limited classification performance.
| S-EPMC10024847 | biostudies-literature
Project description:PurposeTo examine the equivalent uniform dose (EUD) formalism using the universal survival curve (USC) applicable to high-dose stereotactic body radiotherapy (SBRT).Materials and methodsFor nine non-small-cell carcinoma cell (NSCLC) lines, the linear-quadratic (LQ) and USC models were used to calculate the EUD of a set of hypothetical two-compartment tumor dose-volume histogram (DVH) models. The dose was varied by ±5%, ±10%, and ±20% about the prescription dose (60 Gy/3 fractions) to the first compartment, with fraction volume varying from 1% and 5% to 30%. Clinical DVHs of 21 SBRT treatments of NSCLC prescribed to the 70-83% isodose lines were also considered. The EUD of non-standard SBRT dose fractionation (EUDSBRT) was further converted to standard fractionation of 2 Gy (EUDCFRT) using the LQ and USC models to facilitate comparisons between different SBRT dose fractionations. Tumor control probability (TCP) was then estimated from the LQ- and USC-EUDCFRT.ResultsFor non-standard SBRT fractionation, the deviation of the USC- from the LQ-EUDSBRT is largely limited to 5% in the presence of dose variation up to ±20% to fractional tumor volume up to 30% in all NSCLC cell lines. Linear regression with zero constant yielded USC-EUDSBRT = 0.96 × LQ-EUDSBRT (r2 = 0.99) for the clinical DVHs. Converting EUDSBRT into standard 2‑Gy fractions by the LQ formalism produced significantly larger EUDCFRT than the USC formalism, particularly for low [Formula: see text] ratios and large fraction dose. Simplified two-compartment DVH models illustrated that both the LQ- and USC-EUDCFRT values were sensitive to cold spot below the prescription dose with little volume dependence. Their deviations were almost constant for up to 30% dose increase above the prescription. Linear regression with zero constant yielded USC-EUDCFRT = 1.56 × LQ-EUDCFRT (r2 = 0.99) for the clinical DVHs. The clinical LQ-EUDCFRT resulted in median TCP of almost 100% vs. 93.8% with USC-EUDCFRT.ConclusionA uniform formalism of EUD should be defined among the SBRT community in order to apply it as a single metric for dose reporting and dose-response modeling in high-dose-gradient SBRT because its value depends on the underlying cell survival model and the model parameters. Further investigations of the optimal formalism to derive the EUD through clinical correlations are warranted.
| S-EPMC8219592 | biostudies-literature
Project description:BackgroundWe developed a novel concept, equivalent uniform length (EUL), to describe the relationship between the generalized equivalent uniform dose (EUD) and the geometric anatomy around a tumor target. By correlating EUL with EUD, we established two EUD-EUL knowledge-based (EEKB) prediction models for the bladder and rectum that predict initial EUD values for generating quality treatment plans.MethodsEUL metrics for the rectum and bladder were extracted and collected from the intensity-modulated radiotherapy therapy (IMRT) plans of 60 patients with cervical cancer. The two EEKB prediction models were built using linear regression to establish the relationships between EULr and EUDr (EUL and EUD of rectum) and EULb, and EUDb (EUL and EUD of bladder), respectively. The EE plans were optimized by incorporating the predicted initial EUD parameters for the rectum and bladder with the conventional pinnacle auto-planning (PAP) initial dose parameters for other organs. The efficiency of the predicted initial EUD values were then evaluated by comparing the consistency and quality of the EE plans, PAP plans (based on default PAP initial parameters), and manual plans (designed manually by different dosimetrists) for a sample of 20 patients.ResultsLinear regression analyses showed a significant correlation between EUL and EUD (R2 = 0.79 and 0.69 for EUDb and EUDr, respectively). In a sample of 20 patients, the average bladder V40 and V50 derived from the EE plans were significantly lower (V40: 30.00 ± 5.76, V50: 14.36 ± 4.00) than the V40 and V50 values derived from manual plans (V40: 36.03 ± 8.02, V50: 19.02 ± 5.42). Compared with the PAP plans, the EE plans produced significantly lower average V30 and Dmean values for the bladder (V30: 50.55 ± 6.33, Dmean: 31.48 ± 1.97 Gy).ConclusionsOur EEKB prediction models predicted reasonable initial EUD values for the rectum and bladder based on patient-specific geometric EUL values, thereby improving optimization and planning efficiency.
| S-EPMC9426003 | biostudies-literature
Project description:We describe a way to include biologically based objectives in plan optimization specific for carbon ion therapy, beyond the standard voxel-dose-based criteria already implemented in TRiP98, research planning software for ion beams. The aim is to account for volume effects-tissue architecture-dependent response to damage-in the optimization procedure, using the concept of generalized equivalent uniform dose (gEUD), which is an expression to convert a heterogeneous dose distribution (e.g., in an organ at risk (OAR)) into a uniform dose associated with the same biological effect. Moreover, gEUD is closely related to normal tissue complication probability (NTCP). The multi-field optimization problem here takes also into account the relative biological effectiveness (RBE), which in the case of ion beams is not factorizable and introduces strong non-linearity. We implemented the gEUD-based optimization in TRiP98, allowing us to control the whole dose-volume histogram (DVH) shape of OAR with a single objective by adjusting the prescribed gEUD 0 and the volume effect parameter a, reducing the volume receiving dose levels close to mean dose when a = 1 (large volume effect) while close to maximum dose for a >> 1 (small volume effect), depending on the organ type considered. We studied the role of gEUD 0 and a in the optimization, and we compared voxel-dose-based and gEUD-based optimization in chordoma cases with different anatomies. In particular, for a plan containing multiple OARs, we obtained the same target coverage and similar DVHs for OARs with a small volume effect while decreasing the mean dose received by the proximal parotid, thus reducing its NTCP by a factor of 2.5. Further investigations are done for this plan, considering also the distal parotid gland, obtaining a NTCP reduction by a factor of 1.9 for the proximal and 2.9 for the distal one. In conclusion, this novel optimization method can be applied to different OARs, but it achieves the largest improvement for organs whose volume effect is larger. This allows TRiP98 to perform a double level of biologically driven optimization for ion beams, including at the same time RBE-weighted dose and volume effects in inverse planning. An outlook is presented on the possible extension of this method to the target.
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Project description:Radiation-induced esophagitis is the most common local acute toxicity of radiotherapy (RT) delivered for the curative or palliative intent treatment of lung cancer. Although concurrent chemotherapy and higher RT dose are associated with increased esophagitis risk, advancements in RT techniques as well as adherence to esophageal dosimetric constraints may reduce the incidence and severity. Mild acute esophagitis symptoms are generally self-limited, and supportive management options include analgesics, acid suppression, diet modification, treatment for candidiasis, and maintenance of adequate nutrition. Esophageal stricture is the most common late sequela from esophageal irradiation and can be addressed with endoscopic dilatation. Approaches to prevent or mitigate these toxicities are also discussed.
| S-EPMC5310706 | biostudies-other
Project description:PurposeThis study aimed to examine the effect of radiation esophagitis (RE) and the dynamics of RE on subsequent survival in non-small cell lung cancer (NSCLC) patients who underwent radiotherapy.Experimental designPatients with NSCLC treated with fractionated thoracic radiotherapy enrolled in prospective trials were eligible. RE was graded prospectively according to Common Terminology Criteria for Adverse Events (CTCAE) v3.0 per protocol requirement weekly during-RT and 1 month after RT. This study applied conditional survival assessment which has advantage over traditional survival analysis as it assesses the survival from the event instead of from the baseline. P-value less than 0.05 was considered to be significant. The primary endpoint is overall survival.ResultsA total of 177 patients were eligible, with a median follow-up of 5 years. The presence of RE, the maximum RE grade, the evolution of RE and the onset timing of RE events were all correlated with subsequent survival. At all conditional time points, patients first presented with RE grade1 (initial RE1) had significant inferior subsequent survival (multivariable HRs median: 1.63, all P-values<0.05); meanwhile those with RE progressed had significant inferior subsequent survival than those never develop RE (multivariable HRs median: 2.08, all P-values<0.05). Multivariable Cox proportional-hazards analysis showed significantly higher C-indexes for models with inclusion of RE events than those without (all P-values<0.05).ConclusionThis study comprehensively evaluated the impact of RE with conditional survival assessment and demonstrated that RE is associated with inferior survival in NSCLC patients treated with RT.
| S-EPMC11256695 | biostudies-literature
Project description:The aim of our study is to characterize the risk of radiation-induced esophagitis (RE) in a cohort of Non-Small-Cell Lung Cancer (NSCLC) patients treated with concurrent chemotherapy and photon/proton therapy. For each patient, the RE was graded according to the CTCAE v.3. The esophageal dose-volume histograms (DVHs) were extracted. Voxel-based analyses (VBAs) were performed to assess the spatial patterns of the dose differences between patients with and without RE of grade ≥ 2. Two hierarchical NTCP models were developed by multivariable stepwise logistic regression based on non-dosimetric factors and on the DVH metrics for the whole esophagus and its anatomical subsites identified by the VBA. In the 173 analyzed patients, 76 (44%) developed RE of grade ≥ 2 at a median follow-up time of 31 days. The VBA identified regions of significant association between dose and RE in a region encompassing the thoracic esophagus. We developed two NTCP models, including the RT modality and a dosimetric factor: V55Gy for the model related to the whole esophagus, and the mean dose for the model designed on the thoracic esophagus. The cross-validated performance showed good predictions for both models (ROC-AUC of 0.70 and 0.73, respectively). The only slight improvement provided by the analysis of the thoracic esophageal subsites might be due to the relevant sparing of cervical and lower thoracic esophagus in the analyzed cohort. Further studies on larger cohorts and a more heterogeneous set of dose distributions are needed to validate these preliminary findings and shed further light on the spatial patterns of RE development.
| S-EPMC8997452 | biostudies-literature
Project description:Purpose and objectivesWe previously reported that the combination of mean lung dose (MLD) and inflammatory cytokines interleukin-8 (IL-8) and transforming growth factor-β1 (TGF-β1) may provide a more accurate model for radiation-induced lung toxicity (RILT) prediction in 58 patients with non-small cell lung cancer (NSCLC). This study is to validate the previous findings with new patients and to explore new models with more cytokines.Methods and materialsOne hundred forty-two patients with stage I-III NSCLC treated with definitive radiation therapy (RT) from prospective studies were included. Sixty-five new patients were used to validate previous findings, and all 142 patients were used to explore new models. Thirty inflammatory cytokines were measured in plasma samples before RT and 2 weeks and 4 weeks during RT (pre, 2w, 4w). Grade ≥2 RILT was defined as grade 2, and higher radiation pneumonitis or symptomatic pulmonary fibrosis was the primary endpoint. Logistic regression was performed to evaluate the risk factors of RILT. The area under the curve (AUC) for the receiver operating characteristic curves was used for model assessment.ResultsSixteen of 65 patients (24.6%) experienced RILT2. Lower pre IL-8 and higher TGF-β1 2w/pre ratio were associated with higher risk of RILT2. The AUC increased to 0.73 by combining MLD, pre IL-8, and TGF-β1 2w/pre ratio compared with 0.61 by MLD alone to predict RILT. In all 142 patients, 29 patients (20.4%) experienced grade ≥2 RILT. Among the 30 cytokines measured, only IL-8 and TGF-β1 were significantly associated with the risk of RILT2. MLD, pre IL-8 level, and TGF-β1 2w/pre ratio were included in the final predictive model. The AUC increased to 0.76 by combining MLD, pre IL-8, and TGF-β1 2w/pre ratio compared with 0.62 by MLD alone.ConclusionsWe validated that a combination of mean lung dose, pre IL-8 level, and TGF-β1 2w/pre ratio provided a more accurate model to predict the risk of RILT2 compared with MLD alone.
| S-EPMC5465602 | biostudies-literature
Project description:Patients with cardiovascular comorbidity are less tolerant to cardiotoxic drugs and should be treated with reduced doses to prevent cardiotoxicity. However, the safe-equivalent dose of antitumor drugs in patients with cardiovascular disease/risk is difficult to predict because they are usually excluded from clinical trials as a result of ethical considerations. In this study, a translational quantitative system pharmacology-pharmacokinetic-pharmacodynamic (QSP-PK-PD) model was developed based on preclinical study to predict the safe-equivalence dose of doxorubicin in patients with or without cardiovascular disease. Virtual clinical trials were conducted to validate the translational QSP-PK-PD model. The model replicated several experimental and clinical observations: the left ventricular ejection fraction (LVEF) was reduced and the left ventricular end-diastolic volume (LVEDV) was elevated in systolic dysfunction rats, the LVEF was preserved and LVEDV reduced in diastolic dysfunction rats, and patients with preexisting cardiovascular disease were more vulnerable to doxorubicin-induced cardiac dysfunction than cardiovascular healthy patients. A parameter sensitivity analysis showed that doxorubicin-induced cardiovascular dysfunction was mainly determined by the sensitivity of cardiomyocytes to cardiotoxic drugs and the baseline value of LVEDV, reflected in LVEF change percentage from the baseline. Blood pressure was the least sensitive factor affecting doxorubicin-induced cardiotoxicity.
| S-EPMC8673998 | biostudies-literature