Dataset Information

Predicting the survival of patients with bone metastases treated with radiation therapy: a validation study of the Katagiri scoring system.

ABSTRACT:

Background

The selection of radiation therapy dose fractionation schedules for bone metastases is often based on the estimation of life expectancy. Therefore, accurate prognosis prediction is an important issue. It is reported that the Katagiri scoring system can be used to predict the survival of patients with bone metastases. We aimed to assess prognostic factors and validate the Katagiri scoring system in patients who were treated with radiation therapy for bone metastases.

Materials/methods

We retrospectively reviewed data of all patients who were treated with radiation therapy for bone metastases between 2004 and 2013. Age, sex, Karnofsky performance status (KPS), Eastern Cooperative Oncology Group performance status (ECOG PS), primary site (lesions and characteristics), visceral metastases, laboratory data, previous chemotherapy, and multiple bone metastases were analyzed for associations with overall survival (OS). Katagiri scores were calculated for each patient and were used to compare OS.

Results

Out of the 616 patients included in this analysis, 574 had died and 42 remained alive. The median follow-up time for survivors was 42?months. Univariate analysis revealed that age (P?=?0.604) and multiple bone metastases (P?=?0.691) were not significantly associated with OS. Multivariate analysis revealed that sex, ECOG PS, KPS, primary characteristics, visceral metastases, laboratory data, and previous chemotherapy were significantly associated with OS. The survival rates at 3, 6, 12, and 24?months, categorized by Katagiri score, were as follows: score 0-3, 94.4, 77.8, and 61.1%, respectively; score 4-6, 67.7, 48.7, and 31.2%, respectively; and score 7-10, 39.1, 22.1, and 9.0%, respectively (P?ConclusionSex, ECOG PS, KPS, primary characteristics, visceral metastases, laboratory data, and previous chemotherapy were significant predictors of survival in patients with bone metastases. The Katagiri scoring system was significantly correlated with OS and can help us select the optimal dose-fractionation.

SUBMITTER: Kubota H

PROVIDER: S-EPMC6339356 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Predicting the survival of patients with bone metastases treated with radiation therapy: a validation study of the Katagiri scoring system.

Kubota Hikaru H Soejima Toshinori T Sulaiman Nor Shazrina NS Sekii Shuhei S Matsumoto Yoko Y Ota Yosuke Y Tsujino Kayoko K Fujita Ikuo I Fujimoto Takuya T Morishita Masayuki M Ikegaki Junichi J Matsumoto Koji K Sasaki Ryohei R

Radiation oncology (London, England) 20190118 1

<h4>Background</h4>The selection of radiation therapy dose fractionation schedules for bone metastases is often based on the estimation of life expectancy. Therefore, accurate prognosis prediction is an important issue. It is reported that the Katagiri scoring system can be used to predict the survival of patients with bone metastases. We aimed to assess prognostic factors and validate the Katagiri scoring system in patients who were treated with radiation therapy for bone metastases.<h4>Materia ...[more]

PMID: 30658673

Similar Datasets

Project description:BackgroundCurrently, locoregional therapies, such as transarterial chemoembolization (TACE) and ablation, play an important role in the treatment of Hepatocellular carcinoma (HCC). However, an easy-to-use scoring system that predicts recurrence to guide individualized management of HCC with varying risks of recurrence remains an unmet need.MethodsA total of 483 eligible HCC patients treated by TACE combined with ablation from January 1, 2017, to December 31, 2019, were included in the temporal external validation cohort and then used to explore possibilities for refinement of the original scoring system. We investigated the prognostic value of baseline variables on recurrence-free survival (RFS) using a Cox model and developed the easily applicable YA score. The performances of the original scoring system and YA score were assessed according to discrimination (area under the receiver operating curve [AUROC] and Harrell's concordance index [C-statistic]), calibration (calibration curves), and clinical utility [decision curve analysis (DCA) curves]. Finally, improvement in the ability to predict in the different scoring systems was assessed using the Net Reclassification Index (NRI). The YA score was lastly compared with other prognostic scores.ResultsDuring the median follow-up period of 35.6 months, 292 patients experienced recurrence. In the validation cohort, the original scoring system exhibited high discrimination (C-statistic: 0.695) and calibration for predicting the prognosis in HCC. To improve the prediction performance, the independent predictors of RFS, including gender, alpha-fetoprotein (AFP) and des-γ-carboxyprothrombin (DCP), tumor number, tumor size, albumin-to-prealbumin ratio (APR), and fibrinogen, were incorporated into the YA score, an improved score. Compared to the original scoring system, the YA score has better discrimination (c-statistic: 0.712VS0.695), with outstanding calibration and the clinical net benefit, both in the training and validation cohorts. Moreover, the YA score accurately stratified patients with HCC into low-, intermediate- and high-risk groups of recurrence and mortality and outperformed other prognostic scores.ConclusionYA score is associated with recurrence and survival in early- and middle-stage HCC patients receiving local treatment. Such score would be valuable in guiding the monitoring of follow-up and the design of adjuvant treatment trials, providing highly informative data for clinical management decisions.

Project description:Objective: The tumor microenvironment plays a critical role in the radiotherapy and immunotherapy response of cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC). Radioresistance is a key factor in treatment failure among patients who receive radical radiotherapy. Thus, new immune-related biomarkers associated with radiotherapy response in CESC are needed. Methods: In this study, the CIBERSORT and ESTIMATE methods were applied to determine the percentage of tumor-infiltrating cells and the number of immune components in 103 CESCs treated with radiotherapy from The Cancer Genome Atlas (TCGA) database. The main dysregulated genes were subjected to multivariate and univariate analyses. The prognostic value of this system was studied via receiver operating characteristic curve and survival analysis. For further confirmation, the biomarkers' expression levels and predictive value were validated by immunohistochemistry (IHC) and qRT-PCR. The CIBERSORT algorithm was used to calculate the compositional patterns of 22 types of immune cells in cervical cancer patients treated with radiation therapy. Results: Data for 17 radioresistant and 86 radiosensitive tumors were obtained from the The Cancer Genome Atlas database. 53 immune-related DEGs were identified. GO and KEGG analyses revealed that the DEGs were enriched in protein kinase B signaling, growth factors in cytokines, the MAPK pathway and the PI3K-Akt pathway. Then, 14 key immune-related genes built a risk scoring model were deemed prognostic in CESC with radiotherapy. The area under the curve (AUC) of the model was 0.723, and the high-risk group presented worse outcomes than the low-risk group. In addition, the high-risk group tended to have persistent tumors (p = 0.001). The high expression of WT1 and SPOUYT4 were associated with relapse, the high expression of Angiotensinogen and MIEN1 were associated with nonrelapse. Analysis of the immune microenvironment indicated that M0 macrophages, M2 macrophages, activated mast cells and resting memory CD4+ T cells were positively correlated with the risk score (p < 0.05). Conclusion: The novel immune-related risk scoring system has some advantages in predicting the prognosis and treatment response of cervical cancer patients treated with radiotherapy. Moreover, it might provide novel clues for providing targeted immune therapy to these patients.

Project description:Study designRetrospective analysis of a registered cohort of patients treated and irradiated for metastases in the spinal column in a single institute.ObjectiveThis is the first study to develop and internally validate radiomics features for predicting six-month survival probability for patients with spinal bone metastases (SBM).Background dataExtracted radiomics features from routine clinical CT images can be used to identify textural and intensity-based features unperceivable to human observers and associate them with a patient survival probability or disease progression.MethodsA study was conducted on 250 patients treated for metastases in the spinal column irradiated for the first time between 2014 and 2016, at the MAASTRO clinic in Maastricht, the Netherlands. The first 150 available patients were used to develop the model and the subsequent 100 patient were considered as a test set for the model. A bootstrap (B = 400) stepwise model selection, which combines both the forward and backward variable elimination procedure, was used to select the most useful predictive features from the training data based on the Akaike information criterion (AIC). The stepwise selection procedure was applied to the 400 bootstrap samples, and the results were plotted as a histogram to visualize how often each variable was selected. Only variables selected more than 90 % of the time over the bootstrap runs were used to build the final model.A prognostic index (PI) called radiomics score (radscore) and clinical score (clinscore) was calculated for each patient. The prognostic index was not scaled, the original values were used which can be extracted from the model directly or calculated as a linear combination of the variables in the model multiplied by the respective beta value for each patient.ResultsThe clinical model had a good discrimination power. The radiomics model, on the other hand, had an inferior performance with no added predictive power to the clinical model. The internal imaging characteristics do not seem to have a value in the prediction of survival. However, the Shape features were excluded from further analyses in our study since all biopsies had a standard shape hence no variability.

Project description:PurposeOur purpose was to develop predictive nomograms for overall survival (OS), progression-free survival (PFS), and time-to-progression (TTP) at 5 years in patients with early-stage non-small cell lung cancer (ES-NSCLC) treated with stereotactic ablative radiation therapy (SABR).Methods and materialsThe study cohort included 714 ES-NSCLC patients treated with SABR from 2004-2015 with median follow-up of 59 months, divided into training and testing sets (8:2), with the former used for nomogram development. The least absolute shrinkage and selection operator were initially employed to screen for predictors of OS, PFS, and TTP, and identified predictors were subsequently applied toward Cox proportional hazards regression modeling. Significant predictors (P < .05) on multivariable regression were then used to develop nomograms, which were validated via evaluation of concordance indexes (C-index) and calibration plots. Finally, Kaplan-Meier method and Gray's test were employed to compare and confirm differences in outcomes among various groups and explore prognostic factors associated with local versus distant disease progression.ResultsSignificant predictors of both OS and PFS at 5 years included age, sex, Charlson comorbidity index, diffusing capacity of carbon monoxide, systemic immune-inflammation index, and tumor size (P ≤ .01 for all). Eastern Cooperative Oncology Group performance status predicted for OS as well (P = .01), and both tumor size (P < .01) and minimum biological equivalent dose to 95% of planning target volume (PTV D95 BED10; P < .01) were predictive of TTP. The C-indexes for the OS, PFS, and TTP nomograms were 0.73, 0.68, and 0.60 in the training data set and 0.72, 0.66, and 0.59 in the testing data set, respectively. Tumor size > 2.45 cm and PTV D95 BED10 < 113 Gy were significantly associated with both local and distant progression.ConclusionsThese prognostic nomograms can accurately predict for OS, PFS, and TTP at 5 years after SABR for ES-NSCLC and may thus help identify high-risk patients who could benefit from additional systemic therapy.

Project description:PurposeGuidelines recommend short-course (≤10 fractions) external-beam radiation therapy (EBRT) for bone metastases. Stereotactic body radiation therapy (SBRT) may also improve outcomes; however, routine use is not recommended outside clinical trials. We assessed national radiation therapy trends in complex techniques for bone metastases and associated expenditures.Methods and materialsUsing a claims-based Medicare data set covering 84% of beneficiaries, we assessed the relative proportion of all radiation episodes represented by bone metastases. We then evaluated use of short-course and long-course (>10 fractions) EBRT, intensity modulated radiation therapy (IMRT), and SBRT for bone metastases in hospital-affiliated outpatient (OPD) or freestanding (FREE) facilities. We assessed differences using χ2d or Wilcoxon rank sum tests for categorical and continuous variables, respectively. We identified associations with modality, fractionation, and expenditures using multivariable logistic/linear regression.ResultsAmong 467,781 radiation episodes for 17 cancer diagnoses, the overall proportion of episodes dedicated to bone metastases (9.4%) was stable from 2015 to 2017, although treatments were increasing in the hospital-affiliated outpatient setting (P < .005). We identified 40,993 episodes for bone metastases, of which 63% were short-course EBRT, 24% were long-course EBRT, 7% were SBRT, and 6% were IMRT. Techniques more common in the hospital-affiliated outpatient setting included short-course EBRT (OPD, 69%, vs FREE, 56%) and SBRT (OPD, 9%, vs FREE, 5%). Techniques more common among free-standing centers included long-course EBRT (OPD, 19%, vs FREE, 31%) and IMRT (OPD, 4%, vs FREE, 9%). From 2015 to 2017, long-course EBRT decreased by an absolute 8%; short-course EBRT, SBRT, and IMRT increased by 4%, 2.5%, and 1%, respectively. The SBRT/IMRT uptake did not differ by setting (P = .4). Differences in expenditures between SBRT and short-course EBRT decreased by a relative 8% in professional and 12% in technical fees.ConclusionsApproximately 1 in 4 patients received long-course EBRT, with small reductions in use largely replaced by complex treatment modalities. However, expenditures for complex modalities also decreased over time. As alternative payment models take effect, quality metrics are needed to ensure appropriate, effective, and safe delivery of complex technologies.

Dataset Information

Predicting the survival of patients with bone metastases treated with radiation therapy: a validation study of the Katagiri scoring system.

Background

Materials/methods

Results

Publications

Predicting the survival of patients with bone metastases treated with radiation therapy: a validation study of the Katagiri scoring system.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets