Dataset Information

Dosimetry of the brain and hypothalamus predicting acute lymphopenia and the survival of glioma patients with postoperative radiotherapy.

ABSTRACT:

Background

The aim of this study was to investigate dosimetric factors for predicting acute lymphopenia and the survival of glioma patients with postoperative intensity-modulated radiotherapy (IMRT).

Methods

A total of 148 glioma patients were reviewed. Acute lymphopenia was defined as a peripheral lymphocyte count (PLC) lower than 1.0 × 10⁹ /L during radiotherapy with a normal level at pretreatment. PLCs with the corresponding dates and dose volume histogram parameters were collected. Univariate and multivariate Cox regression analyses were constructed to assess the significance of risk factors associated with lymphopenia and overall survival (OS).

Results

Sixty-nine (46.6%) patients developed lymphopenia during radiotherapy. Multivariate analyses revealed that the risk increased with the maximal dose of the hypothalamus (HT Dmax) ?56 Gy (58.9% vs 28.5%, P = 0.002), minimal dose of the whole brain (WB Dmin) ?2 Gy (54.3% vs 33.9%, P = 0.006), or mean dose of the WB (WB Dmean) ?34 Gy (56.0% vs 37.0%, P = 0.022). Patients with older age, high-grade glioma, development of lymphopenia, high HT Dmax, WB Dmin, and WB Dmean had significantly inferior OS in the multivariate analyses.

Conclusions

HT Dmax, WB Dmin, and WB Dmean are promising indicators of lymphopenia and the survival of glioma patients undergoing postoperative IMRT. The necessity and feasibility of dosimetric constraints for HT and WB is warranted with further investigation.

SUBMITTER: Ye LL

PROVIDER: S-EPMC6558490 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

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Publications

Dosimetry of the brain and hypothalamus predicting acute lymphopenia and the survival of glioma patients with postoperative radiotherapy.

Ye Lu-Lu LL Fan Xing-Wen XW Hu Chao-Su CS He Xia-Yun XY Wang Xiao-Shen XS Shen Chun-Ying CY Xu Ting-Ting TT Ying Hong-Mei HM

Cancer medicine 20190414 6

<h4>Background</h4>The aim of this study was to investigate dosimetric factors for predicting acute lymphopenia and the survival of glioma patients with postoperative intensity-modulated radiotherapy (IMRT).<h4>Methods</h4>A total of 148 glioma patients were reviewed. Acute lymphopenia was defined as a peripheral lymphocyte count (PLC) lower than 1.0 × 10<sup>9</sup> /L during radiotherapy with a normal level at pretreatment. PLCs with the corresponding dates and dose volume histogram parameters ...[more]

PMID: 30983159

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Project description:BackgroundBreast cancer is one of the most common cancer in women and a proportion of patients experiences brain metastases with poor prognosis. The study aimed to construct a novel predictive clinical model to evaluate the overall survival (OS) of patients with postoperative brain metastasis of breast cancer (BCBM) and validate its effectiveness.MethodsFrom 2010 to 2020, a total of 310 female patients with BCBM were diagnosed in The Affiliated Cancer Hospital of Xinjiang Medical University, and they were randomly assigned to the training cohort and the validation cohort. Data of another 173 BCBM patients were collected from the Surveillance, Epidemiology, and End Results Program (SEER) database as an external validation cohort. In the training cohort, the least absolute shrinkage and selection operator (LASSO) Cox regression model was used to determine the fundamental clinical predictive indicators and the nomogram was constructed to predict OS. The model capability was assessed using receiver operating characteristic, C-index, and calibration curves. Kaplan-Meier survival analysis was performed to evaluate clinical effectiveness of the risk stratification system in the model. The accuracy and prediction capability of the model were verified using the validation and SEER cohorts.ResultsLASSO Cox regression analysis revealed that lymph node metastasis, molecular subtype, tumor size, chemotherapy, radiotherapy, and lung metastasis were statistically significantly correlated with BCBM. The C-indexes of the survival nomogram in the training, validation, and SEER cohorts were 0.714, 0.710, and 0.670, respectively, which showed good prediction capability. The calibration curves demonstrated that the nomogram had great forecast precision, and a dynamic diagram was drawn to increase the maneuverability of the results. The Risk Stratification System showed that the OS of low-risk patients was considerably better than that of high-risk patients ( P < 0.001).ConclusionThe nomogram prediction model constructed in this study has a good predictive value, which can effectively evaluate the survival rate of patients with postoperative BCBM.

Dataset Information

Dosimetry of the brain and hypothalamus predicting acute lymphopenia and the survival of glioma patients with postoperative radiotherapy.

Background

Methods

Results

Conclusions

Publications

Dosimetry of the brain and hypothalamus predicting acute lymphopenia and the survival of glioma patients with postoperative radiotherapy.

Similar Datasets

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