Effects of Radiotherapy for Brain Metastases on Quality of Life (QoL)

Steinmann, Diana; Schäfer, C.; Oorschot, Birgitt van; Wypior, Hans-Joachim; Bruns, Frank; Bölling, Tobias; Sehlen, Susanne; Hagg, Juliane; Bayerl, Anja; Geinitz, Hans; Hipp, Matthias; Vordermark, Dirk

doi:10.1007/s00066-009-1904-0

Cited by 59 publications

(66 citation statements)

References 24 publications

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“…This finding was also observed in the study by Steinmann et al, which employed the QLQ-BN20 in conjunction with either the QLQ-C15-PAL or the QLQ-C30 to assess QOL in patients with brain metastases [21]. The present study additionally draws attention to the potential psychological implication of this finding as future uncertainty was found to negatively correlate with overall QOL before and 1 month after treatment.…”

Section: Discussionsupporting

confidence: 85%

“…While the QLQ-BN20 and QLQ-C30 used in this study provide a comprehensive overview of QOL, the task of completing 50 questionnaire items can be quite arduous for patients with poor performance status and mental status. In the multicentre pilot study by Steinmann et al, examining the effects of radiotherapy for brain metastases on quality of life, patients were either asked to complete the QLQ-C30 or QLQ-C15-PAL in addition to the QLQ-BN20 [21]. The EORTC QLQ-C15-PAL is a 15-item version of the 30-item QLQ-C30, designed especially for palliative cancer patients with the intent of decreasing assessment burden among the advanced cancer patient population.…”

Section: Discussionmentioning

confidence: 99%

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Quality of life in patients with brain metastases using the EORTC QLQ-BN20 and QLQ-C30

et al. 2012

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Introduction Given the poor life expectancy of the majority of patients with brain metastases, quality of life (QOL) endpoints are especially valuable to assess in this population. The present study assessed QOL in patients with brain metastases before and after treatment for their disease. Methods The European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ-C30) and the EORTC Brain Cancer Module (EORTC QLQ-BN20) questionnaire were administered to assess the QOL of patients with brain metastases before and 1 month after treatment. Linear regression analysis was applied to assess changes in QOL scores over time and to examine associations between the QLQ-BN20 and QLQ-C30 scales, patient demographics and clinical variables. Associations between the QLQ-BN20 and QLQ-C30 scales were evaluated using Spearman correlation. Results There were 47 patients assessed at baseline, 31 (67%) completed follow-up at 1 month post-treatment. The majority (81%) of patients received whole-brain radiotherapy only. Future uncertainty (QLQ-BN20) and fatigue (QLQ-C30) were the most prominent symptoms at baseline. Most QLQ-BN20 and QLQ-C30 scales did not significantly change from baseline to follow-up with the exception of hair loss (p00.0004) and itchy skin (p<0.0001), which worsened post-treatment. Baseline KPS was positively correlated with QLQ-C30 physical functioning scale but negatively correlated to QLQ-BN20 motor dysfunction (p 00.016), hair loss (p00.013) and leg weakness (p00.015) as well as QLQ-C30 pain (p00.042) and appetite loss (p00.030). Conclusion The maintenance of nearly all QOL scores 1 month after treatment indicates the treatment intervention likely played a symptom-stabilizing role and prevented QOL deterioration in the palliative setting.

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Section: Discussionsupporting

confidence: 85%

Section: Discussionmentioning

confidence: 99%

Quality of life in patients with brain metastases using the EORTC QLQ-BN20 and QLQ-C30

et al. 2012

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“…As we have demonstrated, content validation of the EORTC QLQ-BN20+2 when used concurrently with the EORTC QLQ-C15-PAL for patients with brain metastases, these two QOL tools should be used in future clinical trials involving these patients. 14 Have you had difficulty in concentrating on things, like reading a newspaper or watching television?…”

Section: Resultsmentioning

confidence: 99%

“…The use of the EORTC QLQ-BN20+2 with the QLQ-C15-PAL to assess QOL was first reported in 108 patients undergoing various treatments for brain metastases [19]. The questionnaires showed maintenance (no deterioration) of QOL and improvement in a few QOL scores, which was echoed by a study that used the QLQ-BN20 with the QLQ-C15-PAL to reduce patient burden [14]. It was suggested that these two questionnaires replace the use of the QLQ-BN20 and QLQ-C30 combination previously used in many brain metastases studies in order to decrease attrition rates.…”

Section: Discussionmentioning

confidence: 99%

“…Studies of patients with brain metastases continue to use the lengthy QLQ-C30 along with the QLQ-BN20 as there is no tool that has been validated specifically for use in this patient population [14][15][16][17]. A previous study assessed QOL in patients with brain metastases prior to and after treatment by administering the QLQ-C15-PAL with the QLQ-BN20+2, a version of the QLQ-BN20 questionnaire with two additional questions to assess cognitive function [18].…”

Section: Introductionmentioning

confidence: 99%

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Content validation of the EORTC QLQ-BN20+2 with patients and health care professionals to assess quality of life in brain metastases

et al. 2012

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Objective The validated EORTC quality of life (QOL) questionnaire QLQ-BN20 is a cancer subtype-specific supplement to the QLQ-C30 general QOL questionnaire for patients with primary brain neoplasms. The QLQ-C15-PAL core palliative questionnaire is an abbreviated version of the QLQ-C30 designed to decrease patient burden. We conducted content validation of the QLQ-BN20+2 for patients with brain metastases. Methods and materials Patients undergoing treatment for brain metastases, along with health care professionals (HCPs) completed the QLQ-C15-PAL and QLQ-BN20+2 questionnaires. A structured interview followed to assess for any difficulties with the QLQ-BN20+2, irrelevant items, and whether additional pertinent items should be included. Results Seventy-four patients and 71 HCPs participated. The majority of patients (84 %) were treated with whole-brain radiotherapy only. Over 50 % of patients felt that seizures, hair loss and trouble controlling bladder were not related to brain metastases. Questions regarding uncertainty about the future were the most difficult, although still a small proportion (12-16 %). All items were endorsed by over 50 % of HCPs as 'quite' or 'very' relevant to brain metastases patients, with two exceptions: 15 and 12 % of HCPs rated pruritis and future uncertainty as irrelevant, respectively. Conclusion We report the first content validation of the QLQ-BN20+2 and QLQ-C15-PAL QOL questionnaires for patients undergoing treatment for brain metastases, demonstrating feasibility and relevance. These questionnaires should be used together as universal QOL assessment tools in this setting.

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Deep learning for brain metastasis detection and segmentation in longitudinal MRI data

et al. 2022

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Purpose Brain metastases (BM) occur frequently in patients with metastatic cancer. Early and accurate detection of BM is essential for treatment planning and prognosis in radiation therapy. Due to their tiny sizes and relatively low contrast, small BM are very difficult to detect manually. With the recent development of deep learning technologies, several res earchers have reported promising results in automated brain metastasis detection. However, the detection sensitivity is still not high enough for tiny BM, and integration into clinical practice in regard to differentiating true metastases from false positives (FPs) is challenging. Methods The DeepMedic network with the binary cross‐entropy (BCE) loss is used as our baseline method. To improve brain metastasis detection performance, a custom detection loss called volume‐level sensitivity–specificity (VSS) is proposed, which rates metastasis detection sensitivity and specificity at a (sub)volume level. As sensitivity and precision are always a trade‐off, either a high sensitivity or a high precision can be achieved for brain metastasis detection by adjusting the weights in the VSS loss without decline in dice score coefficient for segmented metastases. To reduce metastasis‐like structures being detected as FP metastases, a temporal prior volume is proposed as an additional input of DeepMedic. The modified network is called DeepMedic+ for distinction. Combining a high‐sensitivity VSS loss and a high specificity loss for DeepMedic+, the majority of true positive metastases are confirmed with high specificity, while additional metastases candidates in each patient are marked with high sensitivity for detailed expert evaluation. Results Our proposed VSS loss improves the sensitivity of brain metastasis detection, increasing the sensitivity from 85.3% for DeepMedic with BCE to 97.5% for DeepMedic with VSS. Alternatively, the precision is improved from 69.1% for DeepMedic with BCE to 98.7% for DeepMedic with VSS. Comparing DeepMedic+ with DeepMedic with the same VSS loss, 44.4% of the FP metastases are reduced in the high‐sensitivity model and the precision reaches 99.6% for the high‐specificity model. The mean dice coefficient for all metastases is about 0.81. With the ensemble of the high‐sensitivity and high‐specificity models, on average only 1.5 FP metastases per patient need further check, while the majority of true positive metastases are confirmed. Conclusions Our proposed VSS loss and temporal prior improve brain metastasis detection sensitivity and precision. The ensemble learning is able to distinguish high confidence true positive metastases from metastases candidates that require special expert review or further follow‐up, being particularly well‐fit to the requirements of expert support in real clinical practice. This facilitates metastasis detection and segmentation for neuroradiologists in diagnostic and radiation oncologists in therapeutic clinical applications.

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Effects of Radiotherapy for Brain Metastases on Quality of Life (QoL)

Cited by 59 publications

References 24 publications

Quality of life in patients with brain metastases using the EORTC QLQ-BN20 and QLQ-C30

Quality of life in patients with brain metastases using the EORTC QLQ-BN20 and QLQ-C30

Content validation of the EORTC QLQ-BN20+2 with patients and health care professionals to assess quality of life in brain metastases

Deep learning for brain metastasis detection and segmentation in longitudinal MRI data

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