Development of a Score Predicting Survival after Palliative Reirradiation

Nieder, Carsten; Andratschke, Nicolaus; Angelo, Kent; Haukland, Ellinor; Grosu, Anca L.

doi:10.1155/2014/128240

Cited by 7 publications

(7 citation statements)

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“…The appropriateness of using an arbitrary cut-off to define short survival/end of life (such as the 1 month cut-off used in previous publications) may also be debated, as a number of patients may survive only few days longer than this period (12). In order to avoid administering palliative radiotherapy during the last month of life, or to make informed decisions in cases where patients request treatment, despite limited expectation of survival, a prediction tool was previously developed and validated by Angelo et al (10).…”

Section: Introductionmentioning

confidence: 99%

Palliative radiotherapy during the last month of life: Predictability for referring physicians and radiation oncologists

et al. 2015

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Abstract.Oncologists commonly overestimate the survival time of patients receiving palliative therapy, which may result in the administration of treatments that are too aggressive for patients near the end of their lives. Previous studies have discussed the negative implications of palliative radiotherapy if administered during the last month of life. Models predicting a limited survival time may improve the ability of the oncologists to tailor the treatment according to the needs of each individual patient. In the present study, prognostic factors for survival time, and the use of palliative radiotherapy during the last month of life, were analyzed in 873 patients. Models predicting the likelihood of administering such therapy were examined, and the risk of receiving radiotherapy during the last month of life was observed to be lower in patients with non-metastatic cancer than in those with metastatic cancer (7 vs. 13%, respectively; P=0.12). On multivariate analysis, 11 factors that significantly influenced the survival time were identified. These findings emphasize the complexity of potential prediction models. The most important risk factor regarding the prediction of extremely short survival times was observed to be an Eastern Cooperative Oncology Group performance status (ECOG PS) of 4, followed by an ECOG PS of 3 (median survival times, 14 and 64 days, respectively). A limited number of patients who received palliative radiotherapy during their last month of life died unexpectedly. Disease-specific prediction models were developed; however, the small number of events available for analysis limited their immediate clinical impact. Furthermore, these prediction models identified a minority of patients who received radiotherapy during the last month of life. In conclusion, the majority of the palliative radiotherapy courses administered to patients with advanced cancer during their last month of life may be preventable if accurate decision models for the clinic are developed. However, due to the complexity associated with the prediction of survival times in patients receiving palliative radiotherapy, large databases are required to allow accurate models to be established. The present study also discusses the recommendations of the Department of Oncology and Palliative Medicine of Nordland Hospital (Bodø, Nordland, Norway) with regard to the use of palliative radiotherapy during the last month of life of patients with terminal cancer.

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Section: Introductionmentioning

confidence: 99%

Palliative radiotherapy during the last month of life: Predictability for referring physicians and radiation oncologists

et al. 2015

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“…However, the results were not identical. Currently, these patient-reported symptoms are not included in commonly employed prognostic models, e.g., for brain metastasis and lung cancer [ 13 - 15 , 17 - 18 ].…”

Section: Discussionmentioning

confidence: 99%

“…In line with previous studies [ 11 - 12 ], we identified the patients with scores zero for all items (no symptoms), at least one item with score one-two (minimal symptoms), and at least one item with the score three (moderate symptoms). This study was performed to expand our ongoing efforts to develop prognostic models that support the decision making for personalized palliative approaches [ 13 - 15 ].…”

Section: Introductionmentioning

confidence: 99%

Frequency and Prognostic Impact of Consistently Low Edmonton Symptom Assessment System Score in the Patients Treated with Palliative Radiotherapy

Nieder¹,

Kämpe²

2018

Cureus

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IntroductionOur department's standard work-flow includes assessment of all the patients with the Edmonton Symptom Assessment System (ESAS), a one-sheet questionnaire addressing 11 major symptoms and wellbeing on a numeric scale of zero-10, before the palliative radiotherapy (PRT). Based on previous research, we hypothesized that the patients with minimal or moderate total symptom burden might have better overall survival after the PRT than those with at least one higher symptom score.MethodsWe performed a retrospective analysis of 94 patients and calculated actuarial survival from the first day of the PRT (Kaplan-Meier method). We identified the patients with the score zero for all ESAS items (no symptoms), at least one item with score one-two (minimal symptoms), and at least one item with the score three (moderate symptoms).ResultsHigh proportions of the patients had ESAS scores zero- two for nausea (80%), sadness/depression (65%) and constipation (64%). The mean values were often in the range of two-four. Only one patient reported scores of zero throughout the questionnaire. He was treated for hematuria, a symptom that is not part of the ESAS. Three patients reported scores of zero-two throughout the questionnaire. Except for the performance status zero-one, their baseline characteristics were heterogeneous. Two patients reported scores not exceeding three for all items. These patients had excellent performance status, too. None of the six patients (6%) with relatively low ESAS scores of zero-three received care by the hospital's multidisciplinary palliative team. Only one was using opioid analgesics. The median survival for this small subset of six patients was six months, identical to the result for all the patients with higher symptom burden (p = 0.62).ConclusionThe proportion of the patients with ESAS scores zero-three throughout the questionnaire was 6%, which resulted in the limited statistical power for the survival comparisons. The survival outcomes were similar. Before PRT, 94% of the patients reported at least one ESAS item of severity four-10. The symptoms not included in the questionnaire, e.g., hematuria might result in erroneous assignment to the low-symptom-burden group and obscure the prognostic impact of low ESAS symptom burden.

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“…The same was true for the well established SPT-Chow which is generally accepted as a valid survival tool in palliative cancer care [ 20 – 22 ]. On the other hand, SPT-Nieder which was developed in a small ( n = 87), inhomogeneous patient sample including reirradiations for brain, bone, and lung metastases, as well as primary tumors, among others [ 23 ], showed acceptable predictive separation.…”

Section: Discussionmentioning

confidence: 99%

“…SPT-Chow was chosen because it is a simple and validated tool, widely applicable in palliative settings [ 22 ]. Furthermore, we included the SPT developed for reirradiation in general by Nieder et al [ 23 ]. SPTs as developed by Tokuhashi [ 24 ], Balain [ 25 ], Bauer [ 26 ], Bollen [ 27 ], and Tomita et al [ 28 ], were deemed appropriate.…”

Section: Methodsmentioning

confidence: 99%

Overall survival after reirradiation of spinal metastases – independent validation of predictive models

et al. 2016

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BackgroundIt is unknown if survival prediction tools (SPTs) sufficiently predict survival in patients who undergo palliative reirradiation of spinal metastases. We therefore set out to clarify if SPTs can predict survival in this patient population.MethodsWe retrospectively analyzed spinal reirradiations performed (n = 58, 52 patients, 44 included in analysis). SPTs for patients with spinal metastases were identified and compared to a general palliative score and to a dedicated SPT to estimate prognosis in palliative reirradiation independent of site (SPT-Nieder).ResultsConsistently in all tests, SPT-Nieder showed best predictive performance as compared to other tools. Items associated with survival were general condition (KPS), liver metastases, and steroid use. Other factors like primary tumor site, pleural effusion, and bone metastases were not correlated with survival. We adapted an own score to the data which performed comparable to SPT-Nieder but avoids the pleural effusion item. Both scores showed good performance in identifying long-term survivors with late recurrences.ConclusionsSurvival prediction in case of spinal reirradiation is possible with sufficient predictive separation. Applying SPTs in case of reirradiation helps to identify patients with good life expectancy who might benefit from dose escalation or longer treatment courses.Electronic supplementary materialThe online version of this article (doi:10.1186/s13014-016-0613-y) contains supplementary material, which is available to authorized users.

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Development of a Score Predicting Survival after Palliative Reirradiation

Cited by 7 publications

References 22 publications

Palliative radiotherapy during the last month of life: Predictability for referring physicians and radiation oncologists

Palliative radiotherapy during the last month of life: Predictability for referring physicians and radiation oncologists

Frequency and Prognostic Impact of Consistently Low Edmonton Symptom Assessment System Score in the Patients Treated with Palliative Radiotherapy

Overall survival after reirradiation of spinal metastases – independent validation of predictive models

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