Independent External Validation of a Score Predicting Survival After Radiotherapy for Bone Metastases and Expansion to Patients Treated With Single Fraction Radiotherapy

Nieder, Carsten; Mannsåker, Bård; Dalhaug, Astrid

doi:10.14740/jocmr4060

Cited by 3 publications

(4 citation statements)

References 34 publications

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“…The review-board approved database is regularly updated for survival and has been utilized for different quality-of-care projects before [ 8 , 9 ]. Overall survival (time to death) from the first day of radiotherapy was calculated employing the Kaplan–Meier method for all 287 treatment courses (SPSS 28, IBM Corp., Armonk, NY, USA).…”

Section: Methodsmentioning

confidence: 99%

Early death after palliative radiation treatment: 30-, 35- and 40-day mortality data and statistically robust predictors

et al. 2023

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Background This study analyzed mortality after radiotherapy for bone metastases (287 courses). Endpoints such as treatment in the last month of life and death within 30, 35 and 40 days from start of radiotherapy were evaluated. Methods Different baseline parameters including but not limited to blood test results and patterns of metastases were assessed for association with early death. After univariate analyses, multi-nominal logistic regression was employed. Results Of 287 treatment courses, 42 (15%) took place in the last month of life. Mortality from start of radiotherapy was 13% (30-day), 15% (35-day) and 18% (40-day), respectively. We identified three significant predictors of 30-day mortality (performance status (≤ 50, 60–70, 80–100), weight loss of at least 10% within 6 months (yes/no), pleural effusion (present/absent)) and employed these to construct a predictive model with 5 strata and mortality rates of 0–75%. All predictors of 30-day mortality were also associated with both, 35- and 40-day mortality. Conclusion Early death was not limited to the first 30 days after start of radiotherapy. For different cut-off points, similar predictive factors emerged. A model based on three robust predictors was developed.

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Section: Methodsmentioning

confidence: 99%

Early death after palliative radiation treatment: 30-, 35- and 40-day mortality data and statistically robust predictors

et al. 2023

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“…The database was already review-board approved and has been utilized for different quality-of-care projects [ 10 , 11 ]. Overall survival (time to death) from the first day of PRT was calculated employing the Kaplan–Meier method for all 287 treatment courses (SPSS 28, IBM Corp., Armonk, NY, United States).…”

Section: Methodsmentioning

confidence: 99%

Percent of remaining life on palliative radiation treatment: solely a function of fractionation?

Nieder

Mannsåker

Dalhaug

2023

Rep Pract Oncol Radiother.

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Background This study analyzed the percent of remaining life (PRL) on treatment in patients irradiated for bone metastases. Bone metastases were treated together with other target volumes, if indicated, e.g. a 10-fraction treatment course that included brain and bone metastases. PRL was determined by calculating the time between start and finish of palliative radiotherapy (minimum 1 day in case of a single-fraction regimen) and dividing it by overall survival in days from start of radiotherapy. Materials and methods Different baseline parameters were assessed for association with dichotomized PRL (< 5% vs . ≥ 5%). The retrospective study included 219 patients (287 courses of palliative radiotherapy). After univariate analyses, multi-nominal logistic regression was employed. Results PRL on treatment ranged from 1–23%. Single-fraction radiotherapy resulted in < 5% PRL on treatment in all cases. All courses with 10 fractions resulted in at least 5% PRL on treatment. Significant associations were found between various baseline parameters and PRL category. With fractionation included in the regression model, 3 parameters retained significant p-values: Karnofsky performance status (KPS), none-bone target volume and fractionation (all with p < 0.001). If analyzed without fractionation, none-bone target volume (p < 0.001), hemoglobin (p < 0.001), KPS (p = 0.01), lack of additional systemic treatment (p = 0.01), and hypercalcemia (p = 0.04) were significant. Conclusions Fractionation is an easily modifiable factor with high impact on PRL. Patients with KPS < 70 and those treated for additional target types during the same course are at high risk of spending a larger proportion of their remaining life on treatment.

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“…Analogous to a previous validation approach (14), our singleinstitution database that includes unselected patients irradiated for complicated or uncomplicated bone metastases from histologically verified primary tumors (both completed and interrupted treatment courses according to the intention-to-treat principle, 2009-2018) was analyzed. Radiotherapy prescription was individualized (often 3 Gy ×10, 4 Gy ×5 or 8 Gy ×1), as was systemic therapy.…”

Section: Methodsmentioning

confidence: 99%

“…This heterogeneity causes uncertainty regarding treatment decisions, such as the decision to irradiate at all and the choice of fractionation regimen (9)(10)(11). Several groups have proposed prognostic models, which may support decision making (12)(13)(14). Recently, new technology has resulted in improved opportunities to add complexity to such models, e.g.…”

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confidence: 99%

Independent Validation of a Comprehensive Machine Learning Approach Predicting Survival After Radiotherapy for Bone Metastases

2021

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Background/Aim: The aim of this study was to analyze the survival predictions obtained from a web platform allowing for computation of the so-called Bone Metastases Ensemble Trees for Survival (BMETS). This prediction model is based on a machine learning approach and considers 27 prognostic covariates. Patients and Methods: This was a retrospective single-institution analysis of 326 patients, managed with palliative radiotherapy for bone metastases. Deviations between model-predicted survival and observed survival were assessed. Results: The median actuarial survival was 7.5 months. In total, 59% of patients survived for a period shorter than predicted. Twenty percent of the predictions of the median survival deviated from the observed survival by at least 6 months. Regarding actual survival <3 months (99 of 326 patients), the BMETS-predicted median survival was <3 months, i.e. correct in 67 of 99 cases (68%), whereas the model predicted a median of 4-6 months in 16 (16%) and of >6 months in another 16 cases. Conclusion: The model predicted survival with high accuracy in a large number of patients. Nevertheless, if the model predicts a low likelihood of 3-month survival, actual survival may be very poor (often 1 month or less). Also, in patients who died within 3 months from the start of radiotherapy, the model often predicted longer survival (16% had >6 months predicted median survival). It would, therefore, be interesting to feed the U.S. database utilized to develop the BMETS with additional poor-prognosis patients to optimize the predictions.

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Independent External Validation of a Score Predicting Survival After Radiotherapy for Bone Metastases and Expansion to Patients Treated With Single Fraction Radiotherapy

Cited by 3 publications

References 34 publications

Early death after palliative radiation treatment: 30-, 35- and 40-day mortality data and statistically robust predictors

Early death after palliative radiation treatment: 30-, 35- and 40-day mortality data and statistically robust predictors

Percent of remaining life on palliative radiation treatment: solely a function of fractionation?

Independent Validation of a Comprehensive Machine Learning Approach Predicting Survival After Radiotherapy for Bone Metastases

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