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. 2021 May:158:104-111.
doi: 10.1016/j.radonc.2021.02.011. Epub 2021 Feb 19.

Survival after palliative radiation therapy for cancer: The METSSS model

Nicholas G Zaorsky  1 , Menglu Liang  2 , Rutu Patel  3 , Christine Lin  3 , Leila T Tchelebi  3 , Kristina B Newport  4 , Edward J Fox  5 , Ming Wang  2
Affiliations

Survival after palliative radiation therapy for cancer: The METSSS model

Nicholas G Zaorsky et al. Radiother Oncol. 2021 May.

Abstract

Background: We propose a predictive model that identifies patients at greatest risk of death after palliative radiotherapy, and subsequently, can help medical professionals choose treatments that better align with patient choice and prognosis.

Methods: The National Cancer Database was queried for recipients of palliative radiotherapy during first course of treatment. Cox regression models and adjusted hazard ratios with 95% confidence intervals were used to evaluate survival predictors. The mortality risk index was calculated using predictors from the estimated Cox regression model, with higher values indicating higher mortality risk. Based on tertile cutpoints, patients were divided into low, medium, and high risk groups.

Results: A total of 68,505 patients were included from 2010-2014, median age 65.7 years. Several risk factors were found to predict survival: (1) location of metastases (liver, bone, lung, and brain); (2) age; (3) tumor primary (prostate, breast, lung, other); (4) gender; (5) Charlson-Deyo comorbidity score; and (6) radiotherapy site. The median survival times were 11.66 months, 5.09 months, and 3.28 months in the low (n=22,621), medium (n=22,638), and high risk groups (n=22,611), respectively. A nomogram was created and validated to predict survival, available online, https://tinyurl.com/METSSSmodel. Harrel's C-index was 0.71 and receiver operator characteristic area under the curve was 0.76 at 4 years.

Conclusion: We created a predictive nomogram for survival of patients receiving palliative radiotherapy during their first course of treatment (named METSSS), based on Metastases location, Elderly (age), Tumor primary, Sex, Sickness/comorbidity, and Site of radiotherapy.

Keywords: Cancer; Metastasis; Prediction; Radiation oncology; Survival.

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Conflict of interest statement

Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Figure 1.
Figure 1.. Number of patients receiving therapy and treatment based on disease site.
The majority of patients receiving palliative radiotherapy had lung cancer (n=43,746, 63.9%), followed by leukemia and lymphoma (n=4,873, 7.1%), breast cancer (n=4,364, 6.4%), and prostate cancer (n=2,789, 4.1%) (upper right and left figures). Among the fractionation regimens, 3 Gy × 10 (n=58,521, 85.4%) was most common (bottom right and left figures).
Figure 2.
Figure 2.. Kaplan-Meier survival curves for five-year post palliative radiation therapy.
The x-axis shows the survival time in months, up to 5 years. The y-axis shows the probability of survival from 0 to 1.0. The tertile cutpoints, based on estimated linear predictors from Cox PH regression, divides patients into low (red), medium (green), and high-risk (blue) groups. A survival curve is provided for each METSSS survival group. High-risk patients have the poorest five-year survival. The log-rank test indicates significant differences in survival probability between the three risk groups (p < 0.0001).
Figure 3.
Figure 3.. Nomogram to predict survival after palliative radiotherapy.
Nomogram for predicting survival probability at 1- and 5-years. This work is available online, https://tinyurl.com/METSSSmodel.
Figure 4.
Figure 4.. Internal calibration for 1-year and 5-year survival probability.
Comparison of the blue curve to the gray curve at 1-year and 5-year survival probability shows that the model is well calibrated.
See this image and copyright information in PMC

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