Vol 28, No 1 (2023)
Research paper
Published online: 2023-02-14

open access

Page views 2133
Article views/downloads 316
Get Citation

Connect on Social Media

Connect on Social Media

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

Carsten Nieder12, Bård Mannsåker1, Astrid Dalhaug1
Rep Pract Oncol Radiother 2023;28(1):47-53.

Abstract

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.   

 

research paper

Reports of Practical Oncology and Radiotherapy

2023, Volume 28, Number 1, pages: 47–53

DOI: 10.5603/RPOR.a2023.0013

Submitted: 30.01.2023

Accepted: 10.02.2023

© 2023 Greater Poland Cancer Centre.

Published by Via Medica.

All rights reserved.

e-ISSN 2083–4640

ISSN 1507–1367

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

Carsten Nieder12Bård Mannsåker1Astrid Dalhaug1
1Department of Oncology and Palliative Medicine, Nordland Hospital, Bodø, Norway
2Department of Clinical Medicine, Faculty of Health Sciences, UiT — The Arctic University of Norway, Tromsø, Norway

Address for correspondence: Prof. Dr. Carsten Nieder, Department of Oncology and Palliative Medicine, Nordland Hospital Trust, 8092 Bodø, Norway; e-mail: cnied@hotmail.com

This article is available in open access under Creative Common Attribution-Non-Commercial-No Derivatives 4.0 International (CC BY-NC-ND 4.0) license, allowing to download articles and share them with others as long as they credit the authors and the publisher, but without permission to change them in any way or use them commercially

Abstract
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.
Key words: radiation therapy; bone metastases; palliative treatment; prognostic factors; fractionation
Rep Pract Oncol Radiother 2023;28(1):47–53

Introduction

An ideal palliative radiotherapy (PRT) scenario consists of efficacious yet nontoxic and convenient treatment, which minimizes interference with patients’ other anticancer treatment and daily activity [1]. These goals are not always easy to achieve, but in the context of PRT for painful uncomplicated bone metastases the 8-Gy single fraction regimen is an excellent example for a satisfactory solution [2, 3]. Complicated bone metastases represent a more complex challenge and, often, higher doses of radiation are prescribed to achieve goals beyond pain improvement [4]. Both stereotactic body radiotherapy (SBRT; single dose or hypofractionated) and other, often more fractionated, approaches can be prescribed to achieve these goals [5, 6]. In the literature, variation in practice by patient, tumor, sociodemographic, geographical, and institutional provider factors has been identified [7].

Among other quality of care indicators, percent of remaining life (PRL) has recently received scientific attention [8, 9]. PRL evaluation is accomplished by calculating the time between start and finish of PRT (minimum 1 day in case of a single-fraction regimen) and dividing it by overall survival in days from start of PRT. Patients with short survival receiving prolonged PRT are going to spend a large proportion of their remaining life on treatment, in extreme cases more than 50%, typically between 6 and 25%. A previous study that included single-fraction and other short course regimens reported 8% median PRL [9].

The most efficient way of minimizing PRL is single-fraction radiotherapy, especially when fast track treatment planning results in same day preparations and treatment. Even a patient surviving for 30 days is spending 1 divided by 30 (3%) PRL on treatment. It is not entirely clear whether or not baseline parameters such as age and patterns of metastases have a major impact on PRL, despite an obvious connection between survival/prognostic factors determining survival (the PRL calculation denominator) and eventual PRL. Therefore, we performed in-depth analyses of potential prognostic factors including but not limited to blood test results and imaging-based disease burden, aiming to identify all contributing variables.

Materials and methods

An arbitrary definition of low PRL on treatment was employed, i.e. < 5%, which was based on previously reported median values of 6 and 8%, respectively [8, 9]. The primary endpoint was identification of factors associated with PRL < 5%. We performed a retrospective analysis of our single institution database of patients with palliatively irradiated bone metastases (bone only or bone plus other target volumes in the same treatment course). We included patients treated from 2014 to 2019. Patients who failed to complete all prescribed fractions were also included. We excluded patients who were treated with ablative radiation doses (SBRT). The study evaluated 219 consecutive patients managed with standard palliative external beam radiotherapy techniques. Examples include a single fraction of 8 Gy, 5 fractions of 4 Gy or 10 fractions of 3 Gy (3-D conformal or intensity-modulated). Fractionation was at the discretion of the treating oncologist. In addition to PRT, all eligible patients received standard-of-care systemic anticancer treatment, if indicated. Patients who returned for a new treatment course in the time period of the study were counted twice, resulting in a total number of 287 evaluable treatment courses. In these cases, actual blood test results, imaging reports, Karnofsky performance status (KPS) and other baseline data, as well as survival were registered for each individual treatment course. Imaging and blood tests were part of our routine oncological assessment and typically no older than 3 weeks before PRT. Blood test results were dichotomized (normal/abnormal) according to the institutional upper and lower limits of normal.

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). In 27 cases, survival was censored after median 36 months of follow-up (minimum 28 months). After a minimum follow-up of 28 months, all 27 cases could be assigned to the PRL < 5% group. Date of death was known for all remaining cases/courses. PRL was dichotomized (< 5% vs.5%) and the chi-square test (2-sided) was utilized for further analyses. A multi-nominal logistic regression analysis was also employed. P-values < 0.05 were considered statistically significant.

Results

Many treatment courses were administered in patients with prostate or lung cancer, and in the outpatient setting, as shown in Table 1. Commonly, painful bone metastases were irradiated without including non-bone target volumes in the same course. A single fraction was prescribed in 24% of courses. Overall, 9 courses were not completed as planned. The mean age was 68 years. Median actuarial overall survival was 6 months (1-year rate 32%). PRL on treatment ranged from 1–23%, median 8. Less than 5% PRL was recorded in 136 courses (47%).

Table 1. Baseline characteristics, 219 patients who started 287 treatment courses. Data based on individual treatment courses. Blood test results and disease status (non-irradiated stable versus progression) were not available for all treatment courses

Baseline parameter

Number

Percent

Female sex

118

41

Male sex

169

59

KPS < 70

63

22

KPS70

224

78

Outpatient

182

63

Inpatient

105

37

Age 7180 years

94

33

Age81 years

39

14

Prostate cancer

72

25

Non-small cell lung cancer

56

20

Breast cancer

53

19

Small cell lung cancer

11

4

Renal cell cancer

17

6

Colorectal cancer

32

11

Bladder cancer

10

4

Other primary tumors

36

12

Treatment-related variables

One or two target volumes irradiated

206

72

Three or more target volumes irradiated

81

28

Osseous metastases irradiated (exclusively)

234

82

Extraosseous metastases irradiated

53

18

Pain indication for RT

245

85

Non-pain indication (neurological etc.)

42

15

Prescribed regimen of 10 fractions

100

35

Prescribed regimen of 1 fraction

70

24

Prescribed regimen of 25 fractions

117

41

No systemic therapy

63

22

Previous or ongoing systemic therapy

224

78

Corticosteroid concomitant to RT

115

40

No corticosteroid concomitant to RT

172

60

Opioid analgesic concomitant to RT

189

66

No opioid analgesic concomitant to RT

98

34

Palliative care team involved

96

33

Palliative care team not involved

191

67

Early RT, within 2 mo from cancer diagnosis

91

32

Late RT, > 2 months

196

68

Blood test results

Low hemoglobin

174

61

Normal hemoglobin

112

39

Hypercalcemia

18

6

Normal calcium

262

91

Low albumin

41

14

Normal albumin

229

80

High lactate dehydrogenase

116

40

Normal lactate dehydrogenase

122

43

High alkaline phosphatase

157

55

Normal alkaline phosphatase

111

39

Leukocytosis

54

19

No leukocytosis

232

81

High C-reactive protein

198

69

Normal C-reactive protein

84

29

Abnormal platelet count

56

20

Normal platelet count

229

80

Disease extent and status

Brain metastases

25

9

Liver metastases

87

30

Lung metastases

93

32

Adrenal gland metastases

23

8

Disease progression in non-irradiated area

132

46

Stable disease outside irradiated area

152

53

All baseline parameters included in Table 1 were initially tested for associations with PRL. Those who were significantly associated are displayed in Table 2. Unsurprisingly, 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. Inclusion of non-bone target volumes in a course resulted in only 15% of patients with < 5% PRL, compared to 55% of patients with bone-only target volumes. In this context, it should be emphasized that single-fraction radiotherapy is not typically utilized for none-bone targets such as lymph node or brain metastases. The remaining statistically significant factors involved very different types of baseline information, e.g. blood test results, KPS, primary tumor type and age.

Table 2. Association between percent of remaining life (PRL) and baseline parameters in 287 treatment courses

Parameter

Significance level

PRL < 5% (%)

PRL < 5% (number)

PRL ≥5% (number)

Fractionation

< 0.001

1

100

70

0

25

56

66

51

10

0

0

100

Target volume

< 0.001

Non-bone in addition to bone

15

8

45

Bone alone

55

128

106

Karnofsky performance status

< 0.001

< 70

24

15

48

≥ 70

54

121

103

Systemic treatment

< 0.001

None

24

15

48

Any concurrent/ongoing treatment

54

121

103

Timing of radiotherapy

< 0.001

Early (within 2 months from diagnosis)

33

30

61

Later during the disease trajectory

54

106

90

Hemoglobin level

< 0.001

Low

56

97

77

Normal

34

38

74

Calcium level

0.007

High

17

3

15

Normal

50

131

131

Number of irradiated target volumes

0.008

12 in actual course

52

108

98

3 or more in actual course

35

28

53

Primary cancer diagnosis

0.01

Prostate or breast

56

70

55

Others

41

66

96

Radiotherapy setting

0.01

Inpatient

37

39

66

Outpatient

53

97

85

Age

0.035

80 years or older

62

28

17

Younger than 80 years

45

108

134

Type of symptoms

0.038

Neurological deficit

11

1

8

Others, e.g. pain

49

135

143

All parameters displayed in Table 2 were moved forward to multi-nominal logistic regression analysis, to account for interrelated factors such as fractionation and presence of none-bone target volumes. With fractionation included in the model, 3 parameters retained significant p-values: 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), additional systemic treatment (p = 0.01) and hypercalcemia (p = 0.04) were significant.

Discussion

This study aimed at identification of variables that impact on PRL < 5%, which may be regarded a minor amount of time spent on palliative radiation treatment. In this context, it must be emphasized that we chose this arbitrary definition despite the absence of international consensus on adequate or optimal PRL on treatment. Other definitions, such as < 10%, would also be possible. However, previously described median values of 6 and 8% [8, 9], respectively, informed the present cut-off. One may also argue that limited PRL on treatment is not a surrogate of net appropriateness, efficacy or optimal balance. For example, if 3% PRL would result in short-lived and less complete symptom palliation, while 6% would result in a larger gain, patients could be willing to accept prolonged treatment, because the quality of their remaining life improves [12]. Such trade-off would also have to consider toxicity, inconvenience and cost related to transportation, treatment itself and other factors. For the scenario of uncomplicated painful bone metastases, abundant evidence supports single-fraction radiotherapy, which causes minimal PRL on treatment [2, 3]. Other scenarios are less straightforward and require open discussion about the pros and cons of different treatment regimens [13, 14]. Implementation of single-fraction PRT should be accompanied by long-term efforts to support adequate utilization and prevent perishing [15]. A recent study reported the following predictors of single-fraction prescription: poor PS, lung and urologic primaries, and lower half-body as site of irradiation [16]. Spinal metastases were more likely to receive prolonged treatment, i.e. multiple fractions.

The results of our study highlight that fractionation is a major driver of PRL. Also, the inclusion of non-bone target volumes in a course of bone irradiation impacts greatly on PRL. Both reduced survival due to, e.g., brain metastases or a symptomatic primary tumor in the thorax (as compared to bone-only metastases, especially in prostate or breast cancer), and physician preference of more protracted or fractionated radiotherapy if the indication is not limited to uncomplicated painful bone metastases, may explain why PRL on treatment increases in the presence of non-bone target volumes. Patients with KPS < 70 were not very likely to spend < 5% PRL on treatment. This is mainly related to short survival, and numerous prognostic models include KPS as a main driver of poor prognosis [17–19]. We also observed that patients not receiving systemic treatment are in a comparable situation. Typically, poor KPS impacts on eligibility for systemic therapy, but other factors contribute, too, e.g. comorbidity, reduced organ function and lack of available options when numerous lines of treatment have already been administered.

Interestingly, after testing of a large number of potentially relevant variables (Tab. 1), very few were confirmed as major drivers of PRL in multi-nominal logistic regression analysis. Blood test results such as hypercalcemia are not commonly included in radiotherapy-related prognostic models, but appear to contribute additional information. Their role requires further study in larger databases. Besides number of patients, limitations of the present work include its retrospective single-institution design and the lack of certain baseline data, e.g. lactate dehydrogenase, in a proportion of patients. On the other hand, the study cohort represents a real-world patient population of often elderly patients with highly variable disease burden and survival.

To facilitate decision making in practice, Farris et al. have proposed a pragmatic method to evaluate the suitability of PRT fractionation [8]. They described a novel metric, the palliative appropriateness criteria (PAC) score and provided an online calculator. Our group has recently performed independent validation [9]. Factors significantly associated with long time spent on treatment, i.e. increased PRL, were male gender, Eastern Cooperative Oncology Group (ECOG) PS 3–4, lung or “other” primary diagnosis (vs. breast or prostate), radiotherapy indication (neurological dysfunction vs. pain/other), inpatient status, and extraosseous site treatment [8]. However, factors were not uniform across all different fraction regimens. For example, only 4 factors were relevant in the subgroup selected for single-fraction irradiation. ECOG PS 3–4 was universally associated with significantly higher PRL among all regimens. Extraosseous site of treatment was associated with higher PRL for 2–5 and 10 fraction regimens.

Typical, well-established prognostic models for survival, such as TEACHH and others, did not stratify for radiotherapy fractionation and did not calculate PRL [20–22]. Indirectly, they can contribute some, yet limited, information in so far as patients with long survival (≥ 1 year) treated with 10 fractions always will spend < 5% PRL on treatment. TEACHH includes cancer type (lung and “other” versus breast and prostate), older age (> 60 years versus60 years), liver metastases, ECOG PS (2–4 vs. 0–1), hospitalizations within 3 months before palliative radiotherapy (0 vs. ≥1) and prior palliative chemotherapy courses (≥ 2 vs. 0–1) [20]. Even simple models, such as the one introduced in 2008 by Chow et al. (3 factors: non-breast cancer, metastases other than bone, and KPS60), have demonstrated clinical value [21]. Despite progress in prognostic stratification, survival predictions in oncology tend to be overly optimistic [23, 24]. Not all patients initially thought to represent suitable candidates for PRT are able to complete their treatment. In an analysis of patients who died during PRT, Berger et al. found that once radiotherapy was begun the treatment duration required a median 64% of the remaining lifetime [25]. It is, therefore, clear that prognostic assessment and calculation of PRL have the potential to optimize PRT care pathways.

Conclusions

Radiotherapy fractionation is an easily modifiable factor with high impact on PRL. Patients with KPS < 70 and those treated for additional target types (non-bone) during the same course are at high risk of spending a larger proportion of their remaining life on treatment.

Author contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by C.N. The first draft of the manuscript was written by C.N. and all authors commented on previous versions of the manuscript. All authors have read and agreed to the published version of the manuscript.

Conflicts of interest

The authors declare no conflict of interest.

Funding

This research received no external funding.

Institutional Review Board statement

As a retrospective quality of care analysis, no approval from the Regional Committee for Medical and Health Research Ethics (REK Nord) was necessary. This research project was carried out according to our institutions’ guidelines and with permission to access the patients’ data.

Informed consent statement

Informed consent was obtained from all subjects involved in the study.

Data availability statement

The dataset supporting the conclusions of this article is available at request from the corresponding author, if intended to be used for meta-analyses.

References

  1. Williams GR, Manjunath SH, Butala AA, et al. Palliative Radiotherapy for Advanced Cancers: Indications and Outcomes. Surg Oncol Clin N Am. 2021; 30(3): 563–580, doi: 10.1016/j.soc.2021.02.007, indexed in Pubmed: 34053669.
  2. Behroozian T, Navarro I, Hoskin P, et al. Update on the systematic review/meta-analysis of uncomplicated bone metastases treated with external beam radiation. Radiother Oncol. 2022; 174: 109–110, doi: 10.1016/j.radonc.2022.07.010, indexed in Pubmed: 35850265.
  3. van der Velden J, Willmann J, Spałek M, et al. ESTRO ACROP guidelines for external beam radiotherapy of patients with uncomplicated bone metastases. Radiother Oncol. 2022; 173: 197–206, doi: 10.1016/j.radonc.2022.05.024, indexed in Pubmed: 35661676.
  4. Oldenburger E, Brown S, Willmann J, et al. ESTRO ACROP guidelines for external beam radiotherapy of patients with complicated bone metastases. Radiother Oncol. 2022; 173: 240–253, doi: 10.1016/j.radonc.2022.06.002, indexed in Pubmed: 35688398.
  5. Spencer KL, van der Velden JM, Wong E, et al. Systematic Review of the Role of Stereotactic Radiotherapy for Bone Metastases. J Natl Cancer Inst. 2019; 111(10): 1023–1032, doi: 10.1093/jnci/djz101, indexed in Pubmed: 31119273.
  6. Ito K, Saito T, Nakamura N, et al. Stereotactic body radiotherapy versus conventional radiotherapy for painful bone metastases: a systematic review and meta-analysis of randomised controlled trials. Radiat Oncol. 2022; 17(1): 156, doi: 10.1186/s13014-022-02128-w, indexed in Pubmed: 36100905.
  7. Ong WL, Foroudi F, Milne RL, et al. Variation in the Use of Single- Versus Multifraction Palliative Radiation Therapy for Bone Metastases in Australia. Int J Radiat Oncol Biol Phys. 2020; 106(1): 61–66, doi: 10.1016/j.ijrobp.2019.08.061, indexed in Pubmed: 31505246.
  8. Farris JC, Johnson AG, Carriere PP, et al. Palliative Appropriateness Criteria: A Pragmatic Method to Evaluate the Suitability of Palliative Radiotherapy Fractionation. J Palliat Med. 2023; 26(1): 67–72, doi: 10.1089/jpm.2022.0173, indexed in Pubmed: 35881861.
  9. Nieder C, Haukland EC, Mannsåker B, et al. Palliative appropriateness criteria: external validation of a new method to evaluate the suitability of palliative radiotherapy fractionation. Strahlenther Onkol. 2023 [Epub ahead of print], doi: 10.1007/s00066-022-02040-y, indexed in Pubmed: 36625853.
  10. Nieder C, Mannsaker B, Dalhaug A. Independent External Validation of a Score Predicting Survival After Radiotherapy for Bone Metastases and Expansion to Patients Treated With Single Fraction Radiotherapy. J Clin Med Res. 2020; 12(2): 90–99, doi: 10.14740/jocmr4060, indexed in Pubmed: 32095178.
  11. Nieder C, Haukland E, Mannsåker B, et al. Early palliative radiation therapy in patients with newly diagnosed cancer: Reasons, clinical practice, and survival. Pract Radiat Oncol. 2015; 5(5): e537–e542, doi: 10.1016/j.prro.2015.02.008, indexed in Pubmed: 25823382.
  12. Cañón V, Gómez-Iturriaga A, Casquero F, et al. Quality of life improvement in patients with bone metastases undergoing palliative radiotherapy. Rep Pract Oncol Radiother. 2022; 27(3): 428–439, doi: 10.5603/RPOR.a2022.0048, indexed in Pubmed: 36186707.
  13. Timmermans LM, van der Maazen RWM, Verhaak CM, et al. Patient participation in discussing palliative radiotherapy. Patient Educ Couns. 2005; 57(1): 53–61, doi: 10.1016/j.pec.2004.03.016, indexed in Pubmed: 15797153.
  14. Pilote L, Côté L, Chipenda Dansokho S, et al. Talking about treatment benefits, harms, and what matters to patients in radiation oncology: an observational study. BMC Med Inform Decis Mak. 2019; 19(1): 84, doi: 10.1186/s12911-019-0800-5, indexed in Pubmed: 30975132.
  15. Shahhat S, Hanumanthappa N, Chung YT, et al. Do Sustainable Palliative Single Fraction Radiotherapy Practices Proliferate or Perish 2 Years after a Knowledge Translation Campaign? Curr Oncol. 2022; 29(7): 5097–5109, doi: 10.3390/curroncol29070404, indexed in Pubmed: 35877264.
  16. Ignat P, Todor N, Ignat RM, et al. Prognostic Factors Influencing Survival and a Treatment Pattern Analysis of Conventional Palliative Radiotherapy for Patients with Bone Metastases. Curr Oncol. 2021; 28(5): 3876–3890, doi: 10.3390/curroncol28050331, indexed in Pubmed: 34677249.
  17. Alcorn SR, Fiksel J, Wright JL, et al. Developing an Improved Statistical Approach for Survival Estimation in Bone Metastases Management: The Bone Metastases Ensemble Trees for Survival (BMETS) Model. Int J Radiat Oncol Biol Phys. 2020; 108(3): 554–563, doi: 10.1016/j.ijrobp.2020.05.023, indexed in Pubmed: 32446952.
  18. Sperduto PW, Mesko S, Li J, et al. Survival in Patients With Brain Metastases: Summary Report on the Updated Diagnosis-Specific Graded Prognostic Assessment and Definition of the Eligibility Quotient. J Clin Oncol. 2020; 38(32): 3773–3784, doi: 10.1200/JCO.20.01255, indexed in Pubmed: 32931399.
  19. Angelo K, Norum J, Dalhaug A, et al. Development and validation of a model predicting short survival (death within 30 days) after palliative radiotherapy. Anticancer Res. 2014; 34: 877–885, indexed in Pubmed: 24511026.
  20. Krishnan MS, Epstein-Peterson Z, Chen YH, et al. Predicting life expectancy in patients with metastatic cancer receiving palliative radiotherapy: the TEACHH model. Cancer. 2014; 120(1): 134–141, doi: 10.1002/cncr.28408, indexed in Pubmed: 24122413.
  21. Chow E, Abdolell M, Panzarella T, et al. Recursive partitioning analysis of prognostic factors for survival in patients with advanced cancer. Int J Radiat Oncol Biol Phys. 2009; 73(4): 1169–1176, doi: 10.1016/j.ijrobp.2008.05.067, indexed in Pubmed: 18938045.
  22. Pobar I, Job M, Holt T, et al. Prognostic tools for survival prediction in advanced cancer patients: A systematic review. J Med Imaging Radiat Oncol. 2021; 65(6): 806–816, doi: 10.1111/1754-9485.13185, indexed in Pubmed: 33973382.
  23. Wu SY, Yee E, Vasudevan HN, et al. Risk Stratification for Imminent Risk of Death at the Time of Palliative Radiotherapy Consultation. JAMA Netw Open. 2021; 4(7): e2115641, doi: 10.1001/jamanetworkopen.2021.15641, indexed in Pubmed: 34196716.
  24. Kondziolka D, Parry PV, Lunsford LD, et al. The accuracy of predicting survival in individual patients with cancer. J Neurosurg. 2014; 120(1): 24–30, doi: 10.3171/2013.9.JNS13788, indexed in Pubmed: 24160479.
  25. Berger B, Ankele H, Bamberg M, et al. Patients who die during palliative radiotherapy. Status survey. Strahlenther Onkol. 2014; 190(2): 217–220, doi: 10.1007/s00066-013-0471-6, indexed in Pubmed: 24408054.



Reports of Practical Oncology and Radiotherapy