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30-day mortality in patients treated for brain metastases: extracranial causes dominate

30-day mortality in patients treated for brain metastases: extracranial causes dominate Background: Established prognostic models, such as the diagnosis-specific graded prognostic assessment, were not designed to specifically address very short survival. Therefore, a brain metastases-specific 30-day mortality model may be relevant. We hypothesized that in-depth evaluation of a carefully defined cohort with short survival, arbitrarily defined as a maximum of 3 months, may provide signals and insights, which facilitate the development of a 30-day mortality model. Methods: Retrospective analysis (2011–2021) of patients treated for brain metastases with different approaches. Risk factors for 30-day mortality from radiosurgery or other primary treatment were evaluated. Results: The cause of death was unrelated to brain metastases in 61%. Treatment-related death (grade 5 toxicity) did not occur. Completely unexpected death was not observed, e.g. accident, suicide or sudden cardiac death. Logistic regression analysis showed 9 factors associated with 30-day mortality (each assigned 3–6 points) and a point sum was calculated for each patient. The point sum ranged from 0 (no risk factors for death within 30 days present) to 30. The results can be grouped into 3 or 4 risk categories. Eighty-three percent of patients in the highest risk group (> 16 points) died within 30 days, and none survived for more than 2 months. However, many cases of 30-day mortal- ity (more than half ) occurred in intermediate risk categories. Conclusion: Extracranial tumor progression was the prevailing cause of 30-day mortality and few, if any deaths could be considered relatively unexpected when looking at the complete oncological picture. We were able to develop a multifactorial prediction model. However, the model’s performance was not fully satisfactory and it is not routinely applicable at this point in time, because external validation is needed to confirm our hypothesis-generating findings. Keywords: Palliative radiation therapy, Stereotactic radiotherapy, Brain metastases, Prognostic factors, Biomarkers Background survival (typically if oligometastases are present [2]) Most patients with brain metastases from extracranial and shorter survival may be observed, and considerable primary tumors such as lung or breast cancer receive pal- efforts have been undertaken to predict survival (nomo - liative treatment approaches, because the common pat- grams, scores, online calculators [3–5]). Given that very tern of polymetastatic spread may cause compromised short survival often is synonymous to active treatment in performance status (PS) and eventually also limited sur- the last 30  days of life, oncologists can opt for palliative vival, often in the range of 3–9  months [1]. Both, longer and supportive care rather than brain-directed therapy [6]. Supposing they choose brain-directed therapy, the challenge is to navigate a complex scenario of low-value care, potential overtreatment and futile, but costly proce- *Correspondence: carsten.nieder@nlsh.no dures [7, 8]. Department of Oncology and Palliative Medicine, Nordland Hospital, Prognostic models familiar to many providers, such 8092 Bodø, Norway Full list of author information is available at the end of the article as the diagnosis-specific graded prognostic assessment © The Author(s) 2022. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/. The Creative Commons Public Domain Dedication waiver (http:// creat iveco mmons. org/ publi cdoma in/ zero/1. 0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Nieder et al. Radiation Oncology (2022) 17:92 Page 2 of 7 (DS-GPA) [3], were not designed to specifically address include patients who received their second treatment, very short survival. Different definitions of very short e.g. delayed salvage WBRT after previous SRS. Patients survival may be applied, including 30-day mortality, with leptomeningeal central nervous system metastases which has been evaluated in numerous oncology set- and those managed with best supportive care after diag- tings [9, 10]. General survival prediction models such nosis of brain metastases were not included. The data - as TEACHH may also be utilized [11, 12], but it is still base includes patients with solid tumors only, whereas unclear whether a brain metastases-specific 30-day mor - those with leukemia and lymphoma are excluded. For tality model should be preferred. Our group has previ- the purpose of this exploratory, hypothesis-generating ously studied different models that predict very short study, a cohort size of n = 100 was deemed appropri- survival (not specifically focused on 30 days), but none of ate. We felt that there was no solid fundament for these was considered truly satisfactory [13–15]. The fact statistical hypotheses or power calculations in the plan- that many patients with poor prognosis were not iden- ning process. Starting with recent patients treated in tified by any model was considered a major challenge. 2021, backward inclusion of consecutive patients was Ideally, a model would identify all or almost all patients employed. The target size of 100 patients was reached with very short survival, and simultaneously, patients when including patients treated in the year 2011. predicted to die early would not survive long enough to Besides established baseline parameters such as age, benefit from active treatment. In other words, both over- sex, number of brain metastases and Karnofsky PS, and undertreatment should be avoided, because shorten- blood test results were included (hemoglobin, plate- ing survival by withholding treatment would be a serious lets, C-reactive protein, albumin, lactate dehydrogenase threat too. (LDH); the components of the LabBM score, which These reflections are also applicable to the recently was assigned as originally recommended [16]). These introduced LabPS score (blood test results and PS) [14], were also employed to assign the LDH/albumin-based where the group with the poorest prognosis (3 or 3.5 extracranial score (EC-S) [15]. The pattern and num - points; maximum survival 2.1  months) was very small ber of extracranial sites was registered (uncontrolled (4% of all patients in the study). Most patients with com- primary tumor, liver, lung, bone and other extracra- parably short survival had a lower point sum. The LabPS nial metastases; standard staging considered appropri- score failed to outperform the previously proposed ate by the treating physicians at the time of treatment, extracranial-graded prognostic assessment score (EC- thus subject to temporal and cancer-type-related vari- GPA) [15]. Median survival was 0.7 months in the worst ation [17]). Most likely, the blood test results mirror prognostic group of the latter score, with a hazard ratio the overall burden of disease, including lesions not cor- for death of 44 (95% confidence interval (CI), 6–340) rectly identified on radiological examinations [16, 17]. compared to the best group. However, many patients The total number of brain metastases was derived from with short survival were not assigned to the worst group. magnetic resonance imaging (MRI) reports. Cumula- After these previous, only partially successful studies that tive lesion volume was not available. included all-comers, we changed our methodology, went Cause of death was recorded in order to account for back to the drawing board and hypothesized that in- surprising, unpredictable events such as accidents. Chi- depth evaluation of a carefully defined cohort with short square tests were employed to identify factors predict- survival, arbitrarily defined as a maximum of 3  months, ing 30-day mortality (30  days from SRS, first fraction may provide signals and insights, which facilitate the of WBRT, day 1 of chemotherapy etc.). The latter were development of viable 30-day mortality models. further examined in multinominal logistic regression analysis. Statistical significance was defined as p < 0.05 in two-sided tests. The methods employed by Rades Patients and methods et  al. were utilized to calculate a point sum reflective A previously described, continuously updated quality- of 30-day mortality [18, 19]. For example, a risk fac- of-care database covering all adult patients with brain tor associated with 50% 30-day mortality was assigned metastases at the authors’ institution, which employs 5 points, while 3 points were assigned for a factor electronic health records containing detailed follow-up associated with 30% 30-day mortality. The predictive information, was utilized [14]. The cohort was limited accuracy of our model was evaluated using Harrell’s to patients who survived ≤ 3.0 months from commenc- concordance index (Harell’s C). Harrell’s C shows per- ing their first treatment (start of primary whole-brain fect concordance if the value is 1, whilst a value of 0.5 radiotherapy (WBRT), date of radiosurgery (SRS), start indicates completely random concordance (an unser- of systemic treatment etc.), whether treatment was viceable model in other words). completed or not (intention-to-treat). The study did not N ieder et al. Radiation Oncology (2022) 17:92 Page 3 of 7 Table 1 Patient characteristics, n = 100 Results The most common treatment approach was WBRT Baseline parameter Number (= %) (30 Gy in 10 fractions, 64%; 20 Gy in 5 fractions, 12%). Sex Eighteen percent of all patients failed to complete their Female sex 46 prescribed treatment. Common tumor types included Male sex 54 non-small cell lung cancer (NSCLC, 42%), malignant Tumor type melanoma (12%) and breast cancer (11%). Detailed Non-small cell lung cancer 42 baseline characteristics are shown in Table  1. The Breast cancer, triple negative 3 30-day mortality was 28% and an additional 39% died Breast cancer, Her2 positive 4 between 31 and 60 days. Breast cancer, other 4 The cause of death was unrelated to brain metas- Malignant melanoma 12 tases in 61%. Both, extracranial metastases and Small cell lung cancer 9 uncontrolled primary tumors leading for example to Renal cell cancer 8 hemoptysis or refractory pneumonia were among the Colorectal cancer 10 documented causes of death. Brain metastases may Other gastrointestinal cancer 5 have contributed to death in 32% (uncertainty because Other primary tumors (bladder, head/neck) 3 the patients died at home or in nursing homes; no Extracranial disease firm documentation about the last days in our elec- No extracranial metastases 9 tronic patient records; both intra- and extracranial Extracranial metastases 91 tumor activity was recorded before hospital care was Bone metastases 37 terminated). Definitive confirmation of brain-related Liver metastases 38 death was available in the remaining 7%, including one Lung/pleura metastases 56 patient who died from hemorrhage. Treatment-related Controlled primary tumor 55 death (grade 5 toxicity) did not occur. Completely Uncontrolled primary tumor* 45 unexpected death was not observed, e.g. accident or Active organ sites incl. uncontrolled primary tumor: 0 5 suicide. Active sites: 1** 16 Univariate analyses (all factors included in Table  1 Active sites: 2 25 were tested; chi-square tests) revealed numerous risk Active sites: 3 31 factors for 30-day mortality, which were carried for- ward to confirmatory regression analysis. The predic- Active sites: 4 17 tive factors that achieved statistical significance in Active sites: > 4 6 the logistic regression analysis are shown in Table  2. Brain metastases Based on these 9 factors (each assigned 3–6 points), a Single brain metastasis 12 point sum was calculated for each patient. The point Two or three brain metastases 21 sum ranged from 0 (no risk factors for death within Four or five brain metastases 19 30 days present) to 30. The results can be grouped into Six to ten brain metastases 27 3 or 4 risk categories, as displayed in Table 3. Because More than ten brain metastases 21 the model did not perform optimally (Harrell’s C 0.68; Synchronous brain metastases 24 only 10 cases of 30-day mortality were assigned to the Metachronous brain metastases, within 12 months 37 highest risk group; 10 of 28), we provided a complete Metachronous brain metastases, 13–24 months 11 data overview by tabulating the baseline parameters Metachronous brain metastases, 25–36 months 11 of all 28 patients who experienced 30-day mortality Metachronous brain metastases, 37–60 months 8 in Table  4. As illustrated in the table, 4 of 28 patients Metachronous brain metastases, > 60 months 9 (14%) had less than two risk factors. Among them was Asymptomatic brain metastases 9 a 93-year-old patient with uncontrolled lung cancer Symptom response to steroids 64 and hepatic metastases, whose early death would not No response to steroids 27 be considered surprising by most oncologists. This Largest lesion diameter ≤ 2 cm 48 example illustrates that combining a statistical model Largest lesion diameter 2.1–3.0 cm 23 with oncological experience may be a reasonable Largest lesion diameter 3.1–4.0 cm 19 approach. Largest lesion diameter > 4.0 cm 10 Karnofsky performance status (KPS) KPS 50 14 Nieder et al. Radiation Oncology (2022) 17:92 Page 4 of 7 Table 1 (continued) Table 2 Factors predicting 30-day mortality (p < 0.05 in multinominal logistic regression analysis) Baseline parameter Number (= %) Parameter Percent Points KPS 60 30 30-day KPS 70 44 mortality KPS 80 8 LabBM point sum ≥ 3 55 6 KPS 90 4 Karnofsky performance status (KPS) 50 57 6 Treatment Cancer type* 64 6 Primary systemic treatment 7 Extracranial metastases > 3 organ systems** 45 5 Surgery with post-operative cavity radiotherapy 2 Extracranial metastases 3 organ systems*** 40 4 Stereotactic single fraction radiosurgery 6 Bone metastases present 41 4 Stereotactic fractionated radiotherapy 6 Uncontrolled primary tumor 38 4 Whole-brain radiotherapy, 20 Gy in 5 fractions 12 KPS 60 33 3 Whole-brain radiotherapy, 30 Gy in 10 fracions 64 Number of brain metastases > 3 31 3 Whole-brain radiotherapy, higher dose than 30 Gy 3 bladder, gastrointestinal none-colorectal, breast hormone receptor positive Any systemic therapy after diagnosis of brain metas- 34 Her2 negative tases ** example liver, lung, bone, adrenal glands Age, years *** example skin, peritoneum, pleura < 60 18 60–69 40 70–79 35 Table 3 Point sum leading to the final prediction model 80–89 5 Point sum Number of cases Percent 30-day mortality ≥ 90 2 Extracranial score (EC-S; LDH, albumin, extracranial involvement of at 0–8 3/43 7 least 2 organs, e.g. bone + liver) 9 1/3 All 3 adverse factors present 9 10 2/6 Two of these factors present 42 11 3/10 One of these factors present 36 12 0/2 29 (9–12 points combined) No adverse factors present 13 13 3/7 LabBM score (5 blood test results) 14 5/10 LabBM score 0 (favorable) 15 15 0/3 LabBM score 0.5 7 16 1/4 38 (13–16 points combined) LabBM score 1.0 17 17 2/3 LabBM score 1.5 21 18–30 8/9 83 (17–30 points combined) LabBM score 2.0 14 The two patients with 17–30 points who survived beyond 30 days died after 1.9 LabBM score 2.5 15 and 2.0 months, respectively LabBM score 3.0 9 Harrell’s C of 0.68 was higher than that of LabBM alone (0.61) and EC-S alone (0.60) LabBM score 3.5 2 LDH lactate dehydrogenase progressive after previous treatment or not yet treated ** represents very short survival. We hoped that an examples uncontrolled primary tumor or liver metastases, irrespective of number and size in-depth analysis of a limited number of real-world patients treated with different standard approaches might pave the way towards clinically applicable risk Discussion stratification, provided external validation of the result - After more than a decade of partially successful ing model will be successful. attempts by our group to develop and validate mod- As demonstrated in the Results section, 30-day mor- els that predict short survival after treatment of brain tality is a highly multifactorial event. Patient-, intra- and metastases, the present study represents a rigorous extracranial disease-related risk factors were identified, effort with modified methodology. We increased the e.g. KPS, number of brain metastases, pattern and extent number of evaluated variables, selected a narrowly of extracranial metastases, and blood test results. Inter- defined cohort of patients with maximum survival of estingly, age was not associated with 30-day mortality, 3  months, and focused primarily on a dichotomized despite its well-known prognostic impact in analyses that outcome (30-day mortality yes/no), which undoubtedly N ieder et al. Radiation Oncology (2022) 17:92 Page 5 of 7 Table 4 Factors indicating poor prognosis (bold text) in all 28 patients who died within 30 days. Typically, at least twofactors were present, e.g. poor performance status and numerous brain metastases. Four patients had less than two factors Cancer type RT Incomplete PT control Non-brain Active KPS Number Symptoms Int (mo.) Age (yrs.) EC-S LabBM OS (mo.) Cause of death Factors <2 metastases sites incl. (brain) primary Esophagus WB30 1 1 hep, oss, lym 3 6 3 1 6 70 2 2.5 0.3 extracran Melanoma WB30 0 0 pul, hep, lym 4 6 5 1 0 62 1 0 0.8 intracran NSCLC WB30 1 0 pul, hep, adr, oss, lym 5 8 2 1 0 69 1 0 0.4 extracran Jejunum WB20 0 0 pul, hep, adr, oth 5 7 6 1 0 67 3 3 1.0 extracran NSCLC WB20 0 0 pul, adr, oss, lym 5 5 2 0 0 63 3 3 0.5 extracran NSCLC WB20 0 0 0 1 6 4 1 5 69 1 1.5 0.4 unk NSCLC WB20 0 1 oss, adr, oth 3 5 7 1 3 64 2 2.5 0.6 extracran Kidney WB30 1 0 hep, oss, adr, pul 5 6 5 1 2 56 2 2 0.6 unk NSCLC WB30 0 1 pul 1 5 6 1 3 55 1 1.5 0.8 unk Kidney WB30 1 0 oss, pul 3 6 4 1 35 63 2 1.5 0.1 extracran NSCLC WB30 0 0 pul 2 6 4 1 4 66 2 3 0.7 extracran ER + Her2 - WB30 0 1 pul, lym, adr 3 7 7 1 70 67 1 0 1.0 extracran NSCLC WB30 0 0 adr, oss 3 7 17 1 0 53 2 1 1.0 extracran NSCLC WB20 0 0 hep, adr, lym 4 5 4 0 5 65 3 3 0.7 extracran Bladder WB30 0 1 oss, adr, lym 3 7 2 1 38 74 1 1.5 0.7 unk <2 NSCLC WB20 0 1 pul 1 7 4 1 22 65 1 1.5 0.5 extracran <2 Melanoma WB30 0 1 pul, oss, lym 3 7 18 1 8 77 2 1 1.0 intracran Bladder WB30 0 0 pul, oss, lym 4 6 9 1 25 75 1 2 1.0 extracran Melanoma WB30 0 1 pul, lym, ski 3 5 6 1 6 55 3 1.5 0.7 unk NSCLC SRS 0 1 Pul 1 7 1 1 3 75 1 2 0.8 extracran <2 ER+ Her2- WB30 1 1 hep, pul, oss, oth 4 5 12 1 154 74 3 3 0.3 unk SCLC CTx 1 0 Oss 2 6 50 1 0 82 0 0 0.1 unk Esophagus WB30 1 1 lym, adr, oss 3 5 8 1 6 72 2 1 0.1 unk NSCLC SFRT 0 0 hep, oss, pul 4 5 1 1 0 66 3 3 0.7 extracran NSCLC SFRT 1 0 hep, pul 3 7 1 1 0 93 2 2.5 0.1 extracran <2 Rectum WB30 1 0 pul, lym, oth 4 6 10 1 10 48 1 1.5 0.1 extracran NSCLC WB30 0 0 0 1 6 5 1 0 76 0 0.5 0.7 extracran NSCLC WB30 0 0 hep, oss 3 7 4 1 18 51 2 2 0.7 extracran Bold text is utilized to identify those parameters that indicate a poor prognosis. Regular text indicates parameters unrelated to prognosis RT radiotherapy, PT primary tumor, KPS Karnofsky performance status, Int time interval between cancer diagnosis and brain metastases, EC-S extracranial score, LabBM LabBM score, OS overall survival. NSCLC non-small cell lung cancer, ER + Her2- breast cancer (estrogen receptor positive, Her2 negative), SCLC small cell lung cancer, WB30 whole-brain radiotherapy 30 Gy, WB20 whole-brain radiotherapy 20 Gy, SRS radiosurgery, CTx chemotherapy, SFRT stereotactic fractionated radiotherapy, hep liver, oss bone, lym lymphatic, pul lung, adr adrenal glands, oth other, ski skin, unk extracranial progression, but brain metastases might have contributed as well. Nieder et al. Radiation Oncology (2022) 17:92 Page 6 of 7 looked at complete Kaplan–Meier curves [3, 4]. Given patients with hormone receptor-positive Her2-negative that the model did not identify or explain all instances of disease were at high risk, while those with triple negative 30-day mortality, the real picture is probably even more disease were not. Accidental findings and overfitting of complicated. This is also illustrated by the example of the data are of concern as long as validation results are lack- 93-year-old patient included in Table  4. Reality might ing. In addition, limitations include the single-institution in fact be too complex to replace clinical judgement by design and the uncertainty about the cause of death in a partially helpful models. On the other hand, a large pro- proportion of patients. For validation studies, it would portion of patients in the highest risk group (> 16 points) also be desirable to include intracranial tumor volume died within 30  days, and none survived for more than and additional surrogate markers of poor survival, e.g. 2 months. Therefore, the model could be regarded as one hypercalcemia or cancer-related pericardial effusion or of several components of decision making. As also evi- ascites. There are different ways of measuring radio- or dent from Table  4, no more than two of these 28 early chemotherapy utilization near the end of life, e.g. 30-day deaths can be considered relatively unexpected. Causes mortality calculated from start of treatment, 30-day mor- such as accident, suicide or sudden cardiac death were tality calculated from end of treatment, or treatment in not recorded. the last 30  days of life. Regardless of this study’s limita- It is also important to realize that 30-day mortality tions and the unique patient selection, the topic of active rarely was caused by the brain metastases themselves, treatment in the terminal phase of cancer continues to be although a certain number of patients had causes of important for patients and providers alike [21–24]. death that remained difficult to assign. Only 5 of 100 patients did not harbor active extracranial disease, while more than 50% had at least 3 sites. In this context, one Conclusion should note that we did not account for the number and Extracranial tumor progression was the prevailing cause size of organ lesions. Both, single bone metastases and of 30-day mortality and few, if any deaths could be con- widespread involvement were grouped under the same sidered relatively unexpected when looking at the com- label (bone metastases present). Maybe, a more nuanced plete oncological picture. We were able to develop a assessment would improve the predictive model. On the multifactorial prediction model. However, the model’s other hand, there is reason to believe that the LabBM performance was not fully satisfactory and it is not rou- score reflects the extracranial disease burden [16]. As tinely applicable at this point in time, because external suggested from our regression analysis, several meas- validation is needed to confirm our hypothesis-generat - ures of extracranial disease activity contributed relevant ing findings. information. A different group conducted a retrospective study Abbreviations of patients evaluated for palliative radiotherapy (dif- PS: Performance status; DS-GPA: Diagnosis-specific graded prognostic ferent indications) from 2017 to 2019 who died within assessment; EC-GPA: Extracranial-graded prognostic assessment score; WBRT: Whole-brain radiotherapy; SRS: Stereotactic radiosurgery; LDH: Lactate dehy- 90  days of consultation [20]. Data were collected for drogenase; NSCLC: Non-small cell lung cancer. the TEACHH and Chow models and one point was assigned for each adverse factor. The TEACHH model Acknowledgements Not applicable. included primary site of disease, PS, age, prior palliative chemotherapy courses, hospitalization within the last Author contributions 3 months, and presence of hepatic metastases. The Chow CN, LS, SGA and BM analyzed and interpreted the patient data. CN and ECH drafted the manuscript. All authors read and approved the final manuscript. model included non-breast primary, site of metasta- ses other than bone only, and PS. A total of 505 patients Funding with a median overall survival of 2.1  months were stud- Open Access funding provided by UiT The Arctic University of Norway The publication charges for this article have been funded by a grant from the ied. Based on the TEACHH model, 2%, 77% and 21% publication fund of UiT The Arctic University of Norway. were predicted to live > 1  year, > 3  months to ≤ 1  year, and ≤ 3  months, respectively. Utilizing the Chow model, Availability of data and materials The dataset supporting the conclusions of this article is available at request 21%, 50% and 29% were expected to live 15.0, 6.5, and from the corresponding author, if intended to be used for meta-analyses. 2.3  months, respectively. Thus, neither model cor - rectly predict prognosis in a patient population with a Declarations sur vival < 3 months. External validation of our results in a larger study is Ethics approval and consent to participate As a retrospective quality of care analysis, no approval from the Regional Com- necessary, given that some of the findings are surprising mittee for Medical and Health Research Ethics (REK Nord) was necessary. This and based on small numbers. For example, breast cancer N ieder et al. Radiation Oncology (2022) 17:92 Page 7 of 7 research project was carried out according to our institutions’ guidelines and 13. Nieder C, Marienhagen K, Thamm R, Astner ST, Molls M, Norum J. Predic- with permission to access the patients’ data. tion of very short survival in patients with brain metastases from breast cancer. Clin Oncol (R Coll Radiol). 2008;20:337–9. https:// doi. org/ 10. Consent for publication1016/j. clon. 2008. 03. 005. Not applicable. 14. Nieder C, Yobuta R, Mannsåker B. Expansion of the LabBM score: is the LabPS the best tool predicting survival in patients with brain metastases? Competing interests Am J Clin Oncol. 2021;44:53–7. https:// doi. org/ 10. 1097/ COC. 00000 00000 SGA has received lecture fees from Bristol Myer Squibb and Astra Zeneca. All 000784. other authors declare no conflict of interest. 15. Nieder C, Hess S, Lewitzki V. External validation of a prognostic score for patients with brain metastases: extended diagnosis-specific graded Author details prognostic assessment. Oncol Res Treat. 2020;43:221–7. https:// doi. org/ Department of Oncology and Palliative Medicine, Nordland Hospital, 10. 1159/ 00050 6954. 8092 Bodø, Norway. 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30-day mortality in patients treated for brain metastases: extracranial causes dominate

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Abstract

Background: Established prognostic models, such as the diagnosis-specific graded prognostic assessment, were not designed to specifically address very short survival. Therefore, a brain metastases-specific 30-day mortality model may be relevant. We hypothesized that in-depth evaluation of a carefully defined cohort with short survival, arbitrarily defined as a maximum of 3 months, may provide signals and insights, which facilitate the development of a 30-day mortality model. Methods: Retrospective analysis (2011–2021) of patients treated for brain metastases with different approaches. Risk factors for 30-day mortality from radiosurgery or other primary treatment were evaluated. Results: The cause of death was unrelated to brain metastases in 61%. Treatment-related death (grade 5 toxicity) did not occur. Completely unexpected death was not observed, e.g. accident, suicide or sudden cardiac death. Logistic regression analysis showed 9 factors associated with 30-day mortality (each assigned 3–6 points) and a point sum was calculated for each patient. The point sum ranged from 0 (no risk factors for death within 30 days present) to 30. The results can be grouped into 3 or 4 risk categories. Eighty-three percent of patients in the highest risk group (> 16 points) died within 30 days, and none survived for more than 2 months. However, many cases of 30-day mortal- ity (more than half ) occurred in intermediate risk categories. Conclusion: Extracranial tumor progression was the prevailing cause of 30-day mortality and few, if any deaths could be considered relatively unexpected when looking at the complete oncological picture. We were able to develop a multifactorial prediction model. However, the model’s performance was not fully satisfactory and it is not routinely applicable at this point in time, because external validation is needed to confirm our hypothesis-generating findings. Keywords: Palliative radiation therapy, Stereotactic radiotherapy, Brain metastases, Prognostic factors, Biomarkers Background survival (typically if oligometastases are present [2]) Most patients with brain metastases from extracranial and shorter survival may be observed, and considerable primary tumors such as lung or breast cancer receive pal- efforts have been undertaken to predict survival (nomo - liative treatment approaches, because the common pat- grams, scores, online calculators [3–5]). Given that very tern of polymetastatic spread may cause compromised short survival often is synonymous to active treatment in performance status (PS) and eventually also limited sur- the last 30  days of life, oncologists can opt for palliative vival, often in the range of 3–9  months [1]. Both, longer and supportive care rather than brain-directed therapy [6]. Supposing they choose brain-directed therapy, the challenge is to navigate a complex scenario of low-value care, potential overtreatment and futile, but costly proce- *Correspondence: carsten.nieder@nlsh.no dures [7, 8]. Department of Oncology and Palliative Medicine, Nordland Hospital, Prognostic models familiar to many providers, such 8092 Bodø, Norway Full list of author information is available at the end of the article as the diagnosis-specific graded prognostic assessment © The Author(s) 2022. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/. The Creative Commons Public Domain Dedication waiver (http:// creat iveco mmons. org/ publi cdoma in/ zero/1. 0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Nieder et al. Radiation Oncology (2022) 17:92 Page 2 of 7 (DS-GPA) [3], were not designed to specifically address include patients who received their second treatment, very short survival. Different definitions of very short e.g. delayed salvage WBRT after previous SRS. Patients survival may be applied, including 30-day mortality, with leptomeningeal central nervous system metastases which has been evaluated in numerous oncology set- and those managed with best supportive care after diag- tings [9, 10]. General survival prediction models such nosis of brain metastases were not included. The data - as TEACHH may also be utilized [11, 12], but it is still base includes patients with solid tumors only, whereas unclear whether a brain metastases-specific 30-day mor - those with leukemia and lymphoma are excluded. For tality model should be preferred. Our group has previ- the purpose of this exploratory, hypothesis-generating ously studied different models that predict very short study, a cohort size of n = 100 was deemed appropri- survival (not specifically focused on 30 days), but none of ate. We felt that there was no solid fundament for these was considered truly satisfactory [13–15]. The fact statistical hypotheses or power calculations in the plan- that many patients with poor prognosis were not iden- ning process. Starting with recent patients treated in tified by any model was considered a major challenge. 2021, backward inclusion of consecutive patients was Ideally, a model would identify all or almost all patients employed. The target size of 100 patients was reached with very short survival, and simultaneously, patients when including patients treated in the year 2011. predicted to die early would not survive long enough to Besides established baseline parameters such as age, benefit from active treatment. In other words, both over- sex, number of brain metastases and Karnofsky PS, and undertreatment should be avoided, because shorten- blood test results were included (hemoglobin, plate- ing survival by withholding treatment would be a serious lets, C-reactive protein, albumin, lactate dehydrogenase threat too. (LDH); the components of the LabBM score, which These reflections are also applicable to the recently was assigned as originally recommended [16]). These introduced LabPS score (blood test results and PS) [14], were also employed to assign the LDH/albumin-based where the group with the poorest prognosis (3 or 3.5 extracranial score (EC-S) [15]. The pattern and num - points; maximum survival 2.1  months) was very small ber of extracranial sites was registered (uncontrolled (4% of all patients in the study). Most patients with com- primary tumor, liver, lung, bone and other extracra- parably short survival had a lower point sum. The LabPS nial metastases; standard staging considered appropri- score failed to outperform the previously proposed ate by the treating physicians at the time of treatment, extracranial-graded prognostic assessment score (EC- thus subject to temporal and cancer-type-related vari- GPA) [15]. Median survival was 0.7 months in the worst ation [17]). Most likely, the blood test results mirror prognostic group of the latter score, with a hazard ratio the overall burden of disease, including lesions not cor- for death of 44 (95% confidence interval (CI), 6–340) rectly identified on radiological examinations [16, 17]. compared to the best group. However, many patients The total number of brain metastases was derived from with short survival were not assigned to the worst group. magnetic resonance imaging (MRI) reports. Cumula- After these previous, only partially successful studies that tive lesion volume was not available. included all-comers, we changed our methodology, went Cause of death was recorded in order to account for back to the drawing board and hypothesized that in- surprising, unpredictable events such as accidents. Chi- depth evaluation of a carefully defined cohort with short square tests were employed to identify factors predict- survival, arbitrarily defined as a maximum of 3  months, ing 30-day mortality (30  days from SRS, first fraction may provide signals and insights, which facilitate the of WBRT, day 1 of chemotherapy etc.). The latter were development of viable 30-day mortality models. further examined in multinominal logistic regression analysis. Statistical significance was defined as p < 0.05 in two-sided tests. The methods employed by Rades Patients and methods et  al. were utilized to calculate a point sum reflective A previously described, continuously updated quality- of 30-day mortality [18, 19]. For example, a risk fac- of-care database covering all adult patients with brain tor associated with 50% 30-day mortality was assigned metastases at the authors’ institution, which employs 5 points, while 3 points were assigned for a factor electronic health records containing detailed follow-up associated with 30% 30-day mortality. The predictive information, was utilized [14]. The cohort was limited accuracy of our model was evaluated using Harrell’s to patients who survived ≤ 3.0 months from commenc- concordance index (Harell’s C). Harrell’s C shows per- ing their first treatment (start of primary whole-brain fect concordance if the value is 1, whilst a value of 0.5 radiotherapy (WBRT), date of radiosurgery (SRS), start indicates completely random concordance (an unser- of systemic treatment etc.), whether treatment was viceable model in other words). completed or not (intention-to-treat). The study did not N ieder et al. Radiation Oncology (2022) 17:92 Page 3 of 7 Table 1 Patient characteristics, n = 100 Results The most common treatment approach was WBRT Baseline parameter Number (= %) (30 Gy in 10 fractions, 64%; 20 Gy in 5 fractions, 12%). Sex Eighteen percent of all patients failed to complete their Female sex 46 prescribed treatment. Common tumor types included Male sex 54 non-small cell lung cancer (NSCLC, 42%), malignant Tumor type melanoma (12%) and breast cancer (11%). Detailed Non-small cell lung cancer 42 baseline characteristics are shown in Table  1. The Breast cancer, triple negative 3 30-day mortality was 28% and an additional 39% died Breast cancer, Her2 positive 4 between 31 and 60 days. Breast cancer, other 4 The cause of death was unrelated to brain metas- Malignant melanoma 12 tases in 61%. Both, extracranial metastases and Small cell lung cancer 9 uncontrolled primary tumors leading for example to Renal cell cancer 8 hemoptysis or refractory pneumonia were among the Colorectal cancer 10 documented causes of death. Brain metastases may Other gastrointestinal cancer 5 have contributed to death in 32% (uncertainty because Other primary tumors (bladder, head/neck) 3 the patients died at home or in nursing homes; no Extracranial disease firm documentation about the last days in our elec- No extracranial metastases 9 tronic patient records; both intra- and extracranial Extracranial metastases 91 tumor activity was recorded before hospital care was Bone metastases 37 terminated). Definitive confirmation of brain-related Liver metastases 38 death was available in the remaining 7%, including one Lung/pleura metastases 56 patient who died from hemorrhage. Treatment-related Controlled primary tumor 55 death (grade 5 toxicity) did not occur. Completely Uncontrolled primary tumor* 45 unexpected death was not observed, e.g. accident or Active organ sites incl. uncontrolled primary tumor: 0 5 suicide. Active sites: 1** 16 Univariate analyses (all factors included in Table  1 Active sites: 2 25 were tested; chi-square tests) revealed numerous risk Active sites: 3 31 factors for 30-day mortality, which were carried for- ward to confirmatory regression analysis. The predic- Active sites: 4 17 tive factors that achieved statistical significance in Active sites: > 4 6 the logistic regression analysis are shown in Table  2. Brain metastases Based on these 9 factors (each assigned 3–6 points), a Single brain metastasis 12 point sum was calculated for each patient. The point Two or three brain metastases 21 sum ranged from 0 (no risk factors for death within Four or five brain metastases 19 30 days present) to 30. The results can be grouped into Six to ten brain metastases 27 3 or 4 risk categories, as displayed in Table 3. Because More than ten brain metastases 21 the model did not perform optimally (Harrell’s C 0.68; Synchronous brain metastases 24 only 10 cases of 30-day mortality were assigned to the Metachronous brain metastases, within 12 months 37 highest risk group; 10 of 28), we provided a complete Metachronous brain metastases, 13–24 months 11 data overview by tabulating the baseline parameters Metachronous brain metastases, 25–36 months 11 of all 28 patients who experienced 30-day mortality Metachronous brain metastases, 37–60 months 8 in Table  4. As illustrated in the table, 4 of 28 patients Metachronous brain metastases, > 60 months 9 (14%) had less than two risk factors. Among them was Asymptomatic brain metastases 9 a 93-year-old patient with uncontrolled lung cancer Symptom response to steroids 64 and hepatic metastases, whose early death would not No response to steroids 27 be considered surprising by most oncologists. This Largest lesion diameter ≤ 2 cm 48 example illustrates that combining a statistical model Largest lesion diameter 2.1–3.0 cm 23 with oncological experience may be a reasonable Largest lesion diameter 3.1–4.0 cm 19 approach. Largest lesion diameter > 4.0 cm 10 Karnofsky performance status (KPS) KPS 50 14 Nieder et al. Radiation Oncology (2022) 17:92 Page 4 of 7 Table 1 (continued) Table 2 Factors predicting 30-day mortality (p < 0.05 in multinominal logistic regression analysis) Baseline parameter Number (= %) Parameter Percent Points KPS 60 30 30-day KPS 70 44 mortality KPS 80 8 LabBM point sum ≥ 3 55 6 KPS 90 4 Karnofsky performance status (KPS) 50 57 6 Treatment Cancer type* 64 6 Primary systemic treatment 7 Extracranial metastases > 3 organ systems** 45 5 Surgery with post-operative cavity radiotherapy 2 Extracranial metastases 3 organ systems*** 40 4 Stereotactic single fraction radiosurgery 6 Bone metastases present 41 4 Stereotactic fractionated radiotherapy 6 Uncontrolled primary tumor 38 4 Whole-brain radiotherapy, 20 Gy in 5 fractions 12 KPS 60 33 3 Whole-brain radiotherapy, 30 Gy in 10 fracions 64 Number of brain metastases > 3 31 3 Whole-brain radiotherapy, higher dose than 30 Gy 3 bladder, gastrointestinal none-colorectal, breast hormone receptor positive Any systemic therapy after diagnosis of brain metas- 34 Her2 negative tases ** example liver, lung, bone, adrenal glands Age, years *** example skin, peritoneum, pleura < 60 18 60–69 40 70–79 35 Table 3 Point sum leading to the final prediction model 80–89 5 Point sum Number of cases Percent 30-day mortality ≥ 90 2 Extracranial score (EC-S; LDH, albumin, extracranial involvement of at 0–8 3/43 7 least 2 organs, e.g. bone + liver) 9 1/3 All 3 adverse factors present 9 10 2/6 Two of these factors present 42 11 3/10 One of these factors present 36 12 0/2 29 (9–12 points combined) No adverse factors present 13 13 3/7 LabBM score (5 blood test results) 14 5/10 LabBM score 0 (favorable) 15 15 0/3 LabBM score 0.5 7 16 1/4 38 (13–16 points combined) LabBM score 1.0 17 17 2/3 LabBM score 1.5 21 18–30 8/9 83 (17–30 points combined) LabBM score 2.0 14 The two patients with 17–30 points who survived beyond 30 days died after 1.9 LabBM score 2.5 15 and 2.0 months, respectively LabBM score 3.0 9 Harrell’s C of 0.68 was higher than that of LabBM alone (0.61) and EC-S alone (0.60) LabBM score 3.5 2 LDH lactate dehydrogenase progressive after previous treatment or not yet treated ** represents very short survival. We hoped that an examples uncontrolled primary tumor or liver metastases, irrespective of number and size in-depth analysis of a limited number of real-world patients treated with different standard approaches might pave the way towards clinically applicable risk Discussion stratification, provided external validation of the result - After more than a decade of partially successful ing model will be successful. attempts by our group to develop and validate mod- As demonstrated in the Results section, 30-day mor- els that predict short survival after treatment of brain tality is a highly multifactorial event. Patient-, intra- and metastases, the present study represents a rigorous extracranial disease-related risk factors were identified, effort with modified methodology. We increased the e.g. KPS, number of brain metastases, pattern and extent number of evaluated variables, selected a narrowly of extracranial metastases, and blood test results. Inter- defined cohort of patients with maximum survival of estingly, age was not associated with 30-day mortality, 3  months, and focused primarily on a dichotomized despite its well-known prognostic impact in analyses that outcome (30-day mortality yes/no), which undoubtedly N ieder et al. Radiation Oncology (2022) 17:92 Page 5 of 7 Table 4 Factors indicating poor prognosis (bold text) in all 28 patients who died within 30 days. Typically, at least twofactors were present, e.g. poor performance status and numerous brain metastases. Four patients had less than two factors Cancer type RT Incomplete PT control Non-brain Active KPS Number Symptoms Int (mo.) Age (yrs.) EC-S LabBM OS (mo.) Cause of death Factors <2 metastases sites incl. (brain) primary Esophagus WB30 1 1 hep, oss, lym 3 6 3 1 6 70 2 2.5 0.3 extracran Melanoma WB30 0 0 pul, hep, lym 4 6 5 1 0 62 1 0 0.8 intracran NSCLC WB30 1 0 pul, hep, adr, oss, lym 5 8 2 1 0 69 1 0 0.4 extracran Jejunum WB20 0 0 pul, hep, adr, oth 5 7 6 1 0 67 3 3 1.0 extracran NSCLC WB20 0 0 pul, adr, oss, lym 5 5 2 0 0 63 3 3 0.5 extracran NSCLC WB20 0 0 0 1 6 4 1 5 69 1 1.5 0.4 unk NSCLC WB20 0 1 oss, adr, oth 3 5 7 1 3 64 2 2.5 0.6 extracran Kidney WB30 1 0 hep, oss, adr, pul 5 6 5 1 2 56 2 2 0.6 unk NSCLC WB30 0 1 pul 1 5 6 1 3 55 1 1.5 0.8 unk Kidney WB30 1 0 oss, pul 3 6 4 1 35 63 2 1.5 0.1 extracran NSCLC WB30 0 0 pul 2 6 4 1 4 66 2 3 0.7 extracran ER + Her2 - WB30 0 1 pul, lym, adr 3 7 7 1 70 67 1 0 1.0 extracran NSCLC WB30 0 0 adr, oss 3 7 17 1 0 53 2 1 1.0 extracran NSCLC WB20 0 0 hep, adr, lym 4 5 4 0 5 65 3 3 0.7 extracran Bladder WB30 0 1 oss, adr, lym 3 7 2 1 38 74 1 1.5 0.7 unk <2 NSCLC WB20 0 1 pul 1 7 4 1 22 65 1 1.5 0.5 extracran <2 Melanoma WB30 0 1 pul, oss, lym 3 7 18 1 8 77 2 1 1.0 intracran Bladder WB30 0 0 pul, oss, lym 4 6 9 1 25 75 1 2 1.0 extracran Melanoma WB30 0 1 pul, lym, ski 3 5 6 1 6 55 3 1.5 0.7 unk NSCLC SRS 0 1 Pul 1 7 1 1 3 75 1 2 0.8 extracran <2 ER+ Her2- WB30 1 1 hep, pul, oss, oth 4 5 12 1 154 74 3 3 0.3 unk SCLC CTx 1 0 Oss 2 6 50 1 0 82 0 0 0.1 unk Esophagus WB30 1 1 lym, adr, oss 3 5 8 1 6 72 2 1 0.1 unk NSCLC SFRT 0 0 hep, oss, pul 4 5 1 1 0 66 3 3 0.7 extracran NSCLC SFRT 1 0 hep, pul 3 7 1 1 0 93 2 2.5 0.1 extracran <2 Rectum WB30 1 0 pul, lym, oth 4 6 10 1 10 48 1 1.5 0.1 extracran NSCLC WB30 0 0 0 1 6 5 1 0 76 0 0.5 0.7 extracran NSCLC WB30 0 0 hep, oss 3 7 4 1 18 51 2 2 0.7 extracran Bold text is utilized to identify those parameters that indicate a poor prognosis. Regular text indicates parameters unrelated to prognosis RT radiotherapy, PT primary tumor, KPS Karnofsky performance status, Int time interval between cancer diagnosis and brain metastases, EC-S extracranial score, LabBM LabBM score, OS overall survival. NSCLC non-small cell lung cancer, ER + Her2- breast cancer (estrogen receptor positive, Her2 negative), SCLC small cell lung cancer, WB30 whole-brain radiotherapy 30 Gy, WB20 whole-brain radiotherapy 20 Gy, SRS radiosurgery, CTx chemotherapy, SFRT stereotactic fractionated radiotherapy, hep liver, oss bone, lym lymphatic, pul lung, adr adrenal glands, oth other, ski skin, unk extracranial progression, but brain metastases might have contributed as well. Nieder et al. Radiation Oncology (2022) 17:92 Page 6 of 7 looked at complete Kaplan–Meier curves [3, 4]. Given patients with hormone receptor-positive Her2-negative that the model did not identify or explain all instances of disease were at high risk, while those with triple negative 30-day mortality, the real picture is probably even more disease were not. Accidental findings and overfitting of complicated. This is also illustrated by the example of the data are of concern as long as validation results are lack- 93-year-old patient included in Table  4. Reality might ing. In addition, limitations include the single-institution in fact be too complex to replace clinical judgement by design and the uncertainty about the cause of death in a partially helpful models. On the other hand, a large pro- proportion of patients. For validation studies, it would portion of patients in the highest risk group (> 16 points) also be desirable to include intracranial tumor volume died within 30  days, and none survived for more than and additional surrogate markers of poor survival, e.g. 2 months. Therefore, the model could be regarded as one hypercalcemia or cancer-related pericardial effusion or of several components of decision making. As also evi- ascites. There are different ways of measuring radio- or dent from Table  4, no more than two of these 28 early chemotherapy utilization near the end of life, e.g. 30-day deaths can be considered relatively unexpected. Causes mortality calculated from start of treatment, 30-day mor- such as accident, suicide or sudden cardiac death were tality calculated from end of treatment, or treatment in not recorded. the last 30  days of life. Regardless of this study’s limita- It is also important to realize that 30-day mortality tions and the unique patient selection, the topic of active rarely was caused by the brain metastases themselves, treatment in the terminal phase of cancer continues to be although a certain number of patients had causes of important for patients and providers alike [21–24]. death that remained difficult to assign. Only 5 of 100 patients did not harbor active extracranial disease, while more than 50% had at least 3 sites. In this context, one Conclusion should note that we did not account for the number and Extracranial tumor progression was the prevailing cause size of organ lesions. Both, single bone metastases and of 30-day mortality and few, if any deaths could be con- widespread involvement were grouped under the same sidered relatively unexpected when looking at the com- label (bone metastases present). Maybe, a more nuanced plete oncological picture. We were able to develop a assessment would improve the predictive model. On the multifactorial prediction model. However, the model’s other hand, there is reason to believe that the LabBM performance was not fully satisfactory and it is not rou- score reflects the extracranial disease burden [16]. As tinely applicable at this point in time, because external suggested from our regression analysis, several meas- validation is needed to confirm our hypothesis-generat - ures of extracranial disease activity contributed relevant ing findings. information. A different group conducted a retrospective study Abbreviations of patients evaluated for palliative radiotherapy (dif- PS: Performance status; DS-GPA: Diagnosis-specific graded prognostic ferent indications) from 2017 to 2019 who died within assessment; EC-GPA: Extracranial-graded prognostic assessment score; WBRT: Whole-brain radiotherapy; SRS: Stereotactic radiosurgery; LDH: Lactate dehy- 90  days of consultation [20]. Data were collected for drogenase; NSCLC: Non-small cell lung cancer. the TEACHH and Chow models and one point was assigned for each adverse factor. The TEACHH model Acknowledgements Not applicable. included primary site of disease, PS, age, prior palliative chemotherapy courses, hospitalization within the last Author contributions 3 months, and presence of hepatic metastases. The Chow CN, LS, SGA and BM analyzed and interpreted the patient data. CN and ECH drafted the manuscript. All authors read and approved the final manuscript. model included non-breast primary, site of metasta- ses other than bone only, and PS. A total of 505 patients Funding with a median overall survival of 2.1  months were stud- Open Access funding provided by UiT The Arctic University of Norway The publication charges for this article have been funded by a grant from the ied. Based on the TEACHH model, 2%, 77% and 21% publication fund of UiT The Arctic University of Norway. were predicted to live > 1  year, > 3  months to ≤ 1  year, and ≤ 3  months, respectively. Utilizing the Chow model, Availability of data and materials The dataset supporting the conclusions of this article is available at request 21%, 50% and 29% were expected to live 15.0, 6.5, and from the corresponding author, if intended to be used for meta-analyses. 2.3  months, respectively. Thus, neither model cor - rectly predict prognosis in a patient population with a Declarations sur vival < 3 months. External validation of our results in a larger study is Ethics approval and consent to participate As a retrospective quality of care analysis, no approval from the Regional Com- necessary, given that some of the findings are surprising mittee for Medical and Health Research Ethics (REK Nord) was necessary. This and based on small numbers. For example, breast cancer N ieder et al. Radiation Oncology (2022) 17:92 Page 7 of 7 research project was carried out according to our institutions’ guidelines and 13. Nieder C, Marienhagen K, Thamm R, Astner ST, Molls M, Norum J. Predic- with permission to access the patients’ data. tion of very short survival in patients with brain metastases from breast cancer. Clin Oncol (R Coll Radiol). 2008;20:337–9. https:// doi. org/ 10. Consent for publication1016/j. clon. 2008. 03. 005. Not applicable. 14. Nieder C, Yobuta R, Mannsåker B. Expansion of the LabBM score: is the LabPS the best tool predicting survival in patients with brain metastases? Competing interests Am J Clin Oncol. 2021;44:53–7. https:// doi. org/ 10. 1097/ COC. 00000 00000 SGA has received lecture fees from Bristol Myer Squibb and Astra Zeneca. All 000784. other authors declare no conflict of interest. 15. Nieder C, Hess S, Lewitzki V. External validation of a prognostic score for patients with brain metastases: extended diagnosis-specific graded Author details prognostic assessment. Oncol Res Treat. 2020;43:221–7. https:// doi. org/ Department of Oncology and Palliative Medicine, Nordland Hospital, 10. 1159/ 00050 6954. 8092 Bodø, Norway. Department of Clinical Medicine, Faculty of Health Sci- 16. Berghoff AS, Wolpert F, Holland-Letz T, Koller R, Widhalm G, Gatterbauer ences, UiT—The Arctic University of Norway, Tromsö, Norway. Depar tment B, et al. Combining standard clinical blood values for improving survival of Quality and Health Technology, Faculty of Health Sciences, SHARE—Center prediction in patients with newly diagnosed brain metastases–develop- for Resilience in Healthcare, University of Stavanger, Stavanger, Norway. ment and validation of the LabBM score. Neuro Oncol. 2017;19:1255–62. https:// doi. org/ 10. 1093/ neuonc/ now290. Received: 21 January 2022 Accepted: 1 May 2022 17. Nieder C, Mehta MP, Guckenberger M, Gaspar LE, Rusthoven CG, Sahgal A, et al. Assessment of extracranial metastatic disease in patients with brain metastases: how much effort is needed in the context of evolving survival prediction models? Radiother Oncol. 2021;159:17–20. https:// doi. org/ 10. 1016/j. radonc. 2021. 02. 038. 18. 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Journal

Radiation OncologySpringer Journals

Published: May 12, 2022

Keywords: Palliative radiation therapy; Stereotactic radiotherapy; Brain metastases; Prognostic factors; Biomarkers

References