How radiation oncologists evaluate and incorporate life expectancy estimates into the treatment of palliative cancer patients: a survey-based study

'Perspectives of pulmonologists and thoracic surgeons on Oligometastatic disease: curability, treatment approaches, and disease trajectory'

BACKGROUND

Oligometastatic disease (OMD) is defined by a limited number of metastases, affecting treatment strategies and prognosis. This study evaluates the perspectives of pulmonologists and thoracic surgeons on the curability, treatment approaches, and disease trajectory of synchronous OMD, oligorecurrence, and oligoprogression.

METHODS

A survey was conducted among pulmonologists, thoracic surgeons, and trainees at Yedikule Chest Disease and Thoracic Surgery Research and Training Hospital. Participants provided views on OMD's curability, treatment preferences, and confidence in discussing prognosis using Likert scales. Data were analyzed using descriptive statistics and comparative methods.

RESULTS

Of 160 contacted participants, 60 (37.5%) completed the survey. Most respondents (86.6%) regarded synchronous OMD as curable, with 65% for oligorecurrence and only 23.4% for oligoprogression. Confidence in understanding synchronous OMD's trajectory significantly differed, with attending physicians at 67.9% versus trainees at 43.8% (p < 0.05). Thoracic surgeons had higher confidence in oligorecurrence (88.3%) than pulmonologists (46%, p < 0.05). A preference for combined systemic and local therapies was noted: 73.3% for synchronous OMD, 75% for oligorecurrence, and 78.4% for oligoprogression.

CONCLUSION

The study reveals diverse perspectives on OMD, highlighting the need for multidisciplinary collaboration and ongoing education to improve understanding and management of the disease.

A Practice Model for Palliative Radiotherapy

Despite well-recognized challenges in implementing palliative radiation therapy (PRT), progress remains slow, and conventional approaches have yielded limited success. A transformative strategy is required to overcome systemic barriers and establish a sustainable PRT infrastructure. This proposal presents a novel model to improve accessibility, affordability, and integration into palliative care by addressing key obstacles in training, regulation, facility development, and treatment protocols. A specialized certification track within radiation oncology residency programs is proposed, enabling palliative care physicians to obtain limited PRT licenses under the supervision of fully licensed radiation oncologists. Regulatory adjustments should facilitate this framework, ensuring compliance while expanding the PRT workforce. Dedicated PRT facilities-affiliated with comprehensive radiation therapy centers (CRTCs) and integrated into hospice settings-will enhance accessibility by reducing logistical and financial burdens. These facilities will utilize cost-effective infrastructure, including refurbished linear accelerators, modular construction, and remote physics and dosimetry support, ensuring operational costs remain significantly lower than those of conventional radiotherapy centers. Optimizing PRT delivery requires shifting clinical strategies toward single-fraction treatment as the primary approach, followed by hypofractionation treatment when necessary. Systematic studies with a PRT-oriented mindset should establish PRT-specific treatment recommendations and recommendations, moving away from conventional radiation therapy protocols. By addressing key barriers in education, regulation, infrastructure, and clinical strategy, this model offers a path toward sustainable PRT implementation. While requiring initial investment and regulatory adjustments, it has the potential to improve end-of-life care for terminally ill cancer patients, ensuring greater dignity and comfort while establishing a robust foundation for future reimbursement models.

Palliative Radiotherapy Near the End of Life: An Analysis of Factors Influencing the Administration of Radiotherapy in Advanced Tumor Disease

PURPOSE

Palliative radiotherapy (PRT) toward the end of life (EOL) in advanced tumor disease is contentious. Although EOL RT can alleviate cancer-related symptoms, relief typically occurs weeks to months after treatment, potentially compromising the quality of life of patients during the final stages. This study aims to assess factors influencing the decision-making process regarding EOL RT.

MATERIALS AND METHODS

This retrospective study of a real-world cohort included 684 consecutive patients with a diagnosis of a solid tumor who died between 2017 and 2021. In these patients, factors potentially influencing the administration of EOL RT were analyzed.

RESULTS

Of the 684 patients, 164 received PRT, with 60 (36.6%) receiving EOL RT within the last 30 days of life. The median time from the last RT session to death was 55 days. Significant factors influencing EOL RT administration were age ≤65 years (odds ratio [OR], 1.75 [95% CI, 1.02 to 3.01]), Union for International Cancer Control stage IV (OR, 2.77 [95% CI, 1.41 to 5.46]), lung cancer (OR, 2.16 [95% CI, 1.00 to 4.68]), palliative care referral (OR, 1.80 [95% CI, 0.98 to 3.30]), systemic anticancer treatment ≤30 days before death (OR, 1.87 [95% CI, 1.05 to 3.33]), and Eastern Cooperative Oncology Group performance status ≥2 (OR, 3.73 [95% CI, 1.88 to 7.40]). Furthermore, RT near the EOL was more likely administered at multiple sites (OR, 2.08 [95% CI, 1.00 to 4.29]) and with ≤5 fractions (OR, 2.37 [95% CI, 1.23 to 4.57]), while being associated with lower response rates (OR, 0.43 [95% CI, 0.21 to 0.86]) and increased therapy discontinuation (OR, 4.40 [95% CI, 1.45 to 13.37]).

CONCLUSION

These findings highlight varying RT patterns influenced by specific factors, demonstrating the complexity of EOL treatment decisions in advanced cancer care. Identifying key factors for personalized, patient-centered EOL RT decisions warrants further investigation.

Systemic anticancer therapy near the end of life: an analysis of factors influencing treatment in advanced tumor disease

BACKGROUND

Systemic anticancer treatment (SACT) for advanced cancer patients with limited prognosis before death is associated with high toxicity and reduced quality of life. Guidelines discourage this approach as low-value care. However, a significant number of patients continue to receive SACT in the last 30 days of life.

MATERIALS AND METHODS

A retrospective study was carried out at the University Hospital Krems, encompassing the analysis of patients who were diagnosed with a solid tumor and died between 2017 and 2021, with a particular focus on the use of end-of-life (EOL) SACT.

RESULTS

A total of 685 patients were included in the study. SACT was applied in 342 (49.9%) patients, of whom 143 (41.8%, total population: 20.9%) patients received SACT within the last 30 days of life. Median time from last SACT to death was 44.5 days. The analysis of potential factors impacting the administration of EOL SACT revealed the following significant findings: type of SACT [P < 0.001, targeted therapy odds ratio (OR) 5.09, 95% confidence interval (CI) 2.26-11.48; chemotherapy/targeted therapy OR 3.60, 95% CI 1.47-8.82; immune checkpoint inhibitor OR 2.32, 95% CI 1.37-3.92], no referral to palliative care (PC) (P = 0.009, OR 1.86, 95% CI 1.16-2.96), no admission to PC ward (P < 0.001, OR 2.70, 95% CI 1.67-4.35), and poor Eastern Cooperative Oncology Group (ECOG) performance status (≥2, P < 0.001, OR 3.35, 95% CI 1.93-5.83).

CONCLUSION

The timing of SACT near the EOL is significantly influenced by several factors, including the type of SACT, referral to PC services, admission to PC unit, and ECOG performance status. These findings underscore the complexity of treatment decisions in advanced cancer care and highlight the need for personalized, patient-centered approaches that consider both clinical and patient-related factors to optimize care at the EOL.

Explainable Machine Learning Model to Predict Overall Survival in Patients Treated With Palliative Radiotherapy for Bone Metastases

PURPOSE

The estimation of prognosis and life expectancy is critical in the care of patients with advanced cancer. To aid clinical decision making, we build a prognostic strategy combining a machine learning (ML) model with explainable artificial intelligence to predict 1-year survival after palliative radiotherapy (RT) for bone metastasis.

MATERIALS AND METHODS

Data collected in the multicentric PRAIS trial were extracted for 574 eligible adults diagnosed with metastatic cancer. The primary end point was the overall survival (OS) at 1 year (1-year OS) after the start of RT. Candidate covariate predictors consisted of 13 clinical and tumor-related pre-RT patient characteristics, seven dosimetric and treatment-related variables, and 45 pre-RT laboratory variables. ML models were developed and internally validated using the Python package. The effectiveness of each model was evaluated in terms of discrimination. A Shapley Additive Explanations (SHAP) explainability analysis to infer the global and local feature importance and to understand the reasons for correct and misclassified predictions was performed.

RESULTS

The best-performing model for the classification of 1-year OS was the extreme gradient boosting algorithm, with AUC and F1-score values equal to 0.805 and 0.802, respectively. The SHAP technique revealed that higher chance of 1-year survival is associated with low values of interleukin-8, higher values of hemoglobin and lymphocyte count, and the nonuse of steroids.

CONCLUSION

An explainable ML approach can provide a reliable prediction of 1-year survival after RT in patients with advanced cancer. The implementation of SHAP analysis provides an intelligible explanation of individualized risk prediction, enabling oncologists to identify the best strategy for patient stratification and treatment selection.

Utility of 30-day mortality as a quality metric for palliative radiation treatment: A population-based analysis from Queensland, Australia

INTRODUCTION

Palliative radiotherapy (PRT) is frequently used to treat symptoms of advanced cancer, however benefits are questionable when life expectancy is limited. The 30-day mortality rate after PRT is a potential quality indicator, and results from a recent meta-analysis suggest a benchmark of 16% as an upper limit. In this population-based study from Queensland, Australia, we examined 30-day mortality rates following PRT and factors associated with decreased life expectancy.

METHODS

Retrospective population data from Queensland Oncology Repository was used. Study population data included 22,501 patients diagnosed with an invasive cancer who died from any cause between 2008 and 2017 and had received PRT. Thirty-day mortality rates were determined from the date of last PRT fraction to date of death. Cox proportional hazards models were used to identify factors independently associated with risk of death within 30 days of PRT.

RESULTS

Overall 30-day mortality after PRT was 22.2% with decreasing trend in more recent years (P = 0.001). Male (HR = 1.20, 95% CI = 1.13-1.27); receiving 5 or less radiotherapy fractions (HR = 2.97, 95% CI = 2.74-3.22 and HR = 2.17, 95% CI = 2.03-2.32, respectively) and receiving PRT in a private compared to public facility (HR = 1.61, 95% CI = 1.51-1.71) was associated with decreased survival.

CONCLUSION

The 30-day mortality rate in Queensland following PRT is higher than expected and there is scope to reduce unnecessarily protracted treatment schedules. We encourage other Australian and New Zealand centres to examine and report their own 30-day mortality rate following PRT and would support collaboration for 30-day mortality to become a national and international quality metric for radiation oncology centres.

Thirty-day mortality after palliative radiotherapy in advanced cancer patients: Optimizing end-of-life care in Asia

INTRODUCTION

Evidence-based guidelines recommend hypofractionated palliative radiotherapy (PRT); nonetheless, many patients receive prolonged course of PRT. To identify patients with limited benefits from PRT in end-of-life care, we evaluated the pattern of PRT at an Asian institution and factors associated with 30-day mortality after PRT (30dM).

METHODS

We retrospectively reviewed 228 patients who died after PRT in Yonsei Wonju Severance Christian hospital between October 2014 and March 2022. The associations between clinical factors and survival were assessed using the Cox proportional hazards method. Survival was analysed using the existing models to evaluate their performance in our cohort.

RESULTS

The median PRT duration was 13 (IQR, 7-15) days. Only 11.4% of the patients were treated with hypofractionated radiotherapy. One-third of the patients (32.9%) could not complete PRT and 39 (17.1%) died during PRT. The 30dM was 31.6%. The median time from PRT to death was 17 (IQR, 11-23) days for the patients who died within 30 days. The number of involved organs (≤2 vs. >2; P < 0.001), albumin level (<3.3 vs. ≥3.3; P = 0.016), admission during PRT (P < 0.001), admission 3 months before PRT (P = 0.036) and ICU care during PRT (P < 0.001) were prognostic factors. A comparison of survival based on the existing models yielded unsatisfactory results in our cohort.

CONCLUSION

Almost one-third of the patients received PRT in the last 30 days of life. The use of hypofractionation for PRT was low in this Asian population. Further research is necessary to develop a predictive model of early mortality, allowing tailored end-of-life care for Asian patients.

Prognostication for Patients Receiving Palliative Radiation Therapy

Estimation of patient prognosis plays a central role in guiding decision making for the palliative management of metastatic disease, and a number of statistical models have been developed to provide survival estimates for patients in this context. In this review, we discuss several well-validated survival prediction models for patients receiving palliative radiotherapy to sites outside of the brain. Key considerations include the type of statistical model, model performance measures and validation procedures, studies' source populations, time points used for prognostication, and details of model output. We then briefly discuss underutilization of these models, the role of decision support aids, and the need to incorporate patient preference in shared decision making for patients with metastatic disease who are candidates for palliative radiotherapy.

Prognostic Score in Radiotherapy Practice for Palliative Treatments (PROPHET) Study for Bone Metastases: An Investigation Into the Clinical Effect on Treatment Prescription

Purpose

Bone metastases frequently occur during malignant disease. Palliative radiation therapy (PRT) is a crucial part of palliative care because it can relieve pain and improve patients' quality of life. Often, a clinician's survival estimation is too optimistic. Prognostic scores (PSs) can help clinicians tailor PRT indications to avoid over- or undertreatment. Although the PS is supposed to aid radiation oncologists (ROs) in palliative-care scenarios, it is unclear what type of support, and to what extent, could impact daily clinical practice.

Methods and Materials

A national-based investigation of the prescriptive decisions on simulated clinical cases was performed in Italy. Nine clinical cases from real-world clinical practice were selected for this study. Each case description contained complete information regarding the parameters defining the prognosis class according to the PS (in particular, the Mizumoto Prognostic Score, a validated PS available in literature and already applied in some clinical trials). Each case description contained complete information regarding the parameters defining the prognosis class according to the PS. ROs were interviewed through questionnaires, each comprising the same 3 questions per clinical case, asking (1) the prescription after detailing the clinical case features but not the PS prognostic class definition; (2) whether the RO wanted to change the prescription once the PS prognostic class definition was revealed; and (3) in case of a change of the prescription, a new prescriptive option. Three RO categories were defined: dedicated to PRT (RO-d), nondedicated to PRT (RO-nd), and resident in training (IT). Interviewed ROs were distributed among different regions of the country.

Results

Conversion rates, agreements, and prescription trends were investigated. The PS determined a statistically significant 11.12% of prescription conversion among ROs. The conversion was higher for the residents and significantly higher for worse prognostic scenario subgroups, respectively. The PS improved prescriptive agreement among ROs (particularly for worse-prognostic-scenario subgroups). Moreover, PS significantly increased standard prescriptive approaches (particularly for worse-clinical-case presentations).

Conclusions

To the best of our knowledge, the PROPHET study is the first to directly evaluate the potential clinical consequences of the regular application of any PS. According to the Prophet study, a prognostic score should be integrated into the clinical practice of palliative radiation therapy for bone metastasis and training programs in radiation oncology.

Replacing performance status with a simple patient-reported outcome in palliative radiotherapy prognostic modelling

Background and purpose

Prognostication is key to determining care in advanced incurable cancer. Although performance status (PS) has been shown to be a strong prognostic predictor, inter-rater reliability is limited, restricting models to specialist settings. This study assessed the extent to which a simple patient-reported outcome measure (PROM), the EQ-5D, may replace PS for prognosis of patients with bone metastases.

Materials and methods

Data from 1,011 patients in the Dutch Bone Metastasis Study were used. Cox proportional hazards models were developed to investigate the prognostic value of models incorporating PS alone, the EQ-5D SC dimension alone, all EQ-5D dimensions and EQ-VAS, and finally all dimensions and PS. Three prognostic groups were identified and performance assessed using the Harrell's C-index and Altman-Royston index of separation.

Results

Replacing performance status (PS) with the self-care (SC) dimension of the EQ-5D provides similar model performance. In our SC-based model, three groups are identified with median survival of 86 days (95 % CI 76-101), 174 days (95 % CI 145-213), and 483 days (95 % CI 431-539). Whilst not statistically significantly different, the C-index was 0.706 for the PS-only model, 0.718 for SC-only and 0.717 in our full model, suggesting patient-report outcome models perform as well as that based on PS.

Conclusion

Prognostic performance was similar across all models. The SC model provides prognostic value similar to that of PS, particularly where a prognosis of<6 months is considered. Larger, more contemporaneous studies are needed to assess the extent to which PROMs may be of prognostic value, particularly where specialist assessment is less feasible.

Improving providers' survival estimates and selection of prognosis- and guidelines-appropriate treatment for patients with symptomatic bone metastases: Development of the Bone Metastases Ensemble Trees for Survival Decision Support Platform

RATIONALE, AIMS AND OBJECTIVES

In the management of symptomatic bone metastases, current practice guidelines do not provide clear methodology for selecting palliative radiotherapy (RT) regimens based on specific patient and disease features. Decision support aids may offer an effective means for translating the complex data needed to render individualised treatment decisions, yet no such tools are available for use in this setting. Thus, we describe the development of the Bone Metastases Ensemble Trees for Survival-Decision Support Platform (BMETS-DSP), which aims to optimise selection of evidence-based, individualised palliative RT regimens.

METHOD

The Ottawa Decision Support Framework was used as the theoretical basis for development of BMETS-DSP. First, we utilised stakeholder input and review of the literature to assess determinants underlying the provider decision. Based on this assessment and iterative stakeholder feedback, we developed the web-based, provider-facing BMETS-DSP. Consistent with the underlying theoretical framework, our design also included assessment of decision quality using the International Patient Decision Aids Standards (IPDAS) certification checklist.

RESULTS

Stakeholder input and review of 54 evidence-based publications identified the following determinants of the provider decision: estimated prognosis, characteristics of the target symptomatic lesion and the primary cancer type, consideration of alternative interventions, access to patient-specific recommendations, and patient preferences. Based on these determinants, we developed the BMETS-DSP that (1) collects patient-specific data, (2) displays an individualised predicted survival curve, and (3) provides case-specific, evidence-based recommendations regarding RT, open surgery, systemic therapy, and hospice referral to aid in the decision-making process. The finalised tool met IPDAS quality requirements. Preliminary results of a pilot assessment suggest impact of clinical outcomes.

CONCLUSIONS

We describe the successful development of a provider-facing decision support platform to aid in the provision of palliative RT in better alignment with patient and disease features. Impact of the BMETS-DSP on decision outcomes will be further assessed in a randomised, controlled study.

Factors Influencing Physician Prognosis: A Scoping Review

Introduction. Prognosis is an essential component of informed consent for medical decision making. Research shows that physicians display discrepancies in their prognostication, leading to variable, inaccurate, optimistic, or pessimistic prognosis. Factors driving these discrepancies and the supporting evidence have not been reviewed systematically. Methods. We undertook a scoping review to explore the literature on the factors leading to discrepancies in medical prognosis. We searched Medline (Ovid) and Embase (Ovid) databases for peer-reviewed articles from 1970 to 2017. We included articles that discussed prognosis variation or discrepancy and where factors influencing prognosis were evaluated. We extracted data outlining the participants, methodology, and prognosis discrepancy information and measured factors influencing prognosis. Results. Of 4,723 articles, 73 were included in the final analysis. There was significant variability in research methodologies. Most articles showed that physicians were pessimistic regarding patient outcomes, particularly in early trainees and acute care specialties. Accuracy rates were similar across all time periods. Factors influencing prognosis were clustered in 4 categories: patient-related factors (such as age, gender, race, diagnosis), physician-related factors (such as age, race, gender, specialty, training and experience, attitudes and values), clinical situation-related factors (such as physician-patient relationship, patient location, and clinical context), and environmental-related factors (such as country or hospital size). Discussion. Obtaining accurate prognostic information is one of the highest priorities for seriously ill patients. The literature shows trends toward pessimism, especially in early trainees and acute care specialties. While some factors may prove difficult to change, the physician's personality and psychology influence prognosis accuracy and could be tackled using debiasing strategies. Exposure to long-term patient outcomes and a multidisciplinary practice setting are environmental debiasing strategies that may warrant further research.

Highlights

Literature on discrepancies in physician's prognostication is heterogeneous and sparse.Literature shows that physicians are mostly pessimistic regarding patient outcomes.Literature shows that a physician's personality and psychology influence prognostic accuracy and could be improved with evidence-based debiasing strategies.Medical specialty strongly influences prognosis, with specialties exposed to acutely ill patients being more pessimistic, whereas specialties following patients longitudinally being more optimistic.Physicians early in their training were more pessimist than more experienced physicians.

Prevalence and predictors for 72-h mortality after transfer to acute palliative care unit

Purpose

Accurate prediction of survival is important to facilitate clinical decision-making and improve quality of care at the end of life. While it is well documented that survival prediction poses a challenge for treating physicians, the need for clinically valuable predictive factors has not been met. This study aims to quantify the prevalence of patient transfer 72 h before death onto the acute palliative care unit in a tertiary care center in Switzerland, and to identify factors predictive of 72-h mortality.

Methods

All patients hospitalized between January and December 2020 on the acute palliative care unit of the Competence Center Palliative Care of the Department of Radiation Oncology at the University Hospital Zurich were assessed. Variables were retrieved from the electronic medical records. Univariable and multivariable logistic regressions were used to identify predictors of mortality.

Results

A total of 398 patients were screened, of which 188 were assessed. Every fifth patient spent less than 72 h on the acute palliative care unit before death. In multivariable logistic regression analysis, predictors for 72-h mortality after transfer were no prior palliative care consult (p = 0.011), no advance care directive (p = 0.044), lower performance status (p = 0.035), lower self-care index (p = 0.003), and lower blood albumin level (p = 0.026).

Conclusion

Late transfer to the acute palliative care unit is not uncommon, which can cause additional distress to patients and caretakers. Though clinically practical short-term survival predictors remain largely unidentified, early integration of palliative care should be practiced more regularly in patients with life-limiting illness.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00520-022-07075-6.

Prediction of post-radiotherapy survival for bone metastases: a comparison of the 3-variable number of risk factors model with the new Katagiri scoring system

We investigated patient survival after palliative radiotherapy for bone metastases while comparing the prognostic accuracies of the 3-variable number of risk factors (NRF) model and the new Katagiri scoring system (Katagiri score). Overall, 485 patients who received radiotherapy for bone metastases were grouped as per the NRF model (groups I, II and III) and Katagiri score (low-, intermediate- and high-risk). Survival was compared using the log-rank or log-rank trend test. Independent prognostic factors were identified using multivariate Cox regression analyses (MCRA). MCRA and receiver operating characteristic (ROC) curves were used to compare both models' accuracy. For the 376 evaluable patients, the overall survival (OS) rates decreased significantly in the higher-tier groups of both models (P < 0.001). All evaluated factors except 'previous chemotherapy status' differed significantly between groups. Both models exhibited independent predictive power (P < 0.001). Per NRF model, hazard ratios (HRs) were 1.44 (P = 0.099) and 2.944 (P < 0.001), respectively, for groups II and III, relative to group I. Per Katagiri score, HRs for intermediate- and high-risk groups were 4.02 (P < 0.001) and 7.09 (P < 0.001), respectively, relative to the low-risk group. Areas under the curve (AUC) for predicting 6-, 18- and 24-month mortality were significantly higher when using the Katagiri score (P = 0.036, 0.039 and 0.022). Both models predict survival. Prognostic accuracy of the Katagiri score is superior, especially in patients with long-term survival potential; however, in patients with short prognosis, no difference occurred between both models; simplicity and patient burden should also be considered.

A New Clinical Nomogram From the TCGA Database to Predict the Prognosis of Hepatocellular Carcinoma

Background and Aim

Hepatocellular carcinoma is a common malignant tumor of the digestive system with a poor prognosis. The high recurrence rate and metastasis after surgery reduce the survival time of patients. Therefore, assessing the overall survival of patients with hepatocellular carcinoma after hepatectomy is critical to clinicians' clinical decision-making. Conventional hepatocellular carcinoma assessment systems (such as tumor lymph node metastasis and Barcelona clinical hepatocellular carcinoma) are obviously insufficient in assessing the overall survival rate of patients. This research is devoted to the development of nomogram assessment tools to assess the overall survival probability of patients undergoing liver resection.

Methods

We collected the clinical and pathological information of 438 hepatocellular carcinoma patients undergoing surgery from The Cancer Genome Atlas (TCGA) database, then excluded 87 patients who did not meet inclusion criteria. Univariate and multivariate analyses were performed on patient characteristics and related pathological factors. Finally, we developed a nomogram model to predict patient's prognosis.

Results

A retrospective analysis of 438 consecutive samples from the TCGA database of patients with hepatocellular carcinoma who underwent potentially curative liver resections. Six risk factors were included in the final model. In the training set, the discriminative ability of the nomogram was very good (concordance index = 0.944), and the external verification method (concordance index = 0.962) was used for verification. At the same time, the internal and external calibration of the model was verified, showing that the model was well calibrated. The calibration between the evaluation of the nomogram and the actual observations was good. According to the patient's risk factors, we determined the patient's Kaplan-Meyer survival analysis curve. Finally, the clinical decision curve was used to compare the benefits of two different models in evaluating patients' clinical outcomes.

Conclusions

The nomogram can be used to evaluate the post-hepatectomy 1-, 3-, and 5-year survival rates of patients with hepatocellular carcinoma. The Kaplan-Meyer curve can intuitively display the survival differences among patients with various risk factors. The clinical decision curve is a good reference guide for clinical application.

[Ethical stakes in palliative care in radiation oncology]

In 2021, the Ethics Commission of the SFRO has chosen the issue of the practice of palliative care in radiotherapy oncology. Radiation oncology plays a central role in the care of patients with cancer in palliative phase. But behind the broad name of palliative radiotherapy, we actually find a large variety of situations involving diverse ethical issues. Radiation oncologists have the delicate task to take into account multiple factors throughout a complex decision-making process. While the question of the therapeutic indication and the technical choice allowing it to be implemented remains central, reflection cannot be limited to these decision-making and technical aspects alone. It is also a question of being able to create the conditions for a singularity focused care and to build an authentic care relationship, beyond technicity. It is through this daily ethical work, in close collaboration with patients, and under essential conditions of multidisciplinarity and multiprofessionalism, that our fundamental role as caregiver can be deployed.

Single-institution analysis of the prevalence, indications and outcomes of end-of-life radiotherapy

•

Survival prognostication and patient selection remain challenging tasks.

•

End-of-life radiotherapy until one week before death showed a patient benefit.

•

Treatment prescribed within one week of death often had to be discontinued.

•

Therapy needs to take into account patient preferences for the last phase of life.

Background

Radiotherapy plays an important role for symptom control in advanced stage cancer patients. Yet patients need to be carefully selected, and its use and benefits must be weighed against time spent under treatment and patient priorities in the last phase of life. In this study, we assess prevalence, indications and outcomes of radiotherapy close to death.

Methods

We screened all radiotherapy treatments performed at the Department of Radiation Oncology of the University Hospital Zurich between January 2010 and December 2019 to identify those which occurred near patients’ end-of-life. Analyzed data was extracted from the database of the Comprehensive Cancer Center Zurich, the treatment planning system Aria® and the electronical medical records system KISIM®.

Results

Within 60 days of death, 377 radiotherapy courses were prescribed to 280 patients, which constitutes 3.4% of all radiotherapy courses administered over the last decade at our department. Within 60–31, 30–8, and 7–0 days to death 164, 159, and 54 radiotherapy courses were prescribed, respectively. The most frequent treatment sites were brain (N = 122, 32%) and bone (N = 119, 32%), and there was no statistically significant difference in treatment site between the three sub-groups. The most common regimen was 10x3Gy (N = 130, 35%) in all three sub-groups (p = 0.23). Radiotherapy finished more than one week before death was associated with high completion rates (>80%) and treatment benefit (>55%).

Conclusion

Patient selection and survival prognostication remains challenging for radiation oncologists. While radiotherapy achieved high completion and success rates until one week before death, treatment within one week of death should be restricted to carefully selected patients or avoided altogether.

Early and Midtreatment Mortality in Palliative Radiotherapy: Emphasizing Patient Selection in High-Quality End-of-Life Care

BACKGROUND

Palliative radiotherapy (RT) is effective, but some patients die during treatment or too soon afterward to experience benefit. This study investigates end-of-life RT patterns to inform shared decision-making and facilitate treatment consistent with palliative goals.

MATERIALS AND METHODS

All patients who died ≤6 months after initiating palliative RT at an academic cancer center between 2015 and 2018 were identified. Associations with time-to-death, early mortality (≤30 days), and midtreatment mortality were analyzed.

RESULTS

In total, 1,620 patients died ≤6 months from palliative RT initiation, including 574 (34%) deaths at ≤30 days and 222 (14%) midtreatment. Median survival was 43 days from RT start (95% CI, 41-45) and varied by site (P<.001), ranging from 36 (head and neck) to 53 days (dermal/soft tissue). On multivariable analysis, earlier time-to-death was associated with osseous (hazard ratio [HR], 1.33; P<.001) and head and neck (HR, 1.45; P<.001) sites, multiple RT courses ≤6 months (HR, 1.65; P<.001), and multisite treatments (HR, 1.40; P=.008), whereas stereotactic technique (HR, 0.77; P<.001) and more recent treatment year (HR, 0.82; P<.001) were associated with longer survival. No difference in time to death was noted among patients prescribed conventional RT in 1 to 10 versus >10 fractions (median, 40 vs 47 days; P=.272), although the latter entailed longer courses. The 30-day mortality group included 335 (58%) inpatients, who were 27% more likely to die midtreatment (P=.031). On multivariable analysis, midtreatment mortality among these inpatients was associated with thoracic (odds ratio [OR], 2.95; P=.002) and central nervous system (CNS; OR, 2.44; P=.002) indications, >5-fraction courses (OR, 3.27; P<.001), and performance status of 3 to 4 (OR, 1.63; P=.050). Conversely, palliative/supportive care consultation was associated with decreased midtreatment mortality (OR, 0.60; P=.045).

CONCLUSIONS

Earlier referrals and hypofractionated courses (≤5-10 treatments) should be routinely considered for palliative RT indications, given the short life expectancies of patients at this stage in their disease course. Providers should exercise caution for emergent thoracic and CNS indications among inpatients with poor prognoses due to high midtreatment mortality.

External Validation of the Bone Metastases Ensemble Trees for Survival (BMETS) Machine Learning Model to Predict Survival in Patients With Symptomatic Bone Metastases

PURPOSE

The Bone Metastases Ensemble Trees for Survival (BMETS) model uses a machine learning algorithm to estimate survival time following consultation for palliative radiation therapy for symptomatic bone metastases (SBM). BMETS was developed at a tertiary-care, academic medical center, but its validity and stability when applied to external data sets are unknown.

PATIENTS AND METHODS

Patients treated with palliative radiation therapy for SBM from May 2013 to May 2016 at two hospital-based community radiation oncology clinics were included, and medical records were retrospectively reviewed to collect model covariates and survival time. The Kaplan-Meier method was used to estimate overall survival from consultation to death or last follow-up. Model discrimination was estimated using time-dependent area under the curve (tAUC), which was calculated using survival predictions from BMETS based on the initial training data set.

RESULTS

A total of 216 sites of SBM were treated in 182 patients. Most common histologies were breast (27%), lung (23%), and prostate (23%). Compared with the BMETS training set, the external validation population was older (mean age, 67 v 62 years; P < .001), had more primary breast (27% v 19%; P = .03) and prostate cancer (20% v 12%; P = .01), and survived longer (median, 10.7 v 6.4 months). When the BMETS model was applied to the external data set, tAUC values at 3, 6, and 12 months were 0.82, 0.77, and 0.77, respectively. When refit with data from the combined training and external validation sets, tAUC remained > 0.79.

CONCLUSION

BMETS maintained high discriminative ability when applied to an external validation set and when refit with new data, supporting its generalizability, stability, and the feasibility of dynamic modeling.

How palliative care professionals deal with predicting life expectancy at the end of life: predictors and accuracy

PURPOSE

To assess the accuracy of hospice staff in predicting survival of subjects admitted to hospice, exploring the factors considered most helpful by the hospice staff to accurately predict survival.

METHODS

Five physicians and 11 nurses were asked to predict survival at admission of 827 patients. Actual and predicted survival times were divided into ≤ 1 week, 2-3 weeks, 4-8 weeks, and ≥ 2 months and the accuracy of the estimates was calculated. The staff members were each asked to score 17 clinical variables that guided them in predicting survival and we analyzed how these variables impacted the accuracy.

RESULTS

Physicians' and nurses' accuracy of survival of the patients was 46% and 40% respectively. Survival was underestimated in 20% and 12% and overestimated in 34% and 48% of subjects. Both physicians and nurses considered metastases, comorbidities, dyspnea, disability, tumor site, neurological symptoms, and confusion very important in predicting patients' survival with nurses assigning more importance to intestinal symptoms and pain too. All these factors, with the addition of cough and/or bronchial secretions, were associated with physicians' greater accuracy. In the multivariable models, intestinal symptoms and confusion continued to be associated with greater predictive accuracy. No factors appreciably raised nurses' accuracy.

CONCLUSIONS

Some clinical symptoms rated as relevant by the hospice staff could be important for predicting survival. However, only intestinal symptoms and confusion significantly improved the accuracy of physicians' predictions, despite the high prevalence of overestimated survival.

External validation of life expectancy prognostic models in patients evaluated for palliative radiotherapy at the end-of-life

BACKGROUND

The TEACHH and Chow models were developed to predict life expectancy (LE) in patients evaluated for palliative radiotherapy (PRT). We sought to validate the TEACHH and Chow models in patients who died within 90 days of PRT consultation.

METHODS

A retrospective review was conducted on patients evaluated for PRT from 2017 to 2019 who died within 90 days of consultation. Data were collected for the TEACHH and Chow models; one point was assigned for each adverse factor. TEACHH model included: primary site of disease, ECOG performance status, age, prior palliative chemotherapy courses, hospitalization within the last 3 months, and presence of hepatic metastases; patients with 0-1, 2-4, and 5-6 adverse factors were categorized into groups (A, B, and C). The Chow model included non-breast primary, site of metastases other than bone only, and KPS; patients with 0-1, 2, or 3 adverse factors were categorized into groups (I, II, and III).

RESULTS

A total of 505 patients with a median overall survival of 2.1 months (IQR: 0.7-2.6) were identified. Based on the TEACHH model, 10 (2.0%), 387 (76.6%), and 108 (21.4%) patients were predicted to live >1 year, >3 months to ≤1 year, and ≤3 months, respectively. Utilizing the Chow model, 108 (21.4%), 250 (49.5%), and 147 (29.1%) patients were expected to live 15.0, 6.5, and 2.3 months, respectively.

CONCLUSION

Neither the TEACHH nor Chow model correctly predict prognosis in a patient population with a survival <3 months. A better predictive tool is required to identify patients with short LE.

Development and validation of a nomogram for assessing survival in patients with hepatocellular carcinoma after hepatectomy

BACKGROUND AND AIM

Assessing the average survival rate of patients with hepatocellular carcinoma (HCC) after hepatectomy is important for making critical decisions in everyday clinical practice. The present study aims to develop and validate a nomogram for assessing the overall survival probability for such patients.

METHODS

The putative prognostic indicators for constructing the nomogram were identified using multivariable Cox regression and model selection based on the Akaike information criterion. The nomogram was subjected to internal and external validation. The nomogram endpoints were death within 1, 3, and 5 years.

RESULTS

A consecutive sample of 522 HCC patients who underwent potentially curative hepatectomy was retrospectively analyzed. Age, Barcelona clinic liver cancer (BCLC) stage, tumor size, alanine transaminase, alpha fetal protein, and serum prealbumin were included in the final model. The nomogram's discriminative ability was good in the training set (C-index was 0.74 for 1 year, 0.73 for 3 years, 0.70 for 5 years) and was validated using both an internal bootstrap method (C-index was 0.73 for 1 year, 0.72 for 3 years, 0.69 for 5 years) and an external validating set (C-index was 0.72 for 1 year, 0.72 for 3 years, 0.69 for 5 years). The calibration plots for the endpoints showed optimal agreement between the nomogram's assessment and actual observations.

CONCLUSIONS

The nomogram (an Excel-based tool) can be useful for assessing the probability of survival at 1, 3, and 5 years in patients with HCC after hepatectomy.

Developing an Improved Statistical Approach for Survival Estimation in Bone Metastases Management: The Bone Metastases Ensemble Trees for Survival (BMETS) Model

PURPOSE

To determine whether a machine learning approach optimizes survival estimation for patients with symptomatic bone metastases (SBM), we developed the Bone Metastases Ensemble Trees for Survival (BMETS) to predict survival using 27 prognostic covariates. To establish its relative clinical utility, we compared BMETS with 2 simpler Cox regression models used in this setting.

METHODS AND MATERIALS

For 492 bone sites in 397 patients evaluated for palliative radiation therapy (RT) for SBM from January 2007 to January 2013, data for 27 clinical variables were collected. These covariates and the primary outcome of time from consultation to death were used to build BMETS using random survival forests. We then performed Cox regressions as per 2 validated models: Chow's 3-item (C-3) and Westhoff's 2-item (W-2) tools. Model performance was assessed using cross-validation procedures and measured by time-dependent area under the curve (tAUC) for all 3 models. For temporal validation, a separate data set comprised of 104 bone sites treated in 85 patients in 2018 was used to estimate tAUC from BMETS.

RESULTS

Median survival was 6.4 months. Variable importance was greatest for performance status, blood cell counts, recent systemic therapy type, and receipt of concurrent nonbone palliative RT. tAUC at 3, 6, and 12 months was 0.83, 0.81, and 0.81, respectively, suggesting excellent discrimination of BMETS across postconsultation time points. BMETS outperformed simpler models at each time, with respective tAUC at each time of 0.78, 0.76, and 0.74 for the C-3 model and 0.80, 0.78, and 0.77 for the W-2 model. For the temporal validation set, respective tAUC was similarly high at 0.86, 0.82, and 0.78.

CONCLUSIONS

For patients with SBM, BMETS improved survival predictions versus simpler traditional models. Model performance was maintained when applied to a temporal validation set. To facilitate clinical use, we developed a web platform for data entry and display of BMETS-predicted survival probabilities.

Needs with Regard to Decision Support Systems for Treating Patients with Incurable Non-small Cell Lung Cancer

Treatment decision-making for patients with incurable non-small cell lung cancer (NSCLC) is complex due to the rapidly increasing number of treatments and discovery of new biomarkers. Decision support systems (DSS) could assist thoracic oncologists (TO) weighing of the pros and cons of treatments in order to arrive at an evidence-based and personalized treatment advice. Our aim is to inventory (1) TO's needs with regard to DSS in the treatment of incurable (stage IIIB/IV) NSCLC patients, and (2) preferences regarding the development of future tools in this field. We disseminated an online inventory questionnaire among all members of the Section of Oncology within the Society of Physicians in Chest Medicine and Tuberculosis. Telephone interviews were conducted to better contextualize the findings from the questionnaire. In total, 58 TO completed the questionnaire and expressed a need for new DSS. They reported that it is important for tools to include genetic and immune markers, to be sufficiently validated, regularly updated, and time-efficient. Also, future DSS should incorporate multiple treatment options, integrate estimates of toxicity, quality of life and cost-effectiveness of treatments, enhance communication between caregivers and patients, and use IT solutions for a clear interface and continuous updating of tools. With this inventory among Dutch TO, we summarized the need for new DSS to aid treatment decision-making for patients with incurable NSCLC. To meet the expressed needs, substantial additional efforts will be required by DSS developers, above already existing tools.

Development and Validation of a Nomogram for Assessing Survival in Patients With Metastatic Lung Cancer Referred for Radiotherapy for Bone Metastases

Importance

A survival prediction model for patients with bone metastases arising from lung cancer would be highly valuable.

Objective

To develop and validate a nomogram for assessing the survival probability of patients with metastatic lung cancer receiving radiotherapy for osseous metastases.

Design, Setting, Participants

In this prognostic study, the putative prognostic indicators for constructing the nomogram were identified using multivariable Cox regression analysis with backward elimination and model selection based on the Akaike information criterion. The nomogram was subjected to internal (bootstrap) and external validation; its calibration and discriminative ability were evaluated with calibration plots and the Uno C statistic, respectively. The training and validation set cohorts were from a tertiary medical center in northern Taiwan and a tertiary institution in southern Taiwan, respectively. The training set comprised 477 patients with metastatic lung cancer who received radiotherapy for osseous metastases between January 2000 and December 2013. The validation set comprised 235 similar patients treated between January 2011 and December 2017. Data analysis was conducted May 2018 to July 2018.

Main Outcomes and Measures

The nomogram end points were death within 3, 6, and 12 months.

Results

Of 477 patients in the training set, 292 patients (61.2%) were male, and the mean (SD) age was 62.86 (11.66) years. Of 235 patients in the validating set, 113 patients (48.1%) were male, and the mean (SD) age was 62.65 (11.49) years. In the training set, 186 (39%), 291 (61%), and 359 (75%) patients died within 3, 6, and 12 months, respectively, and the median overall survival was 4.21 (95% CI, 3.68-4.90) months. In the validating set, 84 (36%), 120 (51%), and 144 (61%) patients died within 3, 6, and 12 months, respectively, and the median overall survival was 5.20 (95% CI, 4.07-7.17) months. Body mass index (18.5 to <25 vs ≥25: hazard ratio [HR], 1.42; 95% CI, 1.14-1.78 and <18.5 vs ≥25: HR, 2.31; 95% CI, 1.56-3.44), histology (non-small cell vs small cell lung cancer: HR, 0.59; 95% CI, 0.41-0.86), epidermal growth factor receptor mutation (positive vs unknown: HR, 0.66; 95% CI, 0.46-0.93 and negative vs unknown: HR, 0.98; 95% CI, 0.66-1.45), smoking status (ever smoker vs never smoker: HR, 1.50; 95% CI, 1.24-1.83), age, and neutrophil to lymphocyte ratio were incorporated. The HRs of age and neutrophil to lymphocyte ratio were modeled nonlinearly with restricted cubic splines (both P < .001). The nomogram's discriminative ability was good in the training set (C statistic, ≥0.77; P < .001) and was validated using both an internal bootstrap method (C statistic, ≥0.76; P < .001) and an external validating set (C statistic, ≥0.75; P < .001). The calibration plots for the end points showed optimal agreement between the nomogram's assessment and actual observations.

Conclusions and Relevance

The nomogram (with web-based tool) can be useful for assessing the probability of survival at 3, 6, and 12 months in patients with metastatic lung cancer referred for radiotherapy to treat bone metastases, and it may guide radiation oncologists in treatment decision making and engaging patients in end-of-life discussions and/or hospice referrals at appropriate times.

Impact of Performance Status and Comorbidity on Palliative Radiation Treatment Tolerance and End-Of-Life Decision-Making

Purpose

Previous studies have indicated a relationship between functional status and comorbidity on overall survival when treating patients with bone and brain metastases. However, the degree to which these findings have been integrated into modern-day practice remains unknown. This study examines the impact of performance measures, including Karnofsky Performance Status (KPS) and comorbidity, on palliative radiation therapy treatment tolerance and fractionation schedule. The relationship between a shorter fractionation schedule (SFx) and pending mortality is examined.

Methods and materials

This study included patients who were treated with palliative intent to the brain or bone between January 1, 2016 and June 30, 2016. Demographic and medical characteristics collected included KPS score (stratified as good [90-100], fair [70-80], and poor (≤60]), socioeconomic status, comorbidity (binary measure using the Adult Comorbidity Evaluation-27 scale), site of metastatic disease, and treatment facility. Univariable analyses were performed using the Cox proportional hazards regression model to assess the impact of the variables on the prescribed number of fractions (binary measure, ≥10 [long fractionation schedule], and <10 [SFx]), and major treatment interruptions (MTIs; defined as missing ≥3 radiation therapy treatment days or ending treatment prematurely).

Results

A total of 145 patients were eligible for study inclusion, including 95 patients who were treated for bony metastatic disease and 50 patients for brain metastases. High comorbidity (P = .029) and both fair (P = .051) and poor (P = .065) functional status were associated with more frequent MTIs. However, high comorbidity and low KPS score were not associated with shorter treatment plans. In addition, patients with an earlier time to death were not more likely to receive an SFx (P = .871).

Conclusions

Low KPS and elevated comorbidity scores predict for a poorer prognosis and more frequent MTIs; however, there was no indication that physicians incorporated this information in the fractionation scheduling.

Agreement between patients' and radiation oncologists' cancer diagnosis and prognosis perceptions: A cross sectional study in Japan

This study assessed agreement between radiation oncologist- and cancer patient-reported perceptions about cancer diagnosis, time since diagnosis, treatment purpose, and whether life expectancy had been discussed; and described preferences for prognosis discussions. Adult cancer patients receiving radiotherapy at a Japanese hospital were invited to complete a touchscreen tablet survey. Patient survey responses were linked and comparisons made with a survey completed by their radiation oncologist. Among 146 cancer patient-oncologist dyads, there was almost perfect agreement on cancer diagnosis (ĸ = 0.88, 95% CI: 0.82–0.94), substantial agreement on time since diagnosis (ĸ = 0.70, 95% CI: 0.57–0.83) and moderate agreement on whether treatment goal was curative or palliative (ĸ = 0.44, 95% CI: 0.28–0.57; all p’s < 0.0001). Agreement about whether a life expectancy discussion had occurred was less than expected by chance (κ = -0.06, p = 0.9). Radiation oncologists reported that they had spoken to over two thirds of patients about this, whilst less than one third of patients stated that this discussion had occurred with their radiation oncologist. Over half of the patients who had not discussed life expectancy wanted to. Patients had variable preferences for whether they (80%), their radiation oncologist (78%) or their partner/family (52%) should decide whether they discuss their life expectancy. Although patient self-reported information about diagnosis and time since diagnosis appears to be reasonably accurate (compared with clinician-reported information), limitations of self-reported data about prognostic discussions were highlighted by poor agreement between patient- and clinician-reported information about whether prognostic discussions have occurred. Additional support is needed to improve prognosis communication and understanding in radiation oncology settings.

Use of Radiation Therapy Within the Last Year of Life Among Cancer Patients

PURPOSE

We examined radiation therapy (RT) use within the last year of life (LYOL). As palliative RT (PRT) has been well studied in patients with ≥6-week life expectancies, we hypothesized that PRT use would be constant over the LYOL, except for the last 30 days, when use would decline given lack of prospective data supporting it.

MATERIALS AND METHODS

At a single institution, 870 cancer patients died between October 2, 2014, and September 30, 2015, and had ≥3 evaluation and management visits within the LYOL. Claims and RT data were extracted and linked. Over the LYOL, we evaluated RT use by intent (curative vs palliative) and indications.

RESULTS

Within the LYOL, one-third of patients underwent RT in the last 365 days of life to 444 sites, which decreased to 24.3% and 8.5% in the last 180 and 30 days of life, respectively. Patients who received any RT in the last 365 days of life were younger at death and had a higher proportion of lung, sarcoma, and transplant disease groups. One-quarter of sites were irradiated with curative intent, which remained constant over the LYOL. In contrast, PRT was used at a supralinear rate, in which treatment of bone metastases and use of single-fraction PRT increased closer to death.

CONCLUSIONS

PRT appears to be disproportionately used closer to death, with an increasing proportion of irradiated sites being bone metastases. This may be secondary to increased symptoms from advanced cancer toward the end of life. As patients with very poor prognoses (eg, within 30 days of death) are generally not included in RT clinical trials, further studies are warranted to assess whether PRT for bone metastases at the end of life is efficacious.

A Pilot Study in the Use of Activity Trackers for Assessing Response to Palliative Radiotherapy

Purpose Radiation therapy (RT) has been a frequently used treatment for painful bone metastasis. The aim of this study was to determine the feasibility of using activity trackers (AT) to assess the patient prognosis and the effects of palliative RT. Methods and materials Twelve patients planned to receive palliative RT for axial metastases and were prospectively recruited to participate in this pilot clinical trial. The patients were eligible if there was no intent to change the analgesic medications prior to or within seven days of palliative RT. All the patients were lent a Misfit FlashTM activity tracker (Misfit, Burlingame, California, United States of America) and were asked to wear it from the time of baseline assessment prior to RT until seven days after RT. The patients completed the European Organisation for Research and Treatment of Cancer quality of life (QOL) questionnaire (EORTC-QLQ C30) and the Short Form Brief Pain Inventory (SF-BPI) before the treatment and at days seven, 30 and 90 after completion of the RT. The patients' Karnofsky Performance Status (KPS) was assessed at each visit. The patients' overall survival at the end of the RT was recorded. Average daily steps before and after RT were compared using paired Wilcoxon signed-rank test. The patients' overall survival was estimated using the Kaplan-Meier curve and analyzed using the Log-Rank test. Results The median age of the patients was 62 years (range: 40-79 years). Of the 12 patients, there were five prostate, three breasts, three lungs, and one colon cancer-related patients. Six patients received 20 Gray (Gy) in five fractions and six received 8 Gy in one fraction. By day seven, post-RT, there was a 30% (p <0.02) reduction in the patients' daily activity level. There was no correlation between improvements in the QOL or with the level of pain and with the number of daily steps. While baseline KPS was not prognostic of the patient survival, the patients who on average took more than 7800 steps per day prior to RT lived significantly (p=0.034) longer than those who were less active. Conclusions The baseline activity level is associated with the patient prognosis. A significant decline in the physical activity was observed at one week after palliative RT. The use of activity trackers was to prognosticate and to monitor the patients' response to the palliative RT and should be evaluated further.

Consideration of patient and disease characteristics in selecting radiation regimens for treatment of bone metastases

PURPOSE

Radiation therapy is one of the mainstays of treatment for painful bone metastases; however, the optimal fractionation and dosing of radiation for a given patient and disease characteristics are still subject to debate.

METHODS AND MATERIALS

We retrospectively examined 475 patients who received radiation for bone metastases at our institution from 2009 through 2014 and evaluated survival outcomes based on parameters of their first treatment course and patient demographics. Kaplan-Meier analysis was used to analyze factors associated with overall survival (OS). A recursive partition analysis (RPA) was used to generate a decision tree of patient characteristics resulting in significant differences in survival. A Cox model was used to verify the RPA and evaluate the significance of biologically equivalent dose (BED) along with other factors.

RESULTS

In our cohort, median age was 62 years and median Karnofsky performance status (KPS) was 70. Survival time by primary tumor type: breast (median, 35.9 months), prostate (12.8 months), other (median, 11.0 months), lung (median, 5.3 months), and gastrointestinal (median, 4.0 months) (P < .0001). Primary tumor type and KPS significantly affected survival, whereas age was also significant for survival in certain primary tumor types. Pain control was not found to be significantly affected by primary tumor type (P = .72) or BED (P = .14).

CONCLUSION

Our data demonstrate that selection of radiation fractionation schedules should take into account primary tumor type, KPS, and age, and we have generated an RPA model including these factors to help guide decision making. We also found that shorter fractionation schedules are as effective as longer fractionation schedules for pain control, regardless of primary tumor type.

The Glasgow prognostic score: Useful information when prescribing palliative radiotherapy

The purpose of the present retrospective study was to investigate whether a score reflecting systemic inflammatory processes [the Glasgow Prognostic Score (GPS)] provides relevant information for radiation oncologists. GPS is a three-tiered score [0: normal C-reactive protein (CRP) and albumin; 1: one abnormal result; 2: increased CRP and low albumin]. Correlations between disease type and extent, resource utilization, survival and GPS were analyzed in 703 patients. In the subgroup with GPS 2, significantly higher rates of lung, adrenal gland and liver metastases were observed. An increasing GPS score was associated with a higher likelihood of anemia, leukocytosis and thrombocytosis. Comparable findings were made regarding utilization of palliative care resources, need for blood transfusion and intravenous administration of antibiotics. Compared with GPS 0 or 1, more patients with GPS 2 did not complete their prescribed course of radiotherapy. One-third of patients with GPS 2 received treatment during the final month of life. Multivariate analysis demonstrated that GPS was a significant prognostic factor for overall survival (median, 479, 136, and 61 days, for GPS 0, 1 and 2, respectively). In patients with GPS 2 and additional leukocytosis, the median survival was 38 days. In conclusion, GPS provides important prognostic information. This biomarker-based score may be considered for deciding fractionation, and should be validated further.

Palliative pelvic radiotherapy for symptomatic rectal cancer - a prospective multicenter study

BACKGROUND AND PURPOSE

Palliative pelvic radiotherapy (PPRT) is used to treat locally advanced rectal cancer (RC) although symptomatic effects and toxicities are poorly documented. Aims were to evaluate symptom severity, quality of life (QOL) and toxicity after PPRT.

MATERIAL AND METHODS

Fifty-one patients with symptomatic primary or recurrent RC prescribed PPRT with fractions of 3 Gy to 30-39 Gy were included. Primary outcome was severity of target symptoms (TS) 12 weeks after PPRT. Pelvic symptom burden, toxicity, and QOL were assessed. Response was defined as patient-reported TS improvement or resolution.

RESULTS

Pain (n = 24), rectal dysfunction (n = 16), and hematochezia (n = 9) were the most common TSs. Overall response rate among evaluable patients 12 weeks after PPRT was 28/33 (85%). Eighteen patients did not complete the study follow-up, 16 due to deteriorating health. TS responses were 10/13 (77%) for pain, 9/10 (90%) for rectal dysfunction, and 8/8 for hematochezia. Non-target pelvic symptom severity decreased and median QOL scores remained stable. There was no grade 4 toxicity. Median survival was nine months.

CONCLUSIONS

In the majority of patients with symptomatic primary or recurrent RC, PPRT with 30-39 Gy contributes to pelvic symptom relief, with little toxicity. Patients prescribed PPRT of RC have limited life expectancy. Future studies should investigate simplification of PPRT.

Prognostic value of parameters derived from white blood cell and differential counts in patients receiving palliative radiotherapy

The aim of the present study was to identify white blood cell (WBC) parameters with high prognostic value for the survival of patients receiving palliative radiotherapy. The prognostic value of seven parameters derived from WBC and differential counts was retrospectively evaluated in patients who underwent palliative radiotherapy between October, 2010 and June, 2013. The analyzed parameters were the total WBC count, the absolute and relative lymphocyte count, the absolute and relative neutrophil count, and the neutrophil-to-lymphocyte and lymphocyte-to-monocyte ratios. Following univariate analysis, multivariate Cox regression analysis was performed to adjust for gender, age, disease type, previous chemotherapy, previous radiotherapy and the levels of albumin and lactate dehydrogenase. A total of 220 patients with a median survival of 4.7 months were identified. All seven parameters were found to be statistically significant predictors of survival on univariate Cox regression analysis (P<0.05). Of these parameters, the low relative lymphocyte and high relative neutrophil counts were consistent predictors of poor survival in patients who received chemotherapy within 1 month prior to blood sampling (n=68) and in patients who received steroid treatment at the time of sampling (n=49). Multivariate Cox regression analysis revealed that the relative lymphocyte and neutrophil counts were independent predictors of survival in all 220 patients (P<0.05). In conclusion, relative lymphocyte and neutrophil counts were of high prognostic value for the survival of patients receiving palliative radiotherapy, even in those receiving medications that affect WBC and differential counts.

Influence of the treatment schedule on the physicians' decisions to refer bone metastases patients for palliative radiotherapy: a questionnaire survey of physicians in various specialties

We investigated whether the treatment schedule influences physicians' decisions to refer their patients for radiotherapy. We presented a questionnaire to 104 physicians in various specialties at three hospitals. It included three hypothetical patients with uncomplicated painful bone metastasis: patients with an expected life span of one year (case 1), 6 months (case 2), and 2 months (case 3). The physicians were asked whether they would refer their patients for radiotherapy when a radiation oncologist presented three different treatment schedules: a short (8 Gy/1 fraction/1 day)-, a medium (20 Gy/5 fractions/1 week)-, and a long (30 Gy/10 fractions/2 weeks) schedule. We used Cochran's Q-test to compare the percentage of physicians across the three schedules and a mixed-effect logistic model to identify predictors of the selection of only the one-day schedule. Of the 104 physicians, 68 (65%) responded. Of these, 37 (54%), 27 (40%), and 26 (38%) chose to refer patients for radiotherapy when the short-, medium-, and long schedules, respectively, were proposed in case 1 (p = 0.14). These numbers were 44 (65%), 29 (43%), and 15 (22%) for case 2 (p < 0.001), and 59 (87%), 12 (18%), and 1 (1%) for case 3 (p < 0.001). Hypothetical patient and the physicians' years of practice and perspective regarding side effects were independently predictive of the selection of only the one-day schedule. In conclusion, the treatment schedule influenced the physicians' decisions to refer patients for radiotherapy.

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

BACKGROUND

It is unknown if survival prediction tools (SPTs) sufficiently predict survival in patients who undergo palliative reirradiation of spinal metastases. We therefore set out to clarify if SPTs can predict survival in this patient population.

METHODS

We retrospectively analyzed spinal reirradiations performed (n = 58, 52 patients, 44 included in analysis). SPTs for patients with spinal metastases were identified and compared to a general palliative score and to a dedicated SPT to estimate prognosis in palliative reirradiation independent of site (SPT-Nieder).

RESULTS

Consistently in all tests, SPT-Nieder showed best predictive performance as compared to other tools. Items associated with survival were general condition (KPS), liver metastases, and steroid use. Other factors like primary tumor site, pleural effusion, and bone metastases were not correlated with survival. We adapted an own score to the data which performed comparable to SPT-Nieder but avoids the pleural effusion item. Both scores showed good performance in identifying long-term survivors with late recurrences.

CONCLUSIONS

Survival prediction in case of spinal reirradiation is possible with sufficient predictive separation. Applying SPTs in case of reirradiation helps to identify patients with good life expectancy who might benefit from dose escalation or longer treatment courses.

30 day mortality in adult palliative radiotherapy--A retrospective population based study of 14,972 treatment episodes

Background: 30-day mortality (30DM) has been suggested as a clinical indicator of the avoidance of harm in palliative radiotherapy within the NHS, but no large-scale population-based studies exist. This large retrospective cohort study aims to investigate the factors that influence 30DM following palliative radiotherapy and consider its value as a clinical indicator.

Methods: All radiotherapy episodes delivered in a large UK cancer centre between January 2004 and April 2011 were analysed. Patterns of palliative radiotherapy, 30DM and the variables affecting 30DM were assessed. The impact of these variables was assessed using logistic regression.

Results: 14,972 palliative episodes were analysed. 6334 (42.3%) treatments were delivered to bone metastases, 2356 (15 7%) to the chest for lung cancer and 915 (5.7%) to the brain. Median treatment time was 1 day (IQR 1–7). Overall 30DM was 12.3%. Factors having a significant impact upon 30DM were sex, primary diagnosis, treatment site and fractionation schedule (p < 0.01).

Conclusion: This is the first large-scale description of 30-day mortality for unselected adult palliative radiotherapy treatments. The observed differences in early mortality by fractionation support the use of this measure in assessing clinical decision making in palliative radiotherapy and require further study in other centres and health care systems.

An easy tool to predict survival in patients receiving radiation therapy for painful bone metastases

PURPOSE

Patients with bone metastases have a widely varying survival. A reliable estimation of survival is needed for appropriate treatment strategies. Our goal was to assess the value of simple prognostic factors, namely, patient and tumor characteristics, Karnofsky performance status (KPS), and patient-reported scores of pain and quality of life, to predict survival in patients with painful bone metastases.

METHODS AND MATERIALS

In the Dutch Bone Metastasis Study, 1157 patients were treated with radiation therapy for painful bone metastases. At randomization, physicians determined the KPS; patients rated general health on a visual analogue scale (VAS-gh), valuation of life on a verbal rating scale (VRS-vl) and pain intensity. To assess the predictive value of the variables, we used multivariate Cox proportional hazard analyses and C-statistics for discriminative value. Of the final model, calibration was assessed. External validation was performed on a dataset of 934 patients who were treated with radiation therapy for vertebral metastases.

RESULTS

Patients had mainly breast (39%), prostate (23%), or lung cancer (25%). After a maximum of 142 weeks' follow-up, 74% of patients had died. The best predictive model included sex, primary tumor, visceral metastases, KPS, VAS-gh, and VRS-vl (C-statistic = 0.72, 95% CI = 0.70-0.74). A reduced model, with only KPS and primary tumor, showed comparable discriminative capacity (C-statistic = 0.71, 95% CI = 0.69-0.72). External validation showed a C-statistic of 0.72 (95% CI = 0.70-0.73). Calibration of the derivation and the validation dataset showed underestimation of survival.

CONCLUSION

In predicting survival in patients with painful bone metastases, KPS combined with primary tumor was comparable to a more complex model. Considering the amount of variables in complex models and the additional burden on patients, the simple model is preferred for daily use. In addition, a risk table for survival is provided.

Role of radiation therapy in palliative care of the patient with cancer

Radiotherapy is a successful, time-efficient, well-tolerated, and cost-effective intervention that is crucial for the appropriate delivery of palliative oncology care. The distinction between curative and palliative goals is blurred in many patients with cancer, requiring that treatments be chosen on the basis of factors related to the patient (ie, poor performance status, advanced age, significant weight loss, severe comorbid disease), the cancer (ie, metastatic disease, aggressive histology), or the treatment (ie, poor response to systemic therapy, previous radiotherapy). Goals may include symptom relief at the site of primary tumor or from metastatic lesions. Attention to a patient's discomfort and transportation limitations requires hypofractionated courses, when feasible. Innovative approaches include rapid response palliative care clinics as well as the formation of palliative radiotherapy specialty services in academic centers. Guidelines are providing better definitions of appropriate palliative radiotherapy interventions, and bone metastases fractionation has become the first radiotherapy quality measure accepted by the National Quality Forum. Further advances in the palliative radiation oncology subspecialty will require integration of education and training between the radiotherapy and palliative care specialties.

Supportive and palliative radiation oncology service: impact of a dedicated service on palliative cancer care

PURPOSE

The American Society of Clinical Oncology has recommended tailoring palliative cancer care (PCC) to the distinct and complex needs of advanced cancer patients. The Supportive and Palliative Radiation Oncology (SPRO) service was initiated July 2011 to provide dedicated palliative radiation oncology (RO) care to cancer patients. We used care providers' ratings to assess SPRO's impact on the quality of PCC and compared perceptions of PCC delivery among physicians practicing with and without a dedicated palliative RO service.

METHODS AND MATERIALS

An online survey was sent to 117 RO care providers working at 4 Boston-area academic centers. Physicians and nurses at the SPRO-affiliated center rated the impact of the SPRO service on 8 PCC quality measures (7-point scale, "very unfavorably" to "very favorably"). Physicians at all sites rated their department's performance on 10 measures of PCC (7-point scale, "very poorly" to "very well").

RESULTS

Among 102 RO care providers who responded (response rate, 89% for physicians; 83% for nurses), large majorities believed that SPRO improved the following PCC quality measures: overall quality of care (physician/nurse, 98%/92%); communication with patients and families (95%/96%); staff experience (93%/84%); time spent on technical aspects of PCC (eg, reviewing imaging) (88%/56%); appropriateness of treatment recommendations (85%/84%); appropriateness of dose/fractionation (78%/60%); and patient follow-up (64%/68%). Compared with physicians practicing in departments without a dedicated palliative RO service, physicians at the SPRO-affiliated department rated the overall quality of their department's PCC more highly (P = .02).

CONCLUSIONS

Clinicians indicated that SPRO improved the quality of PCC. Physicians practicing within this dedicated service rated their department's overall PCC quality higher than physicians practicing at academic centers without a dedicated service. These findings point to dedicated palliative RO services as a promising means of improving PCC quality.