A predictive model for survival in metastatic cancer patients attending an outpatient palliative radiotherapy clinic

Predicting the survival of patients with painful tumours treated with palliative radiotherapy: a secondary analysis using the 3-variable number-of-risk-factors model

BACKGROUND

The 3-variable number-of-risk-factors (NRF) model is a prognostic tool for patients undergoing palliative radiotherapy (PRT). However, there is little research on the NRF model for patients with painful non-bone-metastasis tumours treated with PRT, and the efficacy of the NRF model in predicting survival is unclear to date. Therefore, we aimed to assess the prognostic accuracy of a 3-variable NRF model in patients undergoing PRT for bone and non- bone-metastasis tumours.

METHODS

This was a secondary analysis of studies on PRT for bone-metastasis (BM) and PRT for miscellaneous painful tumours (MPTs), including non-BM tumours. Patients were grouped in the NRF model and survival was compared between groups. Discrimination was evaluated using a time-independent C-index and a time-dependent area under the receiver operating characteristic curve (AUROC). A calibration curve was used to assess the agreement between predicted and observed survival.

RESULTS

We analysed 485 patients in the BM group and 302 patients in the MPT group. The median survival times in the BM group for groups I, II, and III were 35.1, 10.1, and 3.3 months, respectively (P < 0.001), while in the MPT group, they were 22.1, 9.5, and 4.6 months, respectively (P < 0.001). The C-index was 0.689 in the BM group and 0.625 in the MPT group. In the BM group, time-dependent AUROCs over 2 to 24 months ranged from 0.738 to 0.765, while in the MPT group, they ranged from 0.650 to 0.689, with both groups showing consistent accuracy over time. The calibration curve showed a reasonable agreement between the predicted and observed survival.

CONCLUSIONS

The NRF model predicted survival moderately well in both the BM and MPT groups.

Palliative radiotherapy: New prognostic factors for patients with bone metastasis

PURPOSE

Many cancer patients develop bone metastases, however the prognosis of overall survival differs. To provide an optimal treatment for these patients, especially towards the end of life, a reliable prediction of survival is needed. The goal of this study was to find new clinical factors in relation to overall survival.

MATERIALS AND METHODS

Prospectively 22 clinical factors were collected from 734 patients. The Kaplan-Meier and Cox regression models were used.

RESULTS

Most patients were diagnosed with lung cancer (29%), followed by prostate (19.8%) and breast cancer (14.7%). Median overall survival was 6.4months. Fourteen clinical factors showed significance in the univariate analyses. In the multivariate analyses 6 factors were found to be significant for the overall survival: Karnofsky performance status, primary tumor, gender, total organs affected, morphine use and systemic treatment options after radiotherapy.

CONCLUSION

Morphine use and systemic treatment options after radiotherapy, Karnofsky performance status, primary tumor, gender and total organs affected are strong prediction factors on overall survival after palliative radiotherapy in patients with bone metastasis. These factors are easily applicable in the clinic.

Thirty-day mortality as a metric for palliative radiotherapy in pediatric patients

PURPOSE OF REVIEW

Thirty-day mortality (30DM) is an emerging consideration for determining whether terminally ill adult patients may benefit from palliative radiotherapy (RT). However, the efficacy and ethics of delivering palliative RT at the end of life (EOL) in children are seldom discussed and not well-established.

RECENT FINDINGS

Palliative RT is perhaps underutilized among patients ≤21 years old with rates as low as 11%. While effective when delivered early, clinical benefit decreases when administered within the last 30 days of life. Pediatric 30DM rates vary widely between institutions (0.7-30%), highlighting the need for standardized practices. Accurate prognosis estimation remains challenging and prognostic models specific to palliative pediatric patients are limited. Discordance between provider and patient/parent perceptions of prognosis further complicates decision-making.

SUMMARY

RT offers effective symptom control in pediatric patients when administered early. However, delivering RT within the last 30 days of life may provide limited clinical benefit and hinder optimal EOL planning and care. Early referral for palliative RT, preferably with fewer fractions (five or fewer), along with multidisciplinary supportive care, optimizes the likelihood of maintaining patients' quality of life. Prognosis estimation remains difficult, and improving patient and family understanding is crucial. Further research is needed to refine prognostic models and enhance patient-centered care.

Decision tree algorithm to predict mortality in incurable cancer: a new prognostic model

OBJECTIVES

To develop and validate a new prognostic model to predict 90-day mortality in patients with incurable cancer.

METHODS

In this prospective cohort study, patients with incurable cancer receiving palliative care (n = 1322) were randomly divided into two groups: development (n = 926, 70%) and validation (n = 396, 30%). A decision tree algorithm was used to develop a prognostic model with clinical variables. The accuracy and applicability of the proposed model were assessed by the C-statistic, calibration and receiver operating characteristic (ROC) curve.

RESULTS

Albumin (75.2%), C reactive protein (CRP) (47.7%) and Karnofsky Performance Status (KPS) ≥50% (26.5%) were the variables that most contributed to the classification power of the prognostic model, named Simple decision Tree algorithm for predicting mortality in patients with Incurable Cancer (acromion STIC). This was used to identify three groups of increasing risk of 90-day mortality: STIC-1 - low risk (probability of death: 0.30): albumin ≥3.6 g/dL, CRP <7.8 mg/dL and KPS ≥50%; STIC-2 - medium risk (probability of death: 0.66 to 0.69): albumin ≥3.6 g/dL, CRP <7.8 mg/dL and KPS <50%, or albumin ≥3.6 g/dL and CRP ≥7.8 mg/dL; STIC-3 - high risk (probability of death: 0.79): albumin <3.6 g/dL. In the validation dataset, good accuracy (C-statistic ≥0.71), Hosmer-Lemeshow p=0.12 and area under the ROC curve=0.707 were found.

CONCLUSIONS

STIC is a valid, practical tool for stratifying patients with incurable cancer into three risk groups for 90-day mortality.

Radiation Therapy in the Last Month of Life: Association With Aggressive Care at the End of Life

CONTEXT

Half of the patients with cancer who undergo radiation therapy do so with palliative intent.

OBJECTIVES

To determine the proportion of undergoing radiation in the last month of life, patient characteristics, cancer course, the type and duration of radiation, whether palliative care was involved, and the of radiation with aggressive cancer care metrics.

METHODS

One thousand seven hundred twenty-seven patients who died of cancer between January 1, 2018, and December 31, 2019, were included. Demographics, cancer stage, palliative care referral, advance directives, use of home health care, radiation timing, and survival were collected. Type of radiation, course, and intent were reviewed. Chi-square analysis was utilized for categorical variables, and Kruskal-Wallis tests for continuous variables. A stepwise selection was used to build a Cox proportional hazard model.

RESULTS

Two hundred thirty-three patients underwent radiation in the last month of life. Younger patients underwent radiation 67.3 years (SD 11.52) versus 69.2 years (SD 11.96). 42.6% had radiation within two weeks of death. The average fraction number was 5.5. Individuals undergoing radiation were more likely to start chemotherapy within the last 30 days of life, continue chemotherapy within two weeks of death, be admitted to the ICU, and have two or more hospitalizations or emergency room visits. Survival measured from the date of diagnosis was shorter for those undergoing radiation, 122 days (IQR 58-462) versus 474 days (IQR 225-1150). Palliative care consultations occurred later in those undergoing radiation therapy.

CONCLUSION

Radiation therapy in the last month of life occurs in younger patients with rapidly progressive cancer, who are subject to more aggressive cancer care, and have late palliative care consults.

Factors Associated with Long-Term Prostate Cancer Survival after Palliative Radiotherapy to a Bone Metastasis and Contemporary Palliative Systemic Therapy: A Retrospective, Population-Based Study

BACKGROUND

Radiation therapy (RT) is an established palliative treatment for bone metastases; however, little is known about post-radiation survival and factors which impact it. The aim of this study was to assess a population-based sample of metastatic prostate cancer patients receiving palliative radiation therapy to bone metastases and contemporary palliative systemic therapy and identify factors that impact long-term survival.

MATERIALS/METHODS

This retrospective, population-based, cohort study assessed all prostate cancer patients receiving palliative RT for bone metastases at a Canadian provincial Cancer program during a contemporary time period. Baseline patient, disease, and treatment characteristics were extracted from the provincial medical physics databases and the electronic medical record. Post-RT Survival intervals were defined as the time interval from the first fraction of palliative RT to death from any cause or date of the last known follow-up. The median survival of the cohort was used to dichotomize the cohort into short- and long-term survivors following RT. Univariable and multivariable hazard regression analyses were performed to identify variables associated with post-RT survival.

RESULTS

From 1 January 2018 until 31 December 2019, 545 palliative RT courses for bone metastases were delivered to n = 274 metastatic prostate cancer patients with a median age of 76 yrs (Interquartile range (IQR) 39-83) and a median follow-up of 10.6 months (range 0.2 to 47.9). The median survival of the cohort was 10.6 months (IQR 3.5-25 months). The ECOG performance status of the whole cohort was ≤2 in n = 200 (73%) and 3-4 in n = 67 (24.5%). The most commonly treated sites of bone metastasis were the pelvis and lower extremities n = 130 (47.4%), skull and spine n = 114 (41.6%), and chest and upper extremities n = 30 (10.9%). Most patients had CHAARTED high volume disease n = 239 (87.2%). On multivariable hazard regression analysis, an ECOG performance status of 3-4 (p = 0.02), CHAARTED high volume disease burden (p = 0.023), and non-receipt of systemic therapy (p = 0.006) were significantly associated with worse post-RT survival.

CONCLUSION

Amongst metastatic prostate cancer patients treated with palliative radiotherapy to bone metastases and modern palliative systemic therapies, ECOG performance status, CHAARTED metastatic disease burden, and type of first-line palliative systemic therapy were significantly associated with post-RT survival durations.

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.

Prognostication in palliative radiotherapy—ProPaRT: Accuracy of prognostic scores

Background

Prognostication can be used within a tailored decision-making process to achieve a more personalized approach to the care of patients with cancer. This prospective observational study evaluated the accuracy of the Palliative Prognostic score (PaP score) to predict survival in patients identified by oncologists as candidates for palliative radiotherapy (PRT). We also studied interrater variability for the clinical prediction of survival and PaP scores and assessed the accuracy of the Survival Prediction Score (SPS) and TEACHH score.

Materials and methods

Consecutive patients were enrolled at first access to our Radiotherapy and Palliative Care Outpatient Clinic. The discriminating ability of the prognostic models was assessed using Harrell’s C index, and the corresponding 95% confidence intervals (95% CI) were obtained by bootstrapping.

Results

In total, 255 patients with metastatic cancer were evaluated, and 123 (48.2%) were selected for PRT, all of whom completed treatment without interruption. Then, 10.6% of the irradiated patients who died underwent treatment within the last 30 days of life. The PaP score showed an accuracy of 74.8 (95% CI, 69.5–80.1) for radiation oncologist (RO) and 80.7 (95% CI, 75.9–85.5) for palliative care physician (PCP) in predicting 30-day survival. The accuracy of TEACHH was 76.1 (95% CI, 70.9–81.3) and 64.7 (95% CI, 58.8–70.6) for RO and PCP, respectively, and the accuracy of SPS was 70 (95% CI, 64.4–75.6) and 72.8 (95% CI, 67.3–78.3).

Conclusion

Accurate prognostication can identify candidates for low-fraction PRT during the last days of life who are more likely to complete the planned treatment without interruption.

All the scores showed good discriminating capacity; the PaP had the higher accuracy, especially when used in a multidisciplinary way.

Validation and extension of the METSSS score in a metastatic cancer patient cohort after palliative radiotherapy within the last phase of life

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Predictive tools are intended to improve decision-making and personalize treatment.

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The “METSSS score” was proposed to predict survival after palliative radiotherapy.

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An extension of the “METSSS score” to radiotherapy during end-of-life proved valid.

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To assess the real quality of the tool, its routine use in clinical practice is encouraged.

Introduction and background

Choosing the right treatment for the right patient in a setting of metastatic cancer disease remains a challenge. To facilitate clinical decision-making, predictive tools have been developed to personalize treatment. Here, we aim to assess the use of the recently proposed “METSSS score” as a prognostic tool for overall survival of cancer patients after palliative radiotherapy in the last phase of life.

Methods

All patients treated with palliative radiotherapy at the end-of-life at the Department of Radiation Oncology of the University Hospital Zurich between January 2010 and December 2019 were included in this study. Data on demographics, diagnosis, treatment and comorbidities was extracted from the treatment planning and the electronical medical records system. To statistically assess the validity of the “METSSS score”, the mortality risk score was calculated, followed by stratification of all patients to prognostic risk groups. The prediction of the 1-year overall survival estimates was subsequently calculated.

Results

Over the past decade, 274 patients have received palliative radiotherapy during the end-of-life period. One third of patients was female (34%, n = 93). The most frequent primary tumor was lung cancer (n = 121, 44%), and 55% of patients (n = 152) had no comorbidities according to the Charlson-Deyo comorbidity index. The most common radiotherapy site was the brain and eye region (42%, n = 115). The median actual overall survival of all patients was 40 days from the start of radiotherapy. The “METSSS score” survival model predicted that 269 patients (98.1%) belong into the high-risk, four patients (1.5%) into the medium-risk, and one patient (0.4%) into the low-risk group. The predicted median 1-year overall survival was 10%.

Discussion

The METSSS score correctly predicted the survival of our end-of-life patient cohort by assigning them into the highest risk category, and it can therefore serve as a decision-making tool when assigning patient to symptomatic radiotherapy.

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.

Life expectancy in older adults with advanced cancer: Evaluation of a geriatric assessment-based prognostic model

OBJECTIVES

Oncologists estimate patients' prognosis to guide care. Evidence suggests oncologists tend to overestimate life expectancy, which can lead to care with questionable benefits. Information obtained from geriatric assessment may improve prognostication for older adults. In this study, we created a geriatric assessment-based prognostic model for older adults with advanced cancer and compared its performance to alternative models.

MATERIALS AND METHODS

We conducted a secondary analysis of a trial (URCC 13070; PI: Mohile) capturing geriatric assessment and vital status up to one year for adults age ≥ 70 years with advanced cancer. Oncologists estimated life expectancy as 0-6 months, 7-12 months, and > 1 year. Three statistical models were developed: (1) a model including age, sex, cancer type, and stage (basic model), (2) basic model + Karnofsky Performance Status (≤50, 60-70, and 80+) (KPS model), and (3) basic model +16 binary indicators of geriatric assessment impairments (GA model). Cox regression was used to model one-year survival; c-indices and time-dependent c-statistics assessed model discrimination and stratified survival curves assessed model calibration.

RESULTS

We included 484 participants; mean age was 75; 48% had gastrointestinal or lung cancer. Overall, 43% of patients died within one year. Oncologists classified prognosis accurately for 55% of patients, overestimated for 35%, and underestimated for 10%. C-indices were 0.61 (basic model), 0.62 (KPS model), and 0.63 (GA model). The GA model was well-calibrated.

CONCLUSIONS

The GA model showed moderate discrimination for survival, similar to alternative models, but calibration was improved. Further research is needed to optimize geriatric assessment-based prognostic models for use in older adults with advanced cancer.

Survival after palliative radiation therapy for cancer: The METSSS model

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

Physician-Predicted Prognosis and Palliative Radiotherapy Treatment Utilization at the End of Life: An Audit of a Large Cancer Center Network

CONTEXT

At our institution, clinical pathways capture physicians' prognostication of patients being evaluated for palliative radiotherapy. We hypothesize a low utilization rate of long-course radiotherapy (LCRT) and stereotactic ablative radiotherapy (SAbR) among patients seen at the end of life, especially those with physician-predicted poor prognosis.

OBJECTIVE

To analyze utilization rates and predictors of LCRT and SAbR at the end of life.

METHODS

A retrospective review was conducted on patients who were evaluated for palliative radiotherapy between January 2017 and August 2019 and died within 90 days of consultation. Binary logistic regression was used to identify predictors for utilization of LCRT (≥10 fractions) and SAbR.

RESULTS

A total of 1608 patients were identified, of which 1038 patients (64.6%) were predicted to die within a year. Six hundred ninety-three patients (66.8%) out of 1038 were prescribed LCRT or SAbR. On a multivariate analysis, patients were less likely to be prescribed LCRT if treated at an academic site (odds ratio [OR], 0.30; 95% confidence interval [CI], 0.23-0.39; P < 0.01) and treated for bone metastases (OR, 0.08; 95% CI, 0.05-0.11; P < 0.01) or other nonbrain/nonbone metastases (OR, 0.19; 95% CI, 0.13-0.30; P < 0.01). SAbR was less likely to be prescribed among patients predicted to die within a year (OR, 0.09; 95% CI, 0.06-0.16; P < 0.01), treated for bone metastases (OR, 0.13; 95% CI, 0.07-0.22; P < 0.01), with poor performance status (OR, 0.51; 95% CI, 0.31-0.85; P = 0.01), and with a breast primary (OR, 0.35; 95% CI, 0.15-0.82; P = 0.02).

CONCLUSION

Although most patients were predicted to have a limited prognosis, LCRT and SAbR were commonly prescribed at the end of life.

Palliative Radiation Therapy for Oncologic Emergencies in the Setting of COVID-19: Approaches to Balancing Risks and Benefits

Palliation of metastatic disease compromises a significant portion of radiation treatments in the United States. These patients present a unique challenge in resource-limited settings, as expeditious treatment is often required to prevent serious morbidity. In order to reduce the risk of infection with severe acute respiratory syndrome coronavirus-2 and maximize the benefit to patients, we present evidence-based recommendations for radiation in patients with oncologic emergencies. Radiation oncologists with expertise in the treatment of metastatic disease at a high-volume comprehensive cancer center reviewed the available evidence and recommended best practices for the treatment of common oncologic emergencies, with attention to balancing the risk of infection with severe acute respiratory syndrome coronavirus-2 and the potential morbidity of delaying treatment. Many prospective trials and national guidelines support the use of abbreviated courses of radiotherapy for patients with oncologic emergencies. As such, in the setting of the current coronavirus disease 2019 pandemic, the use of hypofractionated radiation therapy for patients requiring palliation for oncologic emergencies achieves desirable functional outcomes without compromising care.

Patient-reported symptoms and problems at admission to specialized palliative care improved survival prediction in 30,969 cancer patients: A nationwide register-based study

BACKGROUND

Large, nationally representative studies of the association between quality of life and survival time in cancer patients in specialized palliative care are missing.

AIM

The aim of this study was to investigate whether symptoms/problems at admission to specialized palliative care were associated with survival and if the symptoms/problems may improve prediction of death within 1 week and 1 month, respectively.

SETTING/PARTICIPANTS

All cancer patients who had filled in the EORTC QLQ-C15-PAL at admission to specialized palliative care in Denmark in 2010-2017 were included through the Danish Palliative Care Database. Cox regression was used to identify clinical variables (gender, age, type of contact (inpatient vs outpatient), and cancer site) and symptoms/problems significantly associated with survival. To test whether symptoms/problems improved survival predictions, the overall accuracy (area under the receiver operating characteristic curve) for different prediction models was compared. The validity of the prediction models was tested with data on 5,508 patients admitted to palliative care in 2018.

RESULTS

The study included 30,969 patients with an average age of 68.9 years; 50% were women. Gender, age, type of contact, cancer site, and most symptoms/problems were significantly associated with survival time. The predictive value of symptoms/problems was trivial except for physical function, which clearly improved the overall accuracy for 1-week and 1-month predictions of death when added to models including only clinical variables.

CONCLUSION

Most symptoms/problems were significantly associated with survival and mainly physical function improved predictions of death. Interestingly, the predictive value of physical function was the same as all clinical variables combined (in hospice) or even higher (in palliative care teams).

Prediction model for short-term mortality after palliative radiotherapy for patients having advanced cancer: a cohort study from routine electronic medical data

We developed a predictive score system for 30-day mortality after palliative radiotherapy by using predictors from routine electronic medical record. Patients with metastatic cancer receiving first course palliative radiotherapy from 1 July, 2007 to 31 December, 2017 were identified. 30-day mortality odds ratios and probabilities of the death predictive score were obtained using multivariable logistic regression model. Overall, 5,795 patients participated. Median follow-up was 39.6 months (range, 24.5-69.3) for all surviving patients. 5,290 patients died over a median 110 days, of whom 995 (17.2%) died within 30 days of radiotherapy commencement. The most important mortality predictors were primary lung cancer (odds ratio: 1.73, 95% confidence interval: 1.47-2.04) and log peripheral blood neutrophil lymphocyte ratio (odds ratio: 1.71, 95% confidence interval: 1.52-1.92). The developed predictive scoring system had 10 predictor variables and 20 points. The cross-validated area under curve was 0.81 (95% confidence interval: 0.79-0.82). The calibration suggested a reasonably good fit for the model (likelihood-ratio statistic: 2.81, P = 0.094), providing an accurate prediction for almost all 30-day mortality probabilities. The predictive scoring system accurately predicted 30-day mortality among patients with stage IV cancer. Oncologists may use this to tailor palliative therapy for patients.

A review of the Rapid Response Radiotherapy Program in patients with advanced cancer referred for palliative radiotherapy over two decades

INTRODUCTION

The Rapid Response Radiotherapy Program (RRRP) is an outpatient radiotherapy clinic for palliative cancer patients where consultation, planning, and radiation treatment can take place in 1 day, allowing for rapid access to care. The objective of this study was to compare the patient population and overall survival of patients seen in the RRRP from 2014 to 2017 to that of patients seen in 1999.

METHOD

Patient characteristics including sex, primary cancer site, sites of metastases, and Karnofsky Performance Status (KPS) were recorded at each clinic visit. Date of death (DOD) was retrieved from the Patient Care System (PCS) and Excelicare. To show overall survival from the first clinic visit, a Kaplan-Meier overall survival curve was generated in all patients from 2014 to 2017.

RESULTS

Five hundred ninety-six patients were included in the final analysis. Most patients were male (n = 347) with a primary cancer site of the lung (n = 165) and metastases to the bone (n = 475). Actuarial median overall survival was 15.3 months. In 1999, 395 patients were analyzed, in which a primary of the lung (n = 143) and metastases to the bone (n = 277) were the most prevalent. An additional 72 patients in this population had brain metastases. The actuarial median survival of the 1999 population was 4.5 months.

CONCLUSION

The changing patient population in the RRRP has resulted in visible changes in survival. This may reflect differences in the proportion of patients with specific primaries and sites of metastases, as well as improvements in the availability of palliative radiation over the last two decades.

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.

Patient-reported outcomes are independent predictors of one-year mortality and cardiac events across cardiac diagnoses: Findings from the national DenHeart survey

Aims

Patient-reported quality of life and anxiety/depression scores provide important prognostic information independently of traditional clinical data. The aims of this study were to describe: (a) mortality and cardiac events one year after hospital discharge across cardiac diagnoses; (b) patient-reported outcomes at hospital discharge as a predictor of mortality and cardiac events.

Design

A cross-sectional survey with register follow-up.

Methods

Participants: All patients discharged from April 2013 to April 2014 from five national heart centres in Denmark.

Main outcomes

Patient-reported outcomes: anxiety and depression (Hospital Anxiety and Depression Scale); perceived health (Short Form-12); quality of life (HeartQoL and EQ-5D); symptom burden (Edmonton Symptom Assessment Scale). Register data: mortality and cardiac events within one year following discharge.

Results

There were 471 deaths among the 16,689 respondents in the first year after discharge. Across diagnostic groups, patients reporting symptoms of anxiety had a two-fold greater mortality risk when adjusted for age, sex, marital status, educational level, comorbidity, smoking, body mass index and alcohol intake (hazard ratio (HR) 1.92, 95% confidence interval (CI) 1.52–2.42). Similar increased mortality risks were found for patients reporting symptoms of depression (HR 2.29, 95% CI 1.81–2.90), poor quality of life (HR 0.46, 95% CI 0.39–0.54) and severe symptom distress (HR 2.47, 95% CI 1.92–3.19). Cardiac events were predicted by poor quality of life (HR 0.71, 95% CI 0.65–0.77) and severe symptom distress (HR 1.58, 95% CI 1.35–1.85).

Conclusions

Patient-reported mental and physical health outcomes are independent predictors of one-year mortality and cardiac events across cardiac diagnoses.

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.

Prospective Validation of the Objective Prognostic Score for Advanced Cancer Patients in Diverse Palliative Settings

CONTEXT

Prognostication is an essential part of palliative care to aid decision making and negotiate goals of care. The Objective Prognostic Score (OPS) is an easy-to-use prognosticating tool to predict survival among far-advanced cancer patients in palliative care units (PCUs) in Korea.

OBJECTIVES

This study aimed to prospectively validate the OPS for advanced cancer patients in the palliative care teams (PCTs), PCUs, and home-based palliative care (HPC) in Japan.

METHODS

This was a substudy of a multicenter prospective cohort study that was conducted to validate and compare prognostic tools among advanced cancer patients in Japan. Participants' survival was calculated according to OPS 3 as a cutoff for predicting survival of less than three weeks. Overall accuracy and area under the receiver operator characteristic curves of OPS 3 were calculated for PCT, PCU, and HPC, respectively.

RESULTS

A total of 1146 cases (PCTs 441, PCUs 519, and HPCs 186 cases) were included in final analyses. The overall accuracy of OPS 3 for predicting three-week survival ranged from 0.70 to 0.78 across diverse palliative care settings. The c-statistics ranged from 0.742 to 0.808 across three settings. Participants in the PCT showed the highest overall accuracy and c-statistics for OPS.

CONCLUSION

The OPS can be used for prognostication among advanced cancer patients in PCT, PCU, and HPC settings.

Survival and prognostic factors in patients with stable and unstable spinal bone metastases from solid tumors: a retrospective analysis of 915 cases

Background

Adequate prediction of survival plays an important role in treatment decisions for patients with spinal bone metastases (SBM). Several prognostic factors are already used in daily clinical practice, but factors related to stability of SBM are still unknown. Therefore, we designed this study to identify these prognostic factors.

Methods

We retrospectively assessed 915 patients from solid tumors with commonly metastased into the bone treated at our department between January 2000 and January 2012. Lung cancer (NSCLC), breast and renal cancer listed in Table 1 are the most common solid tumors with bone metastasis in this study. Prostate carcinoma was excluded due to osteoblastic SBM with no influence for stability. We calculated overall survival (OS) and bone survival (BS; time between first diagnosis of bone metastases until death) with the Kaplan-Meier method and assessed prognostic factors for BS with the log-rank test and a Cox regression model separately for patients with stable and unstable SBM.

Results

Median follow-up was 9.3 months. OS after 6 months, 1, 2, and 5 years was 81, 62, 42, and 25 % in patients with stable SBM and 78, 57, 38, and 22 % in patients with unstable SBM (p = 0.851). BS was 57, 38, 22, and 5 % in the group of stable SBM after 6 months, 1, 2, and 5 years. For patients with unstable SBM BS after 6 months, 1, 2, and 5 years was 59, 39, 19, and 8 % (p = 0.755). In multivariate analysis we found male gender (HR = 1.27 [95 % CI 1.01–1.60], p = 0.04), Karnofsky performance status (KPS) <80 % (HR = 1.27 [95%CI 1.04–1.55], p = 0.02) and non-small cell lung cancer (NSCLC; HR = 2.77 [95%CI 1.99–3.86], p < 0.0001) to be independent prognostic factors for shortened survival in patients with stable SBM. Independent prognostic factors for unstable SBM were age per year (HR = 1.01 [95 % CI 1.0–1.02], p = 0.025), multiple SBM (HR = 1.35 [95 % CI 1.1–1.65], p = 0.003), and NSCLC (HR = 2.0 [95 % CI 1.43–2.80], p < 0.0001). Additionally, not wearing an orthopedic corset (HR = 0.77 [95 % CI 0.62–0.96], p = 0.02) was associated with prolonged BS in patients with unstable SBM and in both groups BS was significantly longer in patients without liver metastases (stable SBM: HR = 0.72 [95 % CI 0.56–0.92], p = 0.008; unstable SBM: HR = 0.71 [95 % CI 0.54–0.92], p = 0.01).

Conclusions

Survival was equal for patients with stable and unstable SBM. However, prognostic factors differed in both groups and stability should therefore be considered in treatment decision-making.

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.

Clinical Predictors of Survival for Patients with Stage IV Cancer Referred to Radiation Oncology

BACKGROUND

There is an urgent need for a robust, clinically useful predictive model for survival in a heterogeneous group of patients with metastatic cancer referred to radiation oncology.

METHODS

From May 2012 to August 2013, 143 consecutive patients with stage IV cancer were prospectively evaluated by a single radiation oncologist. We retrospectively analyzed the effect of 29 patient, laboratory and tumor-related prognostic factors on overall survival using univariate analysis. Variables that were statistically significant on univariate analysis were entered into a multivariable Cox regression to identify independent predictors of overall survival.

RESULTS

The median overall survival was 5.5 months. Four prognostic factors significantly predicted survival on multivariable analysis including ECOG performance status (0-1 vs. 2 vs. 3-4), number of active tumors (1 to 5 vs. ≥ 6), albumin levels (≥ 3.4 vs. 2.4 to 3.3 vs. < 2.4 and primary tumor site (Breast, Kidney or Prostate vs. Other). Risk group stratification was performed by assigning points for adverse prognostic factors resulting in very low, low, intermediate and high risk groups. The median survival was > 31.4 months for very low risk patients compared to 14.5 months for low risk, 4.1 months for intermediate risk and 1.2 months for high risk (p < 0.001).

CONCLUSIONS

These data suggest that a model that considers performance status, extent of disease, primary tumor site and serum albumin represents a simple model to accurately predict survival for patients with stage IV cancer who are potential candidates for radiation therapy.

Longitudinal study on the impact of physical activity on the symptoms of lung cancer survivors

PURPOSE

To examine the effect of physical activity on the physical and psychosocial symptoms of lung cancer survivors.

METHODS

A longitudinal design was used in this study. Participants were recruited from the chest and surgical departments of medical centers in Taiwan. The instruments used were the Godin Leisure-Time Exercise Questionnaire and the Taiwanese version of the M.D. Anderson Symptom Inventory.

RESULTS

In total, 185 survivors were followed up for 6 months (response rate 66%). Disturbed sleep was the most prevalent symptom in the participants. A generalized estimating equation (GEE) method was employed to analyze the relationships among intensity of physical activity, symptom severity, and symptom interference in the daily life of the participants. Regarding symptom severity, significant differences were observed in fatigue, drowsiness, and disturbed sleep between the participants who engaged in moderate physical activity and those who did not engage in any physical activity. Regarding symptom interference, the participants who engaged in light physical activity experienced a significantly lower level of symptom interference than did those with a sedentary lifestyle.

CONCLUSION

This is the first study to explore the role of physical activity in alleviating symptoms in lung cancer survivors by using the GEE method. The results suggest that physical activity plays an essential role in alleviating the physical and psychological symptoms of lung cancer survivors.

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.

Development of a score predicting survival after palliative reirradiation

Purpose. To develop a prognostic model for predicting survival after palliative reirradiation (PR). Methods and Materials. We analyzed all 87 PR courses administered at a dedicated palliative radiotherapy facility between 20.06.2007 (opening) and 31.12.2009. Uni- and multivariate survival analyses were performed, the previously published survival prediction score (SPS) was evaluated, and a PR-specific prognostic score was calculated. Results. In multivariate analysis, four parameters significantly influenced survival: performance status, use of steroids, presence of liver metastases, and pleural effusion. Based on these parameters, a 4-tiered score was developed. Median survival was 24.5 months for the favorable group, 9.7 and 2.8 months for the two intermediate groups, and 1.1 months for the unfavorable group (P = 0.019 for comparison between the two favorable groups and P ≤ 0.002 for all other pair-wise comparisons). All patients in the unfavorable group died within 2 months. Conclusion. The performance of PR-specific score was promising and might facilitate identification of patients who survive long enough to benefit from PR. It should be validated in independent patient groups, ideally from several institutions and countries.

Palliative radiotherapy at the end of life: a critical review

When delivered with palliative intent, radiotherapy can help to alleviate a multitude of symptoms related to advanced cancer. In general, time to symptom relief is measured in weeks to months after the completion of radiotherapy. Over the past several years, an increasing number of studies have explored rates of radiotherapy use in the final months of life and have found variable rates of radiotherapy use. The optimal rate is unclear, but would incorporate anticipated efficacy in patients whose survival allows it and minimize overuse among patients with expected short survival. Clinician prediction has been shown to overestimate the length of survival in repeated studies. Prognostic indices can provide assistance with estimations of survival length and may help to guide treatment decisions regarding palliative radiotherapy in patients with potentially short survival times. This review explores the recent studies of radiotherapy near the end of life, examines general prognostic models for patients with advanced cancer, describes specific clinical circumstances when radiotherapy may and may not be beneficial, and addresses open questions for future research to help clarify when palliative radiotherapy may be effective near the end of life.

Simple prognostic model for patients with advanced cancer based on performance status

PURPOSE

Providing survival estimates is important for decision making in oncology care. The purpose of this study was to provide survival estimates for outpatients with advanced cancer, using the Eastern Cooperative Oncology Group (ECOG), Palliative Performance Scale (PPS), and Karnofsky Performance Status (KPS) scales, and to compare their ability to predict survival.

METHODS

ECOG, PPS, and KPS were completed by physicians for each new patient attending the Princess Margaret Cancer Centre outpatient Oncology Palliative Care Clinic (OPCC) from April 2007 to February 2010. Survival analysis was performed using the Kaplan-Meier method. The log-rank test for trend was employed to test for differences in survival curves for each level of performance status (PS), and the concordance index (C-statistic) was used to test the predictive discriminatory ability of each PS measure.

RESULTS

Measures were completed for 1,655 patients. PS delineated survival well for all three scales according to the log-rank test for trend (P < .001). Survival was approximately halved for each worsening performance level. Median survival times, in days, for each ECOG level were: EGOG 0, 293; ECOG 1, 197; ECOG 2, 104; ECOG 3, 55; and ECOG 4, 25.5. Median survival times, in days, for PPS (and KPS) were: PPS/KPS 80-100, 221 (215); PPS/KPS 60 to 70, 115 (119); PPS/KPS 40 to 50, 51 (49); PPS/KPS 10 to 30, 22 (29). The C-statistic was similar for all three scales and ranged from 0.63 to 0.64.

CONCLUSION

We present a simple tool that uses PS alone to prognosticate in advanced cancer, and has similar discriminatory ability to more complex models.

External validation of the number of risk factors score in a palliative care outpatient clinic at a comprehensive cancer center

BACKGROUND

Prognostic tools are available to predict if terminally ill cancer patients have days or weeks to live. Tools for predicting the prognosis in ambulatory patients at an earlier stage are lacking. The Number of Risk Factors (NRF) score developed in ambulatory cancer patients receiving palliative radiation therapy may be suitable for this purpose but has not been tested in a palliative care setting.

OBJECTIVE

Our aim was to evaluate the prognostic accuracy of the NRF score in patients referred to a palliative care outpatient clinic at a comprehensive cancer center.

METHODS

We conducted a retrospective chart review of NRF scores and survival in 300 consecutive, newly referred patients. Measurements included primary cancer type, extent of disease, Karnofsky Performance Scale (KPS) score, and survival duration after first visit. One point was allocated each for cancer other than breast cancer, metastases other than bone, and low KPS score.

RESULTS

Of 300 patients, 236 (79%) had advanced disease. Of those 236, 212 (90%) had a cancer other than breast cancer, 180 (76%) had metastatic disease in sites other than bone, and 64 (27%) had a KPS score <70%. During the 2-year follow-up, 221 (94%) patients died, with overall median survival of 4.9 months (95% confidence interval, 3.9-6.1 months). NRF scores of 0 to 1, 2, and 3 split the sample into subgroups with highly significantly different survival among the groups, with medians 9.0, 4.6, and 2.1 months, respectively (Wilcoxon test χ(2)=43.9, degrees of freedom [df] 2, p<0.0001). A simple parametric model was fit to determine the probability of subgroup members surviving to a certain number of months.

CONCLUSIONS

In cancer patients referred to palliative care earlier in their disease trajectory, the NRF score may be a useful prognostic tool. Further validation in other palliative care populations is needed.

Palliative radiation therapy in patients with metastasized pancreatic cancer - description of a rare patient group

Background

Pancreatic cancer (PAC) patients experience a high rate of locoregional recurrences and distant metastasis finally leading to their demise even after curatively-intended multidisciplinary treatment approaches including surgery, chemotherapy and radiotherapy. However, clinical reports on bone and brain metastases in PAC patients are extremely rare and thus timing and dose description are not well defined. Our work therefore summarizes a mono-institutional experience on the use of radiotherapy (RT) for PAC patients with metastatic disease with the aim of identifying overall survival and treatment response in this rarely reported patient group.

Method

Forty-four PAC patients with 66 metastatic lesions were treated with palliative radiotherapy (RT). Thirty-three patients (48 lesions), 7 patients (11 lesions) and 5 patients (7 lesions) with bone, liver and brain metastases analyzed respectively were analyzed; one patient had both bone and cerebral metastases and was treated for the lesions, thus including him in both subgroups. Indications for RT were pain, neurological impairment, risk of pathological fracture or imminent danger for development of any of these conditions in case of tumor progression. Median age was 64 years (range 38 to 78 years) and there were 27 male (61%) and 17 (39%) female patients. Analyses of overall survival (OS) and local control were performed. OS was calculated from the first day of RT.

Results

Median overall survival (mOS) of all patients after start of RT was 4.2 months. Survival rates after 1, 3 and 6 months were 79.3%, 55.3% and 30.3% respectively. Patients presenting with bone metastasis had a mOS of 3.1 months and after 1, 3 and 6 months, survival rates were 75.3%, 46.5% and 19.9% respectively. Symptomatic response to therapy was recorded in 85% of all evaluated patients with bone metastasis. Patients undergoing radiosurgery because of liver metastasis were locally controlled in all but one patient after a median follow-up of 8.3 months.

Conclusion

Overall survival of all patients with metastatic disease was considerably worse. A major goal for the future must be the selection of an appropriate RT treatment in terms of duration and technique for these PAC patients.

Survival prediction score: a simple but age-dependent method predicting prognosis in patients undergoing palliative radiotherapy

Purpose. Validation of a Canadian three-tiered prognostic model (survival prediction score, SPS) in Norwegian cancer patients referred for palliative radiotherapy (PRT), and evaluation of age-dependent performance of the model. Patients and Methods. We analyzed all 579 PRT courses administered at a dedicated PRT facility between 20.06.07 and 31.12.2009. SPS was assigned as originally described, That is, by taking into consideration three variables: primary cancer type, site of metastases, and performance status. Results. Patients with poor prognosis (non-breast cancer, metastases other than bone, and Karnofsky performance status (KPS) ≤ 60) had median survival of 13 weeks. Those with intermediate prognosis (two of these parameters) survived for a median of 29 weeks, and patients with good prognosis for a median of 114 weeks, P < 0.001. While this model performed well in patients who were 60 years or older, it was less satisfactory in younger patients (no significant difference between the good and intermediate prognosis groups). Conclusion. SPS should mainly be used to predict survival of elderly cancer patients. However, even in this group accuracy is limited because the good prognosis group contained patients with short survival, while the poor prognosis group contained long-term survivors. Thus, improved models should be developed.

Patients who die during palliative radiotherapy. Status survey

BACKGROUND AND PURPOSE

Palliative radiotherapy (RT) is routinely used in end of life care of patients with advanced malignancies; however, unnecessarily burdensome treatment shortly before death should be avoided. There is little knowledge on incidence and causes of intercurrent deaths during palliative RT.

PATIENTS AND METHODS

In this study death events among inpatients receiving palliative RT between January 2009 and December 2011 at this department were retrospectively analyzed. Among epidemiological factors, treatment schedule and chronology, latency and duration of treatment in relation to the actual survival were identified.

RESULTS

In this study 52 patients died during or shortly after palliative RT. Symptomatic bone metastases and brain metastases represented the most common RT indications. The general health status was poor with a median Karnofsky performance score of 50 %, RT was realized with a median single dose of 2.5 Gy to a median total dose of 30.5 Gy and was stopped prematurely in 73 % of patients. On average 53 % of the remaining lifetime was occupied by latency to starting RT. Once RT was begun the treatment duration required a median 64 % of the still remaining lifetime.

CONCLUSION

The majority of patients who died had explicitly adverse pre-existing factors and rarely completed RT as scheduled. Latency to RT and RT duration occupied more than half of the remaining lifetime.

Palliative radiotherapy in patients with a poor performance status: the palliative effect is correlated with prolongation of the survival time

Background

The purpose of this study was to analyze the efficacy and tolerability of palliative radiotherapy (RT) in patients with a poor performance status (PS) and to evaluate the relationship between the palliative effect and survival time.

Methods

One hundred and thirty-three patients with a poor PS (Eastern Cooperative Oncology Group 3 or 4) were treated with palliative RT using the three-dimensional conformal technique and retrospectively analyzed. Each patient's primary symptom treated with palliative RT as the major cause of the poor PS was evaluated using the second item of the Support Team Assessment Schedule (STAS) at the start and one week after the completion of palliative RT.

Results

One hundred and fourteen (86%) of the 133 patients completed the planned palliative radiation dose. Grade 3 acute toxicity was observed in two patients (2%) and Grade 2 acute toxicity was observed in 10 patients (9%). No Grade 2 or higher late toxicities were observed, except for Grade 3 radiation pneumonitis in one patient. Improvement in the STAS scores between pre- and post-palliative RT was recorded in 76 (61%) of the 125 patients with available scores of STAS. A significant improvement in the mean STAS score between pre- and post-palliative RT was recognized (p < 0.0001). Improvement in the STAS score was found to be the most statistically significant prognostic factor for overall survival after palliative RT in both the multivariate and univariate analyses. The median overall survival time in the patients with an improvement in the STAS score was 6.4 months, while that in the patients without improvement was 2.4 months (p < 0.0005).

Conclusions

Palliative RT in patients with a poor PS provides symptomatic benefits in more than half of patients without inducing severe toxicities. The palliative effect is strongly correlated with prolongation of the survival time and may contribute to improving the remaining survival time in patients with metastatic/advanced cancer with a poor PS.

Prevalence, intensity, and prognostic significance of common symptoms in terminally ill cancer patients

BACKGROUND

Quality of life and palliative management of end-stage cancer patients should improve with greater understanding of the prevalence, intensity, and prognostic significance of their symptoms.

OBJECTIVE

We investigated the association between prevalence and intensity of common symptoms and overall survival in Chinese end-stage cancer patients.

DESIGN

For this cross-sectional study, 163 Chinese patients with end-stage cancer completed an Edmonton Symptom Assessment questionnaire, and each was given a Karnofsky Performance Status (KPS) score. Overall survival was estimated via the Kaplan-Meier method. Factors affecting overall survival were determined by univariate and multivariate Cox regression analyses.

RESULTS

Mean survival of these patients was 51 days. Pain, lack of appetite, and poor well-being were the most frequent symptoms, in 90.2%, 88.3%, and 87.7%, respectively. The most severe symptoms were fatigue, lack of appetite, drowsiness, and poor well-being. Fatigue, lack of appetite, drowsiness, shortness of breath, poor well-being, depression, and KPS score significantly affected overall survival rate, with a relative risk of dying of 1.560, 2.320, 1.684, 1.295, 1.912, 1.414, and 0.487, respectively (Cox regression coefficients: 0.361, 0.827, 0.539, 0.185, 0.694, 0.318, and -0.602). Fatigue, lack of appetite, shortness of breath, age, and KPS score were independent risk factors of overall survival, with a relative risk of dying of 1.581, 1.122, 1.123, 1.022, and 0.797, respectively (Cox regression coefficients: 0.458, 0.115, 0.116, 0.022, and -0.227).

CONCLUSION

Fatigue, shortness of breath, lack of appetite, age, and KPS score were associated with overall survival of end-stage Chinese cancer patients.

A predictive model to identify hospitalized cancer patients at risk for 30-day mortality based on admission criteria via the electronic medical record

BACKGROUND

This study sought to develop a predictive model for 30-day mortality in hospitalized cancer patients, by using admission information available through the electronic medical record.

METHODS

Observational cohort study of 3062 patients admitted to the oncology service from August 1, 2008, to July 31, 2009. Matched numbers of patients were in the derivation and validation cohorts (1531 patients). Data were obtained on day 1 of admission and included demographic information, vital signs, and laboratory data. Survival data were obtained from the Social Security Death Index.

RESULTS

The 30-day mortality rate of the derivation and validation samples were 9.5% and 9.7% respectively. Significant predictive variables in the multivariate analysis included age (P < .0001), assistance with activities of daily living (ADLs; P = .022), admission type (elective/emergency) (P = .059), oxygen use (P < .0001), and vital signs abnormalities including pulse oximetry (P = .0004), temperature (P = .017), and heart rate (P = .0002). A logistic regression model was developed to predict death within 30 days: Score = 18.2897 + 0.6013*(admit type) + 0.4518*(ADL) + 0.0325*(admit age) - 0.1458*(temperature) + 0.019*(heart rate) - 0.0983*(pulse oximetry) - 0.0123 (systolic blood pressure) + 0.8615*(O2 use). The largest sum of sensitivity (63%) and specificity (78%) was at -2.09 (area under the curve = -0.789). A total of 25.32% (100 of 395) of patients with a score above -2.09 died, whereas 4.31% (49 of 1136) of patients below -2.09 died. Sensitivity and positive predictive value in the derivation and validation samples compared favorably.

CONCLUSIONS

Clinical factors available via the electronic medical record within 24 hours of hospital admission can be used to identify cancer patients at risk for 30-day mortality. These patients would benefit from discussion of preferences for care at the end of life.

A score to identify patients with metastatic spinal cord compression who may be candidates for best supportive care

BACKGROUND

The objective of the current study was to develop a scoring system that identifies those patients with metastatic spinal cord compression who may be candidates for best supportive care or single-fraction radiotherapy.

METHODS

Ten potential prognostic factors were retrospectively analyzed in 2029 patients, including age, gender, Eastern Cooperative Oncology Group performance status, tumor type, number of involved vertebrae, further bone metastases, visceral metastases, interval from time of cancer diagnosis to the development of MSCC, time to the development of motor deficits, and ambulatory status.

RESULTS

On multivariate analysis, Eastern Cooperative Oncology Group performance status, tumor type, bone metastases, visceral metastases, interval from cancer diagnosis to the development of metastatic spinal cord compression, time to the development of motor deficits, and ambulatory status were found to be significantly associated with survival. The risk score represented the sum of the scores for each of these factors, obtained from the probability of the patient dying within 2 months (shown as the percentage) divided by 10. Risk scores ranged between 6 and 25 points. At a cutoff value of ≥ 24 points, the specificity was 99.8% and the positive predictive value was 96.0%, which indicates that approximately 4% of the patients predicted to die within 2 months survived > 2 months.

CONCLUSIONS

This score identifies patients who have a very poor survival with a high specificity and a high positive predictive value. Patients with a score of ≥ 24 points have a very high probability of dying within 2 months. Thus, overtreatment with intensive therapies can be avoided in these patients, who are very unlikely to benefit.

Predicting survival in advanced hematologic malignancies: do patient-reported symptoms matter?

OBJECTIVE

To investigate whether patient-reported symptoms provide independent prognostic information for survival in patients with hematological malignancies.

STUDY DESIGN AND SETTING

Overall 119 patients with various diagnoses were recruited in an observational study and symptoms were assessed with the M.D. Anderson Symptom Inventory (MDASI). Key potential socio-demographic, biomedical, and physician-reported prognostic candidates were also considered. The Cox proportional hazards regression model was used for both univariate and multivariate analyses of survival. Additional sensitivity analysis, based on 500 bootstrap-generated simulation datasets, was also performed to confirm the results obtained with the Cox regression model.

RESULTS

The median survival of the entire cohort was 4.8 months (range 0-28 months). The MDASI was completed at baseline by 91% of patients. The final multivariate model retained two parameters as independent prognostic factors for survival: clinical prognostic group and patient's self-reported severity of drowsiness. The following hazard ratios (HR) were found for curable vs. terminal: 0.055 (95% CI, 0.022-0.136; P < 0.001) and 0.193 (95% CI, 0.103-0.362: P < 0.001) for advanced vs. terminal. Patient's self-reported severity of drowsiness independently predicted survival with a HR of 1.801 (95% CI, 1.044-3.107; P = 0.033). Additional sensitivity analysis confirmed the independent prognostic value of variables identified in this study.

CONCLUSION

The results suggest that patients' self-reporting of symptoms provides independent prognostic information for survival in patients with hematologic malignancies. These findings underscore the value of collecting patient-reported symptom data in routine clinical practice.

Prognostic factors for non-small cell lung cancer with bone metastasis at the time of diagnosis

INTRODUCTION

The skeletal system is one of the most common distant sites of metastatic non-small cell lung cancer (NSCLC) which may lead to skeletal-related event (SRE). The purpose of this study was to assess the frequency of SRE and the prognostic factors of overall survival (OS) in patients presenting bone metastasis in NSCLC.

METHODS

Two hundred and twenty NSCLC patients with skeletal metastases at the time of diagnosis between January 2000 and August 2007 were investigated retrospectively.

RESULTS

Forty-seven of 110 patients (43%) without a SRE at the time of diagnosis experienced their first SRE during the follow-up. Patients with squamous cell carcinoma had a 1.8-times higher risk of short OS [95% confidence interval (CI) 1.11-2.84, p=0.016], compared with patients with non-squamous cell carcinoma, and patients treated with EGFR TKIs achieved a 50% protective effect in OS compared with patients not treated with them (95% CI 0.32-0.80, p=0.004). Patients with ECOG performance status 0-1 and single bone metastasis had a 1.8-times (95% CI 1.13-2.60, p=0.003) and 2.4-times (95% CI 1.26-4.46, p=0.008) longer OS than patients with performance status≥2 and two or more bone metastases, respectively.

CONCLUSION

Our study demonstrated that the frequency of SRE was common and single bone metastasis, good performance status (ECOG 0, 1), EGFR TKI treatment had good prognosis and histology of squamous cell carcinoma had bad prognosis.

Symptoms tell it all: a systematic review of the value of symptom assessment to predict survival in advanced cancer patients

PURPOSE

To determine the prognostic meaning of symptoms in patients with advanced cancer.

DESIGN

Medline, Embase, Cochrane and Cinahl databases were systematically explored. The predicting symptoms were also evaluated in the three stages of palliative care: disease-directed palliation, symptom-oriented palliation and palliation in the terminal stage.

RESULTS

Out of 3167 papers, forty-four papers satisfied all criteria. Confusion, anorexia, fatigue, cachexia, weight loss, cognitive impairment, drowsiness, dyspnea, dysphagia, dry mouth and depressed mood were associated with survival in ≥ 50% of the studies evaluating these symptoms. Multivariate analysis showed confusion, anorexia, fatigue, cachexia, weight loss, dyspnea and dysphagia as independent prognostic factors in 30-56% of the studies. In the stage of disease-directed palliation anorexia, cachexia, weight loss, dysphagia and pain and in the stage of symptom-oriented palliation confusion, fatigue, cachexia, weight loss, dyspnea, dysphagia and nausea were shown to be independent predictors of survival in >30% of the studies.

CONCLUSION

Symptoms with independent predictive value are confusion, anorexia, fatigue, cachexia, weight loss, dyspnea and dysphagia. New insights are added by the variance between the three palliative stages.

Development of a prognostic model for six-month mortality in older adults with declining health

CONTEXT

Estimation of six-month prognosis is essential in hospice referral decisions, but accurate, evidence-based tools to assist in this task are lacking.

OBJECTIVES

To develop a new prognostic model, the Patient-Reported Outcome Mortality Prediction Tool (PROMPT), for six-month mortality in community-dwelling elderly patients.

METHODS

We used data from the Medicare Health Outcomes Survey linked to vital status information. Respondents were 65 years old or older, with self-reported declining health over the past year (n=21,870), identified from four Medicare Health Outcomes Survey cohorts (1998-2000, 1999-2001, 2000-2002, and 2001-2003). A logistic regression model was derived to predict six-month mortality, using sociodemographic characteristics, comorbidities, and health-related quality of life (HRQOL), ascertained by measures of activities of daily living and the Medical Outcomes Study Short Form-36 Health Survey; k-fold cross-validation was used to evaluate model performance, which was compared with existing prognostic tools.

RESULTS

The PROMPT incorporated 11 variables, including four HRQOL domains: general health perceptions, activities of daily living, social functioning, and energy/fatigue. The model demonstrated good discrimination (c-statistic=0.75) and calibration. Overall diagnostic accuracy was superior to existing tools. At cut points of 10%-70%, estimated six-month mortality risk sensitivity and specificity ranged from 0.8% to 83.4% and 51.1% to 99.9%, respectively, and positive likelihood ratios at all mortality risk cut points ≥40% exceeded 5.0. Corresponding positive and negative predictive values were 23.1%-64.1% and 85.3%-94.5%. Over 50% of patients with estimated six-month mortality risk ≥30% died within 12 months.

CONCLUSION

The PROMPT, a new prognostic model incorporating HRQOL, demonstrates promising performance and potential value for hospice referral decisions. More work is needed to evaluate the model.

Prospective comparison of prognostic scores in palliative care cancer populations

PURPOSE

Predicting prognosis in advanced cancer aids physicians in clinical decision making and can help patients and their families to prepare for the time ahead.

MATERIALS AND METHODS

This multicenter, observational, prospective, nonrandomized population-based study evaluated life span prediction of four prognostic scores used in palliative care: the original palliative prognostic score (PaP Score), a variant of PaP Score including delirium (D-PaP Score), the Palliative Performance Scale, and the Palliative Prognostic Index.

RESULTS

A total of 549 patients were enrolled onto the study. Median survival of the entire group was 22 days (95% confidence intervals [95% CI] = 19-24). All four prognostic models discriminated well between groups of patients with different survival probabilities. Log-rank tests were all highly significant (p < .0001). The PaP and D-PaP scores were the most accurate, with a C index of 0.72 (95% CI = 0.70-0.73) and 0.73 (95% CI = 0.71-0.74), respectively.

CONCLUSION

It can be confirmed that all four prognostic scores used in palliative care studies accurately identify classes of patients with different survival probabilities. The PaP Score has been extensively validated and shows high accuracy and reproducibility in different settings.

Validation of a Predictive Model for Survival in Patients With Advanced Cancer: Secondary Analysis of RTOG 9714

Background

The objective of this study was to validate a simple predictive model for survival of patients with advanced cancer.

Methods

Previous studies with training and validation datasets developed a model predicting survival of patients referred for palliative radiotherapy using three readily available factors: primary cancer site, site of metastases and Karnofsky performance score (KPS). This predictive model was used in the current study, where each factor was assigned a value proportional to its prognostic weight and the sum of the weighted scores for each patient was survival prediction score (SPS). Patients were also classified according to their number of risk factors (NRF). Three risk groups were established. The Radiation Therapy and Oncology Group (RTOG) 9714 data was used to provide an additional external validation set comprised of patients treated among multiple institutions with appropriate statistical tests.

Results

The RTOG external validation set comprised of 908 patients treated at 66 different radiation facilities from 1998 to 2002. The SPS method classified all patients into the low-risk group. Based on the NRF, two distinct risk groups with significantly different survival estimates were identified. The ability to predict survival was similar to that of the training and previous validation datasets for both the SPS and NRF methods.

Conclusions

The three variable NRF model is preferred because of its relative simplicity.

Evaluation and management of fatigue in oncology: a multidimensional approach

Fatigue, one of the most common symptoms experienced by cancer patients, is multidimensional and is associated with significant impairment in functioning and overall quality of life. Although the precise pathophysiology of cancer-related fatigue (CRF) is not well understood, a number of metabolic, cytokine, neurophysiologic, and endocrine changes have been described in these patients. A better understanding of these abnormalities is likely to lead to novel therapeutic interventions. Clinically, all patients presenting with significant fatigue should be evaluated for treatable conditions that might contribute to this symptom. Exercise and treatment of anemia are the two most established interventions for CRF. Psychostimulants seem promising based on early studies. Several complementary medicine treatments that showed efficacy in preliminary studies merit further testing.

Validation of prognostic scores for survival in cancer patients beyond first-line therapy

Background

We aimed to validate prognostic scores for survival in patients undergoing chemotherapy for advanced or metastatic cancer after first-line treatment.

Methods

We previously described two models with good prognostic value based on a combination of Performance Status (PS) and either lactate dehydrogenase (LDH) level or lymphocyte count. These factors were evaluated for their ability to predict overall survival (OS) in a prospective cohort of 299 patients. Clinical and blood parameters were prospectively recorded. Candidate prognostic factors for OS with 0.05 significance level in univariate analysis were included in a multivariate Cox model.

Results

Median age was 59 years (range: 26-85). Primary tumor sites were breast (45%), lung (15%), ovaries (11%) and others (29%). The number of metastatic sites was 1 (29%), 2 (48%), >2 (23%). Median follow-up and median OS were 12 and 6 months, respectively. Multiple regression analysis confirmed that PS >1, lymphocyte count ≤700/μL and LDH >600 UI/L were independent predictors of short OS, as well as interleukin 6 (IL-6) level, serum albumin concentration and platelet count.

Conclusions

Prognostic scores using PS plus LDH level or PS plus lymphocyte count were validated for predicting survival in metastatic cancer patients in relapse beyond first-line treatment. A score combining PS, LDH, lymphocyte and platelet count, serum albumin and IL-6 level was superior in determining patients' prognosis.

Edmonton symptom assessment scale as a prognosticative indicator in patients with advanced cancer

BACKGROUND

Few studies incorporate patient self-assessment scales in prognostic models of survival prediction. The Edmonton Symptom Assessment Scale (ESAS) is commonly used as a symptom screening tool in cancer patients.

OBJECTIVE

The goal of this study was to evaluate the prognostic value of the ESAS for survival prediction in the advanced cancer population.

MATERIALS AND METHODS

Patients completed the ESAS and demographic information prior to palliative radiotherapy consultation and at follow-up at the Odette Cancer Centre between 1999 and 2009. Generalized estimating equation (GEE) methodology was applied to analyze ESAS trends within the last months of life. One-way analysis of variance (ANOVA) with repeated measurements was used to characterize trends between time periods.

RESULTS

ESAS records (2377) from 808 patients (433 male and 375 female) were included in this cohort. Median age was 68 years (range 32-95) with median Karnofsky performance status (KPS) of 60 (range 10-100). Primary cancer sites were of the lung (36%), breast (20%), and prostate (19%). All nine ESAS symptoms significantly deteriorated in the last 4 weeks immediately before death when compared with those scores in the preceding months. At one week prior to death, the worst ESAS symptoms experienced by patients were fatigue, appetite, and well-being with mean scores of 7.4, 6.9, and 6.1, respectively.

CONCLUSIONS

All ESAS scores significantly worsened in the last 4 weeks prior to death compared with those in the previous months. Sudden deterioration of the global ESAS symptoms may predict impending death. Future studies on a prognostic model should incorporate both ESAS symptom severity and trends.