Baseline Edmonton Symptom Assessment System and survival in metastatic renal cell carcinoma

Original Article

Baseline Edmonton Symptom Assessment System and survival in metastatic renal cell carcinoma


J. Graham, MD*, J. Gingerich, MD*, P. Lambert, A. Alamri, MD, P. Czaykowski, MD MSc*


doi: http://dx.doi.org/10.3747/co.25.3935


ABSTRACT

Background

Baseline symptom burden as measured using the Edmonton Symptom Assessment System (esas), a patient-reported, validated, and reliable tool measuring symptom severity in 9 separate domains, might yield prognostic information in patients receiving treatment for metastatic renal cell carcinoma (mrcc) and might add to the existing prognostic models.

Methods

In this retrospective single-centre cohort study, we included patients receiving first-line sunitinib therapy for mrcc between 2008 and 2012. Baseline variables included information relevant to the pre-existing prognostic models and pre-treatment esas summation scores (added together across all 9 domains), with higher scores representing greater symptom burden. We used Kaplan–Meier curves and Cox regression modelling to determine if symptom burden can provide prognostic information with respect to overall survival.

Results

We identified 68 patients receiving first-line therapy for mrcc. Most had intermediate- or poor-risk disease based on both the Memorial Sloan Kettering Cancer Center (mskcc) and the International Metastatic Renal Cell Carcinoma Database Consortium (imdc) models. The median baseline esas summation score was 16 (range: 6–57). In univariable analysis, the hazard ratio for overall survival was 1.270 (p = 0.0047) per 10-unit increase in summation esas. In multivariable analysis, the hazard ratio was 1.208 (p = 0.0362) when controlling for mskcc risk group and 1.240 (p = 0.019) when controlling for imdc risk group.

Conclusions

Baseline symptom burden as measured by esas score appears to provide prognostic information for survival in patients with mrcc. Those results should encourage the investigation of patient-reported symptom scales as potential prognostic indicators for patients with advanced cancer.

KEYWORDS: Kidney cancer, renal cell carcinoma, patient-reported outcomes, prognosis, Edmonton Symptom Assessment System

BACKGROUND

Despite impressive advances in treatment, renal cell carcinoma (rcc) remains a significant global health issue. Approximately 300,000 people worldwide are diagnosed with rcc annually, resulting in 144,000 deaths, most of which are attributable to metastatic disease1.

In metastatic rcc (mrcc), clinical and laboratory variables have been incorporated into a number of models that are designed to stratify patients into prognostic groups and to inform treatment decisions. The Memorial Sloan Kettering Cancer Center (mskcc) and the International Metastatic Renal Cell Carcinoma Database Consortium (imdc) models are the two most commonly used in clinical practice2,3. The imdc model was validated in the era of targeted therapy, and it is now the model most widely used in clinical practice. The model incorporates a number of variables, including Karnofsky performance status, time from diagnosis to initiation of therapy, and laboratory values such as hemoglobin, serum calcium, neutrophil count, and platelet count. Although both models include a measure of performance status, they do not incorporate baseline symptom burden or quality-of-life assessments.

Patients with advanced rcc can present with a diverse range of symptoms. Many can be secondary to local tumour burden, distant metastatic disease, and paraneoplastic syndromes. In that context, evidence suggests that baseline symptom and quality-of-life measures can provide valuable prognostic information in mrcc4.

The Edmonton Symptom Assessment System (esas) is a patient-reported, validated, and reliable tool that measures symptom severity in 9 separate domains. Each of the 9 symptoms within the esas are rated on a scale from 0 to 10, with higher scores representing greater symptom burden (Figure 1). The esas was originally developed and validated to assess symptoms in patients receiving palliative care, and it has been demonstrated to provide prognostic information in that population5. It has since been validated for use in patients with cancer6,7. More recently, the esas score has been demonstrated to predict for outcomes in patients with non-small-cell lung cancer, with a greater symptom burden being associated with decreased survival8. To our knowledge, the esas has not been used for prognostication in patients receiving active systemic therapy for advanced kidney cancer.

 


 

FIGURE 1 The Edmonton Symptom Assessment System.

We hypothesized that baseline symptom burden as measured by the esas score might be able to provide prognostic information in real-world patients receiving standard first-line sunitinib for mrcc and thus could be used in conjunction with the other validated models.

METHODS

Study Population

In this single-institution retrospective cohort study, we reviewed patients receiving first-line sunitinib therapy for mrcc at CancerCare Manitoba between January 2008 and January 2012. CancerCare Manitoba is a standalone medical facility in Winnipeg, Manitoba, and it is the sole provider of consultation services for cancer systemic therapy in our province. Patients whose baseline esas score was recorded before starting treatment were included in the final analysis. In Manitoba, access to sunitinib for this indication requires authorization by a genitourinary medical oncologist, and therefore the CancerCare Manitoba pharmacy has a record of all patients who were started on sunitinib during the period of interest. Our institution requests that all patients complete a baseline esas questionnaire at the time of initial consultation and before each subsequent clinical visit. We use the esas Revised (esas-r), which is a self-administered, paper-based numeric rating scale with a time anchor of “now.”

Data Collection and Analysis

To obtain clinical information, patient electronic health records and charts were reviewed. Important baseline information was collected, including tumour histology, sites of metastatic disease, and relevant clinical and biochemical parameters used in the established mskcc and imdc prognostic risk scores. Baseline patient-reported esas scores were collected before sunitinib was started. The study was approved by the University of Manitoba health research ethics board, and all data were kept confidential, with patients being assigned unique anonymous identifiers.

To assess the prognostic value of the baseline esas, we used Kaplan–Meier curves and Cox proportional hazards regression modelling to determine whether esas scores provide prognostic information about overall survival. The multivariable analysis included two variables: the imdc or mskcc prognostic group and the esas score. Overall survival was defined as the time from initiation of sunitinib to death from any cause. We used multivariable regression analysis to adjust for known prognostic indicators in mrcc. We defined statistical significance as p < 0.05, and we used the R statistical software package (version 3.3.1: The R Foundation, Vienna, Austria) for the analysis.

The esas total score (highest possible total score: 90; lowest possible total score: 0) was obtained by summing the individual domains and was used in the baseline analysis as a continuous variable. The total score was further assessed in a categorical fashion by dichotomizing it at the median esas value for the cohort. Kaplan–Meier curves were created using the dichotomized esas score combined with both the mskcc and imdc models to create a composite variable.

Because of missing patient variables, we used multiple imputation to perform a separate, additional analysis to account for missing data9. To quantify the additional effect of adding the esas to the existing models, we calculated the Akaike information criterion (aic) for each model and then determined the delta aicaic). The aic alone provides a measure of the relative quality of a statistical model for a given set of data. The Δaic compares those values between models, with a larger Δaic value indicating a greater effect of the additional variable on the existing model10.

RESULTS

Between 2008 and 2012, 68 patients with mrcc received first-line sunitinib, and 61 of them had a documented pre-treatment esas score. Table i presents the baseline characteristics of the cohort, which appear to be consistent with the known epidemiology of mrcc. Within the cohort, 78% of the patients were men, and the median age was 64 years. The most common histologic diagnosis was clear cell rcc, representing more than 50% of the cohort. Lung and bone were the most common metastatic sites, with most patients having 1 or 2 sites of metastatic disease. Most patients had a baseline Eastern Cooperative Oncology Group performance status of 0 or 1, but a documented performance status was missing for 35% of the cohort.

TABLE I Baseline characteristics of the study cohort

 

The median baseline esas total score in the cohort was 16 (range: 6–57). Figure 2 presents the distribution of the individual symptom scores within the esas. The symptom subscores most commonly reported as severe (7–10) were appetite, pain, dyspnea, and fatigue.

 


 

FIGURE 2 Distribution of the individual symptom domains within the Edmonton Symptom Assessment System (ESAS).

Most patients in the cohort had intermediate- or poor- risk disease according to the mskcc and imdc models. To further validate our cohort, we performed a univariable analysis using those two models (Table ii). The analysis revealed that patients in the poor-risk groups had, as expected, inferior survival outcomes.

TABLE II Univariable analysis for overall survival

 

The median follow-up duration for the cohort was 13.3 months. Figures 3 and 4 show the Kaplan–Meier curves generated by combining the dichotomized esas score with the mskcc and imdc models. We divided the cohort into four mutually exclusive patient groups based on the risk scores. The group with a low baseline symptom burden (<16) combined with low or intermediate risk in the established models appeared to have a particularly favourable prognosis.

 


 

FIGURE 3 Kaplan–Meier curve combining the dichotomized Edmonton Symptom Assessment System (ESAS) score with the Memorial Sloan Kettering Cancer Center (MSKCC) model.

 


 

FIGURE 4 Kaplan–Meier curve combining the dichotomized Edmonton Symptom Assessment System (ESAS) score with the International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) model.

In both univariable and multivariable analysis with the esas used as a continuous variable, higher baseline symptom burden was associated with inferior overall survival. In the univariable analysis, the hazard ratio was 1.27 (p = 0.0047) for each 10-unit increment in the esas total score. In multivariable analysis, the hazard ratio was 1.208 (p = 0.0362) for each 10-unit increase in the esas total score when controlling for the mskcc risk group and 1.240 (p = 0.019) for each 10-unit increase when controlling for the imdc risk group (Table iii). The &Delta;aic associated with the addition of the esas score to the mskcc model was 2.16; it was 3.27 for the addition of the esas score to the imdc model. Those values indicate a modest effect of esas in improving the existing prognostic models10.

TABLE III Multivariable analyses for overall survival

 

In the imputed analysis adjusting for missing patient data, higher baseline esas scores continued to predict for inferior survival outcomes in both the univariable analysis and the multivariable models controlling for known risk groups (data not shown).

DISCUSSION AND CONCLUSIONS

In this retrospective cohort study, we observed that the baseline symptom burden as measured by the esas total score might provide a modest degree of prognostic information about survival in patients receiving first-line sunitinib for mrcc and that it appeared to do so independently of other widely-used prognostic models.

Our findings are consistent with previously reported data examining the prognostic role of another patient-reported symptom assessment tool, the 15-item Functional Assessment of Cancer Therapy–Kidney Symptom Index (FACIT.org, Elmhurst, IL, U.S.A.). That tool was assessed in patients with mrcc enrolled in the pivotal randomized phase iii trial of sunitinib compared with interferon alfa11. In that clinical trial population, higher baseline quality of life was associated with improved overall survival4. We were able to show similar results with the novel use of a generalized symptom assessment tool that was not designed specifically for patients with cancer. Importantly, our results were seen in a real-world population of patients receiving treatment for advanced kidney cancer.

Interest in the role of patient-reported outcomes (pros) in clinical oncology has been increasing. The use of pros is currently being explored in a number of settings, including monitoring for chemotherapy-related side effects. Basch et al.12 have been studying the use of a Web-based tool that patients can use to report their symptoms in real time. When acted on by the health care team, pros were shown to enhance quality of life for patients receiving outpatient treatment for advanced cancers. In an updated analysis of that study13, patients who used the Web tool to self-report symptoms, compared with patients who received usual care, experienced longer median overall survival.

In another recent publication, the esas-r was also successfully used to evaluate symptom burden in patients prescribed oral cancer therapy14.

Based on our findings, use of the esas in prognostication for patients with cancer receiving active treatment could represent another interesting avenue to explore in the integration of pros into clinical practice. Our results are consistent with those emerging from other studies exploring the role of symptom burden and quality-of-life metrics in clinical oncology8.

Our study is not without a number of important limitations, including small sample size, incomplete data collection, and the selection bias inherent in retrospective designs. Our analysis used multiple imputation to account for missing data, producing results similar to those emerging from the non-imputed analysis and thus confirming a modest but statistically significant effect of baseline esas on survival prognostication.

The potential use of pro measures such as the esas in oncology is an exciting new direction for the use of those tools and reinforces the importance of patient collaboration in their own care. Advanced kidney cancer can present with a diverse range of symptoms of varying severity, and the esas appears to provide a simple and useful way of quantifying severity and providing prognostic information.

Optimally, our results should be further validated in larger, independent datasets of patients with advanced kidney cancer. Additional future research should also consider determining whether changes in the esas as treatment proceeds can reflect a response to therapy in mrcc, and exploring the role of esas in the prognostication of other advanced malignancies, particularly those that lack validated prognostic models.

CONFLICT OF INTEREST DISCLOSURES

We have read and understood Current Oncology’s policy on disclosing conflicts of interest, and we declare that we have none.

AUTHOR AFFILIATIONS

*University of Manitoba and,
CancerCare Manitoba, Winnipeg, MB;,
Department of Surgery, College of Medicine, King Khalid University, Abha, Saudi Arabia..

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Correspondence to: Piotr Czaykowski, 675 McDermot Avenue, Winnipeg, Manitoba R3E 0V9. E-mail:pczaykowski@cancercare.mb.ca

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Current Oncology, VOLUME 25, NUMBER 4, August 2018








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ISSN: 1198-0052 (Print) ISSN: 1718-7729 (Online)