Validating a Patient-Reported Outcomes–Derived Algorithm for Classifying Symptom Complexity Levels Among Patients With Cancer (original) (raw)
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Journal of the National Comprehensive Cancer Network
Background: Patients with cancer in Canada are often effectively managed in ambulatory settings; however, patients with unmanaged or complex symptoms may turn to the emergency department (ED) for additional support. These unplanned visits can be costly to the healthcare system and distressing for patients. This study used a novel patient-reported outcomes (PROs)–derived symptom complexity algorithm to understand characteristics of patients who use acute care, which may help clinicians identify patients who would benefit from additional support. Patients and Methods: This retrospective observational cohort study used population-based linked administrative healthcare data. All patients with cancer in Alberta, Canada, who completed at least one PRO symptom-reporting questionnaire between October 1, 2019, and April 1, 2020, were included. The algorithm used ratings of 9 symptoms to assign a complexity score of low, medium, or high. Multivariable binary logistic regressions were used to ...
Journal of Pain and Symptom Management, 2013
Context. Longitudinal symptom monitoring is important in the setting of patients with advanced cancer. Scores over time may naturally fluctuate, although a patient may feel the same. Objectives. The purpose of this study was to determine the minimal levels of change required to be clinically relevant (minimal clinically important difference [MCID]) using the Edmonton Symptom Assessment System (ESAS). Methods. Between 1999 and 2009, patients completed the ESAS before palliative radiotherapy and at follow-up. MCIDs were calculated using both the anchor-and distribution-based methods for improvement and deterioration; 95% confidence intervals for the differences in mean change scores between adjacent categories also were calculated. Results. A total of 276 patients completed the ESAS at baseline and during at least one follow-up visit. At the four-week follow-up, decrease of 1.2 and 1.1 units in pain and depression scales, respectively, constituted clinically relevant improvement, whereas increase of at least 1.4, 1.8, 1.1, 1.1, and 1.4 units, respectively, in pain, tiredness, depression, anxiety, and appetite loss items were required for deterioration. At the subsequent follow-ups, these values were similar. Overall, the MCID for improvement tended to be smaller than that for deterioration. The distribution-based method estimates tended to be larger than the 0.3 SD estimates, but closer to the 0.5 SD estimates. Conclusion. MCIDs allow health care professionals to determine the success of treatment in improving the patient's quality of life. MCIDs may prompt health care professionals to intervene with new treatment. Future studies should confirm our findings with a variety of anchors.
Journal of Pain and Symptom Management, 2016
To investigate the consistency of symptom cluster composition in advanced cancer patients using different statistical methodologies for all patients across five primary cancer sites, and to examine which clusters predict functional status, a global assessment of health and global quality of life. Methods: Principal components analysis and exploratory factor analysis (with different rotation and factor selection methods) and hierarchical cluster analysis (with different linkage and similarity measures) were used on a dataset of 1562 advanced cancer patients who completed the EORTC QLQ-C30. Results: Four clusters consistently formed for many of the methods and cancer sites: tenseworry-irritable-depressed (emotional cluster); fatigue-pain; nausea-vomiting; and concentrationmemory (cognitive cluster). The emotional cluster was a stronger predictor of overall quality of life than the other clusters. Fatigue-pain was a stronger predictor of overall health than the other clusters. The cognitive cluster and fatigue-pain predicted physical functioning, role functioning, and social functioning. Conclusions: The four identified symptom clusters were consistent across statistical methods and cancer types, although there were some noteworthy differences. Statistical derivation of symptom clusters is in need of greater methodological guidance. A psychosocial pathway in the management of symptom clusters may improve quality of life. Biological mechanisms underpinning symptom clusters need to be delineated by future research.
Personalized symptom goals and response in patients with advanced cancer
Cancer, 2016
Improving symptoms is a major goal of cancer medicine; however, symptom response is often based on group differences and not individualized. In the current study, the authors examined the personalized symptom goal (PSG) for 10 common symptoms in patients with advanced cancer, and identified the factors associated with PSG response. In this prospective, longitudinal, multicenter study, patients from 5 tertiary care hospitals rated the intensity of 10 symptoms using a numeric rating scale of 0 to 10 at the time of their first clinic visit and then at a second visit 14 to 34 days later. The PSG was determined for each symptom by asking patients: "At what level would you feel comfortable with this symptom?" using the same scale of 0 to 10 for symptom intensity. PSG response was defined as symptom intensity at the time of the second visit that was less than or equal to the PSG. Among 728 patients, the median PSG was 1 for nausea; 2 for depression, anxiety, drowsiness, well-bein...
Current Oncology, 2019
Background We assessed whether the presence and severity of common cancer symptoms are associated with the health utility score (hus) generated from the EQ-5D (EuroQol Research Foundation, Rotterdam, Netherlands) in patients with cancer and evaluated whether it is possible pragmatically to integrate routine hus and symptom evaluation in our cancer population. Methods Adult outpatients at Princess Margaret Cancer Centre with any cancer were surveyed cross-sectionally using the Edmonton Symptom Assessment System (esas) and the EQ-5D-3L, and results were compared using Spearman correlation coefficients and regression analyses. Results Of 764 patients analyzed, 27% had incurable disease. We observed mild-to-moderate correlations between each esas symptom score and the hus (Spearman coefficients:-0.204 to-0.416; p < 0.0001 for each comparison), with the strongest associations being those for pain (R =-0.416), tiredness (R =-0.387), and depression (R =-0.354). Multivariable analyses identified pain and depression as highly associated (both p < 0.0001) and tiredness as associated (p = 0.03) with the hus. The ability of the esas to predict the hus was low, at 0.25. However, by mapping esas pain, anxiety, and depression scores to the corresponding EQ-5D questions, we could derive the hus using partial esas data, with Spearman correlations of 0.83-0.91 in comparisons with direct EQ-5D measurement of the hus. Conclusions The hus derived from the EQ-5D-3L is associated with all major cancer symptoms as captured by the esas. The esas scores alone could not predict EQ-5D scores with high accuracy. However, esas-derived questions assessing the same domains as the EQ-5D-3L questions could be mapped to their corresponding EQ-5D questions to generate the hus, with high correlation to the directly measured hus. That finding suggests a potential approach to integrating routine symptom and hus evaluations after confirmatory studies.
Journal of pain and symptom management, 2015
The Edmonton Symptom Assessment System (ESAS) is one of the most commonly used symptom batteries in clinical practice and research. We used the anchor-based.approach to identify the minimal clinically important difference (MCID) for improvement and deterioration for ESAS physical, emotional and total symptom distress scores. In this multicenter prospective study, we asked patients with advanced cancer to complete their ESAS at the first clinic visit and at a second visit three weeks later. The anchor for MCID determination was Patient's Global Impression regarding their physical, emotional and overall symptom burden ("better," "about the same," or "worse"). We identified the optimal sensitivity/specificity cutoffs for both improvement and deterioration for the three ESAS scores and also determined the within-patient changes. A total of 796 patients were enrolled from six centers. The ESAS scores had moderate responsiveness, with area under the recei...
Cancer Symptom Clusters: A Validation Study
Journal of Pain and Symptom Management, 2007
Cancer patients often experience multiple symptoms concurrently, a phenomenon called symptom clustering. Different symptom clusters have been identified by various symptom assessment tools, as well as by different research methods, but no study has reported whether these identified symptom clusters can be replicated in a new sample. The severity of nine symptoms in 321 cancer patients was assessed using a Taiwanese version of the M.D. Anderson Symptom Inventory. The fit between these data and a model with three symptom factors (sickness, gastrointestinal, and emotional) was evaluated using confirmatory factor analysis. Most fitness indices demonstrated a satisfactory fit between the data and a prespecified three-factor model except one; the root mean square error of approximation was <0.06. A modified model with one symptom (lack of appetite) double loaded in the sickness and gastrointestinal factors demonstrated a significantly better fit between the data and the model. Higher scores in each of the three symptom factors were associated with poorer functional status. Metastatic disease and receiving both chemotherapy and radiation therapy were associated with higher scores in sickness and gastrointestinal factors, but not in the emotional factor. Only hospitalization affected patients' scores in emotional factors. Our findings confirmed the prespecified structure of symptom clusters. A modified model showed a better fit. Patients' complex symptom experience may be better represented by subscale scores based on meaningful clusters rather than on an overall score across all symptoms.
Journal of pain and symptom management, 2015
Cancer patients frequently suffer from various symptoms often impairing functional status and quality of life. To enable timely supportive care, these symptoms must be assessed adequately with reliable tools. This study aimed to validate the German version of the M. D. Anderson Symptom Inventory (MDASI). This was a multicenter, cross-sectional, observational study. At five German university hospitals, 697 cancer patients aged from 18 to 80 years undergoing active anticancer treatment were recruited to participate in the study. For the validation, reliability (Cronbach's alpha), construct validity (factor analysis), known group validity (Eastern Cooperative Oncology Group Performance Status), and convergent divergent analyses were calculated. Of the 980 patients who were eligible, 697 patients were included and agreed to participate in the study (71%). Reliability analysis showed good internal consistencies for the MDASI set of symptoms (Cronbach's alpha coefficient = 0.82; 9...
Acta oncologica (Stockholm, Sweden), 2017
Reviews of the literature on symptoms in oncology patients undergoing curative treatment, as well as patients receiving palliative care, suggest that they experience multiple, co-occurring symptoms and side effects. The purposes of this study were to determine if subgroups of oncology patients could be identified based on symptom occurrence rates and if these subgroups differed on a number of demographic and clinical characteristics, as well as on quality of life (QoL) outcomes. Latent class analysis (LCA) was used to identify subgroups (i.e. latent classes) of patients with distinct symptom experiences based on the occurrence rates for the 13 most common symptoms from the Memorial Symptom Assessment Scale. In total, 534 patients with breast, head and neck, colorectal, or ovarian cancer participated. Four latent classes of patients were identified based on probability of symptom occurrence: all low class [i.e. low probability for all symptoms (n = 152)], all high class (n = 149), hi...
Journal of Pain and Symptom Management, 2008
Methods are presented to separate 16 frequently occurring cancer symptoms measured on 10-point symptom severity rating scales into mild, moderate, and severe categories that are clinically interpretable and significant for use in oncology practice settings. At their initial intervention contact, 588 solid tumor cancer patients undergoing chemotherapy reported severity on a standard 11-point rating scale for 16 symptoms. All reporting a one or higher were asked to rate on an 11-point scale how much the symptom interfered with enjoyment of life, relationship with others, general daily activities, and emotions. Factor analysis revealed that these items tapped into the same dimension, and the items were summed to form an interference scale. Cutpoints for mild, moderate, and severe categories of symptom severity were defined by comparing the differences in interference scores corresponding to each successive increases in severity for each symptom. The cut-points differed among symptoms. Pain, fatigue, weakness, cough, difficulty remembering, and depression had lower cut-points for each category compared to other symptoms. Cut-points for each symptom were not related to site or stage of cancer, age, or gender but were associated with a global depression measure. Cut-points were related to limitations in physical function, suggesting differences in the quality of patients' lives. The resulting cut-points summarize severity ratings into clinically significant and useful categories that clinicians can use to assess symptoms in their practices. J Pain Symptom Manage 2008;35:126e135.