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Use of an Abbreviated Form of the Edmonton Staging System in a Hospice Setting
Vol. 31 No. 3 March 2006
Journal of Pain and Symptom Management
193
Letters
Use of an Abbreviated Form of the Edmonton Staging System in a Hospice Setting To the Editor: We welcomed the paper by Fainsinger et al.,1 which assessed the use of a ‘‘revised Edmonton staging system (rESS)’’ in classifying pain. We have used the Edmonton staging system routinely in our clinical practice for the purposes of pain management audit, but found this problematic. Our doctors sometimes found it difficult to ask about previous drug/alcohol abuse or classify psychological distress on the admission assessment, and opioid tolerance had to be retrospectively calculated. We had also found Bruera et al.’s2 outcome of pain score at Day 21 less meaningful for our population of hospice inpatients, many of whom have very short life expectancy. We considered whether the use of an ‘‘abbreviated ESS (aESS)’’ was valid, and whether we could usefully reduce the ESS to two components only: the presence of a neuropathic element to the pain and presence of incident pain.
Procedure and Data Analysis We retrospectively analyzed all the notes of patients admitted into the hospice within a year. Patients were excluded if they were pain free, were confused or comatose on admission, died early in their admission, or had significant missing information in the notes. In our hospice, an admission ESS is completed for patients with pain and a daily pain score (POS3) is routinely taken by the nursing staff, if possible, on all patients. Patients with a completed ESS were categorized into good or poor pain prognosis and the clinical course of the two groups was Ó 2006 U.S. Cancer Pain Relief Committee Published by Elsevier Inc. All rights reserved.
compared in terms of number of days to stable pain control (three POS scores consistently #2 over 5 consecutive days), whether stable pain control was achieved, days to discharge from hospice, number of adjuvant drugs used, and number of opioid switches. The same patients were recategorized into good and poor pain prognosis using the two-component aESS, and the same variables compared. Fisher’s exact test was used to compare the proportions of patients who achieved stable pain control with each group. Significant differences between days to pain control, days to discharge, and numbers of interventions between the groups were assessed using MannWhitney tests. A Chi-squared test was used to demonstrate that the aESS reclassified the patients into groups that were significantly different from those the ESS had defined. Data were analyzed using SPSS for Windows release 11.5.0 (SPSS Inc., Chicago, 2002).
Results Notes of 200 eligible patients were analyzed. For 82 of these patients, it was not possible to calculate stable pain control, and these were excluded from the analyses involving stable pain control. Both the ESS-derived and aESS-derived poor pain prognosis group used more adjuvant medication (P < 0.01), had more opioid switches (P < 0.01), and fewer of those patients achieved stable pain control (see Fig. 1) (P < 0.01). Sensitivity and specificity for the ESS’s prediction of patients who do not achieve pain control were calculated. Sensitivity (number of patients with ESS-defined poor pain prognosis as a proportion of the total patients who do not achieve pain control) and specificity (number of patients with ESSpredicted good pain prognosis as a proportion 0885-3924/06/$--see front matter
194
Letters
100
Comment
90
Number of patients
Vol. 31 No. 3 March 2006
80 70 60 50 40 30 20 10 0 good
poor
Pain Prognosis total population
achieved stable pain control
Fig. 1. A comparison of whether stable pain control was achieved for ESS-derived pain prognosis groups.
of the total number of patients who achieved good pain control) were calculated as described in Bruera et al’s2 paper. The sensitivity of the ESS for whether stable pain control was achieved was 0.95, and the specificity 0.30. The aESS recategorized the groups into significantly different groups than the ESS (P < 0.05). The sensitivity of the aESS-derived poor pain prognosis was 0.91 with a specificity of 0.39. There was no significant difference between the groups for time to stable pain control (P ¼ 0.076 for ESS, 0.052 for aESS) or time to discharge (P ¼ 0.167). This analysis has limitations. The measure of stable pain control was calculated using three consecutive scores over 5 days, which excluded patients with a shorter admission. The number of missing scores, either due to misfiled notes or difficulty in obtaining the score, resulted in the time to stable pain control being artificially prolonged, which may have affected the time to stable pain control result. More patients in the poor pain prognosis group died rather than were discharged, which may have affected the days to discharge results; analyzing length of stay may have yielded a more relevant result. Finally, the study was limited by problems of missing information (as it was based on retrospective data). However, the retrospective nature of the study ensured that the ESS score had not influenced the clinician’s management of the patient.
We conclude that for our population, the two-component aESS defined a population in whom pain may be more difficult to control, with little difference in the sensitivity and specificity of the ESS; indeed, the slightly improved specificity may be advantageous. Fainsinger et al. referred to the usefulness of the rESS, particularly in interpreting research data related to cancer pain management, and we agree with their suggestion that further development of this tool will improve its sensitivity and specificity. As clinicians, we are working within a climate of clinical governance where outcome measures may be used to make assumptions about the quality of health care. A straightforward tool such as the aESS, which can be easily incorporated into routine clinical practice, may be important as an aid to interpreting performance markers of pain management between populations. Papiya Russell, BSc (Med Sci), MBChB, MRCP Marie Curie Hospice Edinburgh, Scotland, United Kingdom Ruth Crook, BSc (Med Sci) Edinburgh Medical School Edinburgh, Scotland, United Kingdom David Oxenham, MBChB, FRCP, FAChPM Marie Curie Hospice Edinburgh, Scotland, United Kingdom doi:10.1016/j.jpainsymman.2006.01.005
References 1. Fainsinger RL, Nekolaichuk CL, Lawlor PG, et al. A multicenter study of the revised Edmonton staging system for classifying cancer pain in advanced cancer patients. J Pain Symptom Manage 2005;29: 224--237. 2. Bruera E, Schoeller T, Wenk R, et al. A prospective multicenter assessment of the Edmonton staging system for cancer pain. J Pain Symptom Manage 1995;10:348--355. 3. Hearn J, Higginson IJ. Development and validation of a core outcome measure for palliative care: the palliative care outcome scale. Palliative Care Core Audit Project Advisory Group. Qual Health Care 1999;8(4):219--227.
Journal of Pain and Symptom Management
193
Letters
Use of an Abbreviated Form of the Edmonton Staging System in a Hospice Setting To the Editor: We welcomed the paper by Fainsinger et al.,1 which assessed the use of a ‘‘revised Edmonton staging system (rESS)’’ in classifying pain. We have used the Edmonton staging system routinely in our clinical practice for the purposes of pain management audit, but found this problematic. Our doctors sometimes found it difficult to ask about previous drug/alcohol abuse or classify psychological distress on the admission assessment, and opioid tolerance had to be retrospectively calculated. We had also found Bruera et al.’s2 outcome of pain score at Day 21 less meaningful for our population of hospice inpatients, many of whom have very short life expectancy. We considered whether the use of an ‘‘abbreviated ESS (aESS)’’ was valid, and whether we could usefully reduce the ESS to two components only: the presence of a neuropathic element to the pain and presence of incident pain.
Procedure and Data Analysis We retrospectively analyzed all the notes of patients admitted into the hospice within a year. Patients were excluded if they were pain free, were confused or comatose on admission, died early in their admission, or had significant missing information in the notes. In our hospice, an admission ESS is completed for patients with pain and a daily pain score (POS3) is routinely taken by the nursing staff, if possible, on all patients. Patients with a completed ESS were categorized into good or poor pain prognosis and the clinical course of the two groups was Ó 2006 U.S. Cancer Pain Relief Committee Published by Elsevier Inc. All rights reserved.
compared in terms of number of days to stable pain control (three POS scores consistently #2 over 5 consecutive days), whether stable pain control was achieved, days to discharge from hospice, number of adjuvant drugs used, and number of opioid switches. The same patients were recategorized into good and poor pain prognosis using the two-component aESS, and the same variables compared. Fisher’s exact test was used to compare the proportions of patients who achieved stable pain control with each group. Significant differences between days to pain control, days to discharge, and numbers of interventions between the groups were assessed using MannWhitney tests. A Chi-squared test was used to demonstrate that the aESS reclassified the patients into groups that were significantly different from those the ESS had defined. Data were analyzed using SPSS for Windows release 11.5.0 (SPSS Inc., Chicago, 2002).
Results Notes of 200 eligible patients were analyzed. For 82 of these patients, it was not possible to calculate stable pain control, and these were excluded from the analyses involving stable pain control. Both the ESS-derived and aESS-derived poor pain prognosis group used more adjuvant medication (P < 0.01), had more opioid switches (P < 0.01), and fewer of those patients achieved stable pain control (see Fig. 1) (P < 0.01). Sensitivity and specificity for the ESS’s prediction of patients who do not achieve pain control were calculated. Sensitivity (number of patients with ESS-defined poor pain prognosis as a proportion of the total patients who do not achieve pain control) and specificity (number of patients with ESSpredicted good pain prognosis as a proportion 0885-3924/06/$--see front matter
194
Letters
100
Comment
90
Number of patients
Vol. 31 No. 3 March 2006
80 70 60 50 40 30 20 10 0 good
poor
Pain Prognosis total population
achieved stable pain control
Fig. 1. A comparison of whether stable pain control was achieved for ESS-derived pain prognosis groups.
of the total number of patients who achieved good pain control) were calculated as described in Bruera et al’s2 paper. The sensitivity of the ESS for whether stable pain control was achieved was 0.95, and the specificity 0.30. The aESS recategorized the groups into significantly different groups than the ESS (P < 0.05). The sensitivity of the aESS-derived poor pain prognosis was 0.91 with a specificity of 0.39. There was no significant difference between the groups for time to stable pain control (P ¼ 0.076 for ESS, 0.052 for aESS) or time to discharge (P ¼ 0.167). This analysis has limitations. The measure of stable pain control was calculated using three consecutive scores over 5 days, which excluded patients with a shorter admission. The number of missing scores, either due to misfiled notes or difficulty in obtaining the score, resulted in the time to stable pain control being artificially prolonged, which may have affected the time to stable pain control result. More patients in the poor pain prognosis group died rather than were discharged, which may have affected the days to discharge results; analyzing length of stay may have yielded a more relevant result. Finally, the study was limited by problems of missing information (as it was based on retrospective data). However, the retrospective nature of the study ensured that the ESS score had not influenced the clinician’s management of the patient.
We conclude that for our population, the two-component aESS defined a population in whom pain may be more difficult to control, with little difference in the sensitivity and specificity of the ESS; indeed, the slightly improved specificity may be advantageous. Fainsinger et al. referred to the usefulness of the rESS, particularly in interpreting research data related to cancer pain management, and we agree with their suggestion that further development of this tool will improve its sensitivity and specificity. As clinicians, we are working within a climate of clinical governance where outcome measures may be used to make assumptions about the quality of health care. A straightforward tool such as the aESS, which can be easily incorporated into routine clinical practice, may be important as an aid to interpreting performance markers of pain management between populations. Papiya Russell, BSc (Med Sci), MBChB, MRCP Marie Curie Hospice Edinburgh, Scotland, United Kingdom Ruth Crook, BSc (Med Sci) Edinburgh Medical School Edinburgh, Scotland, United Kingdom David Oxenham, MBChB, FRCP, FAChPM Marie Curie Hospice Edinburgh, Scotland, United Kingdom doi:10.1016/j.jpainsymman.2006.01.005
References 1. Fainsinger RL, Nekolaichuk CL, Lawlor PG, et al. A multicenter study of the revised Edmonton staging system for classifying cancer pain in advanced cancer patients. J Pain Symptom Manage 2005;29: 224--237. 2. Bruera E, Schoeller T, Wenk R, et al. A prospective multicenter assessment of the Edmonton staging system for cancer pain. J Pain Symptom Manage 1995;10:348--355. 3. Hearn J, Higginson IJ. Development and validation of a core outcome measure for palliative care: the palliative care outcome scale. Palliative Care Core Audit Project Advisory Group. Qual Health Care 1999;8(4):219--227.