Robin Fainsinger, Cheryl Nekolaichuk, Pablo Amigo, Amanda Brisebois, Sarah Burton Macleod, Rebekah Gilbert, Yoko Tarumi, Vincent Thai, Gary Wolch, Lara Fainsinger & Viki Muller Division of Palliative Care Medicine University of Alberta Moving on - the next step in developing an International Classification System for Cancer Pain
Development of the Edmonton Classification System for Cancer Pain (ECS-CP) ESS 1989-1995 ress 2000-2005 ECS-CP Inter-rater reliability (Fainsinger et al, 2005) Predictive validity (Fainsinger et al, 2005) Construct validity (Nekolaichuk et al, 2005) Pain intensity as predictor (Fainsinger et al, 2009) Predictive validity in international sample (Fainsinger et al, 2010) 2005 - present 2
New perspectives Knudsen AK, Aass N, Fainsinger R, et al Classification of pain in cancer patients a systematic review. Palliat Med 2009;23:295 30 Kaasa S, Apolone G, Klepstad P et al. Expert conference on cancer pain assessment and classification the need for international consensus: Work proposals on international standards. BMJ Support Palliat Care, doi:10.1136/bmjspcare-2011-000078 Knudsen AK, Brunelli C, Klepstad P, et al Which domains should be included in a cancer pain system? Analyses of longitudinal data. Pain 2012;153:696-703
Content considerations Patient generated Clinician generated ECS-CP Pain Intensity Mechanism e.g. neuropathic with NeuPSIG Pain localization Incident (& episodic pain) adjusted definition Outcome measures Stable pain control Personalised patient pain control goal Pain relief Psychological distress 24 hour Opioid dose Age Addiction Smoking history Opioid dose escalation/analgesic tolerance Sleep disturbance Cognition Adjuvant analgesics Cancer diagnosis Adjuvant modalities Genetic variation Interdisciplinary team requirements
Diagnosis of Neuropathic Pain The NeuPSIG criteria for defining and grading neuropathic pain (NP):- 1. Pain distribution is neuroanatomically plausible. 2. History is suggestive of a relevant lesion or disease. 3. Negative or positive sensory signs within innervations territory of lesion are present. 4. A diagnostic test confirms lesion or disease. First 2 criteria possible NP Addition of either 3 or 4 probable NP All 4 criteria present definite NP
Incident Pain - Pain can be defined as incident pain when a patient has background pain of no more than moderate intensity with intermittent episodes of moderate to severe pain, usually having a rapid onset and often a known trigger. 1. Background pain mild or moderate (0 6) 2. Intensity of incident pain significantly greater than background pain going from mild (0-3) to moderate (4 6) or mild or moderate to severe (7 10) with at least a 2 point change noted to be significant by patient and/or rater. Both criteria - Ii Background pain severe - Ix
Other additions History of chronic pain - years Smoking history pack years Weekly ECS-CP
Ethical issues Informed consent will not be obtained from patients, as we will only be collecting clinical data routinely documented in all services Will need to get consent if we add data collection beyond standard practice or consider consenting a subset of patients.
Research Hypothesis Patients with less problematic pain features (as classified by the ECS-CP), lower pain intensity and depression scores, and the absence of a smoking history, will require a shorter time to achieve stable pain control, require less complicated analgesic regimens, be more responsive to opioid therapy and use lower opioid doses than patients with more complex pain syndromes.
Objectives Assess the predictive validity of the Edmonton Classification System for Cancer Pain (ECS-CP) and additional variables as a tool for classifying cancer pain, in a pilot sample of 300 palliative patients in the Edmonton Zone Palliative Care Program (EZPCP) in Edmonton, AB Canada. Royal Alexandra Hospital (RAH), n=100 University of Alberta Hospital (UAH), n=100 Grey Nuns Hospital, Tertiary Palliative Care Unit (TPCU), n=100 Test an internet multisite data collection system Compare the achievement of personalized pain goals to the standard definition of stable pain control used in previous studies of the ECS-CP.
Methods Initial and final ECS-CP Track ECS-CP changes over time weekly
Information recorded until study termination Daily pain intensity as recorded by cognitively intact patients only using the Pain-NRS. Daily number of breakthrough pain doses. Final MEDD at study termination. Number and type of adjuvant analgesics and/or other treatments used during the trajectory of care from first assessment to study termination. Date of and reason for study termination (achievement of stable pain control 3 versions, death, or discharge resulting in loss of follow-up)
Stable Pain Control For 3 Consecutive Days: < 3 PRN doses per day Cognitively Intact Cognitively Impaired Pain-NRS < 3/10 Or < PPG
Results Patient Demographics (Initial Assessment) n % Gender Male 166 55 Female 134 45 n Mean Range SD Age (yrs) 300 69 19-98 13 Previous Opioid treatment for chronic non malignant pain (yrs) 21 7 1-30 7 Smoking History (pack yrs) 183 34 1-156 22
Results Diagnosis (n=300) Total Total % Gastro Int 97 32% Lung 73 24% Gastro Uri 55 18% Hematology 23 8% Head & Neck 15 5% Breast 13 4% Brain 10 3% Unknown Primary 7 2% Other 4 1% Musculo-skeletal 3 1% 5 % 8 % 4 % 2 % 1 % 1 % 4 % 18 % 24 % 33 % Gastro Int Lung Gastro Uri Hematology Head & Neck Breast Brain Unknown Primary Other Musculo-skeletal
Results Initial ECS-CP Features for all Pts on Initial Assess (n=300) Feature Total Total % No 69 23% Nc 175 58% Ne 48 16% Nx 8 3% Initial ECS-CP Features for Pts with Pain Syndrome (n=231) Feature Total Total % Io 122 53% Ii 60 26% Ix 49 21% Po 142 61% Pp 37 16% Px 52 23% Ao 193 84% Aa 18 8% Ax 20 9% Co 154 67% Ci 50 22% Cu 23 10% Cx 4 2%
Results Initial ECS-CP Features for Pts with Neuropathic Pain (n=48) Ne Feature Total Total % Pain distribution is neuroanotomically 48 100 History is suggestive of relevant lesion or disease 48 100 Negative or positive sensory signs within innervations territory of lesions are present 34 71 A diagnostic test confirms lesion or disease 34 71 All 4 criteria present = definite NP 34/48
Results Opioid #1 Pain Management (n=231) Total Total % Hydromorphone 92 40% Morphine 57 25% None 34 15% Oxycodone 21 9% Codeine 10 4% Fentanyl 8 3% Methadone 4 2% Tramadol 2 1% Buprenorphine 1 0% Demerol 1 0% Tramacet 1 0% Opioid #2 Pain Management (n=30) Total Total % Hydromorphone 10 33% Morphine 8 27% Codeine 5 17% Fentanyl 2 7% Methadone 2 7% Oxycodone 2 7% Tramadol 1 3% Opioid #3 Pain Management (n=2) Total Total % Codeine 1 50% Tramadol 1 50%
Results Patient Demographics (Initial Assessment) (n=231) Median Mean SD ESAS-R Pain * 5 4.3 3 Depression 3 3.5 3 Anxiety 2 3.2 3 Well-Being 5 5.3 3 * 22% of cases were proxy assessments Personalized Pain Goal (PPG) Palliative Performance Scale (PPS) Median Range 3 0-10 40 10-80
Results PPG (n=169*) Score n % 0 5 3% 1 1 1% 2 33 20% 3 74 44% 4 21 12% 5 26 15% 6 6 4% 7 1 1% 8 1 1% 10 1 1% *Declined to Answer = 3 Unable to Assess= 59 50% 45% 40% 35% 30% 25% 20% 15% 10% 5% 0% 0 1 2 3 4 5 6 7 8 10 PPG
Results Pain Intensity Categories On Admission (n=229*) Pain Intensity UAH % RAH % TPCU% Total% Mild (0-3) 39% 48% 35% 40% Moderate (4-6) 39% 30% 32% 33% Severe (7-10) 23% 23% 32% 27% 100% 90% 80% 70% * Unable to assess 2 patients 60% 50% 40% 30% Severe Moderate Mild 20% 10% 0% UAH % RAH % TPCU %* Total %
Results CAGE Score Distribution (n=202*) Score n 0 158 1 8 2 17 3 11 4 8 *Declined to Answer = 2 Unable to Assess= 27 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 0 1 2 3 4 CAGE Score Distribution n
Results Adjuvant Analgesic (n=259*) Total Total % None 109 42% Corticosteroids 52 20% Tylenol 39 15% Anticonvulsant 28 11% Other 10 4% NSAIDS 9 3% Tricyclic Antidepres 8 3% Bisphosphonate 4 2% Oral L Anest 0 0% *Does not add up to n=231 due to multiple responses from unique patients 45% 40% 35% 30% 25% 20% 15% 10% 5% 0% Total %
Results Other Method of Pain Control (n=237*) Total Total % None 212 89% Radiotherapy 12 5% Chemotherapy 5 2% Other 3 1% Anesthes Procedure 2 1% Surgical Procedure 2 1% Accupuncture 1 0% Transcut Nerve Stimulatio 0 0% *Does not add up to n=231 due to multiple responses from unique patients 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Total %
Results Final Assessment (n=231) 91 patients Achieved stable pain 87/91 Achieved the study definition 4/91 Died or Discharged 85/91 Achieved their PPG 5/91 Died or Discharged 1/91 Fluctuation in Pt Cognition (missing data) 44 patients PRNs only 47 patients Death 45 patients Discharge 4 Patients Active
Results: Stable Pain Control Total Sample (n=300) Pain Syndrome (n=231) (77%) No Pain (n=69) (33%) Ongoing (n=4) Stable Pain (n=135/227) (59%) Death (n=47/227) (21%) Discharge (n=45/227) (20%)
Results: Stable Pain Control Stable Pain (n=135) PPG or Study Defn (n=91) PRN only (n=44) Both Defns (n=81) PPG Only (n=4) Study Defn Only (n=6)
Results: Time to Stable Pain Control (Days) Stable Pain Control Definition Personalized Pain Goal Sample Size Mean (days) Standard Deviation 85 5.86 5.18 Study Definition (cognitively intact) 87 6.32 6.14 PRNs Only (cognitive impairment) 44 8.25 7.85
Discussion The variability in pain classification features across sites may be related to the types of patients admitted to specific sites; Possibility that some of this variation may also be related to differences in interpretation of the ECS-CP; next stage in the validation of the ECS-CP would be to: Increase the sample size Expand to international sites Analyze the relationship between the complexity of pain and the time to reach stable pain control
Conclusion The ECS-CP is able to detect differences across diverse settings enabling clinicians to: better assess and manage cancer pain; report and compare research results; and allocate resources. Further research is needed to assess: training needs; develop strategies to promote uptake of the ECS-CP for clinical, research and administrative purposes.
Acknowledgments Covenant Health Palliative Institute Covenant Health Research Trust Fund Grant Office of the Provost and VP (Academic) Summer Research Award Human Resources and Skills Development Canada: Canada Summer Jobs Program Jerri-Lynn Goulet, Rachel Elston & Hue Quan Nurse consultants at the RAH & UAH