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PCC 98-068 – HSR&D Study

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PCC 98-068
Development of a Cancer Pain Prognostic Scale
Shirley S. Hwang RN MS
East Orange Campus of the VA New Jersey Health Care System, East Orange, NJ
East Orange, NJ
Funding Period: July 1999 - December 2002

BACKGROUND/RATIONALE:
Cancer pain is a highly prevalent and distressful symptom. The original Cancer Pain Prognostic Scale (CPPS) was developed to predict pain relief, of at least 80%, 1 and 2 weeks post assessment and was defined as CPPS = 3 + BPI worst pain severity +4*(FACT Emotional Well-being 17) - 4*(morphine equivalent daily dose > 60 mg)-4*(Presence of Mixed Pain). The rule yields a numerical score that ranges from 0-17. Higher scores correspond to a higher probability of good pain relief. It has the potential to rapidly identify patients with poor pain prognosis, and as a research tool to characterize pain in cancer patients.

OBJECTIVE(S):
The purposes of this project were to (1) validate a CPPS in a new cohort of cancer pain patients; and (2) to perform exploratory analyses to examine the association between different pain management outcomes: pain relief, quality of life, satisfaction, interference by pain and changes in pain severity.

METHODS:
This is a prospective longitudinal survey study. From August 1,1999 to December 31, 2002, a total of 195 consecutive cancer pain patients with cancer-related pain (worst pain severity equal to or greater than 4/10) were recruited. Each participant was interviewed once weekly for a total of three weeks follow-up (4 interviews) with validated instruments.
For objective (1) - the predictive power of the CPPS score was assessed using the c-statistic. We modified the development approach because the predictive was poor. The development procedure consisted of the following steps: (1) identify the 20 strongest predictors as assessed by the bivariate correlations (Kendall’s tau-b); (2) identify the best combinations of predictors identified through a stepwise selection procedure in a logistic regression analysis; (3) validation consisted of fitting the logistic regression model using the final set of variables in the 500 validation datasets. For objective (2) - Repeated measure model was used to assess the changes in outcome over time and the association between different outcomes.

FINDINGS/RESULTS:
For objective (1) : The predictive power of original CPPS was poor, c statistics ranged from 0.54 to 0.61 for relief, worst pain and decrease in worst pain at 1, 2, and 3 weeks (0.5 indicates no predictive value). Five significant variables were identified to predict pain relief at week 1 by modified development approach. They were: MSAS-SF psychological symptom distress, affective social support, presence of neuropathic pain, presence of visceral pain and pain located in legs. We were not able to generate another pain prognostic scale.

For objective (2): In general there were statistically significant changes for all the pain variables (worst pain, pain relief, pain interference), FACT-G parameters (physical, emotional, functional wellbeing and total QOL) from the baseline (week 0) scores. There was significant association between almost all of the outcomes/covariate pairs over times. Most of proximal outcome variable had the same effect of distal outcome variable at all four points in time.

IMPACT:
Although we failed to validate and develop a new cancer pain prognostic scale based on our hypothesis. Results supported our previous findings, that patients with higher MSAS-SF psychological symptom distress, lower affective social support, presence of neuropathic pain, presence of visceral pain and pain located in legs were risk for poor pain relief highlight the importance of multidimensional assessment and effects on pain management outcomes. We defined the clinical significant changes of multidimensional pain management outcomes after 1 week of pharmacological intervention. This information will assist researchers and clinicians to follow cancer pain patients systematically.

PUBLICATIONS:
None at this time.


DRA: Health Systems
DRE: Diagnosis, Technology Development and Assessment
Keywords: Cancer, Pain, Research measure
MeSH Terms: Pain, Neoplasms

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