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PURPOSE: Pain and symptom management is an integral part of the clinical practice of oncology. A number of guidelines have been developed to assist the clinician in optimizing comfort care. We implemented clinical guidelines for cancer pain management in the community setting and evaluated whether these guidelines improved care. PATIENTS AND METHODS: Eighty-one cancer patients, aged 37 to 76 years, were enrolled onto a prospective, longitudinal, randomized controlled study from the outpatient clinic settings of 26 western Washington-area medical oncologists. A multilevel treatment algorithm based on the Agency for Health Care Policy and Research Guidelines for Cancer Pain Management was compared with standard-practice (control) pain and symptom management therapies used by community oncologists. The primary outcome of interest was pain (Brief Pain Inventory); secondary outcomes of interest were all other symptoms (Memorial Symptom Assessment Scale) and quality of life (Functional Assessment of Cancer Therapy Scale). RESULTS: Patients randomized to the pain algorithm group achieved a statistically significant reduction in usual pain intensity, measured as slope scores, when compared with standard community practice (P < .02). Concurrent chemotherapy and patient adherence to treatment were significant mediators of worst pain. There were no significant differences in other symptoms or quality of life between the two treatment groups. CONCLUSION: This guideline implementation study supports the use of algorithmic decision making in the management of cancer pain. These findings suggest that comprehensive pain assessment and evidence-based analgesic decision-making processes do enhance usual pain outcomes.
Pen et al. (Fri,) studied this question.