Finding predictors for successful opioid response in cancer patients: An analysis of data from four randomized controlled trials.

Context: There is no consensus on which "strong" (or step 3 WHO analgesic ladder) opioid to prescribe to a particular patient with cancer-related pain. A better understanding of opioid and patient characteristics on treatment response will contribute to a more personalized opioid treatment.

Objectives: Assessment of potential predictors for successful opioid treatment response in patients with cancer pain.

Methods: An international partnership between four cancer pain research groups resulted in a combined individual-level database from four relevant randomized controlled trials (RCTs; n = 881). Together, these RCTs investigated the short-term (1 week) and medium-term (4 or 5 weeks) treatment responses for morphine, buprenorphine, methadone, oxycodone, and fentanyl. Candidate predictors for treatment response were sex, age, pain type, pain duration, depression, anxiety, Karnofsky performance score, opioid type, and use of anti-neuropathic drug.

Results: Opioid type and pain type were found statistically significant predictors of short-term treatment success. Sex, age, pain type, anxiety, and opioid type were statistically, significantly associated with medium-term treatment success. However, these models showed low discriminative power.

Conclusion: Fentanyl and methadone, and mixed pain were found to be statistically significant predictors of treatment success in patients with cancer-related pain. With the predictors currently assessed our data did not allow for the creation of a clinical prediction model with good discriminative power. Additional - unrevealed - predictors are necessary to develop a future prediction model.