Abstract

Pain is one of the most devastating symptoms for cancer patients. One third of patients who experience pain do not receive effective treatment. A key barrier to effective pain management is lack of routine measurement and monitoring of pain. Patient-reported outcome measures (PROMs) are recommended for measuring cancer pain. However, evidence to guide the selection of the most appropriate measure to identify and monitor cancer pain is limited. A systematic review of measurement properties of PROMs for pain in cancer patients is needed to identify the best validated measure for adoption to an electronic platform. To systematically review measurement properties of PROMs used for adult cancer patients to measure pain and, as a secondary goal, to investigate the evidence of validated mobile health (mHealth) applications used to measure pain (registration number: CRD42017065575). Medline, Embase, and the Cumulative Index to Nursing and Allied Health Literature (CINAHL) were systematically searched in March 2018 for studies examining measurement properties for PROMs for pain in adult cancer patients. The methodological quality of the studies and their results were appraised using the Consensus-based Standards for the Selection of Health Measurement Instruments (COSMIN) checklist and specific measurement properties criteria, respectively. Sixteen studies evaluating 8 instruments were included. No studies using a PROM in an mHealth application were identified. The methodological quality of the measurement properties ranged between poor and fair. No instrument showed strong positive evidence for all the evaluated measurement properties. Based on the available evidence, the Brief Pain Inventory-Short Form (BPI-SF) had the strongest evidence to support its selection for the measurement of cancer pain. The BPI-SF was the best performing measure across all properties evaluated through COSMIN. Better quality validation studies of PROMs for cancer pain are needed to explore the full range of measurement properties. Utilizing mHealth applications to measure pain in cancer patients is an innovative approach worthy of further investigation.

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