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10.11.2018 | Original Research Open Access

Pain Intensity Factors Changing Breakthrough Pain Prevalence in Patients with Advanced Cancer: A Secondary Analysis of a Cross-Sectional Observational International Study

Zeitschrift:
Pain and Therapy
Autoren:
Erik Torbjørn Løhre, Marianne Jensen Hjermstad, Cinzia Brunelli, Anne Kari Knudsen, Stein Kaasa, Pål Klepstad
Wichtige Hinweise

Enhanced digital features

To view enhanced digital features for this article go to https://​doi.​org/​10.​6084/​m9.​figshare.​7246817.

Abstract

Introduction

Different definitions of breakthrough pain (BTP) influence the observed BTP prevalence. This study examined BTP prevalence variability due to use of different cutoffs for controlled background pain, different assessment periods for background pain, and difference between worst and average pain intensity (PI).

Methods

Cancer patients from the EPCRC-CSA study who reported flare-ups of pain past 24 h were potential BTP cases. BTP prevalence was calculated for different cutoffs for background PI on numeric rating scales (NRS 0–10) for the past week, past 48 and past 24 h period. Furthermore, BTP cases were categorized based on the difference between maximum and average PI past 24 h (range, 0 to > 2 points, NRS 0–10).

Results

Of 696 respondents, 302 patients (43.4%) reported pain flares the past 24 h. The BTP prevalence when using a defined background PI ≤ 4 for the past week was 19.8%. This number varied for different defined cutoffs for background PI. Actual background PI and BTP prevalence also varied between the assessment periods “past week”, “past 48 h”, and “past 24 h” (PI 4.0, 3.6, and 3.4; BTP prevalence 19.8, 22.7, and 24.9% for background PI ≤ 4). For patients with background PI ≤ 4 past week, 105 had a difference between maximum and average PI ≥ one point and 48 had a difference > two points.

Conclusions

The reported BTP prevalence is dependent on the cutoff for background PI in the BTP definition, population background PI during the assessment period, and defined cutoff for the difference between worst and average PI.

Funding

NTNU, Norwegian University of Science and Technology.
Literatur
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