The optimal management of chronic pain rests on the selection of adequate and patient-specific treatments and on the continuous assessment of pain to determine treatment effectiveness.
This requires the use of standardized tools to assess all relevant pain domains. However, the subjective nature of chronic pain renders it challenging to assess. In addition, the wide variation in pain tolerance that exists between individuals calls into question the reliability of the data on which clinical decisions are made.
While significant advances have been made to better understand the neurophysiology of pain, assessing and diagnosing chronic pain remains challenging.
Six core domains of chronic pain were recommended for assessment by the Initiative on Methods, Measurement, and Pain Assessment in Clinical Trials (IMMPACT). These domains include physical and emotional functioning, patient satisfaction with treatment, treatment-associated adverse events and adherence to treatment.1
These recommendations were developed to advance research and based on the perspectives of clinicians and researchers. A subsequent survey led to the identification of 19 aspects of the patients’ lives significantly affected by chronic pain, all of which could be used to evaluate treatment effectiveness.2
From a patient perspective, assessment of treatment effectiveness should not only include measurement of pain intensity and functionality, but also improvement in overall well-being and quality of life that includes emotional well-being, fatigue, weakness, and sleep-related issues.
The significant variability in the response to analgesics has led to the introduction of the concept of “precision medicine” to individualize chronic pain management, with a goal of improving both the clinical care of patients with pain and the success rates for analgesic drugs.3
Such an approach is associated with 2 main challenges: the identification of measurable phenotypes that are also most likely to be predictive of individual variations in analgesic treatment outcomes and the identification of measurement tools best suited to evaluate these characteristics.
In order to be systemically used in the clinical setting, outcome measures should be practical and comprehensive, evaluating all areas relevant to pain (eg, psychological factors, impact on sleep).2,4 Optimal management of pain requires accurate assessment and classification of multiple pain domains, and therefore necessitates reliable and validated pain assessment tools.
In addition to guiding treatment decisions, accurate assessment of chronic pain can also serve to document pain severity and track its course. Many of the commonly used chronic pain assessment methods are, however, based on self-assessment. The challenges inherent to this approach are obvious, as patients are expected to be responsible for their treatment outcome, based on their subjective reporting of the pain they experience.5
While recommendations outlined in IMMPACT have successfully been applied in the research setting, practical and relevant methods for pain assessment in the clinical setting are desperately needed. In addition to diagnosing pain, an assessment tool should provide information regarding pain severity, treatment effectiveness, and, whenever possible, the underlying pathophysiology, in order to better guide treatment decisions.
A study recently published in The Journal of Pain proposes an evidence-based conceptual and heuristic model for the assessment of pain.6 In this model, pain classification and assessment allow to determine underlying pathophysiological mechanisms.
Two major goals of pain assessment are identified in this model: assessment of pain burden and assessment of mechanisms of pain. According to the authors, pain burden measurements should include assessment of pain intensity and affect, perceptual qualities, temporal features, and bodily locations. The last 3 parameters may also provide information regarding pain mechanisms.
The researchers acknowledge that sensory pain (ie, pain intensity, affect and perception) is most commonly assessed using the numerical rating and visual analog scales and the McGill Pain Questionnaire.
Although assessment of the temporal aspects of pain (ie, pain duration, variability and modifying factors) is an important component of pain burden, the authors also acknowledge that this modality is not systematically considered by clinicians, perhaps due to its subjective measurement through patient self-report and behavioral measure of pain.
Understanding the mechanisms underlying the development and maintenance of chronic pain will allow for more targeted treatment strategies. Several approaches are currently used to assess pain, and include quantitative sensory testing, skin biopsies, functional and structural brain imaging, chemical neuroimaging and genotyping.
Most of these tools are rarely used for the assessment of pain mechanisms in the clinical setting. The identification of genetic markers of pain holds great potential in the treatment decision-making process based on pain mechanism.
In addition, the recent development of the Patient Reported Outcomes Measurement Information System (PROMIS), an electronic pain measuring tool which uses a computer software to optimize the efficiency and reliability of patient-reported experience of pain, holds great promise.
Find out more about PROMIS here:
- Turk DC, Dworkin RH, et al. Core outcome domains for chronic pain clinical trials: IMMPACT recommendations. Pain. 2003;106(3):337-345.
- Turk DC, Dworkin RH, Revicki D, et al. Identifying important outcome domains for chronic pain clinical trials: an IMMPACT survey of people with pain. Pain. 2008;137(2):276-285.
- Edwards RR, Dworkin RH, Turk DC, et al. Patient phenotyping in clinical trials of chronic pain treatments: IMMPACT recommendations. Pain. 2016 Sep;157(9):1851-1871.
- Haythornthwaite JA. IMMPACT recommendations for clinical trials: opportunities for the RDC/TMD. J Oral Rehabil. 2010;37(10):799-806.
- Pliakos I, Kefaliakos A, Diomidous M. mHealth in Chronic Pain Assessment: Present and Future. Stud Health Technol Inform. 2016;226:260-263.
- Fillingim RB, Loeser JD, Baron R, Edwards RR. Assessment of Chronic Pain: Domains, Methods, and Mechanisms. J Pain. 2016;17(9 Suppl):T10-T20.
- de la Vega R, Miró J. mHealth: a strategic field without a solid scientific soul. a systematic review of pain-related apps. PLoS One. 2014;9(7):e101312.
- de la Vega R, Roset R, Castarlenas E, Sánchez-Rodríguez E, Solé E, Miró J. Development and testing of painometer: a smartphone app to assess pain intensity. J Pain. 2014;15(10):1001-1007.