Comparative Responsiveness of Pain Measures in Cancer Patients

Kroenke, Kurt; Theobald, Dale; Wu, Jingwei; Tu, Wanzhu; Krebs, Erin E.

doi:10.1016/j.jpain.2012.05.004

Cited by 43 publications

(31 citation statements)

References 57 publications

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“…The BPI has well-established validity and reliability among patients with cancer, including sensitivity to change in longitudinal studies. 19,22,59 In this study, Cronbach's alpha for the BPI interference scale was 0.92.…”

Section: Brief Pain Inventorymentioning

confidence: 49%

Changes in and predictors of pain characteristics in patients with head and neck cancer undergoing radiotherapy

Astrup

Rustøen

Miaskowski

et al. 2015

Pain

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Pain is a common symptom in patients with head and neck cancer (HNC) that is associated with significant decrements in physical and psychological functioning. Only 4 studies have evaluated for changes in and predictors of different pain characteristics in these patients. In this longitudinal study of patients with HNC, changes in pain intensity (i.e., average pain, worst pain), pain interference with function, and pain relief were evaluated from the initiation of radiotherapy and through the following 6 months. Hierarchical linear modeling was used to evaluate for changes over time in these 4 pain characteristics, as well as to identify predictors of interindividual variability in each characteristic. Overall, pain intensity and interference with function scores were in the mild-to-moderate range, while pain relief scores were in the moderate range. The occurrence of pain, as well as scores for each pain characteristic, increased from the initiation to the completion of radiotherapy, followed by a gradual decrease to near pretreatment levels at 6 months. However, interindividual variability existed in patients' ratings of each pain characteristic. Predictors of more severe pain characteristic scores were more comorbidities, worse physical functioning, not having surgery before radiotherapy, difficulty swallowing, mouth sores, sleep disturbance, fatigue, more energy, and less social support. Patients with more depressive symptoms had better pain relief. Although some of the predictors cannot be modified (e.g., rrence of surgery), other predictors (e.g., symptoms) can be treated. Therefore, information about these predictors may result in decreased pain in patients with HNC.

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Section: Brief Pain Inventorymentioning

confidence: 49%

Changes in and predictors of pain characteristics in patients with head and neck cancer undergoing radiotherapy

Astrup

Rustøen

Miaskowski

et al. 2015

Pain

View full text Add to dashboard Cite

show abstract

“…For example, the BPI-PI has been found to correlate highly with the WHO Disability Assessment Schedule 2.0 (0.69 to 0.81, from one to 12 months),[20] to discriminate between recurrent and non-fallers (sensitivity = 84.4% and specificity = 57.8% with a cutoff score of 4.6)[21] , and to have good inter-item consistency (alpha=0.89) and responsiveness (standardized response mean = .91). [22] The measure has been used in a substantial range of diseases and conditions and has been translated into many languages. [23] Developed using traditional methods, the BPI produces pain severity and pain interference scores that range from 0 to 10, with higher scores indicating worse pain.…”

Section: Methodsmentioning

confidence: 99%

Establishing a common metric for self-reported pain: linking BPI Pain Interference and SF-36 Bodily Pain Subscale scores to the PROMIS Pain Interference metric

et al. 2015

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Purpose The study purposes were to mathematically link scores of the Brief Pain Inventory Pain Interference (BPI-PI) subscale and the Short Form-36 Bodily Pain (SF36-BP) subscale (legacy pain interference measures) to the NIH Patient Reported Outcome Measurement Information System (PROMIS®) Pain Interference (PROMIS-PI) metric and evaluate results. Methods Linking was accomplished using both equipercentile and item response theory (IRT) methods. Item parameters for legacy items were estimated on the PROMIS-PI metric to allow for pattern scoring. Crosswalk tables also were developed that associated raw scores (summed or average) on legacy measures to PROMIS-PI scores. For each linking strategy, participants’ actual PROMIS-PI scores were compared to those predicted based on their legacy scores. To assess the impact of different sample sizes, we conducted random resampling with replacement across 10,000 replications with sample sizes of n=25, 50, and 75. Results Analyses supported the assumption that all three scales were measuring similar constructs. IRT methods produced marginally better results than equipercentile linking. Accuracy of the links was substantially affected by sample size. Conclusions The linking tools (crosswalks and item parameter estimates) developed in this study are robust methods for estimating the PROMIS-PI scores of samples based on legacy measures. We recommend using pattern scoring for users who have the necessary software and score crosswalks for those who do not.

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“…The BPI total score is a composite of the pain and interference scores and served as the primary outcome; it has proven sensitive to change in previous trials. 17,18 BPI scale scores range from 0 to 10, with higher scores representing worse pain and a 1-point change considered clinically important. 17,19 The primary outcome was the mean between-group difference in BPI total score during the 12-month trial.…”

Section: Outcome Measuresmentioning

confidence: 99%