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Pain Management in Cancer Center Inpatients: A Cluster Randomized Trial to Evaluate a Systematic Integrated Approach-The Edinburgh Pain Assessment and Management Tool.

ABSTRACT: Purpose Pain is suboptimally managed in patients with cancer. We aimed to compare the effect of a policy of adding a clinician-delivered bedside pain assessment and management tool (Edinburgh Pain Assessment and management Tool [EPAT]) to usual care (UC) versus UC alone on pain outcomes. Patients and Methods In a two-arm, parallel group, cluster randomized (1:1) trial, we observed pain outcomes in 19 cancer centers in the United Kingdom and then randomly assigned the centers to either implement EPAT or to continue UC. The primary outcome was change in the percentage of study participants in each center with a clinically significant (≥ 2 point) improvement in worst pain (using the Brief Pain Inventory Short Form) from admission to 3 to 5 days after admission. Secondary outcomes included quality of analgesic prescribing and opioid-related adverse effects. Results Ten centers were randomly assigned to EPAT, and nine were assigned to UC. We enrolled 1,921 patients and obtained outcome data from 93% (n = 1,795). Participants (mean age, 60 years; 49% women) had a variety of cancer types. For centers randomly assigned to EPAT, the percentage of participants with a clinically significant improvement in worst pain increased from 47.7% to 54.1%, and for those randomly assigned to continue UC, this percentage decreased from 50.6% to 46.4%. The absolute difference was 10.7% (95% CI, 0.2% to 21.1%; P = .046) and it increased to 15.4% (95% CI, 5.8% to 25.0%; P = .004) when two centers that failed to implement EPAT were excluded. EPAT centers had greater improvements in prescribing practice and in the Brief Pain Inventory Short Form pain subscale score. Other pain and distress outcomes and opioid adverse effects did not differ between EPAT and UC. Conclusion A systematic integrated approach improves pain outcomes for inpatients in cancer centers without increasing opioid adverse effects.

SUBMITTER: Fallon M

PROVIDER: S-EPMC5929219 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundAdequate pain assessment is critical for evaluating the efficacy of analgesic treatment in clinical practice and during the development of new therapies. Yet the currently used scores of global pain intensity fail to reflect the diversity of pain manifestations and the complexity of underlying biological mechanisms. We have developed a tool for a standardized assessment of pain-related symptoms and signs that differentiates pain phenotypes independent of etiology.Methods and findingsUsing a structured interview (16 questions) and a standardized bedside examination (23 tests), we prospectively assessed symptoms and signs in 130 patients with peripheral neuropathic pain caused by diabetic polyneuropathy, postherpetic neuralgia, or radicular low back pain (LBP), and in 57 patients with non-neuropathic (axial) LBP. A hierarchical cluster analysis revealed distinct association patterns of symptoms and signs (pain subtypes) that characterized six subgroups of patients with neuropathic pain and two subgroups of patients with non-neuropathic pain. Using a classification tree analysis, we identified the most discriminatory assessment items for the identification of pain subtypes. We combined these six interview questions and ten physical tests in a pain assessment tool that we named Standardized Evaluation of Pain (StEP). We validated StEP for the distinction between radicular and axial LBP in an independent group of 137 patients. StEP identified patients with radicular pain with high sensitivity (92%; 95% confidence interval [CI] 83%-97%) and specificity (97%; 95% CI 89%-100%). The diagnostic accuracy of StEP exceeded that of a dedicated screening tool for neuropathic pain and spinal magnetic resonance imaging. In addition, we were able to reproduce subtypes of radicular and axial LBP, underscoring the utility of StEP for discerning distinct constellations of symptoms and signs.ConclusionsWe present a novel method of identifying pain subtypes that we believe reflect underlying pain mechanisms. We demonstrate that this new approach to pain assessment helps separate radicular from axial back pain. Beyond diagnostic utility, a standardized differentiation of pain subtypes that is independent of disease etiology may offer a unique opportunity to improve targeted analgesic treatment.

Project description:BackgroundClinical experience teaches us that patients are willing to accept postoperative pain, despite high pain intensity scores. Nevertheless, relationships between pain scores and other methods of pain assessment, e.g. acceptability of pain or its interference with physical functioning, are not fully established. Our aims were to examine these relationships.MethodsA cross-sectional study was conducted on patients who underwent major surgery between January 2008 and August 2013. Using logistic regression, we quantified the relationships between movement-evoked pain scores on the numerical rating scale (NRS-MEP) and three dichotomous dependent variables: patient's opinion on acceptability of pain (PO: acceptable or unacceptable pain); nurses' observation of patient's performance of necessary activities to expedite recovery (NO: good or bad performance); a compound measure judging the presence of the clinically desirable situation of acceptable pain associated with good patients' performance (PONO: present or not). Using Receiver Operating Characteristics (ROC) analysis, NRS cut-off points were determined such that they best discriminate between patients having one versus the other outcome for PO, NO and PONO.Results15,394 assessments were obtained in 9,082 patients in the first three postoperative days. Nine percent of the patients had unacceptable pain while having an NRS-MEP of 0-4. An estimated 47% (95%CI = 45%-49%) of patients with an NRS-MEP of 7 described their pain as acceptable on day one. Moreover, 33% (31%-35%) performed all required physical activities, and 22% (21%-24%) combined acceptable pain with appropriate movement. NRS cut-off points for PO, NO and PONO were five, four and four, respectively, but had insufficient discriminatory power.ConclusionsOur results suggest pain management should be guided by the many dimensions of the patient's pain experience, not solely by NRS cut-off points. Future research should evaluate the impact of such multidimensional pain assessment on patients' functional outcome.

Project description:BackgroundThe reliable assessment of cortisol is a necessary requirement to produce replicable research. Several recommendations to increase cortisol assessment reliability exist. However, cortisol assessment methodology is still rather heterogeneous. For this reason, the Cortisol Assessment List (CoAL) was created.The CoAL can be used to guide researchers during the planning phase and document which measures were taken to increase cortisol data reliability in original studies. Moreover, the CoAL can be used to evaluate data quality in meta research. The items representing strategies to obtain reliable cortisol data can be weighted to indicate which are absolutely necessary to consider and which could be applied less restrictively in order to balance data quality and feasibility. In this paper, the construction process of the CoAL is described.MethodsItem synthesis of the CoAL included a literature search to extract empirically based suggestions regarding the reliable assessment of cortisol. Estimates for the item weighting system were obtained by inviting experts in the field to participate in an online survey (n = 25). Inter-rater reliability (IRR) of the CoAL, was determined by letting independent raters use the CoAL to evaluate a set of randomly selected original studies (k = 90).ResultsThe CoAL was divided into four subscales related to the reporting of sampling procedures, the consideration of state covariates, trait covariates and exclusion criteria. Survey results indicated high agreement among experts for most items (89%) with approximately half of the items in the CoAL being classified as necessary (Cortisol Awakening Response (CAR): 52%; basal cortisol: 52%; reactive cortisol: 44%) in order to obtain reliable cortisol data. Inter-rater agreement was very high (Cohen's Kappa = .98 - 0.99), indicating sufficient psychometric quality of the CoAL.DiscussionThe CoAL is the first tool to systematically plan, document and evaluate cortisol assessment. The survey results indicate that the majority of respondents are aware of essential requirements to increase data reliability. However, results were heterogeneous for some items, highlighting the need to start a process of developing a broad scientific consensus regarding reliable cortisol assessment. The implementation of the CoAL could be a first step in this direction. In conclusion, the CoAL reflects empirical evidence and expert knowledge regarding cortisol assessment and can be used as a flexible tool to plan and document empirical studies or evaluate cortisol data quality in meta research.

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Pain Management in Cancer Center Inpatients: A Cluster Randomized Trial to Evaluate a Systematic Integrated Approach-The Edinburgh Pain Assessment and Management Tool.

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